Education at a Glance 2018
OECD INDICATORS

Education
Education

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Education at a Glance
2018
OECD INDICATORS

Under embargo until 11/09/2018 at 11.00am CEST

This work is published under the responsibility of the Secretary-General of the OECD. The
opinions expressed and arguments employed herein do not necessarily reflect the official
views of the OECD member countries.
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Please cite this publication as:
OECD (2018), Education at a Glance 2018: OECD Indicators, OECD Publishing, Paris.
http://dx.doi.org/10.1787/eag-2018-en

ISBN (print) 978-92-64-30338-6
ISBN (PDF) 978-92-64-30339-3

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Foreword

Governments are increasingly looking to international comparisons of education opportunities and outcomes as they
develop policies to enhance individuals’ social and economic prospects, provide incentives for greater efficiency in
schooling, and help to mobilise resources to meet rising demands. The OECD Directorate for Education and Skills
contributes to these efforts by developing and analysing the quantitative, internationally comparable indicators that it
publishes annually in Education at a Glance. Together with OECD country policy reviews, these indicators can be used
to assist governments in building more effective and equitable education systems.
Education at a Glance addresses the needs of a range of users, from governments seeking to learn policy lessons to
academics requiring data for further analysis to the general public wanting to monitor how its country’s schools
are progressing in producing world-class students. The publication examines the quality of learning outcomes, the
policy levers and contextual factors that shape these outcomes, and the broader private and social returns that
accrue to investments in education.
Education at a Glance is the product of a long-standing, collaborative effort between OECD governments, the experts
and institutions working within the framework of the OECD Indicators of Education Systems (INES) programme
and the OECD Secretariat. The publication was prepared by the staff of the Innovation and Measuring Progress
Division of the OECD Directorate for Education and Skills, under the responsibility of Deborah Roseveare and
Marie-Hélène Doumet and in co-operation with Étienne Albiser, Éric Charbonnier, Manon Costinot, Fatine Guedira,
Corinne Heckmann, Karinne Logez, Axelle Magnier, Camila de Moraes, Simon Normandeau, Gara Rojas González,
Daniel Sánchez Serra, Markus Schwabe, Giovanni Maria Semeraro and Roland Tusz. Administrative support
was provided by Valérie Forges, and additional analytical support were provided by Agnese Gatti, Yaelin Ham,
Michael Jacobs, Pauline Le Pape, Hanvit Park and Junyeong Park. Marilyn Achiron, Cassandra Davis and
Sophie Limoges provided valuable support in the editorial and production process. The development of the
publication was steered by member countries through the INES Working Party and facilitated by the INES Networks.
The members of the various bodies as well as the individual experts who have contributed to this publication and to
OECD INES more generally are listed at the end of the book.
While much progress has been accomplished in recent years, member countries and the OECD continue to strive to
strengthen the link between policy needs and the best available internationally comparable data. This presents various
challenges and trade-offs. First, the indicators need to respond to education issues that are high on national policy
agendas, and where the international comparative perspective can offer added value to what can be accomplished
through national analysis and evaluation. Second, while the indicators should be as comparable as possible, they
also need to be as country-specific as is necessary to allow for historical, systemic and cultural differences between
countries. Third, the indicators need to be presented in as straightforward a manner as possible, while remaining
sufficiently complex to reflect multi-faceted realities. Fourth, there is a general desire to keep the indicator set as small
as possible, but it needs to be large enough to be useful to policy makers across countries that face different challenges
in education.
The OECD will continue not only to address these challenges vigorously and develop indicators in areas where it is
feasible and promising to develop data, but also to advance in areas where a considerable investment still needs to
be made in conceptual work. The OECD Programme for International Student Assessment (PISA) and its extension
through the OECD Programme for the International Assessment of Adult Competencies (Survey of Adult Skills
[PIAAC]), as well as the OECD Teaching and Learning International Survey (TALIS), are major efforts to this end.

Education at a Glance 2018: OECD Indicators   © OECD 2018

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Table of Contents
Name of
the indicator
in the
2017 edition

Editorial: Education’s promise to all������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������ 11
Introduction: The indicators and their framework����������������������������������������������������������������������������������������������������������������������������������������� 13
Reader’s guide������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������ 17
Executive summary�������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������� 23
Equity in the education sustainable development goal����������������������������������������������������������������������������������������������������������������������������� 27
CHAPTER A

THE OUTPUT OF EDUCATIONAL INSTITUTIONS AND THE IMPACT
OF LEARNING�������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������� 41

Indicator A1
Table A1.1.
Table A1.2.
Table A1.3.

To what level have adults studied?�����������������������������������������������������������������������������������������������������������������������������������42
Educational attainment of 25-64 year-olds (2017)����������������������������������������������������������������������������������������������� 54
Trends in educational attainment of 25-34 year-olds, by gender (2007 and 2017)���������� 55
Educational attainment of native- and foreign-born 25-64 year-olds, by age
at arrival in the country (2017)������������������������������������������������������������������������������������������������������������������������������������������������������ 56

A1

Indicator A2
Table A2.1.

Transition from education to work: Where are today’s youth?�������������������������������������������58
Percentage of 18-24 year-olds in education/not in education,
by work status (2017)��������������������������������������������������������������������������������������������������������������������������������������������������������������������������������� 66
Trends in the percentage of young adults in education/not in education,
employed or not, by age group (2007 and 2017)������������������������������������������������������������������������������������������������������ 67
Percentage of native- and foreign-born 15-29 year-old NEETs,
by age at arrival in the country (2017)���������������������������������������������������������������������������������������������������������������������������������� 68

C5

How does educational attainment affect participation in the labour market?�����70
Employment rates of 25-64 year-olds, by educational attainment (2017)����������������������������� 83
Trends in employment rates of 25-34 year-olds, by educational attainment
and gender (2007 and 2017)�������������������������������������������������������������������������������������������������������������������������������������������������������������� 84
Employment, unemployment and inactivity rates of 25-34 year-olds,
by educational attainment (2017)����������������������������������������������������������������������������������������������������������������������������������������������� 85
Employment rates of native- and foreign-born 25-64 year-olds, by age at arrival
in the country and educational attainment (2017)����������������������������������������������������������������������������������������������� 86

A5

What are the earnings advantages from education?����������������������������������������������������������������������������88
Relative earnings of workers, by educational attainment (2016)������������������������������������������������������� 98
Level of earnings relative to median earnings, by educational attainment (2016)������������ 99
Differences in earnings between female and male full-time workers,
by educational attainment and age group (2016)����������������������������������������������������������������������������������������������� 100
Differences in earnings between native- and foreign-born full-time workers,
by educational attainment and age group (2016)����������������������������������������������������������������������������������������������� 101

A6

What are the financial incentives to invest in education?�������������������������������������������������������102
Private costs and benefits for a man attaining tertiary education (2015)��������������������������� 113
Private costs and benefits for a woman attaining tertiary education (2015)������������������ 114
Public costs and benefits for a man attaining tertiary education (2015)������������������������������ 115

A7

Table A2.2.
Table A2.3.

Indicator A3
Table A3.1.
Table A3.2.
Table A3.3.
Table A3.4.

Indicator A4
Table A4.1.
Table A4.2.
Table A4.3.
Table A4.4.

Indicator A5
Table A5.1a.
Table A5.1b.
Table A5.2a.

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Name of
the indicator
in the
2017 edition

Table A5.2b.
Table A5.3a.
Table A5.3b.

Indicator A6
Table A6.1.
Table A6.2.
Table A6.3.
Table A6.4.

Indicator A7
Table A7.1.
Table A7.2.
Table A7.3.

Public costs and benefits for a woman attaining tertiary education (2015)��������������������� 116
Private/public costs and benefits for a man attaining tertiary education,
by level of tertiary education (2015)������������������������������������������������������������������������������������������������������������������������������������ 117
Private/public costs and benefits for a woman attaining tertiary education,
by level of tertiary education (2015)������������������������������������������������������������������������������������������������������������������������������������ 118

How are social outcomes related to education?����������������������������������������������������������������������������������������120
Percentage of 15-year-old students who report being aware or well aware
of environmental issues, by science proficiency level (2015)��������������������������������������������������������������� 130
Percentage of adults who agree that environmental issues have an impact
on their daily life, by educational attainment (2014 or 2010)������������������������������������������������������������ 131
Percentage of adults who believe in personal responsibility for looking
after the environment, by educational attainment (2016 or 2010-2014)��������������������������� 132
Percentage of adults who report taking personal action to reduce energy use,
by educational attainment (2016 or 2010)������������������������������������������������������������������������������������������������������������������ 133

A8

To what extent do adults participate equally in education and learning?�������134
Participation of native- and foreign-born adults in formal and/or non-formal
education by gender and their population distribution (2012 or 2015)�������������������������������� 144
Participation of native- and foreign-born adults in formal and/or non-formal
education, by labour-force status (2012 or 2015)����������������������������������������������������������������������������������������������� 145
Participation of native- and foreign-born adults in formal and/or non-formal
education, by educational attainment (2012 or 2015)��������������������������������������������������������������������������������� 146

C6

CHAPTER B

ACCESS TO EDUCATION, PARTICIPATION AND PROGRESSION�������������������������������� 147

Indicator B1
Table B1.1.
Table B1.2.

Who participates in education?�����������������������������������������������������������������������������������������������������������������������������������������148
Enrolment rates by age group (2005, 2010 and 2016)��������������������������������������������������������������������������������� 159
Students enrolled as a percentage of the population between the ages of 15
and 20 (2010, 2016)���������������������������������������������������������������������������������������������������������������������������������������������������������������������������������� 160
Profile of students enrolled in lower and upper secondary education (2016)���������������� 161

C1

How do early childhood education systems differ around the world?�������������������162
Enrolment rates in early childhood education and care (ECEC) and primary
education, by age (2016)��������������������������������������������������������������������������������������������������������������������������������������������������������������������� 175
Trends in enrolment rates in early childhood education and care (ECEC)
and primary education, by age (2005, 2010, 2015 and 2016)������������������������������������������������������������� 176
Enrolment of children in early childhood education and care (ISCED 0) by type
of institution and ratio of children to teaching staff (2016)����������������������������������������������������������������� 177
Expenditure on early childhood education and care (ISCED 0) and change
in expenditure as a percentage of GDP in pre-primary education
(2005, 2010, 2014 and 2015)�������������������������������������������������������������������������������������������������������������������������������������������������������� 178

C2

Who is expected to graduate from upper secondary education?�����������������������������������180
Profile of upper secondary graduates from vocational programmes (2016)��������������������� 190
Upper secondary and post-secondary non-tertiary first-time graduation rates
(2016)�������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������� 191
Trends in upper secondary and post-secondary non-tertiary first-time
graduation rates (2005, 2010 and 2016)������������������������������������������������������������������������������������������������������������������������ 192

A2

Table B1.3.

Indicator B2
Table B2.1a.
Table B2.1b.
Table B2.2.
Table B2.3a.

Indicator B3
Table B3.1.
Table B3.2.
Table B3.3.

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Name of
the indicator
in the
2017 edition

Indicator B4
Table B4.1.
Table B4.2.
Table B4.3.

Who is expected to enter tertiary education?��������������������������������������������������������������������������������������������� 194
Profile of new entrants into doctoral programmes (2016)���������������������������������������������������������������������� 203
Profile of first-time entrants into tertiary education (2016)��������������������������������������������������������������� 204
First-time entry rates, by tertiary level (2016)������������������������������������������������������������������������������������������������������� 205

C3

Indicator B5
Table B5.1.
Table B5.2.
Table B5.3.

Who is expected to graduate from tertiary education?���������������������������������������������������������������� 206
Profile of a first-time tertiary graduate (2016)������������������������������������������������������������������������������������������������������ 214
Distribution of tertiary graduates, by field of study (2016)������������������������������������������������������������������ 215
First-time graduation rates, by tertiary level (2016)��������������������������������������������������������������������������������������� 216

A3

Indicator B6
Table B6.1.
Table B6.2.

What is the profile of internationally mobile students?������������������������������������������������������������ 218
International and foreign student mobility in tertiary education (2016)���������������������������� 228
Share of international and foreign students among tertiary students
and distribution by field of education (2016)���������������������������������������������������������������������������������������������������������� 229
Mobility patterns of foreign and international students (2016)����������������������������������������������������� 230

C4

Table B6.3.

Indicator B7
Table B7.1.

Table B7.2.

Table B7.3.

Table B7.4.

How equitable are entry and graduation in tertiary education?����������������������������������� 232
Share of 18-24 year-olds whose parents have not attained tertiary education
among new entrants to bachelor’s, long first degree or equivalent programmes
and in the population, by gender (2015)������������������������������������������������������������������������������������������������������������������������ 241
Share of 20-29 year-olds whose parents have not attained tertiary education
among first‑time graduates from bachelor’s, long first degree or equivalent
programmes and in the population, by gender (2015)��������������������������������������������������������������������������������� 241
Share of 18-24 year-olds who are first- or second- generation immigrants
among new entrants to bachelor’s, long first degree or equivalent programmes
and in the population, by gender (2015)������������������������������������������������������������������������������������������������������������������������ 242
Share of 20-29 year-olds who are first- or second- generation immigrants
among first‑time graduates from bachelor’s, long first degree or equivalent
programmes and in the population, by gender (2015)��������������������������������������������������������������������������������� 242

CHAPTER C

FINANCIAL RESOURCES INVESTED IN EDUCATION�������������������������������������������������������������������� 243

Indicator C1
Table C1.1.

How much is spent per student on educational institutions?������������������������������������������� 246
Total expenditure on educational institutions per full-time equivalent student
(2015)�������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������� 254
Total expenditure on educational institutions per full-time equivalent student
for core educational services, ancillary services and R&D (2015)�������������������������������������������������� 255
Change in total expenditure per student on educational institutions
(2005, 2011 and 2015)�������������������������������������������������������������������������������������������������������������������������������������������������������������������������� 256

Table C1.2.
Table C1.3.

Indicator C2
Table C2.1.
Table C2.2.
Table C2.3.

What proportion of national wealth is spent on educational
institutions?���������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������� 258
Total expenditure on educational institutions as a percentage of GDP (2015)������������� 266
Total expenditure on educational institutions as a percentage of GDP,
by source of funds (2015)������������������������������������������������������������������������������������������������������������������������������������������������������������������� 267
Change in total expenditure on educational institutions as a percentage of GDP
(2005 to 2015)�������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������� 268
Education at a Glance 2018: OECD Indicators   © OECD 2018

B1

B2

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Name of
the indicator
in the
2017 edition

Indicator C3
Table C3.1.
Table C3.2.
Table C3.3.

How much public and private investment on educational institutions
is there?������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������270
Relative proportions of disaggregated public, private and international expenditure
on educational institutions (2015)���������������������������������������������������������������������������������������������������������������������������������������� 277
Distribution of public, private and international sources of funds for educational
institutions before and after transfers (2015)���������������������������������������������������������������������������������������������������������� 278
Trends in the relative proportion of public expenditure on educational institutions
and index of change in the relative share of public, private and international
expenditure from primary to tertiary levels (2005 to 2015)���������������������������������������������������������������� 279

B3

What is the total public spending on education?�����������������������������������������������������������������������������������280
Total public expenditure on education as a percentage of total government
expenditure (2015)������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������� 288
Share of sources of total public funds devoted to education (2015)������������������������������������������� 289
Trends in total public expenditure on education as a percentage of total
government expenditure (initial sources of funds, 2005, 2011 and 2015)������������������������ 290

B4

B5

Table C5.3.

How much do tertiary students pay and what public support do they receive?�����292
Estimated annual average tuition fees charged by tertiary educational institutions
(2015/16)���������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������� 301
Estimated change in the tuition fees charged by tertiary educational institutions
(2005/06 to 2015/16) and recent tuition-fee reforms��������������������������������������������������������������������������������� 303
Public loans to students, repayment and remission in tertiary education (2015/16)������ 305

Indicator C6
Table C6.1.
Table C6.2.
Table C6.3.

On what resources and services is education funding spent?��������������������������������������������308
Share of current and capital expenditure, by education level (2015)����������������������������������������� 314
Current expenditure, by resource category (2015)�������������������������������������������������������������������������������������������� 315
Share of current expenditure, by resource category and type of institution (2015)���� 316

B6

Indicator C7
Table C7.1.
Table C7.2.

Which factors influence teachers’ salary cost?������������������������������������������������������������������������������������������318
Salary cost of teachers per student, by level of education (2016)��������������������������������������������������� 329
Contribution of various factors to salary cost of teachers per student in primary
education (2016)������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������� 330
Contribution of various factors to salary cost of teachers per student
in lower secondary education (2016)���������������������������������������������������������������������������������������������������������������������������������� 331

B7

Indicator C4
Table C4.1.
Table C4.2.
Table C4.3.

Indicator C5
Table C5.1.
Table C5.2.

Table C7.3.
CHAPTER D

TEACHERS, THE LEARNING ENVIRONMENT AND THE ORGANISATION
OF SCHOOLS�������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������� 333

Indicator D1
Table D1.1.
Table D1.2.
Table D1.3a.
Table D1.3b.

How much time do students spend in the classroom?�������������������������������������������������������������������334
Instruction time in compulsory general education (2018)���������������������������������������������������������������������� 345
Organisation of compulsory general education (2018)������������������������������������������������������������������������������� 347
Instruction time per subject in primary education (2018)���������������������������������������������������������������������� 348
Instruction time per subject in general lower secondary education (2018)���������������������� 349

D1

Indicator D2
Table D2.1.
Table D2.2.
Table D2.3.

What is the student-teacher ratio and how big are classes?�������������������������������������������������350
Average class size, by type of institution (2016) and index of change (2005, 2016)���� 357
Ratio of students to teaching staff in educational institutions (2016)������������������������������������ 358
Ratio of students to teaching staff, by type of institution (2016)������������������������������������������������� 359

D2

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Name of
the indicator
in the
2017 edition

Indicator D3
Table D3.1a.

How much are teachers and school heads paid?�������������������������������������������������������������������������������������� 360
Teachers’ statutory salaries, based on the most prevalent qualifications
at different points in teachers’ careers (2017)��������������������������������������������������������������������������������������������������������� 375
Actual salaries of teachers and school heads relative to earnings of tertiary‑educated
workers (2016)������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������� 376
Average actual salaries of teachers and school heads, by age group and
by gender (2016)�������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������� 377
Minimum/maximum school heads’ statutory salaries, based on minimum
qualifications (2017)�������������������������������������������������������������������������������������������������������������������������������������������������������������������������������� 378

D3

Indicator D4
Table D4.1.
Table D4.2.
Table D4.3.

How much time do teachers spend teaching?���������������������������������������������������������������������������������������������� 380
Organisation of teachers’ working time (2017)����������������������������������������������������������������������������������������������������� 391
Number of teaching hours per year (2000, 2005 to 2017)���������������������������������������������������������������������� 393
Tasks and responsibilities of teachers, by level of education (2017)������������������������������������������� 394

D4

Indicator D5
Table D5.1.
Table D5.2.
Table D5.3.

Who are the teachers?���������������������������������������������������������������������������������������������������������������������������������������������������������������������� 396
Age distribution of teachers (2016)�������������������������������������������������������������������������������������������������������������������������������������� 404
Gender distribution of teachers (2016)���������������������������������������������������������������������������������������������������������������������������� 405
Gender distribution of teachers by age group (2016) and percentage
of female teachers for all ages (2005, 2016)��������������������������������������������������������������������������������������������������������������� 406

D5

Indicator D6
Table D6.1.

Who makes key decisions in education systems?���������������������������������������������������������������������������������� 408
Percentage of decisions taken at each level of government
in public lower secondary education (2017)��������������������������������������������������������������������������������������������������������������� 418
Percentage of decisions taken at each level of government
in public lower secondary education, by domain (2017)���������������������������������������������������������������������������� 419
Percentage of decisions taken at the local and school levels in public
lower secondary education, by mode of decision making (2017)���������������������������������������������������� 421

Table D3.2a.
Table D3.4.
Table D3.10.

Table D6.2.
Table D6.3.
ANNEX 1
Table X1.1a.
Table X1.1b.
Table X1.2a.
Table X1.2b.
Table X1.3.
ANNEX 2
Table X2.1.
Table X2.2.
Table X2.3.
Table X2.4a.

CHARACTERISTICS OF EDUCATION SYSTEMS�������������������������������������������������������������������������������������� 423
Typical graduation ages, by level of education (2016)����������������������������������������������������������������������������������� 424
Typical age of entry, by level of education (2016)����������������������������������������������������������������������������������������������� 426
School year and financial year used for the calculation of indicators,
OECD countries���������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������� 427
School year and financial year used for the calculation of indicators,
partner countries������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������ 428
Starting and ending age for students in compulsory education and starting age
for students in primary education (2016)��������������������������������������������������������������������������������������������������������������������� 429
REFERENCE STATISTICS������������������������������������������������������������������������������������������������������������������������������������������������������������ 431
Basic reference statistics (reference period: calendar year 2015 and 2016)���������������������� 432
GDP and total public expenditure (reference period: calendar year 2005, 2010
to 2015, current prices)������������������������������������������������������������������������������������������������������������������������������������������������������������������������ 433
Basic reference statistics (reference period: calendar year 2005, 2010 to 2015,
in 2010 constant prices)���������������������������������������������������������������������������������������������������������������������������������������������������������������������� 435
Teachers’ statutory salaries at different points in their careers, for teachers
with the most prevalent qualifications defined at different points in the teachers’
career (2017)������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������� 437
Education at a Glance 2018: OECD Indicators   © OECD 2018

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Name of
the indicator
in the
2017 edition

Table X2.4c.
Table X2.4f.
Table X2.4g.
Table X2.5.
Table X2.6.
ANNEX 3

Teachers’ statutory salaries at different points in their careers, for teachers
with minimum qualifications (2017)���������������������������������������������������������������������������������������������������������������������������������� 439
Reference statistics used in calculating teachers’ salaries (2000, 2005 to 2017)�������� 441
Trends in average teachers’ actual salaries, in national currency (2000, 2005,
2010 to 2016)���������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������� 443
Proportion of teachers, by level of qualification (2017)������������������������������������������������������������������������������ 445
Percentage of pre-primary, primary, lower secondary and upper secondary teachers, .
by level of attainment (2017)�������������������������������������������������������������������������������������������������������������������������������������������������������� 446
SOURCES, METHODS AND TECHNICAL NOTES����������������������������������������������������������������������������������� 447

Contributors to this publication������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������� 449
Education Indicators in Focus��������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������� 455

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Under embargo until 11/09/2018 at 11.00am CEST

Editorial
Education’s promise to all
We are all born equal, but we are not all born with the same opportunities. Some will be born to wealthy families,
others will struggle to make ends meet. Some will grow up in an environment of conflict and turmoil, and will face the
challenges of displacement and settling in a country that is not their own, others will benefit from a climate of social
stability and prosperity their whole lives. Some will cope with a disability, struggling to learn to perform even basic
tasks, while others may never realise the fortune of their good health. The conditions and social environments we are
allotted at birth may seem as random as a lottery draw, yet they will define our starting position on the path of life by
affecting not only the opportunities available to us, but also the social and emotional capital needed to ease our way.
“The direction in which education starts a man will determine his future life,” said Socrates to Adeimantus in
Plato’s Republic. Indeed, education is the cornerstone of individuals’ progression through life. No one would refute
that every child, every human being, deserves the same opportunities to gain skills and progress through society
regardless of their gender, socio-economic, ethnic or cultural background. Equity is indeed one of the fundamental
values on which so many countries around the world have chosen to build their societies.
In addition to the strong moral and ethical grounds supporting the demand for equity, there is also sound evidence
of the economic and social benefits of an inclusive society, as our Inclusive Growth Initiative has highlighted. Higher
educational attainment leads to higher skills, which lead to higher lifetime earnings. The quality of education can
be a strong predictor of a country’s economic prosperity. Shortfalls in academic achievement are extremely costly,
as governments must then find ways to compensate for them, and ensure the social and economic welfare of all.
The impact of skills inequality, however, extends much farther than a nation’s economic wealth; it ripples out to
all aspects of society such as, in poorer health, in a climate of violence or social unrest – all of which show how
inequality can have long-term, and often tragic, consequences for individuals and communities. This is why the
OECD Framework for Inclusive Growth emphasises investing in people and places that have been left behind, while
supporting inclusive labour markets. Using a dashboard of indicators, the Framework identifies the mechanisms
through which inequalities unfold, and offers suggestions on how countries can design and implement policies that
promote opportunities for all. Fighting inequality in education is central to all these efforts.
Recognising these challenges, this year’s edition of Education at a Glance focuses on equity in education. It shows
that although educational attainment increased significantly over the past decade, inequities that start early tend
to accumulate throughout life, first in education and then in the labour market, and through a number of channels:
socio-economic status, gender, immigrant background and geographic location.
Among the channels of inequity considered, socio-economic status has the strongest impact on participation in
education and learning, and on economic and social outcomes. Children without tertiary-educated mothers are less
likely to be enrolled in early childhood education and care programmes. Although it is widely acknowledged that a
child’s cognitive development begins well before he or she reaches school age, governments still spend less on this
level of education than on any other. Children from disadvantaged backgrounds are also less likely to pursue further
education opportunities as inequalities build on each other throughout life. Those without tertiary-educated parents
are more likely to enrol in vocational than in general upper secondary programmes and are less likely to complete
those programmes. This, in turn, affects their participation in higher education, where the share of entrants without a
tertiary-educated parent is small. Still, two in three adults from low-educated families attain a higher level of education
than their parents, a sign that those from the most disadvantaged backgrounds are now acquiring more skills.
Participation in higher education today matters more than ever. About one in three children of manual workers is
also a manual worker. Technological change, digitalisation and innovation have placed a significant premium on
advanced skills, as lower-skilled jobs are being squeezed out of the market. Those who have attained only upper
secondary education will earn 65% as much as a tertiary graduate, on average, perpetuating this vicious cycle over
the next generations. On average, it takes around four to five generations for children of families in the bottom
earnings decile to attain the mean level of earnings across OECD countries.
Education at a Glance 2018: OECD Indicators   © OECD 2018

11

Editorial
Under embargo until 11/09/2018 at 11.00am CEST
Gender differences also remain a reality despite the many efforts to reduce or eliminate them; but the dynamics
play out differently in school and in the labour market. Boys are more likely than girls to repeat a grade, drop out of
school, and not attain a tertiary education. However, despite their better performance at school, women still have
worse employment and earning outcomes. This is partly the result of the different choices men and women make
when deciding on a field of study. Although there have been widespread attempts to encourage gender diversity
across different careers, women are still less likely to enrol in and graduate from high-paying fields at the tertiary
level. For example, even though engineering skills are in high demand today, only 6% of women graduates complete
an engineering degree compared to 25% of men. Cultural norms and preconceived notions of women’s roles in life,
absorbed during childhood, still influence these choices, often unconsciously.
Migration patterns are also profoundly changing our communities and education systems. Fostering a cohesive
society depends on the capacity to integrate immigrants and ensure that they develop the skills required to
contribute to the labour market and to their communities. However, first- and second-generation immigrants are
less likely to enter and graduate from bachelor’s or long first-degree tertiary programmes in countries with available
data; and foreign-born adults are also less likely than their native-born peers to participate in formal and/or nonformal education throughout their lifetime.
At first glance, it appears Socrates’s words ring true: those who start at a disadvantage are less likely to have access
to a high-quality learning environment or acquire the skills or will to develop and grow in society. But more than a
prophecy, these words are, in fact, a call to action for education systems, a reminder that providing a high-quality,
nurturing learning environment can help narrow these opportunity gaps.
This is exactly the ambition framed by world leaders when they set out to define the Sustainable Development
Goals for education. By committing themselves to ensuring “inclusive and equitable quality education and promote
lifelong learning opportunities for all” by 2030, they set in motion one of the most comprehensive global education
agendas ever attempted. Among the ten targets of this goal, target 4.5 is dedicated to equity and specifically aims
to “eliminate gender disparities in education and ensure access to all levels of education and vocational training
for the vulnerable, including persons with disabilities, indigenous peoples and children in vulnerable situations”.
In addition to addressing gender disparities, the agenda invites countries to monitor equity along a range of other
dimensions that are as relevant for developed countries as for developing countries.
Given the transversal nature of inequities in education throughout the 2030 agenda, this year’s Education at a Glance
marks a substantial contribution to all Sustainable Development Goals by dedicating its chapter on the Sustainable
Development Goals specifically to target 4.5, providing an assessment of where OECD and partner countries stand
on their way to achieving their equity objectives. Results show that achieving equitable participation in education
and quality in learning outcomes remains a challenge for many OECD countries. The gender gap in the participation
rate of adults in formal and non-formal education varies greatly across countries, with women in some countries,
and men in other countries, less likely to participate. Disparities in achieving equity in learning outcomes are also
stark: in all OECD countries, the mathematics performance of 15-year-olds is strongly associated with students’
socio-economic status and the location, urban or rural, of their school. In most countries, this association has not
weakened at all over the past decade
Every individual has a potential for greatness, and deserves the opportunity to grow, develop and contribute fully
to society. Achieving equity in education will require a range of interventions through different policy mechanisms:
targeting funding and resources for education to the most vulnerable; preventing grade repetition and encouraging
those from minority backgrounds to enter mainstream education, with its greater opportunities; ensuring teachers
are equipped with the right training and pedagogical knowledge to identify and support struggling students; and
increasing access to and provision of affordable, high-quality early childhood education.
A lot has already been achieved in bridging some of the opportunity gaps our children face, but this edition of
Education at a Glance reminds us that the path to achieving equity in education remains strewn with obstacles.
We have the responsibility to ensure that personal or social circumstances do not impede students from realising
their potential. This should be education’s promise to all.

Angel Gurría
OECD Secretary-General

12

Education at a Glance 2018: OECD Indicators   © OECD 2018

Under embargo until 11/09/2018 at 11.00am CEST

Introduction:
The indicators and their framework
The organising framework
Education at a Glance 2018: OECD Indicators offers a rich, comparable and up-to-date array of indicators that reflect
a consensus among professionals on how to measure the current state of education internationally. The indicators
provide information on the human and financial resources invested in education, how education and learning
systems operate and evolve, and the returns to investments in education. They are organised thematically, each
accompanied by information on the policy context and interpretation of the data.
The indicators are organised within a framework that distinguishes between the actors in education systems,
groups them according to the types of issues they address, and examines contextual factors that influence policy
(Figure A). In addition to these dimensions, the time perspective makes it possible to visualise dynamic aspects of
the development of education systems.

Contextual factors: demographic, socio- economic, political

Figure A. Organising framework of indicators in Education at a Glance
Impact
Outcome
Output

Participation and progression through:
• Educational systems
• Institutions
• Classrooms

Input :
• Financial, human and physical resources
• Education policy and legislation

Actors in education systems
The OECD Indicators of Education Systems programme seeks to gauge the performance of national education
systems as a whole, rather than to compare individual institutional or other subnational entities. However, there
is increasing recognition that many important features of the development, functioning and impact of education
systems can only be assessed through an understanding of learning outcomes and their relationships to inputs and
processes at the level of individuals and institutions.
To account for this, the first dimension of the organising framework distinguishes the three levels of actors in
education systems:
• education systems as a whole
• providers of educational services (institutions, schools), as well as the instructional setting within those institutions
(classrooms, teachers)
• individual participants in education and learning, the students. These can be either children or young adults
undergoing initial schooling and training or adults pursuing lifelong learning programmes.
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Indicator groups
The second dimension of the organising framework further groups the indicators into three categories:

• Indicators on the output, outcomes and impact of education systems: Output indicators analyse the characteristics
of those exiting the system, such as their educational attainment. Outcome indicators examine the direct effect
of the output of education systems, such as the employment and earning benefits of pursuing higher education.
Impact indicators analyse the long-term indirect effect of the outcomes, such as knowledge and skills acquired,
contributions to economic growth and societal well-being, and social cohesion and equity.

• Indicators on the participation and progression within education entities: These indicators assess the likelihood of

students accessing, enrolling in, and completing different levels of education, as well as the various pathways
followed between types of programmes and across education levels.

• Indicators on the input into education systems or the learning environment: These indicators provide information

on the policy levers that shape the participation, progression, outputs and outcomes at each level. Such policy
levers relate to the resources invested in education, including financial, human (such as teachers and other school
staff), or physical resources (such as buildings and infrastructure). They also relate to policy choices regarding the
instructional setting of classrooms, pedagogical content and delivery of the curriculum. Finally, they analyse the
organisation of schools and education systems, including governance, autonomy, and specific policies to regulate
participation of students in certain programmes.

Contextual factors that influence policy
Policy levers typically have antecedents, external factors that define or constrain policy but are not directly
connected to the policy topic at hand. Demographic, socio-economic and political factors are all important national
characteristics to take into account when interpreting indicators. The recent financial crisis, for example, had a
significant impact on public funds available to education.
The characteristics of the students themselves, such as their gender, age, socio-economic status or cultural background,
are also important contextual factors that influence the outcomes of education policy.
Indicator analysis using the framework
This versatile framework can be used to understand the operation and functioning of any educational entity, from an
education system as a whole to a specific level of education or programme, or even a smaller entity, such as a classroom.
This versatility is important because many features of education systems have varying impacts at different levels of
the system. For example, at the level of students within a classroom, the relationship between student achievement
and class size may be negative, if students in small classes benefit from improved interactions with teachers. At
the class or school level, however, weaker or disadvantaged students are often intentionally grouped and placed
in smaller classes so that they receive more individual attention. At the school level, therefore, the observed
relationship between class size and student achievement is often positive, suggesting that students in larger classes
perform better than students in smaller classes. At higher levels of aggregation, the relationship between student
achievement and class size is further confounded, by the socio-economic intake of individual schools or by factors
relating to the learning culture in different countries. Therefore, to interpret the indicators, it is important to fully
understand the relationships between them.
Analysis of each element of the framework and the interplay between them contribute to understanding a variety
of policy perspectives:
• quality of education outcomes and education opportunities
• equality of education outcomes and equity in education opportunities
• adequacy, effectiveness and efficiency of resources invested in education
• relevance of education policy measures to improve education outcomes.
The structure of chapters and indicators in Education at a Glance
The indicators published in Education at a Glance 2018 have been developed within this framework. The chapters are
structured through the lens of the education system as a whole, although the indicators themselves are disaggregated
and analysed across different levels of education and education settings, and may therefore speak to more than one
element of the framework.

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Chapter A, The output of educational institutions and the impact of learning, contains indicators on the output,
outcomes and impact of education in the form of overall attainment of the population, as well as the learning,
economic and social outcomes (Figure A). Through this analysis, the indicators in this chapter provide context to
shape policies on lifelong learning. They also provide insights into the policy levers needed to address areas where
outcomes and impact may not be aligned with national strategic objectives.
Chapter B, Access to education, participation and progression, considers the full education system from early childhood
to tertiary education and provides indicators on enrolment, progression and completion of students at each level
and programme (Figure A). These indicators can be considered a mixture of output and outcome, to the extent
that the output of each education level serves as input to the next and that progression is the result of policies and
practices at classroom, institution and system levels. But they can also provide context to identify areas where policy
intervention is necessary to address issues of inequity, for example, or to encourage international mobility.
Chapter C and D relate to the input into educational systems (Figure A):
• Chapter C, Financial resources invested in education, provides indicators on investment in education and educational
institutions and how that investment is shared between public and private sources. These indicators are mainly
policy levers, but they also help to explain specific learning outcomes. For example, expenditure on educational
institutions per student is a key policy measure that most directly affects individual learners, but it also acts as a
constraint on the learning environment in schools and learning conditions in the classroom.
• Chapter D, Teachers, the learning environment and the organisation of schools, provides indicators on instruction time,
teachers’ working time and teachers’ and school heads’ salaries. These indicators not only represent policy levers
that can be manipulated, but also provide contexts for the quality of instruction and for the outcomes of individual
learners. This chapter also presents data on the profile of teachers, the levels of government at which decisions
about education are taken and the pathways and gateways for access to secondary and tertiary education.
In addition to the regular indicators and core statistics published, Education at a Glance also contains analytical work
in textboxes. This work usually provides research elements that contribute to the understanding of the indicator, or
additional analysis on a smaller number of countries that complement the findings presented.
The Sustainable Development Goal 4
In September 2015, world’s leaders gathered to set ambitious goals for the future of the global community. Goal 4 of
the Sustainable Development Goals (SDG) seeks to ensure “inclusive and equitable quality education and promote
lifelong learning opportunities for all”. Each target of the SDG 4 framework has at least one global indicator and
a number of related thematic indicators designed to complement the analysis and the measurement of the target.
UNESCO oversees the education SDG agenda in the context of the United Nations–led SDG framework. As the
custodian agency for most of the SDG 4 indicators, the UNESCO Institute of Statistics (UIS) is co-ordinating global
efforts to develop the indicator framework to monitor progress towards SDG 4 targets. In addition to collecting
data, UIS works with partners to develop new indicators, statistical approaches and monitoring tools to better
assess progress across the education-related SDG targets.
In this context, the OECD’s education programmes have a key role to play in the achievement of – and measuring
progress towards – SDG 4 and its targets. There is a high level of complementarity between the SDG 4 agenda
and the OECD’s education policy tools, instruments, evidence and dialogue platforms. The OECD is working with
UIS, the SDG 4 Steering Committee and the technical working groups that have been put in place to help build a
comprehensive data system for global reporting, agree on the data sources and formulae used for reporting on the
SDG 4 global indicators and on selected thematic indicators for OECD member countries and partner countries.
As part of this global effort to advance the dialogue and progress of the SDG monitoring, Education at a Glance is
devoting for the second year a chapter to this universal education agenda. The chapter aims to provide an assessment
of where OECD and partner countries stand on their way to meeting the SDG targets. Depending on the focus of
each edition, the selected global and thematic SDG indicators presented may differ from year to year. Thus, the SDG
presentation draws on the general framework of Education at a Glance.
Equity in Education at a Glance 2018
As the selected theme for this year’s publication, equity is at the forefront of Education at a Glance 2018. Equity in
education means that access, participation and progression to obtain a quality education are available to all and that
personal or social circumstances, such as gender, family or immigrant background, are not obstacles to achieving
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educational potential. Therefore, a large number of indicators in this year’s edition analyse the participation and
progression through education, as well as the outcomes of education across a number of equity dimensions: gender,
parents educational attainment (often considered as a proxy for socio-economic status), immigrant background or
country of origin, and subnational regions.
In line with this general focus of the publication, the SDG chapter in Education at a Glance 2018 focuses on the status
of Target 4.5 that aims to “eliminate gender disparities in education and ensure equal access to all levels of education
and vocational training for the vulnerable, including persons with disabilities, indigenous peoples and children in
vulnerable situations” by 2030.
The table below summarises the indicators and chapters of the publication that contribute to the analysis of equity
in education across a number of equity dimensions.
Table A. Indicators including an equity analysis in Education at a Glance 2018

Chapter A:
The output
of educational
institutions and the
impact of learning

Chapter B:
Access to education,
participation
and progression

Chapter C:
Financial resources
invested in
education

Chapter D:
Teachers,
the learning
environment and
the organisation
of schools

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x
x
x
x
x

x

x
x
x
x

x
x
x
x
x
x

x
x

x
x

x

x

x

Subnational

Immigrant background /
country of origin

A1
A2
A3
A4
A5
A6
A7
B1
B2
B3
B4
B5
B6
B7
C1
C2
C3
C4
C5
C6
C7
D1
D2
D3
D5
D5
D6

Parents’ educational
attainment

Indicator
To what level have adults studied?
Transition from education to work: where are today’s youth?
How does educational attainment affect participation in the labour market?
What are the earnings advantages from education?
What are the financial incentives to invest in education?
How are social outcomes related to education?
To what extent do adults participate equally in education and learning?
Who participates in education?
How do early childhood education systems differ around the world?
Who is expected to graduate from upper secondary education?
Who is expected to enter tertiary education?
Who is expected to graduate from tertiary education?
What is the profile of internationally mobile students?
How equitable are entry and graduation in tertiary education?
How much is spent per student on educational institutions?
What proportion of national wealth is spent on educational institutions?
How much public and private investment on educational institutions is there?
What is the total public spending on education?
How much do tertiary students pay and what public support do they receive?
On what resources and services is education funding spent?
Which factors influence teachers’ salary cost?
How much time do students spend in the classroom?
What is the student-teacher ratio and how big are classes?
How much are teachers and school heads paid?
How much time do teachers spend teaching?
Who are the teachers?
Who makes the decisions in education systems?

Gender

Chapter

Indicator number

Equity dimension

x
x
x

x
x
x

x

x
x
x

x
x

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Reader’s guide
Coverage of the statistics
Although a lack of data still limits the scope of the indicators in many countries, the coverage extends, in
principle, to the entire national education system (within the national territory), regardless of who owns
or sponsors the institutions concerned and regardless of how education is delivered. With one exception
(described below), all types of students and all age groups are included: children (including students with
special needs), adults, nationals, foreigners and students in open-distance learning, in special education
programmes or in education programmes organised by ministries other than the ministry of education,
provided that the main aim of the programme is to broaden or deepen an individual’s knowledge.
Vocational and technical training in the workplace, with the exception of combined school- and workbased programmes that are explicitly deemed to be part of the education system, is not included in the
basic education expenditure and enrolment data.
Educational activities classified as “adult” or “non-regular” are covered, provided that the activities involve
the same or similar content as “regular” education studies, or that the programmes of which they are a part
lead to qualifications similar to those awarded in regular education programmes.
Courses for adults that are primarily for general interest, personal enrichment, leisure or recreation are excluded.
More information on the coverage of the indicators presented in Education at a Glance can be found in the
OECD Handbook for Internationally Comparable Statistics on Education 2018 (OECD, 2018[1]).
Comparability over time
The indicators in Education at a Glance are the result of a continuous process of methodological improvement
aimed at improving the robustness and international comparability of the indicators. As a result, when analysing
indicators over time, it is strongly advised to do so within the most recent edition only, rather than comparing
data across different editions. All comparisons over time presented in this report are based on annual revisions
of historical data and the methodological improvements which have been implemented in this edition.
Country coverage
This publication features data on education from the 35 OECD countries, 2 partner countries that
participate in the OECD Indicators of Education Systems programme (INES), namely Brazil and the Russian
Federation, and other partner G20 and OECD accession countries that are not INES members (Argentina,
China, Colombia, Costa Rica, India, Indonesia, Lithuania,1 Saudi Arabia and South Africa). Data sources for
the non‑INES participating countries can come from the regular INES data collections, from the UNESCO
Institute of Statistics or from Eurostat.
In some instances, and where relevant, a country may be represented through its subnational entities or
specific region.
The statistical data for Israel are supplied by and under the responsibility of the relevant Israeli authorities.
The use of such data by the OECD is without prejudice to the status of the Golan Heights, East Jerusalem and
Israeli settlements in the West Bank under the terms of international law.
Note on subnational regions
When interpreting the results on subnational entities, readers should take into account that the population
size as well as geographic size of subnational entities can vary widely within countries. For example, in
Canada, the population of Nunavut is 37 082 and the territory covers 1.9 million square kilometres, while
the population of the province of Ontario is 13.9 million and the territory covers 909 000 square kilometres
(OECD, 2018[2]). Also, regional disparities tend to be higher especially in big countries like Canada, the
Russian Federation or the United States when more subnational entities are used in the analysis.

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Names used for territorial entities
For consistency, national and subnational entities are referred to as “countries” and “economies”, respectively,
in the whole publication. Territorial and subnational entities are referred to throughout the publication by
their subnational name and country, e.g. England (United Kingdom). For consistency with other indicators
from Education at a Glance, the subnational entity “Flanders (Belgium)” used in the OECD Programme for
the International Assessment of Adult Competencies (Survey of Adult Skills [PIAAC]) and the Teaching and
Learning International Survey (TALIS) will be referred to by the name “Flemish Community of Belgium”
throughout the publication. The Flemish Community of Belgium and French Community of Belgium are
abbreviated in the tables and figures as “Flemish Comm. (Belgium)” and “French Comm. (Belgium)”.
Calculation of international means
The main purpose of Education at a Glance is to provide an authoritative compilation of key international
comparisons of education statistics. While countries attain specific values in these comparisons, readers
should not assume that countries themselves are homogeneous. The country averages include significant
variations among subnational jurisdictions, much as the OECD average encompasses a variety of national
experiences.
For many indicators, an OECD average is presented; for some, an OECD total is shown. The OECD average is
calculated as the unweighted mean of the data values of all OECD countries1 for which data are available or
can be estimated. The OECD average therefore refers to an average of data values at the level of the national
systems and can be used to answer the question of how an indicator value for a given country compares with
the value for a typical or average country. It does not take into account the absolute size of the education
system in each country.
The OECD total is calculated as the weighted mean of the data values of all OECD countries1 for which
data are available or can be estimated. It reflects the value for a given indicator when the OECD area is
considered as a whole. This approach is taken for the purpose of comparing, for example, expenditure charts
for individual countries with those of the entire OECD area for which valid data are available, with this area
considered as a single entity.
For tables using trend series, the OECD average is calculated for countries providing data for all reference
years used. This allows for a comparison of the OECD average over time with no distortion due to the
exclusion of certain countries in the different years.
For many indicators, an EU22 average is also presented. It is calculated as the unweighted mean of the
data values of the 22 countries that are members of both the European Union and the OECD for which data
are available or can be estimated.1 These 22 countries are Austria, Belgium, the Czech Republic, Denmark,
Estonia, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Latvia, Luxembourg, the Netherlands,
Poland, Portugal, the Slovak Republic, Slovenia, Spain, Sweden and the United Kingdom. For some indicators,
a G20 average is presented. The G20 average is calculated as the unweighted mean of the data values of all
G20 countries for which data are available or can be estimated (Argentina, Australia, Brazil, Canada, China,
France, Germany, India, Indonesia, Italy, Japan, Korea, Mexico, the Russian Federation, Saudi Arabia, South
Africa, Turkey, the United Kingdom and the United States; the European Union is the 20th member of the
G20 but is not included in the calculation). The G20 average is not computed if data for both China and India
are not available.
OECD, EU22 and G20 averages and totals can be significantly affected by missing data. In the case of some
countries, data may not be available for specific indicators, or specific categories may not apply. Therefore,
readers should keep in mind that the term “OECD/EU22/G20 average” refers to the OECD, EU22 or G20
countries included in the respective comparisons. Averages are not calculated if more than 40% of countries
have missing information or have information included in other columns.
For some indicators, an average is presented. The average corresponds to the arithmetic mean of the
estimates included in the table or figure.

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Classification of levels of education
The classification of levels of education is based on the International Standard Classification of Education
(ISCED). ISCED is an instrument for compiling statistics on education internationally. ISCED-97 was recently
revised, and the new International Standard Classification of Education (ISCED 2011) was formally adopted
in November 2011 and is now the basis of the levels presented in this publication, with the exception of tables
showing data from the Survey of Adult Skills (PIAAC), which uses the previous ISCED-97 Classification.
In some indicators, intermediate programmes are also used. These correspond to recognised qualifications
from an ISCED 2011 level programme which is not considered as sufficient for ISCED 2011 completion and
is classified at a lower ISCED 2011 level.
The table below lists the ISCED 2011 levels used in the publication (OECD / Eurostat / UNESCO Institute for
Statistics, 2015[3])
Terms used in this publication

ISCED classification

ISCED 0
Early childhood education
Refers to early childhood programmes that have an intentional education component and aim (sub-categories:
to develop cognitive, physical and socio-emotional skills necessary for participation in school 01 for early childhood educational
development and 02 for pre-primary
and society. Programmes at this level are often differentiated by age.
education)

Primary education
Designed to provide a sound basic education in reading, writing and mathematics and a basic
understanding of some other subjects. Entry age: between 5 and 7. Typical duration: 6 years.
Lower secondary education
Completes provision of basic education, usually in a more subject-oriented way with more
specialist teachers. Programmes may differ by orientation, general or vocational, though this
is less common than at upper secondary level. Entry follows completion of primary education
and typical duration is 3 years. In some countries, the end of this level marks the end of
compulsory education.
Upper secondary education
Stronger specialisation than at lower secondary level. Programmes offered are differentiated
by orientation: general or vocational. Typical duration is 3 years.
Post-secondary non-tertiary education
Serves to broaden rather than deepen the knowledge, skills and competencies gained in upper
secondary level. Programmes may be designed to increase options for participants in the
labour market, for further studies at tertiary level, or both. Usually, programmes at this level
are vocationally oriented.
Short-cycle tertiary education
Serves to deepen the knowledge developed at previous levels by imparting new techniques,
concepts and ideas not generally covered in upper secondary education.
Bachelor’s or equivalent level
Designed to provide participants with intermediate academic and/or professional knowledge,
skills and competencies, leading to a first degree or equivalent qualification. Typical duration:
3-4 years full-time study.
Master’s or equivalent level
Stronger specialisation and more complex content than bachelor’s level. Designed to provide
participants with advanced academic and/or professional knowledge. May have a substantial
research component.
Doctoral or equivalent level
Designed to lead to an advanced research qualification. Programmes at this level are devoted to
advanced study and original research, and exist in both academic and professional fields.

ISCED 1

ISCED 2

ISCED 3

ISCED 4

ISCED 5

ISCED 6

ISCED 7

ISCED 8

Fields of education and training

Within ISCED, programmes and related qualifications can be classified by fields of education and training as
well as by levels. Following the adoption of ISCED 2011, a separate review and global consultation process took
place on the ISCED fields of education. The ISCED fields were revised, and the UNESCO General Conference
adopted the ISCED 2013 Fields of Education and Training classification (ISCED-F 2013) (UNESCO-UIS,
2014[4]) in November 2013 at its 37th session. Throughout this publication, the term “field of study” is used
to refer to the different fields of this classification.
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Standard error (S.E.)
The statistical estimates presented in this report are based on samples of adults, rather than values that could
be calculated if every person in the target population in every country had answered every question. Therefore,
each estimate has a degree of uncertainty associated with sampling and measurement error, which can be
expressed as a standard error. The use of confidence intervals is a way to make inferences about the population
means and proportions in a manner that reflects the uncertainty associated with the sample estimates. In this
report, confidence intervals are stated at a 95% level. In other words, the result for the corresponding population
would lie within the confidence interval in 95 out of 100 replications of the measurement on different samples
drawn from the same population.
In tables showing standard errors, the column with the heading “%”indicates the average percentage, and the
column with the heading “S.E.” indicates the standard error. Given the survey method, there is a sampling
uncertainty in the percentages (%) of twice the standard error (S.E.). For example, for the values: % = 10 and
S.E. = 2.6, 10% has an uncertainty zone of twice (1.96) the standard error of 2.6, assuming an error risk of 5%.
Thus, the true percentage would probably (error risk of 5%) be somewhere between 5% and 15% (“confidence
interval”). The confidence interval is calculated as: % +/– 1.96 * S.E., i.e. for the previous example, 5% = 10% –
1.96 * 2.6 and 15% = 10% + 1.96 * 2.6.
Symbols for missing data and abbreviations
These symbols and abbreviations are used in the tables and figures:
a Data are not applicable because the category does not apply.
b There is a break in the series (for example when data for the latest year refer to ISCED 2011 and data
for previous years refer to ISCED-97).
c

There are too few observations to provide reliable estimates.

d Includes data from another category.
m Data are not available – either missing or the indicator could not be computed due to low respondent
numbers
r

Values are below a certain reliability threshold and should be interpreted with caution.

q Data have been withdrawn at the request of the country concerned.
x Data included in another category or column of the table (e.g. x(2) means that data are included
in Column 2 of the table).
Further resources
The website www.oecd.org/education/education-at-a-glance-19991487.htm provides information on the
methods used to calculate the indicators, on the interpretation of the indicators in the respective national
contexts, and on the data sources involved. The website also provides access to the data underlying the
indicators and to a comprehensive glossary for technical terms used in this publication.
All post-production changes to this publication are listed at www.oecd.org/publishing/corrigenda (corrections)
and http://dx.doi.org/10.1787/eag-data-en (updates).
Education at a Glance uses the OECD’s StatLinks service. Below each table and figure in Education at a Glance
2018 is a URL that leads to a corresponding Excel file containing the underlying data for the indicator.
These URLs are stable and will not change. In addition, readers of the Education at a Glance e-book will be
able to click directly on these links and the workbook will open in a separate window.
The Education at a Glance Database on OECD.Stat (http://stats.oecd.org/) houses the raw data and indicators
presented in Education at a Glance, as well as the metadata that provides context and explanations for countries’
data. The Education at a Glance Database allows users to break down data in more ways than is possible in
this publication in order to conduct their own analyses of education systems in participating countries.
The Education at a Glance Database can be accessed from the OECD.stat site under the heading “Education and
Training”. Subnational data presented in this publication can be accessed from a subnational supplement to
Education at a Glance via the website https://nces.ed.gov/surveys/annualreports/oecd/.

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Layout of tables
In all tables, the numbers in parentheses at the top of the columns are simply used for reference. When a
consecutive number does not appear, that column is available on line only.
Abbreviations used in this report
ICT Information and communication technologies
ISCED International Standard Classification of Education
PIAAC Programme for the International Assessment of Adult Competencies
PPP Purchasing power parity
S.E. Standard error
STEM Science, technology, engineering and mathematics
UIS UNESCO Institute of Statistics
UOE Refers to the data collection managed by the three organisations, UNESCO, OECD, Eurostat

Note
1. On 3 May 2018, the Council invited Lithuania to become an OECD Member. However at the time of preparation of
the publication, the deposit of Lithuania’s instrument of accession to the OECD Convention was pending. Therefore
Lithuania does not appear in the list of OECD Members and is not included in the OECD and EU22 averages.

References
OECD (2018), OECD Handbook for Internationally Comparative Education Statistics 2018: Concepts, Standards, [1]
Definitions and Classifications, OECD Publishing, Paris, https://doi.org/10.1787/9789264304444-en.
OECD (2018), OECD Regional Statistics Database, http://stats.oecd.org/Index.aspx?DataSetCode=REGION_DEMOGR. [2]
OECD/Eurostat/UNESCO Institute for Statistics (2015), ISCED 2011 Operational Manual: Guidelines for Classifying [3]
National Education Programmes and Related Qualifications, OECD Publishing, Paris, http://dx.doi.org/10.1787/9789264
228368-en.
UNESCO-UIS (2014), ISCED Fields of Education and Training 2013 (ISCED-F 2013): Manual to Accompany the [4]
International Standard Classification of Education 2011; 2014, UNESCO Institute for Statistics, Montreal, http://
dx.doi.org/10.15220/978-92-9189-150-4-en (accessed on 18 April 2018).

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Executive summary
The impact of socio-economic status on equity in education tends to build
throughout life
Despite significant expansion in educational attainment over the past decade, those people with low-educated
parents, a proxy for low socio-economic status, are less likely to participate in early childhood education
programmes, complete upper secondary school and advance to higher levels of education than those with at
least one tertiary-educated parent. While two-thirds of 25-64 year-olds whose parents have not completed
upper secondary are expected to attain a higher level of education than their parents, most of them attain
upper secondary vocational education. The story is similar at the tertiary level: across OECD countries with
available data, 18-24 year-olds whose parents have not attained tertiary education represent only 47% of new
entrants into bachelor’s, long first-degree or equivalent programmes, although they represent more than 65% of
the population of that age group. These inequalities are then reflected in the labour market: those who have
attained only upper secondary education are less likely to be employed and earn 65% as much as their tertiaryeducated peers.

The gender gap favours girls in education, but men in the labour market
On average across OECD countries with available data, boys make up about 60% of secondary-school grade
repeaters and are less likely to complete that level of education than girls. As a result, a larger share of girls than boys
graduates from this level. Men are also less likely than women to attain tertiary education: 38% of men aged 25-34
were tertiary-educated on average across OECD countries in 2017 compared to 50% of women the same age, and
this gap has been widening over the past 10 years.
Despite better educational attainment, women still have worse employment outcomes. On average across
OECD countries, 80% of tertiary-educated young women are employed, compared with 89% of young men with
the same education, and the disparity increases among those with lower educational attainment. Tertiary-educated
women also earn 26% less than tertiary-educated men, on average across OECD countries. This pay disparity reflects
the gender gap observed between high- and low-paying fields of study at the tertiary level, but may also result
from women’s greater likelihood of going through periods of inactivity or unemployment, which may delay salary
increases.

Foreign-born adults and those with an immigrant background are less likely
to participate in education and to succeed in the labour market
First- and second-generation immigrants are under-represented among entrants into and graduates from bachelor’s
or long first-degree programmes in countries with available data. Foreign-born adults who arrived in their host
country at the age of 26 or older also tend to participate less in formal and/or non-formal education than their
native-born peers or than those who arrived before the age of 25, because they are less familiar with the education
system and language of the host country.
In most OECD countries, employment rates are lower among tertiary-educated foreign-born adults than among
their native-born peers, but the opposite is often observed among those with lower educational attainment.
These opposing trends reflect the difficulties tertiary-educated foreign-born adults face in gaining host-country
recognition for their education and experience, and the attractiveness, for employers, of the lower wage demands
of foreign-born adults with lower educational attainment. Foreign-born adults are also more likely to be neither
employed nor in education or training (NEET). Some 18% of foreign-born 15-29 year-olds are NEET compared to
13% of native-born young adults.

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23

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THE JOURNEY THROUGH EDUCATION AND EMPLOYMENT
What influences an individual's education and employment outcomes?

PARENTS' EDUCATION

IMMIGRANT
BACKGROUND AND
COUNTRY OF BIRTH

GENDER

Employment rate

BELOW UPPER
SECONDARY

Educational attainment

among women, men and foreign-born
individuals who leave school before
completing upper secondary education

among 25-64 year-olds whose
parents had not completed upper
secondary education (2012 or 2015)
Below upper
secondary

37%
14%

68%

25-64
year-olds

47%

32%

60%

25-64
year-olds

21%

Upper secondary –
general
Upper secondary –
vocational
Tertiary

25-64
year-olds

Employment rate
among tertiary-educated women, men
and foreign-born individuals

TERTIARY
Salaries

78%
25-64
year-olds

89%
25-64
year-olds

of those with tertiary education

USD 2 364

Average annual tuition fee for a
bachelor’s degree

75%

More than
of students in
countries with the highest tuition
fees beneﬁt from ﬁnancial aid

81%
25-64
year-olds
Tertiary-educated women

26% less

earn
than tertiary-educated men.

24

Tuition fees and
ﬁnancial aid

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Executive summary
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A signiﬁcant share of total
spending on tertiary education
is privately funded

Male teachers earn less than female teachers
relative to tertiary-educated men and women,
although school heads earn signiﬁcantly more

pre-primary school

Relative earnings of lower secondary teachers and school heads compared
to other full-time tertiary-educated workers

83%

150%

primary, secondary, post-secondary
non-tertiary
91%

69%
public + international

0%

private

among women, men and foreign-born individuals
who completed upper secondary education

Repeaters
repeat a grade in
upper secondary
general programmes

31%

Employment rate

UPPER SECONDARY
4%

9%

tertiary education

School heads

Male teachers

Female teachers

100%

50%

17%

Salaries

Those who completed upper
secondary education earn

58%

of them are boys

65%

82%
68%
25-64
year-olds

25-64
year-olds

72%

as much as tertiary-educated
workers

25-64
year-olds

Who is likely to participate in tertiary education?
Gender

Parents’ education

Immigrant background

Young men are less
likely than women to
earn a tertiary degree

Young adults without tertiary-educated
parents represent almost two-thirds of all
18-24 year-olds but less than half of new
entrants into higher education

First- and second-generation
immigrants are under-represented
among new entrants to tertiary
education.

50% 38%

47% 65%
Population

New entrants

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25

Executive summary
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Despite increases in public spending, a significant share of total funds for tertiary
and pre-primary education comes from private contributions
Between 2010 and 2015, expenditure per student increased by 5% at the primary, secondary and post-secondary
non-tertiary levels, and by 11% at the tertiary level. Educational institutions are still predominantly publicly funded.
In 2015, 90% of funding for primary, secondary and post-secondary non-tertiary education and 66% of funding for
tertiary education came from government coffers. Since a larger share of funding for tertiary education comes from
households, countries have implemented financial mechanisms to support families. At least 75% of students in
countries with the highest tuition fees benefit from these loans or grants.
With more 3-5 year-olds participating in early childhood education, public investment in pre-primary schools is
also increasing, amounting to 83% of total funding in 2015. Over the past decade, this share rose by 4 percentage
points across countries with available data. However, on average across OECD countries, one in three children
enrolled in pre-primary school attends a privately funded institution – a larger proportion than observed in any
other non‑tertiary level of education.

The teaching profession still suffers from large gender imbalances
Nearly all pre-primary teachers are women, but fewer than one in two tertiary instructors is a woman. Over the
past decade, this gender gap has widened at the primary and secondary levels, and narrowed at the tertiary level.
Attracting male teachers to the profession is particularly difficult: while the average actual salary of female teachers
is equal to or higher than the average salary of other full-time, tertiary-educated women, primary and secondary
male teachers earn between 77% and 88% of the average earnings of other full-time, tertiary-educated men.
However, between 2005 and 2017, on average across OECD countries and economies with available data, statutory
salaries of primary and secondary teachers with 15 years of experience and the most common qualifications in their
country, have increased by 5% to 8% and are back to pre-economic-crisis levels. Teachers also have strong incentives
to work to become school leaders: the actual salaries of school heads are at least 35% higher than the salaries of
teachers and at least 20% higher than the average earnings of other tertiary-educated workers.

Other findings
Regional disparities in participation in education tend to widen as the level of education increases. However, the
largest differences between subnational regions are observed in enrolment in early childhood education and care for
children under the age of three.
In half of the OECD countries and economies with available data, school heads and teachers working in a
disadvantaged or remote area are rewarded with additional compensation.
In most countries, decisions on how instruction is organised are predominantly taken at the school level, but
decisions related to planning and structures, personnel management and resources are more likely to be made at
higher levels of authority.

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Equity in the Education
Sustainable Development Goal
• The 17 Sustainable Development Goals (SDGs) adopted by the 70th General Assembly of the United Nations in
2015, otherwise known as the Global Goals or the 2030 Agenda for Sustainable Development, are a universal call
for action to end poverty, protect the planet and ensure that all people enjoy peace and prosperity. The fourth SDG
(SDG 4) is to: “Ensure inclusive and equitable quality education and promote lifelong learning opportunities for
all”. SDG 4 is to be achieved through the accomplishment of ten targets, which represent the most comprehensive
and ambitious agenda for global education ever attempted. Among these, Target 4.5 is of special interest for this
year’s edition of Education at a Glance as it focuses on equity.

• The 2030 Agenda for Sustainable Development widens the focus on participation to levels and programmes
outside compulsory education, including participation in adult education. Achieving equitable participation in
these programmes remains a challenge for many OECD countries.

• The 2030 Agenda for Sustainable Development has also a strong focus on equity in learning outcomes. In all
OECD countries, the performance of 15-year-olds in mathematics is strongly associated with the location of
their school (in rural or urban areas) and with their socio-economic background. These levels of socio-economic
inequity have remained the same for the last decade in the majority of countries.

Figure 1. Mathematics performance and gender, ESCS and location parity indices (2015)
Indicator 4.1.1 - Proportion of 15-year-olds achieving at least a proficiency level 2 (PISA) in mathematics
Parity indices

1.2

Gender
PISA index of economic, social and cultural status (ESCS)
Location

1.0
0.8
0.6
0.4

0.0

Brazil
Indonesia
Hungary
Chile
Turkey
Mexico
Colombia
Argentina
Costa Rica
Slovak Republic
Portugal
Greece
Luxembourg
Czech Republic
Lithuania
France
United States
Belgium
Latvia
New Zealand
Italy
United Kingdom
OECD average
Australia
Austria
EU 22 average
Israel
Sweden
Korea
Germany
Poland
Spain
Netherlands
Iceland
Slovenia
Russian Federation
Norway
Canada
Japan
Finland
Switzerland
Ireland
Estonia
Denmark

0.2

How to read this figure
In Denmark, the proportion of girls achieving at least PISA level 2 in mathematics is almost equal to that of boys (a parity index of 1 indicates
perfect parity). The proportion of children from the bottom quartile of the PISA ESCS index achieving at least PISA level 2 in mathematics is
20% lower than that of childen from the top ESCS quartile.
Note: The gender parity index refers to the ratio of the female value over the male value. ESCS refers to the PISA index of economic, social and cultural
status. The ESCS parity index refers to the ratio of the value for the bottom quartile over the value for the top quartile of the ESCS index. Location parity
is measured using the PISA definition of rural and urban areas (see the Definitions section at the end of this chapter). The location parity index refers to
the ratio of the value for rural areas over the value for urban areas.
Countries are ranked based on the average distance of each index to 1 (high to low).
Source: OECD (2018), Table 2. See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933801487

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Context
It is well recognised that education plays a critical role in eradicating poverty and steering the vision for prosperous
and sustainable development. As the 2018 World Development Report (World Bank Group, 2017[1]) and the 2016
Global Education Monitoring Report (UNESCO, 2016[2]) have made clear, education is also a foundation block
for nearly every other SDG. Education saves lives, improves health and fosters shared understanding and values.
Achieving SDG 4 will therefore be instrumental in realising the broader aspirations of the SDG agenda.
The international community has adopted a strong equity focus in the 2030 Agenda for Sustainable Development,
and in the Education SDG agenda in particular. SDG 4 is broken down into ten targets, each measured by a set
of global and thematic indicators. Among those, one whole target, Target 4.5, is dedicated to equity: “By 2030,
eliminate gender disparities in education and ensure access to all levels of education and vocational training for
the vulnerable, including persons with disabilities, indigenous peoples and children in vulnerable situations.” This
target is cross-cutting by nature and encompasses all types of inequality across all educational outcomes.
In line with the overall equity theme of this year’s edition of Education at a Glance, this chapter focuses on SDG
Target 4.5 (Box 1). It will present data on the global and thematic indicators as agreed internationally within the
context of the United Nations-led SDG framework, which in the case of SDG 4 is convened by UNESCO. The aim
is to provide an assessment of where OECD and partner countries are on their path towards meeting the equity
objectives of SDG Target 4.5.
Other findings

• The socio-economic status of students influences their participation in early childhood education, as well as in
vocational and technical education (see Indicator B2).

• Men and women (25-64 year-olds) have similar literacy skills, but men tend to have higher skills in numeracy.
Socio-economic background is also strongly associated with performance in numeracy. In two-thirds of countries
with available data, adults (25-64 year-olds) with at least one tertiary-educated parent perform better than those
whose parents have not attained this level of education.

• Men are more likely to use information and communications technology (ICT) skills than women, particularly the
more specialised skills, such as programming. On average across OECD countries, less than 10% of adults over
age 15 have recently used a specialised programming language. In all countries, men are at least 50% more likely
to have used programming than women.
Note
In the SDG 4 monitoring framework, each target has at least one global indicator and a number of related thematic
indicators designed to complement the analysis and measurement of the target. In total, there are 11 global
indicators and 32 thematic indicators included in the SDG 4 monitoring framework. A list of all the indicators and
their methodologies is available at http://SDG4monitoring.uis.unesco.org.
The tables and figures in this chapter present only a few of the agreed indicators for each target, selected based on
their relevance for OECD and partner countries and on data availability. Some of the SDG 4 indicators correspond
to indicators already published in other chapters of Education at a Glance. In those cases, the data are not repeated
in this chapter, and reference is made to the corresponding indicator.

Box 1. SDG Target 4.5
This chapter focuses on Target 4.5 of the Sustainable Development Goals, which calls for the elimination of
inequalities in education. Five indicators have been proposed to measure this target, as outlined in Table A below.
Global Indicator 4.5.1 sets the parity index as the main measure of inequity in education within the SDG 4
agenda (Box 2). This indicator casts a wide scope for measuring inequity, as it is meant to be applied to all
other SDG 4 indicators with available data and can be used to measure inequity along several dimensions.
Parity indices across a number of different indicators are presented and discussed in the Participation
and Skills sections of this chapter. Due to data availability, only three dimensions of equity are analysed:
gender, location (rural/urban) and socio-economic status (either measured using the index of economic,
social and cultural status (ESCS) or proxied by parental education).

…

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Indicator 4.5.2 addresses the fact that language can be an important source of inequities in education. Teaching
children in a language they do not speak at home can hinder their ability to learn and reinforce learning gaps
between different groups. Results from PISA 2015 indicate that immigrant students who speak a language at
home that is different from the language of assessment score over 20 points less in science than immigrants
who speak the language of assessment at home. Nevertheless, Indicator 4.5.2 is targeted at younger children
(primary school), for which data is not currently available (OECD, 2016[3]). This indicator is therefore not
addressed in this chapter.
The other three indicators (4.5.3, 4.5.4, and 4.5.5) relate to the financing of education, which is an important
means through which equity can be pursued. These three indicators are addressed in the Resources section of
this chapter.
Table 1. SDG Indicators for Target 4.5
Target 4.5: By 2030, eliminate gender disparities in education and ensure access to all levels of education
and vocational training for the vulnerable, including persons with disabilities, indigenous peoples
and children in vulnerable situations.
Indicator

Definition

4.5.1 (Global)

Parity indices (female/male, rural/urban, bottom/top wealth quintiles and others, such as disability
status, indigenous peoples and conflict-affected, as data become available) for all education indicators
on this list that can be disaggregated

4.5.2

Percentage of students in primary education whose first or home language is the language of
instruction

4.5.3

Extent to which explicit formula-based policies reallocate education resources to disadvantaged
populations

4.5.4

Percentage of total aid to education allocated to least developed countries

4.5.5

Education expenditure per student by level of education and source of funding

Analysis
SDG 4 and its associated targets set an ambitious agenda that emphasises quality learning and equity in education
alongside the more traditional indicators of access and participation. In doing so, it challenges every country in the
world to improve its education system and marks a significant departure from previous global education goals and
targets, such as the Millennium Development Goals, which were not as far-reaching and focused more on access and
participation. The analysis below takes into account this larger scope and reports on equity levels in the areas of
participation, skills acquisition and resources.
Participation in education
The 2030 Agenda for Sustainable Development widens the focus to education levels outside the traditional frame
of compulsory education, including early childhood education and care (Indicator 4.2.2), secondary, post-secondary
and tertiary vocational education (Indicator 4.3.3) and adult education (Indicator 4.3.1). Ensuring inclusive, quality
education at these levels remains a challenge for most OECD member and partner countries.
Target 4.2 reaffirms the importance for all children of receiving a strong foundation through early childhood education
and care (ECEC). Evidence has widely shown that the early years play a pivotal role in determining future performance
and breaking the vicious circle of socio-economic inequality (OECD, 2017[4]). On average across OECD countries,
95% of children one year younger than the official primary school entry age are enrolled in ECEC, and all boys and girls
participate equally in ECEC (Table 1). However, targeting the most disadvantaged groups remains a challenge in many
countries. Indicator B2 of this publication highlights the fact that the mother’s educational attainment often affects
enrolment in ECEC. On average across countries with available data, only 31% of children below the age of 3 whose
mother has not attained tertiary education participate in early childhood education, compared to 41% of those whose
mother has completed tertiary education (Table B2.1c, available on line).
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Box 2. Measuring inequity in education and the parity index
Measuring equity is challenging for at least three reasons. First, the notion of equity is linked to a normative
framework of fairness, which may differ across countries and cultures. Second, there is a general lack of
data availability because equity indicators often require more refined data that allow for disaggregation
among different groups in the population. As an additional challenge, in the case of the SDG framework,
this disaggregation must also follow internationally agreed definitions that do not always match the national
definitions. Third, there are several different methods for measuring equity, all of which have advantages and
disadvantages, and that could lead to different conclusions about the degree of inequity in a given country
(UIS, 2018[5]).
The main indicator chosen to measure equity across the SDG 4 agenda is the parity index. It is defined as
the ratio between the values of a given indicator for two different groups, with the value of the likely most
disadvantaged group in the numerator. A parity index equal to 1 indicates parity between the two considered
groups. A value of less than 1 indicates a disparity in favour of the likely most advantaged group, and a value
greater than 1 indicates a disparity in favour of the most disadvantaged group.
The use of a parity index provides the relative magnitude of the disparity in a simple, easy-to-communicate
way. However, it also has some drawbacks, such as being sensitive to low values and not being symmetrical
around 1 (perfect equality). For example, if the enrolment rate for girls is 40% and for boys it is 50%, the
gender parity index (GPI) has a value of 0.8. If the female and male values are reversed, the GPI has a value
of 1.25, which gives the mistaken impression of greater gender disparity because 1.25 is at a greater distance
from 1 than 0.8 (UIS, 2010[6]). To solve this, an adjusted parity index, which is symmetrical around 1, is used
in the tables and figures of this indicator whenever values for the likely advantaged and likely disadvantaged
groups are switched for an observation (see Methodology section at the end of this chapter).
For more information on measuring inequity in education, please see the UNESCO Handbook on Measuring
Equity in Education (UIS, 2018[5]). The handbook provides a conceptual framework for measuring equity in
education and offers thorough methodological guidance on how to calculate and interpret various types of
equity indicators.

At the other end of non-compulsory education, Target 4.3 focuses on participation in technical, vocational and
tertiary levels of education and training. Each of these programmes plays an important role in preparing students
for the labour market. Participation of 15-24 year-olds in technical-vocational programmes in secondary,
post‑secondary non-tertiary and short-cycle tertiary education (Thematic Indicator 4.3.3) varies widely across
countries, from 4% in Brazil to 30% in Slovenia,1 and has a strong association with both gender and socio-economic
status. In most OECD and partner countries, boys are at least 40% more likely than girls to enrol in vocational
education (Figure 2.a), and students whose parents did not attain tertiary education are more likely to choose upper
secondary vocational programmes than general programmes (Box B3.1).
Finally, Global Indicator 4.3.1 measures the participation rate of adults (25-64 year-olds) in formal and non-formal
education and training in the previous 12 months. By including formal and non-formal education, this indicator
captures participation in any type of programme that aims to improve knowledge, skills and competencies from a
personal, civic, social or employment-related perspective (UNESCO, 2016[2]). In most OECD and partner countries,
at least 20% of 25-64 year-olds have participated in formal or non-formal education and training in the previous
12 months, with participation among men and women varying greatly across countries. Figure 2.b shows that the
gender gap for Global Indicator 4.3.1 varies in magnitude and direction across countries. Participation is higher
among women in 17 countries and higher among men in 13 countries. The most extreme cases are in Turkey, where
participation for women is about 30% lower than for men, and in Estonia, Lithuania and the Russian Federation,
where participation for women is at least 30% higher.
Skills
The ultimate goal of education policy is not to simply provide access to all levels of education, but also to ensure that
all students gain the necessary skills to guide them through life. All children, youth and adults, regardless of their
gender, location or background, should be able to acquire similar skills and reach comparable levels of proficiency.

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The OECD Programme for International Student Assessment (PISA) provides valuable insights to Global
Indicator 4.1.1.c, which measures the “Proportion of children and young people at the end of lower secondary
achieving at least a minimum proficiency level in (i) reading and (ii) mathematics, by sex”. Level 2 proficiency
in reading and mathematics in PISA has been internationally accepted for the purposes of SDG 4 monitoring of
minimum proficiency level achievement at the end of lower secondary in 2017 and 2018. Figure 1 displays parity
indices for Indicator 4.1.1.c, measured along gender, location (urban and rural) and socio-economic background
(based on the PISA index of economic, social and cultural status [ESCS], see the Definitions section at the end of
this chapter). Among 15-year-olds, there are usually as many boys as girls who achieve at least PISA Level 2 in
mathematics, and more girls who achieve PISA Level 2 in reading (Table 2 and Table 3, available on line).2
However, students’ performance remains strongly determined by their school’s location in the majority of
OECD and partner countries. Students in urban schools (located in communities with over 100 000 inhabitants)
are more likely to achieve at least Level 2 than students rural schools (located in communities with fewer than
100 000 inhabitants). Suburban areas are not taken into account. Students in urban schools tend to perform better
because they go to schools that are usually larger and more likely to gather a higher proportion of qualified teachers.
They are also more likely to come from a socio-economically advantaged background, which is directly linked to their
performance in PISA (OECD, 2013[7]).
The performance gap between students from different socio-economic backgrounds remains a reality in all
countries, for both reading and mathematics skills. Even in those where parity is (almost) met along each of the
three dimensions displayed in Figure 1, such as Denmark, Estonia and Slovenia, the proportion of youth achieving
PISA Level 2 in mathematics remains 20% lower among the most disadvantaged students. Even more concerning,
levels of socio-economic inequity have not changed since 2006 in the majority of countries. Figure 3 shows that
in a few countries, such as Australia, Finland and Korea, the discrepancy between students in the top and bottom
quartiles of PISA’s socio-economic ESCS index grew even larger between 2006 and 2015. However, PISA results
show that inequality of opportunity is not set in stone, and that selected school systems succeeded in becoming
more equitable over a relatively short period (OECD, 2017[8]). This is the case in Mexico and the Russian Federation,
where the gap between ESCS quartiles narrowed significantly in this period, although high discrepancies between
disadvantaged and advantaged students remain.
Target 4.4 refers to skills for work. One measure of this target is the percentage of adults who have attained tertiary
education (Thematic Indicator 4.4.3). Across OECD countries, 36% of 25-64 year-olds have attained tertiary
education, but one’s educational attainment is likely to depend on his or her parents’ educational attainment.
Among adults who have at least one parent who attained tertiary education, 68% attained tertiary education
themselves, compared to 21% of those whose parents have not attained upper secondary education (see Box A1.1 in
Indicator A1). While these inequalities may be reflected in the labour market, it is important to keep in mind that
attainment is not a direct measure of skills.
Global Indicator 4.6.1 measures the “Percentage of population in a given age group achieving at least a fixed level of
proficiency in functional (a) literacy and (b) numeracy skills, by sex.” In the Survey of Adult Skills, a product of the
OECD Programme for the International Assessment of Adult Competencies (PIAAC), this fixed level corresponds to
PIAAC score 226 in (a) numeracy and (b) literacy skills. This score corresponds to Level 2 in the Survey of Adult Skills
(PIAAC), which reports results on a scale from Below Level 1 (below 176 points) to Level 5 (376 points or more).
Among 25-64 year-olds, gender parity in numeracy skills is met in less than half of the countries with available data
(Table 2). However, women and men perform similarly in literacy in the majority of OECD and partner countries
(Table 3 available on line). Socio-economic background is more strongly related to performance than gender. In all
countries with available data, adults with at least one tertiary-educated parent have higher numeracy skills than
those whose parents have not attained this level of education (Table 2).
In today’s increasingly digitalised economies, literacy and numeracy skills may not be sufficient to thrive in the
labour market. Related to SDG Target 4.4 on Skills for Work, Global Indicator 4.4.1 measures the “Proportion of
youth and adults with information and communications technology (ICT) skills, by type of skill.” This indicator has
been developed according to the definition of the International Telecommunication Union in the framework of the
Partnership on Measuring ICT for Development (ITU, 2014[9]). ICT skills refer to nine computer-related activities
with varying levels of difficulty, from transferring files between a computer and other devices to writing a computer
programme using a specialised programming language.
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Figure 2.a. Gender parity in participation in technical-vocational programmes (2016)
Indicator 4.3.3 - Participation rate of 15-24 year-olds in technical-vocational programmes
and related gender parity index
%

35
Slovenia

30

Belgium

25
20
Norway

15

Estonia
Greece

Iceland

10

Austria
Czech Republic
Turkey
Slovak Republic
United Kingdom
Finland
Switzerland
Luxembourg
Italy
Australia
Netherlands
Germany
France
Poland
Portugal
Chile
Russian
Federation
Latvia
Korea Spain
Hungary
Sweden

Denmark

Lithuania

Israel

Mexico

Ireland

5

Brazil

0
0.4

0.5

0.6

0.7

0.8

0.9

1.0

1.1

1.2

Gender parity index

Note: Indicator 4.3.3 refers to participation in technical and vocational programmes in secondary, post-secondary non-tertiary and short-cycle
tertiary education (ISCED 2 to 5).
Source: OECD (2018), Table 1. See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933801506

Figure 2.b. Gender parity in participation in adult education (2012 or 2015, 2016)
Indicator 4.3.1 - Participation rate of 25-64 year-olds in formal and non-formal education
and related gender parity index
%

80
Switzerland

70

New Zealand
United States
Norway

Netherlands
Austria
Hungary Canada

60
Korea

50

Chile

40

Japan

Czech
Republic

Australia
Portugal
Italy

Sweden

Germany United Kingdom
France
Belgium
Denmark
Slovenia
Luxembourg
Spain

Iceland

Finland
Latvia

Estonia

Slovak
Republic

30
Turkey

Lithuania

Poland

Ireland

20

Greece

Russian Federation

10
0.5

0.6

0.7

0.8

0.9

1.0

1.1

1.2

1.3

1.4

Gender parity index

Note: Data from the Survey of Adult Skills (PIAAC) are reported and refer to 2012 for Australia, Canada, Korea, Russian Federation and the United States
and 2015 for Chile, Israel, New Zealand and Turkey. For other countries, data from the Adult Education Survey (AES) are reported and refer to 2011 for
Ireland and 2016 for all others.
Source: OECD (2018), Table 1. See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933801525

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Men are more likely to use ICT skills than women, particularly the more specialised skills such as programming.
On average across OECD countries, over 50% of adults over the age of 15 have transferred files between a computer
and other devices in the last three months, and women are only about 10% less likely to have recently used this
skill in comparison to men.3 On the other hand, except in a few countries, such as Denmark and Iceland, less than
10% of adults over the age of 15 have recently used a specialised programming language. In all countries, men are
at least 50% more likely to have recently run a programme than women (Table 2). These results mirror the gender
differences in fields of study and occupations, as men are more likely to obtain a degree in the fields of science,
technology, engineering and mathematics (STEM) (OECD, 2018[10]).

Figure 3. Trends in socio-economic (ESCS) parity index (2006, 2015)
Indicator 4.1.1 - Proportion of 15-year-olds achieving at least proficiency level 2 (PISA) in mathematics
ESCS parity index

1.0

2015

2006

0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
Estonia
Russian Federation
Japan
Canada
Denmark
Finland
Slovenia
Norway
Korea
Iceland
Ireland
Switzerland
Netherlands
Poland
Germany
Latvia
Sweden
Italy
Australia
New Zealand
Austria
Belgium
Lithuania
Spain
Portugal
Czech Republic
France
United States
Luxembourg
Slovak Republic
Israel
Greece
Hungary
Turkey
Mexico
Chile
Colombia
Indonesia
Brazil

0.0

Note: Gray bars indicate that ESCS parity has gotten closer to 1 (perfect parity) between 2006 and 2015, while blue bars indicate that it has gotten
further from 1 in the same period.
Countries are ranked in descending order of the ESCS parity index value in 2015.
Source: OECD (2018), Table 2, and PISA database. See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag2018-36-en).
1 2 https://doi.org/10.1787/888933801544

Resources
Ensuring equitable participation and skills acquisition relies on the availability of resources. That is why Target 4.5
contains three financing-related indicators, each of which tackles education expenditure from a different angle.
Thematic Indicator 4.5.4 on “Education expenditure per student by level of education and source of funding” provides
a meaningful way to measure the availability of resources in a country. This indicator alone cannot measure the
quality or equitability of education in a country, but it serves as a useful reference point. Increased data availability,
such as disaggregation by students’ socio-economic status or location of schools, for example, would provide more
relevant information to measure Target 4.5.
Expenditure per student is presented for OECD and partner countries in Indicator C1 of this edition of Education
at a Glance. Results show that governments are by far the main investors in education, especially at primary and
secondary levels. There are higher shares of private expenditure at the tertiary level, which may raise equity concerns
if financial support to students, such as grants and public loans, are not readily available.
Even though governments are the main source of education expenditure, international assistance remains an
important financing mechanism in least developed countries. Indicator 4.5.5, “Percentage of total aid to education
allocated to least developed countries”, aims to measure the extent to which international education assistance
Education at a Glance 2018: OECD Indicators   © OECD 2018

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The education sustainable development goal
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is targeted to the countries that are most in need. Figure 4 shows the total official development assistance to
education disbursed by each OECD country to all developing countries and the share of this assistance directed to
least developed countries.
These figures only include public bilateral assistance transfers, so transfers to multilateral organisations, such as
the World Bank, the European Commission and other important institutions in education funding worldwide like
the Global Partnership for Education, are not included. As a result, countries that donate mostly through multilateral
organisations may appear lower than those that donate directly to other countries, even if the total amount given is
higher. These figures also do not include aid destined to humanitarian aid or aid allocated for budget support which
could also help achieve education goals.

Figure 4. Official development assistance to education, gross disbursements and percentage
allocated to least developed countries (2016)
Including scholarships and imputed student costs, current prices
USD millions

2 000

Germany

1 800
1 600
United States

1 400
United Kingdom

1 200

France

1 000
800
Japan

600
Australia

400

Norway
Netherlands

Austria
200
Hungary Poland
Latvia
Spain
Denmark
Slovenia
0
Slovak Republic
Estonia
Greece

0

10

Korea
Canada

Belgium

20

Italy

Switzerland

Portugal

Sweden

New Zealand

Finland

Ireland

Luxembourg

Iceland

Czech
Republic

30

40

50

60

70

80

90

100

Percentage of total ODA to education
allocated to least developed countries

Source: OECD (2018), “Creditor Reporting System: Aid activities”, OECD International Development Statistics (database), http://dx.doi.org/10.1787/
data-00061-en (accessed on 03 May 2018).
1 2 https://doi.org/10.1787/888933801563

These two indicators address the availability of resources, but it is not only the amount of resources that matters, but
also how effectively these resources are allocated. Evidence consistently points to the fact that spending more does
not necessarily lead to better outcomes (OECD, 2012[11]). This is especially true as countries try to develop education
systems that strive for both excellence and equity. The SDG Thematic Indicator 4.5.3 attempts to tackle this issue
by measuring “the extent to which explicit formula-based policies reallocate education resources to disadvantaged
populations”. Lack of data and of an international agreement on its scope has led this indicator to be classified as
requiring further development, and it has not yet been approved for monitoring. However, the concept behind the
indicator and the notion that countries must find efficient ways to diminish inequalities in education remain pertinent.
The 2017 OECD report, The Funding of School Education: Connecting Resources and Learning (OECD, 2017[12]), sheds
light on countries’ strategies to allocate resources, taking into account the fact that schools have different resource
needs. For example, in Chile, the Flemish and French Communities of Belgium, Estonia and Israel, at least part of

34

Education at a Glance 2018: OECD Indicators   © OECD 2018

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the main school-funding mechanism is allocated using a formula with different weightings for variables such as
students’ socio-economic characteristics, school location and special educational needs. Some of these countries
also provide targeted funding outside of the main allocation mechanism for specific groups, such as newly arrived
immigrants or refugees. These examples may not be appropriate in every context, and there are several other policy
tools that can be used by countries (UNESCO, 2016[2]). What is important is that countries take steps to ensure that
resource allocation also tackles equity concerns.

Definitions
Level 2 in PISA (baseline proficiency level):

• Mathematics: Students can use basic algorithms, formulae, procedures or conventions to solve problems involving
whole numbers (e.g. to compute the approximate price of an object in a different currency or to compare the total
distance across two alternative routes). They can interpret and recognise situations in contexts that require no more
than direct inference, extract relevant information from a single source and make use of a single representational
mode. Students at this level are capable of making literal interpretations of the results.

• Reading: Students begin to demonstrate the reading skills that will enable them to participate effectively and
productively in life. Some tasks at Level 2 require the student to retrieve one or more pieces of information that
may have to be inferred and may have to meet several conditions. Others require recognising the main idea in a
text, understanding relationships, or interpreting meaning within a limited part of the text when the information
is not prominent and the student must make low-level inferences.
Level 2 (score 226) in PIAAC (baseline proficiency level):

• Numeracy: Tasks at this level require the application of two or more steps or processes involving calculation with
whole numbers and common decimals, percentages and fractions; simple measurement and spatial representation;
estimation; and interpretation of relatively simple data and statistics in texts, tables and graphs.

• Literacy: Tasks at this level require the respondent to make matches between the text, either digital or printed,
and information, and may require paraphrasing or low-level inferences.
The PISA index of economic, social and cultural status (ESCS) was created on the basis of the following variables:
1) the International Socio-Economic Index of Occupational Status (ISEI); 2) the highest level of education of the
student’s parents, converted into years of schooling; 3) the PISA index of family wealth; 4) the PISA index of home
educational resources; and 5) the PISA index of possessions related to “classical” culture in the family home. See
Volume I of PISA 2015 Results (OECD, 2016[3]) for more information.
Technical and vocational education and training is a comprehensive term commonly used by the UNESCO Institute
for Statistics to refer to education, training and skills development in a wide range of occupational fields, production,
services and livelihoods. Vocational education may have work-based components (e.g. apprenticeships, dual-system
education programmes). Successful completion of such programmes leads to labour market-relevant, vocational
qualifications acknowledged as occupationally-oriented by the relevant national authorities and/or the labour market.
Parental education (only two categories are considered in this chapter):
• Below tertiary means that neither parent has attained a tertiary degree (ISCED 2011 levels 5, 6, 7 and 8).
• Tertiary means that at least one parent has attained a tertiary degree (ISCED 2011 levels 5, 6, 7 and 8).
Location is defined based on the number of inhabitants in the community where the school is located. In the PISA
survey, principals are asked to choose the closest description to the community. Rural schools are those where
the principal answered “a village, hamlet or rural area” (fewer than 3 000 people), “a small town” (3 000 to about
15 000 people) or a town (15 000 to about 100 000 people), whereas urban schools are those where the principal
answered either “a city” (100 000 to about 1 million people) or “a large city” (with over 1 million people).
The Development Assistance Committee List of Official Development Assistance Recipients shows all countries and
territories eligible to receive official development assistance. These consist of all low- and middle-income countries,
based on gross national income per capita as published by the World Bank, with the exception of G8 members,
EU members, and countries with a firm date for entry into the European Union. The list also includes all of the
Least Developed Countries as defined by the United Nations (UN-OHRLLS[13]). Least developed countries (LDCs)
are low-income countries confronting severe structural impediments to sustainable development, they are highly
vulnerable to economic and environmental shocks and have low levels of human assets.
Education at a Glance 2018: OECD Indicators   © OECD 2018

35

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Methodology
The parity indices are calculated using the more likely disadvantaged group as the numerator and the more likely
advantaged group in the denominator. The gender parity is calculated as the indicator value for women divided by
the indicator value for men. The ESCS parity index is calculated as Q1%/Q 4%, where Q = a quartile of ESCS. The
location parity index is calculated as the indicator value for rural schools divided by the indicator value for urban
schools. The parental education parity index is calculated as the indicator value for those whose parents have not
attained tertiary education divided by the value for those with at least one tertiary-educated parent.
In order to make the parity index results symmetrical around 1, the adjusted parity index is used whenever the indicator
values for the likely advantaged and likely disadvantaged groups are switched for an observation. For example, if the
enrolment rate for girls (likely disadvantaged) is higher than the enrolment rate for boys (likely advantaged), the
adjusted parity index is calculated for this observation. The adjusted parity index (API) is calculated as API = 2-(value
for likely advantaged group/ value for likely disadvantaged group).
All indicators presented in this chapter follow the agreed SDG methodology, and may differ in some cases from
other indicators presented in Education at a Glance, including on issues such as population data sources (i.e. the
population data used in this chapter is collected from the United Nations Population Division).
Lithuania was not an OECD member at the time of preparation of this publication. Accordingly, Lithuania does not
appear in the list of OECD members and is not included in the zone aggregates.
Indicator Source
4.1.1
OECD, PISA 2015 Database
4.2.2
UOE 2017 data collection
4.3.1
Two different data sources: PIAAC (2012, 2015) and Adult Education Survey (2016)
4.3.3
UOE 2017 data collection
4.4.1
International Telecommunication Union (2015)
4.4.3
Indicator A1 in Education at a Glance 2018
4.5.3
The Funding of School Education OECD
4.5.4
OECD International Development Statistics Database
4.5.5
Indicator C1 in Education at a Glance 2018
4.6.1
PIAAC Database (2012, 2015)

Note regarding data from Israel
The statistical data for Israel are supplied by and are under the responsibility of the relevant Israeli authorities. The use
of such data by the OECD is without prejudice to the status of the Golan Heights, East Jerusalem and Israeli settlements
in the West Bank under the terms of international law.

Notes
1. In many countries, the large majority of students who participate in technical-vocational programmes do so at ages
corresponding to upper secondary education (mostly age 15-19; see Indicator B1 for more information on enrolment in secondary
education). Thus, taking into account the extended 15-24 age span in Indicator 4.3.3 may underestimate participation rates in
these programmes.
2. Although boys and girls are likely to perform similarly at PISA Level 2 in mathematics, the gender gap in favour of boys
increases at higher levels of performance.
3. According to the ITU survey manual, the question asked is: “Which of the following computer-related activities have you
carried out in the last three months? Respondent should select all that apply.” Respondents have the choice among nine ICT
skills. The indicator therefore measures the percentage of individuals who have used the specific skills.

References
ITU (2014), Manual for Measuring ICT Access and Use by Households and Individuals, International Telecommunication Union. [9]
OECD (2018), “How is the tertiary-educated population evolving?”, Education Indicators in Focus, No. 61, OECD Publishing, [10]
Paris, http://dx.doi.org/10.1787/a17e95dc-en.
OECD (2017), Starting Strong 2017: Key OECD Indicators on Early Childhood Education and Care, OECD Publishing, Paris, [4]
http://dx.doi.org/10.1787/9789264276116-en.

36

Education at a Glance 2018: OECD Indicators   © OECD 2018

The education sustainable development goal
Under embargo until 11/09/2018 at 11.00am CEST
OECD (2017), The Funding of School Education: Connecting Resources and Learning, OECD Reviews of School Resources, [12]
OECD Publishing, Paris, http://dx.doi.org/10.1787/9789264276147-en.
OECD (2017), “Where did equity in education improve over the past decade?”, PISA in Focus, No. 68, OECD Publishing, [8]
Paris, http://dx.doi.org/10.1787/33602e45-en.
OECD (2016), PISA 2015 Results (Volume I): Excellence and Equity in Education, PISA, OECD Publishing, Paris, http:// [3]
dx.doi.org/10.1787/9789264266490-en.
OECD (2013), “What makes urban schools different?”, PISA in Focus, No. 28, OECD Publishing, Paris, http://dx.doi. [7]
org/10.1787/5k46l8w342jc-en.
OECD (2012), “Does money buy strong performance in PISA?”, PISA in Focus, No. 13, OECD Publishing, Paris, http:// [11]
dx.doi.org/10.1787/5k9fhmfzc4xx-en.
UIS (2018), Handbook on Measuring Equity in Education, UNESCO Institute for Statistics, Montreal, http://uis.unesco.org/ [5]
sites/default/files/documents/handbook-measuring-equity-education-2018-en.pdf (accessed on 02 May 2018).
UIS (2010), Global Education Digest 2010: Comparing Education Statistics across the World, UNESCO Institute for Statistics, [6]
Montreal, http://unesdoc.unesco.org/images/0018/001894/189433e.pdf (accessed on 05 June 2018).
UNESCO (2016), Global Education Monitoring Report 2016: Education for People and Planet: Creating Sustainable Futures for All. [2]
UN-OHRLLS((n.d.)), About LDCs, http://unohrlls.org/about-ldcs/ (accessed on 10 July 2018).

[13]

World Bank Group (2017), World Development Report 2018: Learning to Realize Education’s Promise, The World Bank, [1]
Washington DC, http://dx.doi.org/10.1596/978-1-4648-1096-1.

”The education sustainable development goal” Tables
1 2 https://doi.org/10.1787/888933801430

Table 1

Equity in participation in education

Table 2

Equity in skills acquisition (mathematics, numeracy and ICT skills)

WEB Table 3

Equity in skills acquisition (reading and literacy skills)

Data can be found on line at http://dx.doi.org/10.1787/eag-data-en.

Education at a Glance 2018: OECD Indicators   © OECD 2018

37

The education sustainable development goal
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Table 1. Equity in participation in education
Indicators 4.2.2, 4.3.1 and 4.3.3 and related parity indices
Target 4.2 – By 2030, ensure that all boys and girls
have access to quality early childhood development,
care and pre-primary education so that
they are ready for primary education
4.2.2 Participation rate in organised learning
one year before the official primary entry age1
(2016)

Partners

OECD

%

Gender parity index4

Target 4.3 – By 2030, ensure equal access for all women and men
to affordable and quality technical, vocational and tertiary education,
including university
4.3.1 Participation rate of adults in formal
and non-formal education2
(2012/2015, 2016)
%

4.3.3 Participation rate
of 15-24 year-olds in technical
and vocational programmes3
(2016)

(S.E.)

Gender parity
index4

%

(3)

Gender parity
index4

(1)

(2)

(4)

(5)

(6)

Australia
Austria
Belgium
Canada
Chile
Czech Republic
Denmark
Estonia
Finland
France5
Germany
Greece
Hungary
Iceland
Ireland5
Israel5
Italy
Japan
Korea
Latvia5
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United Kingdom
United States5

91
99
100
93
97
92
98
91
99
100
100
89
91
99
98
97
98
91
96
97
99
99
99
92
98
100
100
82
94
96
99
99
66
100
91

1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
m
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0

55
60
45
58
47
46
50
44
54
51
52
17
56
m
24
53
42
42
50
48
48
m
64
67
60
26
46
46
46
43
64
69
22
52
59

0.7
m
m
0.6
1.9
m
m
m
m
m
m
m
m
m
m
0.7
m
0.8
0.8
m
m
m
m
0.8
m
m
m
m
m
m
m
m
0.8
m
1.1

1.0
1.0
1.0
1.0
0.8
0.9
1.1
1.3
1.2
1.1
1.0
1.1
0.9
m
1.0
1.0
0.9
0.7
0.8
1.2
1.0
m
1.0
1.0
1.0
1.0
0.9
1.0
1.1
1.0
1.1
1.0
0.6
1.1
1.0

22
28
25
m
18
25
13
12
22
19
20
12
13
10
8
15
23
6
15
16
23
12
22
m
18
19
17
22
30
15
12
23
26
22
m

0.8
0.9
0.9
m
1.0
0.8
0.7
0.7
0.9
0.8
0.8
0.7
0.8
0.5
0.8
1.1
0.6
0.8
0.7
0.9
1.0
1.0
0.9
m
0.6
0.9
0.7
0.9
0.8
0.8
0.8
0.8
0.9
0.9
m

OECD average
EU22 average

95
96

1.0
1.0

49
47

~
~

1.0
1.0

18
19

0.8
0.8

Argentina
Brazil5
China
Colombia
Costa Rica
India
Indonesia
Lithuania5
Russian Federation
Saudi Arabia
South Africa

m
97
m
m
m
m
m
99
96
m
m

m
1.0
m
m
m
m
m
1.0
1.0
m
m

m
m
m
m
m
m
m
28
19
m
m

m
m
m
m
m
m
m
m
1.5
m
m

m
m
m
m
m
m
m
1.3
1.3
m
m

m
4
m
m
m
m
m
9
16
m
m

m
1.2
m
m
m
m
m
0.7
0.9
m
m

G20 average

m

m

m

~

m

m

m

1. Official primary entry ages are reported in Table X1.3. in Annex 1.
2. Data from the Survey of Adult Skills (PIAAC) are reported in italics and refer to 2012 for Australia, Canada, Korea, Russian Federation and the United States and 2015 for
Chile, Israel, New Zealand and Turkey. Data from the Adult Education Survey (AES) are not italicised and refer to 2011 for Ireland and 2016 for all others.
3. Indicator 4.3.3 refers to participation in technical and vocational programmes in secondary, post-secondary non-tertiary and short-cycle tertiary education (ISCED 2 to 5).
4. Gender parity index refers to the ratio of the female value over the male value.
5. Population data is collected from the UOE data or Eurostat database (instead of UNPD).
Source: OECD / UIS / Eurostat (2018), Eurostat (2011, 2016) and PIAAC (2012/2015). See Source section for more information and Annex 3 for notes (http://dx.doi.
org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933801449

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Table 2. Equity in skills acquisition (mathematics, numeracy and ICT Skills)
Indicator 4.1.1 (mathematics), 4.4.1 and 4.6.1 (numeracy) and related parity indices
Target 4.6 – By 2030, ensure that
Target 4.4 – By 2030, substantially increase
Target 4.1 – By 2030, ensure that all
all youth and a substantial
the number of youth and adults who have
girls and boys complete free, equitable
proportion of adults, both men
relevant skills, including technical and
and quality primary and secondary
and women, achieve literacy
vocational skills, for employment, decent work
education leading to relevant and
and numeracy
and entrepreneurship
effective learning outcomes

4.1.1 Proportion of 15-year-olds achieving
at least a minimum proficiency level
(PISA level 2) in mathematics
(2015)1

%

(S.E.)

Partners

OECD

(1)

Gender
parity
index2

ESCS
parity
index3

Location
parity
index4

(2)

(3)

(4)

4.4.1 Proportion 4.4.1 Proportion 4.4.1 Proportion
of adults over
of adults over
of adults over
age 15 with
age 15 with
age 15 with
information and information and information and
communications communications communications
technology
technology
technology
(ICT) skills
(ICT) skills
(ICT) skills
Programming
Presentation
File transfer
language (2015)
(2015)
(2015)

%

Gender
parity
index2

(5)

(6)

%

Gender
parity
index2

%

Gender
parity
index2

(7)

(8)

(9)

(10)

4.6.1 Proportion of adults
(25-64 year-olds) achieving at least
a fixed level of proficiency (score 226)
in functional numeracy skills
(2012/2015)1

%

(S.E.)

Parental
Gender education
parity attainment
index2 parity index5

(11)

(12)

(13)

Australia
Austria
French Comm. (Belgium)
Canada
Chile
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United Kingdom
United States

78
78
80
86
51
78
86
89
86
77
83
64
72
76
85
68
77
89
85
79
74
43
83
78
83
83
76
72
84
78
79
84
49
78
71

0.6
1.1
1.0
0.7
1.3
1.1
0.9
0.7
0.8
0.9
1.0
1.8
1.2
1.0
0.9
1.4
1.1
0.8
1.1
1.0
0.7
1.3
0.9
1.0
0.8
1.0
1.0
1.2
0.6
1.0
1.2
1.0
2.2
1.0
1.4

1.0
0.9
1.0
1.0
0.8
1.0
1.0
1.0
1.1
1.0
1.0
1.0
1.0
1.0
1.0
1.0
0.9
1.0
1.1
1.0
1.0
0.9
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0

0.7
0.7
0.7
0.8
0.4
0.6
0.8
0.8
0.8
0.6
0.8
0.6
0.6
0.8
0.8
0.6
0.7
0.8
0.8
0.7
0.6
0.5
0.8
0.7
0.8
0.8
0.7
0.6
0.8
0.7
0.7
0.8
0.5
0.8
0.6

0.8
0.9
1.2
0.9
0.5
0.8
1.0
0.9
1.0
m
1.1
0.7
0.2
0.9
1.0
1.0
0.9
c
c
0.8
m
0.5
c
0.8
0.9
0.9
0.6
0.6
0.9
1.0
0.9
1.0
0.3
1.2
1.2

m
8
5
m
m
4
13
7
8
5
6
10
3
18
4
m
5
m
5
1
13
m
7
m
10
2
7
3
4
6
10
7
2
7
m

m
0.2
0.2
m
m
0.1
0.5
0.3
0.3
0.3
0.2
0.4
0.3
0.5
0.3
m
0.4
m
0.5
0.3
0.5
m
0.3
m
0.5
0.2
0.4
0.3
0.3
0.4
0.3
m
m
0.4
m

m
42
33
m
m
31
58
37
46
35
39
25
25
58
30
m
31
m
m
24
63
m
43
m
55
21
35
31
33
39
34
m
18
45
m

m
0.7
0.8
m
m
0.9
0.9
1.0
0.9
0.9
0.8
0.9
0.9
1.0
0.9
m
0.8
m
m
1.2
0.9
m
0.8
m
0.9
0.9
0.9
1.0
1.1
0.9
1.0
m
m
0.9
m

m
59
58
m
m
56
71
58
66
62
60
47
54
74
37
m
43
m
48
56
75
m
63
m
61
43
45
57
49
53
63
m
26
52
m

m
0.8
0.9
m
m
0.9
0.9
0.8
0.9
0.9
0.8
0.8
0.9
0.9
0.9
m
0.8
m
0.8
0.9
0.8
m
0.9
m
0.9
0.8
0.8
0.9
1.0
0.9
0.9
m
m
0.9
m

80
85
m
77
38
87
86
86
87
72
81
71
m
m
75
68
68
92
81
m
m
m
86
81
85
77
m
86
74
69
85
m
49
m
70

0.7
0.7
m
0.5
2.6
0.8
0.6
0.5
0.5
0.6
0.7
1.1
m
m
0.9
0.8
1.0
0.6
0.6
m
m
m
0.6
0.7
0.6
0.7
m
0.6
0.8
0.7
0.7
m
1.6
m
0.9

0.9
1.0
m
0.9
0.7
1.0
1.0
1.0
1.0
0.9
0.9
0.9
m
m
0.9
0.9
0.9
1.0
0.9
m
m
m
0.9
0.9
1.0
1.0
m
1.0
1.0
0.9
0.9
m
0.7
m
0.9

0.8
0.9
m
0.8
0.5
0.9
0.9
0.9
0.9
0.7
0.8
0.8
m
m
0.8
0.7
0.8
0.9
0.8
m
m
m
0.9
0.8
0.9
0.8
m
0.9
0.7
0.7
0.9
m
0.6
m
0.7

OECD average
EU22 average

77
79

~
~

1.0
1.0

0.7
0.7

0.8
0.8

7
6

0.3
0.3

37
36

0.9
0.9

55
56

0.9
0.9

77
80

~
~

0.9
1.0

0.8
0.8

Argentina6
Brazil
China
Colombia
Costa Rica
India
Indonesia
Lithuania
Russian Federation
Saudi Arabia
South Africa

44
30
m
34
38
m
31
75
81
m
m

1.7
1.2
m
1.2
1.5
m
1.6
1.1
1.2
m
m

0.8
0.8
m
0.8
0.8
m
1.1
1.0
1.0
m
m

0.5
0.3
m
0.3
0.4
m
0.3
0.7
0.8
m
m

0.7
0.4
m
0.7
1.1
m
0.3
0.8
0.9
m
m

m
6
m
m
m
m
m
4
1
m
m

m
0.6
m
m
m
m
m
0.3
0.3
m
m

m
12
m
m
m
m
m
32
8
m
m

m
0.9
m
m
m
m
m
1.0
1.2
m
m

m
21
m
m
m
m
m
55
28
m
m

m
0.8
m
m
m
m
m
0.9
0.9
m
m

m
m
m
m
m
m
m
82
86
m
m

m
m
m
m
m
m
m
0.8
1.5
m
m

m
m
m
m
m
m
m
1.0
1.0
m
m

m
m
m
m
m
m
m
0.8
1.0
m
m

G20 average

m

~

m

m

m

m

m

m

m

m

m

m

~

m

m

1. For indicators 4.1.1 and 4.6.1, parity indices are in bold when the difference between the two considered groups is statistically significant.
2. The gender parity index refers to the ratio of the female value over the male value.
3. ESCS refers to the PISA index of economic, social and cultural status. The ESCS parity index refers to the ratio of the value for the bottom quartile over the value
for the top quartile of the ESCS index.
4. The location parity index refers to the ratio of the value for rural areas over the value for urban areas.
5. The parental attainment parity index refers to the ratio of the value for individuals whose parents have not attained tertiary education over the value for those
with at least one tertiary-educated parent.
6. For PISA results, coverage is too small to ensure comparability.
c: There are too few observations or no observation to provide reliable estimates (i.e. there are fewer than 30 students or fewer than 5 schools with valid data).
Source: PISA (2015), ITU (2015) and PIAAC (2012/2015). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933801468

Education at a Glance 2018: OECD Indicators   © OECD 2018

39

Under embargo until 11/09/2018 at 11.00am CEST

Under embargo until 11/09/2018 at 11.00am CEST

Chapter

A

The Output of
Educational Institutions
and the Impact of Learning

Indicator A1 To what level have adults studied?
1 2 https://doi.org/10.1787/888933801582

Indicator A2 Transition from education to work: Where are today’s youth?
1 2 https://doi.org/10.1787/888933801772

Indicator A3 How does educational attainment affect participation in the labour market?
1 2 https://doi.org/10.1787/888933801962

Indicator A4 What are the earnings advantages from education?
1 2 https://doi.org/10.1787/888933802171

Indicator A5 What are the financial incentives to invest in education?
1 2 https://doi.org/10.1787/888933802361

Indicator A6 How are social outcomes related to education?
1 2 https://doi.org/10.1787/888933802608

Indicator A7 To what extent do adults participate equally in education and learning?
1 2 https://doi.org/10.1787/888933802798

Education at a Glance 2018: OECD Indicators   © OECD 2018

41

Under embargo until 11/09/2018 at 11.00am CEST

INDICATOR A1

TO WHAT LEVEL HAVE ADULTS STUDIED?
• In most countries, less than 20% of younger adults (age 25-34) have not completed upper secondary
education. Gender differences are small in most countries, but the difference between men and
women is over 10 percentage points in India, Portugal and Spain. More women than men do not
have upper secondary education in India, while more men than women are in this situation in
Portugal and Spain.

• On average across OECD countries, 50% of women age 25-34 are tertiary-educated, compared to
38% of men.

• Among 25-34 year-olds in most OECD countries, the majority of those who attained bachelor’s or
master’s degrees are women, but 51% of those who attained a doctorate or equivalent degree are men.

Figure A1.1. Percentage of 25-34 year-olds without upper secondary education,
by gender (2017)
Men

%

Women

70
60
50
40
30
20

0

China1
India1
Costa Rica
Mexico
Indonesia
Turkey
Brazil1
Spain
Portugal
Argentina
Colombia
Saudi Arabia1
Italy
Iceland
Norway
South Africa
Denmark
Latvia
Sweden
Belgium
Chile1
OECD average
Greece
EU22 average
Estonia
New Zealand
Netherlands
France
Luxembourg
Hungary
Germany
United Kingdom
Australia
Austria
Finland
Ireland
Lithuania
Israel
United States
Switzerland
Slovak Republic
Canada
Russian Federation1
Slovenia
Poland
Czech Republic
Korea

10

1. Year of reference differs from 2017. Refer to the source table for more details.
Countries are ranked in descending order of the total percentage of 25-34 year-old men without upper secondary education.
Source: OECD (2018), Table A1.2. See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/
eag-2018-36-en).
1 2 https://doi.org/10.1787/888933801658

Context
Giving everyone a fair chance to obtain a quality education is a fundamental part of the social contract.
To improve social mobility and socio-economic outcomes, it is critically important to eliminate
inequalities in educational opportunities. This will promote inclusive growth by broadening the pool
of candidates for high-skilled jobs.
Educational attainment is measured as the percentage of the population that has reached a certain
level of education and holds a formal qualification at that level. It is frequently used as a proxy
measure of human capital and the level of an individual’s skills (i.e. a measure of the skills associated
with a given level of education and available in the population and the labour force). In this sense,
qualifications certify and offer information on the type of knowledge and skills that graduates have
acquired in formal education.

42

Education at a Glance 2018: OECD Indicators   © OECD 2018

Under embargo until 11/09/2018 at 11.00am CEST
Higher levels of educational attainment are associated with several positive economic and social
outcomes for individuals (see Indicators A3, A4, A5 and A6). Highly educated individuals are more
socially engaged and have higher employment rates and higher relative earnings. Higher proficiency
in literacy and numeracy is also strongly associated with higher levels of formal education
(OECD, 2016[1]).

INDICATOR A1

Individuals thus have incentives to pursue more education, and governments have incentives to
provide appropriate infrastructure and organisation to support the expansion of higher educational
attainment across the population. Over past decades, almost all OECD countries have seen significant
increases in educational attainment, especially among the young and among women.
According to the International Migration Outlook 2017 (OECD, 2017[2]), 13% of the total population in
OECD countries are foreign-born. The size and the characteristics of this group vary across countries,
and it is important to analyse these elements to better understand the composition of a country’s
population. It is also important to consider how a country’s geographic location or proximity to
other countries affects the demographics of the country’s foreign-born population. According to the
OECD Demography and Population database, for example, in almost all European OECD countries,
most immigrants are from Europe (OECD, 2018[3]). Educational attainment of the native-born and
foreign‑born population should also inform policies related to human capital within these two groups.
In some cases, similarities or divergences between the two groups can signal the need for formal
and/ or non-formal adult education programmes (see Indicator A7).
Other findings

• The expansion of tertiary education has largely been to the advantage of women. Among
55‑64 year-olds, there is a perfect gender balance in the percentage of men and women who are
tertiary-educated on average across OECD countries. However, among the younger generation
(age 25-34), a larger share of women than men are attaining tertiary education.

• The share of young men with vocationally oriented upper secondary or post-secondary non‑tertiary
education is higher than that of young women, but the share of young men and women who
completed general programmes as the highest educational level is about the same.

• There are no clear patterns in the distribution of educational attainment among the native-born
and foreign-born population across OECD countries. For instance, in Australia, Canada, Ireland,
Israel and Poland, the percentage of tertiary-educated foreign-born adults is highest, at over 50%.
In contrast, in Costa Rica and Italy, over 45% of foreign-born adults have not completed upper
secondary education.

Education at a Glance 2018: OECD Indicators   © OECD 2018

43

chapter A The Output of Educational Institutions and the Impact of Learning
Under embargo until 11/09/2018 at 11.00am CEST

A1

Analysis
Below upper secondary education
In most OECD countries, the large majority of younger adults (age 25-34) had at least an upper secondary
qualification in 2017. In just a few decades, upper secondary schooling has been transformed from a vehicle for
upward social mobility into a minimum requirement for life in modern society. Young people who leave school before
completing upper secondary education not only face difficulties in the labour market, but also have particularly
low cognitive skills compared with upper secondary graduates. Those who leave school before completing upper
secondary education are twice as likely to have low numeracy skills as those with an upper secondary education
(OECD, 2015[4]).
The percentage of younger adults with below upper secondary education has fallen between 2007 and 2017. Across
OECD countries, the share decreased from 20% in 2007 to 15% in 2017. Despite this progress, several countries
are still lagging behind and have a high proportion of young adults without upper secondary education. While the
share of young adults without upper secondary education is lower than 10% among 25-34 year-olds in Canada,
the Czech Republic, Ireland, Israel, Korea, Lithuania, Poland, the Russian Federation, the Slovak Republic, Slovenia,
Switzerland and the United States, it is 50% or more in China, Costa Rica, India, Indonesia and Mexico. In Korea,
only 2% of men and women age 25-34 did not complete upper secondary education, the lowest share across OECD
and partner countries for both genders (Table A1.2).
In most countries, there is a higher percentage of young men than young women without an upper secondary
qualification. Gender disparities are generally larger in countries where the percentage of young adults without
upper secondary education is high. For example, the gender gap is above 5 percentage points in about one-quarter of
OECD and partner countries: Argentina, Brazil, Colombia, Costa Rica, Denmark, Estonia, Iceland, India, Italy, Latvia,
Portugal, South Africa and Spain. With the exception of Estonia and Latvia, in all these countries, the percentage
of young adults without upper secondary education is above the OECD average of 15%. In India, Portugal and
Spain, the gap is above 10 percentage points, the largest gender gap among OECD and partner countries. One
exception is Mexico, where the share of young men and young women without upper secondary education is high
but similar (52% for both). Other countries with similar shares for young men and women without upper secondary
education are Austria, Chile, the Czech Republic, Germany, Hungary, Korea, the Slovak Republic, Switzerland and
the United Kingdom (Table A1.2).
Upper secondary or post-secondary non-tertiary education
Despite the expansion of tertiary education, upper secondary education is still the most commonly attained
level of education among 25-64 year-olds in 17 OECD countries. However, it represents the largest share among
25‑34 year‑olds in 14 OECD countries. On average across OECD countries, the share of people with upper secondary
or post-secondary non-tertiary education among 25-34 year-olds is 41%. Across OECD and partner countries, it
ranges from as low as 18% in China to as high as 76% in South Africa (Table A1.2 and [OECD, 2018[5]]).
Upper secondary education across OECD countries is mainly divided into two types of programmes. Programmes
defined as “general” are often designed to prepare students for further education, and those defined as “vocational
education and training” (VET) are designed to lead directly to the labour market. Within upper secondary education
or post-secondary non-tertiary education, more adults completed vocational programmes than general programmes
as their highest educational attainment across countries. On average across OECD countries, 24% of 25-34 year‑olds
completed a vocational programme and 18% completed a general programme as their highest education level.
The lower share for general programmes can be explained by the fact that these programmes are usually designed
to prepare students for further education, and those who acquire this qualification often continue to tertiary
education. The prevalence of vocational programmes differs across countries. While the share of 25-34 year-olds
with vocational programmes is as low as 2% in Costa Rica and Mexico, followed by 3% in Israel, elsewhere it is much
more significant: about 50% in Germany and the Slovak Republic (OECD, 2018[5]).
A gender difference is also observed among 25-34 year-olds with upper secondary or post-secondary non-tertiary
education. Across OECD countries, on average, 46% of young men have this level of education as their highest
attainment, while the share is lower among young women (37%). The share of young men with vocationally oriented
upper secondary or post-secondary non-tertiary education (28%) as their highest level of education is higher than
that of young women (21%), but the share of young men (19%) and young women (17%) who completed general
programmes is about the same (Table A1.2 and [OECD, 2018[5]]).

44

Education at a Glance 2018: OECD Indicators   © OECD 2018

To what level have adults studied? – INDICATOR A1

chapter A

Under embargo until 11/09/2018 at 11.00am CEST

A1

Box A1.1. Programme orientation and intergenerational mobility in education
Education is often seen as a tool to level inequalities. But educational attainment often persists from one
generation to the next, and it can also perpetuate inequalities. To facilitate social inclusion and improve socioeconomic outcomes, now and for future generations, countries need to offer all young people a fair chance to
obtain a quality education.
Growing up in a family where the parents have low levels of education often means having less financial
support available for continuing studies. This situation is worsened if the education system does not provide
support for students from disadvantaged backgrounds. In the short term, staying in education can involve
foregoing earnings from employment. In such cases, those from disadvantaged backgrounds cannot incur the
opportunity cost and thus leave education earlier.
To examine these issues, this box draws on data from the Survey of Adult Skills (PIAAC) (see Source section
at the end of this indicator), on the educational attainment of the 25-64 year-olds relative to their parents’
educational attainment (see Definitions and Source section at the end of this indicator). These data include the
disaggregation by programme orientation (general/vocational) for adults whose highest level of education is
upper secondary or post-secondary non-tertiary education, which complements analyses on intergenerational
mobility in education published in earlier editions of Education at a Glance (OECD, 2014[6]; OECD, 2015[7];
OECD, 2016[1]; OECD, 2017[8]).
England (United Kingdom), the Flemish Community of Belgium, Italy, Northern Ireland (United Kingdom),
Sweden, Turkey and the United States have been excluded from the analysis, because information on the
disaggregation between general and vocational orientation is missing for over 10% of 25-64 year-olds with
upper secondary or post-secondary non-tertiary education (Table A1.a, available on line).
Educational attainment of 25-64 year-olds whose parents have not attained upper secondary
education
Figure A1.a shows that, on average across OECD countries and economies that participated in the Survey
of Adult Skills (PIAAC), 43% of 25-64 year-olds have parents who did not complete upper secondary
education. Among those adults, 36% achieved the same low level of educational attainment, meaning
that 64% succeeded in completing a higher level of education than their parents. The breakdown of this
upward mobility in education is as follows: 14% of 25-64 year-olds whose parents who did not complete
upper secondary education attained upper secondary or post-secondary non-tertiary general education;
30% attained upper secondary or post-secondary non-tertiary vocational education; and 20% attained
tertiary education. This means that, in most countries, upper secondary or post-secondary non-tertiary
vocational education is the prominent programme for upward mobility in education for 25-64 year-olds with
parents who did not complete upper secondary education (Figure A1.a and Table A1.b, available on line).
In eight countries, upward mobility to general programmes is higher than upward mobility to vocational
programmes, with a statistically significant difference. This is the case for Japan, where 37% of 25‑64 year‑olds
with parents who did not complete upper secondary education attained upper secondary or post-secondary
non-tertiary general education themselves, the largest share among these countries. In contrast, in 15 countries,
upward mobility to upper secondary or post-secondary non-tertiary vocational education is higher than upward
mobility to general programmes. The highest shares are observed in the Czech Republic and Poland, where more
than 65% of 25-64 year-olds with parents who did not complete upper secondary education are attaining these
programmes (Figure A1.a).
Educational attainment of 25-64 year-olds who have at least one parent who attained tertiary
education
The educational attainment distribution of 25-64 year-olds who have at least one parent who attained tertiary
education (22% on average) is radically different from that of adults with parents who did not complete upper
secondary education. Among adults who have at least one parent who attained tertiary education, only 5% did
not complete upper secondary education, 13% attained upper secondary or post-secondary non-tertiary
general education, 16% attained upper secondary or post-secondary non-tertiary vocational education, and
66% attained tertiary education (Figure A1.b and Table A1.a, available on line).

…

Education at a Glance 2018: OECD Indicators   © OECD 2018

45

chapter A The Output of Educational Institutions and the Impact of Learning
Under embargo until 11/09/2018 at 11.00am CEST

Figure A1.a. Educational attainment of 25-64 year-olds whose parents have not attained
an upper secondary education (2012 or 2015)
Survey of Adult Skills (PIAAC)

Lithuania1 (41%)

Russian Federation* (30%)

Estonia (30%)

Finland (46%)

Poland (33%)

Japan (27%)

Canada (29%)

Israel1 (34%)

Czech Republic (12%)

Korea (60%)

Germany (12%)

New Zealand1 (40%)

Denmark (34%)

Norway (31%)

OECD average (43%)

Australia (49%)

France (52%)

Austria (31%)

Slovak Republic (32%)

Ireland (56%)

Netherlands (54%)

Greece1 (69%)

Chile1 (50%)

%

100
90
80
70
60
50
40
30
20
10
0

Slovenia1 (38%)

Tertiary
Upper secondary or post-secondary non-tertiary – general orientation
Upper secondary or post-secondary non-tertiary – vocational orientation
Below upper secondary

Spain (75%)

A1

Note: The percentage in parentheses represents the share of 25-64 year-olds whose parents have below upper secondary education. Countries
where more than 10% of the 25-64 year-olds with upper secondary or post-secondary non-tertiary education could not be distinguished
between general and vocational orientation have been excluded. The values for the average were redistributed to add up to 100%. Data from
the Survey of Adult Skills (PIAAC) are based on ISCED-97. See Definitions, Methodology and Source sections for more information.
1. Reference year is 2015; for all other countries and economies the reference year is 2012.
* See note on data for the Russian Federation in the Source section.
Countries are ranked in descending order of the percentage of 25-64 year-olds with below upper secondary education.
Source: OECD (2018), Tables A1.a and A1.b, available on line. See Source section for more information and Annex 3 for notes (http://dx.doi.
org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933801734

Most people with at least one tertiary-educated parent achieve at least an upper secondary education,
considered to be the minimum threshold for successful labour market entry and continued employability.
Children of tertiary-educated parents have higher probabilities of attaining tertiary education and greater
opportunities to reach the level of education they aspire to. However, this does not mean that all children
of tertiary-educated parents will also attain tertiary education. For instance, in Austria, the Czech Republic,
Germany and Slovenia, at least 35% of 25-64 year-olds with at least one tertiary-educated parent have
upper secondary or post-secondary non-tertiary vocational education as their highest level of education
(Figure A1.b). Indicator A3 shows that young adults who attained vocational programmes in these four
countries have labour-market outcomes that are similar to or even better than those of tertiary-educated
young adults. Therefore attaining upper secondary or post-secondary non-tertiary vocational education
can be a deliberate choice and may not represent a second-chance programme for those who did not attain
tertiary education in some countries.
However, in most countries, the share of 25-64 year-olds with upper secondary or post-secondary vocational
education is lower among those with highly educated parents than among those with parents who did not
complete upper secondary education. In some countries, the difference is very large. In the Slovak Republic,
for example, 36% of adults with parents who did not complete upper secondary education attained upper
secondary or post-secondary vocational education themselves, while only 8% attained at most this level of
education among those with tertiary-educated parents. This shows that, in a large majority of cases, having
tertiary-educated parents leads to high educational attainment (Figures A1.a and A1.b).

…

46

Education at a Glance 2018: OECD Indicators   © OECD 2018

To what level have adults studied? – INDICATOR A1

chapter A

Under embargo until 11/09/2018 at 11.00am CEST

A1

Figure A1.b. Educational attainment of 25-64 year-olds who have at least one parent
who attained tertiary education (2012 or 2015)
Survey of Adult Skills (PIAAC)

Austria (18%)

Lithuania1 (39%)

Czech Republic (13%)

Germany (32%)

Slovenia1 (16%)

Estonia (32%)

Norway (31%)

Netherlands (21%)

Finland (16%)

Slovak Republic (11%)

Greece1 (11%)

OECD average (22%)

Australia (28%)

Chile1 (19%)

Denmark (29%)

New Zealand1 (37%)

Ireland (18%)

Spain (11%)

Canada (35%)

France (16%)

Israel1 (40%)

Korea (14%)

Japan (30%)

Russian Federation * (26%)

%

100
90
80
70
60
50
40
30
20
10
0

Poland (12%)

Tertiary
Upper secondary or post-secondary non-tertiary – general orientation
Upper secondary or post-secondary non-tertiary – vocational orientation
Below upper secondary

Note: The percentage in parentheses represents the share of 25-64 year-olds who have at least one parent who attained tertiary education.
Countries where more than 10% of the 25-64 year-olds with upper secondary or post-secondary non-tertiary education could not be
distinguished between general and vocational orientation have been excluded. The values for the average were redistributed to add up to 100%.
Data from the Survey of Adult Skills (PIAAC) are based on ISCED-97. See Definitions, Methodology and Source sections for more information.
1. Reference year is 2015; for all other countries and economies the reference year is 2012.
* See note on data for the Russian Federation in the Source section.
Countries are ranked in descending order of the percentage of tertiary-educated 25-64 year-olds.
Source: OECD (2018), Tables A1.a and A1.b, available on line. See Source section for more information and Annex 3 for notes (http://dx.doi.
org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933801753

Box A1.1 Tables

WEB Table A.1a

Adults’ educational attainment, by programme orientation, and their parents’
educational attainment (2012 or 2015)

WEB Table A.1b

Adults’ educational attainment broken down by programme orientation and parents’
educational attainment (2012 or 2015)

Tertiary education
Tertiary education has expanded significantly over recent decades, and people with tertiary education now account
for the largest share of 25-34 year-olds in many OECD countries. On average across OECD countries, 36% of adults
age 25-64 are tertiary-educated. As a result of the expansion of tertiary education, the share of younger adults
(age 25-34) with tertiary education is 44% on average across OECD countries, much higher than the share of
55‑64 year-olds (27%) (Tables A1.2, A1.3 and [OECD, 2018[5]]).
The proportion of 25-34 year-olds with tertiary education is at least 60% in Canada and Korea. But it is below 15% in
India and South Africa, where the dominant share of adults have below upper secondary education (Figure A1.2).
In most OECD and partner countries, those with a bachelor’s or equivalent degree account for the largest share
of tertiary-educated 25-34 year-olds. But in some countries, such as Austria and China, those with a short-cycle
tertiary degree represent the largest share of tertiary-educated 25-34 year-olds. In the Czech Republic, France,
Italy, Luxembourg, Poland, Portugal, the Russian Federation, the Slovak Republic, Slovenia and Spain, those with a
master’s or equivalent degree account for the largest share (Figure A1.2).
Education at a Glance 2018: OECD Indicators   © OECD 2018

47

chapter A The Output of Educational Institutions and the Impact of Learning
Under embargo until 11/09/2018 at 11.00am CEST

Figure A1.2. Percentage of 25-34 year-olds with tertiary education,
by level of tertiary education (2017)

A1

Short-cycle tertiary
Bachelor or equivalent
Master's or equivalent
Doctoral or equivalent

Korea
Canada
Japan
Russian Federation1
Lithuania
Ireland
Australia
United Kingdom
Luxembourg
Switzerland
Norway
Israel
United States
Iceland
Sweden
Netherlands
Denmark
Belgium
Slovenia
France
New Zealand
OECD average
Poland
Estonia
Spain
Greece
EU22 average
Latvia
Finland
Austria
Slovak Republic
Czech Republic
Portugal
Turkey
Germany
Hungary
Chile1
Colombia
Costa Rica
Italy
Saudi Arabia1
Mexico
Argentina
China1
Brazil1
Indonesia
India1
South Africa

%

80
70
60
50
40
30
20
10
0

Note: Some categories might be included in other categories. Please refer to Table A1.1 for details.
1. Year of reference differs from 2017. Refer to Table A1.1 for more details.
Countries are ranked in descending order of the percentage of tertiary-educated 25-34 year-olds.
Source: OECD (2018), Education at a Glance Database, http://stats.oecd.org/. See Source section for more information and Annex 3 for notes
(http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933801677

The expansion of tertiary education has largely been to the advantage of women. Among 55-64 year-olds, there is
a perfect gender balance on average across OECD countries, where the share of tertiary-educated 55-64 year‑olds
is even among both genders (27%). Among the younger generation (age 25-34) a larger share of women than men
have a tertiary degree. On average across OECD countries, 50% of women age 25-34 are tertiary-educated, while the
proportion is 38% for men. In Korea and Saudi Arabia, the change in the gender composition has been the largest,
going from a gap of 16 percentage points in favour of men among 55-64 year-olds to a gap of about 10 percentage
points in favour of women among 25-34 year-olds. In Korea, the share of tertiary-educated women rose from
14% among 55-64 year-olds to 75% among 25-34 year-olds, while for men it went from 29% to 65%. This expansion
of tertiary education is very large for both genders, but larger for women. In the case of Saudi Arabia, 22% of men
are tertiary-educated in the two age groups, while the share of women increased from 5% among 55-64 year-olds
to 31% among 25-34 year-olds (Table A1.2 and [OECD, 2018[5]]).
Gender balance reverses with higher levels within the tertiary level. Women make up the majority of 25-34 year‑olds
who attained a bachelor’s degree in 30 OECD countries. Among 25-34 year-olds who attained a master’s degree, the
number of countries where women form the majority rises to 33. Among OECD countries with data on those who
attained a doctorate or equivalent degree, women make up more than 50% in only 11 countries.

Educational attainment of native-born and foreign-born adults
The educational attainment levels of native-born and foreign-born adults vary widely across OECD countries. In
some countries, the share of adults with tertiary education is higher among native-born adults than among foreignborn adults, while the opposite situation is observed in some other countries. Age at arrival in the country also
has different associations across OECD countries. In some countries, the share of adults with tertiary education is
higher among those who arrived in the country by age 15, while in other countries the share is higher among those
who arrived after age 15. In other words, no clear patterns emerge across OECD countries in tertiary educational
attainment among native-born and foreign-born adults.
The only element that shows some consistency across OECD countries is that the share of tertiary-educated adults
among native-born and foreign-born adults tends to follow the overall country pattern. In Canada, for example, the
share of tertiary-educated adults is high among native-born adults (53%), and it is even higher among foreign-born

48

Education at a Glance 2018: OECD Indicators   © OECD 2018

To what level have adults studied? – INDICATOR A1

chapter A

Under embargo until 11/09/2018 at 11.00am CEST
adults (67%), regardless of their age at arrival in the country. In Italy, the opposite situation is observed. The share
of tertiary-educated adults is generally low, regardless of whether they are native-born (20%) or foreign-born (14%)
and regardless of their age at arrival in the country (Figure A1.3).
In Denmark, Estonia, Lithuania and the Slovak Republic, the difference in the share of tertiary-educated people who
arrived by the age of 15 and those who arrived later is higher than 15 percentage points (Figure A1.3).

Figure A1.3. Percentage of tertiary-educated native- and foreign-born 25-64 year-olds,
by age at arrival in the country (2017)
Native-born adults

(0%)
Mexico

(3%)

Italy (14%)

Chile

(1%)

1

Portugal (10%)

(4%)
Czech Republic

Slovak Republic

(2%)
Hungary

Costa Rica (11%)

Germany (21%)

Luxembourg (57%)

(1%)
Poland

New Zealand (33%)

(9%)
Greece

Austria (24%)

EU22 average (15%)

Latvia (11%)

France (15%)

Slovenia (12%)

Spain (16%)

Denmark (14%)

Netherlands (15%)

Estonia (12%)

Australia (34%)

(5%)

Sweden (24%)

Lithuania

Belgium (21%)

Ireland (22%)

Switzerland (36%)

Israel (25%)

United States (19%)

Canada (28%)

%

70
60
50
40
30
20
10
0

OECD average (17%)

Foreign-born adults
Arrived in the country by the age of 15
Arrived in the country at 16 or older
Age at arrival unknown

Note: The percentage in parentheses represents the share of foreign-born adults among 25-64 year-olds.
1. Year of reference differs from 2017. Refer to the source table for more details.
Countries are ranked in descending order of the percentage of tertiary-educated native-born adults.
Source: OECD (2018), Table A1.3. See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933801696

Evidence from the OECD Programme for International Student Assessment (PISA) shows that reading proficiency at
age 15 does not vary significantly between those who arrived before age 5 and those who arrived between age 6 and
age 11. However, immigrant students who arrived at age 12 or older have lower results than 15-year-old immigrant
students in the same grade who arrived before age 12 (OECD, 2015[9]). Students who arrive at a later age can face the
increased difficulty of learning a new language and/or a different culture. Moreover, as they have already completed
several years of schooling in their home country, it might be challenging to adapt and perform in their new school
system.
This may partly explain the differences in the share of tertiary-educated foreign-born adults in Denmark, Estonia,
Lithuania and the Slovak Republic between those who arrived by the age of 15 and those who arrived after that.
However, in some other countries, the share of tertiary-educated adults is higher among those who arrived at
age 16 or older (Figure A1.3). The explanations for these differences can be diverse. For example, as tertiary
qualification is obtained after age 16, it is not possible to know if the qualification was obtained in the host
country or in the country of origin, and this may vary across countries. The 25-64 age group is also large enough
to include different waves of migration, with significant variation in individual characteristics and educational
attainment.
Regardless of the age at arrival in the country, it is important for countries to know the general human capital of
their foreign-born population. Figure A1.4 shows the diversity in the distribution of educational attainment among
the foreign-born population across OECD countries. In Australia and Canada, two countries with about 30% of
foreign-born adults, the percentage of tertiary-educated foreign-born adults is among the highest, at over 50%.
These two countries also have a large share of tertiary-educated adults: 45% in Australia and 57% in Canada.
Education at a Glance 2018: OECD Indicators   © OECD 2018

49

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chapter A The Output of Educational Institutions and the Impact of Learning
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In addition, these countries have selective migration policies designed to attract highly educated and skilled
migrants. In contrast, in Costa Rica (with 11% of foreign-born adults) and Italy (with 14%), around 50% or more
of foreign-born adults have not completed upper secondary education. And these two countries have a low share of
tertiary-educated adults: 23% in Costa Rica and 19% in Italy (Table A1.3).
A common characteristic is that, regardless of their educational attainment, foreign-born adults perform lower in
literacy than native-born adults. Data from the Survey of Adult Skills (PIAAC) shows that the mean literacy score
for migrants was 248 points, compared to 276 points for natives, a gap equivalent to about four years of schooling
(OECD/EU, 2015[10]).

Figure A1.4. Educational attainment of foreign-born 25-64 year-olds (2017)
Percentage of adults with a given level of education as the highest level attained

Costa Rica (11%)

(9%)

Italy (14%)

Greece

Slovenia (12%)

Germany (21%)

(1%)
Slovak Republic

Spain (16%)

(2%)
Hungary

Netherlands (15%)

France (15%)

(3%)
Chile1

Austria (24%)

(4%)
Czech Republic

Latvia (11%)

Portugal (10%)

Belgium (21%)

EU22 average (15%)

(5%)
Lithuania

OECD average (17%)

Luxembourg (57%)

United States (19%)

Switzerland (36%)

Sweden (24%)

Denmark (14%)

(0%)
Mexico

New Zealand (33%)

(1%)
Poland

Ireland (22%)

Israel (25%)

Australia (34%)

%

100
90
80
70
60
50
40
30
20
10
0

Estonia (12%)

Below upper secondary
Upper secondary or post-secondary non-tertiary
Tertiary

Canada (28%)

A1

Note: The percentage in parentheses represents the share of foreign-born adults among 25-64 year-olds.
1. Year of reference differs from 2017. Refer to the source table for more details.
Countries are ranked in descending order of the percentage of tertiary-educated foreign-born adults.
Source: OECD (2018), Table A1.3. See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933801715

Subnational variations in educational attainment levels
On average across OECD countries, about 15% of younger adults (age 25-34) have below upper secondary
education as their highest level of educational attainment, but there are significant subnational variations within
countries. In 13 of the 19 OECD and partner countries that reported subnational data on educational attainment,
the share of 25‑34 year‑olds with this level of educational attainment in the subnational region with the highest
share is over twice as large as in the subnational region with the lowest share. When dividing the highest by
the lowest shares within countries, the ratio is above six only in Canada and the Russian Federation, two large
countries with many subnational regions. For example, in one region of Canada, 41% of 25-34 year-olds are
without an upper secondary education, while in another region the share is only 5%. In contrast, across the OECD
and partner countries that reported subnational data, the difference is the smallest in Ireland and Slovenia, two
countries with only a few subnational regions: in Ireland, 10% in the region with the highest share and 8% in the
region with the lowest share, and in Slovenia, 6% in the region with the highest share and 5% in the region with
the lowest share (OECD/NCES, 2018[11]).
In general, less regional variation is observed in the relative share of 25-34 year-olds with upper secondary
or post‑secondary non-tertiary education. Among countries with data, the Russian Federation, Switzerland,
Turkey and the United States are the only countries in which the percentage of those with upper secondary or
post‑secondary non-tertiary education in the subnational region with the highest share is more than twice as
large as in the subnational region with the lowest share (OECD/NCES, 2018[11]).

50

Education at a Glance 2018: OECD Indicators   © OECD 2018

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chapter A

Under embargo until 11/09/2018 at 11.00am CEST
As for tertiary education, Brazil, Canada, Germany, the Russian Federation, Turkey and the United States are the
countries in which the percentage of 25-34 year-olds with this level of educational attainment is over twice as large
in the subnational region with the highest share as in the subnational region with the lowest share. By contrast,
Ireland and Slovenia are again the two countries showing the lowest within-country variation (OECD/NCES,
2018[11]).

Definitions
Age groups: Adults refer to 25-64 year-olds; younger adults refer to 25-34 year-olds; and older adults refer to
55‑64 year-olds.
Completion of intermediate programmes for educational attainment (ISCED 2011) corresponds to a recognised
qualification from an ISCED 2011 level programme that is not considered sufficient for ISCED 2011 level completion
and is classified at a lower ISCED 2011 level. In addition, this recognised qualification does not give direct access to
an upper ISCED 2011 level programme.
Educational attainment refers to the highest level of education reached by a person.
Levels of education: See the Reader’s Guide at the beginning of this publication for a presentation of all ISCED 2011
levels.
The previous classification, ISCED-97, is used for the analyses based on the Survey of Adult Skills (PIAAC) in
Box A1.1. The levels of education are defined as follows: below upper secondary corresponds to levels 0, 1, 2 and 3C
short programmes; upper secondary or post-secondary non-tertiary general corresponds to levels 3A, 3B, 3C
long programmes and level 4 that are identified with a general orientation; upper secondary or post-secondary
non-tertiary vocational corresponds to levels 3A, 3B, 3C long programmes and level 4 that are identified with a
vocational orientation; and tertiary corresponds to levels 5B, 5A and 6. The variable Area of study (B_Q01b) was
used instead of the variable VET to distinguish between general programmes (general programmes and humanities,
languages and arts) and vocational programmes (teacher training and education science; social sciences, business
and law; science, mathematics and computing; engineering, manufacturing and construction; agriculture and
veterinary; health and welfare; and services) at level 4.
Vocational programmes: The International Standard Classification of Education (ISCED 2011) defines
vocational programmes as education programmes that are designed for learners to acquire the knowledge, skills
and competencies specific to a particular occupation, trade, or class of occupations or trades. Such programmes
may have work-based components (e.g. apprenticeships and dual-system education programmes). Successful
completion of such programmes leads to vocational qualifications relevant to the labour market and acknowledged
as occupationally oriented by the relevant national authorities and/or the labour market.

Methodology
Educational attainment profiles are based on annual data on the percentage of the adult population (25-64 year-olds)
in a specific age group that has successfully completed a specified level of education.
In OECD statistics, recognised qualifications from ISCED 2011 level 3 programmes that are not of sufficient
duration for ISCED 2011 level 3 completion are classified at ISCED 2011 level 2 (see the Reader’s Guide). Where
countries have been able to demonstrate equivalencies in the labour market value of attainment formally classified
as “completion of intermediate upper secondary programmes” (e.g. achieving five good GCSEs or equivalent in
the United Kingdom) and “full upper secondary attainment”, attainment of these programmes is reported as
ISCED 2011 level 3 completion in the tables that show three aggregate levels of educational attainment (UNESCO
Institute for Statistics, 2012 [12]).
Countries have defined general or vocational orientation based on the features of the education programme and the
resulting credentials and qualifications. Some countries may also use variables based on students’ choice of field of
study and students’ destinations after their studies, because such variables also reflect the distribution of students
in general and vocational programmes.
Most OECD countries include people without formal education under the international classification ISCED 2011
level 0. Therefore averages for the category “less than primary educational attainment” are likely to be influenced
by this inclusion.
Education at a Glance 2018: OECD Indicators   © OECD 2018

51

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chapter A The Output of Educational Institutions and the Impact of Learning
Under embargo until 11/09/2018 at 11.00am CEST

A1

Please see the OECD Handbook for Internationally Comparative Education Statistics 2018 (OECD, 2018[13]) for more
information and Annex 3 for country-specific notes (http://dx.doi.org/10.1787/eag-2018-36-en).
For the methodology used in Box A1.1, please see the Methodology section in Indicator A7.
Lithuania was not an OECD member at the time of preparation of this publication. Accordingly, Lithuania does not
appear in the list of OECD members and is not included in the zone aggregates.

Source
Data on population and educational attainment for most countries are taken from OECD and Eurostat databases,
which are compiled from National Labour Force Surveys by the OECD LSO (Labour Market, Economic and Social
Outcomes of Learning) Network. Data on educational attainment for Indonesia and Saudi Arabia are taken from the
International Labour Organization (ILO) database, and data for China are from the UNESCO Institute of Statistics
(UIS) database.
Data on subnational regions for selected indicators are released by the OECD, with the support from the US National
Centre for Education Statistics (NCES), and 19 countries have submitted their data for this edition of Indicator A1:
Australia, Austria, Belgium, Brazil, Canada, Finland, Germany, Greece, Ireland, Italy, Poland, the Russian Federation,
Slovenia, Spain, Sweden, Switzerland, Turkey, the United Kingdom and the United States. Subnational estimates
were provided by countries using national data sources or by Eurostat based on data for Level 2 of the Nomenclature
of Territorial Units for Statistics (NUTS 2). For the United Kingdom, the subnational regions are based on NUTS 1.
Data used in Box A1.1 are based on the OECD Programme for the International Assessment of Adult Competencies
(the Survey of Adult Skills [PIAAC]).
Note regarding data from Israel
The statistical data for Israel are supplied by and are under the responsibility of the relevant Israeli authorities. The use
of such data by the OECD is without prejudice to the status of the Golan Heights, East Jerusalem and Israeli settlements
in the West Bank under the terms of international law.

Note regarding data from the Russian Federation in the Survey of Adult Skills (PIAAC)
The sample for the Russian Federation does not include the population of the Moscow municipal area. The data published,
therefore, do not represent the entire resident population aged 16-65 in the Russian Federation but rather the population
of the Russian Federation excluding the population residing in the Moscow municipal area. More detailed information
regarding the data from the Russian Federation as well as that of other countries can be found in the Technical Report of the
Survey of Adult Skills, Second Edition (OECD, 2016[14]).

References
OECD (2018), Education at a Glance Database – Educational attainment and labour-force status, http://stats.oecd.org/Index.
aspx?datasetcode=EAG_NEAC.

[5]

OECD (2018), Immigrants in OECD countries (DIOC) Database - Immigrants by sex and age, http://stats.oecd.org/Index.
aspx?DataSetCode=DIOC_SEX_AGE (accessed on 16 May 2018).

[3]

OECD (2018), OECD Handbook for Internationally Comparative Education Statistics 2018: Concepts, Standards, Definitions [13]
and Classifications, OECD Publishing, Paris, https://doi.org/10.1787/9789264304444-en.
OECD (2017), Education at a Glance 2017: OECD Indicators, OECD Publishing, Paris, http://dx.doi.org/10.1787/eag-2017-en.

[8]

OECD (2017), International Migration Outlook 2017, OECD Publishing, Paris, http://dx.doi.org/10.1787/migr_outlook2017-en.

[2]

OECD (2016), Education at a Glance 2016: OECD Indicators, OECD Publishing, Paris, http://dx.doi.org/10.1787/eag-2016-en.

[1]

OECD (2016), Technical Report of the Survey of Adult Skills (PIAAC), 2nd Edition, OECD, Paris, www.oecd.org/skills/piaac/ [14]
PIAAC_Technical_Report_2nd_Edition_Full_Report.pdf.
OECD (2015), Education at a Glance 2015: OECD Indicators, OECD Publishing, Paris, http://dx.doi.org/10.1787/eag-2015-en.

[7]

OECD (2015), Immigrant Students at School: Easing the Journey towards Integration, OECD Reviews of Migrant Education,
OECD Publishing, Paris, http://dx.doi.org/10.1787/9789264249509-en.

[9]

52

Education at a Glance 2018: OECD Indicators   © OECD 2018

To what level have adults studied? – INDICATOR A1

chapter A

Under embargo until 11/09/2018 at 11.00am CEST
OECD (2015), “What are the advantages today of having an upper secondary qualification?”, Education Indicators in Focus,
No. 34, OECD Publishing, Paris, http://dx.doi.org/10.1787/5jrw5p4jn426-en.

[4]

OECD (2014), Education at a Glance 2014: OECD Indicators, OECD Publishing, Paris, http://dx.doi.org/10.1787/eag-2014-en.

[6]

OECD/EU (2015), Indicators of Immigrant Integration 2015: Settling In, OECD Publishing, Paris, http://dx.doi.org/10.1787/ [10]
9789264234024-en.
OECD/NCES (2018), Education at a Glance Subnational Supplement,OECD/National Center for Education Statistics, Paris and [11]
Washington, DC, https://nces.ed.gov/surveys/annualreports/oecd/index.asp.
UNESCO Institute for Statistics (2012), International Standard Classification of Education: ISCED 2011, UNESCO Institute [12]
for Statistics, Montreal, http://uis.unesco.org/sites/default/files/documents/international-standard-classification-ofeducation-isced-2011-en.pdf.

Indicator A1 Tables
1 2 https://doi.org/10.1787/888933801582

Table A1.1 Educational attainment of 25-64 year-olds (2017)
Table A1.2 Trends in educational attainment of 25-34 year-olds, by gender (2007 and 2017)
Table A1.3 Educational attainment of native- and foreign-born 25-64 year-olds, by age at arrival in the country (2017)
Cut-off date for the data: 18 July 2018. Any updates on data can be found on line at http://dx.doi.org/10.1787/eag-data-en. More breakdowns can
also be found at http://stats.oecd.org/, Education at a Glance Database.

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53

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chapter A The Output of Educational Institutions and the Impact of Learning
Under embargo until 11/09/2018 at 11.00am CEST
Table A1.1. Educational attainment of 25-64 year-olds (2017)
Percentage of adults with a given level of education as the highest level attained

A1

Upper secondary
or post-secondary
non‑tertiary

Primary

Completion of
intermediate
lower secondary
programmes

Lower secondary

Completion of
intermediate
upper secondary
programmes

Upper secondary

Post-secondary
non-tertiary

Short-cycle
tertiary

Bachelor’s or
equivalent

Master’s or
equivalent

Doctoral or
equivalent

Tertiary

Less than
primary
Partners

OECD

Below upper secondary

All levels
of
education

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

Australia
Austria
Belgium
Canada
Chile1
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United Kingdom
United States

0
m
3
x(2)
7
0
x(2)
0
x(2)
2
x(2)
1
0
x(2)
0
2
1
x(6)
x(2)
0
0
13
1
x(4)
0
0
2
0
0
3
x(2)
0
5
0
1

5
1
5
2d
6
0
3d
1
2d
6
4d
13
1
0d
6
4
5
x(6)
4d
0
9
17
6
x(4)
0
7
29
0
1
8
3d
2
41
2
3

a
a
a
a
a
a
a
a
a
a
a
0
a
a
a
a
a
a
a
a
a
2
a
a
a
a
a
x(2)
a
a
a
a
a
a
a

14
14
15
7
22
6
16
11
9
14
10
13
15
23
12
7
33
x(6)
8
9
14
27
15
21d
17
1
21
8
11
31
12
10
15
17
6

a
a
a
a
a
a
c
a
a
a
a
0
a
a
a
a
a
a
a
3
a
4
a
a
a
a
a
0
a
a
2
a
a
17
a

30
50
35
24
42
70d
42
40
43
43
46
32
52
27
22
36
41
49d
40
46
34
20
41
27
37
59
23
66
53
23
34
45d
19
19
44d

5
3
2
11
a
x(6)
0
9
1
0
12
9
8
8
14
a
1
x(8)
a
8
3
a
0
14
2
3
1
2
a
0
7
x(6)
a
a
x(6)

12
15
0
26
8
0
5
6
12
14
1
2
1
3
10
14
0
21d
13
3
3
1
2
4
12
0
c
0
7
11
10
x(9, 10, 11)
5
10
11

26
4
22
21
13
6
21
12
17
10
15
26
13
21
25
23
4
30d
34d
19
12
15
21
28
19
7
6
3
7
10
17
21d
12
23
23

7
12
17
10d
1d
17
13
20
15
10
12
3
9
17
10
12
14
x(9)
x(9)
12
24
1
13
5
11
23
17
20
16
15
14
19d
2
12
11

1
1
1
x(10)
x(10)
1
1
1
1
1
1
1
1
1
1
1
0
x(9)
x(9)
0
2
0
1
1
1
1
1
1
4
1
2
3d
0
1
2

100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100

OECD average
EU22 average

2
1

6
5

m
m

14
14

m
m

39
42

5
4

7
5

17
14

12
14

1
1

100
100

5
17
3
x(4)
13
46
17
0
x(2)
3
x(2)

18
20
25
x(4)
29
14
27
0
1d
24
15d

a
a
a
a
8
a
a
0
a
a
a

16
15
47
41d
7
11
18
4
5
19
12

a
a
a
5
2
a
a
2
a
a
a

40
34d
15d
31d
16
18
26
32
20
32
58

a
x(6)
x(6)
x(6)
0
0
0
20
21
a
8

x(9)
x(9)
6
x(9)
6
1
3
a
25
x(9)
1

21d
15d
3
22d
15
10d
8
26
1
23d
5

x(9)
x(9)
0d
x(9)
2d
x(9)
1
14
26
x(9)
1d

x(9)
x(9)
x(10)
x(9)
x(10)
x(9)
0
1
0
x(9)
x(10)

100
100
100
100
100
100
100
100
100
100
100

9

13

m

16

m

33

m

9

16

8

m

100

Argentina
Brazil1
China2
Colombia
Costa Rica
India3
Indonesia
Lithuania
Russian Federation4
Saudi Arabia5
South Africa
G20 average

Note: In most countries data refer to ISCED 2011. For Indonesia and Saudi Arabia data refer to ISCED-97. See Definitions and Methodology sections for more
information. Data and more breakdowns are available at http://stats.oecd.org/, Education at a Glance Database.
1. Year of reference 2015.
2. Year of reference 2010.
3. Year of reference 2011.
4. Year of reference 2016.
5. Year of reference 2014.
Source: OECD/ILO/UIS (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933801601

54

Education at a Glance 2018: OECD Indicators   © OECD 2018

To what level have adults studied? – INDICATOR A1

chapter A

Under embargo until 11/09/2018 at 11.00am CEST
Table A1.2. Trends in educational attainment of 25-34 year-olds, by gender (2007 and 2017)
Percentage of 25-34 year-olds with a given level of education as the highest level attained
Upper secondary
or post-secondary non-tertiary

Below upper secondary

Partners

OECD

Men

Women

Total

Men

Women

A1

Tertiary

Total

Men

Women

Total

2007

2017

2007

2017

2007

2017

2007

2017

2007

2017

2007

2017

2007

2017

2007

2017

2007

2017

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

(13)

(14)

(15)

(16)

(17)

(18)

Australia
Austria
Belgium
Canada
Chile1
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan2
Korea
Latvia
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United Kingdom3
United States

20b
11
20b
10
m
5b
21b
18
12
18
14b
29b
15
31
19b
17b
36b
m
3b
25
24b
65
19b
23
19
9b
63
6b
9b
40
10b
9b
55b
19b
15

12
12
18
8
17
6
21
16
11
15
14
17
14
24
10
9
29
m
2
19
14
52
16
16
21
7
38
8
7
39
19
8
42
13
9

17b
16
17b
7
m
6b
18b
10
8
16
16b
19b
15
28
13b
12b
28b
m
2b
14
22b
66
16b
18
14
7b
48
6b
6b
29
8b
12b
67b
21b
11

9
11
15
5
16
6
13
9
8
13
13
12
14
15
6
6
22
m
2
10
12
52
11
14
17
4
23
9
4
28
15
8
47
12
7

19b
14
18b
9
m
6b
19b
14
10
17
15b
24b
15
29
16b
15b
32b
m
3b
20
23b
65
17b
21
17
8b
56
6b
8b
35
9b
10b
61b
20b
13

11
11
17
7
17
6
17
13
10
14
13
14
14
19
8
8
25
m
2
15
13
52
13
15
19
5
30
9
6
34
17
8
44
12
8

45b
59
45b
42
m
81b
47b
56
57
45
64b
45b
67
40
43b
48b
50b
m
43b
55
44b
19
47b
m
46
67b
22
79b
71b
25
56b
52b
30b
38b
49

43
52
42
40
55
67
41
50
55
45
56
48
62
37
41
53
51
m
33
51
39
25
43
44
37
59
37
64
60
24
41
42
27
38
48

36b
52
36b
30
m
77b
42b
47
44
38
61b
50b
59
35
36b
40b
49b
m
40b
54
39b
18
45b
m
35
57b
24
74b
53b
25
46b
57b
20b
36b
44

32
45
33
26
52
53
32
38
42
38
55
38
50
29
36
36
45
m
23
36
33
26
38
38
28
42
34
48
40
23
30
41
21
34
41

41b
55
40b
36
m
79b
44b
52
51
41
62b
47b
63
38
40b
44b
49b
m
42b
55
41b
18
46b
m
40
62b
23
77b
62b
25
51b
55b
25b
37b
47

37
48
38
33
53
60
37
44
49
42
56
43
56
33
38
44
48
m
28
44
36
26
40
41
32
51
36
56
50
24
36
42
24
36
44

35b
30
36b
48
m
14b
32b
26
31
37
22b
25b
18
29
38b
35b
15b
50d b
53b
19
32b
17
34b
m
35
24b
15
15b
20b
35
34b
39b
16b
43b
36

45
36
40
52
28
27
38
34
33
39
30
35
25
39
49
38
20
59d
65
30
47
23
42
40
42
34
26
27
33
36
40
49
31
50
43

46b
32
47b
63
m
17b
40b
43
48
46
23b
31b
26
37
51b
48b
23b
58d b
58b
32
40b
16
39b
m
51
36b
28
20b
40b
45
46b
31b
13b
43b
45

59
44
51
70
31
40
55
53
50
49
32
50
36
57
58
58
33
62d
75
54
55
23
51
48
55
54
42
43
56
49
55
51
32
54
52

41b
31
41b
56
m
15b
36b
34
39
41
23b
28b
22
33
44b
42b
19b
54d b
55b
26
36b
16
37b
m
43
30b
21
17b
30b
40
40b
35b
14b
43b
40

52
40
46
61
30
34
47
43
41
44
31
42
30
47
53
48
27
60d
70
42
51
23
47
44
48
44
34
35
45
43
47
50
32
52
48

OECD average
EU22 average

22
20

17
16

19
16

14
12

20
18

15
14

49
53

46
48

44
47

37
39

47
50

41
44

30
27

38
35

38
36

50
48

34
32

44
42

Argentina
Brazil1
China4
Colombia
Costa Rica
India5
Indonesia
Lithuania
Russian Federation6
Saudi Arabia7
South Africa

m
57
m
m
62
m
64b
17b
m
m
m

34
41
63
33
54
58
48
9
7
32
21

m
49
m
m
56
m
67b
12b
m
m
m

25
32
66
27
45
70
51
5
5
29
15

m
53
m
m
59
m
66b
14b
m
m
m

30
36
64
30
50
64
50
7
6
31
18

m
35
m
m
15
m
29b
50b
m
m
m

51
45
19
42
22
26
37
44
42
46
73

m
39
m
m
16
m
24b
43b
m
m
m

53
49
16
42
23
18
31
30
31
40
78

m
37
m
m
16
m
26b
47b
m
m
m

52
47
18
42
22
22
34
37
36
43
76

m
8
m
m
23
m
8b
33b
m
m
m

15
14
18
24
24
16
14
46
50
22
5

m
12
m
m
28
m
9b
45b
m
m
m

22
20
18
32
32
12
18
66
65
31
7

m
10
m
m
25
m
8b
39b
m
m
m

18
17
18
28
28
14
16
56
58
26
6

G20 average

m

28

m

26

m

27

m

41

m

36

m

39

m

32

m

39

m

35

Note: In most countries there is a break in the time series, represented by the code “b”, as data for 2017 refer to ISCED 2011 while data for 2007 refer to ISCED-97.
For Indonesia and Saudi Arabia data refer to ISCED-97. See Definitions and Methodology sections for more information. Data and more breakdowns are available at
http://stats.oecd.org/, Education at a Glance Database.
1. Year of reference 2015 instead of 2017.
2. Data for tertiary education include upper secondary or post-secondary non-tertiary programmes (less than 5% of adults are in this group).
3. Data for upper secondary attainment include completion of a sufficient volume and standard of programmes that would be classified individually as completion of
intermediate upper secondary programmes (17% of adults aged 25-64 are in this group).
4. Year of reference 2010 instead of 2017.
5. Year of reference 2011 instead of 2007.
6. Year of reference 2016 instead of 2017.
7. Year of reference 2014 instead of 2017.		
Source: OECD/ILO/UIS (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933801620

Education at a Glance 2018: OECD Indicators   © OECD 2018

55

chapter A The Output of Educational Institutions and the Impact of Learning
Under embargo until 11/09/2018 at 11.00am CEST
Table A1.3. Educational attainment of native- and foreign-born 25-64 year-olds, by age

A1

at arrival in the country (2017)

Partners

OECD

Percentage of foreign-born
adults among 25-64 year-olds

Percentage of adults with a given level of education as the highest level attained
Upper secondary or post-secondary
non‑tertiary

Tertiary

Foreign-born adults

Foreign-born adults

Foreign-born adults

Arrived
Arrived
in
in
the
country the
Native- by the country
at 16
age
born
adults of 15 or older Total

Arrived
Arrived
in
in
the
country the
Native- by the country
age at 16 or
born
Total adults of 15 older Total

Arrived
Arrived
in
in
the
country the
Native- by the country
age at 16 or
born
Total adults of 15 older Total

Total

Below upper secondary

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

(13)

(14)

(15)

(16)

Australia
Austria
Belgium
Canada
Chile1
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United Kingdom
United States

34
24
21
28
3
4
14
12
m
15
21
9
2
m
22
25
14
m
m
11
57
0
15
33
m
1
10
1
12
16
24
36
m
m
19

22
11
20
9
36
6
18
12
m
19
9
26
16
m
21
13
37
m
m
13
17
62
20
26
m
8
54
9
11
41
12
5
m
m
6

x(5)
29
29
6
14
x(5)
36
12
m
27
26
36
19
m
16
9
42
m
m
11
24
x(5)
x(5)
16
m
x(5)
30
c
11
42
19
15
m
m
19

x(5)
26
35
8
21
x(5)
20
5
m
43
33
40
14
m
8
11
50
m
m
5
20
x(5)
x(5)
9
m
x(5)
34
13
27
40
35
26
m
m
25

14
27
34
8
20
13
21
9
m
38
32
39
15
m
9
11
49
m
m
8
21
27
28
11
m
4
32
10
23
41
31
24
m
m
23

19
15
23
9
35
6
19
11
12
22
13
27
16
23
18
13
39
m
12
12
23
62
22
21
18
8
52
9
12
41
17
12
61
19
9

39
56
38
38
42
70
43
49
m
45
62
42
60
m
37
38
43
m
m
53
57
20
41
42
m
62
23
68
53
21
46
51
m
m
46

x(10)
51
40
29
53
x(10)
35
58
m
45
54
46
44
m
35
39
45
m
m
55
50
x(10)
x(10)
38
m
x(10)
35
54
58
27
42
52
m
m
42

x(10)
41
30
25
48
x(10)
34
45
m
25
40
42
57
m
35
26
36
m
m
63
40
x(10)
x(10)
39
m
x(10)
36
65
58
33
21
32
m
m
35

29
43
32
26
48
55
35
50
m
31
43
43
55
m
35
31
38
m
m
59
42
27
41
39
m
41
35
61
58
32
25
34
m
m
36

36
53
37
34
42
70
42
49
44
43
58
42
60
35
36
36
42
m
40
54
36
20
41
41
39
62
24
68
53
23
41
45
19
35
44

39
33
42
53
22
24
38
39
m
36
30
32
24
m
43
48
20
m
m
34
26
17
38
32
m
30
23
23
37
38
41
43
m
m
48

x(15)
20
31
65
33
x(15)
29
29
m
28
19
18
37
m
49
51
13
m
m
34
25
x(15)
x(15)
46
m
x(15)
35
41
31
31
39
33
m
m
39

x(15)
33
35
67
31
x(15)
46
50
m
32
27
18
29
m
57
63
14
m
m
32
40
x(15)
x(15)
51
m
x(15)
30
22
16
27
44
43
m
m
41

57
31
34
67
31
32
44
41
m
31
25
18
30
m
55
58
14
m
m
33
38
46
30
50
m
54
33
29
19
27
44
41
m
m
40

45
32
40
57
22
24
39
40
44
35
29
31
24
42
46
51
19
51d
48
34
40
17
37
38
43
30
24
23
34
36
42
43
20
46
46

OECD average
EU22 average

17
15

20
19

22
26

24
26

22
24

22
20

46
48

45
46

39
41

40
43

43
46

34
33

34
30

37
32

38
33

36
34

Argentina
Brazil1
China2
Colombia
Costa Rica
India3
Indonesia
Lithuania
Russian Federation4
Saudi Arabia5
South Africa

m
m
m
m
11
m
m
5
m
m
m

m
m
m
m
59
m
m
5
m
m
m

m
m
m
m
x(5)
m
m
3r
m
m
m

m
m
m
m
x(5)
m
m
3
m
m
m

m
m
m
m
70
m
m
3
m
m
m

39
51
76
46
60
71
62
7
6
45
27

m
m
m
m
16
m
m
54
m
m
m

m
m
m
m
x(10)
m
m
43r
m
m
m

m
m
m
m
x(10)
m
m
62
m
m
m

m
m
m
m
17
m
m
60
m
m
m

40
34
15
31
17
18
26
53
41
32
66

m
m
m
m
24
m
m
40
m
m
m

m
m
m
m
x(15)
m
m
54r
m
m
m

m
m
m
m
x(15)
m
m
35
m
m
m

m
m
m
m
13
m
m
37
m
m
m

21
15
10
22
23
11
12
40
53
23
7

G20 average

m

m

m

m

m

36

m

m

m

m

36

m

m

m

m

30

Note: In most countries data refer to ISCED 2011. For Indonesia and Saudi Arabia data refer to ISCED-97. See Definitions and Methodology sections for more
information. Data and more breakdowns are available at http://stats.oecd.org/, Education at a Glance Database.
1. Year of reference 2015.
2. Year of reference 2010.
3. Year of reference 2011.
4. Year of reference 2016.
5. Year of reference 2014.
Source: OECD/ILO/UIS (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933801639

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Under embargo until 11/09/2018 at 11.00am CEST

INDICATOR A2

TRANSITION FROM EDUCATION TO WORK:
WHERE ARE TODAY’S YOUTH?
• On average across OECD countries, 6% of 15-19 year-olds are neither employed nor in education
or training (NEET), and this percentage increases to 16% among 20-24 year-olds and 18% among
25-29 year-olds.

• In almost all OECD and partner countries, the share of the inactive population among 18-24 year-old
NEETs is higher for women than for men: on average, over 65% of NEET women are inactive, while
the share does not reach 50% among NEET men.

• On average across OECD countries, 18% of foreign-born 15-29 year-olds are NEETs, compared to
13% of native-born 15-29 year-olds.

Figure A2.1. Percentage of 18-24 year-old NEETs, by gender (2017)
Men

Women

Turkey
Mexico
Colombia
Costa Rica
Italy
Chile1
Greece
Spain
Israel
France
Hungary
Slovak Republic
Latvia
OECD average
Russian Federation
Estonia
United States
Poland
New Zealand
Portugal
EU22 average
Finland
United Kingdom
Lithuania
Ireland
Denmark
Australia
Belgium
Canada
Germany
Sweden
Austria
Norway
Slovenia
Luxembourg
Netherlands
Switzerland
Iceland

%

50
45
40
35
30
25
20
15
10
5
0

Note: NEET refers to young people neither employed nor in education or training.
1. Year of reference differs from 2017. Refer to the Table A2.1 for more details.
Countries are ranked in descending order of the total percentage of 18-24 year-old NEET women.
Source: OECD (2018), Education at a Glance Database, http://stats.oecd.org/. See Source section for more information and Annex 3
for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933801848

Context
The length and the quality of the schooling that individuals receive have an impact on their transition
from education to work, as do labour-market conditions, the economic environment and the cultural
context. In some countries, young people traditionally complete education before they look for work,
while in other countries education and employment are concurrent. In some countries, there is little
difference between how young women and young men experience the transition from education to
work, while in other countries significant proportions of young women raise their family full time
after leaving the education system and do not enter the labour force. When labour-market conditions
are unfavourable, young people often tend to stay in education longer, because high unemployment
rates drive down the opportunity costs of education, and they can improve their skills for when the
labour-market situation improves.
To improve the transition from education to work, regardless of the economic climate, education
systems should aim to ensure that individuals have the skills required in the labour market. During
recessions, public investment in education could be a sensible way to counterbalance unemployment
and invest in future economic growth, by building the needed skills. In addition, public investment
could be directed towards potential employers, in the form of incentives to hire young people.

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Being left out of employment can have long-lasting consequences, especially when people experience
long spells of unemployment and become discouraged. NEETs among young people represent a
current concern, but there can also be significant future consequences for individuals and society if
no action is taken to address this issue.

INDICATOR A2

Young immigrants are particularly at risk. According to the International Migration Outlook 2017
(OECD, 2017[1]) 13% of the total population in OECD countries are foreign-born. Some of these
people are still suffering the consequences of the economic crisis. For example, in Europe, where the
recovery from the crisis has been slower, migrant youth have experienced rising unemployment rates
since 2007.
Other findings

• A higher ending age of compulsory education is not systematically associated with higher
participation in education. In Chile, for example, the percentage of 15-19 year-olds in education is
below the OECD average, although the ending age of compulsory education (age 18) is among the
highest across OECD countries.

• In over half of OECD and partner countries that reported subnational data on the transition from
education to work, the share of 15-29 year-old NEETs in the subnational region with the highest
share is twice or more as large as in the subnational region with the lowest share.

• Across OECD and partner countries, 53% of 18-24 year-olds are studying, and 17% of 18-24 year-olds
combine education and employment.
Note
This indicator analyses the situation of young people in transition from education to work: those who
are in education, those who are employed, and those who are neither employed nor in education or
training. The latter group includes not only those who have not managed to find a job (unemployed
NEETs), but also those who are not actively seeking employment (inactive NEETs). Part of the analysis
focuses on 18-24 year-olds, as compulsory education does not affect the proportion of inactive or
unemployed at this age, when a significant proportion of young people are continuing their studies
after compulsory education.

Education at a Glance 2018: OECD Indicators   © OECD 2018

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Analysis
Young men and women (age 18-24) who are NEETs
Across OECD and partner countries, 53% of 18-24 year-olds are studying. Most of these young students are only
studying, but across countries 17% of them combine education and employment. This share varies between countries,
from less than 3% in Hungary, Italy and the Slovak Republic to over 35% in Iceland and the Netherlands (Table A2.1).
The transition from education to work can be a difficult period for many young people. Spells of unemployment,
job insecurity because of low-paid or temporary contracts, and the uncertainties associated with starting to live
autonomously produce a challenging phase in young people’s lives.
Of the 18-24 year-olds who have left education (47% on average across OECD countries), most are working, but
there is still a high share of NEETs. Among all 18-24 year-olds, 33% are not in education and employed, and 14% are
NEETs (Table A2.1).
The percentages of NEETs are generally similar by gender. On average across OECD countries, the difference between
men and women is about 2 percentage points, but there is significant variation across countries. In Chile, Colombia,
Costa Rica, Mexico and Turkey, the share of NEETs is generally high, and it is systematically higher for women than
for men, with differences of at least 10 percentage points. In contrast, in Austria and Switzerland, the share of
NEETs aged 18-24 is generally low, and it is about 5 percentage points lower for women than for men (Figure A2.1).
With regard to inactive NEETs, gender gaps are larger than for the whole NEET population, and countries follow a
similar trend. Figure A2.2 shows that in almost all OECD and partner countries, the share of the inactive population
among NEETs is higher for women than for men. On average in 2017, over 65% of NEET women are inactive, while
the share does not reach 50% among NEET men (Figure A2.2).

Greece (23%)

Portugal (15%)

(9%)

Spain (21%)

France (19%)

Switzerland

Belgium (13%)

Italy (27%)

Ireland (13%)

(5%)

Latvia (17%)

Iceland

EU22 average (14%)

(9%)
Luxembourg

Slovak Republic (15%)

Austria (11%)

Sweden (10%)

Finland (15%)

(9%)
Slovenia

Canada (12%)

New Zealand (13%)

Poland

Australia (12%)

(9%)

(13%)

Germany

Denmark (13%)

(7%)

United Kingdom (14%)

(9%)
Norway

Netherlands

Chile1 (21%)

Costa Rica (22%)

Hungary (14%)

United States (14%)

Israel (17%)

Estonia (13%)

Turkey (31%)

Lithuania (13%)

Women

%

100
90
80
70
60
50
40
30
20
10
0

OECD average (15%)

Men

Colombia (25%)

Figure A2.2. Share of the inactive among 18-24 year-old NEETs, by gender (2017)

Mexico (22%)

A2

Note: NEET refers to young people neither employed nor in education or training. The percentage in parentheses represents the share of
18‑24 year-old NEETs.
1. Year of reference differs from 2017. Refer to the Table A2.1 for more details.
Countries are ranked in descending order of the share of the inactive among 18-24 year-old NEET women.
Source: OECD (2018), Education at a Glance Database, http://stats.oecd.org/. See Source section for more information and Annex 3 for notes
(http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933801867

In Greece, Portugal and Spain, the share of the inactive population is low among both men and women who are
NEETs. This implies that most NEETs are actively looking for a job and therefore fall into the category of unemployed
NEETs. In contrast, in Mexico and Turkey, about 90% of women NEETs are inactive, the highest share across all
OECD and partner countries. In these two countries, the share of inactive NEETs is much lower among men, showing
a strong gender gap in the composition of the NEET population. Costa Rica and the Slovak Republic also show a
large gender gap in the share of inactive NEETs, with a difference of above 30 percentage points. The reasons for this

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large gap can be diverse, but one factor is that women may still largely be the ones responsible for raising families
and may decide to leave the labour market to care for their children. They would, therefore, be over-represented
among the inactive. It is also worth noting that the share of 18-24 year-old NEETs is 7 percentage points higher in
Costa Rica than in the Slovak Republic (Figure A2.2 and Table A2.1).
Transition from education to work by age
The period between age 15 and age 29 is quite long, and there are many changes associated with the teenage years
and young adulthood. Breaking this period down into smaller age groups allows for a better assessment of the
different situations among this population. In most countries, the period from age 15-19 encompasses the end
of upper secondary education and the transition to work or tertiary education. The periods from age 20-24 and
age 25‑29 are a time of increased financial autonomy, when most people leave education and enter the labour
market. On average across OECD countries, about 40% of 20-24 year-olds are no longer in education and are in
employment. This percentage rises to over 65% among 25-29 year-olds (Table A2.2 and [OECD, 2018[2]]).
Not all those who leave education find work. When they do, many accept temporary contracts or low-paid jobs, due
to their lack of experience. This difficult transition to the labour market is also reflected in the high percentage of
NEETs. On average across OECD countries, 16% of 20-24 year-olds are NEETs, and this percentage increases to
18% among 25-29 year-olds (Figure A2.3).

Figure A2.3. Percentage of NEETs for selected countries, by age group (2017)
A. Average share of NEETs
by age group across OECD countries

%

40
35

35

30

30

25

25

20

OECD average

20

15

15

10

10

5

5

0

0

%

40

15-19

20-24

25-29 Age

C. Countries with a high share of NEETs
among 15-19 year-olds and beyond

35

%

40

20

25-29 Age

D. Countries with a steep and continuous
increase in the share of NEETs with age
Italy
Greece
Spain

15
10

5

5
20-24

20-24

20

10

15-19

15-19

25

Costa Rica

15

Iceland

30

Colombia

25

Netherlands

Sweden

35

Turkey

30

0

B. Countries with a low share
of NEETs across all age groups

%

40

25-29 Age

0

15-19

20-24

25-29 Age

Note: NEET refers to young people neither employed nor in education or training.
Source: OECD (2018), Education at a Glance Database, http://stats.oecd.org/. See Source section for more information and Annex 3 for notes
(http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933801886

Across OECD and partner countries, the transition from education to work is very diverse. Figure A2.3 shows
some of the patterns observed across selected countries. In Colombia, Costa Rica and Turkey, the share of NEETs
is generally high, but particularly so among 15-19 year-olds: more than 15% are in this situation, compared to the
OECD average of about 6%. At this age, being out of education means that the highest possible level of education
completed is upper secondary education, but it is likely that a high share will not even have completed that level
(see Indicator A1). In these countries, it seems that there are lost opportunities for a number of young adults who
could benefit from the positive outcomes of further education (Figure A2.3).
Education at a Glance 2018: OECD Indicators   © OECD 2018

61

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Greece, Italy and Spain have all been severely hit by the last economic crisis, and the high share of the NEET
population still reflects that. In these countries, the level of NEETs is a little higher than the OECD average among
15-19 year-olds, but there is a steep and continuous increase in the share of NEETs with age. In Greece, the share
of NEETs among 15-19 year-olds is below 10%, and it reaches 35% among 25-29 year-olds, the highest share across
all OECD countries. In Greece and Spain, the high level of NEETs among 25-29 year-olds is mostly associated with
high unemployment and problems in finding a job, rather than with high inactivity. In Italy, both inactivity and
unemployment among 25-29 year-olds are above the OECD average (Figure A2.3 and [OECD, 2018[2]]).
In contrast, in Iceland, the Netherlands and Sweden, the share of NEETs is low across all age groups. This is
particularly true in Iceland, where the level of NEETs is constant, at about 5% across all age groups. Interestingly,
the low share of NEETs is not so much related to a higher-than-average share of employed people, but rather to a
higher-than-average share of 25-29 year-olds in education. Similar observations hold true for the Netherlands and
Sweden, where adults seem to stay in education longer (Figures A2.3 and A2.4, and [OECD, 2018[2]]).
A comparison of data on the ending age of compulsory education and the share of 15-19 year-olds in education
across countries shows that there is no direct link between the two. For example, in Slovenia, the enrolment rate
of 15-19 year-olds is 94%, despite the fact that compulsory education ends at age 14, the lowest school-leaving age
across OECD countries (see Annex 1). In contrast, Chile is one of the OECD countries with the highest ending age
of compulsory education (age 18), but the enrolment rate of 15-19 year-olds is 83%, suggesting that dropout rates
are high (Figure A2.4).

Figure A2.4. Percentage of the population in education, by age group (2017)
15-19 year-olds

%

20-24 year-olds

25-29 year-olds

100
90
80
70
60
50
40
30
20
10
0

Latvia
Luxembourg
Lithuania
Poland
Czech Republic
Belgium
Slovenia
Germany
Denmark
Russian Federation
Finland
Portugal
EU22 average
Netherlands
Hungary
Greece
Sweden
France
Slovak Republic
Spain
Switzerland
Austria
Estonia
Italy
OECD average
Ireland
Canada
Australia
South Africa
United States
Chile1
Norway
United Kingdom
New Zealand
Iceland
Turkey
Israel
Costa Rica
Brazil1
Mexico
Colombia

A2

1. Year of reference differs from 2017. Refer to the Table A2.1 for more details.
Countries are ranked in descending order of the percentage of 15-19 year-olds in education.
Source: OECD (2018), Education at a Glance Database, http://stats.oecd.org/. See Source section for more information and Annex 3 for notes
(http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933801905

Native-born and foreign-born young people who are NEETs
In most OECD countries, the share of foreign-born NEETs among 15-29 year-olds is larger than the share of
native-born NEETs of the same age. On average across OECD countries, 18% of foreign-born 15-29 year-olds are
NEETs, while 13% of native-born 15-29 year-olds are in this situation. The differences are largest in Austria and
Germany, where the percentage is about 25% among foreign-born 15-29 year-olds and below 10% among nativeborn 15-29 year-olds. In contrast, in about one third of countries, the difference between the two groups is below
3 percentage points. For example, there is only a small difference between the two groups in New Zealand. It has
one of the highest shares of foreign-born 15-29 year-olds (27%), but the share of NEETs among them (10%) is

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the lowest among all OECD countries with data. This low share of NEETs among foreign-born 15-29 year-olds in
New Zealand might be related to its point-based immigration system, which prioritises higher-skilled migrants and
makes migration more selective (Figure A2.5 and [OECD, 2017[1]]).
In Greece, Italy and Spain, about one in three foreign-born 15-29 year-olds are NEETs. In these countries, a high
share of native-born 15-29 year-olds are also NEETs, but to a much lower extent than foreign-born 15-29 year-olds.
The share of foreign-born 15-29 year-old NEETs in Greece (over 35%) is the highest across OECD countries. But
this may affect fewer people than in Italy and Spain, because in Greece only 7% of 15-29 year-olds were born abroad,
while this is the case for 12% in Italy and 17% in Spain (Figure A2.5).

Figure A2.5. Percentage of native- and foreign-born 15-29 year-old NEETs (2017)
Foreign born

%

Native born

40
35
30
25
20
15
10

(2%)
Lithuania

New Zealand (27%)

Luxembourg (38%)

(2%)

Israel (10%)

(1%)
Poland

Hungary

(3%)

Australia (25%)

(3%)
Estonia

Czech Republic

Canada (21%)

Ireland (19%)

Sweden (18%)

Switzerland (23%)

Denmark (12%)

(8%)
France

Netherlands (10%)

(4%)
Chile1

(7%)
Portugal

OECD average (12%)

(2%)
Latvia

United States (11%)

(1%)
Mexico

EU22 average (11%)

(5%)

Austria (19%)

Slovenia

Germany (16%)

Belgium (14%)

(8%)

Spain (17%)

Costa Rica

Italy (12%)

Greece

0

(7%)

5

Note: NEET refers to young people neither employed nor in education or training. The percentage in parentheses represents the share of foreign-born
15-29 year-olds.
1. Year of reference differs from 2017. Refer to the source table for more details.
Countries are ranked in descending order of the percentage of 15-29 year-old foreign-born NEETs.
Source: OECD (2018), Table A2.3. See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933801924

Subnational variations in the percentage of young people who are NEETs
On average across OECD countries, 47% of 15-29 year-olds are studying, 39% are not studying and working, and
13% are NEETs, but there are significant subnational variations within countries (Table A2.2 and [OECD/NCES,
2018[3]]).
In 10 of the 17 OECD and partner countries that reported subnational data on the transition from education to
work, the share of 15-29 year-old NEETs in the subnational region with the highest share is twice or more as large
as in the subnational region with the lowest share. When dividing the highest shares by the lowest shares within
countries, the ratio is 3 or more in Canada, Italy, the Russian Federation and Spain. In contrast, across the OECD
and partner countries that reported subnational data, the difference is smallest in Ireland and Slovenia. However,
this may be related to the fact that there are only two subnational entities in these two countries (Figure A2.6).
Many countries in Figure A2.6 have outlier region(s) with a particularly high percentage of NEETs compared to the
national average. This is particularly striking for Canada and the Russian Federation (two large countries with many
subnational regions), but it is also true for Austria, Germany, Italy, Poland, Spain and Turkey (Figure A2.6).
In general, the variations are low in Belgium, Finland, Ireland and Slovenia, but these countries have five or fewer
subnational regions (far fewer than the 85 subnational regions in the Russian Federation) (Figure A2.6).
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Figure A2.6. Percentage of 15-29 year-old NEETs, by subnational regions (2017)

A2

Country average

%

Regional average

45
40
35
30
25

OECD average

20
15
10

Sweden

Austria

Slovenia

Germany

Finland

Australia

United Kingdom

Canada

Ireland

Poland

Belgium

All OECD and partners

Russian Federation1

United States1

Spain

Greece

Italy

0

Turkey

5

Note: The country average is the weighted average of the regions and can differ from the country average shown in Table A2.2 as the data source may be
different. “All OECD and partner countries” refers to the country averages shown in Table A2.2. NEET refers to young people neither employed nor in
education or training.
1. Year of reference 2016.
Countries are ranked in descending order of the percentage of 15-29 year-old NEETs (country average).
Source: OECD/NCES (2018), Education at a Glance Subnational Supplement, https://nces.ed.gov/surveys/annualreports/oecd/index.asp. See
Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933801943

Definitions
Educational attainment refers to the highest level of education attained by a person.
Employed, inactive and unemployed individuals: See Definitions section in Indicator A3.
Individuals in education are those who had received formal education and/or training in the regular educational
system in the four weeks prior to being surveyed.
Levels of education: See the Reader’s Guide at the beginning of this publication for a presentation of all ISCED 2011 levels.
NEET: Neither employed nor in education or training.

Methodology
Data usually refer to the second quarter of studies, as this is the most relevant period for knowing if the young person
is really studying or has left education for the labour force. This second quarter corresponds in most countries to
the first three months of the calendar year, but in some countries to the spring quarter (i.e. March, April and May).
Education or training corresponds to formal education; therefore, someone not working but following non-formal
studies is considered a NEET.
For information on the methodology for subnational regions, see Indicator A1.
Please see the OECD Handbook for Internationally Comparative Education Statistics 2018 (OECD, 2018[4]) for more
information and Annex 3 for country-specific notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Lithuania was not an OECD member at the time of preparation of this publication. Accordingly, Lithuania does not
appear in the list of OECD members and is not included in the zone aggregates.

Source
For information on the sources, see Indicator A1.
Data on subnational regions for selected indicators are released by the OECD, with support from the US National
Centre for Education Statistics (NCES), and 17 countries have submitted their data for this edition of Indicator A2:
Australia, Austria, Belgium, Canada, Finland, Germany, Greece, Ireland, Italy, Poland, the Russian Federation,

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Slovenia, Spain, Sweden, Turkey, the United Kingdom and the United States. Subnational estimates were provided
by countries using national data sources or by Eurostat based on data for Level 2 of the Nomenclature of Territorial
Units for Statistics (NUTS 2). For the United Kingdom, the subnational regions are based on NUTS 1.

Note regarding data from Israel
The statistical data for Israel are supplied by and are under the responsibility of the relevant Israeli authorities. The use
of such data by the OECD is without prejudice to the status of the Golan Heights, East Jerusalem and Israeli settlements
in the West Bank under the terms of international law.

References
OECD (2018), Education at a Glance Database – Transition from education to work, http://stats.oecd.org/Index.aspx?datasetcode [2]
=EAG_TRANS.
OECD (2018), OECD Handbook for Internationally Comparative Education Statistics 2018: Concepts, Standards, Definitions [4]
and Classifications, OECD Publishing, Paris, https://doi.org/10.1787/9789264304444-en.
OECD (2017), International Migration Outlook 2017, OECD Publishing, Paris, http://dx.doi.org/10.1787/migr_outlook- [1]
2017-en.
OECD/NCES (2018), Education at a Glance Subnational Supplement, OECD/National Center for Education Statistics, Paris [3]
and Washington, DC, https://nces.ed.gov/surveys/annualreports/oecd/index.asp.

Indicator A2 Tables
1 2 https://doi.org/10.1787/888933801772

Table A2.1 Percentage of 18-24 year-olds in education/not in education, by work status (2017)
Table A2.2 Trends in the percentage of young adults in education/not in education, employed or not, by age group
(2007 and 2017)
Table A2.3 Percentage of native- and foreign-born 15-29 year-old NEETs, by age at arrival in the country (2017)
Cut-off date for the data: 18 July 2018. Any updates on data can be found on line at http://dx.doi.org/10.1787/eag-data-en. More breakdowns can
also be found at http://stats.oecd.org/, Education at a Glance Database.

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Table A2.1. Percentage of 18-24 year-olds in education/not in education, by work status (2017)

A2

In education

Not in education

Total

Total

Employed

Unemployed

Inactive

(1)

(2)

(3)=(1)+(2)

(4)

(5)

(6)=(3)+(4)+(5)

(7)

(8)

(9)

Australia
Austria
Belgium
Canada
Chile1
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United Kingdom
United States

5.7
7.7
0.2
x(2)
x(2)
m
x(2)
c
x(2)
6.4
16.0
a
a
a
a
x(2)
a
m
m
a
a
a
x(2)
a
0.5
a
a
0.2
x(2)
x(2)
a
16.9
a
4.6
x(2)

26.1
14.1
3.6
23.4d
9.3d
m
34.3d
18.1
19.7d
4.3
14.2
4.7
2.8
38.8
17.1
10.7d
2.3
m
m
12.6
10.2
9.6
40.2d
20.1
19.6
8.9
5.3
2.7
21.2d
6.7d
16.3
16.1
13.7
13.7
20.7d

31.8
21.8
3.8
23.4
9.3
m
34.3
18.1
19.7
10.7
30.1
4.7
2.8
38.8
17.1
10.7
2.3
m
m
12.6
10.9
9.6
40.2
20.1
20.2
8.9
5.3
2.9
21.2
6.7
16.3
33.1
13.7
18.3
20.7

3.0
1.6
0.9
2.7
2.8
m
4.3
2.9
6.1
0.8
1.1
2.6
0.2
3.2
1.3
0.7
0.7
m
m
0.6
1.3
0.7
3.4
1.8
3.0
1.4
2.8
0.2
1.2
4.9
6.8
2.2
4.6
1.9
1.4

16.8
28.3
57.0
24.2
38.2
m
24.2
28.6
30.8
42.1
31.2
54.6
46.3
11.6
31.1
18.2
50.1
m
m
39.4
53.3
26.5
22.1
15.2
27.1
45.4
46.3
47.9
46.9
48.0
30.2
17.6
22.5
22.8
24.8

51.6
51.7
61.7
50.2
50.3
m
62.7
49.6
56.6
53.5
62.5
61.8
49.3
53.6
49.6
29.6
53.1
m
m
52.6
65.5
36.8
65.7
37.1
50.3
55.6
54.4
51.0
69.2
59.6
53.3
52.8
40.7
43.0
47.0

36.7
37.4
25.3
37.5
28.6
m
24.6
37.6
28.4
27.8
28.0
15.2
36.2
41.5
37.0
53.6
20.4
m
m
30.7
25.4
41.0
27.2
50.0
40.9
31.0
30.4
34.2
21.6
19.5
37.1
38.6
28.2
43.4
38.9

4.9
5.1
6.8
5.5
6.0
m
3.4
3.7
6.8
10.7
3.3
14.6
4.1
2.5
6.8
3.4
12.6
m
m
8.5
4.6
3.1
1.9
5.2
2.6
5.6
9.2
8.0
4.6
13.4
4.4
4.1
8.9
5.2
3.9

6.8
5.7
6.1
6.7
15.1
m
9.3
9.1
8.2
8.0
6.1
8.4
10.3
2.4
6.6
13.3
13.9
m
m
8.3
4.6
19.1
5.2
7.6
6.2
7.7
6.0
6.9
4.6
7.5
5.2
4.5
22.3
8.4
10.2

11.7
10.8
12.9
12.2
21.1
m
12.7
12.8
15.0
18.7
9.5
23.0
14.5
4.9
13.4
16.7
26.6
m
m
16.7
9.1
22.1
7.1
12.9
8.8
13.3
15.2
14.8
9.1
20.9
9.6
8.6
31.1
13.6
14.1

48.4
48.3
38.3
49.8
49.7
m
37.3
50.4
43.4
46.5
37.5
38.2
50.7
46.4
50.4
70.4
46.9
m
m
47.4
34.5
63.2
34.3
62.9
49.7
44.4
45.6
49.0
30.8
40.4
46.7
47.2
59.3
57.0
53.0

100
100
100
100
100
m
100
100
100
100
100
100
100
100
100
100
100
m
m
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100

OECD average
EU22 average

m
m

15.0
13.0

16.9
14.7

2.3
2.2

33.4
39.4

52.6
56.3

32.9
29.4

6.0
6.8

8.4
7.4

14.5
14.3

47.4
43.7

100
100

Argentina
Brazil
China
Colombia
Costa Rica
India
Indonesia
Lithuania
Russian Federation
Saudi Arabia
South Africa

m
m
m
a
a
m
m
a
m
m
a

m
m
m
11.1
16.3
m
m
15.9
6.6
m
m

m
m
m
11.1
16.3
m
m
15.9
6.6
m
m

m
m
m
3.2
4.9
m
m
1.5
c
m
m

m
m
m
16.7
24.8
m
m
45.7
44.4
m
m

m
m
m
30.9
46.0
m
m
63.1
52.8
m
m

m
m
m
43.8
31.9
m
m
23.8
33.9
m
m

m
m
m
9.8
7.5
m
m
5.3
5.7
m
m

m
m
m
15.4
14.5
m
m
7.8
7.6
m
m

m
m
m
25.3
22.0
m
m
13.1
13.3
m
m

m
m
m
69.1
54.0
m
m
36.9
47.2
m
m

m
m
m
100
100
m
m
100
100
m
m

G20 average

m

m

m

m

m

m

m

m

m

m

m

m

Unemployed Inactive

Total

Other employed

NEET

Students in work-study
programmes
Partners

OECD

Employed

Total

(10)=(8)+(9) (11)=(7)+(10)

Total
(12)=(6)+(11)

Note: NEET refers to young people neither employed nor in education or training. See Definitions and Methodology sections for more information. Data and more
breakdowns available at http://stats.oecd.org/, Education at a Glance Database.
1. Year of reference 2015.
Source: OECD (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933801791

66

Education at a Glance 2018: OECD Indicators   © OECD 2018

Transition from education to work: Where are today’s youth? – INDICATOR A2

chapter A

Under embargo until 11/09/2018 at 11.00am CEST
Table A2.2. Trends in the percentage of young adults in education/not in education, employed or not,

by age group (2007 and 2017)

20-24 year-olds
2017

2007

2017

Not in education

Not in education

Not in education

Not in education

OECD

In
education Employed

Partners

15-29 year-olds

2007

NEET

In
education Employed

NEET

In
education Employed

NEET

In
education Employed

NEET

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

Australia
Austria
Belgium
Canada
Chile1
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United Kingdom
United States

39.1b
33.5
39.2b
38.4
m
42.1b
48.9b
45.4
51.9
41.9
45.7b
48.1b
49.2
51.9
25.9b
28.5b
41.7b
31.8b
m
42.5
55.1b
24.6
50.8b
38.8
37.7
56.5b
35.5
29.4b
58.7b
34.9
39.6b
41.0b
18.6b
29.7b
35.7

50.1b
54.7
45.3b
47.8
m
46.9b
43.1b
39.3
34.8
40.1
39.1b
34.5b
33.9
43.1
62.0b
31.9b
35.7b
56.1b
m
41.0
35.6b
49.8
42.2b
47.6
53.6
25.2b
49.3
50.7b
30.9b
48.2
47.3b
48.6b
35.1b
52.3b
48.1

10.7b
11.8
15.5b
13.8
m
11.0b
8.0b
15.3
13.3
17.9
15.2b
17.4b
16.9
5.0
12.1b
39.6b
22.6b
12.1b
m
16.5
9.2b
25.6
6.9b
13.6
8.8
18.3b
15.2
19.9b
10.4b
16.9
13.1b
10.4b
46.3b
18.1b
16.2

45.8
42.8
51.8
42.8
44.7
47.8
56.6
41.6
49.1
42.8
54.6
56.6
38.9
46.8
37.5
27.8
43.9
m
m
40.5
60.1
29.5
58.9
32.2
45.5
43.6
44.5
40.8
62.7
51.9
46.0
43.2
35.8
41.7
38.8

42.6
45.4
33.0
44.0
34.6
41.7
29.2
45.2
34.0
36.5
35.4
19.4
45.0
47.6
48.1
54.8
26.0
m
m
39.2
29.8
46.8
33.4
54.5
44.4
40.5
38.4
42.7
26.8
24.9
43.5
47.7
31.4
45.4
47.0

11.5
11.8
15.2
13.2
20.7
10.5
14.2
13.2
17.0
20.7
10.1
24.0
16.1
5.6
14.4
17.3
30.1
m
m
20.3
10.2
23.8
7.7
13.3
10.1
15.9
17.1
16.5
10.5
23.2
10.5
9.1
32.9
12.9
14.2

45.4b
43.6
45.4b
43.7
m
44.8b
52.8b
48.0
56.5
46.1
52.4b
43.9b
48.6
51.3
33.3b
41.0b
44.5b
39.5b
m
48.2
49.8b
33.5
53.1b
46.2
44.4
53.4b
39.1
40.5b
56.3b
35.4
50.1b
45.5b
24.3b
40.1b
44.5

44.1b
45.1
41.9b
44.3
m
43.5b
40.1b
38.9
33.4
39.4
35.0b
39.5b
35.7
44.1
55.9b
29.3b
35.5b
48.9b
m
37.0
41.2b
43.2
40.2b
41.9
48.1
31.0b
47.5
42.3b
33.6b
49.0
39.9b
44.3b
34.4b
45.0b
42.3

10.5b
11.3
12.7b
12.1
m
11.7b
7.1b
13.0
10.1
14.5
12.6b
16.6b
15.6
4.6
10.7b
29.7b
20.0b
11.7b
m
14.8
8.9b
23.3
6.7b
12.0
7.5
15.5b
13.4
17.2b
10.1b
15.6
10.1b
10.2b
41.3b
14.9b
13.2

48.1
47.2
48.8
44.0
48.5
46.1
57.7
44.4
54.4
47.1
52.7
52.1
42.5
47.8
46.4
43.9
47.9
m
m
43.5
54.2
37.5
56.1
39.1
46.2
43.7
49.9
41.1
56.1
51.2
50.5
47.3
42.5
42.8
44.1

41.0
42.0
37.9
43.8
33.5
43.0
30.5
43.9
33.0
36.3
37.9
25.2
43.5
47.3
40.5
42.5
27.0
m
m
42.7
38.0
41.3
36.3
49.7
45.0
43.1
37.7
42.7
33.0
28.9
41.4
44.3
30.3
45.0
42.6

10.9
10.8
13.2
12.2
18.0
10.9
11.8
11.8
12.6
16.5
9.3
22.8
14.0
4.9
13.1
13.6
25.1
m
m
13.9
7.7
21.2
7.5
11.2
8.8
13.3
12.4
16.2
10.9
19.9
8.0
8.4
27.2
12.2
13.3

OECD average
EU22 average

40.4
43.0

43.8
42.4

15.9
14.6

45.1
48.0

39.4
36.5

15.6
15.6

45.0
46.6

41.1
40.5

13.9
12.9

47.4
48.9

39.1
37.7

13.4
13.4

Argentina
Brazil1
China
Colombia
Costa Rica
India
Indonesia
Lithuania2
Russian Federation
Saudi Arabia
South Africa

m
24.6
m
m
m
m
m
51.4b
m
m
m

m
52.0
m
m
m
m
m
32.7b
m
m
m

m
23.4
m
m
m
m
m
15.9b
m
m
m

m
24.9
m
25.5
41.5
m
m
53.2
44.0
m
30.8

m
48.1
m
49.5
38.1
m
m
30.8
41.4
m
21.3

m
27.0
m
25.0
20.5
m
m
16.1
14.6
m
47.9

m
35.1
m
m
m
m
m
56.0b
m
m
m

m
45.0
m
m
m
m
m
32.6b
m
m
m

m
19.9
m
m
m
m
m
11.4b
m
m
m

m
36.6
m
34.6
44.6
m
m
50.2
37.6
m
40.9

m
40.9
m
43.6
34.0
m
m
38.6
50.0
m
21.9

m
22.5
m
21.9
21.4
m
m
11.2
12.4
m
37.2

m

m

m

m

m

m

m

m

m

m

m

m

G20 average

Note: NEET refers to young people neither employed nor in education or training. See Definitions and Methodology sections for more information. Data and more
breakdowns available at http://stats.oecd.org/, Education at a Glance Database.
1. Year of reference 2015 instead of 2017.
2. Year of reference 2005 instead of 2007.
Source: OECD (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933801810

Education at a Glance 2018: OECD Indicators   © OECD 2018

67

A2

chapter A The Output of Educational Institutions and the Impact of Learning
Under embargo until 11/09/2018 at 11.00am CEST
Table A2.3. Percentage of native- and foreign-born 15-29 year-old NEETs, by age

A2

at arrival in the country (2017)

Partners

OECD

Foreign-born
Native-born

Arrived in the country
by the age of 15

Arrived in the country
at 16 or older

Total

(1)

(2)

(3)

(4)

(5)

Australia
Austria
Belgium
Canada
Chile1
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United Kingdom
United States

11.0
7.7
11.4
11.7
18.0
10.9
11.1
11.7
m
14.0
6.6
21.8
14.0
m
12.9
13.7
23.8
m
m
13.8
5.5
21.2
6.4
12.0
m
13.3
12.0
16.3
9.9
17.7
6.9
6.5
m
m
12.6

m
20.2
18.7
9.3
14.1
m
13.6
c
m
17.9
11.4
31.3
11.6
m
15.7
9.6
25.9
m
m
c
7.5
m
m
7.9
m
m
15.0
m
8.0r
23.2
9.9
10.5
m
m
15.6

m
26.9
30.3
19.4
18.9
m
19.8
19.4r
m
16.5
32.1
47.6
12.9
m
13.5
19.5
46.6
m
m
c
15.6
m
m
11.9
m
m
29.1
c
36.8r
41.3
17.4
18.1
m
m
22.1

12.5
23.9
24.2
13.1
17.8
12.8
16.6
13.1
m
17.2
24.1
36.0
12.3
m
14.5
12.3
34.3
m
m
19.8r
11.4
21.4
17.1
9.6
m
12.5
18.5
c
23.8
30.4
13.2
14.8
m
m
18.7

10.9
10.8
13.2
12.2
18.0
10.9
11.8
11.8
12.6
16.5
9.3
22.8
14.0
4.9
13.1
13.6
25.1
m
m
13.9
7.7
21.2
7.5
11.2
8.8
13.3
12.4
16.2
10.9
19.9
8.0
8.4
27.2
12.2
13.3

OECD average
EU22 average

12.7
12.4

m
16.4

m
27.1

18.4
19.8

13.4
13.4

Argentina
Brazil1
China
Colombia
Costa Rica
India
Indonesia
Lithuania
Russian Federation
Saudi Arabia
South Africa

m
m
m
m
21.0
m
m
11.2
m
m
m

m
m
m
m
m
m
m
11.8r
m
m
m

m
m
m
m
m
m
m
m
m
m
m

m
m
m
m
26.9
m
m
11.3
m
m
m

m
22.5
m
21.9
21.4
m
m
11.2
12.4
m
37.2

m

m

m

m

m

G20 average

Total

Note: NEET refers to young people neither employed nor in education or training. See Definitions and Methodology sections for more information. Data and more
breakdowns available at http://stats.oecd.org/, Education at a Glance Database.
1. Year of reference 2015.
Source: OECD (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933801829

68

Education at a Glance 2018: OECD Indicators   © OECD 2018

Under embargo until 11/09/2018 at 11.00am CEST

Under embargo until 11/09/2018 at 11.00am CEST

INDICATOR A3

HOW DOES EDUCATIONAL ATTAINMENT AFFECT
PARTICIPATION IN THE LABOUR MARKET?
• On average across OECD countries, 81% of 25-34 year-old adults who have at least an upper
secondary education are employed, compared to 60% among those who have not completed upper
secondary education.

• On average across OECD countries, the employment rate of younger women (age 25-34) without
upper secondary education is 45%, compared to 71% for their male peers, but the disparities narrow
as educational attainment increases.

• While labour-market outcomes for foreign-born adults without upper secondary education are
mixed across OECD and partner countries, foreign-born adults with tertiary education have lower
employment prospects than their native-born peers in most countries with data.

Figure A3.1. Employment rates of 25-34 year-olds
with below upper secondary education, by gender (2017)
Men

Women

Iceland
Luxembourg
Portugal
Korea
Switzerland
Latvia
Sweden
Norway
New Zealand
Colombia
Spain
Netherlands
Brazil1
Estonia
United Kingdom2
Indonesia
Austria
Russian Federation1
OECD average
EU22 average
Israel
Australia
Argentina
Slovenia
Germany
Hungary
Chile1
Canada
Mexico
United States
Denmark
Costa Rica
Czech Republic
Lithuania
Belgium
France
Italy
Finland
Slovak Republic
Ireland
Greece
Poland
South Africa
Turkey
Saudi Arabia1

%

100
90
80
70
60
50
40
30
20
10
0

1. Year of reference differs from 2017. Refer to the source table for details.
2. Data for upper secondary attainment include completion of a sufficient volume and standard of programmes that would be
classified individually as completion of intermediate upper secondary programmes (17% of adults aged 25-64 are in this group).
Countries are ranked in descending order of the employment rate of 25-34 year-old women with below upper secondary education.
Source: OECD / ILO (2018), Table A3.2. See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/
eag-2018-36-en).
1 2 https://doi.org/10.1787/888933802057

Context
The economies of OECD countries depend upon a supply of highly skilled workers. Expanded
education opportunities have increased the pool of skilled people across countries, and those with high
qualifications are more likely to be employed. On the other hand, while employment opportunities
still exist for those with lower qualifications, their labour-market prospects are relatively challenging.
People with the lowest educational qualifications have low earnings (see Indicator A4) and are
often working in routine jobs that are at greater risk of being automated, therefore increasing their
likelihood of being unemployed (Arntz, Gregory and Zierahn, 2016[1]). These disparities in labourmarket outcomes can exacerbate inequalities in society.
Education systems face challenges in responding to changing demands for skills in the labour market.
Given the technological advances that have been transforming the needs of the global labour market,
employment prospects are better among those with higher skills, particularly in information and
communication technology (ICT), and those who are comfortable using ICT for problem solving.
Such skills may be acquired outside of formal education and, in some cases, can help people find jobs
despite lower educational attainment (Lane and Conlon, 2016[2]).

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Under embargo until 11/09/2018 at 11.00am CEST
Employment and unemployment rates over time provide a basis for assessing the long-term trends
and variations in labour-market risks among men and women with different levels of education and
at different ages. These results can help governments better understand how economies may evolve
in the coming years. In turn, that understanding could inform education policies, with the aim of
ensuring that the students of today are better prepared for the jobs of tomorrow.

INDICATOR A3

With the recent increase in migration flows to OECD countries, the labour-market situation
of foreign-born adults stimulates the public debate. According to the International Migration
Outlook 2017 (OECD, 2017[3]), 13% of the total population in OECD countries are foreign-born.
The important rise in humanitarian migration largely contributed to the growing preoccupation
with reviewing migration policies. However, humanitarian migration makes up only a part of
total population flows. A large share of migrants moves for work reasons, and there is evidence of
positive social and economic returns to migration. Overall, foreign-born adults largely contribute to
increasing the workforce, and they generally contribute more in taxes and social contributions than
they receive in benefits (OECD, 2014[4]).
Other findings

• On average across OECD countries, the unemployment rate is almost twice as high for those who
have not completed upper secondary education as for those with higher qualifications: 15% of
younger adults (age 25-34) without upper secondary education are unemployed, compared
to around 7% for those with a higher level of education (i.e. upper secondary, post-secondary
non‑tertiary education or tertiary education).

• On average across OECD countries, about 35% of adults (age 25-64) who have not completed
upper secondary education are inactive, compared to 20% of adults with upper secondary or
post‑secondary non-tertiary education and 12% of adults with a tertiary degree.

• Between 2007 and 2017, the gender gap in employment rates for younger adults (age 25-34) with
low educational attainment has decreased by more than 5 percentage points in about one-third
of OECD countries, while the gender gap increased by 5 or more percentage points in Estonia,
Lithuania, New Zealand, Poland, the Slovak Republic and Slovenia.

• Across OECD and partner countries that participated in the Survey of Adult Skills (PIAAC), a large
majority of workers report having a level of education that corresponds to the level needed for
their job.

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A3

Analysis
Educational attainment and employment
Upper secondary education is the minimum educational attainment level for successful labour-market integration.
Adults (age 25-64) without at least this level of education are penalised in the labour market. On average across
OECD countries, the employment rate is 85% for tertiary-educated adults, 76% for adults with an upper secondary
or post-secondary non-tertiary qualification, and less than 60% for adults who have not completed upper secondary
education (Table A3.1).
The increase in employment rates for those with an upper secondary or post-secondary non-tertiary education
compared to those with lower levels of education is 25 percentage points or more in Belgium, the Czech Republic,
Poland and the Slovak Republic. Countries with the lowest increase (below 10 percentage points) are Argentina,
Brazil, Colombia, Costa Rica, Greece, Indonesia, Korea, Mexico and Saudi Arabia (Table A3.1).
Adults who have not completed upper secondary education enjoy high employment rates (between 70% and 80%)
in only a few countries: Colombia, Iceland, Indonesia and New Zealand. In all other countries, these adults are
penalised in the labour market. Less than half are employed in Belgium, Poland, the Slovak Republic, Slovenia and
South Africa (Figure A3.1).
On average across OECD countries, getting a tertiary education improves employment rates by roughly a further
10 percentage points, compared to adults with an upper secondary or post-secondary non-tertiary education.
The difference is 15 percentage points or more in Latvia, Lithuania, Poland, Slovenia and South Africa. The
employment advantage is 7 percentage points or less in Australia, the Czech Republic, Denmark, Estonia,
Germany, Hungary, Iceland, Korea, New Zealand, Portugal, the Slovak Republic, Sweden, Switzerland and
the United Kingdom. One explanation for this situation is that, in some of these countries, employment rates for
adults with an upper secondary or post-secondary non-tertiary vocational qualification are almost as high as for
tertiary graduates. For example, in Germany and Switzerland, a majority of vocational graduates participate in
combined school- and work-based programmes, which smooth the transition from education to work (Table A3.1
and [OECD, 2018[5]]).
In all OECD and partner countries, younger adults (age 25-34) are better educated than their older peers. In
most OECD countries, the share of the population without upper secondary education among younger adults
is less than 20% (see Indicator A1). This generational change has an impact in the labour-market outcomes
for graduates: on average across OECD countries, 81% of younger adults who have gone beyond compulsory
education are employed, compared to 60% who have not completed upper secondary education (Table A3.2 and
(OECD, 2018[5]).
For younger adults in Argentina, Brazil, Chile, France, Indonesia, Ireland, Israel, Korea, Latvia, Lithuania, Mexico,
Poland, South Africa, Turkey and the United States, a tertiary degree has an employment advantage of 10 percentage
points or more compared to younger adults with only upper secondary or post-secondary non-tertiary education
(Table A3.2).
Educational attainment and employment and gender
In all OECD and partner countries except Norway and Portugal, employment rates are lower for women than for
men, regardless of the educational attainment level.
Employment rates are particularly low for women without upper secondary education. On average across OECD
countries, the employment rate of younger women without upper secondary education is 45%, compared to 71%
for their male peers. In most OECD and partner countries, less than half of young women without upper secondary
education are employed, but the employment rate of women is lowest in Saudi Arabia and Turkey, where only one in
four women with below upper secondary education are employed (Figure A3.1).
In contrast, in half of OECD countries, the employment rates of younger men (age 25-34) without upper secondary
education exceed 70%. Almost full employment (more than 90%) of young men is reached in Colombia, Indonesia,
Mexico and Saudi Arabia, but these high employment rates of younger men seem to be achieved at the expense of
younger women, as women’s employment rates in these countries are between 40 and 70 percentage points lower. In
a few countries, such as Iceland, Luxembourg and Portugal, younger men without upper secondary education have
relatively high employment rates (around 80%), with concurrent high employment rates for women (about 70%)
(Figure A3.1).

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Disparities by gender in employment rates narrow as educational attainment increases. On average across
OECD countries, the gender difference in employment rates among 25-34 year-olds without upper secondary
qualification is 25 percentage points (71% for men and 45% for women). This difference shrinks to 16 percentage
points among individuals with upper secondary or post-secondary non-tertiary education (84% for men and
68% for women) and 9 percentage points among tertiary-educated men and women (89% for men and 80% for
women) (Table A3.2).
Educational attainment and unemployment
In many OECD and partner countries, unemployment rates are especially high among younger adults (age 25-34).
On average across OECD countries, the unemployment rate is almost twice as high for those who have not completed
upper secondary education: 15% compared to 8% for those with upper secondary or post-secondary non-tertiary
education. The unemployment rate of tertiary-educated younger adults is only 6% (Table A3.3).
The situation is especially severe for younger adults without an upper secondary education in the Slovak Republic
and South Africa, where the unemployment rate for this group exceeds 30%. It is also very high in France, Greece
and Spain, where about 25% of these younger adults are unemployed (Table A3.3).
Having attained upper secondary education or above reduces the risk of unemployment. The positive impact
of further education on the unemployment rate is especially high in Australia, Austria, Germany, Hungary,
the Slovak Republic, Sweden and Switzerland. In all these countries, the unemployment rate for younger adults
with an upper secondary or post-secondary non-tertiary education is about one-third the unemployment rate for
younger adults with below upper secondary education (Table A3.3).
While unemployment rates for 25-34 year-olds in many countries improve only slightly with education beyond upper
secondary or post-secondary non-tertiary education, the positive effect of tertiary education on unemployment
rates in this age group is especially high in Argentina, the Czech Republic, Estonia, France, Iceland, Ireland, Latvia,
New Zealand, Poland, the Russian Federation and the United States. In these countries, unemployment rates for
25-34 year-olds with tertiary attainment are about half the rates of younger adults with an upper secondary or
post-secondary non-tertiary education. In Lithuania and South Africa, the unemployment rate of tertiary-educated
younger adults is only one-third of their lower educated peers (Table A3.3).
In Costa Rica, Iceland, Israel, Korea, Mexico, Portugal and Turkey, unemployment rates are similar across educational
attainment levels. In a few countries, the relationship between unemployment rates and educational attainment
levels is reversed. In Saudi Arabia, for example, 20% of tertiary-educated younger adults are unemployed, compared
to only 2% of those who have not completed upper secondary education (Table A3.3).
Educational attainment and inactivity
The percentage of inactive people (i.e. individuals not employed and not looking for a job) is higher among those
with lower educational attainment levels. On average across OECD countries, around 35% of adults aged 25‑64
who have not completed upper secondary education were inactive in 2017, compared to 20% of adults with
upper secondary or post-secondary non-tertiary education and around 10% of adults with a tertiary degree
(OECD, 2018[5]).
Women have consistently higher inactivity rates than men across all educational attainment levels, but the rates
are especially high among those who have not completed upper secondary education. The difference in inactivity
rates for men and women with below upper secondary education is 22 percentage points, while the difference for
those with upper secondary or post-secondary non-tertiary education is 14 percentage points, and the difference
for those with tertiary education is 8 percentage points (Figure A3.2).
The gender gap in inactivity rates of adults without upper secondary education is highest in Saudi Arabia
(76 percentage points) and Turkey (50 percentage points), and the gap is 40 percentage points or more in Chile,
Costa Rica and Mexico. Even though the difference in inactivity rates of men and women decreases with higher
educational attainment levels, in one-third of OECD countries, the gender gap in activity rates of adults with tertiary
education is still more than 10 percentage points, and it is above 20 percentage points in Korea (26 percentage
points) and Saudi Arabia (39 percentage points) (Figure A3.2).
In only a few countries, including Lithuania, Norway, Portugal and Slovenia, the gender gap in inactivity rates of
tertiary-educated adults is almost closed (less than 3 percentage points) (Figure A3.2).
Education at a Glance 2018: OECD Indicators   © OECD 2018

73

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Figure A3.2. Gender differences in inactivity rates, by educational attainment (2017)

A3

25-64 year-olds, percentage-point difference (inactivity rate for women minus inactivity rate for men)
76

Percentage
points

Below upper secondary
Upper secondary or post-secondary non-tertiary
Tertiary

50
40
30
20

0

Saudi Arabia1 (32%)
Turkey (35%)
Mexico (30%)
Costa Rica (27%)
Chile1 (24%)
Argentina (22%)
Indonesia (24%)
Israel (19%)
Colombia (18%)
Italy (28%)
Brazil1 (24%)
Ireland (21%)
Greece (24%)
Poland (24%)
United States (23%)
Netherlands (17%)
OECD average (20%)
Canada (18%)
Belgium (23%)
Hungary (21%)
Korea (23%)
Spain (19%)
EU22 average (19%)
Denmark (17%)
South Africa (26%)
Germany (16%)
Czech Republic (17%)
Russian Federation1 (20%)
France (21%)
Finland (18%)
United Kingdom2 (18%)
Slovak Republic (20%)
Latvia (17%)
Luxembourg (20%)
Australia (19%)
New Zealand (14%)
Austria (20%)
Switzerland (13%)
Portugal (17%)
Estonia (15%)
Slovenia (22%)
Sweden (11%)
Norway (17%)
Iceland (10%)
Lithuania (15%)

10

Note: The percentage in parentheses shows the inactivity rate of 25-64 year-old adults.
1. Year of reference differs from 2017. Refer to Table A3.1 for details.
2. Data for upper secondary attainment include completion of a sufficient volume and standard of programmes that would be classified individually
as completion of intermediate upper secondary programmes (17% of adults aged 25-64 are in this group).
Countries are ranked in descending order of the gender differences in inactivity rates of the population with below upper secondary education.
Source: OECD / ILO (2018), Education at a Glance Database, http://stats.oecd.org/. See Source section for more information and Annex 3 for notes
(http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933802076

Overall trends in employment rates by educational attainment
Since the Great Recession in the late 2000s and early 2010s, employment rates have returned to the level they were
a decade earlier in most OECD and partner countries. On average across OECD countries, regardless of educational
attainment, about 75% of adults (age 25-64) were employed in 2017, which is similar to 2007 levels. However, these
trends hide diverging employment trends of younger adults (age 25-34) and older adults (age 55-64) (OECD, 2018[5]).
On average across OECD countries, the employment rate of 25-34 year-olds with tertiary education was about 85% in
2007 and 2017. In a few countries, including Indonesia, Japan and New Zealand, the employment rate for these
younger adults has increased over the last decade, but the opposite tendency can be observed in many countries.
In Costa Rica, Denmark, Greece, Italy, the Slovak Republic, Slovenia and Spain, the employment rate of younger
adults with tertiary education is 5 or more percentage points lower in 2017 than it was in 2007. Some of these
countries are especially hit by the Great Recession, and their economies have not yet recovered fully (Figure A3.3).
In contrast, on average across OECD countries, the employment rates of 55-64 year-olds with tertiary education
have increased by 6 percentage points, from 67% in 2007 to 73% in 2017 (Figure A3.3). The increase in employment
rates of older adults can be partly explained by the fact that, on average across 24 OECD countries with available
data, the age of labour-market exit (effective retirement age) has increased over the last 15 years for both men and
women. In contrast, from the 1970s to the late 1990s, the average retirement age was decreasing. The age of labourmarket exit in 2017 was 64.3 on average across the OECD, and it was 1.5 years lower for women than for men.
However, beyond the OECD average statistics, there are vast differences across countries. The average effective age
of labour-market exit ranges from 60.2 in France and the Slovak Republic to 72.1 in Korea. It is lower than 62 in
Belgium, France, Luxembourg and the Slovak Republic and higher than 66 in Chile, Iceland, Israel, Japan, Korea,
Mexico, New Zealand and Turkey (OECD, 2017[6]).

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Figure A3.3. Trends in employment rates of 25-34 and 55-64 year-olds with tertiary education
(2007 and 2017)

%

55-64 year-olds
2007
2017

25-34 year-olds
2007
2017

95
90
85
80
75
70
65
60
55

45

Iceland
New Zealand
Sweden
Norway
Switzerland
Italy
Lithuania
Germany
Czech Republic
Netherlands
Estonia
Israel
Latvia
Saudi Arabia1
Denmark
Japan
Chile1
Finland
OECD average
Australia
South Africa
United States
EU22 average
Argentina
Korea
Portugal
Slovak Republic
Austria
Ireland
Colombia
Poland
Hungary
Luxembourg
Indonesia
Spain
Slovenia
United Kingdom2
Canada
Belgium
France
Brazil1
Mexico
Costa Rica
Russian Federation1
Greece
Turkey

50

1. Year of reference differs from 2017. Refer to Table A3.2 for details.
2. Data for upper secondary attainment include completion of a sufficient volume and standard of programmes that would be classified individually
as completion of intermediate upper secondary programmes (17% of adults aged 25-64 are in this group).
Countries are ranked in descending order of the employment rate of tertiary-educated 55-64 year-olds in 2017.
Source: OECD / ILO (2018), Education at a Glance Database, http://stats.oecd.org/. See Source section for more information and Annex 3 for notes
(http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933802095

In more than half of OECD countries, the employment rates of older adults with tertiary education have increased
by at least 5 percentage points over the last decade. In many of these countries, employment rates increased by more
than 10 percentage points, with the highest increases in Italy and Poland (Figure A3.3).
The increase in employment rates of older adults over time can be observed across educational attainment levels.
On average across OECD countries, the employment rate of 55-64 year-olds without upper secondary education
has increased by 6 percentage points, from 40% in 2007 to 46% in 2017. Over the same period, the employment
rate increased by 8 percentage points (from 52% to 60%) for those with an upper secondary or post-secondary
non‑tertiary education and by 6 percentage points (from 67% to 73%) for tertiary graduates (OECD, 2018[5]).
On average across OECD countries and different educational attainment levels, the gender gap in employment rates
among younger adults has remained more or less stable over the last decade, but it has evolved differently across
countries (Table A3.2).
In most OECD and partner countries, the gender gap in employment rates of adults without upper secondary
education has fallen between 2007 and 2017. In most of these countries, this decline is due to a decreasing
employment rate for men, rather than an increasing employment rate for women. The decline in the gender gap due
to rising employment rates for younger women is highest in Korea (16 percentage points), where the employment
rate of young women (age 25-34) without upper secondary education rose from 42% in 2007 to 58% in 2017, while
the employment rate of young men remained stable (about 70% in 2007 and 2017) (Table A3.2).
In a few countries, the gender gap has increased for younger adults (age 25-34) with low educational attainment.
In Lithuania, Poland and Slovenia, for example, the employment rates of younger women without secondary
education have declined much faster than those of younger men, leading to an increase in the gender gap of 5 or
more percentage points (Table A3.2).
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Labour-market outcomes for foreign-born adults by educational attainment
The labour-market outcomes for foreign-born adults compared to native-born adults vary widely across OECD and
partner countries. For both native-born and foreign-born adults, the likelihood of being employed increases with
higher educational attainment, but it increases more steeply for native-born adults than for foreign-born adults
(Table A3.4).
Among countries with available data, there are both higher and lower levels of employment rates for adults
without upper secondary education for native-born versus foreign-born adults. For example, in Chile, Hungary,
Israel, Italy, Luxembourg, Portugal and the United States, the employment rates of foreign-born adults without
upper secondary education are more than 10 percentage points higher than those of their native-born peers. In
contrast, in Denmark, the Netherlands and Sweden, the employment rates of foreign-born adults are more than
10 percentage points lower than those of their native-born peers. The difference between the employment rates
of native-born and foreign-born adults may vary depending on the age at arrival in the country for foreign-born
adults (Table A3.4).

Figure A3.4. Employment rates of native- and foreign-born 25-64 year-olds
with tertiary education, by age at arrival in the country (2017)
Native-born adults

(0%)

(9%)

Mexico

Greece

Costa Rica (11%)

(1%)

Italy (14%)

Slovak Republic

Spain (16%)

United States (19%)

(3%)
1

Chile

(2%)
Hungary

Canada (28%)

(4%)
Czech Republic

OECD average (17%)

Ireland (22%)

EU22 average (15%)

France (15%)

Australia (34%)

Belgium (21%)

Portugal (10%)

Israel (25%)

Denmark (14%)

(1%)
Poland

Slovenia (12%)

Latvia (11%)

Austria (24%)

Luxembourg (57%)

Germany (21%)

Netherlands (15%)

(5%)
Lithuania

New Zealand (33%)

Sweden (24%)

Estonia (12%)

Foreign-born adults
Arrived in the country by the age of 15
Arrived in the country at 16 or older
Age at arrival unknown

%

100
95
90
85
80
75
70
65
60
55
50

Switzerland (36%)

A3

Note: The percentage in parentheses represents the share of foreign-born adults among 25-64 year-olds.	
1. Year of reference differs from 2017. Refer to the source table for details.	
Countries are ranked in descending order of the employment rate of tertiary-educated native-born adults.
Source: OECD / ILO (2018), Table A3.4. See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933802114

While labour-market outcomes for foreign-born adults without upper secondary education are mixed across OECD
and partner countries, foreign-born adults with tertiary education have lower employment prospects than their
native-born peers in most countries with data. In Austria, Belgium, Denmark, Estonia, France, Germany, Greece,
Italy, Latvia, the Netherlands, Spain and Sweden, the gap in the employment rate between tertiary-educated
native‑born and foreign-born adults is more than 10 percentage points, systematically in favour of tertiary-educated
native-born adults (Table A3.4).
For foreign-born adults with a tertiary degree, the age at arrival in the country determines employment prospects.
In most countries, the employment rates for foreign-born adults who arrived by age 16 are higher than for those who
arrived in the country at a later age. For instance, in Greece, Italy and Portugal, early arrival yields an employment
advantage of around 20 percentage points (Figure A3.4).

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Since foreign-born adults who arrived in the country at an early age have spent some years in the education system
of the host country and gained credentials recognised by the host country, their labour-market outcomes are better
than of those who arrived at a later age with a foreign qualification. Foreign-born adults often face problems getting
their education and experience recognised in their host country. The challenges they face in getting their credentials
valued in the host country also explain why they are often overqualified for their positions (OECD, 2017[3]).
In addition, foreign-born adults generally have fewer alternatives in terms of family support than native-born adults.
They also generally have lower unemployment insurance and fewer possibilities of returning to school (OECD,
2017[3]). As shown in the European Union Minorities and Discrimination Survey (FRA, 2017[7]), foreign-born adults
also often face discrimination when looking for work, particularly foreign-born adults from North Africa. Thus,
foreign-born workers are likely to have a lower reservation wage (the lowest wage rate at which a worker would be
willing to accept a particular type of job), and this implies that they are more likely to accept any job they can get.
This may explain the fact that, in many countries, the employment rate for foreign-born adults with low educational
attainment is higher than for their native-born peers.

Box A3.1. Qualification match or mismatch among workers
The objectives of formal education are very broad, but preparation for an active life in society through gainful
employment is an important one, conditioning well-being to a large extent. The educational qualifications of
workers and the educational requirements of jobs meet in the labour market. Qualification matching through
this process is a measure of the close links between the education system and the labour market. The first
two international reports of the Survey of Adult Skills (PIAAC) (see Source section at the end of this indicator)
have presented highlights of qualification mismatch, suggesting that overqualification is particularly common
among foreign-born workers and those employed in small establishments, in part-time jobs or on fixed-term
contracts (OECD, 2013[8]; OECD, 2016[9]).
At the individual level, a qualification mismatch occurs when an individual works in a job that does not require
the level of formal education the worker holds (i.e. being overqualified or underqualified) (see Definitions and
Methodology sections at the end of this indicator). Being in one of these two types of mismatch is likely to
have an impact on earnings (see Box A4.1 in Indicator A4). Aggregated at the national level, overqualification
may be the result of an oversupply of qualified workers relative to the structure of jobs in the economy, while
underqualification may be the result of workers succeeding in having their skills valued beyond their formal
educational attainment.
Overqualification and underqualification are present to varying extents
Across countries and economies that participated in the Survey of Adult Skills (PIAAC), a large majority of
workers report having a level of education that corresponds to the level needed for their job (Figure A3.a).
For example, on average, 85% of workers with a qualification of upper secondary education (ISCED 3) or below
reported working in a job that requires this level of education. Among workers with a qualification of tertiarytype A or advanced research programmes (ISCED 5A or 6), 75% reported being in a similarly well-matched
situation. For adults with a tertiary-type B degree (ISCED 5B), the match between the level of education
attained and the level of education required on the job is not as high, but this is probably due to the fact that
these levels of education are less common and, therefore, fewer employers are asking for such qualifications
(Figure A3.a).
On average across OECD countries and economies that participated in the Survey of Adult Skills (PIAAC), 15% of
workers reported being overqualified for their job (which means having a qualification of ISCED 5A or 6 while
working in a job needing ISCED 3 or below). The highest shares are observed in England (United Kingdom)
and Japan, where over 25% of workers reported being in this situation (Figure A3.a and Table A3.a, available
on line).
In contrast, on average only 5% of workers reported being underqualified for their job (which means having
a qualification of ISCED 3 or below while working in a job needing ISCED 5A or 6). The shares are highest
in Finland, Israel, Italy and the Netherlands, where at least 10% of workers reported being in this situation
(Figure A3.a, and Table A3.a, available on line).

…

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Figure A3.a. Qualification match or mismatch among workers (2012 or 2015)
Survey of Adult Skills (PIAAC), employed 25-64 year-olds, OECD average
ISCED 5A or 6 needed for the job
ISCED 5B needed for the job
ISCED 4 needed for the job
ISCED 3 or below needed for the job

%

100
90
80
70
60
50
40
30
20
10
0

5
6
6

83

Underqualified

19

Underqualified

41

Well matched

73

Overqualified

10
3

Well matched

Well matched
9

30

14

ISCED 3 or below attained (56%)

ISCED 5B attained (13%)

Overqualified

ISCED 5A or 6 attained (27%)

Note: The percentage in parentheses represents the proportion of workers with this level of education. The values were redistributed to add up
to 100%. Data from the Survey of Adult Skills (PIAAC) are based on ISCED-97. The labels “underqualified”, “well matched” and “overqualified”
have been added to ease the reading, but in some cases the boundaries between ISCED levels can be blurred. See Definitions, Methodology and
Source sections for more information.
Source: OECD (2018), Table A3.a, available on line. See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/
eag-2018-36-en).
1 2 https://doi.org/10.1787/888933802133

Migration status and age
Among personal characteristics that may be associated with various situations of overqualification and
underqualification, whether one is born in the country of present residence is a major factor in most countries
with a sizeable immigrant population. In Norway and Sweden, the share of overqualified workers is at least
three times as large among immigrants as among the native-born population. In addition to other issues such
as language or culture, credential recognition is a serious problem for first-generation immigrants with higher
levels of education seeking a job that matches their level of education (Table A3.b, available on line).
Age is often closely associated with experience in the labour market, and it also plays a role in both mismatched
situations. On the one hand, young people may accept jobs below their qualification in order to enter the
labour market. On the other hand, older workers may succeed in having their skills and further training
valued beyond their formal educational attainment. Both situations would lead to different age patterns
among overqualified and underqualified workers. Data from the Survey of Adult Skills (PIAAC) support this
hypothesis, showing that the mean age among overqualified workers is 39, seven years younger than the mean
age among underqualified workers (46) (Table A3.b, available on line).
Numeracy skills
Skills are far from homogeneous at any level of formal education, and skills are an important driver for individual
employment and economic outcomes (OECD, 2015[10]). On average among similarly-educated adults, numeracy
skills tend to be lower among those who are overqualified than among those who are well matched (Figure A3.b).
This implies that a formal qualification does not guarantee finding a job corresponding to one’s educational
attainment. Formal qualifications should also be accompanied by good skills. Otherwise, there is a higher
likelihood of ending up in a job where the education requirements are below the acquired qualification.
The same pattern holds for all countries and economies that participated in the Survey of Adult Skills (PIAAC),
with only a few exceptions where data on the overqualified are missing or where the differences are not
statistically significant. Among tertiary-educated adults holding an ISCED 5A or 6 degree, the largest differences
in the mean numeracy score between well-matched and overqualified workers are observed in Canada, Denmark,
Israel and Norway, where the gap is above 30 score points (which is equivalent to over four years of schooling).

…

78

Education at a Glance 2018: OECD Indicators   © OECD 2018

chapter A

How does educational attainment affect participation in the labour market? – INDICATOR A3

Under embargo until 11/09/2018 at 11.00am CEST
In contrast, the difference between well-matched and overqualified workers is not statistically significant in ten
countries or economies (Figure A3.b).

Figure A3.b. Mean numeracy score among adults with ISCED 5A or 6,
by selected qualification match or mismatch among workers (2012 or 2015)
Survey of Adult Skills (PIAAC), employed 25-64 year-olds

Chile2

Turkey1, 2

Russian Federation*1

Italy1

Spain

Greece1, 2

Israel2

Poland

Ireland

Korea

Lithuania1, 2

United States

Slovenia1, 2

OECD average

Northern Ireland (UK)1

Canada

Estonia

Australia

England (UK)

New Zealand2

France

Norway

Slovak Republic1

Germany

Netherlands

Sweden

Austria1

Finland

Japan

Czech Republic1

Flemish Comm. (Belgium)

340
330
320
310
300
290
280
270
260
250
240

Denmark

ISCED 5A or 6 degree working in a job needing the same level of qualification (well matched)
ISCED 5A or 6 degree working in a job needing ISCED 3 or below (overqualified)

Mean score

Note: Some data points are not displayed because there are too few observations to provide a reliable estimate. Data from the Survey of
Adult Skills (PIAAC) are based on ISCED-97. See Definitions, Methodology and Source sections for more information.
1. The difference between well-matched and overqualified workers is not statistically significant at 5%.
2. Reference year is 2015; for all other countries and economies the reference year is 2012.
* See note on data for the Russian Federation in the Source section.							
Countries are ranked in descending order of the mean score of adults reporting having an educational attainment equivalent to what is needed for their job
(well matched).
Source: OECD (2018), Table A3.c, available on line. See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/
eag-2018-36-en).
1 2 https://doi.org/10.1787/888933802152

Box A3.1 Tables

WEB Table A3.a

Qualification match or mismatch among workers and distribution of educational attainment
among workers (2012 or 2015)

WEB Table A3.b

Selected qualification mismatches among workers, by mean age and native-born/foreign-born
status (2012 or 2015)

WEB Table A3.c

Mean numeracy score among adults with ISCED 5A and 6, by selected qualification match
or mismatch among workers (2012 or 2015)

Subnational variations in labour-market outcomes by educational attainment level
On average across the 19 OECD and partner countries with subnational data on labour-force status, employment
rates tend to vary more across regions among those with lower levels of education than among those with higher
levels of education. For example, in the United States (one large country with many subnational regions), among
adults who have not completed upper secondary education, the employment rate ranges from 32% to 68% between
states while, among adults with upper secondary education, the employment rate ranges from 60% to 79% between
states (OECD/NCES, 2018[11]).
Education at a Glance 2018: OECD Indicators   © OECD 2018

79

A3

chapter A The Output of Educational Institutions and the Impact of Learning
Under embargo until 11/09/2018 at 11.00am CEST

A3

In general, the regional variation in employment rates is the lowest among adults with tertiary education. In most
countries, the difference in the employment rate in the subnational region with the lowest and the highest rate is
below 10 percentage points. The Russian Federation (another large country with many subnational regions) is the
country with the largest disparities, with a low of 69% and a high of 93% (OECD/NCES, 2018[11]).
In many countries, employment rates in the region including the capital city are above the country average, regardless
of educational attainment level. In Spain, for example, the employment rate for adults who have not completed
upper secondary education in the capital city region is 60%, 4 percentage points higher than the country average
of 56%. This is also the case for most other educational attainment levels. In contrast, in Austria and Germany,
employment rates in the capital region are below the country average, regardless of educational attainment level
(OECD/NCES, 2018[11])

Definitions
Active population (labour force) is the total number of employed and unemployed persons, in accordance with the
definition in the Labour Force Survey.
Age groups: Adults refer to 25-64 year-olds; younger adults refer to 25-34 year-olds; and older adults refer to
55‑64 year-olds.
Educational attainment refers to the highest level of education attained by a person.
Employed individuals are those who, during the survey reference week, were either working for pay or profit for at
least one hour or had a job but were temporarily not at work. The employment rate refers to the number of persons
in employment as a percentage of the working-age population.
Inactive individuals are those who, during the survey reference week, were neither employed nor unemployed
(i.e. individuals who are not looking for a job). The inactivity rate refers to inactive persons as a percentage of the
population (i.e. the number of inactive people is divided by the number of all working-age people).
Levels of education: See the Reader’s Guide at the beginning of this publication for a presentation of all ISCED 2011
levels.
The previous classification, ISCED-97, is used for the analyses based on the Survey of Adult Skills (PIAAC) in
Box A3.1. The levels of education are defined as follows: below upper secondary corresponds to levels 0, 1, 2
and 3C short programmes; upper secondary corresponds to levels 3A, 3B and 3C long programmes; post-secondary
non-tertiary corresponds to levels 4A and 4B; and tertiary corresponds to levels 5B, 5A and 6. ISCED 5A consists
of largely theory-based programmes designed to provide sufficient qualifications for entry to advanced research
programmes and professions with high skill requirements, such as medicine, dentistry or architecture. Duration
is at least three years full time, although usually four or more years. These programmes are not exclusively offered
at universities, and not all programmes nationally recognised as university programmes fulfil the criteria to be
classified as tertiary-type A. Tertiary-type A programmes include second-degree programmes, such as the American
master’s degree. ISCED 5B consists of programmes that are typically shorter than those of tertiary-type A and focus
on practical, technical or occupational skills for direct entry into the labour market, although some theoretical
foundations may be covered. They have a minimum duration of two years full-time equivalent at the tertiary level.
ISCED 6 consists of programmes that lead directly to the award of an advanced research qualification (e.g. PhD).
The theoretical duration of these programmes is three years, full time, in most countries (for a cumulative total of
at least seven years full-time equivalent at the tertiary level), although the actual enrolment time is typically longer.
Programmes are devoted to advanced study and original research.
Qualification match/mismatch: For the analysis in Box A3.1, an overqualified worker is defined as a job holder who
has attained an education at ISCED 5A or 6 while holding a job that needs only ISCED 3 or less. An underqualified
worker is defined as a job holder who has attained ISCED 3 or below while holding a job that needs ISCED 5A
or 6. A well-matched worker is an individual reporting working in a job that needs his/her level of education. The
ISCED-97 categories used for analysis in Box A3.1 are: ISCED 0-3, ISCED 4, ISCED 5B and ISCED 5A-6.
Unemployed individuals are those who, during the survey reference week, were without work, actively seeking
employment, and currently available to start work. The unemployment rate refers to unemployed persons as
a percentage of the labour force (i.e. the number of unemployed people is divided by the sum of employed and
unemployed people).
The working-age population is the total population aged 25-64.

80

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How does educational attainment affect participation in the labour market? – INDICATOR A3

chapter A

Under embargo until 11/09/2018 at 11.00am CEST

Methodology

A3

For information on methodology, see Indicator A1.
The match or mismatch presented in Box A3.1 is dependent on the number of education levels selected. In
this analysis, educational attainment is classified in four groups; breaking that down further into more groups
would result in a higher mismatch. This caution is especially relevant for the category “ISCED 3 or below”, which
encompasses four different attainment levels (ISCED 0 to 3) and represents over 50% of workers. It is also important
to note that the mismatch presented in this analysis does not reflect misalignments between the field of study of
the worker and what is needed for the job. The definitions of overqualification and underqualification can vary
across the different studies on the topic. The question asked by the Survey of Adult Skills on job requirements is the
following: “Still talking about your current job: If applying today, what would be the usual qualifications, if any, that
someone would need to get this type of job?”. The analysis focuses on the comparison between ISCED 3 or below
with ISCED 5A or 6 and does not look at the situation for ISCED 4 and 5B. This decision is driven by the blurred
boundary between ISCED 5B and ISCED 5A or 6, and it also takes into account the fact that the ISCED 4 level is
not well defined in the labour market. For more information on the methodology used in Box A3.1, please see the
Methodology section in Indicator A7.
Please see the OECD Handbook for Internationally Comparative Education Statistics 2018 (OECD, 2018[12]) for more
information and Annex 3 for country-specific notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Lithuania was not an OECD member at the time of preparation of this publication. Accordingly, Lithuania does not
appear in the list of OECD members and is not included in the zone aggregates.

Source
For information on sources, see Indicator A1.
Data on subnational regions for selected indicators are released by the OECD, with the support from the
US National Centre for Education Statistics (NCES), and 19 countries have submitted their data for this edition
of Indicator A3: Australia, Austria, Belgium, Canada, Colombia, Finland, Germany, Greece, Ireland, Italy, Poland,
the Russian Federation, Slovenia, Spain, Sweden, Switzerland, Turkey, the United Kingdom and the United States.
Subnational estimates were provided by countries using national data sources or by Eurostat based on data for
Level 2 of the Nomenclature of Territorial Units for Statistics (NUTS 2). For the United Kingdom, the subnational
regions are based on NUTS 1.
Data used in Box A3.1 are based on the OECD Programme for the International Assessment of Adult Competencies
(the Survey of Adult Skills [PIAAC]).
Note regarding data from Israel
The statistical data for Israel are supplied by and are under the responsibility of the relevant Israeli authorities. The use
of such data by the OECD is without prejudice to the status of the Golan Heights, East Jerusalem and Israeli settlements
in the West Bank under the terms of international law.
Note regarding data from the Russian Federation in the Survey of Adult Skills (PIAAC)
The sample for the Russian Federation does not include the population of the Moscow municipal area. The data published,
therefore, do not represent the entire resident population aged 16-65 in the Russian Federation but rather the population
of the Russian Federation excluding the population residing in the Moscow municipal area. More detailed information
regarding the data from the Russian Federation as well as that of other countries can be found in the Technical Report of the
Survey of Adult Skills, Second Edition (OECD, 2016 [13]).

References
Arntz, M., T. Gregory and U. Zierahn (2016), “The risk of automation for jobs in OECD countries: A comparative [1]
analysis”, OECD Social, Employment and Migration Working Papers, No. 189, OECD Publishing, Paris, http://dx.doi.
org/10.1787/5jlz9h56dvq7-en.
FRA (European Union Agency for Fundamental Rights) (2017), Second European Union Minorities and Discrimination [7]
Survey: Main Results, FRA, Vienna, http://dx.doi.org/10.2811/268615.
Education at a Glance 2018: OECD Indicators   © OECD 2018

81

chapter A The Output of Educational Institutions and the Impact of Learning
Under embargo until 11/09/2018 at 11.00am CEST

A3

Lane, M. and G. Conlon (2016), “The impact of literacy, numeracy and computer skills on earnings and employment [2]
outcomes”, OECD Education Working Papers, No. 129, OECD Publishing, Paris, http://dx.doi.org/10.1787/5jm2cv4t4gzs-en.
OECD (2018), Education at a Glance Database - Educational attainment and labour-force status, http://stats.oecd.org/Index. [5]
aspx?datasetcode=EAG_NEAC.
OECD (2018), OECD Handbook for Internationally Comparative Education Statistics 2018: Concepts, Standards, Definitions [12]
and Classifications, OECD Publishing, Paris, https://doi.org/10.1787/9789264304444-en.
OECD (2017), International Migration Outlook 2017, OECD Publishing, Paris, http://dx.doi.org/10.1787/migr_outlook- [3]
2017-en.
OECD (2017), Pensions at a Glance 2017: OECD and G20 Indicators, OECD Publishing, Paris, http://dx.doi.org/10.1787/ [6]
pension_glance-2017-en.
OECD (2016), Skills Matter: Further Results from the Survey of Adult Skills, OECD Skills Studies, OECD Publishing, Paris, [9]
http://dx.doi.org/10.1787/9789264258051-en.
OECD (2016), Technical Report of the Survey of Adult Skills, Second Edition, OECD, Paris, www.oecd.org/skills/piaac/PIAAC_ [13]
Technical_Report_2nd_Edition_Full_Report.pdf.
OECD (2015), Education at a Glance 2015: OECD Indicators, OECD Publishing, Paris, http://dx.doi.org/10.1787/eag-2015-en. [10]
OECD (2014), “Is migration good for the economy?”, Migration Policy Debates, www.oecd.org/migration/OECD%20 [4]
Migration%20Policy%20Debates%20Numero%202.pdf (accessed on 05 February 2018).
OECD (2013), OECD Skills Outlook 2013 : First results from the Survey of Adult Skills, OECD Publishing, Paris, http://dx.doi. [8]
org/10.1787/9789264204256-en.
OECD/NCES (2018), Education at a Glance Subnational Supplement, OECD/National Center for Education Statistics, Paris [11]
and Washington, DC, https://nces.ed.gov/surveys/annualreports/oecd/index.asp.

Indicator A3 Tables
1 2 https://doi.org/10.1787/888933801962

Table A3.1 Employment rates of 25-64 year-olds, by educational attainment (2017)
Table A3.2 Trends in employment rates of 25-34 year-olds, by educational attainment and gender (2007 and 2017)
Table A3.3 Employment, unemployment and inactivity rates of 25-34 year-olds, by educational attainment (2017)
Table A3.4 Employment rates of native- and foreign-born 25-64 year-olds, by age at arrival in the country
and educational attainment (2017)
Cut-off date for the data: 18 July 2018. Any updates on data can be found on line at http://dx.doi.org/10.1787/eag-data-en. More breakdowns can
also be found at http://stats.oecd.org/, Education at a Glance Database.

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How does educational attainment affect participation in the labour market? – INDICATOR A3

chapter A

Under embargo until 11/09/2018 at 11.00am CEST
Table A3.1. Employment rates of 25-64 year-olds, by educational attainment (2017)
Percentage of employed 25-64 year-olds among all 25-64 year-olds
Upper secondary or post-secondary
non-tertiary

Partners

OECD

Postsecondary
Upper
Below upper
secondary secondary non-tertiary

Total

A3

Tertiary
Short-cycle Bachelor’s or Master’s or Doctoral or
tertiary
equivalent equivalent equivalent

Total

All levels
of education

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

Australia
Austria
Belgium
Canada
Chile1
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan2
Korea
Latvia
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United Kingdom3
United States

59
54
47
56
62
51
62
65
53
53
60
50
55
77
51
52
52
x(2)
66
61
60
65
61
73
61
42
68
39
46
56
67
67
52
63
56

77
76
73
72
72
82d
81
79
73
73
80
58
77
88
70
74
71
79d
73
73
74
71
80
80
79
69
82
75
70
70
87
82d
63
83
70d

83
81
87
79
a
x(2)
93
78
c
66
86
63
84
95
75
a
75
x(5)
a
73
80
a
84
87
85
73
83
77
a
78
83
x(2)
a
a
x(2)

78
77
73
74
72
82
81
79
74
73
82
59
78
90
72
74
71
m
73
73
75
71
80
83
80
70
82
75
70
70
86
82
63
81
70

82
86
81
81
80
88
85
81
82
84
90
63
86
89
80
84
c
79d
77
86
82
70
87
88
82
67
c
91
78
79
85
x(6, 7, 8)
66
82
78

85
80
84
83
86
81
84
84
84
84
88
71
83
92
85
87
73
88d
78d
86
81
80
88
89
90
85
83
73
89
79
90
88d
77
86
82

84
89
87
85d
95d
87
89
88
87
88
88
83
88
95
89
90
83
x(6)
x(6)
90
89
87
91
88
93
89
88
83
88
84
92
88d
85
86
85

89
92
93
x(7)
x(7)
92
94
94
97
90
93
85
93
98
90
93
93
x(6)
x(6)
98
93
89
95
93
95
98
92
86
93
90
93
92d
93
88
90

84
86
85
82
84
86
86
86
85
85
89
72
85
93
85
87
81
84d
77
88
86
80
89
89
89
88
87
82
87
81
89
88
75
85
82

77
76
72
77
71
81
79
80
76
73
81
61
76
88
74
78
65
82
74
76
76
69
79
83
80
73
76
74
73
68
84
83
59
80
74

OECD average
EU22 average

58
55

75
75

80
79

76
76

81
82

84
83

88
87

92
92

85
85

76
75

Argentina
Brazil1
China
Colombia
Costa Rica
India
Indonesia
Lithuania
Russian Federation4
Saudi Arabia5
South Africa

65
65
m
72
64
m
73
52
51
60
43

74
74d
m
75d
69
m
74
71
68
65
55

a
x(2)
m
x(2)
c
m
m
77
75
a
74

74
74
m
75
69
m
74
73
72
65
58

x(6)
x(9)
m
x(9)
71
m
78
a
77
x(6)
82

85d
x(9)
m
x(9)
83
m
87
90
88
75d
85

x(6)
x(9)
m
x(9)
89d
m
94
91
85
x(6)
85d

x(6)
x(9)
m
x(9)
x(7)
m
98
94
89
x(6)
x(7)

85
83
m
83
81
m
85
91
81
75
85

73
71
m
75
69
m
75
79
75
65
56

G20 average

m

m

m

m

m

m

m

m

m

m

Note: In most countries data refer to ISCED 2011. For Indonesia and Saudi Arabia data refer to ISCED-97. See Definitions and Methodology sections for more
information. Data and more breakdowns are available at http://stats.oecd.org/, Education at a Glance Database.
1. Year of reference 2015.
2. Data for tertiary education include upper secondary or post-secondary non-tertiary programmes (less than 5% of adults are in this group).
3. Data for upper secondary attainment include completion of a sufficient volume and standard of programmes that would be classified individually as completion of
intermediate upper secondary programmes (17% of adults aged 25-64 are in this group).
4. Year of reference 2016.										
5. Year of reference 2014.										
Source: OECD/ILO (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933801981

Education at a Glance 2018: OECD Indicators   © OECD 2018

83

chapter A The Output of Educational Institutions and the Impact of Learning
Under embargo until 11/09/2018 at 11.00am CEST
Table A3.2. Trends in employment rates of 25-34 year-olds, by educational attainment and gender

A3

(2007 and 2017)

Percentage of employed 25-34 year-olds among all 25-34 year-olds
Upper secondary
or post-secondary non-tertiary

Below upper secondary

Partners

OECD

Men

Women

Total

Men

Women

Tertiary

Total

Men

Women

Total

2007

2017

2007

2017

2007

2017

2007

2017

2007

2017

2007

2017

2007

2017

2007

2017

2007

2017

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

(13)

(14)

(15)

(16)

(17)

(18)

Australia
Austria
Belgium
Canada
Chile1
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan2
Korea
Latvia
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United Kingdom3
United States

80b
78
69b
70
m
66b
84b
77
74
75
68b
89b
60
90
74b
61b
81b
m
71b
79
90b
93
88b
80
77
61b
87
27b
78b
85
75b
84b
83b
78b
77

65
64
60
65
79
71
66
79
58
64
65
70
73
82
56
74
65
m
70
76
83
92
75
81
68
59
80
48
75
69
73
71
84
76
69

46b
56
44b
50
m
35b
63b
53
53
45
42b
43b
33
74
45b
22b
42b
m
42b
52
71b
40
59b
56
61
38b
71
21b
59b
58
51b
59b
20b
44b
46

44
46
37
42
43
38
41
50
m
37
43
31
43
72
31
44
34
m
58
56
72
42
50
52
52
30
68
32
43
51
55
58
27
49
42

64b
65
58b
62
m
50b
74b
69
66
61
55b
71b
47
83
62b
45b
64b
m
61b
70
81b
64
75b
69
70
51b
80
24b
70b
74
64b
70b
49b
60b
64

55
56
50
57
61
54
56
69
48
52
55
54
58
78
46
62
52
m
64
70
78
66
65
68
61
48
76
40
64
61
66
65
54
63
57

91b
89
88b
86
m
93b
91b
95
85
89
82b
86b
87
93
90b
74b
83b
m
76b
91
88b
91
94b
92
90
84b
80
89b
89b
86
89b
91b
86b
90b
84

89
86
83
83
80
94
83
92
79
82
86
68
91
89
82
74
73
m
71
86
88
89
88
91
85
89
82
89
88
73
87
89
87
91
80

68b
73
72b
74
m
63b
82b
69
70
72
72b
62b
63
76
71b
58b
64b
m
51b
70
77b
58
83b
69
81
63b
77
62b
79b
72
79b
78b
31b
73b
68

67
83
70
70
57
66
72
68
67
66
79
48
69
80
63
66
53
m
54
69
79
54
77
68
74
60
82
62
76
65
81
82
35
75
66

81b
82
81b
81
m
79b
87b
83
78
81
77b
73b
76
86
81b
67b
73b
m
64b
81
83b
73
88b
82
86
74b
78
76b
85b
79
84b
84b
65b
82b
76

80
85
78
78
69
82
78
82
74
74
83
59
82
85
73
71
64
m
65
79
84
71
83
80
80
77
82
78
83
69
84
85
65
83
73

93b
92
91b
89
m
93b
91b
94
94
90
93b
84b
92
95
93b
87b
75b
92
84b
92
89b
90
96b
92
91
92b
87
93b
94b
89
89b
94b
87b
93b
92

91
89
89
89
89
93
85
94
90
90
90
75
94
96
90
90
69
93d
81
94
90
88
93
93
87
95
85
90
90
79
88
91
85
93
88

80b
83
89b
83
m
70b
86b
82
81
84
83b
77b
74
89
87b
81b
69b
69
65b
83
86b
77
92b
76
88
85b
84
76b
88b
82
86b
84b
68b
85b
81

79
85
86
84
83
71
81
75
79
84
84
63
74
90
85
84
65
79d
69
83
84
74
90
85
88
84
86
68
81
76
86
86
64
84
81

85b
87
90b
85
m
80b
89b
87
87
87
88b
80b
82
92
89b
84b
71b
80
74b
86
87b
83
94b
83
89
88b
85
83b
90b
85
87b
90b
79b
89b
86

84
87
87
86
85
80
83
83
83
87
87
68
82
93
87
87
66
86d
75
87
87
81
91
89
88
88
86
77
84
77
87
89
75
89
85

OECD average
EU22 average

76
75

71
68

48
49

45
44

63
63

60
58

88
88

84
85

69
71

68
70

79
80

77
78

91
91

89
88

81
82

80
80

85
86

84
83

Argentina
Brazil1
China
Colombia
Costa Rica
India
Indonesia
Lithuania
Russian Federation4
Saudi Arabia5
South Africa

m
88
m
m
94
m
92b
66b
m
m
m

84
83
m
90
85
m
91
57
65
94
47

m
56
m
m
45
m
46
53b
m
m
m

43
50
m
51
41
m
47
38
46
24
29

m
72
m
m
71
m
67b
61b
m
m
m

67
68
m
72
66
m
68
51
57
65
40

m
90
m
m
95
m
80b
87b
m
m
m

84
86
m
88
88
m
90
86
88
91
58

m
69
m
m
59
m
39b
75b
m
m
m

60
64
m
62
55
m
49
69
70
12
43

m
79
m
m
77
m
60b
81b
m
m
m

72
75
m
75
71
m
71
79
80
59
50

m
92
m
m
94
m
72b
92b
m
m
m

93
91
m
89
84
m
91
94
94
92
86

m
86
m
m
85
m
54b
89b
m
m
m

85
83
m
78
77
m
79
91
82
35
81

m
89
m
m
89
m
62b
90b
m
m
m

88
86
m
83
80
m
84
92
87
62
83

G20 average

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

Note: In most countries there is a break in the time series, represented by the code “b”, as data for 2017 refer to ISCED 2011 while data for 2007 years refer to
ISCED-97. For Indonesia and Saudi Arabia data refer to ISCED-97. See Definitions and Methodology sections for more information. Data and more breakdowns are
available at http://stats.oecd.org/, Education at a Glance Database.
1. Year of reference 2015 instead of 2017.
2. Data for tertiary education include upper secondary or post-secondary non-tertiary programmes (less than 5% of adults are in this group).
3. Data for upper secondary attainment include completion of a sufficient volume and standard of programmes that would be classified individually as completion of
intermediate upper secondary programmes (17% of adults aged 25-64 are in this group).			
4. Year of reference 2016 instead of 2017.
5. Year of reference 2014 instead of 2017.
Source: OECD/ILO (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933802000

84

Education at a Glance 2018: OECD Indicators   © OECD 2018

How does educational attainment affect participation in the labour market? – INDICATOR A3

chapter A

Under embargo until 11/09/2018 at 11.00am CEST
Table A3.3. Employment, unemployment and inactivity rates of 25-34 year-olds,

A3

by educational attainment (2017)

Partners

OECD

Employment and inactivity rates are measured as a percentage of all 25-34 year-olds; unemployment rates
as a percentage of 25-34 year-olds in the labour force
Employment rate

Unemployment rate

Inactivity rate

Below upper
secondary

Upper
secondary
or postsecondary
non-tertiary

Tertiary

Below upper
secondary

Upper
secondary
or postsecondary
non-tertiary

Tertiary

(1)

(2)

(3)

(4)

(8)

(9)

Australia
Austria
Belgium
Canada
Chile1
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan2
Korea
Latvia
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United Kingdom3
United States

Upper
secondary
or postsecondary
non-tertiary
(5)

55
56
50
57
61
54
56
69
48
52
55
54
58
78
46
62
52
m
64
70
78
66
65
68
61
48
76
40
64
61
66
65
54
63
57

80
85
78
78
69
82
78
82
74
74
83
59
82
85
73
71
64
m
65
79
84
71
83
80
80
77
82
78
83
69
84
85
65
83
73

84
87
87
86
85
80
83
83
83
87
87
68
82
93
87
87
66
86d
75
87
87
81
91
89
88
88
86
77
84
77
87
89
75
89
85

13.4
18.8
22.7
14.0
11.6
13.9
10.2
12.3
15.8
26.3
15.2
30.0
13.7
3.4
19.7
5.3
23.8
m
4.4
14.7
c
3.2
8.6
8.5
10.5
16.0
11.3
31.8
14.8
27.8
16.7
14.6
11.7
9.5
13.2

OECD average
EU22 average

60
58

77
78

84
83

Argentina
Brazil1
China
Colombia
Costa Rica
India
Indonesia
Lithuania
Russian Federation4
Saudi Arabia5
South Africa

67
68
m
72
66
m
68
51
57
65
40

72
75
m
75
71
m
71
79
80
59
50

G20 average

m

m

(6)

Below upper
secondary
(7)

4.4
5.5
9.0
7.5
9.2
3.2
5.6
6.0
9.8
12.7
3.8
28.1
3.8
3.8
9.7
5.8
15.7
m
7.0
9.7
4.0
4.4
4.7
5.0
4.7
6.1
10.0
8.9
8.3
18.4
5.3
4.7
11.3
3.8
6.2

4.1
3.7
4.7
5.0
6.7
1.6
7.8
3.0
5.6
5.8
2.8
25.4
2.4
1.9
4.2
3.8
13.7
2.6d
6.6
4.6
4.8
5.7
2.7
2.5
2.9
3.2
8.1
5.5
8.8
13.9
4.8
4.5
13.1
2.7
2.8

36
31
36
34
32
37
37
22
43
30
36
23
33
19
43
35
32
m
33
18
15
32
29
26
32
42
15
42
24
15
21
24
39
31
34

17
10
15
16
24
15
17
13
18
15
14
17
15
11
19
25
25
m
31
12
13
26
13
15
16
18
9
15
9
15
11
10
27
13
22

12
10
8
10
9
19
10
15
12
8
10
9
16
5
9
10
23
11d
20
9
9
14
7
9
10
9
7
19
7
10
9
7
14
9
13

14.8
17.8

7.8
8.7

5.8
6.4

30
30

17
15

11
11

88
86
m
83
80
m
84
92
87
62
83

11.1
10.6
m
8.5
10.0
m
3.1
18.6
16.5
2.1
38.8

8.1
10.9
m
11.5
11.2
m
5.2
8.1
8.5
8.4
34.3

4.3
6.5
m
11.0
8.8
m
5.3
2.8
4.4
19.6
9.7

25
23
m
21
27
m
30
37
32
33
35

22
16
m
15
20
m
25
14
12
35
24

8
8
m
7
12
m
11
5
9
23
8

m

m

m

m

m

m

m

Tertiary

Note: In most countries data refer to ISCED 2011. For Indonesia and Saudi Arabia data refer to ISCED-97. See Definitions and Methodology sections for more
information. Data and more breakdowns are available at http://stats.oecd.org/, Education at a Glance Database.
1. Year of reference 2015.
2. Data for tertiary education include upper secondary or post-secondary non-tertiary programmes (less than 5% of adults are in this group).
3. Data for upper secondary attainment include completion of a sufficient volume and standard of programmes that would be classified individually as completion of
intermediate upper secondary programmes (17% of adults aged 25-64 are in this group).
4. Year of reference 2016.
5. Year of reference 2014.
Source: OECD/ILO (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933802019

Education at a Glance 2018: OECD Indicators   © OECD 2018

85

chapter A The Output of Educational Institutions and the Impact of Learning
Under embargo until 11/09/2018 at 11.00am CEST
Table A3.4. Employment rates of native- and foreign-born 25-64 year-olds, by age at arrival

A3

in the country and educational attainment (2017)

Percentage of employed 25-64 year-olds among all 25-64 year-olds

Total

Native-born

Arrived in
the country at 16
or older

Total

Total

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

(13)

(14)

(15)

x(4)
57
38
63
54
x(4)
56
68
m
52
63
57
57r
m
49
65
56
m
m
53
66
x(4)
x(4)
69
m
x(4)
76
c
58r
57
67
71
m
m
68

x(4)
51
44
53
83
x(4)
53
61
m
48
57
57
79
m
48
73
61
m
m
56
65
x(4)
x(4)
65
m
x(4)
71
c
53
58
56
67
m
m
66

54
52
43
55
81
59
53
64
m
49
58
57
75
m
48
71
61
m
m
53
65
63
49
67
m
c
73
c
54
58
57
68
m
m
66

59
54
47
56
62
51
62
65
53
53
60
50
55
77
51
52
52
m
66
61
60
65
61
73
61
42
68
39
46
56
67
67
52
63
56

80
77
76
75
71
82
83
80
m
74
82
60
78
m
72
72
71
m
m
74
76
71
82
85
m
70
82
75
73
71
88
83
m
m
69

x(9)
84
64
73
78
x(9)
64
74
m
64
82
61
89
m
63
79
69
m
m
70
71
x(9)
x(9)
84
m
x(9)
86
74
71
68
80
81
m
m
77

x(9)
71
63
71
83
x(9)
69
67
m
61
75
52
80
m
71
79
67
m
m
58
74
x(9)
x(9)
77
m
x(9)
74
69
70
68
73
78
m
m
73

73
73
63
71
81
85
69
71
m
63
77
54
81
m
70
79
68
m
m
63
74
64
68
79
m
76
80
71
70
68
75
79
m
m
74

78
77
73
74
72
82
81
79
74
73
82
59
78
90
72
74
71
m
73
73
75
71
80
83
80
70
82
75
70
70
86
82
63
81
70

87
89
87
84
84
86
88
87
m
87
91
73
85
m
87
88
82
m
m
89
89
80
90
91
m
88
87
82
88
82
93
92
m
m
83

x(14)
87
83
85
90
x(14)
77
73
m
78
90
72
75
m
84
88
88
m
m
84
80
x(14)
x(14)
90
m
x(14)
92
83
86
78
91
88
m
m
82

x(14)
77
74
79
87
x(14)
75
77
m
71
76
52
83
m
80
84
68
m
m
70
86
x(14)
x(14)
85
m
x(14)
73
82
78
70
77
81
m
m
76

81
78
76
80
85
83
76
76
m
73
78
56
82
m
80
85
71
m
m
77
85
75
80
86
m
79
83
82
81
71
80
82
m
m
78

84
86
85
82
84
86
86
86
85
85
89
72
85
93
85
87
81
84d
77
88
86
80
89
89
89
88
87
82
87
81
89
88
75
85
82

OECD average
EU22 average

57
55

60
58

60
57

60
57

58
55

76
76

74
73

71
68

72
71

76
76

86
86

84
82

76
75

78
77

85
85

Argentina
Brazil1
China
Colombia
Costa Rica
India
Indonesia
Lithuania
Russian Federation4
Saudi Arabia5
South Africa

m
m
m
m
63
m
m
46
m
m
m

m
m
m
m
x(4)
m
m
c
m
m
m

m
m
m
m
x(4)
m
m
c
m
m
m

m
m
m
m
69
m
m
c
m
m
m

65
65
m
72
64
m
73
52
51
60
43

m
m
m
m
69
m
m
74
m
m
m

m
m
m
m
x(9)
m
m
c
m
m
m

m
m
m
m
x(9)
m
m
66
m
m
m

m
m
m
m
67
m
m
67
m
m
m

74
74
m
75
69
m
74
73
72
65
58

m
m
m
m
81
m
m
91
m
m
m

m
m
m
m
x(14)
m
m
c
m
m
m

m
m
m
m
x(14)
m
m
80
m
m
m

m
m
m
m
74
m
m
81
m
m
m

85
83
m
83
81
m
85
91
81
75
85

G20 average

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

Arrived in
the country
by the age of 15

Total

(2)

61
56
48
56
62
50
64
66
m
54
62
48
55
m
51
47
50
m
m
62
52
65
64
74
m
42
68
39
48
55
74
66
m
m
46

Arrived in
the country
by the age of 15

(1)

Arrived in
the country
by the age of 15

Arrived in
the country at 16
or older

Foreign-born

Native-born

Foreign-born

Total

Foreign-born

Total

Tertiary

Arrived in
the country at 16
or older

Upper secondary or post-secondary
non‑tertiary

Australia
Austria
Belgium
Canada
Chile1
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan2
Korea
Latvia
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United Kingdom3
United States

Native-born
OECD
Partners

Below upper secondary

Note: In most countries data refer to ISCED 2011. For Indonesia and Saudi Arabia data refer to ISCED-97. See Definitions and Methodology sections for more
information. Data and more breakdowns are available at http://stats.oecd.org/, Education at a Glance Database.
1. Year of reference 2015.
2. Data for tertiary education include upper secondary or post-secondary non-tertiary programmes (less than 5% of adults are in this group).
3. Data for upper secondary attainment include completion of a sufficient volume and standard of programmes that would be classified individually as completion of
intermediate upper secondary programmes (17% of adults aged 25-64 are in this group).
4. Year of reference 2016.
5. Year of reference 2014.
Source: OECD (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933802038

86

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Under embargo until 11/09/2018 at 11.00am CEST

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INDICATOR A4

WHAT ARE THE EARNINGS ADVANTAGES FROM EDUCATION?
• On average across OECD countries, 25-64 year-old adults with a tertiary degree earn 54% more
than those with only upper secondary education, while those with below upper secondary education
earn 22% less.

• Across all levels of educational attainment, the gender gap in earnings persists, and a large gender
gap in earnings is seen between male and female full-time workers with tertiary education: across
OECD countries, tertiary-educated women earn only 74% as much as tertiary-educated men.

• Countries with a lower share of people with low educational attainment tend to enjoy lower income
inequality. Income inequality is largest in countries with a high share of people without upper
secondary education, such as Brazil, Costa Rica and Mexico, and smallest in countries with a low share
of people without upper secondary education, such as the Czech Republic and the Slovak Republic.

Figure A4.1. Trends in women’s earnings as a percentage of men’s earnings
for full-time workers with tertiary education (2005, 2016)
25-64 year-old full-time workers
2016

%

110

2005
Women earn more than man

100

Women earn less than man

90
80
70
60

40

Costa Rica
Slovenia
Sweden
Turkey1
Belgium2
Spain2
Luxembourg1
Latvia1
Colombia
Switzerland
United Kingdom
New Zealand
Netherlands2
Finland2
Australia
Austria
Denmark
Lithuania2
Germany
Norway
OECD average
Greece
Canada2
Korea
France2
Portugal
Poland
Ireland1
Italy2
United States
Czech Republic2
Estonia
Slovak Republic
Hungary
Mexico1
Israel
Brazil2
Chile2

50

1. Earnings net of income tax.
2. Year of reference differs from 2016. Refer to the source table for details.
Countries are ranked in descending order of the earnings of 25-64 year-old women as a percentage of men’s earnings in 2016.
Source: OECD (2018), Table 4.3 and Education at a Glance Database, http://stats.oecd.org/. See Source section for more information
and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933802266

Context
Higher levels of education usually translate into better employment opportunities (see Indicator A3)
and higher earnings. While people with higher qualifications are generally better placed to see their
earnings strongly increase over time, those without upper secondary education (who usually have
lower earnings at the start of their career) tend to see only a slight increase of their earnings with
age (see Indicator A6 in Education at a Glance 2017 [OECD, 2017[1]]). Hence, the potential for higher
earnings and faster earnings progression can be an important incentive for individuals to pursue
education and training. It may also be one of the decisive factors in their choice of field of study at
tertiary level.
A number of factors other than education also play a role in individuals’ earnings. In many countries,
earnings are systematically lower for women than men across all levels of educational attainment.
This may be related to gender differences in the sectors where they work and the types of occupation
(OECD, 2016[2]). Variations in earnings also reflect other factors, including the demand for skills in
the labour market, the supply of workers and their skills, the minimum wage and other labour-market

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laws, and structures and practices (such as the strength of labour unions, the coverage of collectivebargaining agreements and the quality of working environments). These factors also contribute to
differences in the distribution of earnings. In some countries, earnings vary little, while in other
countries there are large earnings disparities, leading to wide inequalities.

INDICATOR A4

With the recent increase in migration flows to OECD countries, the labour-market situation
of foreign-born adults stimulates the public debate. According to the International Migration
Outlook 2017 (OECD, 2017[3]), 13% of the total population in OECD countries are foreign-born. The
size and the characteristics of this group vary across countries, and it is important to analyse these
elements to better understand the composition of a country’s population. Data from the International
Migration Outlook 2017 show that in 2015, 11% of the permanent migration flow was under the work
category, 33% under the free-movement category, 32% under the family category and 13% under the
humanitarian category. Migration Policy Debates (OECD, 2014[4]) shows that there is evidence of the
positive social and economic returns to migration. Overall, foreign-born adults largely contribute to
increasing the workforce, and they generally contribute more in taxes and social contributions than
they receive in benefits.
Other findings

• Across countries, the likelihood of earning more than the median increases with educational
attainment. On average across OECD countries, two out of three tertiary-educated adults earn
more than the median of all employed people, including both full-time and part-time earners, while
only one out of four adults without upper secondary education do so.

• In most of countries with available data, the gender gap between the earnings of men and women
with tertiary education working full time has decreased between 2005 and 2016. The decrease is
5 or more percentage points in Brazil, the Netherlands and New Zealand.

• In Belgium, Chile, Colombia, France, Germany, Luxembourg, Slovenia, Switzerland and the United States,
the earnings of foreign-born workers with tertiary education are at the same level or even higher than
the earnings of their native-born peers.

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Analysis
Differences in earnings between women and men, by educational attainment
Women do not earn as much as men in any OECD and partner countries. Across OECD countries, tertiary-educated
women working full time earn only 74% of the earnings of tertiary-educated men. This gender gap of 26% in
earnings is slightly higher than the gap for adults with below upper secondary and for adults with upper secondary
or post-secondary non-tertiary education (both 22%) (Figure A4.1 and Table A4.1).
There is a high variation in the earnings level of women working full time compared to that of men. Tertiary-educated
women earn 65% of men’s earnings in Brazil, Chile, and Israel and 80% or more in Belgium, Costa Rica, Latvia,
Luxembourg, Slovenia, Spain, Sweden and Turkey. Costa Rica is the country where the earning of tertiary‑educated
women are closest to men’s earnings, but they are still 7% lower (Figure A4.1).
As women are more likely to work part time than men, the gender gap in the average earnings of workers
(including full-time and part-time earners) is even larger (OECD, 2016[5]). Across OECD countries, 24% of women
aged 25‑64 and 17% of men in the same age group work part time or part year (OECD, 2018[6]). On average, among
those with tertiary education, female workers in full-time or part-time work earn only 68% of the earnings of
tertiary-educated men across OECD countries. The gender gap among women with an upper secondary education
or those with below upper secondary education is about the same as among those with tertiary education (both
around 68% [OECD, 2018[6]]).
Reasons for the gender gap include gender stereotyping, social conventions and discrimination against women
(OECD, 2017[7]), but also differences between men and women in the choice of fields of study. Men are more likely than
women to study in fields associated with higher earnings, such as engineering, manufacturing and construction, or
science, mathematics and computing, while a higher share of women enrol in fields associated with lower earnings,
including teacher training and education science, and humanities, languages and arts (see Indicator A6 in Education
at a Glance 2016, [OECD, 2016[5]]). Other reasons may relate to difficulties in combining a professional career with
household and family responsibilities. To manage these different commitments, women are more likely to seek
less competitive career paths and greater flexibility at work, leading to lower earnings than men with the same
educational attainment (OECD, 2016[2]).
In recent years, awareness of the differences in pay of men and women has increased. Many countries have introduced
new national policies to reduce disparities in earnings between men and women. Some countries have put in place
concrete measures, such as pay transparency, to foster equity in pay between men and women (OECD, 2017[7]). In
most of the countries with available data, the gender gap between the earnings of men and women with tertiary
education has decreased between 2005 and 2016 (Figure A4.1).
Relative earnings, by educational attainment
On average across OECD countries, adults (age 25-64) without upper secondary education earn about 20% less for
part-time or full-time employment than those with upper secondary education, while those with a tertiary degree
have an earnings advantage of about 55% (Table A4.1).
The relative earnings disadvantages for adults without an upper secondary qualification are generally smaller than
the earnings advantages of the tertiary-educated. In Austria, Brazil, Chile, Mexico and the Slovak Republic, adults
without upper secondary education earn about 35% less for part-time or full-time work than adults with upper
secondary education. The earnings disadvantage represents about 40% for those without an upper secondary
qualification in Brazil and Mexico (the highest earnings disadvantage across OECD and partner countries), but
15% or less in Australia, Estonia, Finland, Latvia, Lithuania and New Zealand (Table A4.1).
Having a tertiary degree carries a considerable earnings advantage in most OECD and partner countries. The
relative earnings for full-time and part-time workers are largest in Brazil, where adults with a tertiary education earn
150% more than adults with an upper secondary education. In Chile, Colombia, Costa Rica, Hungary and Mexico,
tertiary-educated adults earn about twice as much as their peers with lower educational attainment (Table A4.1). In
all of these countries, the share of adults with tertiary education is among the lowest in OECD and partner countries
(less than 25%), which partly explains the large earnings advantage of tertiary-educated workers (see Indicator A6
in Education at a Glance 2017 [OECD, 2017[1]]).
In some countries, the relative earnings are below the OECD average even though the share of tertiary-educated
people is large (see Indicator A1). For example, in Australia, Denmark, Estonia, New Zealand and Norway, where

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about 40% of adults are tertiary-educated, the earnings advantage from a tertiary degree is only about 30%, and
in Sweden, with a similar share of tertiary-educated people, it is just 15% (Table A4.1). However, tertiary-educated
people have among the highest employment rates in these countries (see Indicator A3).
Distribution of earnings, by educational attainment
Data on the distribution of earnings among groups with different levels of education show the degree to which
earnings centre around the country median. “Median earnings” refer to earnings of all workers, without adjusting
for differences in hours worked.
Across OECD and partner countries, the likelihood of earning more than the median increases with educational
attainment. On average across OECD countries, 68% of tertiary-educated adults earn more than the median of all
employed adults, including both full-time and part-time earners, while only 26% of adults without upper secondary
education do so. In Brazil, Chile, Colombia, Costa Rica, Hungary, Mexico and Portugal, more than 80% of tertiaryeducated adults earn more than the median. With the exception of Colombia, Hungary and Portugal, most of these
adults earn more than twice the median. The strongly skewed earnings distribution signals income inequality, which
may affect the social cohesion of communities (Figure A4.2 and Table A4.2, and see the section below on income
inequality and the share of adults without upper secondary education).

Figure A4.2. Percentage of adults earning more than the median,
by educational attainment (2016)
25-64 year-old workers (full- and part-time workers)
Tertiary
Upper secondary or post-secondary non-tertiary
Below upper secondary

%

100
90
80
70
60
50
40
30
20
0

Brazil1
Costa Rica
Mexico2
Chile1
Hungary
Portugal
Colombia
Slovenia3
Czech Republic1
Turkey2
Slovak Republic
Poland
Latvia2
France1
Germany
OECD average
Switzerland
Korea
United Kingdom
Greece
Luxembourg2
United States
Belgium2
Ireland2
Italy1
Spain1
Norway
Austria
Finland1
Netherlands1
Lithuania1
Australia
Japan1
Israel
Denmark
New Zealand
Estonia
Sweden
Canada1

10

1. Year of reference differs from 2016. Refer to the source table for details.
2. Earnings net of income tax.
3. Data refer to full-time, full-year earners only.
Countries are ranked in descending order of the percentage of 25-64 year-olds with tertiary education earning more than the median.
Source: OECD (2018), Table A4.2. See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933802285

In contrast, on average across OECD countries, only 26% of adults without upper secondary education earn more
than the median. In Italy, New Zealand and Portugal, at least 35% of adults without upper secondary education earn
more than the median earnings. The share of workers without upper secondary education earning more than twice
the median is only 3% on average across OECD countries. However, in Brazil, Canada, Estonia, Mexico, Portugal and
Spain, 5% or more of workers without upper secondary education reach this earnings level, suggesting that factors
other than educational attainment play an important role in high remuneration in these countries (Figure A4.2 and
Table A4.2).
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Among adults with upper secondary or post-secondary non-tertiary education, the shares of those earning more than
the median earnings in a country are between the shares for those with tertiary and below upper secondary education.
On average, 43% of adults with upper secondary or post-secondary non-tertiary education earn more than the median
earnings across OECD countries. In Brazil, Costa Rica, Colombia, Italy, Mexico and Portugal, the share exceeds 50%. In
most of these countries, the share of adults without upper secondary education is more than double the OECD average
of 15%, which partly explains the higher share of workers with above-median earnings (Figure A4.2 and see Table A1.2).
Income inequality and the share of adults without upper secondary education
Over the past few decades, income inequality has risen in OECD countries. Rising income inequality has a significant
impact on economic growth, as it reduces the capacity of the poorer population to invest in their own skills and
education. More equal societies tend to be able to provide better education opportunities to their population and
cultivate the conditions for inclusive economic growth (OECD, 2015[8]).
One common approach to measure income inequality is the ratio of the disposable income of the 90th decile to
the 10th decile of the population aged 18-65 (the P90/P10 decile ratio). As shown in Figure A4.3, in Costa Rica,
the per capita income of an individual at the top decile of the income distribution is ten times higher than that of
an individual at the bottom decile, indicated by a P90/P10 ratio of 10. In terms of income inequality, Costa Rica is
followed by Brazil, Chile, Estonia, Greece, Israel, Lithuania, Mexico, Spain, Turkey and the United States, where the
P90/P10 ratio exceeds 5. The lowest income inequality can be found in the Czech Republic, Denmark, Iceland and
the Slovak Republic (P90/P10 ratio of 3) (Figure A4.3 and [OECD, 2018[9]]).

Figure A4.3. Percentage of 25-64 year-olds without upper secondary education
and income inequality (2015)
Income inequality measured as the P90/P10 decile ratio
P90/P10 decile ratio

11
Costa Rica

10
9
Brazil1

8
Chile

Increasing inequality

A4

Mexico1

7
6

Estonia

5

Poland
Switzerland1
Czech
Republic

4
3

Slovak
Republic

2

OECD average

Israel

Sweden

Austria
Finland
Slovenia
Korea

Greece

Turkey

Spain

Australia1

Latvia
Hungary1
Germany1

Canada

R2 = 0.4

United Kingdom

United States

Lithuania

New Zealand1

Italy1

Portugal

Ireland1

Denmark1

Belgium
Netherlands
Iceland1
France

Luxembourg1

1
0
0

10

20

30

40

50

60

70

Population without upper secondary education (%)

Note: The P90/P10 decile ratio is the ratio of the upper bound value of the ninth decile (i.e. the 10% of people with highest income) to that of
the upper bound value of the first decile. The income distribution is measured with regard to the disposable income of the population aged 18-65.
1. Year of reference 2014.
Source: OECD (2018), Education at a Glance Database and OECD Income Distribution database (IDD), http://stats.oecd.org/. See Source section for
more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933802304

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When comparing P90/P10 decile income ratios across OECD and partner countries with the shares of adults without
upper secondary education in their population, it seems that countries with a lower share of people without upper
secondary education tend to enjoy lower income inequality. Income inequality is largest in countries with a high
share of people without upper secondary education, such as Brazil, Costa Rica and Mexico, and lowest in countries
with a small share of people without upper secondary education, such as the Czech Republic and the Slovak Republic.
Although Figure A.4.3 suggests a relatively strong linear relationship, this correlation weakens when removing
Brazil and Costa Rica, the countries with the largest income inequality (Figure A4.3).
Differences in earnings between native-born and foreign-born workers, by educational attainment
Foreign-born adults have more difficulty finding a job than their native-born peers, as they face various problems,
such as recognition of credentials obtained abroad, lack of skills needed, language difficulties or discrimination
when looking for work. Therefore, foreign-born workers (full-time workers) are more likely to accept any job they
can get, which affects their level of earnings compared to their native-born peers (OECD, 2017[3]) (FRA, 2017[10]).
In most OECD and partner countries, earnings of foreign-born adults working full time are lower than those of their
native-born peers, across educational attainment levels.
In many countries, foreign-born workers with below upper secondary education earn less than their native-born
peers. This is especially true in Estonia, New Zealand, Spain and Sweden, where the earnings gap is about 20% or
more. The exceptions, where foreign-born workers without upper secondary education earn more than native-born
peers, are Germany (18%) and Switzerland (6%) (Figure A4.4).
Foreign-born workers with upper secondary or post-secondary education also face a disadvantage in earnings
compared to native-born workers. The earnings gap between foreign-born and native-born workers with upper
secondary or post-secondary education is 30 or more percentage points in Chile, Italy and Spain. In contrast, in
France and Germany, earnings of foreign-born workers with upper secondary or post-secondary non-tertiary
education are similar to those of native-born workers with the same educational attainment, and in Colombia,
foreign-born workers earn about 25% more than their native-born peers (Figure A4.4).

Figure A4.4. Earnings of foreign-born workers as a percentage of earnings of native-born
full-time workers, by educational attainment (2016)
25-64 year-old workers (full-time workers)

%

140

Tertiary
Upper secondary or post-secondary non-tertiary
Below upper secondary

226

130
120
110
100
90
80

Italy1

Spain1

Finland1, 2

Estonia

New Zealand

Austria

Latvia3

Israel

Sweden

Norway

Ireland3

Costa Rica

Switzerland

Luxembourg3

France1

Germany

Slovenia

United States

Belgium1, 2

Chile1

60

Colombia

70

1. Year of reference differs from 2016. Refer to the source table for details.
2. Data refer to full-time and part-time workers.
3. Earnings net of income tax.
Countries are ranked in descending order of the earnings of tertiary-educated foreign-born workers as a percentage of earnings of tertiary-educated native-born
workers.
Source: OECD (2018), Table A4.4. See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933802323

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In Belgium, Chile, Colombia, France, Germany, Luxembourg, Slovenia, Switzerland and the United States, the
earnings of foreign-born workers with tertiary education are at the same level or even higher than the earnings of
their native-born peers. In Chile, foreign-born workers with tertiary education earn 30% more than native-born
tertiary-educated adults, and in Colombia, the earnings advantage increases to about 125%. In contrast, in Estonia,
Finland, Italy and Spain, foreign-born workers with tertiary education earn less than 80% of the earnings of their
native-born peers (Figure A4.4).
There is a high variation in the earnings differences between native-born and foreign-born workers across countries
and educational attainment levels. In Belgium, Chile, Colombia, Finland and the United States the earnings gap
between educational attainment levels exceeds 20 percentage points. On the other hand, in Austria and Estonia, the
difference in the earnings gap between foreign-born and native-born workers across educational attainment levels
is low (less than 7 percentage points, Figure A4.4).

Box A4.1. Qualification match or mismatch and earnings
Based on data from the Survey of Adult Skills (PIAAC) (see Source section at the end of this indicator), this
box explores the relationship between overqualification and underqualification and earnings. It complements
Box A3.1 on qualification match or mismatch among workers, as it provides details on how qualification match
or mismatch relates to earnings (see Indicator A3).
Earnings appear more closely related to job levels than to educational attainment (i.e. those working in
a job requiring a tertiary degree earn similar wages independently of whether they are underqualified or
well matched, but those with a tertiary degree working in a job requiring much lower qualification earn
much less than well-matched workers). As shown in Figure A4.a, individuals with a qualification of upper
secondary education (ISCED-97 level 3) or below working in a job needing a qualification of tertiary-type A
or advanced research programmes (ISCED 5A or 6 degree) (i.e. underqualified workers) have a median
earning of about USD 19 per hour, similar to well-matched workers in those jobs. In most countries no
statistically significant differences can be observed between these two groups. Those holding an ISCED 5A
or 6 degree working in a job needing ISCED level 3 or below (i.e. overqualified workers) have a median
earning of about USD 11 per hour (Figure A4.a). The reasons for the qualification mismatch can vary across
and within countries, but Box A3.1 demonstrates that those who are overqualified are likely to have lower
numeracy skills. Overqualified people may be working in a job requiring lower skills than their education
attainment level because they have not been able demonstrate sufficient skills to get a job at the level of
their qualification (see Indicator A3).
There are differences across countries, but the patterns are fairly consistent. The largest gaps in median hourly
earnings (over USD 10 per hour) between well-matched and overqualified workers are observed in Canada,
Denmark, Germany, Ireland and the United States. The difference is particularly high in Canada (about USD 15
per hour), where workers with a degree at ISCED level 5A or 6 working in a job needing ISCED 3 or below earn
less than half the median hourly earnings of those who are in a well-matched situation (Figure A4.a).
In contrast, in the Czech Republic, the difference in earnings between well-matched, overqualified and
underqualified workers is not statistically significant. Earnings are generally low in the Czech Republic,
Estonia, Greece and Turkey, but despite this low earnings level, overqualified workers are also likely to earn
about half the earnings of well-matched workers. For example, in Turkey, well-matched workers with a degree
at ISCED level 5A or 6 have median earnings of about USD 11 per hour, while those holding an ISCED 5A
or 6 degree working in a job needing ISCED level 3 or below have median earnings of about USD 4 per hour.
However, this is a limited issue, as the share of overqualified workers in Turkey (9%) is well below the average
across countries that participated in the Survey of Adult Skills (PIAAC) (15%) (Figure A4.a and Table A3.a,
available on line).
Data show that workers have to demonstrate skills commensurate with their formal level of qualification
for employers to offer a salary they would expect with that level of qualification. The importance of skills
is shown, in contrast, when underqualified workers have earnings surpassing their formal qualification,

…

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as employers recognise their actual skills rather than their formal qualifications. It is, therefore, important to
assess the mismatch situation more closely, especially for the overqualified population who invested in their
human capital and for whom society invested in their education, without fully developing skills rewarded in
the labour market.

Figure A4.a. Median hourly earnings, by selected qualification match or mismatch
among workers (2012 or 2015)
Survey of Adult Skills (PIAAC), employed 25-64 year-olds, median hourly earnings in equivalent 2012 USD
converted using PPPs for private consumption
ISCED 3 degree or below working in a job needing ISCED 5A or 6 (underqualified)
ISCED 5A or 6 degree working in a job needing the same level of qualification (well matched)
ISCED 5A or 6 degree working in a job needing ISCED 3 or below (overqualified)

USD ppp/hour

35
30
25
20
15
10

Russian Federation*4

Slovak Republic2

Lithuania3

Estonia

Czech Republic1, 2, 4

Turkey3

Poland2

Greece3

Chile3

Israel3

Slovenia3

Spain1

Italy1

Korea1

Sweden1

OECD average1

France1

Northern Ireland (UK)

New Zealand1, 3

Japan1

Finland

Austria1

England (UK)

Norway1

Netherlands

Australia1, 2

Flemish Comm. (Belgium)1

Ireland

Canada1

Germany1

Denmark1

0

United States1

5

Note: Some data points are not displayed because there are too few observations to provide a reliable estimate. Data from the Survey of Adult
Skills (PIAAC) are based on ISCED-97. See Definitions, Methodology and Source sections for more information.
1. The earnings difference between well-matched and underqualified workers is not statistically significant at 5%.
2. The earnings difference between overqualified and underqualified workers is not statistically significant at 5%.
3. Reference year is 2015; for all other countries and economies the reference year is 2012.
4. The earnings difference between well-matched and overqualified workers is not statistically significant at 5%.
* See note on data for the Russian Federation in the Source section.						
Countries are ranked in descending order of the median hourly earnings of the population reporting that their educational attainment matches the
attainment level needed for their job (well matched).						
Source: OECD (2018), Table A.4a, available on line. See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/
eag-2018-36-en).
1 2 https://doi.org/10.1787/888933802342

Definitions
Adults refer to 25-64 year-olds.
Educational attainment refers to the highest level of education attained by a person.
Levels of education: See the Reader’s Guide at the beginning of this publication for a presentation of all ISCED 2011
levels.
The previous classification, ISCED-97, is used for the analyses based on the Survey of Adult Skills (PIAAC) in
Box A4.1. See Indicator A3 for the definition of the different education levels based on ISCED-97.
Qualification match/mismatch: See Indicator A3 for this definition.
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Methodology
The analysis of relative earnings of the population with specific educational attainment (Table A4.1) includes fulltime and part-time workers. The analysis of differences in earnings between men and women (Table A4.3) and the
analysis of differences in earnings between native-born and foreign-born workers (Table A4.4) include full-time
workers only. The analysis of the distribution of earnings includes full-time and part-time workers. It does not
control for hours worked, although the number of hours worked is likely to influence earnings in general and the
distribution in particular. For the definition of full-time earnings, countries were asked whether they had applied a
self-designated full-time status or a threshold value of the typical number of hours worked per week.
Earnings data are based on an annual, monthly or weekly reference period, depending on the country. The length of
the reference period for earnings also differs. Data on earnings are before income tax for most countries. Earnings
of self-employed people are excluded for many countries and, in general, there is no simple and comparable method
to separate earnings from employment and returns to capital invested in a business.
This indicator does not take into consideration the impact of effective income from free government services.
Therefore, although incomes could be lower in some countries than in others, the state could be providing both free
healthcare and free schooling.
The total average for earnings (men plus women) is not the simple average of the earnings figures for men and women.
Instead it is the average based on earnings of the total population. This overall average weights the average earnings
separately for men and women by the share of men and women with different levels of educational attainment.
Please see the OECD Handbook for Internationally Comparative Education Statistics 2018 (OECD, 2018[11]) for more
information and Annex 3 for country-specific notes (http://dx.doi.org/10.1787/eag-2018-36-en).
For the methodology used in Box A4.1 please see the Methodology section in Indicator A7.
Lithuania was not an OECD member at the time of preparation of this publication. Accordingly, Lithuania does not
appear in the list of OECD members and is not included in the zone aggregates.

Source
The indicator is based on the data collection on education and earnings by the OECD LSO (Labour Market and Social
Outcomes of Learning) Network. The data collection takes account of earnings for individuals working full time full
year, as well as part time or part year, during the reference period. This database contains data on dispersion of earnings
from work and on student earnings versus non-student earnings. The source for most countries is national household
surveys such as Labour Force Surveys (LFS), European Union Statistics on Income and Living Conditions (EU-SILC) or
other dedicated surveys collecting data on earnings. About one fourth of countries use data from tax or other registers.
Data used in Box A4.1 are based on the OECD Programme for the International Assessment of Adult Competencies
(the Survey of Adult Skills [PIAAC]).
Note regarding data from Israel
The statistical data for Israel are supplied by and are under the responsibility of the relevant Israeli authorities. The use
of such data by the OECD is without prejudice to the status of the Golan Heights, East Jerusalem and Israeli settlements
in the West Bank under the terms of international law.
Note regarding data from the Russian Federation in the Survey of Adult Skills (PIAAC)
The sample for the Russian Federation does not include the population of the Moscow municipal area. The data published,
therefore, do not represent the entire resident population aged 16-65 in the Russian Federation but rather the population
of the Russian Federation excluding the population residing in the Moscow municipal area. More detailed information
regarding the data from the Russian Federation as well as that of other countries can be found in the Technical Report of the
Survey of Adult Skills, Second Edition (OECD, 2016 [12]).

References
FRA (2017), Second European Union Minorities and Discrimination Survey: Main Results, FRA (European Union Agency for [10]
Fundamental Rights), Vienna, http://dx.doi.org/10.2811/268615.
OECD (2018), Education at a Glance Database - Education and earnings, http://stats.oecd.org/Index.aspx?datasetcode=EAG_ [6]
EARNINGS.

96

Education at a Glance 2018: OECD Indicators   © OECD 2018

What are the earnings advantages from education? – INDICATOR A4

chapter A

Under embargo until 11/09/2018 at 11.00am CEST
OECD (2018), OECD Handbook for Internationally Comparative Education Statistics 2018: Concepts, Standards, Definitions [11]
and Classifications, OECD Publishing, Paris, https://doi.org/10.1787/9789264304444-en.
OECD (2018), OECD Income Distribution database (IDD), http://stats.oecd.org/Index.aspx?DataSetCode=IDD (accessed [9]
on 31 May 2018).
OECD (2017), Education at a Glance 2017: OECD Indicators, OECD Publishing, Paris, http://dx.doi.org/10.1787/eag-2017-en. [1]
OECD (2017), International Migration Outlook 2017, OECD Publishing, Paris, http://dx.doi.org/10.1787/migr_outlook- [3]
2017-en.
OECD (2017), The Pursuit of Gender Equality: An Uphill Battle, OECD Publishing, Paris, http://dx.doi.org/10.1787/ [7]
9789264281318-en.
OECD (2016), Education at a Glance 2016 : OECD Indicators, OECD Publishing, Paris, http://dx.doi.org/10.1787/eag-2016-en [5]
(accessed on 12 January 2018).
OECD (2016), OECD Employment Outlook 2016, OECD Publishing, Paris, http://dx.doi.org/10.1787/empl_outlook-2016-en. [2]
OECD (2016), Technical Report of the Survey of Adult Skills, Second Edition, OECD, Paris, www.oecd.org/skills/piaac/PIAAC_ [12]
Technical_Report_2nd_Edition_Full_Report.pdf.
OECD (2015), In It Together: Why Less Inequality Benefits All, OECD Publishing, Paris, http://dx.doi.org/10.1787/ [8]
9789264235120-en.
OECD (2014), “Is migration good for the economy?”, Migration Policy Debates, www.oecd.org/migration/OECD%20 [4]
Migration%20Policy%20Debates%20Numero%202.pdf (accessed on 05 February 2018).

Indicator A4 Tables
1 2 https://doi.org/10.1787/888933802171

Table A4.1 Relative earnings of workers, by educational attainment (2016)
Table A4.2 Level of earnings relative to median earnings, by educational attainment (2016)
Table A4.3 Differences in earnings between female and male full-time workers, by educational attainment
and age group (2016)
Table A4.4 Differences in earnings between native- and foreign-born full-time workers, by educational attainment
and age group (2016)
Cut-off date for the data: 18 July 2018. Any updates on data can be found on line at http://dx.doi.org/10.1787/eag-data-en. More breakdowns can
also be found at http://stats.oecd.org/, Education at a Glance Database.

Education at a Glance 2018: OECD Indicators   © OECD 2018

97

A4

chapter A The Output of Educational Institutions and the Impact of Learning
Under embargo until 11/09/2018 at 11.00am CEST
Table A4.1. Relative earnings of workers, by educational attainment (2016)
25-64 year-olds with income from employment (full- and part-time workers); upper secondary education = 100

A4

Partners

OECD

Tertiary
Below upper
secondary

Post-secondary
non-tertiary

Short-cycle tertiary

Bachelor’s or
equivalent

Master’s, doctoral
or equivalent

(1)

(2)

(3)

(4)

(5)

Australia
Austria
Belgium1
Canada1
Chile1
Czech Republic1, 2
Denmark
Estonia
Finland1
France3
Germany
Greece
Hungary
Iceland
Ireland4
Israel
Italy3
Japan5
Korea
Latvia4
Luxembourg4
Mexico4
Netherlands3
New Zealand
Norway
Poland
Portugal
Slovak Republic2
Slovenia
Spain1
Sweden
Switzerland2
Turkey4
United Kingdom
United States2

(6)

87
69
82
83
68
74
80
89
98
80
76
77
76
m
80
77
78
78
72
89
77
59
82
87
76
83
75
65
m
73
82
78
72
76
74

101
112
c
126
a
m
136
89
118
c
114
99
98
m
91
a
m
x(6)
a
97
c
a
124
108
102
100
103
m
m
101r
109
m
a
a
m

107
133
c
121
142
112
116
90
124
125
151
145
110
m
129
115
x(5)
x(6)
116
118
122
133
132
114
118
m
166
123
m
x(6)
98
x(4, 5)
x(6)
125
112

135
93
126
152
264
142
111
124
125
142
165
133
172
m
167
149
x(5)
x(6)
149
136
139
192
132
130
114
139
170d
124
m
x(6)
105
141d
x(6)
148
169

152
174
165
186
472
180
166
139
169
210
183
174
234
m
208
216
138d
x(6)
198
166
159
303
184
154
156
161
x(4)
174
m
x(6)
135
167d
x(6)
172
233

131
146
141
144
237
169
129
127
141
155
169
140
194
m
168
159
138
152d
145
145
148
195
150
132
127
156
169
168
m
151
115
155
171
150
175

OECD average
EU22 average

78
79

m
107

123
125

144
136

191
173

154
151

Argentina
Brazil1, 2
China
Colombia2
Costa Rica
India
Indonesia
Lithuania3
Russian Federation
Saudi Arabia
South Africa

m
62
m
67
69
m
m
86
m
m
m

m
m
m
m
c
m
m
113
m
m
m

m
x(4)
m
m
119
m
m
a
m
m
m

m
235d
m
m
207
m
m
155
m
m
m

m
449
m
m
337
m
m
213
m
m
m

m
249
m
236
203
m
m
179
m
m
m

G20 average

m

m

m

m

m

m

Total

Note: See Definitions and Methodology sections for more information. Data and more breakdowns available at http://stats.oecd.org/, Education at a Glance Database.
1. Year of reference 2015.
2. Index 100 refers to the combined ISCED levels 3 and 4 of the educational attainment levels in the ISCED 2011 classification.
3. Year of reference 2014.
4. Earnings net of income tax.
5. Year of reference 2012.
Source: OECD (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933802190

98

Education at a Glance 2018: OECD Indicators   © OECD 2018

What are the earnings advantages from education? – INDICATOR A4

chapter A

Under embargo until 11/09/2018 at 11.00am CEST
Table A4.2. Level of earnings relative to median earnings, by educational attainment (2016)
Median earnings from work for the 25-64 year-olds with earnings (full- and part-time workers) for all levels of education
Upper secondary or post-secondary
non-tertiary

More than half the
median but at or below
the median

More than the median
but at or below 1.5 times
the median

More than 1.5 times
the median but at or
below twice the median

More than twice
the median

At or below half of the
median

More than half the
median but at or below
the median

More than the median
but at or below 1.5 times
the median

More than 1.5 times
the median but at or
below twice the median

More than twice
the median

At or below half
of the median

More than half the
median but at or below
the median

More than the median
but at or below 1.5 times
the median

More than 1.5 times the
median but at or below
twice the median

More than twice
the median

Tertiary

At or below half
of the median
Partners

OECD

Below upper secondary

A4

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

(13)

(14)

(15)

Australia
Austria
Belgium1
Canada2
Chile2
Czech Republic2
Denmark
Estonia
Finland2
France3
Germany
Greece
Hungary
Iceland
Ireland1
Israel
Italy3
Japan4
Korea
Latvia1
Luxembourg1
Mexico1
Netherlands3
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia5
Spain2
Sweden
Switzerland
Turkey1
United Kingdom
United States

13
37
12
38
23
22
29
19
29
34
41
30
2
m
41
28
31
37
27
9
20
29
33
23
31
0
9
37
0
37
19
32
33
28
42

57
39
68
34
53
58
40
48
37
37
30
43
79
m
28
50
32
33
56
66
65
38
36
42
41
73
55
45
85
31
49
50
43
46
40

22
18
20
16
16
17
24
20
25
20
19
19
15
m
20
14
24
18
13
18
11
21
24
23
21
20
24
13
14
20
26
17
18
20
11

4
4
1
6
5
2
4
6
6
5
7
5
3
m
6
4
8
7
3
5
4
8
5
8
5
5
6
3
1
8
4
1
5
5
3

4
1
0
6
3
0
2
7
3
3
2
4
1
m
4
4
4
4
1
2
1
6
2
4
2
2
5
1
0
5
2
1
2
2
3

8
21
6
28
11
10
17
13
22
21
22
19
0
m
30
17
19
29
14
6
12
12
22
19
16
0
6
18
0
24
11
22
17
21
26

50
32
63
29
41
47
38
46
38
38
36
35
61
m
33
45
30
29
48
57
52
26
35
34
38
58
40
36
64
26
40
39
35
39
37

29
29
29
21
24
32
34
26
30
27
28
31
24
m
21
21
30
19
23
26
20
25
28
27
32
28
29
28
28
22
34
30
26
25
20

8
11
2
11
12
8
8
7
7
8
10
9
9
m
9
8
12
12
8
8
12
15
10
12
9
9
11
11
6
14
10
6
13
9
9

6
7
0
11
11
4
4
9
3
5
4
6
6
m
7
9
10
11
6
3
3
21
5
8
5
5
15
6
2
13
4
2
8
5
8

5
16
2
21
3
3
14
8
14
11
13
11
0
m
15
11
16
17
6
2
3
5
15
13
12
0
3
12
0
17
15
10
11
10
13

31
19
33
22
14
18
23
31
22
20
18
22
17
m
20
26
19
20
27
28
30
11
21
25
23
28
14
16
21
18
27
22
13
23
21

36
24
49
21
17
37
38
30
33
32
26
33
28
m
21
20
27
21
29
35
30
15
26
27
39
34
22
28
32
17
36
34
15
28
23

14
17
12
15
17
18
14
13
17
18
19
18
22
m
19
15
16
16
17
19
21
17
18
17
14
17
20
19
25
15
12
19
27
18
15

14
23
4
21
50
23
11
18
15
19
24
15
32
m
26
28
22
27
21
16
16
52
20
17
12
20
41
26
22
33
10
15
35
20
28

OECD average
EU22 average

26
24

48
50

19
20

5
5

3
2

16
15

41
43

27
28

9
9

7
6

10
9

22
22

28
30

17
18

23
21

Argentina
Brazil2
China
Colombia
Costa Rica
India
Indonesia
Lithuania3
Russian Federation
Saudi Arabia
South Africa

m
29
m
38
23
m
m
31
m
m
m

m
42
m
35
51
m
m
44
m
m
m

m
15
m
20
20
m
m
13
m
m
m

m
6
m
4
4
m
m
8
m
m
m

m
7
m
3
3
m
m
3
m
m
m

m
9
m
19
11
m
m
20
m
m
m

m
40
m
28
37
m
m
43
m
m
m

m
22
m
32
29
m
m
19
m
m
m

m
12
m
10
13
m
m
11
m
m
m

m
18
m
10
11
m
m
7
m
m
m

m
2
m
7
3
m
m
15
m
m
m

m
12
m
13
13
m
m
22
m
m
m

m
13
m
21
19
m
m
20
m
m
m

m
13
m
13
16
m
m
17
m
m
m

m
60
m
47
50
m
m
27
m
m
m

G20 average

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

Note: See Definitions and Methodology sections for more information. Data and more breakdowns are available at http://stats.oecd.org/, Education at a Glance Database.
1. Earnings net of income tax.
2. Year of reference 2015.
3. Year of reference 2014.
4. Year of reference 2012.
5. Data refer to full-time, full-year earners only.						
Source: OECD (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933802209

Education at a Glance 2018: OECD Indicators   © OECD 2018

99

chapter A The Output of Educational Institutions and the Impact of Learning
Under embargo until 11/09/2018 at 11.00am CEST
Table A4.3. Differences in earnings between female and male full-time workers,

A4

by educational attainment and age group (2016)

Adults with income from employment (full-time workers), average annual earnings of women as a percentage of men’s earnings
Upper secondary or post-secondary
non-tertiary

Partners

OECD

Below upper secondary

Tertiary

25-64

35-44

55-64

25-64

35-44

55-64

25-64

35-44

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

55-64
(9)

Australia
Austria
Belgium1
Canada1
Chile1
Czech Republic1
Denmark
Estonia
Finland1
France2
Germany
Greece
Hungary
Iceland
Ireland3
Israel
Italy2
Japan
Korea
Latvia3
Luxembourg3
Mexico3
Netherlands2
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain1
Sweden
Switzerland
Turkey3
United Kingdom
United States

82

81

80

77

74

70

76

79

73

76

71

70

82

81

80

76

73

80

c

c

c

86

89

c

82

86

c

70

73

74

69

66

72

72

76

66

78

81

74

73

72

74

65

71

59

81

82

83

79

75

86

69

66

82

84

81

83

81

79

83

76

78

72

62

62

61

63

60

72

69

77

69

81

79

80

79

76

79

77

76

74

76

c

c

83

87

95

72

80

c

75

c

76

84

80

89

74

83

82

71

71

70

80

85

67

74

80

63

83

81

84

84

81

87

67

62

76

m

m

m

m

m

m

m

m

m

92

c

c

73

84

59

71

77

75

66

63

54

70

67

73

65

65

66

80

75

79

79

77

77

70

67

73

m

m

m

m

m

m

m

m

m

70

77

66

65

68

62

72

75

74

76

77

85

73

69

78

80

83

90

83

c

c

81

c

c

81

87

c

74

72

75

78

73

93

66

76

35

87

90

88

83

89

79

77

87

75

80

75

85

76

75

84

77

80

73

82

80

81

79

77

78

74

75

71

75

73

76

80

74

87

71

69

74

77

77

74

74

75

68

71

76

69

74

74

74

75

71

81

68

62

73

83

81

83

87

82

95

83

81

87

78

72

89

78

70

80

81

79

82

90

c

93

85

84

84

82

82

77

77

76

73

83

85

82

78

88

78

67

68

c

80

77

c

82

88

c

79

73

84

74

70

73

78

79

67

74

73

87

73

68

78

70

70

71

OECD average
EU22 average

78

76

78

78

76

79

74

77

73

79

76

80

79

78

80

75

77

76

Argentina
Brazil1
China
Colombia
Costa Rica
India
Indonesia
Lithuania2
Russian Federation
Saudi Arabia

m
69
m
78
85
m
m
79
m

m
69
m
79
92
m
m
76
m

m
68
m
75
73
m
m
73
m

m
65
m
79
78
m
m
79
m

m
66
m
76
76
m
m
76
m

m
60
m
78
c
m
m
85
m

m
65
m
79
93
m
m
75
m

m
66
m
80
97
m
m
70
m

m
63
m
69
99
m
m
80
m

m

m

m

m

m

m

m

m

m

South Africa

m

m

m

m

m

m

m

m

m

G20 average

m

m

m

m

m

m

m

m

m

Note: See Definitions and Methodology sections for more information. Data and more breakdowns available at http://stats.oecd.org/, Education at a Glance Database.
1. Year of reference 2015.						
2. Year of reference 2014.						
3. Earnings net of income tax.						
Source: OECD (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933802228

100 Education at a Glance 2018: OECD Indicators   © OECD 2018

What are the earnings advantages from education? – INDICATOR A4

chapter A

Under embargo until 11/09/2018 at 11.00am CEST
Table A4.4. Differences in earnings between native- and foreign-born full-time workers,

A4

by educational attainment and age group (2016)

Adults with income from employment (full-time workers), average annual earnings of foreign-born workers
as a percentage of native-born workers’ earnings
Upper secondary or post-secondary
non-tertiary

OECD

Below upper secondary

Australia
Austria
Belgium1
Canada
Chile2
Czech Republic
Denmark
Estonia
Finland1, 2
France3
Germany
Greece
Hungary
Iceland
Ireland4
Israel
Italy3
Japan
Korea
Latvia4
Luxembourg4
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain2
Sweden
Switzerland
Turkey
United Kingdom
United States

Partners

OECD average
EU22 average
Argentina
Brazil
China
Colombia
Costa Rica
India
Indonesia
Lithuania
Russian Federation
Saudi Arabia

Tertiary

25-64

35-44

55-64

25-64

35-44

55-64

25-64

35-44

55-64

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

m

m

m

m

m

m

m

m

m

84

86

76

77

83

70

82

86

72

87

m

m

82

m

m

108

m

m

m

m

m

m

m

m

m

m

m

88

113

c

66

71

c

133

128

c

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

74

c

89

74

85

82

79

93

71

96

99

109

83

81

85

76

79

77

88

c

c

102

c

c

101

c

c

118

m

m

102

m

m

102

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

85

c

c

85

72

c

93

78

c

95

m

m

89

m

m

91

m

m

82

88

73

69

70

58

68

56

88

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

93

c

116r

92

97

99

86

73

102

82

c

c

75

c

m

101

c

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

73

51

35

80

73

95

81

87

80

81

80

99

85

81

100

91

96

154

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

92

90

96

88

87

88

105

106

100

72

79

74r

63

63

62r

74

56

100r

76

c

c

81

73

87

91

97

87

106

99r

116

89

90

89

99

99

99

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

91

74

118

86

85

82

107

112

92

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m
m
m
101
90
m
m
m
m

m
m
m
c
91
m
m
m
m

m
m
m
c
c
m
m
m
m

m
m
m
125
82
m
m
m
m

m
m
m
96r
c
m
m
m
m

m
m
m
c
c
m
m
m
m

m
m
m
226
94
m
m
m
m

m
m
m
161r
c
m
m
m
m

m
m
m
c
c
m
m
m
m

m

m

m

m

m

m

m

m

m

South Africa

m

m

m

m

m

m

m

m

m

G20 average

m

m

m

m

m

m

m

m

m

Note: See Definitions and Methodology sections for more information. Data and more breakdowns available at http://stats.oecd.org/, Education at a Glance Database.
1. Earnings refer to full-time and part-time workers.
2. Year of reference 2015.						
3. Year of reference 2014.						
4. Earnings net of income tax.						
Source: OECD (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933802247

Education at a Glance 2018: OECD Indicators   © OECD 2018

101

Under embargo until 11/09/2018 at 11.00am CEST

INDICATOR A5

WHAT ARE THE FINANCIAL INCENTIVES TO INVEST
IN EDUCATION?
• Not only does education pay off for individuals financially, but the public sector also benefits
from having a large proportion of tertiary-educated individuals through, for instance, greater tax
revenues and social contributions.

• Adults who complete tertiary education benefit from substantial returns on investment, because
they are more likely to be employed and to earn more than adults without tertiary education.

• Across OECD countries on average, a man invests around USD 52 500 (direct costs plus foregone
earnings) to earn a tertiary degree, while a woman invests around USD 41 700. Because men tend to
have higher earnings and employment rates, they also have higher total benefits over their career:
USD 319 600 for men, compared to USD 234 000 for women.

Figure A5.1. Private net financial returns for a man or a woman attaining
tertiary education (2015)
As compared with returns to upper secondary education, in equivalent USD converted
using PPPs for GDP, future costs and benefits are discounted at a rate of 2%
Equivalent USD
(in thousands)

Man

Woman

600
500
400
300
200

0

Chile
United States
Luxembourg1
Ireland
Switzerland
Hungary
Poland1
Israel
Austria
France1
Japan1
Germany
OECD average
Korea
Canada
New Zealand
Czech Republic
Slovenia
EU22 average
Slovak Republic
Australia
United Kingdom
Denmark1
Portugal
Finland
Norway
Turkey
Italy1
Spain
Belgium
Estonia
Greece
Latvia

100

1. Reference year differs from 2015. Refer to the source table for more details.
Countries are ranked in descending order of private net financial returns for a man.
Source: OECD (2018), Tables A5.1a and A5.1b. See Source section for more information and Annex 3 for notes (http://dx.doi.
org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933802494

Context
Investing time and money in education is an investment in human capital. Better chances of
employment (see Indicator A3) and higher earnings (see Indicator A4) are strong incentives for adults
to invest in education and postpone employment. Although women currently have higher levels of
education than men on average (see Indicator A1), men reap more benefits from their investment, as
they have better employment and earning outcomes from education, on average.
Countries benefit from more highly educated individuals, through reduced public expenditure on
social welfare programmes and higher revenues earned through taxes paid once individuals enter
the labour market. As both individuals and governments benefit from higher levels of educational
attainment, it is important to consider the financial returns to education alongside other indicators,
such as completion and access to higher education (see Indicator B7).
It is crucial for policy makers to understand the economic incentives to invest in education. For
instance, large increases in labour-market demand for more highly educated workers can drive up
earnings and returns until supply catches up. Such conditions signal a need for additional investment
in education.

102 Education at a Glance 2018: OECD Indicators   © OECD 2018

Under embargo until 11/09/2018 at 11.00am CEST
Other factors not reflected in this indicator also affect the returns to education. The financial
returns may be affected by the field of study and by the country-specific economic, labour-market
and institutional context, as well as by social and cultural factors. Furthermore, returns to education
are not limited to financial returns, but also include other economic outcomes, such as increased
productivity boosting economic growth, and social outcomes, such as higher involvement towards
environmental protection (see Indicator A6).

INDICATOR A5

Other findings

• In most OECD countries, the main cost for tertiary education is not direct payments, such as
tuition fees and living expenses, but the earnings individuals forego while they are in school. This
is true even when taking into account the fact that many students work while pursuing further
education.

• Private benefits from investing in education depend on countries’ tax and social benefits systems.
For example, in Chile, Estonia and Korea, income taxes and social contributions amount to less
than a quarter of the gross earning benefits for a man attaining tertiary education, while in
Belgium, they add up to more than half of the gross earning benefits.

• For all countries with available data, the private net financial returns from obtaining a bachelor’s,
master’s or doctoral degree are at least 40% higher than the returns from obtaining a short-cycle
tertiary degree.
Note
This indicator provides information on the incentives to invest in further education by considering
its costs and benefits, including net financial returns and internal rate of return. It examines the
choice between pursuing higher levels of education and entering the labour market, focusing on two
scenarios:
1) investing in tertiary education versus entering the labour market with an upper secondary
degree
2) investing in upper secondary education versus entering the labour market without an upper
secondary degree.
Two types of investors are considered:
1) the individual (referred to here as “private”) who chooses to pursue higher levels of education
and the additional net earnings and costs he or she can expect
2) the government (referred to here as “public”) that decides to invest in education and the
additional revenue it would receive (e.g. as tax revenues) and the costs involved.
This indicator estimates the financial returns on investment in education only up to a theoretical
retirement age of 64 and, therefore, does not take pensions into account. Values are presented
separately for men and women, to account for gender differences in earnings and unemployment
rates. The direct costs to education presented in this indicator do not take into account student loans.
Please note that due to continuous improvements to this indicator’s methodology, the values
presented in this edition of Education at a Glance are not comparable with those in previous editions.

Education at a Glance 2018: OECD Indicators   © OECD 2018

103

chapter A The Output of Educational Institutions and the Impact of Learning
Under embargo until 11/09/2018 at 11.00am CEST

A5

Analysis
Financial incentives for individuals to invest in tertiary education
Figure A5.1 shows that, on average across OECD countries, investing in education pays off in the long run for both
men and women. The gains associated with a higher level of education that individuals can expect to receive over
their career exceed the costs they bear during their studies. This is true for tertiary education, and it also holds for
upper secondary education (Figure A5.1, Tables A5.1a and b, and Tables A5.4a and b, available on line).
Across OECD countries, the average private financial returns from tertiary education for a man are USD 267 100.
Although young women tend to complete higher education more often than young men (see Indicator A1), women
tend to have lower relative net financial returns to investing in tertiary education than men. For a woman, on
average, net financial returns from tertiary education are USD 192 300, representing less than three-quarters of
those for a man (Figure A5.1).
The private financial returns from tertiary education are higher for men than for women in all OECD countries with
available data, with the exception of Belgium, Estonia, Norway, Spain and Turkey. Women in these countries still
faced lower earnings and employment rates than men in 2016, but the gain from a tertiary degree, as compared
to attaining only upper secondary, is higher for women than for men. This means that, in these countries, the gap
between earnings and employment by level of educational attainment is higher for women than for men.
The generally lower returns for women can be attributed to a variety of factors, such as women’s lower earnings,
lower employment rates, a higher share of part-time work on average and differences in choices of field of study
between men and women. The availability of affordable, high-quality early childhood education and care can also
influence women’s employment outcomes. Japan has the largest gender difference, with net financial returns for a
tertiary-educated man about 13 times higher than for a woman with a similar level of education. In Japan, the tax
system and the labour-market structure tend to drive down women’s returns from tertiary education. However,
private net financial returns may increase for Japanese women in the future, as the current government aims to
promote higher labour-market participation among women by introducing a number of specific policy measures
(Cabinet Secretariat, 2016[1]) (Tables A5.1a and b).
Another way to analyse returns to education is through the internal rate of return, which is the real interest rate that
would equalise the costs and benefits, leading the investment to break even. It can be interpreted as the interest rate
on the investment made on a higher level of education that an individual can expect to receive every year during a
working-age life. On average across OECD countries, the internal rate of return to tertiary education is 14% for men
and 16% for women. The higher internal rate of return for women reflects the fact that their initial investment to
attain the higher level of education (in terms of foregone earnings) is lower (Tables A5.1a and b).
The costs and benefits of tertiary education for individuals
Private net financial returns are the difference between the costs and benefits associated with attaining an additional
level of education. In this analysis, the costs include direct costs of attaining education and foregone earnings, while
the benefits include earnings from employment and unemployment benefits. To show the impact of the tax system
on total benefits, the income tax effect, social contributions effect and social transfers effect are also analysed (see
Definitions section at the end of this indicator).
Total private costs (composed of direct costs and foregone earnings) generally rise with the level of education. On
average across OECD countries, the total direct cost for a man or a woman to attain tertiary education is about
USD 9 000. However, in most countries, the main costs are foregone earnings, i.e. the earnings an individual could
expect to receive if he/she decided not to pursue further education. These vary substantially across countries,
depending on the length of education, earnings levels and the difference in earnings across levels of educational
attainment. The current model also takes into account the fact that, in many countries, it is common for students
to work while studying, thus decreasing their foregone earnings and the total cost of education. Indicator A6 in
Education at a Glance 2017 (OECD, 2017[2]) shows the prevalence of student employment and the level of student
earnings across OECD and partner countries.
Foregone earnings for a man while attaining tertiary education vary from USD 8 500 in Turkey to more than
USD 80 000 in Luxembourg. When direct costs and foregone earnings are combined, Japan has the highest total
private costs. A man or woman attaining tertiary education in Japan can expect total costs to be more than seven
times higher than those in Turkey (Tables A5.1a and b).

104 Education at a Glance 2018: OECD Indicators   © OECD 2018

What are the financial incentives to invest in education? – INDICATOR A5

chapter A

Under embargo until 11/09/2018 at 11.00am CEST

Figure A5.2. Private costs and benefits of education for a man or a woman attaining
tertiary education (2015)

A5

As compared with returns to upper secondary education, in equivalent USD converted using PPPs for GDP,
future costs and benefits are discounted at a rate of 2%
Equivalent USD
(in thousands)

Man – total costs

Man – total benefits

Woman – total costs

Woman – total benefits

600
500
400
300
200
100
0

Latvia

Greece

Estonia

Spain

Turkey

Belgium

Italy1

Finland

Portugal

Denmark1

Norway

Slovak Republic

Korea

Slovenia

EU22 average

Canada

Australia

New Zealand

United Kingdom

OECD average

Germany

Czech Republic

Israel

France1

Austria

Japan1

Hungary

Ireland

Poland1

Switzerland

Chile

Luxembourg1

-200

United States

-100

1. Reference year differs from 2015. Refer to the source table for more details.
Countries are ranked in descending order of total private benefits for a man.					
Source: OECD (2018), Tables A5.1a and A5.1b. See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag2018-36-en).
1 2 https://doi.org/10.1787/888933802513

Figure A5.2 shows that the earning advantages of higher education bring considerable benefits for individuals, but
how men and women benefit can depend on country-specific labour-market outcomes. On average, the total benefit
for a tertiary-educated man is USD 319 600, while the total benefit for a tertiary-educated woman is USD 234 000.
This means that, over a career of 40 years, a tertiary-educated man will get about USD 2 100 more per year in
total benefits (compared to a man with only upper secondary education) than a woman with the same level of
education. This is mainly due to gender gaps in earnings (see Indicator A4), but is also related to higher inactivity
and unemployment rates for women (see Indicator A3) (Tables A5.1a and b).
While further education yields higher earnings over the career of an individual, private benefits from investing
in education also depend on countries’ tax and social benefits systems (Brys and Torres, 2013[3]). For instance, in
Chile, Estonia and Korea, income taxes and social contributions amount to less than a quarter of the gross earning
benefits for a man attaining tertiary education, while in Belgium they add up to more than half of the gross earning
benefits. As women tend to have lower earnings, they often fall into lower income tax brackets. For example, in
Greece, Ireland and Israel, the income tax and social contributions relative to gross earnings for a tertiary-educated
woman are about 10 percentage points lower than for a tertiary-educated man (Tables A5.1a and b). Taxes and social
contributions also relate to pensions and retirement programmes, which are not considered in this indicator.
Financial incentives for governments to invest in tertiary education
Governments are major investors in education (see Indicator C3). From a budgetary point of view, it is important
to analyse if these investments will be recovered, particularly in an era of substantial fiscal constraints. Since higher
levels of educational attainment tend to translate into higher earnings (see Indicator A4), investments in education
generate higher public returns, because tertiary-educated adults pay higher income taxes and social contributions
and require fewer social transfers. On average across OECD countries, the public net financial returns are about
USD 135 600 for a man who has completed tertiary education and USD 72 100 for a woman (Tables A5.2a and b).
The net financial returns on investment for governments are generally closely related to private returns. Countries
where individuals benefit the most from pursuing tertiary education are also those where governments gain the
largest returns. This is the case in Ireland, Luxembourg and the United States, countries with very large net financial
private and public returns.
Education at a Glance 2018: OECD Indicators   © OECD 2018

105

chapter A The Output of Educational Institutions and the Impact of Learning
Under embargo until 11/09/2018 at 11.00am CEST
However, different tax systems can considerably affect whether public returns will follow private returns. Chile, for
example, has the highest private returns for a man attaining tertiary education, but because it collects a smaller
share of individuals’ additional earnings in the form of taxes and social contributions, it has the third-lowest public
returns (Tables A5.1a and A5.2a).

Figure A5.3. Public costs and benefits of education for a man or a woman attaining
tertiary education (2015)
As compared with returns to upper secondary education, in equivalent USD converted using PPPs for GDP,
future costs and benefits are discounted at a rate of 2%

Estonia

Chile

Korea

Latvia

Greece

Turkey

Spain

Slovak Republic

Canada

New Zealand

Woman – total benefits

Czech Republic

Poland1

Japan1

United Kingdom

Australia

Switzerland

Woman – total costs

Israel

Finland

Norway

OECD average

Portugal

France1

Man – total benefits

EU22 average

Italy1

Hungary

Denmark1

Belgium

Slovenia

Austria

Germany

Man – total costs

United States

600
500
400
300
200
100
0
-100
-200

Ireland

Equivalent USD
(in thousands)

Luxembourg1

A5

1. Reference year differs from 2015. Refer to the source table for more details.
Countries are ranked in descending order of total public benefits for a man.
Source: OECD (2018), Tables A5.2a and A5.2b. See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag2018-36-en).
1 2 https://doi.org/10.1787/888933802532

The costs and benefits of tertiary education for governments
Public net financial returns are based on the difference between costs and benefits associated with an individual
attaining an additional level of education. In this analysis, the costs include direct public costs for supporting
education and foregone taxes on earnings, while the benefits are calculated using income tax, social contributions,
social transfers and unemployment benefits.
For governments, direct costs represent the largest share of total public costs for tertiary education, even though
student loans are not taken into account in this indicator. This is particularly true in countries such as Denmark,
Finland and Norway, where students pay low or no tuition fees and have access to generous public subsidies for
higher education (see Indicator C5). Countries with high direct costs are also the countries with the largest total
public costs, reaching over USD 100 000 for men in Luxembourg and Norway. In contrast, Chile and Greece have
the lowest total public costs (less than USD 10 000 for men and women) of all OECD countries. On average across
OECD countries, the total public cost to attain tertiary education is USD 48 500 for a man and USD 44 700 for a
woman (Tables A5.2a and b).
Governments offset the costs of direct investment and foregone tax revenue associated with education by receiving
additional tax revenue and social contributions from higher-paid workers, who often have higher educational
attainment. On average, these total public benefits are USD 188 100 for a man with tertiary education and
USD 116 800 for a woman (Tables A5.2a and b).
Total public benefits differ between men and women, mainly due to differences in labour-market outcomes. This
suggests that governments have a role to play in easing the integration and participation of women in the labour
market, in order to assure higher gains from the large investment that women make in their education. On average,
the total public benefits of education for a man attaining tertiary education are about 60% larger than the total
public benefits for a tertiary-educated woman. Across OECD countries, Luxembourg has the largest total public
benefits of tertiary education for a man (USD 467 700) and for a woman (above USD 306 800) (Tables A5.2a and b).

106 Education at a Glance 2018: OECD Indicators   © OECD 2018

What are the financial incentives to invest in education? – INDICATOR A5

chapter A

Under embargo until 11/09/2018 at 11.00am CEST
The internal rate of return to governments is higher for a man (10% for tertiary and 9% for upper secondary) than for
a woman with similar levels of education (8% for tertiary and 5% for upper secondary). This difference by gender is due
to the fact that the public costs (i.e. public investment) are very similar for men and women while the public benefits for
a man are higher than the public benefits for a woman (Tables A5.2a and b, and Tables A5.5a and b, available on line).
On average, the total public benefits (USD 188 100) for a tertiary-educated man can be broken down into income
tax effect (USD 132 500), social contribution effect (USD 51 900), transfers effect (USD 600) and unemployment
benefits effect (USD 3 100). For a tertiary-educated woman, the total public benefits (USD 116 800) can be broken
down into USD 74 700 in income tax effect, USD 37 400 in social contribution effect, USD 2 700 in transfers effect
and USD 2 000 in unemployment benefits effect (Tables A5.2a and b). The transfers effect for a tertiary-educated
man are low on average and close to zero in most countries, because even those with only upper secondary attainment
are likely to reach earnings that are high enough to not qualify for substantial social transfers from the government.
For women, the transfers effect is positive in most countries and higher on average. This difference reflects the
generally lower earnings of women compared to men, particularly among those without tertiary education, which
makes them more likely to receive social transfers from the government.
Higher taxes can sometimes deter private investment in different areas (including education), and a number of
countries have tax policies that effectively lower the actual tax paid by adults, particularly by those in high-income
brackets. For example, tax relief for interest payments on mortgage debt has been introduced in many OECD
countries to encourage home ownership. These benefits favour those with higher levels of education and high
marginal tax rates. The tax incentives for housing are particularly large in the Czech Republic, Denmark, Finland,
Norway and the United States (Andrews, Caldera Sánchez and Johansson, 2011[4]).
Private and public costs and benefits by level of tertiary education
The returns for tertiary education can be broken down into short-cycle tertiary (ISCED 5) and bachelor’s, master’s
and doctoral or equivalent level (ISCED 6 to 8). The composition of the population with qualifications at each
tertiary level differs between countries (see Indicator A1), and the mix of qualifications can have a significant effect
on the financial returns to education for the aggregate tertiary level (Figure A5.4).

Figure A5.4. Private costs and benefits of education for a woman attaining a short-cycle
tertiary degree or a bachelor’s, master’s and doctoral or equivalent degree (2015)
As compared with returns to upper secondary education, in equivalent USD converted using PPPs for GDP,
future costs and benefits are discounted at a rate of 2%
Bachelor’s, master’s, doctoral or equivalent degree – total benefits
Short-cycle tertiary degree – total benefits
Bachelor’s, master’s, doctoral or equivalent degree – total costs
Short-cycle tertiary degree – total costs

Equivalent USD
(in thousands)

550
450
350
250
150
50

Latvia

Greece

Slovak Republic

Estonia

Denmark1

Italy1

Czech Republic

Hungary

Korea

Belgium

Germany

Portugal

EU22 average

Finland

OECD average

France1

Poland1

New Zealand

United Kingdom

Austria

Norway

Israel

Canada

Australia

Switzerland

United States

Ireland

-150

Chile

-50

Note: Short-cycle tertiary degree corresponds to ISCED level 5 and bachelor’s, master’s, doctoral or equivalent degree corresponds to ISCED levels 6,
7 and 8.
1. Year of reference differs from 2015. Refer to the source table for further details.
Countries are ranked in descending order of total private benefits for a woman with a bachelor’s, master’s, doctoral or equivalent degree.
Source: OECD (2018), Table A5.3b. See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933802551

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107

A5

chapter A The Output of Educational Institutions and the Impact of Learning
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A5

For all countries with available data, the private net financial returns from obtaining a bachelor’s, master’s, doctoral
or equivalent degree are greater than from obtaining a short-cycle tertiary degree. With the exception of Korea,
this is also the case for the public net financial returns. Although the total costs of a bachelor’s, master’s, doctoral
or equivalent degree tend to be higher than those of a short-cycle tertiary degree, the total benefits accrued along
individuals’ working lives compensate for the higher initial costs (Tables A5.3a and b).
Therefore, private financial returns for the aggregate tertiary level will underestimate the value of investing in
bachelor’s, master’s and doctoral degrees, especially in countries with a larger share of adults whose highest level of
attainment is short-cycle tertiary.

Box A5.1. The effect of the discount rate on the net financial returns to education
The calculation of the financial returns, or the net present value (NPV), of education corresponds to a costbenefit analysis that converts future expected flows into a present value by using a discount rate. The discount
rate takes into account the fact that money tomorrow is worth less than money today, and must therefore be
“discounted” at a specific rate to find its current worth. The choice of the discount rate is challenging, and it
will make a considerable difference when analysing the returns to long-term investments, as is the case with
investment in education.
The results presented in the tables and figures of this indicator are calculated using a discount rate of 2%,
based on the average real interest on government bonds across OECD countries. However, it can be argued
that education is not a risk-free investment, and that the discount rate should therefore be higher.
OECD countries that perform similar cost-benefit analysis use higher discount rates than 2%, but the rate
used varies widely across countries. Table A5.a shows the discount rate used by some OECD governments to
assess public investments, not necessarily education-related investments.

Table A5.a. Discount rates used by governments in national cost-benefit analysis
Discount rate (%)
Australia

7.0

Canada

8.0

Chile

6.0

France

4.0

Germany

3.0

Ireland

5.0

Italy

5.0

New Zealand

6 to 8

Norway

3.5

United Kingdom

3.5

United States

7.0

Source: OECD (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933802570

In order to assess the magnitude of the impact of the discount rate it is helpful to perform a sensitivity
analysis. Table A5.b shows how the net present value for a man attaining tertiary education changes when
three different discount rates are used. Changing from a discount rate of 2% to a rate of 3.75% reduces the
NPV by over 30% in all countries with available data. If a discount rate of 8% is used, the NPV falls by over 70%
in all countries and even becomes negative in Norway. These comparisons highlight the sensitivity of the NPV
results to changes in the discount rate.

…

108 Education at a Glance 2018: OECD Indicators   © OECD 2018

What are the financial incentives to invest in education? – INDICATOR A5

chapter A

Under embargo until 11/09/2018 at 11.00am CEST

Table A5.b. Net financial returns for a man attaining tertiary education, by discount rate (2015)
As compared with a man attaining upper secondary education, in equivalent USD converted using PPPs for GDP
Discount rate
2%

3.75%

(1)

(2)

8%
(3)

Australia
Austria
Belgium
Canada
Chile
Czech Republic
Denmark
Estonia
Finland
France1
Germany
Greece
Hungary
Ireland
Israel
Italy1
Japan2
Korea
Latvia
Luxembourg1
New Zealand
Norway
Poland1
Portugal
Slovak Republic
Slovenia
Spain
Switzerland
Turkey
United Kingdom
United States

234 500
309 700
170 300
255 600
516 500
252 100
204 400
119 200
200 600
308 500
282 800
114 000
339 300
417 500
330 500
185 100
284 600
261 000
86 700
430 600
252 500
198 700
336 000
201 500
237 900
245 100
176 600
414 900
189 900
231 700
495 000

132 300
166 500
94 600
152 500
334 300
145 700
115 200
68 400
116 900
178 300
166 300
64 300
221 500
268 000
224 100
93 600
160 400
168 900
52 400
249 100
151 300
98 700
210 300
107 300
143 400
141 900
100 900
248 500
124 300
134 800
311 400

22 800
25 300
15 400
41 000
134 300
29 900
21 800
12 500
27 500
43 500
41 400
12 800
85 800
101 800
98 100
4 500
28 200
67 100
13 000
58 800
42 200
- 2 400
70 300
13 300
39 500
33 400
22 200
69 500
51 100
27 700
108 700

OECD average
EU22 average

267 100
242 500

159 552
147 043

43 903
36 662

Note: Values are based on the difference between men who attained a tertiary education compared with those who have attained an
upper secondary education. Values have been rounded up to the nearest hundred.
1. Year of reference 2014.
2. Year of reference 2012. Students’ earnings are not included in the calculation of foregone earnings.
Source: OECD (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933802589

Definitions
Adults refer to 15-64 year-olds.
Direct costs are the direct expenditure on education per student during the time spent in school. Direct cost to
education does not include student loans.
• Private direct costs are the total expenditure by households on education. They include net payments to
educational institutions as well as payments for educational goods and services outside of educational institutions
(school supplies, tutoring, etc.).
• Public direct costs are the spending by government on a student’s education. They include direct public
expenditure on educational institutions, government scholarships and other grants to students and households,
and transfers and payments to other private entities for educational purposes. They do not include student loans.
Foregone earnings are the net earnings an individual would have had if he or she had entered the labour market and
successfully found a job minus the net earnings an individual can expect to have while studying.
Education at a Glance 2018: OECD Indicators   © OECD 2018

109

A5

chapter A The Output of Educational Institutions and the Impact of Learning
Under embargo until 11/09/2018 at 11.00am CEST
Foregone taxes on earnings are the additional tax revenues the government would have received if the individual
had chosen to enter the labour force and successfully found a job instead of choosing to pursue further studies.
Gross earnings benefits are the discounted sum of earnings premiums over the course of a working-age life
associated with a higher level of education, provided that the individual successfully enters the labour market.
The income tax effect is the discounted sum of additional levels of income tax paid by the private individual or
earned by the government over the course of a working-age life associated with a higher level of education.
The internal rate of return is the (hypothetical) real interest rate equalising the costs and benefits related to the
educational investment. It can be interpreted as the interest rate an individual can expect to receive every year
during a working-age life on the investment made on a higher level of education.
Levels of education: See the Reader’s Guide at the beginning of this publication for a presentation of all ISCED 2011
levels.
Net financial returns are the net present value of the financial investment in education, the difference between the
discounted financial benefits and the discounted financial cost of education, representing the additional value that
education produces over and above the 2% real interest that is charged on these cash flows.
The social contribution effect is the discounted sum of additional employee social contributions paid by the private
individual or received by the government over the course of a working-age life and associated with a higher level of
education.
The transfers effect is the discounted sum of additional social transfers from the government to the private
individual associated with a higher education level over the course of a working-age life. Social transfers include two
types of benefits: housing benefits and social assistance.
The unemployment benefit effect is the discounted sum of additional unemployment benefits associated with a
higher education level over the course of a working-age life and received during periods of unemployment.

Methodology
This indicator estimates the financial returns on investment in education from the age of entry into further
education to a theoretical retirement age of 64. Returns to education are studied purely from the perspective of
financial investment that weighs the costs and benefits of the investment.
Two periods are considered (Diagram 1):
1) time spent in school during which the private individual and the government pay the cost of education
2) time spent in the labour market during which the individual and the government receive the added payments
associated with further education.
In calculating the returns to education, the approach taken here is the net present value of the investment. To allow
direct comparisons of costs and benefits, the NPV expresses present value for cash transfers happening at different
times. In this framework, costs and benefits during a working-age life are transferred back to the start of the
investment. This is done by discounting all cash flows back to the beginning of the investment with a fixed interest
rate (discount rate).

Diagram 1. Financial returns on investment in education over a life-time
for a representative individual
Foregone earnings

Direct cost

Net additional earnings

In school

In the labour market

Total costs
Total benefits

Y1
Y2
Y3
Y4
Y5
Y6
Y7
Y8
Y9
Y10
Y11
Y12
Y13
Y14
Y15
Y16
Y17
Y18
Y19
Y20
Y21
Y22
Y23
Y24
Y25
Y26
Y27
Y28
Y29
Y30
Y31
Y32
Y33
Y34
Y35
Y36
Y37
Y38
Y39
Y40
…
…
…
…

A5

110 Education at a Glance 2018: OECD Indicators   © OECD 2018

What are the financial incentives to invest in education? – INDICATOR A5

chapter A

Under embargo until 11/09/2018 at 11.00am CEST
To set a value for the discount rate, long-term government bonds have been used as a benchmark. The choice of
discount rate is challenging, as it should reflect not only the overall time horizon of the investment, but also the
cost of borrowing or the perceived risk of the investment (Box A5.1). To allow for comparability and to facilitate
interpretation of results, the same discount rate (2%) is applied across all OECD countries. All values presented in
the tables in this indicator are in NPV equivalent USD using purchasing power parities (PPPs).
Changes in the methodology between Education at a Glance 2018 and 2017
Three important methodological changes were introduced in this edition:
1) The current model includes student earnings in the calculation of the foregone earnings. In the previous
edition, it was assumed that students did not work and did not have earnings or pay taxes. The model continues
to assume that students do not receive any transfers from the government.
2) The current model takes into account the probability of individuals being inactive, by using the employment
rate instead of 1 minus the unemployment rate as the probability of having earnings.
3) Pooled earnings data from three different years are used instead of the earnings from a single reference year.
In addition, the reference year for this indicator has been moved one year forward. The reference year for this
edition is 2015, while the reference year for last year’s edition was 2013.
Please see the OECD Handbook for Internationally Comparative Education Statistics 2018 (OECD, 2018[5]) for more
information and Annex 3 for country-specific notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Lithuania was not an OECD member at the time of preparation of this publication. Accordingly, Lithuania does not
appear in the list of OECD members and is not included in the zone aggregates.

Source
The source for the direct costs of education is the UOE data collection on finance (year of reference 2015 unless
otherwise specified in the tables).
The data on gross earnings are from the OECD Network on Labour Market and Social Outcomes earnings data
collection. Earnings are age-, gender- and attainment-level specific. For the calculation of this indicator, data on
earnings has been pooled from three different years (2013-15). A moving average will be used for future editions.
Income tax data are computed using the OECD Taxing Wages model, which determines the level of taxes based on a
given level of income. This model computes the level of the tax wedge on income for several household composition
scenarios. For this indicator, a single worker with no children is used. For country-specific details on income tax in
this model, see Taxing Wages 2017 (OECD, 2017[6]).
Employee social contributions are computed using the OECD Taxing Wages model’s scenario of a single worker of
age 40 with no children. For country-specific details on employee social contributions in this model, see Taxing
Wages 2017 (OECD, 2017[6]).
Social transfers and unemployment benefits are computed using the OECD Tax-Benefit model, assuming a single
worker of age 40 with no children. Individuals are considered eligible for full unemployment benefits during
unemployment. For country-specific details on social transfers or unemployment benefits in the Tax-Benefit model,
see OECD Benefits and Wages country-specific information, available on line at www.oecd.org/els/soc/benefitsand-wages-country-specific-information.htm.
Note regarding data from Israel
The statistical data for Israel are supplied by and are under the responsibility of the relevant Israeli authorities. The use
of such data by the OECD is without prejudice to the status of the Golan Heights, East Jerusalem and Israeli settlements
in the West Bank under the terms of international law.

References
Andrews, D., A. Caldera Sánchez and Å. Johansson (2011), “Housing markets and structural policies in OECD countries”, [4]
OECD Economics Department Working Papers, No. 836, OECD Publishing, Paris, http://dx.doi.org/10.1787/5kgk8t2k9vf3-en.
Brys, B. and C. Torres (2013), “Effective personal tax rates on marginal skills investments in OECD countries: A new [3]
methodology”, OECD Taxation Working Papers, No. 16, OECD Publishing, Paris, http://dx.doi.org/10.1787/5k425747xbr6-en.

Education at a Glance 2018: OECD Indicators   © OECD 2018

111

A5

chapter A The Output of Educational Institutions and the Impact of Learning
Under embargo until 11/09/2018 at 11.00am CEST

A5

Cabinet Secretariat (2016), Japan Revitalization Strategy (Growth Strategy) Revised in 2015: Main Achievements to Date and [1]
Further Reforms, www.kantei.go.jp/jp/singi/keizaisaisei/pdf/new_seika_torikumien.pdf.
OECD (2018), OECD Handbook for Internationally Comparative Education Statistics 2018: Concepts, Standards, Definitions [5]
and Classifications, OECD Publishing, Paris, https://doi.org/10.1787/9789264304444-en.
OECD (2017), Education at a Glance 2017: OECD Indicators, OECD Publishing, Paris, http://dx.doi.org/10.1787/eag-2017-en. [2]
OECD (2017), Taxing Wages 2017, OECD Publishing, Paris, http://dx.doi.org/10.1787/tax_wages-2017-en.

[6]

Indicator A5 Tables
1 2 https://doi.org/10.1787/888933802361

Table A5.1a Private costs and benefits for a man attaining tertiary education (2015)
Table A5.1b Private costs and benefits for a woman attaining tertiary education (2015)
Table A5.2a Public costs and benefits for a man attaining tertiary education (2015)
Table A5.2b Public costs and benefits for a woman attaining tertiary education (2015)
Table A5.3a Private/public costs and benefits for a man attaining tertiary education,
by level of tertiary education (2015)
Table A5.3b Private/public costs and benefits for a woman attaining tertiary education,
by level of tertiary education (2015)
WEB Table A5.4a Private costs and benefits for a man attaining upper secondary education (2015)
WEB Table A5.4b Private costs and benefits for a woman attaining upper secondary education (2015)
WEB Table A5.5a Public costs and benefits for a man attaining upper secondary education (2015)
WEB Table A5.5b Public costs and benefits for a woman attaining upper secondary education (2015)
Cut-off date for the data: 18 July 2018. Any updates on data can be found on line at http://dx.doi.org/10.1787/eag-data-en. Data can also be found
at http://stats.oecd.org/, Education at a Glance Database.

112 Education at a Glance 2018: OECD Indicators   © OECD 2018

What are the financial incentives to invest in education? – INDICATOR A5

chapter A

Under embargo until 11/09/2018 at 11.00am CEST
Table A5.1a. Private costs and benefits for a man attaining tertiary education (2015)
As compared with a man attaining upper secondary education, in equivalent USD converted using PPPs for GDP,
future costs and benefits are discounted at a rate of 2%

A5

OECD

Earnings benefits decomposition
(taking into account the unemployment effect)
Social
Gross
earnings Income contribution
effect
benefits tax effect

Internal
rate
of return

Transfers
effect

Unemployment
benefits
effect

Total
benefits

Net
financial
returns

(7)

(8)

(9)=(4)+(5)
+(6)+(7)+(8)

(10)=(9)+(3)

(11)

- 2 500

308 600

234 500

10%

0

- 2 300

372 300

309 700

10%

0

- 11 100

220 500

170 300

10%

- 14 900

0

- 7 000

310 600

255 600

13%

- 13 200

- 41 200

0

11 500

545 500

516 500

31%

- 92 500

- 51 600

0

- 4 000

321 200

252 100

11%

0

- 15 600

1 400

255 600

204 400

11%

- 2 800

0

- 1 800

161 700

119 200

10%

- 35 100

0

4 300

247 900

200 600

12%

572 500 - 134 600

- 74 600

- 100

2 000

365 200

308 500

12%

677 100 - 208 700

- 118 500

0

- 5 400

344 500

282 800

12%

- 30 900

- 32 800

0

- 4 100

141 900

114 000

11%

- 94 500

- 109 300

0

- 5 300

381 600

339 300

20%

m

m

m

m

m

m

m

- 45 900

885 500 - 366 900

- 35 700

- 900

- 18 600

463 400

417 500

22%

- 16 800

- 24 400

536 800 - 119 200

- 60 200

0

- 2 500

354 900

330 500

30%

- 35 300

- 43 900

438 100 - 161 600

- 42 500

0

- 5 000

229 000

185 100

8%

- 29 600

- 59 300

- 88 900

527 300

- 77 700

- 70 300

0

- 5 800

373 500

284 600

10%

Korea

- 7 600

- 19 700

- 27 300

352 200

- 37 100

- 29 500

0

2 700

288 300

261 000

25%

Latvia

- 9 200

- 22 500

- 31 700

181 200

- 35 800

- 19 000

0

- 8 000

118 400

86 700

11%

Luxembourg1

0

- 85 300

- 85 300

983 600 - 344 000

- 121 100

0

- 2 600

515 900

430 600

12%

Mexico

m

m

m

m

m

m

m

m

m

m

m

Netherlands

m

m

m

m

m

m

m

m

m

m

m

New Zealand

- 18 700

- 41 800

- 60 500

446 400 - 131 400

0

0

- 2 000

313 000

252 500

13%

Norway

0

- 70 300

- 70 300

456 700 - 147 600

- 37 500

0

- 2 600

269 000

198 700

8%

Poland1

- 3 000

- 45 900

- 48 900

533 900

- 95 200

0

- 7 900

384 900

336 000

16%

Direct
costs

Foregone
earnings

Total
costs

(1)

(2)

(3)=(1)+(2)

- 31 500

- 42 600

- 74 100

482 900 - 171 800

0

0

Austria

0

- 62 600

- 62 600

678 400 - 208 100

- 95 700

Belgium

- 1 400

- 48 800

- 50 200

489 000 - 187 100

- 70 300

Canada

- 20 800

- 34 200

- 55 000

457 800 - 125 300

Chile

- 10 400

- 18 600

- 29 000

588 400

Czech Republic

- 4 200

- 64 900

- 69 100

469 300

Denmark1

0

- 51 200

- 51 200

493 300 - 223 500

Estonia

0

- 42 500

- 42 500

204 000

- 37 700

Finland

0

- 47 300

- 47 300

430 900 - 152 200

France1

- 5 400

- 51 300

- 56 700

Germany

- 3 400

- 58 300

- 61 700

Greece

- 3 300

- 24 600

- 27 900

209 700

Hungary

- 9 000

- 33 300

- 42 300

590 700

Iceland

m

m

m

m

Ireland

0

- 45 900

Israel

- 7 600

Italy1

- 8 600

Japan2

Australia

(4)

(5)

(6)

- 45 900

Portugal

- 8 400

- 46 100

- 54 500

458 300 - 157 100

- 50 400

0

5 200

256 000

201 500

9%

Slovak Republic

- 6 500

- 37 300

- 43 800

397 800

- 63 200

- 53 300

0

400

281 700

237 900

13%

Slovenia

- 500

- 48 200

- 48 700

537 700 - 116 200

- 118 800

0

- 8 900

293 800

245 100

12%

Spain

- 10 500

- 31 500

- 42 000

339 400

- 85 000

- 21 500

0

- 14 300

218 600

176 600

11%

m

m

m

m

m

m

m

m

m

m

m

- 6 600

- 71 500

- 78 100

655 300 - 129 800

- 40 800

0

8 300

493 000

414 900

14%
31%

Sweden
Switzerland
Turkey

- 3 100

- 8 500

- 11 600

295 400

- 54 000

- 44 300

0

4 400

201 500

189 900

United Kingdom

- 39 500

- 41 100

- 80 600

466 300

- 97 400

- 52 600

- 1 000

- 3 000

312 300

231 700

11%

United States

- 35 700

- 35 000

- 70 700

904 300 - 257 500

- 69 200

0

- 11 900

565 700

495 000

18%

OECD average

- 9 200

- 43 300

- 52 500

507 700 - 132 500

- 51 900

- 600

- 3 100

319 600

267 100

14%

EU22 average

- 5 600

- 46 200

- 51 800

501 800 - 142 100

- 60 000

- 900

- 4 500

294 300

242 500

12%

Note: Values are based on the difference between men who attained a tertiary education compared with those who have attained an upper secondary education.
Values have been rounded up to the nearest hundred. Direct cost to education does not include student loans.
Due to changes in the methodology, values in this edition of Education at a Glance cannot be compared to results from previous editions. See Definitions and
Methodology sections for more information.
1. Year of reference 2014.
2. Year of reference 2012. Students’ earnings are not included in the calculation of foregone earnings.
Source: OECD (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933802380

Education at a Glance 2018: OECD Indicators   © OECD 2018

113

chapter A The Output of Educational Institutions and the Impact of Learning
Under embargo until 11/09/2018 at 11.00am CEST
Table A5.1b. Private costs and benefits for a woman attaining tertiary education (2015)
As compared with a woman attaining upper secondary education, in equivalent USD converted using PPPs for GDP,
future costs and benefits are discounted at a rate of 2%

A5

OECD

Earnings benefits decomposition
(taking into account the unemployment effect)
Social
Gross
Unemployment
earnings Income contribution Transfers
benefits
effect
effect
benefits tax effect
effect

Direct
costs

Foregone
earnings

Total
costs

(1)

(2)

(3)=(1)+(2)

(4)

(5)

- 31 500

- 24 300

- 55 800

410 700

- 125 300

Austria

0

- 55 600

- 55 600

395 700

Belgium

- 1 400

- 39 600

- 41 000

461 800

Canada

- 20 800

- 20 100

- 40 900

341 600

Chile

- 10 400

- 9 200

- 19 600

355 800

Czech Republic

Australia

Total
benefits

Net
financial
returns

Internal
rate
of return

(7)

(8)

(9)=(4)+(5)
+(6)+(7)+(8)

(10)=(9)+(3)

(11)

0

- 100

- 5 900

279 400

223 600

14%

- 95 600

- 75 300

0

- 2 300

222 500

166 900

9%

- 149 500

- 87 000

0

- 9 100

216 200

175 200

15%

- 64 500

- 27 300

- 800

1 200

250 200

209 300

17%

- 2 000

- 24 900

0

7 400

336 300

316 700

35%

(6)

- 4 200

- 47 300

- 51 500

268 300

- 50 000

- 29 500

- 4 500

- 6 300

178 000

126 500

8%

Denmark1

0

- 25 300

- 25 300

311 600

- 120 600

0

- 6 300

- 5 300

179 400

154 100

18%

Estonia

0

- 21 500

- 21 500

182 700

- 33 100

- 2 700

0

- 300

146 600

125 100

19%

Finland

0

- 45 300

- 45 300

345 100

- 105 500

- 28 400

- 200

0

211 000

165 700

13%

France1

- 5 400

- 41 500

- 46 900

356 000

- 70 200

- 49 100

- 6 200

- 4 100

226 400

179 500

13%

Germany

- 3 400

- 46 500

- 49 900

382 700

- 88 400

- 78 300

- 1 000

- 1 900

213 100

163 200

10%

Greece

- 3 300

- 23 700

- 27 000

172 800

- 7 300

- 26 900

0

- 5 200

133 400

106 400

12%

Hungary

14%

- 9 000

- 26 300

- 35 300

301 600

- 48 300

- 55 800

0

- 5 300

192 200

156 900

Iceland

m

m

m

m

m

m

m

m

m

m

m

Ireland

0

- 34 700

- 34 700

571 600

- 160 400

- 24 400

- 600

- 4 900

381 300

346 600

29%

Israel

- 7 600

- 7 400

- 15 000

322 700

- 42 900

- 32 200

0

3 500

251 100

236 100

35%

Italy1

- 8 600

- 26 200

- 34 800

303 800

- 83 900

- 28 800

0

- 1 700

189 400

154 600

10%

Japan2

- 29 600

- 52 600

- 82 200

201 700

- 16 600

- 27 600

- 50 200

- 4 100

103 200

21 000

3%

Korea

- 7 600

- 23 700

- 31 300

204 400

- 7 400

- 17 100

0

2 600

182 500

151 200

19%

Latvia

- 9 200

- 13 100

- 22 300

148 900

- 29 200

- 15 600

0

400

104 500

82 200

13%

Luxembourg1

0

- 76 300

- 76 300

709 700

- 225 100

- 88 100

0

6 400

402 900

326 600

14%

Mexico

m

m

m

m

m

m

m

m

m

m

m

Netherlands

m

m

m

m

m

m

m

m

m

m

m

New Zealand

- 18 700

- 36 200

- 54 900

355 500

- 78 200

0

- 2 100

- 8 200

267 000

212 100

15%

Norway

0

- 44 300

- 44 300

384 700

- 92 700

- 31 500

0

- 1 500

259 000

214 700

14%

Poland1

- 3 000

- 29 300

- 32 300

380 700

- 31 000

- 67 900

0

- 8 800

273 000

240 700

19%

Portugal

- 8 400

- 34 500

- 42 900

354 200

- 108 400

- 39 000

0

4 100

210 900

168 000

11%

Slovak Republic

- 6 500

- 21 800

- 28 300

233 400

- 34 700

- 31 700

0

- 3 400

163 600

135 300

12%

Slovenia

- 500

- 29 700

- 30 200

421 200

- 79 200

- 93 100

0

- 13 000

235 900

205 700

15%

Spain

- 10 500

- 23 700

- 34 200

329 800

- 68 800

- 20 900

0

- 2 300

237 800

203 600

15%

Sweden
Switzerland

m

m

m

m

m

m

m

m

m

m

m

- 6 600

- 70 500

- 77 100

474 900

- 67 300

- 29 700

0

3 600

381 500

304 400

14%
41%

Turkey

- 3 100

- 4 500

- 7 600

282 500

- 39 300

- 42 400

0

10 500

211 300

203 700

United Kingdom

- 39 500

- 33 800

- 73 300

369 500

- 71 200

- 42 300

- 12 200

- 1 300

242 500

169 200

10%

United States

- 35 700

- 18 400

- 54 100

539 900

- 118 200

- 41 300

0

- 6 400

374 000

319 900

18%

OECD average

- 9 200

- 32 500

- 41 700

350 800

- 74 700

- 37 400

- 2 700

- 2 000

234 000

192 300

16%

EU22 average

- 5 600

- 34 800

- 40 400

350 100

- 83 000

- 44 200

- 1 600

- 3 200

218 100

177 700

13%

Note: Values are based on the difference between women who attained a tertiary education compared with those who have attained an upper secondary education.
Values have been rounded up to the nearest hundred. Direct cost to education does not include student loans.
Due to changes in the methodology, values in this edition of Education at a Glance cannot be compared to results from previous editions. See Definitions and
Methodology sections for more information.
1. Year of reference 2014.
2. Year of reference 2012. Students’ earnings are not included in the calculation of foregone earnings.
Source: OECD (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933802399

114 Education at a Glance 2018: OECD Indicators   © OECD 2018

chapter A

What are the financial incentives to invest in education? – INDICATOR A5

Under embargo until 11/09/2018 at 11.00am CEST
Table A5.2a. Public costs and benefits for a man attaining tertiary education (2015)
As compared with a man attaining upper secondary education, in equivalent USD converted using PPPs for GDP,
future costs and benefits are discounted at a rate of 2%

A5

OECD

Earnings benefits decomposition
(taking into account the unemployment effect)
Direct
costs

Foregone
taxes on
earnings

Total
costs

Income
tax effect

Social
contribution
effect

Transfers
effect

Unemployment
benefits
effect

(1)

(2)

(3)=(1)+(2)

(4)

(5)

(6)

(7)

(8)=(4)+(5)
+(6)+(7)

(9)=(8)+(3)

(10)

Australia

- 29 600

- 5 300

- 34 900

171 800

0

0

2 500

174 300

139 400

11%

Austria

- 65 500

- 16 100

- 81 600

208 100

95 700

0

2 300

306 100

224 500

8%

Belgium

- 52 000

- 300

- 52 300

187 100

70 300

0

11 100

268 500

216 200

11%

Canada

- 40 700

- 3 300

- 44 000

125 300

14 900

0

7 000

147 200

103 200

8%

Chile

- 8 700

800

- 7 900

13 200

41 200

0

- 11 500

42 900

35 000

10%

Czech Republic

- 30 000

- 11 700

- 41 700

92 500

51 600

0

4 000

148 100

106 400

9%

Denmark1

- 80 400

- 6 600

- 87 000

223 500

0

15 600

- 1 400

237 700

150 700

7%

Estonia

- 42 700

- 5 300

- 48 000

37 700

2 800

0

1 800

42 300

- 5 700

1%

Finland

- 75 100

18 000

- 57 100

152 200

35 100

0

- 4 300

183 000

125 900

8%
10%

Total
benefits

Net
financial
returns

Internal
rate
of return

France1

- 51 700

6 600

- 45 100

134 600

74 600

100

- 2 000

207 300

162 200

Germany

- 68 700

- 22 600

- 91 300

208 700

118 500

0

5 400

332 600

241 300

9%

Greece

- 12 800

9 300

- 3 500

30 900

32 800

0

4 100

67 800

64 300

17%

Hungary

15%

- 23 400

- 12 200

- 35 600

94 500

109 300

0

5 300

209 100

173 500

Iceland

m

m

m

m

m

m

m

m

m

m

Ireland

- 43 900

12 500

- 31 400

366 900

35 700

900

18 600

422 100

390 700

21%

Israel

- 24 200

1 100

- 23 100

119 200

60 200

0

2 500

181 900

158 800

16%

Italy1

- 35 600

9 500

- 26 100

161 600

42 500

0

5 000

209 100

183 000

11%

Japan2

- 23 000

- 11 200

- 34 200

77 700

70 300

0

5 800

153 800

119 600

10%

Korea

- 19 200

- 1 900

- 21 100

37 100

29 500

0

- 2 700

63 900

42 800

7%

Latvia

- 29 100

- 4 100

- 33 200

35 800

19 000

0

8 000

62 800

29 600

6%

Luxembourg1

- 167 900

- 9 700

- 177 600

344 000

121 100

0

2 600

467 700

290 100

7%

m

m

m

m

m

m

m

m

m

m

Mexico
Netherlands

m

m

m

m

m

m

m

m

m

m

New Zealand

- 32 000

- 2 300

- 34 300

131 400

0

0

2 000

133 400

99 100

10%

Norway

- 81 600

- 19 200

- 100 800

147 600

37 500

0

2 600

187 700

86 900

4%

Poland1

- 31 100

- 5 400

- 36 500

45 900

95 200

0

7 900

149 000

112 500

11%

Portugal

- 33 800

5 100

- 28 700

157 100

50 400

0

- 5 200

202 300

173 600

11%

Slovak Republic

- 52 800

- 1 200

- 54 000

63 200

53 300

0

- 400

116 100

62 100

6%

Slovenia

- 35 700

- 9 600

- 45 300

116 200

118 800

0

8 900

243 900

198 600

11%

Spain

- 35 500

10 700

- 24 800

85 000

21 500

0

14 300

120 800

96 000

9%

m

m

m

m

m

m

m

m

m

m

Switzerland

- 96 200

- 3 000

- 99 200

129 800

40 800

0

- 8 300

162 300

63 100

4%

Turkey

- 24 600

800

- 23 800

54 000

44 300

0

- 4 400

93 900

70 100

9%

United Kingdom

- 27 900

1 500

- 26 400

97 400

52 600

1 000

3 000

154 000

127 600

16%

United States

- 48 600

- 4 900

- 53 500

257 500

69 200

0

11 900

338 600

285 100

14%

OECD average

- 45 900

- 2 600

- 48 500

132 500

51 900

600

3 100

188 100

139 600

10%

EU22 average

- 49 800

- 1 600

- 51 400

142 100

60 000

900

4 500

207 500

156 200

10%

Sweden

Note: Values are based on the difference between men who attained a tertiary education compared with those who have attained an upper secondary education.
Values have been rounded up to the nearest hundred. Direct cost to education does not include student loans.
Due to changes in the methodology, values in this edition of Education at a Glance cannot be compared to results from previous editions. See Definitions and
Methodology sections for more information.
1. Year of reference 2014.
2. Year of reference 2012. Students’ earnings are not included in the calculation of foregone earnings.
Source: OECD (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933802418

Education at a Glance 2018: OECD Indicators   © OECD 2018

115

chapter A The Output of Educational Institutions and the Impact of Learning
Under embargo until 11/09/2018 at 11.00am CEST
Table A5.2b. Public costs and benefits for a woman attaining tertiary education (2015)
As compared with a woman attaining upper secondary education, in equivalent USD converted using PPPs for GDP,
future costs and benefits are discounted at a rate of 2%

A5

OECD

Earnings benefits decomposition
(taking into account the unemployment effect)
Direct
costs

Foregone
taxes on
earnings

Total
costs

Income
tax effect

Social
contribution
effect

Transfers
effect

Unemployment
benefits effect

Total
benefits

(1)

(2)

(3)=(1)+(2)

(4)

(5)

(6)

(7)

(8)=(4)+(5)
+(6)+(7)

(9)=(8)+(3)

(10)

Australia

- 29 600

- 500

- 30 100

125 300

0

100

5 900

131 300

101 200

12%

Austria

- 65 500

- 10 200

- 75 700

95 600

75 300

0

2 300

173 200

97 500

6%

Belgium

- 52 000

4 200

- 47 800

149 500

87 000

0

9 100

245 600

197 800

13%

Canada

- 40 700

- 800

- 41 500

64 500

27 300

800

- 1 200

91 400

49 900

7%

Chile

- 8 700

800

- 7 900

2 000

24 900

0

- 7 400

19 500

11 600

7%

Czech Republic

- 30 000

- 3 800

- 33 800

50 000

29 500

4 500

6 300

90 300

56 500

7%

Denmark1

- 80 400

3 300

- 77 100

120 600

0

6 300

5 300

132 200

55 100

5%

Estonia

- 42 700

- 1 500

- 44 200

33 100

2 700

0

300

36 100

- 8 100

1%

Finland

- 75 100

21 400

- 53 700

105 500

28 400

200

0

134 100

80 400

7%

France1

- 51 700

10 400

- 41 300

70 200

49 100

6 200

4 100

129 600

88 300

10%

Germany

- 68 700

- 15 500

- 84 200

88 400

78 300

1 000

1 900

169 600

85 400

5%

Greece

- 12 800

11 600

- 1 200

7 300

26 900

0

5 200

39 400

38 200

22%

Hungary

9%

Net
financial
returns

Internal
rate
of return

- 23 400

- 9 500

- 32 900

48 300

55 800

0

5 300

109 400

76 500

Iceland

m

m

m

m

m

m

m

m

m

m

Ireland

- 43 900

9 400

- 34 500

160 400

24 400

600

4 900

190 300

155 800

14%

Israel

- 24 200

2 600

- 21 600

42 900

32 200

0

- 3 500

71 600

50 000

9%

Italy1

- 35 600

9 600

- 26 000

83 900

28 800

0

1 700

114 400

88 400

8%

Japan2

- 23 000

700

- 22 300

16 600

27 600

50 200

4 100

98 500

76 200

13%

Korea

- 19 200

- 2 200

- 21 400

7 400

17 100

0

- 2 600

21 900

500

2%

Latvia

- 29 100

600

- 28 500

29 200

15 600

0

- 400

44 400

15 900

4%

Luxembourg1

- 167 900

- 10 100

- 178 000

225 100

88 100

0

- 6 400

306 800

128 800

5%

Mexico

m

m

m

m

m

m

m

m

m

m

Netherlands

m

m

m

m

m

m

m

m

m

m

New Zealand

- 32 000

300

- 31 700

78 200

0

2 100

8 200

88 500

56 800

8%

Norway

- 81 600

- 8 300

- 89 900

92 700

31 500

0

1 500

125 700

35 800

4%

Poland1

- 31 100

1 000

- 30 100

31 000

67 900

0

8 800

107 700

77 600

10%

Portugal

- 33 800

9 900

- 23 900

108 400

39 000

0

- 4 100

143 300

119 400

11%

Slovak Republic

- 52 800

1 400

- 51 400

34 700

31 700

0

3 400

69 800

18 400

3%

Slovenia

- 35 700

3 600

- 32 100

79 200

93 100

0

13 000

185 300

153 200

12%

Spain

- 35 500

8 600

- 26 900

68 800

20 900

0

2 300

92 000

65 100

7%

m

m

m

m

m

m

m

m

m

m

Switzerland

- 96 200

- 5 000

- 101 200

67 300

29 700

0

- 3 600

93 400

- 7 800

2%

Turkey

- 24 600

1 400

- 23 200

39 300

42 400

0

- 10 500

71 200

48 000

8%

United Kingdom

- 27 900

5 400

- 22 500

71 200

42 300

12 200

1 300

127 000

104 500

21%

United States

- 48 600

- 900

- 49 500

118 200

41 300

0

6 400

165 900

116 400

10%

OECD average

- 45 900

1 200

- 44 700

74 700

37 400

2 700

2 000

116 800

72 100

8%

EU22 average

- 49 800

2 500

- 47 300

83 000

44 200

1 600

3 200

132 000

84 700

9%

Sweden

Note: Values are based on the difference between women who attained a tertiary education compared with those who have attained an upper secondary education.
Values have been rounded up to the nearest hundred. Direct cost to education does not include student loans.
Due to changes in the methodology, values in this edition of Education at a Glance cannot be compared to results from previous editions. See Definitions and
Methodology sections for more information.
1. Year of reference 2014.
2. Year of reference 2012. Students’ earnings are not included in the calculation of foregone earnings.
Source: OECD (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933802437

116 Education at a Glance 2018: OECD Indicators   © OECD 2018

What are the financial incentives to invest in education? – INDICATOR A5

chapter A

Under embargo until 11/09/2018 at 11.00am CEST
Table A5.3a. Private/public costs and benefits for a man attaining tertiary education,

A5

by level of tertiary education (2015)

As compared with a man attaining upper secondary education, in equivalent USD converted using PPPs for GDP,
future costs and benefits are discounted at a rate of 2%
Bachelor’s, master’s and doctoral or equivalent level (ISCED 6 to 8)

OECD

Short-cycle tertiary (ISCED 5)
Private

Public

Private

Public

Total
Total costs benefits

Net
financial
Total
returns Total costs benefits

Net
financial
Total
returns Total costs benefits

Net
financial
Total
returns Total costs benefits

Net
financial
returns

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

Australia

- 38 800

155 600

116 800

- 15 200

84 100

68 900

- 80 400

361 400

281 000

- 39 600

207 300

167 700

Austria

- 53 000

236 800

183 800

- 68 200

207 300

139 100

- 67 700

555 300

487 600

- 88 200

438 800

350 600

Belgium

m

m

m

m

m

m

- 51 000

221 600

170 600

- 53 400

269 400

216 000

Canada

- 46 700

186 700

140 000

- 29 200

86 500

57 300

- 53 300

406 100

352 800

- 49 400

201 900

152 500

Chile

- 19 700

193 800

174 100

- 3 000

9 600

6 600

- 49 000

689 800

640 800

- 15 500

62 700

47 200

m

m

m

m

m

m

- 69 000

334 300

265 300

- 41 500

154 000

112 500
183 500

Czech Republic
Denmark1

- 23 500

127 400

103 900

- 40 100

103 200

63 100

- 54 500

289 200

234 700

- 92 700

276 200

Estonia

a

a

a

a

a

a

- 42 500

193 800

151 300

- 48 000

50 100

2 100

Finland

a

a

a

a

a

a

- 47 300

295 700

248 400

- 57 100

218 100

161 000

France1

- 28 000

186 200

158 200

- 22 100

99 700

77 600

- 64 500

496 800

432 300

- 51 400

289 300

237 900

m

m

m

m

m

m

- 61 900

361 900

300 000

- 91 700

349 600

257 900

Germany
Greece
Hungary

a

a

a

a

a

a

- 27 900

142 600

114 700

- 3 500

65 100

61 600

- 25 200

119 600

94 400

- 15 900

68 900

53 000

- 43 100

387 200

344 100

- 36 600

212 200

175 600

Iceland

m

m

m

m

m

m

m

m

m

m

m

m

Ireland

- 28 600

240 900

212 300

- 19 500

187 500

168 000

- 50 500

547 000

496 500

- 34 600

514 200

479 600

Israel

- 8 800

134 500

125 700

- 6 200

37 100

30 900

- 31 000

458 600

427 600

- 32 100

261 600

229 500

Italy1

m

m

m

m

m

m

- 43 900

229 000

185 100

- 26 100

209 100

183 000

Japan

m

m

m

m

m

m

m

m

m

m

m

m

Korea

- 16 200

196 600

180 400

- 7 800

34 600

26 800

- 30 700

310 100

279 400

- 26 000

71 800

45 800

Latvia

m

m

m

m

m

m

- 34 500

125 500

91 000

- 36 600

64 100

27 500

Luxembourg1

m

m

m

m

m

m

m

m

m

m

m

m

Mexico

m

m

m

m

m

m

m

m

m

m

m

m

Netherlands

m

m

m

m

m

m

m

m

m

m

m

m

New Zealand

m

m

m

m

m

m

- 65 500

338 600

273 100

- 40 700

145 600

104 900

Norway

- 39 300

126 900

87 600

- 40 400

91 700

51 300

- 71 600

348 600

277 000

- 103 500

243 600

140 100

Poland1

m

m

m

m

m

m

- 48 900

402 100

353 200

- 36 400

155 100

118 700

Portugal

m

m

m

m

m

m

- 54 500

268 400

213 900

- 28 700

213 900

185 200

Slovak Republic

m

m

m

m

m

m

- 44 600

284 300

239 700

- 55 400

116 900

61 500

Slovenia

m

m

m

m

m

m

m

m

m

m

m

m

Spain

m

m

m

m

m

m

m

m

m

m

m

m

Sweden

m

m

m

m

m

m

m

m

m

m

m

m

Switzerland

m

m

m

m

m

m

- 79 000

485 700

406 700

- 100 500

159 400

58 900

Turkey

m

m

m

m

m

m

m

m

m

m

m

m

United Kingdom

- 41 600

144 300

102 700

m

m

m

- 84 000

361 400

277 400

- 29 000

183 900

154 900

United States

- 39 800

158 500

118 700

- 30 100

82 800

52 700

- 88 500

673 900

585 400

- 67 000

412 100

345 100

OECD average

m

m

m

m

m

m

- 55 400

368 000

312 600

- 49 400

213 300

163 900

EU22 average

m

m

m

m

m

m

- 52 400

323 300

270 900

- 47 700

222 400

174 700

Note: Values are based on the difference between men who attained a specific level of tertiary education compared with those who have attained an upper secondary
education. Values have been rounded up to the nearest hundred. Direct cost to education does not include student loans.
Due to changes in the methodology, values in this edition of Education at a Glance cannot be compared to results from previous editions. See Definitions and
Methodology sections for more information.
1. Year of reference 2014.
Source: OECD (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933802456

Education at a Glance 2018: OECD Indicators   © OECD 2018

117

chapter A The Output of Educational Institutions and the Impact of Learning
Under embargo until 11/09/2018 at 11.00am CEST
Table A5.3b. Private/public costs and benefits for a woman attaining tertiary education,

A5

by level of tertiary education (2015)

As compared with a woman attaining upper secondary education, in equivalent USD converted using PPPs for GDP,
future costs and benefits are discounted at a rate of 2%
Bachelor’s, master’s and doctoral or equivalent level (ISCED 6 to 8)

Short-cycle tertiary (ISCED 5)
Public

Private

OECD

Total
costs

Total
benefits

Net
financial
returns

Total
costs

Total
benefits

Private
Net
financial
returns

Total
costs

Total
benefits

Public
Net
financial
returns

Total
costs

Total
benefits

Net
financial
returns

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

Australia

- 30 200

148 700

118 500

- 13 000

60 900

47 900

- 59 900

335 500

275 600

- 34 300

160 800

126 500

Austria

- 47 000

161 100

114 100

- 63 200

120 300

57 100

- 60 000

292 000

232 000

- 81 900

231 300

149 400

Belgium

m

m

m

m

m

m

- 41 700

213 200

171 500

- 48 900

241 900

193 000

Canada

- 37 400

166 300

128 900

- 27 600

55 700

28 100

- 37 300

323 800

286 500

- 46 600

126 800

80 200

Chile

- 12 500

126 100

113 600

- 3 000

6 300

3 300

- 33 800

448 700

414 900

- 15 400

31 500

16 100
62 300

Czech Republic
Denmark1
Estonia

m

m

m

m

m

m

- 51 400

190 800

139 400

- 33 600

95 900

- 11 600

123 900

112 300

- 35 500

63 200

27 700

- 26 900

187 600

160 700

- 82 100

146 200

64 100

a

a

a

a

a

a

- 21 500

172 200

150 700

- 44 200

42 300

- 1 900

Finland

a

a

a

a

a

a

- 45 300

255 200

209 900

- 53 700

171 200

117 500

France1

- 22 800

180 900

158 100

- 20 100

110 000

89 900

- 53 600

277 800

224 200

- 47 200

153 700

106 500

Germany

m

m

m

m

m

m

- 50 100

215 800

165 700

- 84 500

172 300

87 800

Greece

a

a

a

a

a

a

- 27 000

126 100

99 100

- 1 200

36 800

35 600

- 20 500

64 200

43 700

- 14 100

38 200

24 100

- 36 000

196 400

160 400

- 33 800

111 800

78 000

Iceland

m

m

m

m

m

m

m

m

m

m

m

m

Ireland

- 21 600

248 900

227 300

- 21 400

85 500

64 100

- 38 200

441 900

403 700

- 37 900

243 800

205 900

Israel

- 4 400

93 400

89 000

- 5 500

10 100

4 600

- 20 300

320 600

300 300

- 30 300

102 800

72 500

Italy1

m

m

m

m

m

m

- 34 800

189 500

154 700

- 26 000

114 400

88 400

Hungary

Japan

m

m

m

m

m

m

m

m

m

m

m

m

Korea

- 18 800

119 300

100 500

- 8 000

10 700

2 700

- 35 200

210 800

175 600

- 26 400

28 900

2 500

Latvia

m

m

m

m

m

m

- 24 100

109 200

85 100

- 31 400

46 500

15 100

Luxembourg1

m

m

m

m

m

m

m

m

m

m

m

m

Mexico

m

m

m

m

m

m

m

m

m

m

m

m

Netherlands

m

m

m

m

m

m

m

m

m

m

m

m

New Zealand

m

m

m

m

m

m

- 59 400

281 100

221 700

- 37 800

94 500

56 700

Norway

- 25 400

128 200

102 800

- 34 500

50 100

15 600

- 45 100

307 000

261 900

- 92 400

152 300

59 900

Poland1

m

m

m

m

m

m

- 32 300

278 800

246 500

- 30 000

109 700

79 700

Portugal

m

m

m

m

m

m

- 42 900

221 300

178 400

- 23 900

151 700

127 800

Slovak Republic

m

m

m

m

m

m

- 28 800

166 400

137 600

- 52 700

70 800

18 100

Slovenia

m

m

m

m

m

m

m

m

m

m

m

m

Spain

m

m

m

m

m

m

m

m

m

m

m

m

Sweden

m

m

m

m

m

m

m

m

m

m

m

m

Switzerland

m

m

m

m

m

m

- 78 000

385 000

307 000

- 102 600

94 400

- 8 200

Turkey

m

m

m

m

m

m

m

m

m

m

m

m

United Kingdom

- 36 500

93 000

56 500

m

m

m

- 76 500

288 900

212 400

- 25 000

148 300

123 300

United States

- 30 400

150 000

119 600

- 27 800

57 000

29 200

- 67 700

436 100

368 400

- 62 000

204 200

142 200

OECD average

m

m

m

m

m

m

- 43 400

264 300

220 900

- 45 600

126 300

80 700

EU22 average

m

m

m

m

m

m

- 40 700

224 900

184 200

- 43 400

134 600

91 200

Note: Values are based on the difference between women who attained a specific level of tertiary education compared with those who have attained an upper
secondary education. Values have been rounded up to the nearest hundred. Direct cost to education does not include student loans.
Due to changes in the methodology, values in this edition of Education at a Glance cannot be compared to results from previous editions. See Definitions and
Methodology sections for more information.
1. Year of reference 2014.
Source: OECD (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933802475

118 Education at a Glance 2018: OECD Indicators   © OECD 2018

Under embargo until 11/09/2018 at 11.00am CEST

Under embargo until 11/09/2018 at 11.00am CEST

INDICATOR A6

HOW ARE SOCIAL OUTCOMES RELATED TO EDUCATION?
• Among 15-year-old students, environmental awareness increases significantly and systematically
with higher levels of science proficiency.

• In most OECD countries, there is a positive, but not always statistically significant, correlation
between higher educational attainment and environmental acknowledgement, attitude and action.

• Seven of the 17 United Nations Sustainable Development Goals (SDGs) are directly linked to the
environment and environmental protection, but in some schools this topic is not included in the
curriculum for eighth-grade students (13.5 years old on average).

Figure A6.1. Environmental awareness, acknowledgement, attitude and action,
by science proficiency level or educational attainment (2014, 2015 or 2016)
Average for 15-year-old students and for 25-64 year-olds
Science proficiency level
among 15 year-old students

Educational attainment among 25-64 year-olds

Level 5 or above
Level 2 to below Level 5
Below Level 2
%

100
90
80
70
60
50
40
30

Tertiary
Upper secondary or post-secondary non-tertiary
Below upper secondary

Awareness

Acknowledgement

Attitude

Action

Aware or well aware
of increase of greenhouse gases
in the atmosphere

Agree that environmental
issues have an impact
on their daily life

Believe in personal
responsibility of looking
after the environment

Report taking
personal actions
to reduce energy use

%

100
90
80
70
60
50
40
30

Note: Data on awareness are from PISA (2015), data on acknowledgement are from Eurobarometer (2014) and data on attitude and
action are from the European Social Survey (2016).						
Items are ordered by the cognitive and behavioural processes that govern the complex dynamics in an individual’s interactions with the
environment.						
Source: OECD (2018), Tables A6.1, A6.2, A6.3 and A6.4. See Source section for more information and Annex 3 for notes (http://dx.doi.
org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933802703

Context
Environmental considerations are present in our everyday well-being, from adverse weather
events to the loss of biodiversity and the quality of the air we breathe and the water we consume.
The environment and environmental protection are fast emerging as the centrepiece of human
development and a defining moment for humanity (UN, 2013[1]; World Economic Forum, 2018[2]).
Over the past 150 years, the world has experienced unprecedented industrial and technological
advances in parallel with phenomenal population growth. Along this unprecedented developmental
path, the world’s ecosystem has been put under ever-increasing pressure to absorb ecological damage
resulting from extensive industrialisation and increased demands on its natural resources (Dimick,
2014[3]; WWF, 2016[4]). The prevailing scientific views put the ecosystem at a delicate crossroads in its
ability to sustain a healthy and balanced habitation for all those living on earth (Ripple et al., 2017[5];
UNEP, 2016[6]; Waters et al., 2016[7]).
Amid mounting global challenges, there have been many examples over the last few decades of
positive developments on a local or a national scale. More importantly, in recent years, we have
seen the convergence of global forces calling for concerted policies and actions to halt and reverse
environmental damage. These developments underline the fact that global efforts are key to ensuring
environmental sustainability (Goosen, 2012[8]). The latest effort culminated in the United Nations
Climate Change Conference in Bonn, Germany in November 2017. Of the 17 SDGs, 7 either explicitly
deal with or are embedded in an environmental context (Box A6.2).

120 Education at a Glance 2018: OECD Indicators   © OECD 2018

Under embargo until 11/09/2018 at 11.00am CEST
Education plays a fundamental role in achieving the SDGs. Education for Sustainable Development
(ESD) is explicitly recognised as a target for the goal on inclusive and equitable education for all.
Education empowers individuals to make changes in their own behaviour. It is through the
transformation of individuals’ own behaviour that they collectively contribute to sustainable
development, by promoting the necessary societal, economic and political changes.

INDICATOR A6

Reporting the relationship between education and the environment in Education at a Glance 2018 is
the first in a four-year reporting cycle to implement the new thematic framework for the indicator on
education and social outcomes, as described in Education at a Glance 2017, Box A8.1 (OECD, 2017[9]).
Over the next three years, the indicator on education and social outcomes will focus on work-life balance
and social connections (in 2019), civic engagement, governance and personal safety (in 2020), and
health status and subjective well-being (in 2021). That will complete the first full cycle of monitoring
the well-being of societies in relation to education.
Other findings

• When adults are asked if they take personal action to reduce energy use, a large number of countries
show statistically significant differences between levels of educational attainment. In contrast,
when adults are asked if they agree that environmental issues have an impact on their daily life
or whether they believe in personal responsibility for looking after the environment, only a few
countries show statistically significant differences.

• Less than 30% of adults report signing a petition for environmental reasons or giving money to
an environmental group. But despite this low share, the difference by educational attainment level
is more significant than for other types of actions, such as reduction of energy use, which around
45% of adults report doing, regardless of their educational attainment.
Note
This indicator presents data drawn from a variety of sources. The Programme for International
Student Assessment (PISA) 2015 and the European Social Survey (ESS) (Round 8 in 2016) are the
principal data sources. It also includes data from the International Civics and Citizenship Education
Study (ICCS) of eighth-grade students in 2016, as well as from three international population-based
surveys used as supplementary sources: Eurobarometer (special modules 416 and 417 in 2014), the
International Social Survey Programme (ISSP) (Environment III in 2010) and the World Values Survey
(WVS) (Wave 6 in 2010-14).
For each international population-based survey, the percentages of adults for each educational
attainment level were compared at a country level with their respective percentages in Indicator A1.
In cases where data for a country were found to have major problems with ISCED compatibility that
could not be satisfactorily resolved, the data were excluded from the analysis. More information on
data assessment and different questions used in the surveys is included in the Methodology section at
the end of this indicator.
As the questions asked in these surveys differ in some aspects, the results are not directly compared
in the analysis. However, differences by level of educational attainment within countries and patterns
across countries can still provide good insights into the links between education and environmental
social outcomes.

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Under embargo until 11/09/2018 at 11.00am CEST

A6

Analysis
The analysis presented in this indicator uses the following 4As framework, which describes the cognitive and
behavioural processes that govern the dynamics of an individual’s interactions with the environment. The processes
follow incremental steps of intensity to construct a pathway towards enhanced engagement with environmental
issues:
1. Awareness of environmental issues describes an individual’s level of knowledge or perception of a situation, the
circumstances surrounding the situation and future developments. This is largely a passive process, requiring
no higher-level cognitive interaction beyond simple fact recognition.
2. Acknowledgement of environmental issues reflects what the individual and, by inference, the society accepts
as the norm. Acknowledgement is one step beyond simply accepting or receiving, to explicitly admit knowledge
of the issue. It implies undertaking cognitive fact processing.
3. Attitude towards environmental issues refers to a set of emotions and beliefs that is moderated by the
individual’s value system. Implicitly implied in attitude are the complex value judgements the individual has
made, which constitute a higher-level cognitive process.
4. Action in response to environmental issues depicts the outward expression of the individual’s attitudes, by way
of taking a certain course of action. Action is clearly in the behavioural domain, but inaction on the part of an
individual can be equally revealing.
Figure A6.1 pools data for countries from the main data sources to provide a high-level and schematic overview
of the results across the 4As presented above. There is a marked and, in most cases, statistically significant
improvement in social environmental outcomes among those with higher educational attainment. Overall levels
across the 4As are high, although data points should not be compared across the 4As, as they were drawn from
different sources and for different reference population groups. Among the 4As, awareness has the widest spread
across the groups, and attitude has the narrowest spread. This suggests that students’ proficiency in science has
a large influence in raising awareness, while educational attainment does not seem to play a large role in shaping
attitudinal beliefs.
Awareness of environmental issues
Data from PISA 2015 show a generally high level of self-reported awareness of a range of environmental issues
among 15-year-old students. Across OECD countries, environmental issues pertaining to the use and preservation
of natural resources (such as extinction of plants and animals, the consequences of deforestation and other land
use, and water shortage) attract high levels of awareness. About seven out of ten students or more reported having
at least some knowledge of these issues and being able to explain them in general terms. In comparison, there
was a relatively lower level of awareness of environmental issues related to technology-induced products (such as
the increase of greenhouse gases in the atmosphere, nuclear waste and the use of genetically modified organisms)
(Table A6.1).
When looking at students’ self-reported awareness according to their PISA science proficiency level, there is a
sharp contrast between those with a high proficiency level and those with a low proficiency level. The percentage of
students reporting awareness of environmental issues increases significantly with an increased science proficiency
level, and that pattern is consistent across all seven environmental issues (Figure A6.2).
The awareness and science proficiency gradient is particularly steep for Japan, where students also tend to
report lower overall levels of awareness across most environmental issues. Students’ self-reported awareness of
environmental issues relating to the use and preservation of natural resources shows a large difference by proficiency
level in Belgium and France. In Korea and Luxembourg, self-reported awareness relating to technology-induced
products shows a steep gradient by science proficiency level (Table A6.1).
Figure A6.2 also shows that, across OECD countries, the increase of greenhouse gases in the atmosphere is the issue
that most separates students at different levels of PISA science proficiency. On average, students with proficiency
Level 5 or above are more than two-and-a-half times more likely to report being aware of greenhouse gases than
students with proficiency Level 2 or below. The same observation holds true in the majority of countries (Table A6.1).

122 Education at a Glance 2018: OECD Indicators   © OECD 2018

How are social outcomes related to education? – INDICATOR A6

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Figure A6.2. Percentage of 15-year-old students who report being aware
or well aware of environmental issues, by science proficiency level (2015)

A6

Programme for International Student Assessment (PISA), OECD average
Level 5 or above
Level 2 to below Level 5
Below Level 2

%

100
90
80
70
60
50
40
30
20
10
0

Air pollution

Increase of
greenhouse gases
in the atmosphere

Consequences
of deforestation
for other land use

Extinction
of plants
and animals

Water shortage

Nuclear waste

Use of genetically
modified organisms

Note: “Aware or well aware” is measured by the categories “I know something about this and could explain the general issue” and “I am familiar with
this and I would be able to explain this well”.					
Environmental issues are ranked in descending order of the percentage of 15-year-old students with a science proficiency of Level 5 or above who report being
“aware or well aware” of the issue.					
Source: OECD (2018), Table A6.1. See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933802722

Box A6.1. Environmental education at schools
The field of environmental education has a well-established history of over forty years (Stevenson et al.,
2013[10]). Over these four decades, environmental education has emerged from being an isolated consideration
into a discussion integrated with social issues of health, education, poverty and wider social progress. In recent
years, this field has received considerably more attention, as topics such as conservation, biodiversity and
sustainability gained prominence.
On average across OECD countries, between half and three-quarters of 15-year-old students reported that
their school was the main source of information on a range of environmental issues. Environmental education
at school helps young people to acquire the knowledge, skills and values necessary to support the transition to
a more sustainable world. “Do today’s 15-year-olds feel environmentally responsible?”, PISA in Focus, No. 21
concludes that schools appear to play a central role as a source of knowledge on environmental issues (OECD,
2012[11]).
Education and environmental education were at the core of United Nations Decade of Education for Sustainable
Development (2005-14), with its mission to integrate the principles, values and practices of sustainable
development into all aspects of education and learning. According to the 2015 monitoring report by the
United Nations Economic Commission for Europe, in over 90% of the member states that submitted a national
implementation report, ESD is integrated in their national education policy documents (Creech and Buckler,
2015[12]). The vast majority of these countries have moved beyond a policy framework to curricula and/or
standards. National efforts are commonly focused on addressing: 1) key sustainable development themes in
curricula; 2) broad competencies and learning outcomes; and 3) pedagogical approaches.
Countries reported diverse approaches to addressing ESD in the curriculum, from embedding ESD in education
frameworks and requirements for knowledge, skills, attitudes and competences to trialling experimental
curricula with sustainability-focused modules and supporting extracurricular activities, such as field studies
and competitions (Creech and Buckler, 2015[12]). Many countries reported increasing availability of tools and
resources, but some countries underlined that the level of demand for these materials is unknown.

…
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The 2016 ICCS, which gathered information from eighth-grade students (13.5 years old on average), their
teachers and their school, found that the topic of the environment and environmental sustainability is
commonly included in the Grade 8 curriculum. Among the 15 OECD member and partner countries that
participated and responded to the question on curriculum topics, 11 countries indicated that this topic is part
of the curriculum at this level of education (ICCS/IEA,2016[13]).
There is also evidence of widespread emphasis on environmental sustainability in teaching and school practice
in some countries. Figure A6.a shows the proportion of schools where the principal reported that all or most
eighth-grade students had the opportunity to take part in environmental sustainability activities in the
current school year. As the unit of analysis is the individual school, the error range is relatively large.
In Finland, Italy, Lithuania, Mexico, the Russian Federation and Slovenia, 70% of schools or more reported
that all or most of their eight-grade students took part in environmental sustainability activities in the 2016
school year. Chile, Denmark, Korea, the Netherlands and Norway reported a significantly lower proportion of
schools where students participated in environmental sustainability activities (Figure A6.a).

Figure A6.a. Percentage of schools where all or most of the eighth-grade students take part
in internal or external school activities related to environmental sustainability (2016)
International Civics and Citizenship Education Study

Netherlands

Chile

Norway

Denmark

Korea

Colombia

Sweden

Estonia

Flemish Comm. (Belgium)

Latvia

Lithuania

Italy

Russian Federation

Finland

Mexico

%

100
90
80
70
60
50
40
30
20
10
0

Slovenia

A6

Note: Eighth-grade students are 13.5 years old on average.
Source: International Civics and Citizenship Education Study (2016). See Source section for more information and Annex 3 for notes
(http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933802760

Acknowledgement of environmental issues
Overall, there is a widespread consensus on the impact of environmental issues. Among countries participating in
the Eurobarometer survey, which monitors public opinion in EU Member States, about 70% to 90% of adults agree
that environmental issues are affecting their everyday lives. Among countries participating in the ISSP, a crossnational collaboration programme conducting annual surveys on diverse topics relevant to social sciences, data
show a lower share of adults who agree that environmental issues have an impact on their daily life, but on average
still more than 45% do so (Table A6.2). The difference between the two sources is partly explained by the way the
question is asked (see Methodology section).
The level of acknowledgement of environmental issues differs substantially by educational attainment. On average
across countries, the higher the educational attainment, the higher the level of acknowledgement of environmental
issues. However, at country level, there are relatively few cases of statistically significant comparisons. This is
because of the general nature of these surveys and the inherent imprecision in the statistical estimates derived
from small sub-samples (Table A6.2).

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The education gradient on the acknowledgement of environmental impacts is particularly steep in Belgium, Latvia,
Turkey and the United Kingdom. In these countries, the proportion of adults who agree that environmental issues
are having an impact on their everyday lives is significantly higher among with those with tertiary education than
among those without tertiary education (Table A6.2).
Attitude towards environmental issues
On average, over two-thirds of adults identify themselves as having a positive attitude towards protecting the
environment. Compared to the levels of awareness or acknowledgement, the level of positive attitude towards
environmental protection seems more evenly spread across different educational attainment levels. This suggests
that other dynamics, such as societal norms and social desirability, are involved in formulating attitudes. Nonetheless,
an educational gradient is still clearly discernible. On average across countries, the level of positive attitude towards
environmental protection increases with higher educational attainment (Table A6.3).
Adults with tertiary education reported a significantly higher level of positive attitude towards environmental
protection than adults with less than tertiary education. This is particularly true for the Czech Republic and
the United Kingdom. In the case of the Czech Republic, there is also a significant difference in the level of positive
attitude between adults with below upper secondary education and adults with upper secondary or post-secondary
non-tertiary education (Table A6.3).
In contrast, Israel and Switzerland seem to have an inverse relationship between attitude towards environmental
protection and educational attainment. However, the differences between educational attainment categories are
not statistically significant (Table A6.3).
Taking actions on environmental issues
There is a wide spectrum of actions one can take for an environmental cause. General population-based social
surveys tend to focus on either behavioural patterns and lifestyle changes in personal consumption or explicit
participatory steps in support of certain environmental causes.

Figure A6.3. Percentage of adults who report taking personal action to reduce energy use,
by educational attainment (2016 or 2010)
European Social Survey and International Social Survey Programme, 25-64 year-olds

Latvia

Slovak Republic

Average

Turkey

Portugal

Russian Federation1, 2

Israel

Iceland

Czech Republic

Norway1

Poland1

Ireland

Estonia

Austria1, 2

Sweden1

Average

Switzerland

Belgium

United Kingdom

Slovenia

Finland

Netherlands

France

United States2

International Social Survey
Programme (2010)

European Social Survey (2016)

Germany1

100
90
80
70
60
50
40
30
20
10
0

Below upper secondary

Chile2

%

Upper secondary or post-secondary non-tertiary

Spain2

Tertiary

Note: As the questions asked in the different surveys vary, survey results are not directly compared in the analysis (see Definitions section for more
information). Blue zone denotes statistically significant differences between some or all educational attainment levels.
1. Some discrepancies remain in the survey sample distribution by highest educational attainment compared to data published in Indicator A1.
2. Data on survey respondents’ highest educational attainment have been re-coded to improve compatibility with ISCED 2011. See Annex 3 for
country-specific notes.
Countries are ranked in descending order of the percentage of tertiary-educated 25-64 year-olds who report taking personal action to reduce energy use.
Source: OECD (2018), Table A6.4. See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933802741

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A6

Among countries participating in the ESS (an academically driven cross-national survey conducted across Europe),
on average more than 70% of adults reported that they always or often take action to reduce energy use for
environmental reasons (Table A6.4). The overall level of positive action is slightly above the level of positive attitude
noted in the previous section. However, as will be shown later, attitude is not always matched by actions.
As with other cognitive domains, behavioural patterns also demonstrate a positive education gradient, in which
the proportion of adults taking action increases with increased educational attainment. But unlike other cognitive
domains, on average across countries, the incremental difference is more marked between adults with below upper
secondary education and adults with upper secondary or post-secondary non-tertiary education (Table A6.4).

Box A6.2. United Nations SDGs and individual actions
Of the 17 SDGs, 7 are directly linked to the environment and environmental protection (Goals 6, 7, 11, 12,
13, 14 and 15) (UN, 2015[15]). These goals are designed to be world-changing, and the UN team prepared the
“Lazy Person’s Guide to Saving the World”, which offers examples of things that individuals can do to make an
impact (UN, 2018[16]).
Questions about such grassroots actions are often asked in social surveys on the environment. For example, in
the ISSP, adults were asked how often they take six specific actions in their consumption and lifestyle choices,
including sorting waste and recycling, buying fruit and vegetables grown without pesticides or chemicals,
reducing energy or fuel use at home, or restricting use of a car for environmental reasons.
Figure A6.b presents pooled data for the OECD and partner countries participating in the survey. Detailed
analysis of data from the action “reducing energy use” is presented in Figure A6.3. With the exception of the
action “save or reuse water for environmental reasons”, all other actions exhibit a marked positive education
gradient in which the proportion of adults who always or often follow through on the environmental action
increases with higher levels of education (Figure A6.b).
Figure A6.b. Percentage of adults who report taking personal action

for environmental reasons, by educational attainment (2010)
International Social Survey Programme, average, 25-64 year-olds
Tertiary
Upper secondary or post-secondary non-tertiary
Below upper secondary

%

100
90
80
70
60
50
40
30
20
10
0

Sort
waste for
recycling

Reduce
energy
use

Buy fruit
and
vegetables
grown
without
pesticides
or
chemicals

Avoid
buying
certain
products

Save
or re-use
water

Sign
a petition

Cut back
on
driving

Give
money to
an
environmental
group

Member
of group
aiming to
preserve
or protect
environment

Take
part in
a protest
or
demonstration

Note: The average includes data for Australia, Austria, Belgium, Canada, Chile, Czech Republic, Denmark, Finland, France, Germany, Israel,
Japan, Korea, Latvia, Mexico, the Netherlands, New Zealand, Norway, Portugal, the Slovak Republic, Slovenia, Spain, Sweden, Switzerland,
Turkey, the United Kingdom and the United States.
Items are ranked in descending order of the percentage of tertiary-educated adults who report taking personal action for each item.
Source: International Social Survey Programme (2010). See Source section for more information and Annex 3 for note (http://dx.doi.
org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933802779

…

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As mentioned earlier, a different set of actions, chosen by some individuals, involves a more active form of
public and civic participation. The ISSP also asked adults if they are a member of a group whose main aim is
to preserve or protect the environment and whether, in the last five years, they have signed a petition about
an environmental issue, given money to an environmental group or taken part in a protest or demonstration
about an environmental issue. Interestingly, while the percentage of positive responses to the civic and
participatory actions is generally much lower compared to actions on consumption and lifestyle choices,
the positive education gradient is much more marked, particularly between those with tertiary education
and those with less than tertiary education. This last finding suggests that the influence of education seems
stronger on civic actions than on lifestyle and consumption (Figure A6.b).

Germany has the steepest education gradients, with a difference of about 20 percentage points between adults
with tertiary education and adults with below upper secondary education who reported often or always reducing
energy consumption. Austria, Finland, France, Ireland, Israel, Poland and the United Kingdom all have statistically
significant differences between some or all levels of educational attainment (Figure A6.3).
Further analysis of the data shows that, out of every four adults who believe looking after the environment is important,
only three always or often reduce energy use for environmental reasons. Moreover, an educational gradient is equally
observable among those who take action and those who do not. In other words, increased educational attainment is
associated with greater efficacy of channelling positive attitude to positive actions (ESS, 2017[14]).

Definitions
Acknowledgement of environmental issues is defined differently by different surveys. For the Eurobarometer
survey, it refers to adults who totally agree or tend to agree that environmental issues have a direct effect on daily
life. For the ISSP, it refers to adults who agree or agree strongly that environmental problems have a direct effect on
their everyday lives.
Action in response to environmental issues is also defined differently by different surveys. For the ESS, it refers to
adults who often, very often or always do things to reduce energy use, such as switching off appliances that are not
being used, walking for short journeys or only using heating or air conditioning when really needed. For the ISSP,
it refers to adults who often or always reduce energy or fuel use at home for environmental reasons.
Adults refer to 25-64 year-olds.
Attitude towards environmental issues refers to adults who answer that a person with the following characteristics
is “like me” or “very much like me”: In the ESS, the characteristics are: “He/she strongly believes that people should
care for nature. Looking after the environment is important to him/her.” In the WVS, the characteristics are:
“Looking after the environment is important to this person; to care for nature and save life resources.”
Educational attainment refers to the highest level of education achieved by a person.
Education gradient refers to a change in the value of a variable when considering different levels of educational
attainment. A steep education gradient implies a large change in the value of a selected variable at different levels
of educational attainment.
Environmental awareness on a specific environmental issue refers to 15-year-old students who answered that they
know something about the issue and could explain the general issue or that they are familiar with the issue and
would be able to explain it well.
Science proficiency levels: To help users interpret what student scores mean in substantive terms, PISA scales are
divided into proficiency levels. For PISA 2015, the range of difficulty of science tasks is represented by seven levels of
science proficiency (ranging from the highest, Level 6, to Level 1b). Below Level 2 represents a score below 410 points;
Level 2 to below Level 5 represents a score between 410 and 632 inclusively; and Level 5 or above represents a score
above 632. For more information on science proficiency levels see PISA 2015 Results (Volume I): Excellence and Equity
in Education (OECD, 2016[17]).
Education at a Glance 2018: OECD Indicators   © OECD 2018

127

A6

chapter A The Output of Educational Institutions and the Impact of Learning
Under embargo until 11/09/2018 at 11.00am CEST

A6

Methodology
For each survey, the percentages of adults for each educational attainment level were compared at a country level
with their respective percentages in Indicator A1. Following consultations with countries, data on educational
attainment were recoded to improve compatibility with the levels in Indicator A1 for the following surveys and
countries:

• ESS: Austria and the Russian Federation
• Eurobarometer: Austria, Belgium, Finland and Spain
• ISSP: Chile, Israel, Spain, Switzerland and the United States
• WVS: Chile and Turkey
In the ESS, some discrepancies still exist in the survey sample distribution for Austria, Poland, the Russian Federation
and Sweden, even after the recoding of educational attainment for Austria and the Russian Federation. Similar
discrepancies also exist for Greece in the Eurobarometer (see Annex 3, http://dx.doi.org/10.1787/eag-2018-36-en).
Lithuania was not an OECD member at the time of preparation of this publication. Accordingly, Lithuania does not
appear in the list of OECD members and is not included in the zone aggregates.

Source
Data from PISA 2015 provided evidence on environmental awareness among 15-year-old students.
Data from the 2016 ICCS provided evidence on eighth-grade students who had the opportunity to take part in
activities related to environmental sustainability.
Data from the 2016 ESS (Round 8) provided evidence on adults’ attitudes and actions in response to environmental
issues.
Data from the 2014 Eurobarometer (special modules 416 and 417) provided evidence on adults’ acknowledgement
of environmental issues.
Data from the 2010 ISSP (Environment III) provided evidence on adults’ acknowledgement and action in response
to environmental issues.
Data from the 2010-2014 WVS (Wave 6) provided evidences on adults’ attitudes towards environmental issues.

Note regarding data from Israel
The statistical data for Israel are supplied by and are under the responsibility of the relevant Israeli authorities. The use
of such data by the OECD is without prejudice to the status of the Golan Heights, East Jerusalem and Israeli settlements
in the West Bank under the terms of international law.

References
Creech, H. and C. Buckler (2015), Learning from each other: achievements, challenges and ways forward, Third evaluation [12]
report of the UNECE Strategy for Education for Sustainable Development, United Nations Economic Commission for Europe
Steering, Geneva, www.unece.org/fileadmin/DAM/env/esd/11thMeetSC/Documents/1521609E.pdf.
Dimick, D. (2014), As World’s Population Booms, Will Its Resources Be Enough for Us?, https://news.nationalgeographic.com/ [3]
news/2014/09/140920-population-11billion-demographics-anthropocene/ (accessed on 27 February 2018).
ESS (2017), Data and Documentation by Round, www.europeansocialsurvey.org/data/download.html?r=8 (accessed on [14]
28 February 2018).
Goosen, M. (2012), “Environmental management and sustainable development”, Procedia Engineering, Vol. 33, pp. 6-13, [8]
http://dx.doi.org/10.1016/J.PROENG.2012.01.1171.
ICCS/IEA (2016), International Civic and Citizenship Education Study 2016, http://iccs.iea.nl/cycles/2016.html (accessed [13]
on 27 February 2018).
OECD (2017), Education at a Glance 2017: OECD Indicators, OECD Publishing, Paris, http://dx.doi.org/10.1787/eag-2017-en. [9]
OECD (2016), PISA 2015 Results (Volume I): Excellence and Equity in Education, OECD Publishing, Paris, http://dx.doi. [17]
org/10.1787/9789264266490-en.

128 Education at a Glance 2018: OECD Indicators   © OECD 2018

How are social outcomes related to education? – INDICATOR A6

chapter A

Under embargo until 11/09/2018 at 11.00am CEST
OECD (2012), “Do today’s 15-year-olds feel environmentally responsible?”, PISA in Focus, No. 21, OECD Publishing, Paris, [11]
http://dx.doi.org/10.1787/5k918xhzk88t-en.
Ripple, W. et al. (2017), “World scientists’ warning to humanity: A second notice”, BioScience, Vol. 67/12, pp. 1026-1028, [5]
http://dx.doi.org/10.1093/biosci/bix125.
Stevenson, R. et al. (2013), International Handbook of Research on Environmental Education, Routledge, London, www. [10]
routledge.com/International-Handbook-of-Research-on-Environmental-Education/Stevenson-Brody-Dillon-Wals/p/
book/9780415892391 (accessed on 27 February 2018).
UN (2018), Lazy Person’s Guide to Saving the World, www.un.org/sustainabledevelopment/takeaction/ (accessed on [16]
27 February 2018).
UN (2015), Transforming our world: The 2030 Agenda for Sustainable Development, https://sustainabledevelopment.un.org/ [15]
post2015/transformingourworld (accessed on 15 May 2018).
UN (2013), Open Working Group proposal for Sustainable Development Goals, https://sustainabledevelopment.un.org/ [1]
focussdgs.html (accessed on 27 February 2018).
UNEP (2016), Rate of Environmental Damage Increasing Across the Planet but Still Time to Reverse Worst Impacts, www. [6]
un.org/sustainabledevelopment/blog/2016/05/rate-of-environmental-damage-increasing-across-planet-but-still-timeto-reverse-worst-impacts/ (accessed on 27 February 2018).
Waters, C. et al. (2016), “The Anthropocene is functionally and stratigraphically distinct from the Holocene.”, Science, [7]
Vol. 351/6269, http://dx.doi.org/10.1126/science.aad2622.
World Economic Forum (2018), The Global Risks Report 2018 13th Edition, World Economic Forum, Geneva, www3. [2]
weforum.org/docs/WEF_GRR18_Report.pdf (accessed on 27 February 2018).
WWF (2016), Living Planet Report 2016: Risk and Resilience in a New Era, wwf.panda.org/about_our_earth/all_publications/ [4]
lpr_2016/ (accessed on 27 February 2018).

Indicator A6 Tables
1 2 https://doi.org/10.1787/888933802608

Table A6.1 Percentage of 15-year-old students who report being aware or well aware of environmental issues,
by science proficiency level (2015)
Table A6.2 Percentage of adults who agree that environmental issues have an impact on their daily life,
by educational attainment (2014 or 2010)
Table A6.3 Percentage of adults who believe in personal responsibility for looking after the environment,
by educational attainment (2016 or 2010-2014)
Table A6.4 Percentage of adults who report taking personal action to reduce energy use,
by educational attainment (2016 or 2010)
Cut-off date for the data: 18 July 2018. Any updates on data can be found on line at http://dx.doi.org/10.1787/eag-data-en. More breakdowns can
also be found at http://stats.oecd.org/, Education at a Glance Database.

Education at a Glance 2018: OECD Indicators   © OECD 2018

129

A6

chapter A The Output of Educational Institutions and the Impact of Learning
Under embargo until 11/09/2018 at 11.00am CEST
Table A6.1. Percentage of 15-year-old students who report being aware or well aware

A6

of environmental issues, by science proficiency level (2015)
Programme for International Student Assessment (PISA)

Increase of greenhouse gases
in the atmosphere

Partners

OECD

Science
proficiency:
Science
Level 5
proficiency:
or above
Below Level 2

All science
proficiency
levels

Use of
genetically
modified
organisms

Nuclear
waste

All science
proficiency
levels

All science
proficiency
levels

Consequences
of
deforestation
for other
land use
Air pollution

Extinction
of plants
and animals

Water
shortage

All science
proficiency
levels

All science
proficiency
levels

All science
proficiency
levels

All science
proficiency
levels

%

S.E.

%

S.E.

%

S.E.

%

S.E.

%

S.E.

%

S.E.

%

S.E.

%

S.E.

%

(1)

(2)

(5)

(6)

(7)

(8)

(15)

(16)

(23)

(24)

(31)

(32)

(39)

(40)

(47)

(48)

(55)

S.E.
(56)

Australia
Austria
Belgium
Canada
Chile
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United Kingdom
United States

40
26
26
47
30
20
41
30
35
31
32
42
38
28
44
29
50
19
40
29
28
40
27
29
42
30
59
27
31
43
53
27
40
51
33

(1.2)
(1.9)
(1.3)
(1.7)
(1.4)
(1.6)
(2.3)
(3.1)
(2.8)
(1.9)
(2.8)
(1.9)
(2.1)
(1.9)
(2.4)
(1.7)
(1.9)
(2.4)
(2.1)
(2.3)
(1.7)
(1.3)
(2.0)
(2.3)
(1.9)
(2.6)
(2.2)
(1.5)
(2.2)
(1.8)
(2.0)
(2.4)
(1.3)
(1.8)
(1.8)

95
94
95
97
93
90
98
91
97
96
93
97
93
95
98
82
97
90
96
83
95
c
98
90
98
94
100
94
95
97
99
92
c
98
88

(1.0)
(1.5)
(1.1)
(0.6)
(3.3)
(1.7)
(0.9)
(1.4)
(0.7)
(1.1)
(1.3)
(1.8)
(2.1)
(2.9)
(0.7)
(2.4)
(1.3)
(1.2)
(1.0)
(3.5)
(1.7)
c
(0.8)
(1.8)
(0.8)
(1.9)
(0.2)
(1.8)
(1.5)
(1.2)
(0.5)
(1.7)
c
(0.7)
(2.0)

69
57
62
78
51
50
73
62
74
66
65
67
63
56
79
46
73
59
72
48
55
52
69
60
73
57
86
55
67
72
81
60
55
80
55

(0.6)
(1.0)
(0.7)
(0.7)
(1.1)
(0.9)
(0.9)
(1.0)
(1.0)
(0.8)
(1.1)
(1.2)
(0.8)
(0.9)
(1.0)
(1.0)
(1.0)
(1.2)
(0.9)
(0.9)
(0.6)
(1.1)
(1.0)
(1.0)
(0.9)
(1.1)
(0.7)
(0.9)
(0.6)
(0.9)
(0.9)
(1.2)
(1.3)
(0.7)
(1.2)

45
32
24
59
30
19
36
57
28
61
35
43
23
43
35
46
57
42
47
49
39
35
20
41
36
48
56
24
74
42
43
34
70
55
49

(0.7)
(0.8)
(0.7)
(0.7)
(0.8)
(0.7)
(1.0)
(1.1)
(1.0)
(0.8)
(0.8)
(1.2)
(0.8)
(0.7)
(0.8)
(0.9)
(0.8)
(0.9)
(1.2)
(1.0)
(0.7)
(0.8)
(0.9)
(0.8)
(1.1)
(1.1)
(0.9)
(0.7)
(0.6)
(1.0)
(1.4)
(0.9)
(1.2)
(1.1)
(1.0)

50
58
53
57
53
64
59
61
66
50
65
53
43
50
59
35
52
36
43
64
56
49
59
39
53
60
67
57
55
56
60
58
69
62
53

(0.5)
(0.8)
(0.7)
(0.6)
(0.8)
(0.9)
(1.0)
(0.8)
(0.8)
(0.7)
(1.0)
(0.8)
(0.8)
(0.9)
(0.7)
(0.6)
(0.8)
(0.9)
(1.0)
(0.8)
(0.7)
(0.7)
(0.8)
(0.7)
(0.9)
(0.9)
(0.7)
(0.8)
(0.8)
(0.8)
(1.1)
(0.9)
(0.8)
(1.0)
(1.0)

79
76
73
82
72
77
79
84
72
68
79
59
71
70
84
64
73
59
52
86
70
75
77
69
82
86
85
66
80
70
51
70
75
78
74

(0.5)
(0.7)
(0.7)
(0.7)
(0.8)
(0.7)
(0.7)
(0.6)
(0.8)
(0.7)
(0.9)
(0.8)
(0.8)
(0.8)
(0.7)
(0.9)
(0.8)
(1.0)
(1.0)
(0.6)
(0.6)
(0.8)
(0.9)
(0.8)
(0.7)
(0.6)
(0.6)
(0.7)
(0.6)
(0.9)
(1.0)
(0.8)
(0.9)
(0.6)
(0.8)

81
82
81
88
80
85
82
87
90
79
85
90
87
79
88
82
87
71
87
89
81
85
61
73
81
89
91
82
91
83
76
81
87
83
83

(0.5)
(0.6)
(0.5)
(0.5)
(0.7)
(0.5)
(0.7)
(0.6)
(0.5)
(0.6)
(0.6)
(0.8)
(0.7)
(0.7)
(0.6)
(0.7)
(0.6)
(0.8)
(0.6)
(0.5)
(0.6)
(0.6)
(1.0)
(0.8)
(0.7)
(0.6)
(0.5)
(0.7)
(0.4)
(0.7)
(0.8)
(0.7)
(0.8)
(0.6)
(0.7)

82
76
72
85
81
75
74
86
85
70
79
85
82
73
81
73
74
62
83
84
76
82
76
74
82
83
90
75
83
81
81
74
85
82
81

(0.4)
(0.6)
(0.6)
(0.5)
(0.7)
(0.6)
(0.8)
(0.6)
(0.6)
(0.7)
(0.7)
(0.8)
(0.7)
(0.9)
(0.6)
(0.6)
(0.7)
(0.9)
(0.7)
(0.7)
(0.6)
(0.6)
(0.7)
(0.8)
(0.6)
(0.6)
(0.5)
(0.8)
(0.6)
(0.7)
(0.7)
(0.8)
(0.7)
(0.5)
(0.5)

64
65
59
68
79
73
66
82
71
58
68
83
78
75
76
78
74
45
86
73
65
81
62
54
74
73
88
75
85
70
72
62
82
59
69

(0.5)
(0.8)
(0.7)
(0.6)
(0.8)
(0.7)
(0.8)
(0.6)
(0.8)
(0.8)
(0.8)
(0.8)
(0.8)
(0.7)
(0.7)
(0.5)
(0.7)
(1.0)
(0.6)
(0.7)
(0.6)
(0.8)
(0.8)
(0.9)
(0.7)
(0.8)
(0.5)
(0.7)
(0.4)
(0.8)
(0.8)
(1.1)
(0.7)
(0.8)
(0.8)

OECD average
EU22 average

35
36

(0.3)
(0.5)

94
95

(0.3)
(0.3)

64
66

(0.2)
(0.2)

42
41

(0.2)
(0.2)

55
58

(0.1)
(0.2)

73
75

(0.1)
(0.2)

83
84

(0.1)
(0.1)

79
79

(0.1)
(0.1)

71
72

(0.1)
(0.2)

CABA (Argentina)1
Brazil
B-S-J-G (China)2
Colombia
Costa Rica
India
Indonesia
Lithuania
Russian Federation
Saudi Arabia
South Africa

23
38
36
32
36
m
17
37
34
m
m

(2.9)
(0.9)
(2.0)
(1.2)
(1.2)
m
(1.2)
(1.6)
(2.2)
m
m

88
96
98
95
c
m
c
96
83
m
m

(8.6)
(3.2)
(0.7)
(6.2)
c
m
c
(2.1)
(3.6)
m
m

44
55
73
45
49
m
27
64
57
m
m

(2.8)
(0.9)
(1.2)
(1.0)
(1.0)
m
(1.2)
(1.0)
(1.1)
m
m

25
36
37
40
25
m
19
64
57
m
m

(1.7)
(0.7)
(0.9)
(0.8)
(0.7)
m
(1.0)
(0.9)
(1.2)
m
m

35
49
37
37
39
m
15
57
71
m
m

(1.8)
(0.7)
(0.8)
(0.7)
(0.8)
m
(0.7)
(0.7)
(1.1)
m
m

76
68
88
61
71
m
58
80
89
m
m

(1.9)
(0.8)
(0.6)
(1.0)
(0.8)
m
(1.2)
(0.6)
(0.7)
m
m

83
79
91
m
78
m
67
88
89
m
m

(1.4)
(0.7)
(0.5)
m
(0.8)
m
(1.2)
(0.6)
(0.7)
m
m

75
75
82
71
74
m
64
84
86
m
m

(1.5)
(0.7)
(0.6)
(0.9)
(0.9)
m
(1.1)
(0.7)
(0.8)
m
m

72
72
89
77
74
m
62
80
54
m
m

(1.6)
(0.8)
(0.6)
(0.8)
(0.9)
m
(1.1)
(0.6)
(0.9)
m
m

G20 average

36

(0.5)

93

(0.8)

61

(0.3)

46

(0.2)

50

(0.2)

73

(0.2)

83

(0.2)

78

(0.2)

69

(0.2)

Note: More columns showing data by proficiency level are available for consultation on line (see StatLink below). See Definitions sections for more information.
1. Refers to the adjudicated region of Ciudad Autónoma de Buenos Aires (CABA).
2. Refers to the four PISA-participating China provinces: Beijing, Shanghai, Jiangsu and Guangdong (B-S-J-G).
Source: OECD (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933802627

130 Education at a Glance 2018: OECD Indicators   © OECD 2018

How are social outcomes related to education? – INDICATOR A6

chapter A

Under embargo until 11/09/2018 at 11.00am CEST
Table A6.2. Percentage of adults who agree that environmental issues have an impact on their daily life,

by educational attainment (2014 or 2010)

Eurobarometer and International Social Survey Programme, 25-64 year-olds
Eurobarometer (2014)

Partners

OECD

Below upper secondary

Upper secondary
or post-secondary non-tertiary

Tertiary

Total

%

S.E.

%

S.E.

%

S.E.

%

(1)

(2)

(3)

(4)

(5)

(6)

(7)

S.E.
(8)

Austria1

70

(4.7)

66

(2.7)

73

(2.8)

69

(1.8)

Belgium1

66

(5.6)

67

(2.7)

78

(2.5)

72

(1.8)

Czech Republic

77

(6.2)

78

(1.7)

75

(4.3)

78

(1.5)

Estonia

78

(6.4)

78

(2.2)

81

(2.4)

79

(1.6)

Finland1

79

(4.8)

77

(2.7)

76

(2.3)

77

(1.7)

Greece2

93

(2.1)

95

(1.2)

96

(1.5)

q

q

Hungary

73

(4.1)

80

(1.9)

86

(2.9)

80

(1.5)

Ireland

80

(3.9)

80

(2.2)

85

(2.1)

82

(1.4)

Latvia

58

(6.7)

79

(2.1)

79

(2.7)

77

(1.6)

Luxembourg

75

(5.0)

78

(3.6)

89

(2.7)

82

(2.1)

Poland

81

(3.8)

80

(2.0)

76

(3.5)

79

(1.6)

Slovak Republic

76

(6.1)

85

(1.6)

83

(2.8)

84

(1.3)

Slovenia

86

(4.0)

88

(1.5)

88

(2.3)

88

(1.2)

Spain1

85

(2.2)

89

(2.1)

91

(1.9)

88

(1.2)

United Kingdom

81

(4.4)

78

(2.2)

90

(1.5)

84

(1.3)

Average

77

(1.3)

80

(0.6)

83

(0.7)

80

(0.4)

Lithuania

75

(8.3)

87

(1.8)

90

(1.8)

88

(1.3)

International Social Survey Programme (2010)
Below upper secondary

Upper secondary
or post-secondary non-tertiary

Tertiary

Total

%

S.E.

%

S.E.

%

S.E.

%

(1)

(2)

(3)

(4)

(5)

(6)

(7)

S.E.
(8)

Chile1

55

(3.1)

62

(2.4)

63

(2.9)

60

(1.6)

Israel1

47

(4.7)

52

(3.0)

61

(2.5)

56

(1.8)

Norway

19

(2.9)

16

(1.9)

24

(2.2)

20

(1.3)

Portugal

55

(2.6)

52

(4.1)

61

(4.0)

55

(1.9)

Switzerland1

37

(4.7)

36

(2.3)

42

(3.0)

38

(1.7)

Turkey

44

(1.8)

40

(3.0)

57

(4.4)

45

(1.5)

United States1

54

(4.5)

46

(2.3)

51

(2.5)

49

(1.6)

Average

44

(1.4)

44

(1.1)

51

(1.2)

46

(0.6)

1. Data on survey respondents’ highest educational attainment have been re-coded to improve compatibility with ISCED 2011.
2. Values for “Total” are suppressed because of discrepancies in the survey sample distribution by highest educational attainment compared to data published in Indicator A1.
Source: OECD (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933802646

Education at a Glance 2018: OECD Indicators   © OECD 2018

131

A6

chapter A The Output of Educational Institutions and the Impact of Learning
Under embargo until 11/09/2018 at 11.00am CEST
Table A6.3. Percentage of adults who believe in personal responsibility for looking after

A6

the environment, by educational attainment (2016 or 2010-2014)
European Social Survey and World Values Survey, 25-64 year-olds
European Social Survey (2016)

Partners

OECD

Below upper secondary

Upper secondary
or post-secondary non-tertiary

Tertiary

Total

%

S.E.

%

S.E.

%

S.E.

%

S.E.

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

Austria1, 2

65

(4.0)

66

(1.6)

72

(2.4)

q

q

Belgium

76

(2.9)

74

(2.2)

74

(2.0)

74

(1.3)

Czech Republic

43

(3.9)

55

(1.5)

65

(3.0)

55

(1.3)

Estonia

70

(3.9)

72

(1.7)

76

(2.0)

73

(1.2)

Finland

65

(4.8)

72

(2.1)

75

(1.7)

73

(1.3)

France

63

(3.6)

63

(1.9)

64

(2.2)

63

(1.3)

Germany2

70

(4.5)

72

(1.5)

76

(1.5)

q

q

Iceland

59

(4.9)

59

(3.6)

70

(2.7)

64

(2.0)

Ireland

61

(2.5)

61

(2.0)

68

(1.5)

64

(1.1)

Israel

68

(4.6)

62

(2.0)

59

(1.8)

61

(1.3)

Netherlands

66

(3.1)

66

(2.4)

72

(2.2)

68

(1.4)

Norway2

57

(5.8)

46

(2.7)

57

(2.1)

q

q

Poland2

74

(2.1)

80

(2.1)

77

(2.4)

q

q

Slovenia

87

(3.1)

85

(1.7)

89

(1.9)

86

(1.2)

Sweden2

64

(5.9)

62

(2.3)

65

(2.3)

q

q

Switzerland

84

(3.1)

78

(2.0)

75

(2.2)

78

(1.3)

United Kingdom

56

(2.9)

59

(2.7)

71

(1.9)

64

(1.4)

Average

66

(1.0)

67

(0.5)

71

(0.5)

69

(0.4)

Russian Federation1, 2

65

(5.6)

68

(2.5)

65

(1.3)

q

q

World Values Survey (2010-2014)
Below upper secondary

Upper secondary
or post-secondary non-tertiary

Tertiary

Total

%

S.E.

%

S.E.

%

S.E.

%

(1)

(2)

(3)

(4)

(5)

(6)

(7)

S.E.
(8)

Chile1, 3

55

(3.1)

62

(2.4)

63

(2.9)

60

(1.6)

Turkey1, 3

19

(2.9)

16

(1.9)

24

(2.2)

20

(1.3)

United States4

55

(2.6)

52

(4.1)

61

(4.0)

55

(1.9)

Average

43

(1.6)

43

(1.7)

49

(1.8)

45

(0.9)

1. Data on survey respondents’ highest educational attainment have been re-coded to improve compatibility with ISCED 2011.
2. Values for “Total” are suppressed because of discrepancies in the survey sample distribution by highest educational attainment compared to data published in Indicator A1.
3. Year of reference 2012.
4. Year of reference 2011.
Source: OECD (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933802665

132 Education at a Glance 2018: OECD Indicators   © OECD 2018

How are social outcomes related to education? – INDICATOR A6

chapter A

Under embargo until 11/09/2018 at 11.00am CEST
Table A6.4. Percentage of adults who report taking personal action to reduce energy use,

A6

by educational attainment (2016 or 2010)

European Social Survey and International Social Survey Programme, 25-64 year-olds
European Social Survey (2016)

Partners

OECD

Below upper secondary

Upper secondary
or post-secondary non-tertiary

Tertiary

Total

%

S.E.

%

S.E.

%

S.E.

%

S.E.

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

Austria1, 2

61

(4.1)

62

(1.6)

73

(2.4)

q

q

Belgium

73

(3.1)

72

(2.2)

78

(1.9)

75

(1.3)

Czech Republic

57

(3.9)

61

(1.4)

65

(3.0)

62

(1.2)

Estonia

68

(4.0)

70

(1.7)

72

(2.1)

70

(1.3)

Finland

68

(4.7)

74

(2.0)

80

(1.6)

77

(1.2)

France

71

(3.4)

81

(1.5)

83

(1.8)

80

(1.1)

Germany2

68

(4.6)

82

(1.3)

87

(1.2)

q

q

Iceland

57

(4.7)

57

(3.6)

63

(2.8)

60

(2.0)

Ireland

63

(2.5)

68

(2.0)

72

(1.5)

69

(1.1)

Israel

49

(4.6)

59

(1.9)

62

(1.8)

60

(1.3)

Netherlands

71

(2.9)

74

(2.2)

81

(2.0)

76

(1.3)

Norway2

75

(5.0)

68

(2.5)

69

(1.9)

q

q

Poland2

62

(2.4)

77

(2.2)

72

(2.5)

q

q

Slovenia

77

(3.9)

78

(1.9)

79

(2.5)

79

(1.4)

Sweden2

62

(5.9)

66

(2.3)

73

(2.2)

q

q

Switzerland

75

(3.7)

77

(2.0)

77

(2.1)

77

(1.4)

United Kingdom

66

(2.8)

73

(2.5)

78

(1.7)

74

(1.3)

Average

66

(1.0)

71

(0.5)

74

(0.5)

71

(0.4)

Russian Federation1, 2

39

(5.9)

51

(2.7)

46

(1.4)

q

q

International Social Survey Programme (2010)
Below upper secondary

Upper secondary
or post-secondary non-tertiary

Tertiary

Total

%

S.E.

%

S.E.

%

S.E.

%

(1)

(2)

(3)

(4)

(5)

(6)

(7)

S.E.
(8)

Chile1

38

(2.8)

42

(2.4)

46

(3.0)

42

(1.6)

Latvia

21

(4.2)

16

(1.8)

26

(3.4)

19

(1.5)

Portugal

49

(2.5)

55

(4.1)

51

(4.1)

51

(1.9)

Slovak Republic

37

(2.5)

41

(2.9)

42

(4.9)

39

(1.7)

Spain1

43

(1.9)

46

(2.5)

50

(2.0)

46

(1.2)

Turkey

39

(1.7)

44

(3.0)

44

(4.4)

41

(1.4)

United States1

44

(4.4)

38

(2.2)

46

(2.5)

42

(1.6)

Average

39

(1.1)

40

(1.1)

44

(1.4)

40

(0.6)

1. Data on survey respondents’ highest educational attainment have been re-coded to improve compatibility with ISCED 2011.
2. Values for “Total” are suppressed because of discrepancies in the survey sample distribution by highest educational attainment compared to data published in Indicator A1.
Source: OECD (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933802684

Education at a Glance 2018: OECD Indicators   © OECD 2018

133

Under embargo until 11/09/2018 at 11.00am CEST

INDICATOR A7

TO WHAT EXTENT DO ADULTS PARTICIPATE EQUALLY
IN EDUCATION AND LEARNING?
• Participation in formal and/or non-formal education increases with educational attainment across
countries and economies that participated in the Survey of Adult Skills (PIAAC). But it increases
more steeply for native-born adults and foreign-born adults who arrived in the country by age 25
than for foreign-born adults who arrived in the country at age 26 or older.

• On average, the participation in formal and/or non-formal education of foreign-born adults who
arrived at age 26 or older is slightly lower than that of native-born adults and foreign-born adults
who arrived by age 25.

• Having a job increases participation in formal and/or non-formal education overall, but slightly
more for native-born adults and foreign-born adults who arrived by age 25 than for foreign-born
adults who arrived at age 26 or older.

Figure A7.1. Participation of native- and foreign-born adults in formal and/or
non-formal education (2012 or 2015)
Survey of Adult Skills (PIAAC), 25-64 year-olds
Participation of native-born adults and foreign-born adults who arrived in the country by the age of 25
Participation of foreign-born adults who arrived in the country at 26 or older

%

80
70
60
50
40
30
20

Russian Federation* (2%)

Greece1 (1%)

Turkey1 (0%)

Slovak Republic (0%)

Poland2 (0%)

Lithuania1 (0%)

Chile1 (2%)

Japan2 (0%)

Korea (1%)

Czech Republic (1%)

Finland (3%)

England (UK) (7%)

Northern Ireland (UK) (3%)

Ireland (11%)

New Zealand1 (18%)

Norway (7%)

Australia2 (30%)

Spain (8%)

OECD average (6%)

Flemish Comm. (Belgium) (4%)

Estonia (2%)

United States (5%)

France (5%)

Canada (13%)

Italy (4%)

Denmark (5%)

Netherlands (5%)

Austria (7%)

Sweden (9%)

Slovenia1 (3%)

Germany (5%)

0

Israel1 (8%)

10

Note: The percentage in parentheses is the share of foreign-born adults who had arrived in the country at the age of 26 or older
out of the total adult population. Blue zone denotes statistically significant percentage-point differences. Some data points are not
displayed because there are too few observations to provide a reliable estimate. See Definitions and Methodology sections for more
information.
1. Reference year is 2015, for all other countries and economies the reference year is 2012.
2. Age at arrival in the country is not taken into account for the disaggregation between native- and foreign-born adults. Thus, the
two categories presented are native-born adults and foreign-born adults.
* See note on data for the Russian Federation in the Source section.
Countries are ranked in descending order of the percentage-point difference between the two groups.
Source: OECD (2018), Table A7.1. See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/
eag-2018-36-en).
1 2 https://doi.org/10.1787/888933802874

Context
Adult learning can play an important role in helping adults to develop and maintain key informationprocessing skills and acquire other knowledge and skills throughout their lives. It is crucial to provide
and ensure access to organised learning opportunities for adults beyond initial formal education,
especially for workers who need to adapt to changes throughout their careers (OECD, 2013[1]).

134 Education at a Glance 2018: OECD Indicators   © OECD 2018

Under embargo until 11/09/2018 at 11.00am CEST
Lifelong learning can also contribute to non-economic goals, such as personal fulfilment, improved
health, civic participation and social inclusion. However, the large variation in adult learning activities
and participation among OECD countries at similar levels of economic development suggests that
there are significant differences in learning cultures, learning opportunities at work and adulteducation systems (Borkowsky, 2013[2]).

INDICATOR A7

This indicator looks for the first time at participation in formal and/or non-formal education by
country of birth (i.e. native-born or foreign-born adults), complementing the analyses on adult
education and learning published in earlier editions of Education at a Glance. Formal and/or nonformal education is particularly important for foreign-born adults, whatever their level of education,
as it can help with their integration process in the host country (OECD, 2017[3]). For foreign-born
adults lacking expertise in the language(s) spoken in the host country, it is crucial to have access to
language training. Other types of adult training are also important for all foreign-born adults, to help
them adapt their skills or acquire new skills for labour-market needs in the host country.
The 2015 OECD/EU report, Indicators of Immigrant Integration 2015: Settling In, identifies notable
differences in literacy skills between native-born and foreign-born adults, with a decreasing gap as the
period of stay in the host country increases. The report also concludes that a weaker mastery of the
host country’s language may affect immigrants’ participation in formal and/or non-formal education.
Foreign-born adults report needing training more often than native-born adults, but foreign-born
adults are less likely than native-born adults to attend education and training courses. The cost of
training and the lack of required standards are the two main reasons reported by foreign-born adults
for not participating (OECD/EU, 2015[4]).
Other findings

• The difference in participation in formal and/or non-formal education between native-born adults
and foreign-born adults who arrived in the country by age 25 and foreign-born adults who arrived
in the country at age 26 or older is observed regardless of the overall share of foreign-born adults
who arrived in the country at age 26 or older and the overall level of participation in formal and/ or
non-formal education in a country.

• In countries where the difference between participation in formal and/or non-formal education
by native-born adults and foreign-born adults who arrived by age 25 and that of foreign-born
adults who arrived at age 26 or older is statistically significant for all adults, in most cases, the
differences are also statistically significant when disaggregated by employed adults and tertiaryeducated adults.
Note
While formal education provides a basis for adult education, it is important that those who have gone
through a formal education system outside of their host country also have access to and benefit from
formal and/or non-formal education.
Foreign-born adults may face different barriers to participation in education. For instance, foreignborn adults who received all or most of their education in a different country may lack familiarity with
the educational opportunities provided in their host country. As a result, they may participate less
than native-born adults or adults who arrived in the host country at an early age.
When analysing the impact of the country of birth on participation in formal and/or non-formal
education, it is important to factor in the information on when the person arrived in the host country.
Indeed, the age at arrival in the country (along with other variables, such as knowledge of the language
of the host country, birth country, reason for migration, human development index for the birth
countries and educational background) is crucial to assess the difference in access to formal and/or
non-formal education by foreign-born adults and native-born adults.
In this indicator, we divide the population into two groups: 1) native-born adults and foreign-born
adults who arrived in the country by age 25; and 2) foreign-born adults who arrived at age 26 or older.
The term “native-born adults” includes adults who were born in the country; it does not take into
account whether their parent(s) were born in the country or not.
Education at a Glance 2018: OECD Indicators   © OECD 2018

135

chapter A The Output of Educational Institutions and the Impact of Learning
Under embargo until 11/09/2018 at 11.00am CEST

A7

Analysis
Participation in formal and/or non-formal education for native-born adults and foreign-born adults
On average across countries and economies that participated in the Survey of Adult Skills (PIAAC) (see Source section
at the end of this indicator), about half of the adults (age 25-64) had participated in formal and/or non-formal
education during the 12 months preceding the survey. Participation rates ranged widely, from 25% or less in Greece,
Italy, Turkey and the Russian Federation to above 65% in Denmark, Finland, New Zealand and Sweden (Table A7.1).
For native-born adults and foreign-born adults who arrived by age 25, participation in formal and/or non-formal
education in all countries is similar to the average for the whole population, with a difference of 1 or 2 percentage
points. For foreign-born adults who arrived at age 26 or older, participation is on average about 2 percentage points
lower than for native-born adults and foreign-born adults who arrived by age 25 (Figure A7.1 and Table A7.1).
In Finland, New Zealand and Norway, participation in formal and/or non-formal education is above 60% for both
native-born adults and foreign-born adults who arrived by age 25 and foreign-born adults who arrived at age 26 or
older. This demonstrates a high level of participation in formal and/or non-formal education overall, regardless of
country of birth. In nine countries with data on both native-born adults and foreign-born adults who arrived by age 25
and foreign-born adults who arrived at age 26 or older, the difference in participation between the two groups is
statistically significant. In all these cases, foreign-born adults who arrived in the country at age 26 or older participate
less in formal and/or non-formal education than native-born adults and foreign-born adults who arrived by age 25.
The participation rate among foreign-born adults who arrived in the country at age 26 or older remains relatively high
in some countries. In Canada, Denmark, the Netherlands and Sweden, over 50% of foreign-born adults who arrived at
age 26 or older participate in formal and/or non-formal education, compared to 48% on average across OECD countries
and economies. In contrast, in Germany and Israel, the difference between the two groups is 15 percentage points, and
participation among foreign-born adults who arrived at 26 or older is below average (Figure A7.1).
The gap in participation in formal and/or non-formal education is not influenced by the proportion of foreignborn adults who arrived at age 26 or older. In both Austria and Norway, for example, 7% of foreign-born adults
arrived at age 26 or older. In Norway, there is almost no difference in participation between those who arrived by
age 25 and those who arrived at age 26 or older, and both groups have a higher-than-average participation rate.
In Austria, about 50% of native-born adults and foreign-born adults who arrived by age 25 participate in formal
and/or non‑formal education, but the share is about 15 percentage points lower among foreign-born adults who
arrived at age 26 or older. This suggests that some countries are successful at offering equal opportunities to both
groups and thereby ensuring high participation while, in some other countries, foreign-born adults who arrived at
26 and older seem to be left behind (Figure A7.1).
Participation in formal and/or non-formal education for native-born adults and foreign-born adults,
by labour-force status
On average across OECD countries and economies that participated in the Survey of Adult Skills (PIAAC), 50% of
25-64 year-olds responded that they had participated in formal and/or non-formal education during the 12 months
preceding the survey. Participation rates are, on average, higher among employed adults (58%) than among
unemployed adults (43%) and inactive adults (i.e. not those seeking employment) (22%) (Tables A7.1 and A7.2).
Participation rates also vary between foreign-born and native-born adults, even among those with equivalent
labour‑force status. On average across OECD countries and economies, 52% of employed foreign-born adults who
arrived at age 26 or older participated in formal and/or non-formal education. This share is 7 percentage points
lower than the average participation rate across OECD countries and economies for employed native-born adults and
foreign-born adults who arrived by age 25. This average difference, 7 percentage points, is statistically significant
and is about triple the average difference among all adults (Figures A7.1 and A7.2).
In 11 of the 21 countries and economies with available data, the differences in participation rates between nativeborn adults and foreign-born adults who arrived by age 25 and foreign-born adults who arrived at age 26 or older
are statistically significant. In the Flemish Community of Belgium, Italy and Spain, the differences between the
two groups become statistically significant when accounting for employed adults. In all of the 11 countries and
economies, employed foreign-born adults who arrived at age 26 or older participate less in formal and/or non‑formal
education than employed native-born adults and foreign-born adults who arrived by age 25. The gap in participation
rates ranges from 10 percentage points in Denmark to over 20 percentage points in France, Germany, Israel and
Slovenia. Also, in all of the 11 countries and economies, the gaps are larger when accounting for employed adults
than for all adults regardless of labour-force status (Figures A7.1 and A7.2).

136 Education at a Glance 2018: OECD Indicators   © OECD 2018

To what extent do adults participate equally in education and learning? – INDICATOR A7

chapter A

Under embargo until 11/09/2018 at 11.00am CEST

Figure A7.2. Participation of native- and foreign-born adults in formal and/or
non-formal education among employed adults (2012 or 2015)

A7

Survey of Adult Skills (PIAAC), 25-64 year-olds
Participation of native-born adults and foreign-born adults who arrived in the country by the age of 25
Participation of foreign-born adults who arrived in the country at 26 or older

%

80
70
60
50
40
30
20

Russian Federation* (2%)

Greece1 (1%)

Turkey1 (0%)

Lithuania1 (0%)

Slovak Republic (0%)

Poland2 (0%)

Japan2 (0%)

Korea (1%)

Chile1 (2%)

Czech Republic (1%)

New Zealand1 (18%)

Norway (7%)

England (UK) (7%)

Finland (3%)

Australia2 (30%)

Ireland (11%)

Estonia (2%)

Netherlands (5%)

Northern Ireland (UK) (3%)

Denmark (5%)

OECD average (6%)

Canada (13%)

United States (5%)

Spain (8%)

Sweden (9%)

Flemish Comm. (Belgium) (4%)

Italy (4%)

Austria (7%)

France (5%)

Israel1 (8%)

Slovenia1 (3%)

0

Germany (5%)

10

Note: The percentage in parentheses is the share of foreign-born adults who had arrived in the country at the age of 26 or older out of the total
adult population. Blue zone denotes statistically significant percentage-point differences. Some data points are not displayed because there are too
few observations to provide a reliable estimate. See Definitions and Methodology sections for more information.
1. Reference year is 2015, for all other countries and economies the reference year is 2012.
2. Age at arrival in the country is not taken into account for the disaggregation between native- and foreign-born adults. Thus, the two categories
presented are native-born adults and foreign-born adults.
* See note on data for the Russian Federation in the Source section.
Countries are ranked in descending order of the percentage-point difference between the two groups.
Source: OECD (2018), Table A7.2. See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933802893

One of the reasons that the gap is especially marked among employed adults might be that having a job does
not significantly increase participation rates for foreign-born adults who arrived at age 26 or older, while it does
increase participation rates for native-born adults and foreign-born adults who arrived by age 25. On average
across OECD countries and economies, the participation rate is only 4 percentage points higher for employed
foreign-born adults who arrived at age 26 or older (52%) than for all foreign-born adults who arrived in the
country at age 26 or older (48%). However, the participation rate is 8 percentage points higher for employed
native-born adults and foreign‑born adults who arrived by age 25 (58%) than for all native-born adults and
foreign-born adults who arrived by age 25 (50%), and the difference is statistically significant (Figures A7.1
and A7.2).
This suggests that, although having a job has a positive effect on participation in formal and/or non-formal
education in general, foreign-born adults who arrived at age 26 or older may enjoy fewer advantages from
employment in terms of access to formal and/or non-formal education. In France and Spain, the participation
gap in formal and/ or non‑formal education between native-born adults and foreign-born adults who arrived by
age 25 and foreign-born adults who arrived at age 26 or older is particularly larger among employed adults than
among all adults (Figures A7.1 and A7.3). This may be related to the fact that those working in low-qualified jobs
often have a lower participation rate in adult education and learning. In France and Spain, a high share of foreignborn adults who arrived at age 26 or older have low educational attainment and may end up in such jobs.
Education at a Glance 2018: OECD Indicators   © OECD 2018

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Participation in formal and/or non-formal education for native-born adults and foreign-born
adults, by educational attainment
On average across OECD countries and economies that participated in the Survey of Adult Skills (PIAAC), 70% of
tertiary-educated adults participated in formal and/or non-formal education during the 12 months preceding the
survey. This share is well above the participation rates for those with below upper secondary education (26%) and
those with upper secondary or post-secondary non-tertiary education (46%) (Table A7.3).
Foreign-born adults who arrived in the country at age 26 or older participate less than native-born adults and
foreign-born adults who arrived in the country by age 25, even among those with equivalent educational attainment
levels. On average across OECD countries and economies, 61% of tertiary-educated foreign-born adults who
arrived at age 26 or older participated in formal and/or non-formal education, 10 percentage points lower than
the participation rate of native-born adults and foreign-born adults with equivalent educational attainment who
arrived by age 25 (Figure A7.3).
The differences in participation rates between native-born adults and foreign-born adults who arrived by age 25 and
foreign-born adults who arrived at age 26 or older are statistically significant in 10 out of the 16 countries with data.
Among those countries, the difference ranges from 7 percentage points in Australia and Ireland to 27 percentage
points in Israel. The gap is also above 15 percentage points in Austria, France, Germany and Spain (Figure A7.3).

Figure A7.3. Participation of native- and foreign-born adults in formal and/or
non-formal education among tertiary-educated adults (2012 or 2015)
Survey of Adult Skills (PIAAC), 25-64 year-olds
Participation of native-born adults and foreign-born adults who arrived in the country by the age of 25
Participation of foreign-born adults who arrived in the country at 26 or older

%

90
80
70
60
50
40
30
20

Russian Federation* (2%)

Greece1 (1%)

Turkey1 (0%)

Italy (4%)

Japan2 (0%)

Slovak Republic (0%)

Lithuania1 (0%)

Korea (1%)

Poland2 (0%)

Czech Republic (1%)

Northern Ireland (UK) (3%)

Chile1 (2%)

Finland (3%)

Slovenia1 (3%)

Netherlands (5%)

New Zealand1 (18%)

England (UK) (7%)

Australia2 (30%)

Ireland (11%)

Norway (7%)

Estonia (2%)

OECD average (6%)

Sweden (9%)

Flemish Comm. (Belgium) (4%)

Canada (13%)

United States (5%)

Spain (8%)

Denmark (5%)

France (5%)

Austria (7%)

0

Germany (5%)

10
Israel1 (8%)

A7

Note: The percentage in parentheses is the share of foreign-born adults who had arrived in the country at the age of 26 or older out of the total
adult population. Blue zone denotes statistically significant percentage-point differences. Some data points are not displayed because there are too
few observations to provide a reliable estimate. See Definitions and Methodology sections for more information.
1. Reference year is 2015, for all other countries and economies the reference year is 2012.
2. Age at arrival in the country is not taken into account for the disaggregation between native- and foreign-born adults. Thus, the two categories
presented are native-born adults and foreign-born adults.
* See note on data for the Russian Federation in the Source section.
Countries are ranked in descending order of the percentage-point difference between the two groups.
Source: OECD (2018), Table A7.3. See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933802912

138 Education at a Glance 2018: OECD Indicators   © OECD 2018

To what extent do adults participate equally in education and learning? – INDICATOR A7

chapter A

Under embargo until 11/09/2018 at 11.00am CEST
On average across OECD countries and economies, the participation rate for tertiary-educated foreign-born adults
who arrived at age 26 or older is 13 percentage points higher than for the entire population of foreign-born adults
who arrived at age 26 or older. However, for native-born adults and foreign-born adults who arrived in the country
by age 25, the difference is larger (21 percentage points), showing a stronger impact of tertiary education on
participation for native-born adults and foreign-born adults who arrived by age 25 than for foreign-born adults who
arrived at age 26 or older. The participation gap between the two groups is at least 10 percentage points larger than
the differences among all adults in France and Spain (Figures A7.1 and A7.3).

Box A7.1. Active labour market programmes in OECD countries
Active labour market programmes (ALMPs) aim to support the efficient functioning of the labour market
by increasing the employability and motivation of jobseekers and expanding their earnings opportunities
(OECD, 2015[5]; OECD, 2017[6]). ALMPs include labour market services (such as placement and related services
and benefit administration) and labour market programmes (such as training, employment incentives, direct
job creation or startup incentives) (OECD, 2017[6]).
Evidence shows that training programmes have long-term impact on employment and earnings for their
participants. However, it is important that training programmes correspond with labour market needs, and
they should, therefore, also reflect employers’ needs, to maximise their impact (OECD, 2015[5]).
Countries’ investment in training as part of ALMPs
The OECD Database on Labour Market Programmes provides data on participation and expenditure patterns of
different labour market programmes, one of which is training programmes. Figure A7.a shows that the highest
expenditure on training programmes as a percentage of GDP is found in Austria, Denmark and Finland, where
the share is above 0.40% of GDP. In contrast, in Australia, Hungary, Japan, Mexico, Poland, the Slovak Republic
and the United Kingdom, public expenditure on training programmes as part of ALMPs is the lowest, at less
than 0.02% of GDP.

Figure A7.a. Public expenditure on training programmes within active labour market
programmes as a percentage of GDP (2015)
%

0.7
0.6
0.5
0.4
0.3
0.2

Mexico

Slovak Republic

United Kingdom3

Japan

Poland

Hungary

Australia

United States

Czech Republic

Korea

Slovenia

Luxembourg

Israel

Latvia

Lithuania

Netherlands

Estonia2

Chile

Canada

Greece

Norway

Spain

New Zealand2

Sweden

OECD average

Italy

Belgium

Switzerland

Ireland1

Germany

France

Portugal

Austria

Finland

0

Denmark

0.1

1. The changes from 2014 to 2015 are largely driven by the substantial increase in GDP in 2015. For more information on this increase see
www.cso.ie/en/media/csoie/newsevents/documents/pr_GDPexplanatorynote.pdf. In 2016 Ireland produced a modified GNI (GNI*) that was
recommended by the Economic Statistics Review Group and is designed to exclude globalisation effects that are disproportionately impacting
the measurement size of the Irish economy.
2. Reference year is 2014.		
3. Reference year is 2011.		
Countries are ranked in descending order of public expenditure on training programmes as part of active labour market programmes as a percentage
of GDP. 		
Source: OECD (2018), Labour Market Programmes; Public expenditure and participant stocks on LMP, https://stats.oecd.org/Index.
aspx?DataSetCode=LMPEXP#.
1 2 https://doi.org/10.1787/888933802931

…

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A7

Some countries have high expenditure on other ALMP categories. For example, Sweden spends 0.60% of GDP
on employment incentives, and Hungary spends 0.74% of GDP on direct job creation. However, on average,
training represents 25% of public expenditure on all ALMPs across OECD countries, and there is a high
correlation between public expenditure on training programmes and total public expenditure on ALMPs.
Activating training programmes when unemployment is high
While there is no consensus on the fact that ALMPs have a large positive impact during economic downturns,
some studies have shown positive correlations with re-employment. Nordlund showed that in Sweden training
programmes had a positive impact, regardless of the state of the economy (Nordlund, 2011[7]). However, during
slower economic periods, training programmes were beneficial because of their bridging effect in delaying the
return to the labour market at times when finding a job was more difficult. For Germany, Lechner, Miquel and
Wunsch (2011[8]) showed a long-term positive impact for participants who registered in training programmes
in the 1990s when the unemployment rate was high. However, these findings cannot be generalised. Wunsch
and Lechner (2008[9]) found that a similar set of programmes in the 2000s failed to improve the participants’
chances of finding regular employment. They conclude that aspects such as the quality of the programmes,
the participants or the assignment process, and certain characteristics of the labour market play an important
role. A meta-study analysing the findings from 137 evaluations of several types of ALMPs found that a higher
unemployment rate in the labour market at the time of participation in a programme was associated with a
significantly higher probability of a positive estimated impact (Kluve, 2010[10]).
Figure A7.b presents the average evolution of public expenditure on ALMPs and, more specifically, on training
programmes between 2004 and 2015. Public expenditure on all ALMPs went from 0.46% of GDP in 2008 to
0.60% in 2010. In parallel, public expenditure on training programmes went from 0.12% of GDP in 2008 to
0.17% in 2010. This shows that public expenditure on ALMPs and on training programmes followed similar
trends, as they each increased by 30% between 2008 and 2010 as an effect of rising unemployment rates.
On average across OECD countries, spending on training programmes always represented about 25% of all
spending on ALMPs, regardless of the economic situation. On average, the public expenditure on training
programmes shows alignment with total spending on ALMPs, but evolution within countries presents variations
in terms of resource allocation, with some important shifts between 2008 and 2009. For example, in Canada,
Estonia, Latvia, Portugal and Slovenia, the share of training programmes in the budgets of ALMPs rose by at
least 10 percentage points, mainly due to a rise in expenditure on institutional training. In Poland, the share
decreased by 15 percentage points over the same period, due to a cut in special support for apprenticeships
(OECD, 2017[6]).
Figure A7.b. Trends in public expenditure on training programmes within active labour market
programmes and on all active labour market programmes as a percentage of GDP (2004-2015)
OECD average
All active labour market programmes
Training programmes

%

0.7
0.6
0.5
0.4
0.3
0.2
0.1
0

2004
(5.9%)

2005
(5.7%)

2006
(5.2%)

2007
(4.8%)

2008
(5.1%)

2009
(7.1%)

2010
(7.3%)

2011
(7.0%)

2012
(7.0%)

2013
(7.0%)

2014
(6.5%)

2015
(6.0%)

Note: The percentage in parentheses represents the weighted average of the unemployment rate for 25-64 year-olds.
Source: OECD (2018), Labour Market Programmes; Public expenditure and participant stocks on LMP, https://stats.oecd.org/Index.
aspx?DataSetCode=LMPEXP#.
1 2 https://doi.org/10.1787/888933802950

140 Education at a Glance 2018: OECD Indicators   © OECD 2018

To what extent do adults participate equally in education and learning? – INDICATOR A7

chapter A

Under embargo until 11/09/2018 at 11.00am CEST
The participation in formal and/or non-formal education decreases with lower educational attainment. This holds
true for both groups among countries and economies with data on participation of native-born and foreign-born
adults in formal and/or non-formal education by educational attainment. In all of the seven countries where the
differences are statistically significant, foreign-born adults who arrived at age 26 or older with upper secondary or
post-secondary non-tertiary education participated less in formal and/or non-formal education than native-born
adults and foreign-born adults who arrived by age 25. The gaps are above 20 percentage points and the largest in
Germany, Israel and Italy (Table A7.3).
At below upper secondary level, only a few countries have estimates on the participation of foreign-born adults who
arrived at age 26 or older. But among countries with data, both native-born adults and foreign-born adults who
arrived by age 25 and foreign-born adults who arrived at age 26 or older tend to have lower participation rates than
those with higher educational attainment. While foreign-born adults who arrived at age 26 or older participated
more in formal and/or non-formal education than native-born adults and foreign-born adults who arrived by age 25
in some countries, the differences are not statistically significant in all countries with data (Table A7.3).
As noted above, the difference in participation rates is the largest among tertiary-educated adults in most of the
countries surveyed. This gap can be related to the difficulties that highly educated foreign-born adults who arrived
at age 26 or older may face to benefit from their skills if they do not master the language of the host country
and have a poor understanding of local labour-market dynamics. This situation may result in lower employment
rates and employment in lower-paid jobs, both of which hamper opportunities for foreign-born adults to access
employer-sponsored training. According to the OECD/EU report, Indicators of Immigrants Integration 2015:
Settling In (OECD/EU, 2015[4]), immigrants, especially those who migrated recently, have markedly lower levels of
literacy in the host-country language than people born in the host country, regardless of their level of education.
A tertiary education degree is no guarantee of proficiency, particularly in host countries where the language
is not widely used beyond national borders, (OECD, 2015[5]). As foreign-born adults have different language
and educational backgrounds it is important to provide tailor-made measures to ensure successful integration.
Providing formal and/or non-formal education programmes solely to address the language barrier might be
insufficient, if the skills of foreign-born adults are not fully exploited on the labour market. Combining language
classes with professional integration programmes could better respond to the needs of the labour market and
result in quicker and more successful transitions to employment (OECD, 2017[3]).

Definitions
Adults refer to 25-64 year-olds.
Adult education and learning: Formal education is planned education provided in the system of schools, colleges,
universities and other formal educational institutions that normally constitutes a continuous “ladder” of full-time
education for children and young people. The providers may be public or private. Non-formal education is sustained
educational activity that does not correspond exactly to the definition of formal education. Non-formal education
may take place both within and outside educational institutions and cater to individuals of all ages. Depending on
country contexts, it may cover education programmes in adult literacy, basic education for out‑of‑school children,
life skills, work skills and general culture. The Survey of Adult Skills (PIAAC) uses a list of possible non-formal
education activities (including open or distance-learning courses, private lessons, organised sessions for on‑the‑job
training, and workshops or seminars) to prompt respondents to list all of their learning activities during the previous
12 months. Some of these learning activities might be of short duration.
Levels of education: Below upper secondary corresponds to ISCED-97 levels 0, 1, 2 and 3C short programmes;
upper secondary or post-secondary non-tertiary corresponds to ISCED-97 levels 3A, 3B, 3C long programmes,
and level 4; and tertiary corresponds to ISCED-97 levels 5A, 5B and 6.

Methodology
The observations based on a numerator with fewer than 5 observations or on a denominator with fewer than
30 observations times the number of categories have been replaced by “c” in the tables. For Chile, the Czech Republic,
Greece, Japan, Korea, Lithuania, Poland, the Russian Federation, the Slovak Republic and Turkey, too few
observations are available to provide reliable estimates on the variable “Foreign-born adults who arrived in the
country at age 26 or older”. The participation in formal and/or non-formal education for native-born adults and
foreign-born adults who arrived by age 25 is maintained in the figures for cross-country comparison purposes.
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A7

For Australia, Japan and Poland, data on age at arrival in the country is not taken into account for the disaggregation
between native-born adults and foreign-born adults. Thus, the two groups should be understood as native-born
adults and foreign-born adults, regardless of the age at arrival in the country.
The selection of languages available in the Survey of Adult Skills (PIAAC) varied, even in countries where a significant
proportion of foreign-born adults come from similar backgrounds. For example, Turkish foreign-born adults make
up a considerable share among foreign-born adults in both Austria and Germany, but the background questionnaire
was provided in Turkish only in Austria, not in Germany.
Respondents in some countries were offered interpretation support beyond the official translations of the
background questionnaire. In Sweden, for example, if the respondent was not sufficiently proficient in Swedish, the
interviewer offered to have an interpreter present during the interview for the background questionnaire.
Depending on the country, foreign-born adults who did not master the language of the host country were excluded
from the survey.
With the exception of the data in Box A7.1, all data in this indicator are taken from the Survey of Adult Skills
(PIAAC). As the Survey of Adult Skills (PIAAC) was not specifically designed to analyse migrant populations, the
sample size can be small for foreign-born adults who arrived in the country at age 26 or older. Due to the small
number of observations, the data need to be interpreted with care, and the interpretation should take into account
the standard errors and statistically significant differences.
Please see Annex 3 for country-specific notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Lithuania was not an OECD member at the time of preparation of this publication. Accordingly, Lithuania does not
appear in the list of OECD members and is not included in the zone aggregates.

Source
All data are based on the OECD Programme for the International Assessment of Adult Competencies (the Survey of
Adult Skills [PIAAC]), except for Box A7.1.

Note regarding data from Israel
The statistical data for Israel are supplied by and are under the responsibility of the relevant Israeli authorities. The use
of such data by the OECD is without prejudice to the status of the Golan Heights, East Jerusalem and Israeli settlements
in the West Bank under the terms of international law.

Note regarding data from the Russian Federation in the Survey of Adult Skills (PIAAC)
The sample for the Russian Federation does not include the population of the Moscow municipal area. The data published,
therefore, do not represent the entire resident population aged 16-65 in the Russian Federation but rather the population
of the Russian Federation excluding the population residing in the Moscow municipal area. More detailed information
regarding the data from the Russian Federation as well as that of other countries can be found in the Technical Report of the
Survey of Adult Skills, Second Edition (OECD, 2016[11]).

References
Borkowsky, A. (2013), “Monitoring adult learning policies: A theoretical framework and indicators”, OECD Education [2]
Working Papers, No. 88, OECD Publishing, Paris, http://dx.doi.org/10.1787/5k4c0vxjlkzt-en.
Kluve, J. (2010), “The effectiveness of European active labor market programs”, Labour Economics, Vol. 17/6, pp. 904-918, [10]
http://dx.doi.org/10.1016/J.LABECO.2010.02.004.
Lechner, M., R. Miquel and C. Wunsch (2011), “Long-run effects of public sector sponsored training in West Germany”, [8]
Journal of the European Economic Association, Vol. 9/4, pp. 742-784, http://dx.doi.org/10.1111/j.1542-4774.2011.01029.x.
Nordlund, M. (2011), “What works best when? The role of active labour market policy programmes in different business [7]
cycles”, International Journal of Social Welfare, Vol. 20/1, pp. 43-54, http://dx.doi.org/10.1111/j.1468-2397.2009.00683.x.
OECD (2017), International Migration Outlook 2017, OECD Publishing, Paris, http://dx.doi.org/10.1787/migr_outlook- [3]
2017-en.

142 Education at a Glance 2018: OECD Indicators   © OECD 2018

To what extent do adults participate equally in education and learning? – INDICATOR A7

chapter A

Under embargo until 11/09/2018 at 11.00am CEST
OECD (2017), Labour Market Programmes Database - Public expenditure and participant stocks on LMP, https://stats.oecd. [6]
org/Index.aspx?DataSetCode=LMPEXP (accessed on 28 November 2017).
OECD (2016), Technical Report of the Survey of Adult Skills (PIAAC), 2nd Edition, OECD, Paris, www.oecd.org/skills/piaac/ [11]
PIAAC_Technical_Report_2nd_Edition_Full_Report.pdf.
OECD (2015), OECD Employment Outlook 2015, OECD Publishing, Paris, http://dx.doi.org/10.1787/empl_outlook-2015-en. [5]
OECD (2013), OECD Skills Outlook 2013 : First results from the Survey of Adult Skills, OECD Publishing, Paris, http://dx.doi. [1]
org/10.1787/9789264204256-en.
OECD/EU (2015), Indicators of Immigrant Integration 2015: Settling In, OECD Publishing, Paris, http://dx.doi.org/10.1787/ [4]
9789264234024-en.
Wunsch, C. and M. Lechner (2008), “What did all the money do? On the general ineffectiveness of recent West German [9]
labour market programmes”, Kyklos, Vol. 61/1, pp. 134-174, http://dx.doi.org/10.1111/j.1467-6435.2008.00396.x.

Indicator A7 Tables
1 2 https://doi.org/10.1787/888933802798

Table A7.1 Participation of native- and foreign-born adults in formal and/or non-formal education,
by gender and their population distribution (2012 or 2015)
Table A7.2 Participation of native- and foreign-born adults in formal and/or non-formal education,
by labour-force status (2012 or 2015)
Table A7.3 Participation of native- and foreign-born adults in formal and/or non-formal education,
by educational attainment (2012 or 2015)
Cut-off date for the data: 18 July 2018. Any updates on data can be found on line at http://dx.doi.org/10.1787/eag-data-en. More breakdowns can
also be found at http://stats.oecd.org/, Education at a Glance Database.

Education at a Glance 2018: OECD Indicators   © OECD 2018

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chapter A The Output of Educational Institutions and the Impact of Learning
Under embargo until 11/09/2018 at 11.00am CEST
Table A7.1. Participation of native- and foreign-born adults in formal and/or non-formal education

A7

by gender and their population distribution (2012 or 2015)
Survey of Adult Skills (PIAAC), 25-64 year-olds
Participation in forma and/or non-formal education

Native-born adults
and foreign-born adults who arrived
in the country by the age of 25

OECD

%

Men
S.E.

Foreign-born adults
who arrived in the country at 26 or older

Women
%
S.E.

Total
%
S.E.

%

Men
S.E.

Total population distribution

Women
%
S.E.

Total
%
S.E.

%

Total
S.E.

Native-born
adults and
foreign-born Foreign-born
adults who
adults who
arrived in the arrived in the
country
country by
the age of 25 at 26 or older
%
S.E.
%
S.E.

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

(13)

(14)

(15)

(16)

(17)

(18)

Australia1

57

(1.2)

55

(1.1)

56

(0.9)

57

(2.1)

52

(1.9)

55

(1.4)

56

(0.7)

70

(0.7)

30

(0.7)

Austria

51

(1.2)

48

(1.1)

49

(0.7)

41

(4.9)

29

(4.9)

36

(3.8)

48

(0.7)

93

(0.4)

7

(0.4)

Canada

60

(0.8)

59

(0.8)

59

(0.6)

52

(2.5)

51

(1.8)

52

(1.7)

58

(0.6)

87

(0.4)

13

(0.4)

Chile2

53

(2.2)

42

(2.1)

48

(1.9)

c

c

c

c

c

c

47

(1.9)

98

(0.9)

2

(0.9)

Czech Republic

53

(1.7)

46

(1.3)

50

(1.2)

c

c

c

c

c

c

50

(1.2)

99

(0.3)

1

(0.3)

Denmark

64

(1.0)

69

(0.9)

67

(0.7)

54

(3.2)

61

(2.8)

58

(2.2)

66

(0.6)

95

(0.1)

5

(0.1)

Estonia

48

(1.0)

57

(0.9)

53

(0.7)

c

c

42

(4.7)

45

(3.9)

53

(0.7)

98

(0.2)

2

(0.2)

Finland

63

(1.0)

70

(1.1)

66

(0.7)

c

c

c

c

69

(5.0)

66

(0.7)

97

(0.2)

3

(0.2)

France

37

(0.8)

36

(0.9)

36

(0.6)

23

(3.3)

31

(3.5)

27

(2.5)

36

(0.6)

95

(0.2)

5

(0.2)

Germany

57

(1.3)

51

(1.4)

54

(1.1)

39

(6.4)

32

(5.2)

35

(4.0)

53

(1.0)

95

(0.4)

5

(0.4)

Greece2

22

(1.1)

19

(1.0)

21

(0.8)

c

c

c

c

c

c

20

(0.8)

99

(0.3)

1

(0.3)

Ireland

52

(1.2)

49

(1.0)

51

(0.8)

56

(3.7)

48

(3.3)

52

(2.4)

51

(0.7)

89

(0.5)

11

(0.5)

Israel2

54

(1.1)

55

(1.2)

55

(0.8)

39

(5.3)

29

(3.6)

33

(3.5)

53

(0.8)

92

(0.4)

8

(0.4)

Italy

27

(1.5)

23

(1.0)

25

(1.0)

c

c

18

(6.2)

16

(4.4)

25

(1.0)

96

(0.4)

4

(0.4)

Japan1

48

(1.1)

35

(0.9)

42

(0.8)

c

c

c

c

c

c

42

(0.8)

100

(0.1)

0

(0.1)

Korea

54

(1.1)

46

(1.0)

50

(0.8)

c

c

c

c

c

c

50

(0.8)

99

(0.1)

1

(0.1)

Netherlands

67

(1.1)

62

(1.0)

65

(0.6)

55

(6.0)

53

(5.8)

54

(4.1)

64

(0.6)

95

(0.4)

5

(0.4)

New Zealand2

68

(1.2)

67

(1.3)

67

(0.9)

71

(3.0)

67

(2.8)

69

(2.3)

68

(0.8)

82

(0.7)

18

(0.7)

Norway

63

(1.1)

66

(1.1)

64

(0.8)

66

(3.8)

63

(4.5)

65

(2.8)

64

(0.7)

93

(0.4)

7

(0.4)

Poland1

35

(1.1)

36

(1.1)

35

(0.8)

c

c

c

c

c

c

35

(0.8)

100

(0.0)

0

(0.0)

Slovak Republic

34

(1.2)

32

(1.1)

33

(0.8)

c

c

c

c

c

c

33

(0.8)

100

(0.1)

0

(0.1)

Slovenia2

47

(1.1)

50

(1.0)

49

(0.8)

32

(5.7)

c

c

35

(4.3)

48

(0.8)

97

(0.3)

3

(0.3)

Spain

47

(0.9)

46

(1.1)

47

(0.7)

48

(4.2)

38

(3.9)

42

(2.9)

47

(0.7)

92

(0.3)

8

(0.3)

Sweden

65

(1.2)

69

(1.1)

67

(0.8)

48

(4.3)

61

(4.4)

55

(2.9)

66

(0.8)

91

(0.4)

9

(0.4)

Turkey2

29

(1.2)

16

(0.9)

23

(0.8)

c

c

c

c

c

c

23

(0.8)

100

(0.1)

0

(0.1)

United States

59

(1.6)

60

(1.4)

60

(1.1)

62

(6.4)

45

(5.0)

53

(3.4)

59

(1.1)

95

(0.4)

5

(0.4)

Flemish Comm. (Belgium)

49

(1.3)

49

(1.1)

49

(0.8)

c

c

52

(5.2)

44

(4.4)

49

(0.8)

96

(0.3)

4

(0.3)

England (UK)

58

(1.4)

54

(1.1)

56

(0.9)

61

(5.5)

61

(4.6)

61

(3.5)

56

(0.9)

93

(0.4)

7

(0.4)

Northern Ireland (UK)

48

(1.5)

49

(1.2)

49

(1.0)

c

c

56

(7.5)

51

(5.4)

49

(0.9)

97

(0.4)

3

(0.4)

OECD average

51

(0.2)

49

(0.2)

50

(0.2)

50

(1.1)

47

(1.0)

48

(0.8)

50

(0.2)

94

(0.1)

6

(0.1)

Lithuania2

30

(1.4)

36

(1.3)

34

(0.8)

c

c

c

c

c

c

34

(0.8)

100

(0.1)

0

(0.1)

Russian Federation*

16

(1.6)

23

(2.0)

20

(1.6)

c

c

c

c

c

c

20

(1.6)

98

(0.4)

2

(0.4)

Countries

Partners

Economies

1. Age at arrival in the country is not taken into account for the disaggregation between native- and foreign-born adults. Thus, the two categories presented are
native-born adults and foreign-born adults.
2. Reference year is 2015, for all other countries and economies the reference year is 2012.
* See note on data for the Russian Federation in the Source section.
Source: OECD (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933802817

144 Education at a Glance 2018: OECD Indicators   © OECD 2018

To what extent do adults participate equally in education and learning? – INDICATOR A7

chapter A

Under embargo until 11/09/2018 at 11.00am CEST
Table A7.2. Participation of native- and foreign-born adults in formal and/or non-formal education,

by labour-force status (2012 or 2015)

Survey of Adult Skills (PIAAC), 25-64 year-olds

OECD

Native-born adults
and foreign-born adults
who arrived in the
country by the age of 25
%
S.E.

Participation
of employed adults

Participation
of unemployed adults

Participation
of inactive adults

Foreign-born adults
who arrived in the
country at 26 or older
%
S.E.

Native-born adults
and foreign-born adults
who arrived in the
country by the age of 25
%
S.E.

Native-born adults
and foreign-born adults
who arrived in the
country by the age of 25
%
S.E.

Total
%

S.E.

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(13)

(14)

Australia1

66

(1.0)

63

(1.6)

65

(0.8)

51

(6.1)

19

(1.7)

Austria

56

(0.9)

40

(3.9)

55

(0.9)

53

(6.3)

21

(1.6)

Canada

67

(0.6)

56

(1.9)

65

(0.6)

49

(3.4)

26

(1.2)

Chile2

53

(2.1)

c

c

53

(2.0)

48

(6.9)

23

(2.7)

Czech Republic

61

(1.4)

c

c

61

(1.4)

32

(4.9)

13

(1.7)

Denmark

74

(0.8)

64

(2.5)

73

(0.7)

63

(3.9)

34

(1.8)

Estonia

61

(0.9)

53

(4.5)

61

(0.9)

36

(2.8)

16

(1.1)

Finland

76

(0.7)

73

(5.7)

76

(0.7)

58

(3.7)

29

(1.7)

France

44

(0.8)

24

(2.8)

43

(0.8)

28

(3.0)

13

(1.0)

Germany

60

(1.2)

34

(4.8)

59

(1.1)

41

(4.7)

24

(2.1)

Greece2

29

(1.2)

c

c

28

(1.2)

17

(1.9)

9

(1.1)

Ireland

62

(1.0)

58

(2.8)

62

(1.0)

40

(2.7)

24

(1.4)

Israel2

62

(1.0)

38

(4.2)

60

(0.9)

44

(4.3)

28

(1.5)

Italy

33

(1.3)

18

(5.2)

32

(1.2)

19

(2.5)

10

(1.1)

Japan1

49

(0.9)

c

c

49

(0.9)

c

c

17

(1.3)

Korea

56

(1.0)

c

c

56

(1.0)

51

(4.9)

30

(1.5)

Netherlands

73

(0.8)

64

(5.4)

73

(0.8)

56

(5.0)

26

(1.8)

New Zealand2

73

(1.0)

76

(2.2)

73

(0.9)

56

(3.8)

39

(2.3)

Norway

70

(0.8)

71

(3.2)

70

(0.8)

54

(5.8)

28

(2.1)

Poland1

46

(1.0)

c

c

46

(1.0)

27

(2.8)

10

(0.9)

Slovak Republic

45

(1.1)

c

c

44

(1.1)

12

(2.0)

7

(0.8)

Slovenia2

60

(0.9)

34

(5.1)

59

(0.9)

47

(3.2)

23

(1.3)

Spain

56

(0.9)

44

(4.6)

55

(0.9)

42

(2.6)

24

(1.4)

Sweden

72

(0.9)

59

(3.2)

71

(0.8)

52

(4.9)

36

(2.4)

Turkey2

35

(1.4)

c

c

35

(1.4)

27

(3.6)

11

(0.7)

United States

68

(1.2)

57

(4.7)

68

(1.2)

47

(3.2)

25

(1.8)

Flemish Comm. (Belgium)

56

(0.9)

43

(5.2)

56

(0.9)

52

(7.3)

20

(1.5)

England (UK)

65

(1.1)

65

(4.2)

65

(1.1)

49

(4.5)

20

(1.6)

Northern Ireland (UK)

61

(1.2)

53

(6.0)

61

(1.2)

46

(6.6)

14

(1.2)

OECD average

58

(0.2)

52

(0.9)

58

(0.2)

43

(0.8)

21

(0.3)

Countries

Partners

Economies

Lithuania2

43

(1.0)

c

c

43

(1.0)

14

(2.3)

8

(1.2)

Russian Federation*

24

(1.8)

c

c

24

(1.8)

23

(3.6)

9

(1.3)

Note: Additional columns showing data for participation of unemployed and inactive adults are available for consultation on line (see StatLink below).
1. Age at arrival in the country is not taken into account for the disaggregation between native- and foreign-born adults. Thus, the two categories presented are
native-born adults and foreign-born adults.
2. Reference year is 2015, for all other countries and economies the reference year is 2012.
* See note on data for the Russian Federation in the Source section.
Source: OECD (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933802836

Education at a Glance 2018: OECD Indicators   © OECD 2018

145

A7

chapter A The Output of Educational Institutions and the Impact of Learning
Under embargo until 11/09/2018 at 11.00am CEST
Table A7.3. Participation of native- and foreign-born adults in formal and/or non-formal education,

A7

by educational attainment (2012 or 2015)

OECD

Survey of Adult Skills (PIAAC), 25-64 year-olds
Participation of adults
with below upper
secondary education

Participation of adults
with upper secondary
or post-secondary
non‑tertiary education

Native-born adults
and foreign-born adults
who arrived in the
country by the age of 25
%
S.E.

Native-born adults
and foreign-born adults
who arrived in the
country by the age of 25
%
S.E.

Participation of adults with tertiary education
Native-born adults
and foreign-born adults
who arrived in the
country by the age of 25
%
S.E.

Foreign-born adults
who arrived in the
country at 26 or older
%
S.E.

Total
%

S.E.

(1)

(2)

(7)

(8)

(13)

(14)

(15)

(16)

(17)

(18)

Australia1

35

(1.8)

53

(1.3)

79

(1.2)

72

(1.7)

76

(1.1)

Austria

26

(2.0)

49

(0.9)

73

(1.4)

53

(5.8)

71

(1.5)

Canada

26

(1.3)

52

(0.9)

73

(0.9)

59

(1.9)

70

(0.8)

Chile2

25

(1.8)

46

(2.1)

74

(1.4)

c

c

74

(1.5)

Czech Republic

19

(2.5)

48

(1.4)

72

(2.5)

c

c

71

(2.6)

Denmark

44

(2.0)

62

(1.1)

83

(0.8)

67

(2.9)

82

(0.7)

Estonia

28

(1.4)

43

(1.0)

71

(1.0)

61

(5.4)

70

(1.0)

Finland

32

(2.2)

62

(1.0)

82

(0.9)

c

c

81

(0.9)

France

18

(1.0)

33

(1.0)

58

(1.1)

38

(4.8)

56

(1.1)

Germany

22

(2.6)

48

(1.5)

72

(1.4)

49

(5.8)

71

(1.3)

Greece2

7

(1.2)

18

(1.1)

41

(1.7)

c

c

41

(1.7)

Ireland

29

(1.5)

47

(1.2)

74

(1.2)

66

(2.6)

72

(1.1)

Israel2

23

(2.0)

45

(1.4)

71

(1.1)

44

(4.4)

68

(1.1)

Italy

12

(1.2)

32

(1.4)

59

(2.2)

c

c

59

(2.1)

Japan1

22

(2.2)

32

(1.2)

56

(1.1)

c

c

56

(1.1)

Korea

21

(1.3)

43

(1.3)

71

(1.1)

c

c

71

(1.1)
(0.9)

Countries

Netherlands

42

(1.3)

65

(1.3)

83

(0.9)

c

c

82

New Zealand2

49

(1.7)

65

(1.3)

79

(1.2)

75

(2.6)

78

(1.1)

Norway

40

(1.9)

62

(1.5)

79

(0.9)

70

(3.9)

78

(0.9)

Poland1

14

(1.9)

24

(1.0)

67

(1.5)

c

c

67

(1.5)

Slovak Republic

6

(0.9)

30

(1.1)

62

(1.5)

c

c

62

(1.5)

Slovenia2

19

(1.5)

46

(1.1)

76

(1.3)

c

c

76

(1.3)

Spain

28

(1.0)

49

(2.1)

72

(1.2)

56

(5.3)

71

(1.2)

Sweden

44

(2.3)

65

(1.1)

82

(1.2)

71

(3.8)

81

(1.1)

Turkey2

14

(0.7)

31

(2.0)

53

(1.8)

c

c

53

(1.8)

United States

28

(2.4)

50

(1.6)

79

(1.1)

68

(5.6)

79

(1.2)

Flemish Comm. (Belgium)

20

(1.8)

41

(1.3)

70

(1.2)

59

(6.4)

69

(1.2)

England (UK)

33

(1.6)

54

(1.5)

73

(1.2)

66

(4.8)

72

(1.3)

Northern Ireland (UK)

23

(1.5)

52

(1.9)

72

(1.6)

c

c

72

(1.5)

OECD average

26

(0.3)

46

(0.3)

71

(0.3)

61

(1.1)

70

(0.2)

Lithuania2

10

(2.3)

22

(1.1)

65

(1.5)

c

c

65

(1.5)

Russian Federation*

6

(3.0)

11

(2.0)

25

(1.9)

c

c

24

(1.8)

Partners

Economies

Note: Additional columns showing data for participation of adults with below upper secondary education and for adults with upper secondary or post-secondary
non-tertiary education are available for consultation on line (see StatLink below). Data from the Survay of Adult Skills (PIAAC) are based on ISCED-97. See Definitions
section for more information.
1. Age at arrival in the country is not taken into account for the disaggregation between native- and foreign-born adults. Thus, the two categories presented are
native-born adults and foreign-born adults.
2. Reference year is 2015, for all other countries and economies the reference year is 2012.
* See note on data for the Russian Federation in the Source section.
Source: OECD (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933802855

146 Education at a Glance 2018: OECD Indicators   © OECD 2018

Under embargo until 11/09/2018 at 11.00am CEST

Chapter

B

Access to Education,
Participation
and Progression

Indicator B1 Who participates in education?
1 2 https://doi.org/10.1787/888933802969

Indicator B2 How do early childhood education systems differ around the world?
1 2 https://doi.org/10.1787/888933803121

Indicator B3 Who is expected to graduate from upper secondary education?
1 2 https://doi.org/10.1787/888933803330

Indicator B4 Who is expected to enter tertiary education?
1 2 https://doi.org/10.1787/888933803482

Indicator B5 Who is expected to graduate from tertiary education?
1 2 https://doi.org/10.1787/888933803615

Indicator B6 What is the profile of internationally mobile students?
1 2 https://doi.org/10.1787/888933803748

Indicator B7 Is participation and progression through tertiary education equitable?
1 2 https://doi.org/10.1787/888933803900

Education at a Glance 2018: OECD Indicators   © OECD 2018

147

Under embargo until 11/09/2018 at 11.00am CEST

WHO PARTICIPATES IN EDUCATION?
INDICATOR B1

• On average across OECD countries, at least 90% of the population was enrolled in education
from age 4 to 17 in 2016, a wider age range than compulsory education (on average age 6-16).
The transition to the labour market or to tertiary education typically occurs between 17 and 20.

• In 2016, 85% of 15-19 year-olds were enrolled in education on average across OECD countries.
Enrolment rates for 15-year-olds and 16-year-olds were above 95% for almost all OECD countries,
but they drop to 63% for 19-year-olds and 54% for 20-year-olds.

• Repeaters represent 2% of students enrolled in general programmes in lower secondary education
and 4% in upper secondary education. On average across OECD countries with available data, boys
are more likely to repeat a grade than girls.

Figure B1.1. Enrolment rate transition from age 16 to age 20 (2016)
Students in full-time and part-time programmes in both public and private institutions
100
90
80
70
60
50
40
30
20
10
0

Age 16

Age 17

Age 18

Age 19

Age 20

Australia
Ireland
Lithuania
Sweden
Saudi Arabia
United Kingdom
Canada1
Netherlands
New Zealand1
Portugal
Belgium
United States
Czech Republic
Slovenia
Estonia
Latvia
Japan
Israel
Iceland
Korea
Finland
Spain
EU22 average
Poland
Germany
OECD average
Norway
Denmark
France
Italy
Hungary
Chile
Switzerland
Slovak Republic
Greece
Argentina
Luxembourg
Russian Federation
Austria
Brazil
Turkey
Colombia
Mexico

%

1. Excludes post-secondary non-tertiary education.
Countries are ranked in descending order of enrolment rates at age 16.
Source: OECD (2018), Table B1.2. See Source section at the end of this indicator for more information and Annex 3 for notes
(http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933803045

Context
Paths through the education system can be diverse, both across countries and for different individuals
within the same country. Experiences in primary and lower secondary are probably the most similar
across countries. At these levels, education is usually compulsory and not very differentiated as pupils
progress through primary and lower secondary education. But as people have different abilities, needs
and preferences, most education systems try to offer different types of education programmes and
modes of participation, especially at the more advanced levels of education (upper secondary and
beyond) and for adults.
Ensuring that people have suitable opportunities to attain adequate levels of education is a critical
challenge and depends on their capacity to progress through the different levels of an educational
system. Successful completion of upper secondary programmes is vital to address equity issues
(see Indicator A9 in Education at a Glance 2017 [OECD, 2017[1]]), but graduation rates still vary widely
among OECD countries (see Indicator B3). Developing and strengthening both general and vocational
education (see Definitions section at the end of this indicator) at upper secondary level can make
education more inclusive and appealing to individuals with different preferences and inclinations.

148 Education at a Glance 2018: OECD Indicators   © OECD 2018

Under embargo until 11/09/2018 at 11.00am CEST
In many education systems, vocational education and training (VET) enables some adults to reintegrate
into a learning environment and develop skills that will increase their employability. In addition,
VET programmes are often chosen by students who found it difficult to progress through earlier levels
of education and are thus more at risk of not completing upper secondary education (OECD, 2017[1]).
A strong upper secondary system, therefore, ensures flexible pathways for students to either pursue
higher education or enter directly into the labour market.

INDICATOR B1

Other findings

• Across the OECD, at least 90% of students can expect to be in education for an average duration of
14 years, ranging from 10 years in the Slovak Republic and Turkey to 17 years in Norway.

• Young adults spend more years studying: between 2005 and 2016, the enrolment of 20-24 year‑olds
in education increased by 6 percentage points on average across OECD countries with available
data for both years.

• The share of part-time enrolment increases with higher levels of education and with the average age
of students enrolled. On average across OECD countries, part-time students represented 20% of
enrolment in tertiary education in 2016. The share of part-time students increases to 35% among
students age 25 or older and to 44% among students age 30 or older.

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Analysis

B1

Compulsory education
In OECD countries, compulsory education typically begins with primary education starting at age 6, earlier in about
one-third of OECD and partner countries and later (at age 7) in Estonia, Finland, Indonesia, the Russian Federation,
South Africa and Sweden. In addition, compulsory education ends with completion or partial completion of upper
secondary education at an age ranging from 14 in Korea and Slovenia to 18 in Belgium, Chile, Germany, the Netherlands
and Portugal. Although compulsory education goes from age 6 to 16 on average across the OECD, the enrolment rate is
high in a wider age range, and at least 90% of the population is enrolled for 14 years, from age 4 to age 17, on average.
The age interval is generally shorter for OECD partner countries, and full enrolment (defined in this indicator as
enrolment rates exceeding 90%) can be as long as three years, as in South Africa, or four years, as in Colombia.
In more than two-thirds of OECD countries, the enrolment rate of 3-year-olds and 4-year-olds in education
exceeded 90% in 2016 (full enrolment). Enrolment at even earlier ages is relatively common in some countries, with
Denmark, Iceland and Norway achieving full enrolment for 2-year-olds (see also Indicator B2). In other countries,
full enrolment is achieved for children between age 5 and age 6, except in the Slovak Republic where full enrolment
is achieved at age 7. Across most OECD countries, full enrolment ends when students are around 17 or 18 years old,
but it ends substantially earlier in Mexico (age 14), Austria and Turkey (both at age 15). There is no country in which
more than 90% of 19-year-olds are enrolled in education.
In all OECD countries, compulsory education comprises primary and lower secondary programmes. In most
countries, compulsory education also covers, at least partially, upper secondary education, depending on the
theoretical age ranges associated with the different levels of education in each country. In OECD countries, there is
nearly universal coverage of basic education, as enrolment rates among 5-14 year-olds attained or exceeded 95% in
all OECD countries except the Slovak Republic (93%). Enrolment of 5-14 year-olds is nearly universal among OECD
partner countries, except in Colombia (87%), Costa Rica (93%) and South Africa (84%).
Profile of students in secondary education
Lower secondary education programmes are typically designed to build on the learning outcomes from primary
education and usually aim to lay the foundation for lifelong learning and human development upon which further
education would be based. Programmes at this level are usually organised to let students transition to a more subjectoriented curriculum, introducing theoretical concepts across a broad range of subjects. Programmes classified at
this level may be referred to as secondary (stage one or lower grades), junior secondary school, middle school or
junior high school. The duration of lower secondary educational programmes ranges from a minimum of two years
in Belgium to five years in the Slovak Republic and up to six years in Germany.
Upper secondary education is typically designed to complete secondary education in preparation for tertiary
education or to provide skills to enter the labour market, or both. Programmes at this level offer students more varied,
specialised and in-depth instruction than at lower secondary level. Students typically enter this level between age 14
and age 16, and these programmes usually end 12 or 13 years after the beginning of primary school. Programmes
classified at this level may be referred to as secondary school (stage two or upper grades), senior secondary school
or (senior) high school. Lower and upper secondary education includes second-chance programmes, literacy
programmes, adult education and continuing education. The length of upper secondary education varies from two
years in Australia, Ireland, Lithuania and the Russian Federation to five years in Italy.
In recent years, countries have increased the diversity of their upper secondary programmes. This diversification
is both a response to the growing demand for upper secondary education and a result of changes in curricula and
labour-market needs. Curricula have gradually evolved from separating general and vocational programmes to
offering more comprehensive programmes that include both types of learning, leading to more flexible pathways
into further education or the labour market.
The structure of secondary education depends on several factors, including the entry age, the length of the
programmes and the existence of vocational and combined school- and work-based programmes, as well as the
extent to which the programmes allow adult enrolment for those enrolled after entry into the labour market
(e.g. second-chance programmes, literacy programmes, adult education and continuing education).
Across OECD countries, the average age of enrolment in lower secondary education is 14, although it varies from
12 in Austria and Italy to 17 in Mexico and 19 in Belgium. The average age of enrolment at upper secondary level
reaches 19, but at this level, the average age varies more than at lower levels, due to the greater variety of programmes,
including those more oriented towards the needs of the labour market, and whether they cater to adult learners.

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In fact, the average age of enrolment varies from 16 in Israel, Italy, Japan, Korea, Mexico, the Russian Federation
and the United States to 25 in Finland. Denmark, Finland, Iceland and New Zealand have the largest increase in the
average age of enrolment from lower to upper secondary programmes (above seven years).
Public institutions tend to dominate the overall share of enrolments across education levels, although their
share tends to decrease with increasing levels of education. On average across OECD countries in 2016, around
85% of students in lower secondary education were enrolled in public institutions. Among all OECD and partner
countries, only Belgium, Chile and the United Kingdom have more than 50% of students enrolled at this level
in private institutions, which include a large percentage of students enrolled in government-dependent private
institutions. At upper secondary level, the share of enrolment in public institutions drops to 80% on average
across OECD countries, with a decrease by over 20 percentage points in Iceland, Japan and Korea, where private
institutions play a more prominent role at this level. By contrast, a larger share of students are enrolled in public
institutions at upper secondary level than at lower secondary level in Denmark, Israel and Spain.
Vocational education and training programmes
Vocational education and training programmes are seen to be effective for developing skills to ensure a smooth and
successful transition into the labour market. Countries with well-established VET and apprenticeship programmes
have been more effective in holding the line on youth unemployment (see Indicator A3). At the same time, some
countries consider vocational education a less attractive option than academic education, and some research
suggests that participation in vocational education increases the risk of unemployment at later ages (Hanushek,
Woessmann and Zhang, 2011[2]).
Vocational programmes in OECD countries offer different combinations of vocational studies along with apprenticeship
programmes. Upper secondary students in many education systems can enrol in vocational programmes, but some
OECD countries delay vocational training until students graduate from upper secondary education. For instance,
while vocational programmes are offered as upper secondary education in Austria, Germany, Hungary and Spain,
similar programmes are typically offered as post-secondary education in Canada.
On average across OECD countries, 56% of students in upper secondary education were enrolled in general programmes
in 2016, while 44% were enrolled in vocational upper secondary programmes (Table B1.3). The distribution of
secondary students enrolled in vocational versus general programmes largely depends on the education programmes
available, as well as the labour-market outcomes of these programmes. In about one-third of the countries with
available data, a larger share of upper secondary students are enrolled in vocational programmes than in general
programmes, with at least 70% in the Czech Republic, Finland and Slovenia. In contrast, in Argentina and Ireland,
where vocational programmes are not offered at all at this level, as well as in Brazil, Canada and India, more than
90% of upper secondary students are enrolled in general programmes (Table B1.3).
In combined school- and work-based programmes, between 10% and 75% of the curriculum is presented in the
school environment or through distance education. These include apprenticeship programmes that involve
concurrent school-based and work-based training, as well as programmes that involve alternating periods of
attendance at educational institutions and participation in work-based training (see Definitions section at the end
of this indicator). On average across the OECD, 11% of students in upper secondary education are enrolled in this
type of programme, although they are offered in and data are available for only 21 OECD countries. In Hungary and
Latvia, all vocational programmes are combined school- and work-based programmes.
Repeaters
Completing educational programmes at different ISCED levels over their lifetime allows individuals to progress
to higher levels of education and empowers them throughout life to access and have better opportunities in the
labour market. At the same time, dropping out or repeating a grade can lead to premature withdrawal from school
and lower employability of school leavers, causing a loss for educational systems in terms of social and financial
resources, such as students’ learning, school buildings’ usage and teachers’ work time (UNESCO International
Bureau of Education, 1970[3]).
Equity in education can be related to the policies that schools employ to sort and select students. Grade repetition,
the practice of retaining students in the same grade, is used to give struggling students more time to master gradeappropriate content before moving on to the next grade (and prevent them from dropping out). Even if research
finds that grade repetition can be ineffective in enhancing the achievement of low performers in the short run
(OECD, 2016[4]), early retention may lead to better outcomes than late retention and retained students may catch
up after several years (Fruehwirth, Navarro and Takahashi, 2016[5]).
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The way educational systems cope with students who repeat grades may differ to a large extent between countries
and within the same countries, depending on educational levels, programmes, rural or urban areas, socio-economic
conditions or other factors. In most countries, repeaters tend to be concentrated in the last two years before
graduation, while in some others the distribution over different grades is more even. In a smaller number of
countries, repeating grades is restricted by law and school regulations, and the concept of repeating does not even
exist, especially at lower educational levels. This is the case for lower secondary education programmes in Norway,
for upper secondary programmes in Finland, and for both types of programmes in the United Kingdom. In Canada,
lower and upper secondary school students generally repeat only courses that they have failed and not whole grades,
while primary students are typically not made to repeat grades.
The share of repeaters varies to a large extent by country and by educational level. It reaches 2% in lower secondary
general programmes (this excludes adult learners) and increases with higher levels of education. Grade repetition
is relatively uncommon in lower secondary general programmes and is below 5% in most countries. However, the
share of repeaters exceeds 10% in Argentina, Costa Rica, Luxembourg and Spain (Figure B1.2).

Figure B1.2. Share of repeaters and share of boys in the number of repeaters
in secondary education (2016)
General programmes only
Lower secondary
%

India

Russian Federation

Ireland

Korea

South Africa1

India

Russian Federation

Ireland

Korea

South Africa1

Mexico

Finland

Lithuania
Lithuania

Finland

Slovenia
Slovenia

Mexico

Denmark

Czech Republic

Denmark

Czech Republic

Israel

Switzerland

Saudi Arabia

France

Estonia

Hungary

Slovak Republic

Latvia

Turkey

Poland

Austria

OECD average

Germany

Italy

EU22 average

Colombia

Chile

Greece

Belgium

Luxembourg

Argentina1

Spain

%

Switzerland

Israel

Saudi Arabia

France

Estonia

Hungary

Slovak Republic

Latvia

Turkey

Austria

Poland

OECD average

Germany

Italy

EU22 average

Colombia

Chile

Greece

Belgium

Luxembourg

Argentina

1

Share of boys in the number of repeaters

Spain

80
70
60
50
40
30
20
10
0

Upper secondary

Share of repeaters

Costa Rica

18
16
14
12
10
8
6
4
2
0

Costa Rica

B1

Socio-economically disadvantaged students with an immigrant background and boys are more likely to repeat
grades than advantaged students (OECD, 2016[4]) and this could also lead to persisting socio-economic inequalities.
Completion rates are usually lower for students with a disadvantaged background (e.g. lower educational status of
parents, first-generation immigrants) (OECD, 2017[1]) (OECD, 2016[6]).

1. Year of reference 2015.
Countries are ranked in descending order of the share of repeaters in lower secondary education.
Source: OECD (2018), Table B1.3. See Source section at the end of this indicator for more information and Annex 3 for notes (http://dx.doi.
org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933803064

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Grade repetition is more common in upper secondary education, especially in the Czech Republic, Luxembourg,
Mexico and South Africa, where repeaters represent at least 10% of the enrolled students, but also in Belgium, Chile,
Costa Rica (all three countries at 8%) and Italy (7%).
The share of repeaters in upper secondary education is 4% on average across OECD countries, 2 percentage points
higher than for lower secondary education. The largest increase in the share of repeaters at upper secondary level
is observed in the Czech Republic (10 percentage points higher than for lower secondary programmes) and Mexico
(13 percentage points higher). Conversely, the share of repeaters is lower at upper than at lower secondary level in
Argentina, Colombia, Costa Rica, Greece and the Slovak Republic.
Box B1.1. Over-age students
Over-age students are those who are at least two years older than the intended age for each grade. The number
and share of over-age students are a complementary metric to those of repeaters: over-age students in the last
grade are those who are likely to start the next educational level with at least a two-year delay compared to
the intended age. The number of repeaters and over-age students are strictly linked, as in most countries the
main reason for a high share of over-age students is the accumulation over different grades of students who
have repeated at least one year (i.e. the marginal increase in the number of over-age students at each grade
is correlated with the number of repeaters at that grade). Over-age attendance as a result of grade repetition
and/or late entry risks reducing participation in education (UNESCO, 2016[7]).
It is relatively common in partner countries such as Argentina, Brazil, Colombia, Costa Rica, Saudi Arabia
and South Africa, but also in Chile and Hungary, to have a high share of over-age enrolment in the last
grade of primary school, especially in Brazil, Colombia and South Africa, where over-age students represent
more than 10% of pupils enrolled. For all other countries with available data, this share ranges between 0%
and 5% (Figure B1.a). In the last grade of lower secondary education, this share increases for most countries
and doubles on average across the OECD (from 2% to 4%). The share of over-age students increases most
from the last grade of primary education to the last grade of lower secondary education for Argentina
(by 10 percentage points), Costa Rica (by 14 percentage points), Luxembourg (by 12 percentage points)
and Spain (by 8 percentage points), while it decreases substantially for Hungary (by 7 percentage points),
highlighting a high rate of dropout and a drop in enrolment rates for 15-19 year-olds.

Figure B1.a. Share of over-age students in the last grade of primary
and lower secondary education (2016)
Primary

%

Lower secondary (general programmes)

25
20
15
10

Czech Republic

France

Greece

Russian Federation

Ireland

New Zealand

Korea

Sweden

Australia

Switzerland

Israel

Denmark

Italy

Spain

Estonia

Slovenia

Turkey

Belgium

EU22 average

Latvia

Luxembourg

Lithuania

OECD average

Mexico

Indonesia

Austria

United States

Saudi Arabia

Argentina1

Chile

Costa Rica

Brazil

Hungary

Colombia

0

South Africa1

5

1. Year of reference 2015.
Countries are ranked in descending order of their share of over-age students in primary education.
Source: OECD (2018), Table B1.3 and data available on line. See Source section at the end of this indicator for more information and Annex 3
for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933803102

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On average across OECD countries with available data, boys are more likely to repeat a grade than girls and represent
60% of the number of repeaters in lower secondary education and 58% in upper secondary education (Figure B1.2).
This is true in lower secondary education for all the countries, with the exception of Turkey, where girls are overrepresented in the number of repeaters (only 42% are boys). In Indonesia, Israel, Italy, Latvia, Lithuania, Mexico,
Poland and Slovenia, two out of three repeaters at lower secondary level are boys. This is also the case in upper
secondary education for Israel, Poland, the Slovak Republic and Turkey, while grade repetition is more common for
girls in Estonia.
Participation of 15-19 year-olds in education
On average across OECD countries, 85% of the population aged 15-19 are enrolled in education. This age range
corresponds to the end of compulsory education and upper secondary programmes in many countries. By age 19 or 20,
students in most OECD countries transition to tertiary education or leave school to enter the labour market. While
enrolment is nearly universal at age 15 and 16 (above 90% for most countries), enrolment rates start dropping at later
ages. The countries that experience the largest decrease between age 16 and age 20 are Israel, Luxembourg and Sweden.
In 2016, enrolment rates among 15-16 year-olds (i.e. those typically in upper secondary programmes) reached at
least 95% on average across the OECD. At age 17, 92% of individuals are enrolled in education on average across
the OECD, reaching 99% or more in Ireland, and Sweden, but also in partner countries Lithuania and Saudi Arabia.
By contrast, fewer than 80% of 17-year-olds are enrolled in education in Brazil, Costa Rica, Indonesia, Mexico and
Turkey, with the lowest rate in Colombia (52%).
Enrolment patterns start dropping significantly at age 18: 76% of 18-year-olds are enrolled in secondary, postsecondary non-tertiary, or tertiary education, on average across OECD countries. Declines in enrolment for this
age group coincide with the end of upper secondary education. The drop in enrolment between age 17 and age 18
is at least 25 percentage points in Brazil, Chile, Greece, Korea, New Zealand and Turkey. By the time students reach
age 19, enrolment rates decrease to 63% on average across OECD countries (Table B1.2). In some countries, the
enrolment rate follows a different pattern and increases after the age of 18: for example, in Greece the enrolment
rate increases from 64% at the age of 18 to 74% at the age of 20.
The share of students enrolled in each education level and at each age is illustrative of the different educational
systems and pathways in countries. As students get older, they move on to higher educational levels or types
of programmes, and the enrolment rate in upper secondary education (combined general and vocational)
decreases. Depending on the structure of the educational system, students across the OECD may start enrolling
in post‑secondary non-tertiary or tertiary education from the age of 17. However this is still the exception for
this age group, with 90% of 17-year-olds still enrolled in secondary education, on average across OECD countries.
Students start diversifying their pathways significantly from age 18, although the age of transition between upper
secondary and tertiary education varies substantially among countries. While at least 90% of 18-year-olds are
still enrolled in upper secondary in Finland, Norway, Poland, Slovenia and Sweden, more than 60% of students
in Korea and the Russian Federation are already starting their tertiary education at that age. On average across
OECD countries, 26% of 19-year-olds are still enrolled in secondary education. However, in the Czech Republic,
Denmark, Iceland, Luxembourg, the Netherlands, Poland and Switzerland, more than 40% of 19-year-olds are still
enrolled in secondary education. These high shares may partly be explained by the structure of the education system
and the strength of the labour opportunities offered by vocational upper secondary programmes in these countries,
making them more attractive than tertiary education. Enrolment of 19-year-olds in tertiary education averages
34% across OECD countries, ranging from 2% in Luxembourg (the low share is due in large part to the high number
of students studying abroad) and 3% in Iceland to 73% in Korea.
Enrolment of 18-, 19- and 20-year-olds has been increasing since 2010, although the extent of the increase for each
age varies across countries. Among OECD and partner countries with available data, Australia has had the most
striking increase in enrolment of 18-year-olds since 2010, with a rise of 11 percentage points. Other countries have
seen a more moderate increase. Enrolment of 18-year-olds has increased by 6 to 9 percentage points in Belgium,
Chile, Mexico, and Spain in the past decade, but the current enrolment rate in Chile and Mexico is still below the
OECD average of 76%. While most countries with available data have seen enrolment levels of 18-year-olds rise since
2010, some countries have witnessed a decline: of 8 percentage points in Germany (partly because of the recent
inflow of refugees which increased the population of this age), 10 percentage points in Hungary and 6 percentage
points in Lithuania. The enrolment rate has increased by at least 11 percentage points in Australia (for 19- and
20-year-olds), Estonia (for 20-year-olds) and Spain (for 19- and 20-year-olds). In Poland, enrolment has increased
by at least 35 percentage points for both ages (Table B1.2).

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Post-secondary non-tertiary education programmes (see Reader’s Guide) play a smaller role in most OECD and
partner countries. These types of programmes are not offered at all in Argentina, Chile, Costa Rica, Denmark,
Indonesia, Korea, Mexico, the Netherlands, Saudi Arabia, Slovenia, Turkey and the United Kingdom. On average
across OECD countries, 1% to 4% of young adults between age 17 and age 19 are enrolled in either general or
vocational programmes at this level. In some countries, however, enrolment at this level is more substantial.
The proportion of 19-year-olds enrolled in post-secondary non-tertiary programmes is 11% in Germany and Greece
and 17% in Hungary and Ireland (Table B1.2).
Participation of 20-29 year-olds in education
For 20-year-olds, the enrolment rate drops to 55% on average across OECD countries, as students start to enter the
labour market. Rates vary from 40% or less in Luxembourg, Mexico and most OECD partner countries to 70% or
higher in Australia, Belgium, Greece, the Netherlands and Slovenia. Levels of enrolment at this age depend on
the structure of the education system and the labour-market outcomes expected from the programmes. More
than half of the enrolled 20-year-olds are in secondary or post-secondary non-tertiary programmes in Denmark,
Germany, Iceland, Luxembourg, Switzerland and South Africa, while tertiary education constitutes the typical level
of enrolment of most 20-year-olds in other OECD countries, and it represents over 90% of enrolment in Chile,
Korea, the Russian Federation and the United States.
The sharpest decline in enrolment across age groups occurs between the age groups 20-24 and 25-29, on average
across OECD and partner countries. In OECD countries in 2016, an average of 42% of 20-24 year-olds, but only
16% of 25-29 year-olds, were enrolled in upper secondary, post-secondary non-tertiary education or tertiary
education programmes. However, the enrolment rate of 20-24 year-olds in education increased over time, as did
that of other age groups. Among the countries with available data, the largest increases between 2005 and 2016
were in Australia, Poland and Spain (14 percentage points or more). Other countries, however, witnessed a decrease
in enrolment rates over this 11-year span: Finland, Hungary, Lithuania and New Zealand experienced a drop of at
least 3 percentage points (Table B1.1).
Enrolment for 25-29 year-olds follows the same pattern of increase as other groups: on average across OECD countries,
the enrolment rate in 2016 was 3 percentage points higher than its value in 2010. Australia and Poland experienced the
sharpest increase (8 percentage points or more), while enrolment decreased in other countries, including New Zealand
and the Russian Federation, where it dropped by at least 5 percentage points in the period 2005-16.
Participation of adults over 30 years of age
It is crucial to ensure that adults have access to organised learning opportunities beyond initial formal education.
Such opportunities can help adults who need to adapt to changes throughout their working careers, those who
want to enter the labour force but feel that they lack the necessary qualifications, or those who feel they need
to improve their skills and knowledge to participate more actively in social life. Adult education aims to improve
people’s technical or professional qualifications, develop their abilities and enrich their knowledge. Participants
in adult education may or may not complete a level of formal education, but they stand to gain from acquiring or
updating knowledge, skills and competencies. Adult learning takes many forms, including formal and non-formal
education, on-the-job training and informal education. This section deals with formal educational programmes
(i.e. institutional, intentional and planned education provided by public organisations and recognised private
bodies). A broader view of adult education, including non-formal education, is found in Indicator A7.
For adults over age 30, enrolment in formal educational programmes can be still considerable. On average across
OECD countries, only 7% of adults between age 30 and age 39 are enrolled in education, but the rates can be as high as
19% in Australia and 16% in Finland. Since 2005, enrolment rates for this age group have been increasing on average
across OECD countries, with a maximum increase of 6 percentage points in Australia. In other countries, however,
enrolment in this age group has been decreasing, for example in New Zealand and Slovenia (by 4 percentage points).
The enrolment rate of adults over age 40 was 1% on average across the OECD countries with available data in
2016. However, the rates are still relatively high in Australia (6%) and in Belgium, Finland, Iceland, New Zealand,
Sweden and the United Kingdom (all six countries at 3%). The higher enrolment rates for these age groups in certain
countries may be explained by more part-time enrolments or the prevalence of lifelong learning programmes. For
instance, credit-based systems in Sweden allow adults to study selected parts of a programme in formal education
as a way to upgrade their skills in specific areas. Students may select their own combination of freestanding courses
and if these combinations meet stipulated requirements, a qualification may be awarded.
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Figure B1.3. Part-time enrolment in tertiary education, by age group (2016)
Percentage of students enrolled part time

Greece

Czech Republic

Japan

Portugal

Estonia

Denmark

Israel

Germany

Ireland

Netherlands

EU22 average

Canada1

Slovenia

Luxembourg

Lithuania

30 and above

OECD average

Slovak Republic

United Kingdom

25 and above

Spain

Switzerland

Latvia

Iceland

Hungary

Poland

Norway

United States

Russian Federation

Finland

Australia

Sweden

Belgium

All ages

%

100
90
80
70
60
50
40
30
20
10
0

New Zealand

B1

1. Excludes enrolment in short-cycle tertiary programmes in private institutions.
Countries are ranked in descending order of their share of part-time enrolment in tertiary education for all ages.
Source: OECD (2018), Education at a Glance Database, http://stats.oecd.org/. See Source section at the end of this indicator for more information
and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933803083

The share of part-time enrolment increases with higher levels of education and with the average age of students
enrolled. On average across OECD countries, part-time students represented 20% of enrolment in tertiary education
in 2016 (Figure B1.3), compared to 9% in upper secondary education. This share is higher in many countries and can
exceed 40% in Australia, New Zealand and Sweden.
The share of part-time students increases to 35%, even when students younger than 25 are excluded, reaching
two‑thirds of total enrolment or more in Hungary, New Zealand and the Russian Federation. Part-time enrolment is
even more common among students age 30 or older and reaches 44% across all OECD countries with available data.
The countries for which the share of part-time enrolment increases the most with age (from all ages to 30‑year‑olds
and above) are Hungary, the Netherlands, the Slovak Republic and Slovenia, with increases of over 50 percentage
points. In no country does part-time enrolment decrease with age.
Subnational variations in enrolment
Subnational variation in enrolment patterns reveals the equality of access to education across a country, as well as
labour-market opportunities and perceptions on lifelong learning for levels beyond compulsory education. Between
the ages of 5-14 (corresponding to compulsory education in many countries) and 15-19 (when students transition to
the labour market or to tertiary education), subnational differences are lower than for other ages, with coefficients
of variation across regions lower than 20% in all countries with subnational data.
On average across all countries with subnational data and across age groups starting at age 5, the largest variation in
enrolment at subnational level can be observed for older age groups. While regional differences in enrolment levels
for 20-29 year-olds are lower in Belgium, Germany, Sweden and the United States, the coefficient of variation shows
considerable variations and exceeds 35% in Austria, Colombia, Korea, Slovenia and Turkey. Colombia and Turkey
have also the highest ratios between the highest and lowest enrolment levels in their regions for this age group.
Subnational disparities in enrolment increase for 30-39 year-olds. The variation is especially high in Spain and
Turkey, where the coefficient of regional variation exceeds 60%. In this age group, however, regional differences
compared to 20-29 year-olds decrease to a large extent for Slovenia. The enrolment rate for older ages (40‑year‑olds
and above) are relatively low, reaching 1% on average across OECD countries. Regional differences at this age are
still observed across countries with available data, particularly in Belgium, Germany and Italy, where the coefficient
of variation across regions increases the most for this age group.

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Definitions
The data in this indicator cover formal education programmes that represent at least the equivalent of one semester
(or one-half of a school/academic year) of full-time study and take place entirely in educational institutions or are
delivered as combined school- and work-based programmes.
Full enrolment, for the purposes of this indicator, is defined as enrolment rates exceeding 90%.
General education programmes are designed to develop learners’ general knowledge, skills and competencies, often
to prepare them for other general or vocational education programmes at the same or a higher education level. General
education does not prepare people for employment in a particular occupation, trade or class of occupations or trades.
Vocational education and training (VET) programmes prepare participants for direct entry into specific occupations
without further training. Successful completion of such programmes leads to a vocational or technical qualification
that is relevant to the labour market. Vocational programmes are further divided into two categories (school-based
programmes and combined school- and work-based programmes), determined by the amount of training provided
in school as opposed to the workplace. The degree to which a programme has a vocational or general orientation
does not necessarily determine whether participants have access to tertiary education. In several OECD countries,
vocationally-oriented programmes are designed to prepare students for further study at the tertiary level, and in
some countries general programmes do not always provide direct access to further education.
In combined school- and work-based programmes, between 10% and 75% of the curriculum is presented in the
school environment or through distance education. Therefore, the work-based component of a school- and work‑based
programme would be a minimum of 25% and a maximum of 90%. These programmes can be organised in conjunction
with education authorities or institutions. They include apprenticeship programmes that involve concurrent schoolbased and work-based training, as well as programmes that involve alternating periods of attendance at educational
institutions and participation in work-based training (sometimes referred to as “sandwich” programmes).
Private institutions are institutions that receive more than 50% of their core funding from government agencies,
if they are controlled and managed by a non-governmental organisation (e.g. a church, trade union or business
enterprise), or if their governing board consists mostly of members not selected by a public agency.
Repeaters are those students who enrol in the same grade for a second or further time. Students who participate in
a second or further education programme at the same level of education after having successfully completed a first
programme are not regarded as repeaters. Repeaters include re-entrants to the same programme.
Over-age students are defined as those at least two years older than each grade’s intended age. Over-age students
are defined according to each country’s education system keeping into account the different starting age for each
grade. Students above the typical age are defined as those enrolled in upper secondary education that are 20 years
old or older, regardless of the starting and ending ages at this level.
A full-time student as someone who is enrolled in an education programme whose intended study load amounts to
at least 75% of the normal full-time annual study load. A part-time student is one who is enrolled in an education
programme whose intended study load is less than 75% of the normal full-time annual study load.

Methodology
Except where otherwise noted, figures are based on head counts, because of the difficulty for some countries to
quantify part-time study. Net enrolment rates are calculated by dividing the number of students of a particular
age group enrolled in all levels of education by the size of the population of that age group. While enrolment and
population figures refer to the same period in most cases, mismatches may occur due to data availability in some
countries resulting in enrolment rates exceeding 100%.
The share of repeaters is the number of repeaters in a grade and year compared to the number of total students
enrolled in the same grade and year. This indicator must therefore be interpreted with caution, as repeaters are not
compared to their grade and year of origin but to the grade and year where they are re-enrolled.
For more information, please see the OECD Handbook for Internationally Comparative Education Statistics 2018:
Concepts, Standards, Definitions and Classifications (OECD, 2018[8]) and Annex 3 for country-specific notes (http://
dx.doi.org/10.1787/eag-2018-36-en).
Lithuania was not an OECD member at the time of preparation of this publication. Accordingly, Lithuania does not
appear in the list of OECD members and is not included in the zone aggregates.
Education at a Glance 2018: OECD Indicators   © OECD 2018

157

B1

chapter B Access to Education, Participation and Progression
Under embargo until 11/09/2018 at 11.00am CEST

Source

B1

Data refer to the academic year 2015/16 and are based on the UNESCO-UIS/OECD/EUROSTAT data collection on
education statistics administered by the OECD in 2017 (for details, see Annex 3 at http://dx.doi.org/10.1787/eag2018-36-en). Data from Argentina, China, Colombia, India, Indonesia, Saudi Arabia and South Africa are from the
UNESCO Institute of Statistics (UIS).
Data on subnational regions for selected indicators have been released by the OECD, with support from the
US National Centre for Education Statistics (NCES) and are currently available for 15 countries. Subnational
estimates were provided by countries using national data sources or by Eurostat based on data for Level 2 of the
Nomenclature of Territorial Units for Statistics (NUTS 2).

Note regarding data from Israel
The statistical data for Israel are supplied by and are under the responsibility of the relevant Israeli authorities. The use
of such data by the OECD is without prejudice to the status of the Golan Heights, East Jerusalem and Israeli settlements
in the West Bank under the terms of international law.

References
Fruehwirth, J., S. Navarro and Y. Takahashi (2016), “How the timing of grade retention affects outcomes: Identification [5]
and estimation of time-varying treatment effects”, Journal of Labor Economics, Vol. 34/4, pp. 979-1021, http://dx.doi.
org/10.1086/686262.
Hanushek, E., L. Woessmann and L. Zhang (2011), “General education, vocational education, and labor-market outcomes [2]
over the life-cycle”, IZA Discussion Papers, 6083, http://ftp.iza.org/dp6083.pdf (accessed on 27 April 2018).
OECD (2018), OECD Handbook for Internationally Comparative Education Statistics 2018: Concepts, Standards, Definitions [8]
and Classifications, OECD Publishing, Paris, https://doi.org/10.1787/9789264304444-en.
OECD (2017), Education at a Glance 2017 : OECD Indicators, OECD Publishing, http://dx.doi.org/10.1787/eag-2017-en.

[1]

OECD (2016), Education at a Glance 2016 : OECD Indicators, OECD Publishing, Paris, http://dx.doi.org/10.1787/eag-2016-en [6]
(accessed on 12 January 2018).
OECD (2016), PISA 2015 Results (Volume I): Excellence and Equity in Education, PISA, OECD Publishing, Paris, http://dx.doi. [4]
org/10.1787/9789264266490-en.
UNESCO (2016), “Leaving no one behind: How far on the way to universal primary and secondary education? Global [7]
number of out−of−school children and youth, 2000−2014”, UNESCO Policy Paper, 27, http://uis.unesco.org/sites/default/
files/documents/fs37-leaving-no-one-behind-how-far-on-the-way-to-universal-primary-and-secondary-education2016-en.pdf (accessed on 27 June 2018).
UNESCO International Bureau of Education (1970), Educational Trends in 1970: An International Survey, UNESCO, Paris, [3]
http://unesdoc.unesco.org/images/0000/000006/000673eo.pdf.

Indicator B1 Tables
1 2 https://doi.org/10.1787/888933802969

Table B1.1 Enrolment rates by age group (2005, 2010 and 2016)
Table B1.2 Students enrolled as a percentage of the population between the ages of 15 and 20 (2010, 2016)
Table B1.3 Profile of enrolled students (2016)
Cut-off date for the data: 18 July 2018. Any updates on data can be found on line at http://dx.doi.org/10.1787/eag-data-en. More breakdowns can
also be found at http://stats.oecd.org/, Education at a Glance Database.

158 Education at a Glance 2018: OECD Indicators   © OECD 2018

Who participates in education? – INDICATOR B1

chapter B

Under embargo until 11/09/2018 at 11.00am CEST
Table B1.1. Enrolment rates by age group (2005, 2010 and 2016)
Students in full-time and part-time programmes in both public and private institutions
2016

Ages 30 to 39

Ages 20 to 24

Ages 25 to 29

Ages 30 to 39

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

(13)

(14)

100
98
98
100
98
98
99
97
97
99
98
97
96
99
100
97
98
100
97
98
97
100
100
99
99
95
98
93
97
97
99
100
95d
98
99

91
78
93
78
81
91
86
89
87
85
86
84
84
87
93
66
83
m
87
92
76
59
93
81
87
93
89
84
93
87
87
85
71
85
83

58
34
47
33
43
41
55
40
51
36
48
52
36
46
44
20
34
m
50
44
21
25
53
36
45
50
37
33
61
49
42
39
52
34
34

30
18
14
10
16
10
32
16
31
7
21
21
10
26
12
20
11
m
9
15
6
8
18
16
18
11
10
7
13
16
27
17
29
14
15

19
6
7
4
6
3
9
7
16
2
5
8
3
12
6
6
2
m
2
6
2
4
5
10
8
3
4
2
2
5
15
4
13
10
7

6
1
3
0
1
0
1
1
3
0
0
1
1
3
2
1
0
m
0
1
0
2
1
3
2
1
1
0
0
1
3
1
2
3
2

45
33
52
36
36
39
49
44
53
34
45
m
41
m
32
24
35
m
54
44
m
19
47
42
48
11
37
m
54
37
m
34
m
27
38

19
17
17
11
13
11
27
14
31
6
17
m
11
m
9
21
11
m
10
11
m
5
12
20
19
2
14
m
16
12
m
14
m
10
15

12
5
9
5
4
4
8
6
15
1
3
m
4
m
5
5
3
m
2
5
m
2
3
12
7
1
9
m
5
4
m
4
m
6
7

44
m
42
m
m
34
m
40
55
32
41
m
38
m
32
m
33
m
46
m
m
17
m
41
46
12
34
m
50
34
m
31
m
m
32

21
m
15
m
m
10
m
14
30
7
18
m
13
m
10
m
10
m
9
m
m
5
m
21
19
3
12
m
17
11
m
13
m
m
13

13
m
8
m
m
4
m
10
13
1
2
m
6
m
4
m
3
m
2
m
m
2
m
14
7
1
4
m
6
3
m
4
m
m
6

OECD average

14

4-17

98

85

42

16

7

1

39

14

6

37

14

6

Average for countries
with available data for
all reference years

~

~

~

~

43

16

6

~

40

14

6

37

14

6

EU22 average

14

4-17

98

87

43

15

6

1

40

14

5

37

13

5

Argentina4
Brazil
China
Colombia
Costa Rica
India
Indonesia
Lithuania
Russian Federation
Saudi Arabia
South Africa4

12
11
m
4
m
m
m
14
13
11
3

5-16
4-14
m
9-12
m
m
m
5-18
5-17
6-16
7-9

100
98
m
87
93
m
m
100
96
100
84

76
69
m
59
m
m
m
94
84
m
m

40
29
m
25
m
m
m
47
33
m
25

21
14
m
12
m
m
m
13
7
m
8

m
8
m
6
m
m
m
6
3
m
2

m
2
m
2
m
m
m
1
0
m
1

m
m
m
m
m
m
m
56
m
m
m

m
m
m
m
m
m
m
16
m
m
m

m
m
m
m
m
m
m
6
m
m
m

m
m
m
m
m
m
m
49
34
m
m

m
m
m
m
m
m
m
17
13
m
m

m
m
m
m
m
m
m
6
1
m
m

G20 average

m

m

m

m

m

m

m

m

m

m

m

m

m

m

Ages 25 to 29

(3)

4-17
4-15
3-18
5-16
5-17
4-17
2-17
4-17
6-18
3-17
3-17
5-17
4-16
2-16
4-17
3-17
3-17
4-17
3-17
4-18
4-16
4-14
4-17
4-17
2-18
5-18
4-17
7-16
4-18
3-17
3-18
5-17
6-15
3-17
5-16

Ages 20 to 24

(2)

14
12
16
12
13
14
16
14
13
15
15
13
13
15
14
15
15
14
14
15
13
11
14
14
17
14
14
10
15
15
16
13
10
15
12

Ages 15 to 19

(1)

Australia
Austria
Belgium
Canada1
Chile
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel1
Italy
Japan2
Korea
Latvia
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey3
United Kingdom
United States

Ages 5 to 14

Ages 25 to 29

2005

Ages 20 to 24

2010
Age 40 and older

2016
Ages 30 to 39

OECD

Number
Age range
of years
at which
for which
at least 90% at least 90%
of the
of the
population
population
of school age of school age
are enrolled are enrolled

Partners

B1

Students as a percentage of the population of a specific age group

1. Excludes post-secondary non-tertiary education.
2. Breakdown by age not available after 15 years old.
3. The age group of 5-14 year-olds includes 15-17 year-olds in primary education.
4. Year of reference 2015.											
Source: OECD/UIS/Eurostat (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933802988

Education at a Glance 2018: OECD Indicators   © OECD 2018

159

chapter B Access to Education, Participation and Progression
Under embargo until 11/09/2018 at 11.00am CEST
Table B1.2. Students enrolled as a percentage of the population between the ages of 15 and 20

(2010, 2016)

Students enrolled in full-time and part-time programmes in both public and private institutions

B1

2016

2010

Secondary

Post-secondary
non-tertiary

Tertiary

Secondary

Post-secondary
non-tertiary

Tertiary

Secondary

Post-secondary
non-tertiary

Tertiary

All levels
of education

All levels
of education

All levels
of education

All levels
of education

Age 17 Age 18 Age 19 Age 20

Tertiary

Age 20

Post-secondary
non-tertiary

Age 19

Secondary

Age 18

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

(13)

(14)

(15)

(16)

(17)

(18)

Australia
Austria
Belgium
Canada1
Chile
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United Kingdom
United States

100
94
98
100
97
100
99
98
98
96
97
96
96
99
100
97
97
97
100
98
92
82
100
98
100
95
96
97
97
96
100
98
90
100
100

100
89
98
99
93
98
95
97
96
94
94
92
94
96
100
96
94
97
96
96
90
72
99
98
95
95
97
92
97
96
100
93
83
99
97

90
73
96
83
92
95
91
94
96
88
88
93
88
89
90
91
92
93
96
97
82
57
90
86
93
94
97
88
96
89
99
91
77
92
87

1
1
0
m
a
m
a
0
0
0
4
0
0
0
6
m
0
0
a
0
0
a
a
2
0
0
0
0
a
0
0
0
a
a
0

6
13
1
3
0
0
0
0
0
3
0
1
0
0
3
1
0
0
1
0
0
3
8
2
0
1
0
0
0
0
0
0
1
2
1

39
43
51
23
34
88
85
88
95
35
65
16
68
81
42
16
78
3
9
89
72
23
63
27
90
93
53
76
91
43
95
79
34
39
30

3
1
2
m
a
m
a
0
0
1
7
1
5
0
16
m
0
1
a
0
0
a
a
7
0
0
0
3
a
0
0
1
a
a
1

38
29
38
35
30
2
1
1
1
42
7
48
5
0
28
9
3
m
61
4
1
20
25
31
0
2
28
3
2
37
1
4
18
33
37

22
19
27
8
11
48
56
36
35
12
39
9
28
67
5
2
20
1
0
36
41
11
43
9
39
44
26
33
30
26
26
49
11
22
5

4
1
3
m
a
m
a
3
0
1
11
11
17
0
17
m
0
0
a
2
0
a
a
6
1
4
1
5
a
0
1
1
a
a
2

51
31
51
43
48
24
8
27
15
51
19
54
21
3
55
14
33
m
73
37
2
27
38
41
20
35
38
22
54
47
15
11
40
42
52

18
9
14
4
5
14
28
15
20
6
22
5
11
31
2
1
7
m
0
13
25
6
28
5
20
10
13
6
17
17
16
25
10
15
0

4
2
4
m
a
m
a
5
0
0
12
13
16
0
12
m
0
m
a
3
0
a
a
5
1
8
1
3
a
0
1
1
a
a
2

51
31
54
42
51
41
21
35
27
47
28
56
29
18
56
15
37
m
69
47
8
28
44
42
36
47
40
34
57
49
23
21
49
43
47

87
87
98
m
89
m
86
m
95
88
93
m
98
m
m
88
m
m
91
100
m
53
95
86
92
96
89
m
100
84
m
90
m
m
82

69
72
81
m
58
m
82
m
94
77
87
m
88
m
m
26
m
m
68
93
m
37
85
65
88
92
76
m
92
73
m
84
m
m
68

66
50
83
m
51
m
63
m
52
64
71
m
74
m
m
16
m
m
74
82
m
32
75
58
60
44
64
m
82
62
m
61
m
m
61

62
39
75
m
46
m
49
41
49
52
58
m
63
m
m
18
m
m
71
59
m
26
67
55
57
19
55
m
64
53
m
44
m
m
53

OECD average
Average for countries
with available data
for all reference years
EU22 average

97

95

90

1

2

56

2

18

26

4

34

13

4

39

89

75

61

51

~

~

89

1

2

55

2

21

26

4

35

13

4

40

89

75

61

51

97

95

91

1

2

66

2

16

30

5

33

14

5

39

93

84

67

53

Argentina2
Brazil
China
Colombia
Costa Rica
India
Indonesia
Lithuania
Russian Federation3
Saudi Arabia
South Africa2

94
86
m
83
85
m
m
100
85
100
76

88
85
m
72
78
m
m
100
55
99
m

79
68
m
38
53
m
m
98
39
100
m

a
1
m
0
a
m
a
0
13
a
0

1
5
4
14
m
m
5
0
40
m
1

39
33
m
19
31
m
m
83
3
59
m

a
2
m
0
a
m
a
1
11
a
1

19
14
22
23
m
m
19
9
65
m
7

19
20
m
9
19
m
m
22
0
27
35

a
2
m
0
a
m
a
7
5
a
2

32
20
35
27
m
m
23
49
63
m
10

9
11
m
5
14
m
m
6
0
11
24

a
2
m
0
a
m
a
8
2
a
3

36
22
36
27
m
m
23
54
54
m
11

m
m
m
m
m
m
m
100
m
m
m

m
m
m
m
m
m
m
100
m
m
m

m
m
m
m
m
m
m
88
m
m
m

m
m
m
m
m
m
m
77
m
m
m

m

m

m

m

4

m

m

28

m

m

39

m

m

40

m

m

m

m

Secondary
OECD
Partners

Age 17

Secondary

Age 15 Age 16

G20 average

1. Excludes post-secondary non-tertiary education.
2. Year of reference 2015.
3. Data on upper secondary vocational programmes are included in post-secondary non-tertiary and short-cycle tertiary programmes.
Source: OECD/UIS/Eurostat (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933803007

160 Education at a Glance 2018: OECD Indicators   © OECD 2018

Who participates in education? – INDICATOR B1

chapter B

Under embargo until 11/09/2018 at 11.00am CEST
Table B1.3. Profile of students enrolled in lower and upper secondary education (2016)
Upper secondary

Percentage of students in public
institutions

Percentage of repeaters in general
programmes

Percentage of girls among the repeaters
in general programmes

Percentage of over-age students in
the last grade (general programmes
only)

Percentage of girls among the over-age
students in general programmes

Average age of enrolment

Percentage of students in public
institutions

Percentage of part-time students

In combined school- and
work-based programmes

Percentage of girls in vocational
programmes (as % of all programmes)

In general programmes

In vocational programmes

Percentage of repeaters in general
programmes

Percentage of girls among the repeaters
in general programmes

Percentage
of students above
typical age
(20 years old)

Average age of enrolment
Partners

OECD

Lower secondary

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

(13)

(14)

(15)

(16)

Australia
Austria
Belgium
Canada
Chile
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United Kingdom
United States

m
12
19
13
13
13
15
15
14
13
13
14
13
14
14
13
12
13
13
14
14
17
14
13
14
14
15
13
13
15
16
14
13
m
13

59
90
42
92
42
97
71
96
95
78
90
96
83
99
100
83
96
93
82
98
81
90
99
95
96
93
86
92
100
68
83
91
95
28
91

m
2
7
m
4
1
1
2
0
2
2
4
2
m
0
1
3
m
0
2
10
1
m
m
a
2
m
2
1
11
a
1
2
a
m

m
39
40
m
42
42
41
38
45
39
38
35
39
m
46
28
33
m
46
33
46
28
m
m
a
32
m
45
32
40
a
43
58
a
m

m
8
6
m
9
4
1
7
m
2
m
4
2
a
0
1
3
a
0
5
14
3
m
1
a
m
m
m
1
9
0
1
3
a
5

m
40
40
m
37
37
39
37
m
41
m
35
38
a
49
39
35
a
40
32
49
37
m
46
a
m
m
m
37
39
44
44
52
a
36

m
17
22
17
17
18
21
20
25
17
18
17
18
21
17
16
16
16
16
19
18
16
21
21
19
18
18
17
18
20
21
18
18
21
16

60
89
41
93
37
85
97
97
80
71
92
96
73
77
99
94
91
67
57
96
82
81
90
87
90
86
79
84
94
73
83
85
92
19
91

50
0
30
0
0
1
8
11
a
0
2
7
12
22
1
a
0
5
0
15
1
a
8
27
3
12
8
2
22
14
28
1
a
34
a

56
69
59
9
28
73
41
39
71
41
38
29
21
32
a
40
56
23
18
38
61
38
68
30
50
51
41
69
70
35
37
65
48
53
m

x(10)
32
3
x(10)
2
6
33
1
9
10
31
a
21
15
a
3
a
a
a
38
13
a
m
x(10)
17
8
a
7
a
1
2
58
a
20
m

49
64
57
8
26
67
36
30
69
36
38
20
16
26
a
41
43
20
15
32
59
36
67
32
42
41
36
63
64
32
36
57
47
54
m

7
3
21
m
7
1
19
11
6
0
4
1
10
23
4
1
1
m
0
17
5
4
2
2
10
18
9
2
4
7
32
11
26
0
m

82
12
25
m
3
17
72
36
65
13
44
16
16
65
a
0
6
m
0
18
25
6
46
67
26
2
20
7
28
57
40
24
6
53
m

m
6
8
m
8
11
1
4
a
5
m
1
5
m
1
2
7
m
0
6
11
14
m
m
m
4
m
0
1
m
a
5
6
a
m

m
47
37
m
42
37
48
61
a
45
m
41
45
m
47
28
35
m
37
49
43
44
m
m
m
33
m
28
43
m
a
50
34
a
m

OECD average
EU22 average

14
14

85
85

2
3

40
39

3
4

40
40

19
19

80
82

9
10

44
48

11
11

40
44

8
8

28
28

4
4

42
43

Argentina1
Brazil
China
Colombia
Costa Rica
India
Indonesia
Lithuania

15
14
m
14
16
m
m

76
86
88
81
91
58
61

11
m
m
3
12
0
m

41
m
m
41
40
46
25

16
15
m
20
23
m
m

49
38
m
40
43
m
m

17
18
m
17
19
m
18

70
86
89
74
90
41
53

m
m
m
a
a
m
m

a
9
41
26
33
3
43

m
a
m
a
a
m
m

a
10
38
27
34
1
37

9
15
m
14
23
m
8

a
28
m
1
22
m
6

6
m
m
1
8
2
m

42
m
m
41
43
44
m

14

97

1

27

5

32

19

98

5

27

a

20

9

19

1

40

Russian Federation

13

99

0

49

1

m

16

97

1

54

m

46

0

m

0

55

Saudi Arabia

14

92

2

45

11

48

18

83

m

m

m

m

12

m

2

35

South Africa1

15

96

m

m

m

m

m

m

m

12

m

11

15

78

16

50

G20 average

m

81

3

41

m

m

m

74

m

32

m

29

m

m

5

42

In vocational programmes

Percentage
of students

1. Year of reference 2015.
Source: OECD/UIS/Eurostat (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933803026

Education at a Glance 2018: OECD Indicators   © OECD 2018

161

B1

Under embargo until 11/09/2018 at 11.00am CEST

HOW DO EARLY CHILDHOOD EDUCATION SYSTEMS DIFFER
AROUND THE WORLD?
INDICATOR B2

• Early childhood education and care (ECEC) has experienced a surge of policy attention in
OECD countries in recent decades, with a focus on children under the age of 3. On average across
OECD countries in 2016, around one-third of children under age 3 are enrolled in ECEC, an increase
of 5 percentage points compared to 2010.

• Universal or near-universal participation in at least one year of ECEC is now the norm in
OECD countries, which is significant progress towards one of the education targets of the
United Nations Sustainable Development Goals (SDG 4.2.2). Between 2005 and 2016, average
enrolment of 3-5 year-olds in pre-primary or primary education rose from 75% to 85%.

• Despite progress, significant inequities persist in the access of very young children to ECEC services.
For example, children under age 3 are more likely to participate to ECEC when they come from
relatively advantaged socio-economic backgrounds or when their mother has completed tertiary
education.

Figure B2.1. Enrolment rates of children under the age of 3 in early childhood
education and care, by type of service (2010 and 2016)
All ECEC services (Early childhood education [ISCED 0]
and other registered ECEC services outside the scope of ISCED 0)

%

70

2016 – Early childhood education and care (ISCED 0)1
2016 – Other registered ECEC services
2010 – ISCED 0 and other registered ECEC services

60
50
40
30
20
0

Denmark
Israel
Norway
Korea
Colombia
Iceland
Belgium
Sweden
New Zealand
Slovenia
Australia
Germany
Portugal
Spain
Finland
OECD average
Estonia
Lithuania
EU22 average
Brazil
Chile
Russian Federation
Austria
Indonesia
Slovak Republic
Czech Republic
Hungary
Argentina
France2
Poland
Mexico
Costa Rica
Luxembourg3
Turkey
Netherlands
Ireland

10

Note: Early childhood education = ISCED 0, other registered ECEC services = ECEC services outside the scope of ISCED 0, because
they are not in adherence with all ISCED criteria. To be classified in ISCED 0, ECEC services should: 1) have adequate intentional
educational properties; 2) be institutionalised (usually school-based or otherwise institutionalised for a group of children); 3) have
an intensity of at least two hours per day of educational activities and a duration of at least 100 days a year; 4) have a regulatory
framework recognised by the relevant national authorities (e.g. curriculum); and 5) have trained or accredited staff (e.g. requirement
of pedagogical qualifications for educators).						
1. According to ISCED criteria. 									
2. Data for “Other registered ECEC services” come from the survey “Enquête Modes de garde et d’accueil des jeunes enfants 2013”
conducted by the statistical division of the French Ministry for Solidarities and Health (DREES). Figures refer to the primary
custody arrangements.
3. Year of reference 2014 instead of 2016 for children under the age of 3 enrolled in “Other registered ECEC services”. Data come
from the OECD family database (www.oecd.org/els/family/database.htm).
Countries are ranked in descending order of the enrolment rates in ISCED 0 of children under the age of 3 in 2016.
Source: OECD (2018), Table B2.1a. See Source section at the end of this indicator for more information and Annex 3 for notes
(http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933803216

162 Education at a Glance 2018: OECD Indicators   © OECD 2018

Under embargo until 11/09/2018 at 11.00am CEST
Context
Economic prosperity depends on maintaining high employment-to-population ratio, and the
increasing number of women entering the labour market has contributed to greater government
interest in expanding ECEC services. The availability of quality ECEC services and other provisions
aiming at improving work-life balance give fathers and mothers greater opportunities to enter
employment and to ensure that it is feasible for families to combine work and family responsibilities
([OECD, 2018[1]]; [OECD, 2011[2]]) and (OECD, 2016[3]).

INDICATOR B2

However, the benefits of ECEC services are not limited to better labour-market outcomes and fertility
rates. There is an increasing awareness of the key role that ECEC plays for children’s development,
learning and well-being. Children who start strong will be more likely to obtain better outcomes
when they grow older. This is particularly true for children from disadvantaged socio-economic
backgrounds, because they have often fewer opportunities to develop these abilities in their homelearning environments (OECD, 2017[4]).
Such evidence has prompted policy makers to design early interventions, to take initiatives that aim
at enhancing the quality of ECEC services and improve the equity of access to ECEC settings, and to
rethink their education spending patterns to gain “value for money” (Duncan and Magnuson, 2013[5]).
Despite these general trends, significant differences exist across OECD countries in the quality of
ECEC services provided to young children, in the types of ECEC services available and in the usual
number of hours per week that each child is enrolled.
Currently, over half of OECD countries have all ECEC services administered under the responsibility
of one leading authority at the national and/or regional level. Those countries also have integrated
ECEC curricula adapted to the age of children from below age 1 until the beginning of primary school.
An increasing number of countries have recently move towards these types of integrated systems
(OECD, 2017[4]).
Other findings

• In 2015, expenditure on ECEC (ISCED 0) accounted for an average of 0.8% of GDP, of which around
three-quarters went to pre-primary education (ISCED 02). In pre-primary education, expenditure
increased faster than GDP in the 18 countries with available data for 2005 and 2015.

• Affordability is a key driver of equity in participation in ECEC. The share of public funding in total
expenditure tends to be lower in early childhood development institutions (ISCED 01) than for
pre-primary education. The share of public spending in pre-primary education has increased over
the period 2005-15 by 4 percentage points, on average across OECD countries.

• Children under the age of 3 are much more likely to be enrolled in private ECEC settings than older
children. The proportion of children enrolled in private early childhood development institutions
(ISCED 01) is considerably larger than for pre-primary education (ISCED 02) and exceeds 50% in
about two-thirds of OECD countries.

• On average across OECD countries, each teacher (excluding teachers’ aides) working in pre-primary
education takes care of 14 children. Interestingly, the number of children per teacher has fallen
between 2005 and 2016 in about two-thirds of the 21 OECD countries with available data. On
average, the number of children enrolled in pre-primary education increased by 18% between 2005
and 2016, a period within which the number of teachers increased by 29%.

Education at a Glance 2018: OECD Indicators   © OECD 2018

163

chapter B Access to Education, Participation and Progression
Under embargo until 11/09/2018 at 11.00am CEST

Analysis
Types of early childhood education and care services

B2

There is a consensus among OECD countries about the growing need for early childhood education and care. However,
the types of ECEC services available to children and parents in OECD countries differ greatly. Variations exist in the
targeted age groups, the governance of centres, the funding of services, the type of delivery (full-day versus part-day
attendance), as well as the location of provision, either in centres/schools or at home (OECD, 2017[4]).
Generally, formal ECEC services can be classified in two categories:

• The ECEC services reported in the ISCED 2011 classification (OECD/Eurostat/UNESCO Institute for Statistics,
2015[6]). To be classified in ISCED 0, ECEC services should :
1) have adequate intentional educational properties
2) be institutionalised (usually school-based or otherwise institutionalised for a group of children)
3) have an intensity of at least two hours per day of educational activities and a duration of at least 100 days
a year
4) have a regulatory framework recognised by the relevant national authorities (e.g. curriculum)
5) have trained or accredited staff (e.g. requirement of pedagogical qualifications for educators).

• The other registered ECEC services that are considered an integral part of countries’ ECEC provision but do not
comply with all the ISCED 0 criteria to be considered educational programmes (e.g. crèches in France or Amas in
Portugal). The distinction between these two categories is explicitly shown in Figure B2.1 and in Table B2.4.
Informal care services (generally unregulated care arranged by the child’s parent either in the child’s home or
elsewhere, provided by relatives, friends, neighbours, babysitters or nannies) are not covered in this indicator
(see Definitions section at the end of this indicator for more details).
Enrolment in early childhood education and care

Enrolment of children under the age of 3
Participation in high-quality ECEC can have positive effects on children’s well-being, learning and development in
the first years of life (OECD, 2018[1]).
On average across OECD countries in 2016, around one-third of children under age 3 are enrolled in ECEC,
either full time or part time. This average hides great differences across countries. The length of parental leave
also influences the age at which children enrol in ECEC services. ECEC services for children under age 3 are
almost non-existent in Mexico (only 2% of children enrolled) and Turkey, while over half of children under age 3
are already enrolled in Belgium, Denmark, Iceland, Israel, Korea, Luxembourg, the Netherlands and Norway
(Figure B2.1)
Despite significant differences across countries, a common pattern emerges. The share of children under the age
of 3 enrolled in ECEC is on the rise in most countries and has increased on average from 25% to 31% between
2010 and 2016 (Table B2.1b). This is particularly marked in many European countries, as a result of further
stimulus by the 2010 objectives set by the European Union (EU) at its Barcelona meeting (to supply subsidised
full-day places for one-third of children under the age of 3 by 2010) (OECD, 2017[4]). More globally, the rise
in ECEC provision over the last decades has greatly contributed to the increase in women’s participation in
the labour force, particularly for mothers with children under age 3. Countries with higher enrolment rates of
children under age 3 in 2016 tend to be those in which the employment rates of mothers are highest ([OECD,
2018[1]] [OECD, 2018[7]]; Figure B2.1).
However, the wider enrolment in ECEC services does not account for the quality of education provided to children. In
countries such as Norway, for instance, not only do more than half of the children below age 3 attend ECEC services,
but they also attend programmes integrated within the education system from below age 1 until the beginning of
primary school. In these programmes, children are often exposed to an ECEC setting with trained or accredited
staff, explicit pedagogical goals and a regulatory framework recognised by the relevant national authorities, even
before the age of 3. In other countries with similar enrolment rates, such as Luxembourg and the Netherlands,
different standards are often set for different ECEC settings or for different age groups of children (see more details
in Table B2.4).

164 Education at a Glance 2018: OECD Indicators   © OECD 2018

How do early childhood education systems differ around the world? – INDICATOR B2

chapter B

Under embargo until 11/09/2018 at 11.00am CEST

Enrolment of children under the age of 3, by socio-economic profiles
Research shows that children coming from a disadvantaged family or children with an immigrant background can
benefit the most from attending high-quality ECEC (see Box B2.1). While promoting equity in education from the
earliest age possible is paramount, the existence of inequalities in the economic, social and cultural backgrounds of
children in ECEC centres is becoming more of a challenge in OECD countries. This is particularly true as children
from poorer families traditionally face greater barriers in accessing ECEC services. It is also often reported that
although the children of deprived families need high-quality ECEC the most, these families often have lack of
knowledge about existing ECEC services ([OECD, 2017[4]] and Box B2.1).
Children below the age of 3 with tertiary-educated mothers are more likely to participate in ECEC. In particular, on
average across countries with available data, children with tertiary-educated mothers are more likely to participate
in an ECEC programme than those whose mothers are without tertiary education, by about 10 percentage points.
The difference is statistically significant and exceeds 20 percentage points in Austria, Belgium, Ireland and
the Netherlands (Figure B2.2 and [OECD, 2018[7]]). Women with tertiary education are more likely to be employed
and have higher income than those without tertiary education, and they are therefore more likely to be able to
afford private costs to enrol their children in such programmes ([OECD, 2018[1]] [OECD, 2018[7]]).

Figure B2.2. Participation rates of children under the age of 3,
by mother’s educational attainment (2014)
All ECEC services (Early childhood education [ISCED 0] and other registered ECEC services outside the scope of ISCED 0)

Czech Republic

Slovak Republic

Greece*

Poland*

Israel1

Hungary

Latvia

Austria*

Italy*

Finland

Tertiary-educated mother

Estonia1

United Kingdom*

Average

Spain

Ireland*

Slovenia1

Germany

Belgium*

Non-tertiary-educated mother

Portugal*

Luxembourg*

Iceland*

Denmark

Norway1, 2

100
90
80
70
60
50
40
30
20
10
0

Netherlands*

Overall

%

Note: For most European countries, data refer to the 2014 wave of EU-SILC survey led by Eurostat. EU-SILC data are based on surveys and may as
a result be affected by sample size and sample selection issues. The EU-SILC survey includes unregulated paid childminders’ services. Differences in
enrolment rates across groups are not statistically significant at p<0.05 for a few countries. In countries with an *, differences in enrolment rates across
groups are statistically significant at p<0.05.
1. 2016 data, provided by the country. No sampling, therefore, no p-value reported. In Norway, data are based on children aged 1 and 2 years old.
2. Data provided by the country only for ISCED 0.
Countries are ranked in descending order of the overall enrolment rates of children under the age of 3.
Source: OECD (2018), Table B2.1c, available on line, and OECD Family Database. See Source section at the end of this indicator for more information
and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933803235

Indeed, children under the age of 3 are more likely to be enrolled in ECEC programmes when they come from
relatively advantaged socio-economic backgrounds. On average across OECD countries, only 28% of children in
households where income is in the lowest tertile are enrolled in ECEC services, compared to over 44% of those from
the wealthiest tertile (Table B2.1c, [OECD, 2018[7]] and [OECD, 2016[8]]). This difference across income groups is
statistically significant in more than half of the countries with available data, notably in those where the overall
enrolment rates are the lowest, i.e. countries in which only a small proportion of children globally are enrolled in
ECEC services (such as the Czech Republic, Hungary and Poland).
Education at a Glance 2018: OECD Indicators   © OECD 2018

165

B2

chapter B Access to Education, Participation and Progression
Under embargo until 11/09/2018 at 11.00am CEST

Enrolment of children from age 3 until entry to primary education

In many OECD countries, legal entitlements to a place in ECEC services are universal for at least one or two years
before the start of compulsory schooling. On average, 86% of children between age 3 and age 5 are enrolled in ECEC
services, at that age usually in pre-primary education (ISCED 02). In 18 of the 42 countries with available data, the
enrolment of children between age 3 and age 5 is near universal, exceeding 90%.
This trend is the result of the expansion of ECEC services over the past decades in many countries. Over this
period, the increased focus on ECEC policy has resulted in the extension of compulsory education to lower ages,
an increased provision of free ECEC for some ages and targeted population groups, universal provision for older
children and, in some countries, the creation of integrated ECEC programmes from age 1 until entry into primary
education. In figures, between 2005 and 2016, average enrolment of 3-5 year-olds in pre-primary or primary
education rose from 75% to 85%. A few countries have had spectacular increases in ECEC over this period, as in
Chile, Lithuania, Poland, the Russian Federation and Turkey. By contrast, other countries have not shown much
change. For instance, Switzerland was in the group of countries that reported the lowest enrolment rates in 2005
and still in 2016 (Figure B2.3).

Figure B2.3. Change in enrolment rates of children aged 3 to 5 years (2005, 2010 and 2016)
Early childhood education (ISCED 0) and primary education
2005

%

100
90
80
70
60
50
40
30
20
10
0

2010

2016

France
United Kingdom
Israel
Belgium
Denmark
Iceland
Spain
Norway
Sweden
Italy
Germany
Netherlands
Korea
New Zealand
Latvia
Hungary
Japan
Estonia
Austria
EU22 average
Slovenia
Portugal
Czech Republic
OECD average
Luxembourg
Australia
Poland
Lithuania
Russian Federation
Mexico
Brazil
Chile
Finland
Colombia
Ireland
Argentina1
Slovak Republic
Indonesia
United States
Greece
Costa Rica
Switzerland
Turkey
Saudi Arabia1

B2

In many OECD countries, ECEC begins for most children well before they are 5 years old. Almost nine out of ten
4-year‑olds (88%) are enrolled in pre-primary and primary education across OECD countries. In the OECD countries
that are part of the European Union, 91% of 4-year-olds are enrolled. OECD enrolment rates in pre-primary education
at this age vary from 98% or higher in Belgium, Denmark, France, Iceland, Israel and the United Kingdom, to less than
50% in Switzerland and Turkey. The highest enrolment rates of 3-year-olds in ECEC are found in Belgium, Denmark,
France, Hungary, Iceland, Israel, Korea, Norway, Spain and the United Kingdom, exceeding 95% (Table B2.1a).

1. Year of reference 2015 instead of 2016.
Countries are ranked in descending order of the enrolment rates of 3-5 year-olds in 2016.
Source: OECD (2018), Tables B2.1a and b. See Source section at the end of this indicator for more information and Annex 3 for notes (http://dx.doi.
org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933803254

Enrolment in ECEC, by subnational regions
If 3 is the starting age of universal entitlement to ECEC in many countries, some strong regional differences remain
in access to pre-primary education at this age. For instance, a striking difference is observed in Austria, where
up to 90% of 3-year-olds are enrolled in pre-primary in the Burgenland and Niederösterreich area, compared to
only 54% in Styria (Steiermark) (OECD/NCES, 2018[9]). The difference between regions in enrolment rates of
3-year-olds equals or exceeds 20 percentage points in Poland, the Russian Federation, Spain and the United States.
This emphasises the importance of granting equal access to ECEC across urban and rural areas.

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At age 4, enrolment is universal or near universal in most of the countries. However, differences between subnational
regions still exist in the 14 countries with available data by subnational regions (see Source section). In Austria,
Finland, Italy, Korea, Poland, the Russian Federation, Spain, Turkey and the United States, there is a difference
of more than 10 percentage points in enrolment of 4-year-olds in pre-primary or primary education between the
region with the highest rate and the region with the lowest rate.

Enrolment in ECEC, by type of institution
Parents’ needs and expectations regarding accessibility, cost, programme, staff quality, and accountability are all
important in assessing the expansion of ECEC programmes and the type of providers. When parents’ needs for
quality, accessibility or affordability are not met by public institutions, some parents may be more inclined to send
their children to private pre-primary institutions (Shin, 2009[10]).

Box B2.1. Integrating young immigrant children by encouraging their enrolment
in high-quality early childhood education and care
The populations of OECD countries are becoming increasingly heterogeneous because of migration. On
average across the OECD, the share of the foreign-born population has increased from 6% to over 9% in the
last two decades. Increased mobility leading to greater diversity requires particular efforts towards integration,
especially in the early stages of education (OECD, 2016[11])
Integrating young immigrant children into their new communities is of key importance in the long run.
Education systems can help by encouraging their enrolment in ECEC services. However, in most countries,
the participation of immigrant children in these programmes is considerably lower than for those without an
immigrant background (OECD, 2017[4]; Magnuson and Waldfogel, 2006[12]). On average in the OECD Programme
for International Student Assessment (PISA) 2015, immigrant students who reported that they had attended an
ECEC setting (ISCED 0) for at least one year scored 36 points higher in the science assessment than those who
had attended for less than one year (the equivalent of around one year of formal schooling). After accounting for
the socio-economic status of children, a significant difference of 25 score points remains (OECD, 2017[4]).
Expansion of ECEC programs has been implemented across countries to serve a variety of objectives, such as
providing care to children living in remote areas, providing equity for economically disadvantaged children,
easing the transition of new immigrants into new cultures, or supporting indigenous cultures. In several
countries (Denmark, Finland, the Netherlands, Norway and Sweden), policies have been implemented to
expand access to early childhood services for immigrant and ethnic minority groups. They are meant to expose
children and families to the language and traditions of their new home and provide opportunities for parents
to establish social contacts and networks.
Countries with indigenous populations (Australia, Canada, New Zealand and the United States) also implemented
measures to preserve traditional languages and cultures, while seeking to empower families within society. Despite
this progress, the need for early childhood staff and provision to value and respond to the needs of ethnically,
culturally and linguistically diverse families still remains a challenge in many countries (OECD, 2017[4]).
The quality of ECEC services is crucial for ensuring that ECEC benefits those who need it most. On this key
question, the literature review and meta-analysis findings summarised in the report Engaging Young Children
(OECD, 2018[13]) show that children in ECEC classrooms or playrooms with a larger share of immigrant or
bilingual children seemed to experience lower-quality staff-child interactions. Similarly, it was shown that
classrooms or playrooms with a larger share of immigrant or bilingual children affect children’s development:
children from disadvantaged backgrounds attending preschools with a larger percentage of other children
with similarly disadvantaged backgrounds presented lower language and literacy skills.
The lower quality of settings with a large percentage of immigrant or bilingual children might reflect the barriers
to access and the added risk experienced overall by disadvantaged families (EACEA P9 Eurydice, 2009[14])
and ethnic minority or multilingual families in specific locations (Stewart and Waldfogel, 2017[15]). A further
explanation that has been suggested is that working with disadvantaged children is more challenging, and
additional resources might be needed to counteract these challenges to raise process quality (Pianta et al.,
2005[16]; OECD, 2018[13]).

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B2

In most countries, the share of children enrolled in private ECEC institutions is considerably larger than in primary
and secondary education. Private institutions can be classified under two different categories: independent private
and government-dependent. Independent private institutions are controlled by a non-governmental organisation
or by a governing board not selected by a government agency and receive less than 50% of their core funding from
government agencies. Although government-dependent private institutions have similar governance structures,
they rely on government agencies for more than 50% of their core funding.
On average across OECD countries, about half of children in early childhood educational development programmes
(ISCED 01) are enrolled in private institutions. This average, however, hides huge discrepancies across countries.
In Denmark, Finland, Hungary, Iceland, Slovenia, Sweden, Lithuania and the Russian Federation, 20% or less
of children in early childhood educational development programmes attend private ECEC institutions, while in
Belgium, Indonesia, Israel, Korea, New Zealand, Portugal, Turkey and the United Kingdom, all or almost all children
are in private institutions (Table B2.2).
Private institutions usually are more common for children under the age of 3 than for older ones. Thus, about two‑thirds
of children enrolled in pre-primary education (ISCED 02) attend public institutions across OECD countries, and up
to about three-quarters of children for EU22 countries, reflecting the development of public policies promoting the
public provision of ECEC that occurred in most European countries over the past two decades. In a few countries,
however, ECEC remains mostly privately provided and funded: in India, Ireland and Japan, more than 70% of
children attending pre-primary programmes are in independent private institutions (Table B2.2).

Box B2.2. How many hours per year, on average, does a child participate
in pre-primary education?
From a child development perspective, there is little evidence on the optimal hours of participation to ECEC.
Therefore, research on the benefits of full-time compared to part-time ECEC attendance is less conclusive than
evidence regarding the benefits of a longer period of participation to ECEC. However, from a labour-market
perspective, the availability of ECEC services with an adequate number of hours per week is a crucial factor to
enable parents of young children to take up full-time employment (OECD, 2017[4]).
While participation rates by age provide a proxy of how long children are enrolled in ECEC over their childhood
(e.g. in years), they do not provide any information about the intensity of participation in pre-primary
education (i.e. whether children are enrolled only a few hours per day or all day long). On average, a child attends
pre‑primary education for an average of 31 hours per week and 40 weeks per year. This average, however, hides
huge differences across countries and excludes out-of-school-hours activities. Children attend pre-primary
education from 15 hours per week in Mexico to up to 50 hours per week in the Russian Federation. Similarly,
pre-primary settings are typically open 30 weeks per year in the Russian Federation and up to 52 weeks per
year in Hungary.
In addition to other factors such as teachers’ salaries, ECEC provision or child-to-staff ratios, the number
of hours per year a child attends pre-primary education largely influences the amount of public budgets to
invest in pre-primary education. For instance, increasing the number of hours children spend on pre-primary
education, or decreasing the staff-to-child ratio, results in a need for additional staff, thus increasing the
public budget. Figure B2.a shows that, with the exception of Norway, countries with the highest number of
opening hours per week and weeks per year are also countries in which child-to-teacher ratios are below the
OECD average. Among these countries, Iceland, Latvia, and Hungary spend more on pre-primary education as
a percentage of GDP than OECD countries on average, while expenditure as a percentage of GDP is at the level
of the average in the Slovak Republic (Table B2.3a).
For a more complete understanding of ECEC provision however, enrolment rates and intensity of participation
need to be analysed together. Countries such as Belgium, France and Spain offer relatively lower opening hours
and weeks in pre-primary settings and child-to-staff ratios are above the OECD average of 14, but enrolment
is universal for children age 3 to age 5 (Table B2.1b). In the Slovak Republic, on the other hand, pre-primary
schools are open over 40 hours per week, but enrolment rates are below the OECD average, as 73% of children
age 3 to age 5 are enrolled in pre-primary edcuation (Table B2.1a).

…

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Figure B2.a. Number of hours per week and weeks per year children
attend pre‑primary education (ISCED 02) (2016)
Number of hours
per week

Country average

55
50

B2

Countries with a ratio is 10 or lower
CTR between 11 and 14
CTR over 14

Russian Federation

45
Greece1

40

Latvia

Iceland

Hungary

Slovak Republic

35

Norway2
Country average

30

Israel

25

Belgium
Spain

20

France

Portugal

Switzerland1 Japan3

15

Mexico

10
25

30

35

40

45

50

55

Number of weeks per year

Note: The three different symbols correspond to the ratio of children to teaching staff (CTR) in pre-primary education. Data on the CTR for
Israel are missing.
1. Year of reference of data on CTR: 2014 for Switzerland and 2015 for Greece.
2. Average attendance hours of children enrolled in ISCED 02 programmes.
3. The average hours and weeks per year in pre-primary education (ISCED 02) may be inconsistent with the actual situation because these data
are based on a regulation defined by National Curriculum Standards for Kindergarten.
Source: OECD (2018) and INES ad-hoc survey. See Source section at the end of this indicator for more information and Annex 3 for notes
(http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933803311

Financing early childhood education and care
Sustained public financial support is critical for the growth and quality of ECEC programmes. Appropriate funding
helps to recruit trained staff who are qualified to support children’s cognitive, social and emotional development.
Investment in early childhood facilities and materials also helps support the development of child-centred
environments for well-being and learning. In countries that do not channel sufficient public funding towards
achieving both broad access and high-quality programmes, some parents may be more inclined to send their
children to private ECEC services. Moreover, if the cost of ECEC is not sufficiently subsidised, the ability of parents
to pay will influence greatly the participation to ECEC of children from disadvantaged socio-economic backgrounds
(OECD, 2017[4]).

Expenditure per child
In pre-primary education, annual expenditure per child for both public and private settings averages USD 8 528 in
OECD countries, ranging from USD 5 000 or less in Brazil, Colombia and the Czech Republic to more than USD 13 000 in
Luxembourg, Norway and Sweden. Annual expenditure per child enrolled in early childhood educational development
programmes (ISCED 01) is significantly higher than in pre-primary education (ISCED 02) in 12 out of the 14 OECD
countries with available data for both programmes, averaging USD 12 433. The smaller child-to-staff ratio in early
childhood development programmes is one of the main drivers of this difference (Tables B2.3a and B2.2). The average
number of hours children spend in an ECEC setting per year also influences different countries’ spending (Box B2.2).

Public and private funding of ECEC
The source of funding for ECEC settings varies across countries. In some countries, the public sector provides universal
access from a certain age. In others, ECEC settings are mainly provided by the private sector, or there is a mix of the
two (Table B2.3b). Many governments may also delegate responsibility for ECEC public funding to local authorities. In
general, public funding is more decentralised in ECEC than at any other level of education (OECD, 2018[17]).
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Expenditure as a percentage of GDP
Spending on ECEC can also be analysed relative to a nation’s wealth. Expenditure on all ECEC settings accounts for
an average of 0.8% of GDP across OECD countries, of which three-quarters are allocated to pre-primary education
(Figure B2.4). While 0.3% or less of GDP is spent on pre-primary education in Australia, Greece, Ireland and Japan,
countries such as Iceland and Sweden spend over 1% of GDP (Table B2.3a). These differences are largely explained by
enrolment rates, legal entitlements and intensity of participation, as well as the different starting ages for primary
education. Comparison between countries’ relative expenditure on ECEC is also a function of the duration of preprimary education. For example, a shorter duration of pre-primary education as the result of an earlier transition
between pre-primary to primary education, such as in Australia, Ireland, New Zealand and the United Kingdom,
partly explains why these four countries have expenditure on ECEC as a percentage of GDP below the OECD average.
Table B2.4 summarises the theoretical duration of countries’ ECEC programmes and the OECD family database
provides additional information (OECD, 2018[7]).
Investments in high-quality ECEC pay dividends in terms of children’s short-term and long-term learning and
development. That is why many OECD countries have increased spending on ECEC, particularly to expand access
or to increase the number of hours per week covered by legal entitlements to a place in ECEC (Box B2.2). This
direction has also been the result of further stimulus by the 2010 objectives set by the European Union (EU) at
its Barcelona meeting. In the 18 countries with available data, the increase in the number of children enrolled
in pre-primary education between 2005 and 2015 goes hand in hand with an increase in financial investment.

Figure B2.4. Expenditure on pre-primary (ISCED 02) education as a percentage of GDP
(2005, 2010 and 2015)
2010

2015

Germany

2005

% of GDP

Slovak Republic

Public and private institutions
1.4
1.2
1.0
0.8
0.6
0.4

Japan

Ireland

Greece

Australia

Colombia

Switzerland

Netherlands

United Kingdom

Costa Rica

United States

Czech Republic

Italy

Austria

Korea

New Zealand

Spain

Portugal

Luxembourg

OECD average

Lithuania

EU22 average

Brazil

Belgium

Poland

Slovenia

Chile

France

Latvia

Hungary

Israel

Finland

Norway

0.0

Iceland

0.2
Sweden

B2

Generally, a substantial and increasing public investment in ECEC is observed on average across OECD countries,
although differences exist between pre-primary (ISCED 02) and early childhood educational development (ISCED 01).
On average across OECD countries, in early childhood educational development, public sources account for 72% of
total expenditure, while in pre-primary education, the share of public expenditure is higher, at 83% of the total. Public
spending in pre-primary education has also increased over the period from 2005 to 2015, by 4 percentage points on
average for countries with available data for both reference years, and by more than 10 percentage points in Chile,
Germany, Israel and Korea (Table B2.3b, available on line). In 2015, Japan, Turkey and the United Kingdom are the
only countries where private funds account for more than 40% of total expenditure in pre-primary education. In
Turkey, most of the private funding comes from households but families have access to well-developed public subsidies
system. In Japan, the high cost is shared between households, foundations and the business sector while a large part
of the private funding comes from households in the United Kingdom (Table B2.3b, available on line).

Note: Comparison between countries’ relative expenditure on ECEC is also a function of the duration of pre-primary education. For example, a shorter
duration of pre-primary education as the result of an earlier transition to primary education may explain why some countries have expenditure on
ECEC as a percentage of GDP below the OECD average (see duration of pre-primary education in Table B2.4, available on line).
Countries are ranked in descending order of expenditure as a percentage of GDP in 2015.
Source: OECD (2018), Table B2.3a. See Source section at the end of this indicator for more information and Annex 3 for notes (http://dx.doi.
org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933803273

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In all these countries, expenditure on pre-primary educational settings increased at a faster rate than GDP, resulting
on average across OECD countries in an increase in expenditure on educational institutions as a percentage of GDP
of 0.1 percentage points between 2005 and 2015. The increase is at least of 0.3 percentage points over this period in
Brazil (from 0.4% to 0.7%), Chile (from 0.5% to 0.8%) and Korea (from 0.1% to 0.6%) (Figure B2.4).
Variation in child-staff ratios across OECD countries
Research demonstrates that enriched, stimulating environments and high-quality pedagogy are fostered by betterqualified practitioners, and that better-quality staff-child interactions facilitate better learning outcomes. In that
context, lower child-staff ratios are found to be consistently supportive of staff-child relationships across different
types of ECEC settings. Smaller ratios are often seen as beneficial, because they allow staff to focus more on the
needs of individual children and reduce the amount of class time needed to deal with disruptions (OECD, 2018[13]).
The ratio of children to teaching staff is an important indicator of the resources devoted to education. Child-staff
ratios and group size are often the most commonly used regulations to improve ECEC quality. On average across
OECD countries, there are 14 children for every teacher working in pre-primary education. But wide variations are
observed across countries. Thus, the child-teacher ratio, excluding teachers’ aides, ranges from more than 20 children
per teacher in Brazil, Chile, Colombia, France, Mexico and South Africa to less than 10 in Iceland and Slovenia.
Some countries also make extensive use of teachers’ aides at the pre-primary level to assist teachers in their daily
tasks and deal with children with special needs: 11 of the 22 countries with available data reported smaller childto-staff ratios than child-to-teacher ratios. Among these countries, the child-to-staff ratios are substantially lower
than child-to-teacher ratios (at least three children or fewer) only in Austria, Brazil, Chile, France, Lithuania and
Norway (Table B2.2).
Child-to-staff ratio matters more for interactions with children under the age of 3 than with children age 3 to age 5
(OECD, 2018[13]). In most countries, the ratios of children to teacher are smaller in early childhood development
programmes than in pre-primary education. On average across the 11 OECD countries with available data for
both programmes, there are 14 children for each teacher working in pre-primary education, while the ratio is only
8 children per teacher in early childhood development programmes (Table B2.2).

Figure B2.5. Changes in number of children, number of teachers and number of children
per teacher in pre-primary education (2005, 2016)
Index of change between 2005 and 2016 (2005 = 100), based on head counts

Russian Federation

Chile

France2

Portugal

Hungary

Czech Republic

United States

Israel

Lithuania

Italy

Slovenia

EU22 average

OECD average

Belgium

Spain

Greece

Mexico

Austria

Switzerland

Germany1

Luxembourg

Poland

190
180
170
160
150
140
130
120
110
100
90
80
70
60

Slovak Republic

Change in number of children
Change in number of teachers
Change in number of children per teacher

Index
of change

1. Year of reference 2006 instead of 2005.
2. Excluding independent-private institutions.
Countries are ranked in ascending order of the change over the period 2005-2016 in number of children per teacher in pre-primary education (ISCED 02).
Source: OECD (2018), Table B2.2. See Source section at the end of this indicator for more information and Annex 3 for notes (http://dx.doi.
org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933803292

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Over the last decade, many countries have implemented policies to increase participation in ECEC and reduce
child‑to-staff ratios. As a result, the number of children per teacher has fallen between 2005 and 2016 in two‑thirds
of the 20 OECD countries with available data for pre-primary education. On average, the number of children
enrolled in pre-primary education increased by 18% between 2005 and 2016, a period over which the number of
teachers increased by 29%. However, some exceptions exist. In Chile, the Czech Republic, France, Hungary, Portugal,
the Russian Federation and the United States, the number of children per teacher is higher in 2016 than a decade
ago (Figure B2.5).

Definitions
ECEC services: The types of ECEC services available to children and parents differ greatly. Despite those differences,
most ECEC settings typically fall into one of the following categories ([OECD, 2017[4]] and Table B2.4):

• Regular centre-based ECEC: More formalised ECEC centres typically belong to one of these three sub-categories:
−− Centre-based ECEC for children under the age of 3: Often called “crèches”, these settings may have an educational
function, but they are typically attached to the social or welfare sector and associated with an emphasis on care.
Many of them are part time and provided in schools, but they can also be provided in designated ECEC centres.
−− Centre-based ECEC for children from the age of 3: Often called kindergarten or pre-school, these settings tend to
be more formalised and are often linked to the education system.
−− Age-integrated centre-based ECEC for children from birth or age 1 up to the beginning of primary school: Called
kindergarten, pre-school, or pre-primary, these settings offer a holistic pedagogical provision of education and
care (often full-day).

• Family day care ECEC: Licensed home-based ECEC, which is most prevalent for children under age 3. These
settings may or may not have an educational function and be part of the regular ECEC system.

• Licensed or formalised drop-in ECEC centres: Often receiving children across the entire ECEC age bracket and
even beyond, these drop-in centres allow parents to complement home-based care by family members or family
day care with more institutionalised services on an ad-hoc basis (without having to apply for a place).
Some of these ECEC services are in adherence with the criteria defined in the ISCED 2011 classification (see ISCED 0
definition). Others are considered an integral part of countries’ ECEC provision but are not in adherence with all the
ISCED criteria. Figure B2.1 and Table B2.4 make the distinction between these two categories explicit.
Informal care services: Generally unregulated care arranged by the child’s parent either in the child’s home or
elsewhere, provided by relatives, friends, neighbours, babysitters or nannies, these services are not covered in this
indicator.
ISCED level 0 refers to early childhood programmes that have an intentional education component. To be reported
in ISCED level 0, a programme must:

• have adequate intentional educational or pedagogical properties
• take place in an institutionalised setting (usually school-based or otherwise institutionalised for a group of
children)

• meet a minimum intensity/duration (an intensity of at least 2 hours per day and a duration of at least 100 days
a year)

• have a regulatory framework recognised by the relevant national authorities (e.g. curriculum, guidelines,
standards or instructions)

• be delivered by trained or accredited staff (e.g. requirement of pedagogical qualifications for educators)
There are two categories of ISCED level 0 programmes, which are classified depending on age and the level of
complexity of the educational content:

• ISCED 01 refers to early childhood educational development programmes, typically aimed at children under
age 3. The learning environment is visually stimulating, and the language is rich and fosters self-expression,
with an emphasis on language acquisition and the use of language for meaningful communication. There are
opportunities for active play so that children can exercise their co-ordination and motor skills under supervision
and in interaction with staff.

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• ISCED 02 refers to pre-primary education programmes, aimed at children in the years immediately prior to
starting compulsory schooling, typically aged between age 3 and age 5. Through interaction with peers and
educators, children improve their use of language and their social skills, start to develop logical and reasoning
skills, and talk through their thought processes. They are also introduced to alphabetical and mathematical
concepts, understanding and use of language, and are encouraged to explore their surrounding world and
environment. Supervised gross motor activities (i.e. physical exercise through games and other activities) and
play-based activities can be used as learning opportunities to promote social interactions with peers and to
develop skills, autonomy and school readiness.
Equivalised disposable income tertile refers to the disposable (i.e. post-tax and post-transfer) income of the
household in which the child lives, equivalised using the square root scale to account for the effect of family size
on the household’s standard of living. The income tertiles are calculated based on the distribution by equivalised
disposable income of children aged less than or equal to 12.
Mother’s educational attainment measures whether or not the mother of the enrolled child has attained tertiary
education (highest level of education attained at ISCED levels 5 to 8).
Please see Indicators C1, C2 and D2 for definitions of Expenditure per student on educational institutions,
Expenditure on educational institutions relative to GDP, and Child-to-staff ratios.

Methodology
The concepts used to define full-time and part-time participation at other ISCED levels, such as study load, child
participation, and the academic value or progress that the study represents, are not easily applicable to ISCED
level 0. In addition, the number of daily or weekly hours that represent typical full-time enrolment in an education
programme at ISCED level 0 varies widely between countries. Because of this, full-time-equivalents cannot be
calculated for ISCED level 0 programmes in the same way as for other ISCED levels.
For data-reporting purposes, countries separate ISCED level 0 data into ISCED 01 and ISCED 02 by age only, as
follows: data from age-integrated programmes designed to include children younger and older than 3 are allocated
to 01 and 02 according to the age of the children. This may involve estimation of expenditure and personnel at
levels 01 and 02.
For more information please see the OECD Handbook for Internationally Comparative Education Statistics 2018 (OECD,
2018[18]) and Annex 3 for country-specific notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Lithuania was not an OECD member at the time of preparation of this publication. Accordingly, Lithuania does not
appear in the list of OECD members and is not included in the zone aggregates.

Source
Data refer to the school year 2015/16 and financial year 2015 and are based on a special survey administered by the
OECD in 2017 (for details see Annex 3 at http://dx.doi.org/10.1787/eag-2018-36-en).
Data from Argentina, China, Colombia, India, Indonesia, Saudi Arabia and South Africa are from the UNESCO
Institute of Statistics (UIS).
Data on subnational regions for selected indicators have been released by the OECD, with support from the
US National Centre for Education Statistics (NCES) and are currently available for 14 countries: Austria, Colombia,
Finland, Germany, Ireland, Italy, Korea, Poland, the Russian Federation, Slovenia, Spain, Sweden, Turkey and
the United States. Subnational estimates were provided by countries using national data sources or were calculated
by Eurostat based on data for Level 2 of the Nomenclature of Territorial Units for Statistics (NUTS 2) for all countries
except the United Kingdom (NUTS 1).

Note regarding data from Israel
The statistical data for Israel are supplied by and are under the responsibility of the relevant Israeli authorities. The use
of such data by the OECD is without prejudice to the status of the Golan Heights, East Jerusalem and Israeli settlements
in the West Bank under the terms of international law.

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Duncan, G. and K. Magnuson (2013), “Investing in preschool programs”, Journal of Economic Perspectives, Vol. 27/2, [5]
pp. 109-132, http://dx.doi.org/10.1257/jep.27.2.109.
EACEA P9 Eurydice (2009), Tackling Social and Cultural Inequalities through Early Childhood Education and Care in Europe, [14]
Education, Audiovisual & Culture Executive Agency, http://dx.doi.org/10.2797/18055.
Magnuson, K. and J. Waldfogel (2006), “Preschool and school readiness of children of immigrants”, Social Science Quarterly, [12]
Vol. 87/5, pp. 1241-1262, http://dx.doi.org/10.1111/j.1540-6237.2006.00426.x.
OECD (2018), Engaging Young Children: Lessons from Research about Quality in Early Childhood Education and Care, Starting [13]
Strong, OECD Publishing, Paris, http://dx.doi.org/10.1787/9789264085145-en.
OECD (2018), “How does access to early childhood education services affect the participation of women in the labour [1]
market?”, Education Indicators in Focus, No. 59, OECD Publishing, Paris, http://dx.doi.org/10.1787/232211ca-en.
OECD (2018), OECD Family Database, www.oecd.org/els/family/database.htm.

[7]

OECD (2018), OECD Handbook for Internationally Comparative Education Statistics 2018: Concepts, Standards, Definitions [18]
and Classifications, OECD Publishing, Paris, https://doi.org/10.1787/9789264304444-en.
OECD (2018), OECD Online Education Database, www.oecd.org/education/database.htm.

[17]

OECD (2017), Starting Strong 2017: Key OECD Indicators on Early Childhood Education and Care, Starting Strong, OECD [4]
Publishing, Paris, http://dx.doi.org/10.1787/9789264276116-en.
OECD (2016), International Migration Outlook 2016, OECD Publishing, Paris, http://dx.doi.org/10.1787/migr_outlook- [11]
2016-en.
OECD (2016), Walking the Tightrope: Background Brief on Parents’ Work-Life Balance across the Stages of Childhood, OECD, [3]
www.oecd.org/social/family/Background-brief-parents-work-life-balance-stages-childhood.pdf.
OECD (2016), Who Uses Childcare? Background Brief on Inequalities in the Use of Formal Early Childhood Education and Care [8]
(ECEC) among Very Young Children, OECD, Paris, www.oecd.org/els/family/Who_uses_childcare-Backgrounder_inequalities_
formal_ECEC.pdf.
OECD (2011), How’s Life?: Measuring Well-being, OECD Publishing, Paris, http://dx.doi.org/10.1787/9789264121164-en. [2]
OECD/Eurostat/UNESCO Institute for Statistics (2015), ISCED 2011 Operational Manual: Guidelines for Classifying National [6]
Education Programmes and Related Qualifications, OECD Publishing, Paris, http://dx.doi.org/10.1787/9789264228368-en.
OECD/NCES (2018), Education at a Glance Subnational Supplement, OECD/National Center for Education Statistics, Paris [9]
and Washington, DC, https://nces.ed.gov/surveys/annualreports/oecd/index.asp.
Pianta, R. et al. (2005), “Features of pre-kindergarten programs, classrooms, and teachers: Do they predict observed [16]
classroom quality and child-teacher interactions?”, Applied Developmental Science, Vol. 9/3, pp. 144-159, http://dx.doi.
org/10.1207/s1532480xads0903_2.
Shin, E. (2009), A Survey on the Development of the Pre-school Free Service Model, Korean Educational Development Institute. [10]
Stewart, K. and J. Waldfogel (2017), Closing Gaps Early: The Role of Early Years Policy in Promoting Social Mobility in England, [15]
The Sutton Trust, London.

Indicator B2 Tables
1 2 https://doi.org/10.1787/888933803121

Table B2.1a Enrolment rates in early childhood education and care and primary education, by age (2016)
Table B2.1b Trends in enrolment rates in early childhood education and care (ECEC) and primary education,
by age (2005, 2010, 2015 and 2016)
WEB Table B2.1c Participation of children under the age of 3 in early childhood education and care,
by socio-economic profile (2016)
Table B2.2 Enrolment of children in early childhood education and care by type of institution and ratio
of children to teaching staff (2016)
Table B2.3a Expenditure on early childhood education and care (ISCED 0) (2005, 2010, 2014 and 2015)
WEB Table B2.3b Relative proportions of public and private expenditure on early childhood education and care (ISCED 0)
(2005 to 2015)
WEB Table B2.4 Coverage of early childhood education and care in OECD and partner countries
Cut-off date for the data: 18 July 2018. Any updates on data can be found on line at http://dx.doi.org/10.1787/eag-data-en. Data can also be found
at http://stats.oecd.org/, Education at a Glance Database.

174 Education at a Glance 2018: OECD Indicators   © OECD 2018

How do early childhood education systems differ around the world? – INDICATOR B2

chapter B

Under embargo until 11/09/2018 at 11.00am CEST
Table B2.1a. Enrolment rates in early childhood education and care (ECEC) and primary education,

by age (2016)

Age 6

Other registered
ECEC services

Total

ECEC services
(ISCED 0)

Other registered
ECEC services

Total

ECEC services
(ISCED 0)

Primary education
(ISCED 1)

Total

Pre-primary
(ISCED 02)

Primary education
(ISCED 1)

Total

Pre-primary
(ISCED 02)

Primary education
(ISCED 1)

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

(13)

(14)

(15)

(16)

(17)

(18)

(19)

(20)

(21)

Australia
Austria
Belgium
Canada
Chile
Czech Republic
Denmark
Estonia
Finland
France1
Germany
Greece1
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Luxemboug2
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United Kingdom
United States

29
7
x(7)
m
13
0
41
6
16
0
24
2
1
24
a
48
m
0
36
m
0
1
a
31
37
0
28
0
23
24
24
m
m
x(7)
m

1
x(8)
x(8)
a
a
x(8)
x(8)
1
m
x(8)
a
m
4
17
x(8)
a
m
m
a
m
m
a
x(8)
m
0
x(8)
1
x(8)
m
m
1
m
m
m
m

30
x(9)
x(9)
m
13
x(9)
41
7
16
x(9)
24
m
4
41
x(9)
48
m
m
36
m
m
1
x(9)
31
37
x(9)
29
x(9)
23
24
25
m
m
m
m

57
41
53
m
33
16
90
64
58
12
65
11
14
95
a
73
16
1
87
m
4
5
a
66
92
9
49
16
70
57
88
m
1
51
m

1
x(8)
x(8)
a
a
x(8)
x(8)
7
m
x(8)
a
m
28
0
x(8)
a
m
m
a
m
m
a
x(8)
m
0
x(8)
1
x(8)
m
m
2
m
a
m
m

58
41
53
m
33
16
90
71
58
x(9)
65
m
42
95
x(9)
73
m
m
87
m
m
5
x(9)
66
92
x(9)
50
x(9)
70
57
90
m
1
m
m

38
18
45
m
20
5
57
25
30
4
37
5
5
48
a
56
5
0
53
m
1
2
a
43
55
3
35
5
39
35
45
m
0
18
m

1

63

1

91
92

99

99

m
56
78
97
90
73

m
86
91
98
92
79

2
41
4
0
16
46
7

57
95
100
81
48
92
1
0
99
63

98
98
100
97
94
99

0

97
89
67

a
m
m

45

a

86
89
96
71
83
67
84
96
92
2
9
100
38

2
m

95
93
93
93
91
96
93
97
86
90
71
90
96
94
48
34
100
67

80
0
1
0
0
0
2
0
0
1
0
0
0
2
92
0
8
0
1
0
5
24
0
95
0
0
0
0
0
0
0
1
15

100
97
99
95
95
91
98
93
84

84

20
97
98
95
95
91
95
93
84
100
97
94
96
96
0
96
88
96
90
97
91
76
99
3
97
98
95
82
92

100

m
0
a
a
m
m
3
m
m
a
m
13
0
m
a
0

89
92

99

76
99
m
56
78
97
87
73
99
92
27
85
97
49
100
92

64
76

56
m
0
9
1
2
m
m
1
m
a
m
m

39
20
60
m
20
7
62
28
30
36
37
m
17
60
17
56
m
m
53
m
55
2
56
43
55
12
36
8
39
35
46
m
0
m
m

OECD average
EU22 average

16
11

m
m

25
21

45
41

m
m

45
41

25
22

9
11

34
33

75
81

Argentina3
Brazil
China
Colombia
Costa Rica
India
Indonesia
Lithuania
Russian Federation
Saudi Arabia
South Africa3

2
13
m
50
1
m
3
6
4
a
m

m
m
m
m
m
m
m
a
m
m
m

m

10
39
m
47
3
m
12
58
48
a
m

m
m
m
m
m
m
m
a
m
m
m

m

39
m
47
m
m
m
58
48
m
m

5
22
m
49
2
m
6
23
18
a
m

m

13
m
50
m
m
m
6
4
m
m

m
m
m
m
m
m
a
m
m
m

m
22
m
49
m
m
m
23
18
m
m

G20 average

m

m

m

m

m

m

m

m

m

m

2
14
a
a
2
5
3
m
32

a
m
12
12
17

a
m
m
a
m
53
a

99

100

96
65
95
98
59
98

m
m
m
2
m
a
m
m

92
27
98
97
49
100
92
84
97
89
67
45
88
89
96
71
83
67
84
96
95
2
9
100
38

95
93
93
93
91
96
93
97
86
90
71
90
96
94
48
34
100
67

2
0
0
m
0
0
0
0
0
0
0
0
0
0
31
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
3
0

1
1

76
82

87
90

1
2

88
91

40

m

62
m
49
5
m
35
78
79
5
5

m
m
m
m
m
m
a
m
m
m

40
62
m
49
5
m
35
78
79
5
5

85
90
m
44
64
m
71
84
84
22
8

0
0
m
0
0
m
0
0
0
0
0

m

m

m

m

0

m
0

96

99

m
86
91
98
92
79

92

97

97

4

91

98
1
35
3
60
0
0
14
1
0
0
93
5
1
0
0
1
21
8
39
7
1
97
55
0
0
22

82
85

12
9

95
95

22
30

85
90
m
44
64
m
71
84
84
22
8

99
90
m
56
90
m
96
90
91
45
17

1
7
m
18
0
m
3
0
0
5
22

99
97
m
74
91
m
99
90
91
50
39

m

m

m

m

100

96
65
95
98
90
98
96

98

95
98
55
0
87

100

97
94
96
98
92
97
96

96
90
97
95
100
99
98

97
98
95
82
92
98

95
99
70

Total

ECEC services
(ISCED 0)

B2

Total

Age 5

Other registered
ECEC services

Age 4

ECEC services
(ISCED 0)

Age 3

Total

Under the age of 3

Other registered
ECEC services

Age 2

ECEC services
(ISCED 0)
Partners

OECD

Under the age of 2

93

98
100
98

93

96

30
99
97
83

91
99
97
97

96
100

97
100

95
4
93
99
100

95
97

99

99
74

99
100

100
99
100

95

89

97

49
90
97
1
45
94

89
97
98

99
100

94

98

98

81

100

76
67

98
97

1 100 100
10
92 100
m
m
m
7
76
82
1
88
89
m
m
m
x(21) x(21) 100
95
4
99
81
11
92
2
96
97
22
53
75
m

m

m

Note: Early childhood education = ISCED 0, other registered ECEC services = ECEC services outside the scope of ISCED 0, because they are not in adherence with all
ISCED criteria. To be classified in ISCED 0, ECEC services should: 1) have an adequate intentional educational properties; 2) be institutionalised (usually school-based
or otherwise institutionalised for a group of children); 3) have an intensity of at least 2 hours per day of educational activities and a duration of at least 100 days a
year; 4) have a regulatory framework recognised by th e relevant national authorities (e.g. curriculum); and 5) have trained or accredited staff (e.g. requirement of
pedagogical qualifications for educators).
1. For France, data for “Other registered ECEC services” come from the survey “Enquête Modes de garde et d’accueil des jeunes enfants 2013” conducted by the
statistical division of the French Ministry for Solidarities and Health (DREES). Figures refer to the primary custody arrangements. For Greece, ECEC data include
only part of the children enrolled in early childhood development programmes (ISCED 01).
2. Year of reference 2014 instead of 2016 for children under the age of 3 enrolled in “Other registered ECEC services”. Data come from the OECD family database
(www.oecd.org/els/family/database.htm).
3. Year of reference 2015 instead of 2016.
Source: INES ad-hoc survey and OECD/UIS/Eurostat (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933803140

Education at a Glance 2018: OECD Indicators   © OECD 2018

175

chapter B Access to Education, Participation and Progression
Under embargo until 11/09/2018 at 11.00am CEST
Table B2.1b. Trends in enrolment rates in early childhood education and care (ECEC) and primary education,

by age (2005, 2010, 2015 and 2016)

Index of change between
2005 and 2016 (2005 = 100)
in enrolment rates in ECEC
and primary education
of children aged 3 to 5

B2

2005

2010

2015

2016

2005

2010

2015

2005

2010

2015

2005

2010

2015

2005

2010

2015

2016

Change in number
of children enrolled

Change in
population

Change in
enrolment rates

Partners

OECD

Enrolment rates in ECEC and primary education

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

(13)

(14)

(15)

(16)

(17)

(18)

(19)

(20) = (18)/(19)

Australia
Austria
Belgium
Canada
Chile
Czech Republic
Denmark1
Estonia
Finland1
France1
Germany2
Greece1
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Luxembourg3
Mexico
Netherlands
New Zealand1
Norway
Poland
Portugal
Slovak Republic1
Slovenia1
Spain1
Sweden
Switzerland
Turkey
United Kingdom
United States

m
m
m
m
m
m
m
m
25
9
17
m
7
53
m
m
m
16
m
m
m
2
m
m
33
3
21
7
25
15
m
m
m
m
m

38
12
m
m
m
m
m
23
27
5
27
m
10
55
m
m
m
19
38
m
m
2
m
m
53
4
27
3
34
26
46
m
m
m
m

39
19
m
m
19
4
58
24
28
4
37
m
16
60
m
28
m
23
52
m
m
2
56
42
55
9
35
5
38
34
46
m
m
m
m

39
20
60
m
20
7
62
28
30
4
37
m
17
60
17
56
m
m
53
m
55
2
56
43
55
12
36
5
39
35
46
m
0
m
m

m
51
100
m
23
66
m
m
62
100
80
m
85
94
m
66
99
69
m
66
62
26
82
m
83
29
64
61
67
94
m
9
2
m
39

73
66
99
m
38
60
87
85
67
99
90
m
84
95
m
78
95
75
80
73
73
37
84
m
95
46
78
60
84
96
95
4
4
m
41

70
75
98
m
56
77
97
86
68
99
93
26
94
97
38
100
92
80
92
87
66
46
83
89
95
66
82
60
83
95
94
3
9
100
43

m
83
100
m
42
91
m
m
69
100
89
m
91
95
m
84
100
95
m
73
95
69
98
m
89
38
79
74
76
99
m
39
5
m
68

51
90
99
m
75
86
97
90
73
100
96
m
93
97
m
83
99
97
84
82
97
85
100
m
97
59
87
73
100
97
98
41
17
m
65

90
93
99
m
87
85
98
91
74
100
97
66
95
97
89
98
96
94
91
92
95
89
96
94
97
79
91
76
89
97
95
47
32
100
66

m
93
100
m
53
97
m
m
73
100
93
79
97
97
97
91
100
99
m
94
94
96
100
m
91
49
89
85
84
100
m
91
32
100
93

99
96
99
m
87
93
98
91
77
100
97
95
96
96
100
96
99
99
90
93
93
100
99
m
97
76
96
82
99
99
99
95
61
99
92

100
97
99
95
94
91
99
92
79
100
98
94
95
94
96
97
97
97
93
96
99
100
99
97
98
95
97
81
92
98
97
98
72
98
91

m
76
100
m
39
85
m
m
68
100
88
m
87
95
m
80
100
87
m
77
84
64
93
m
88
38
78
74
75
98
m
47
13
m
66

74
86
99
m
67
79
94
89
73
100
94
m
87
96
m
86
98
90
85
82
87
78
94
m
96
60
87
72
94
97
97
47
27
m
66

87
90
99
m
79
85
98
90
74
100
96
64
91
96
74
99
95
90
92
92
86
82
93
94
97
80
90
72
88
97
95
49
38
100
67

85
90
99
m
79
87
98
91
79
100
95
63
92
97
77
99
95
92
93
93
85
83
95
93
97
85
90
73
89
97
96
50
37
100
66

m
123
112
m
176
129
m
m
125
103
101
m
100
110
m
152
96
93
m
119
114
126
89
m
117
235
97
109
145
111
m
120
251
m
102

122
103
113
113
87
126
93
118
108
103
93
97
94
107
134
122
102
89
82
100
113
97
88
110
106
106
84
110
124
112
129
112
90
120
103

m
119
99
m
201
102
m
m
116
99
108
m
106
103
m
124
94
105
m
120
101
130
101
m
110
222
115
100
117
99
m
106
279
m
99

OECD average
Average for
countries with
available data for
all reference years
EU22 average

18

25

31

33

63

71

75

78

84

88

88

94

95

76

83

86

86

126

106

119

20

25

30

31

61

70

76

76

84

87

86

93

94

75

80

84

85

126

104

122

14

20

28

31

73

80

80

85

90

91

91

94

95

83

88

89

89

119

108

111

Argentina
Brazil1
China
Colombia1
Costa Rica1
India
Indonesia
Lithuania
Russian Federation1
Saudi Arabia
South Africa

m
m
m
m
m
m
m
13
21
m
m

m
m
m
m
m
m
m
16
17
m
m

5
21
m
29
2
m
3
22
18
m
m

m
22
m
49
2
m
6
23
18
m
m

m
m
m
m
m
m
m
53
51
m
m

m
m
m
m
m
m
m
68
63
m
m

40
61
m
60
5
m
24
77
76
1
5

m
m
m
m
m
m
m
58
54
m
m

m
61
m
m
m
m
m
73
74
m
m

85
84
m
81
61
m
67
86
88
10
8

m
m
m
m
m
m
m
65
54
m
m

m
72
m
m
m
m
m
77
78
m
m

99
93
m
95
89
m
100
89
87
37
39

m
m
m
m
m
m
m
59
53
m
m

m
m
m
m
m
m
m
72
71
m
m

m
80
m
78
52
m
65
84
83
16
17

75
80
m
78
53
m
68
84
83
25
m

m
m
m
m
m
m
m
131
216
m
m

m
82
m
98
93
m
m
91
136
m
m

m
m
m
m
m
m
m
144
159
m
m

G20 average

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

Under the age of 3

Age 3

Age 4

Age 5

Ages 3 to 5

ISCED 0
and other registered
ECEC services

ISCED 0
and primary
education

ISCED 0
and primary
education

ISCED 0
and primary
education

ISCED 0
and primary
education

Note: Early childhood education = ISCED 0, other registered ECEC services = ECEC services outside the scope of ISCED 0, because they are not in adherence with
all ISCED criteria. To be classified in ISCED 0, ECEC services should: 1) have an adequate intentional educational properties; 2) be institutionalised (usually schoolbased or otherwise institutionalised for a group of children); 3) have an intensity of at least 2 hours per day of educational activities and a duration of at least 100 days
a year; 4) have a regulatory framework recognised by the relevant national authorities (e.g. curriculum); and 5) have trained or accredited staff (e.g. requirement of
pedagogical qualifications for educators).
1. Includes only early childhood education and care (ISCED 0) for children under the age of 3. For Greece, ECEC data include only part of the children enrolled in early
childhood development programmes (ISCED 01).
2. Year of reference 2006 instead of 2005.
3. Year of reference 2014 instead of 2016 for children under the age of 3 enrolled in “Other registered ECEC services”. Data come from the OECD family database
(www.oecd.org/els/family/database.htm).
Source: INES ad-hoc survey and OECD/UIS/Eurostat (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933803159

176 Education at a Glance 2018: OECD Indicators   © OECD 2018

How do early childhood education systems differ around the world? – INDICATOR B2

chapter B

Under embargo until 11/09/2018 at 11.00am CEST
Table B2.2. Enrolment of children in early childhood education and care (ISCED 0) by type of institution

and ratio of children to teaching staff (2016)

Early childhood educational development programmes = ISCED 01, pre-primary education = ISCED 02
Distribution of children
in ISCED 01,
by type of institution

Distribution of children
in ISCED 02,
by type of institution

Public

Public

Independent private

Total

Children to contact staff
(teachers and teachers’ aides)

Children to teaching staff

Children to contact staff
(teachers and teachers’ aides)

Children to teaching staff

Children to contact staff
(teachers and teachers’ aides)

Children to teaching staff

Change in number of children
enrolled

Change in number of teachers

Change in number of children
per teacher

Total (ISCED 0)

Government-dependent private

ISCED 02

Total

ISCED 01

Independent private

Private

Ratio of children
to staff in full-time equivalents,
by type of ECEC service

Government-dependent private

Partners

OECD

Private

Index of change between 2005
and 2016 (2005 = 100) in number
of children per teacher in
pre-primary education (ISCED 02)
(based on head counts)

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

(13)

(14)

(15)

(16)

(17) = (15) /(16)

Australia
Austria
Belgium
Canada
Chile
Czech Republic
Denmark
Estonia
Finland
France1
Germany2
Greece1
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United Kingdom
United States

m
33
16
m
68
a
85
x(5)
80
a
27
62
86
83
a
a
a
a
9
m
a
36
a
1
48
a
4
a
94
51
81
a
a
18
m

m
x(4)
74
m
30
a
15
a
20
a
x(4)
a
8
17
a
33
a
a
91
m
a
a
a
99
52
a
79
a
6
15
19
a
a
78
a

m
x(4)
11
m
2
a
0
x(7)
a
a
x(4)
38
7
0
a
67
a
a
a
m
a
64
a
a
a
a
18
a
0
33
0
a
100
4
m

m
67
84
m
32
a
15
x(8)
20
a
73
38
14
17
a
100
a
a
91
m
a
64
a
99
52
a
96
a
6
49
19
a
100
82
m

16
71
47
93
32
96
79
96
88
87
35
91
90
85
2
63
72
26
21
93
89
86
70
1
52
78
53
94
95
68
83
95
84
52
59

84
x(8)
53
x(8)
61
4
21
a
12
13
x(8)
a
7
15
0
30
0
a
79
a
0
a
a
99
48
3
31
6
4
29
17
1
a
43
a

a
x(8)
0
x(8)
7
a
0
4
a
0
x(8)
9
3
0
98
7
28
74
a
7
11
14
30
a
a
20
16
a
0
4
0
4
16
5
41

84
29
53
7
68
4
21
4
12
13
65
9
10
15
98
37
28
74
79
7
11
14
30
99
48
22
47
6
5
32
17
5
16
48
41

m
6
m
m
4
a
m
m
m
a
5
m
10
3
a
m
a
a
5
m
a
5
a
m
3
a
m
a
6
m
m
a
m
m
m

m
9
m
m
11
a
m
x(14)
m
a
5
m
10
3
a
m
a
a
5
m
a
14
a
m
9
a
m
a
6
10
m
a
m
m
m

m
9
15
m
10
13
m
m
m
15
9
m
12
5
m
m
13
14
13
m
11
25
14
m
6
m
m
12
9
m
m
m
m
m
11

m
13
15
m
25
13
m
x(14)
10
23
10
m
12
5
m
m
13
15
13
10
11
25
16
m
15
14
17
12
9
15
m
m
17
m
13

m
8
m
m
10
13
m
m
m
15
7
m
12
4
m
m
13
14
9
m
11
21
14
m
5
m
m
12
8
m
5
m
m
m
m

m
12
m
m
24
13
m
8
m
23
8
m
12
4
m
m
13
15
9
10
11
24
16
m
12
14
m
12
8
13
13
m
m
m
m

m
118
112
m
152
137
m
m
m
98
98
115
95
m
m
151
97
93
m
m
116
118
m
m
m
138
100
107
146
127
m
107
m
m
105

m
148
123
m
123
125
m
m
m
84
128
132
87
m
m
153
99
m
m
m
155
148
m
m
m
190
91
119
151
144
m
139
m
m
103

m
79
90
m
123
109
m
m
m
117
76
87
110
m
m
99
98
m
m
m
75
80
m
m
m
73
110
90
97
88
m
77
m
m
102

OECD average
EU22 average

44
53

m
m

m
m

56
47

67
74

m
m

m
m

33
26

5
7

8
8

12
12

14
13

11
11

13
13

118
115

129
127

92
90

Argentina3
Brazil
China
Colombia
Costa Rica
India
Indonesia
Lithuania
Russian Federation
Saudi Arabia
South Africa3

44
64
a
100
23
a
0
90
99
a
m

x(4)
a
a
a
x(4)
a
x(4)
a
a
a
m

x(4)
36
a
a
x(4)
a
x(4)
10
1
a
m

56
36
a
a
77
a
100
10
1
a
m

68
76
46
77
88
23
5
96
99
56
94

x(8)
a
x(8)
a
x(8)
5
x(8)
a
a
x(8)
x(8)

x(8)
24
x(8)
23
x(8)
72
x(8)
4
1
x(8)
x(8)

32
24
54
23
12
77
95
4
1
44
6

m
8
a
m
8
a
m
7
x(13)
a
m

m
14
a
m
8
a
32
10
x(14)
a
m

m
18
m
m
12
m
m
7
x(13)
m
30

m
21
19
33
12
m
11
10
x(14)
11
30

m
12
m
m
11
m
m
7
7
m
m

m
18
19
m
11
m
18
10
11
11
m

m
m
m
m
m
m
m
119
174
m
m

m
m
m
m
m
m
m
121
102
m
m

m
m
m
m
m
m
m
98
170
m
m

m

m

m

m

58

m

m

42

m

m

m

17

m

15

m

m

m

G20 average

1. Data for Columns 11 to 17 represent public and government-dependent private institutions only.
2. Year of reference 2006 instead of 2005.
3. Year of reference 2015 instead of 2016.
Source: OECD/UIS/Eurostat (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933803178

Education at a Glance 2018: OECD Indicators   © OECD 2018

177

B2

chapter B Access to Education, Participation and Progression
Under embargo until 11/09/2018 at 11.00am CEST
Table B2.3a. Expenditure on early childhood education and care (ISCED 0) and change in expenditure

as a percentage of GDP in pre-primary education (2005, 2010, 2014 and 2015)
Public and private institutions

B2

Annual expenditure per child in USD,
converted using PPPs (2015)

Expenditure on ECEC services
as a percentage of GDP (2015)

Partners

OECD

ISCED 0

Total

Early
childhood
educational
development
(ISCED 01)

Pre-primary
(ISCED 02)

Total

2005

2010

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

7 123
11 815
m
m
9 148
a
m
x(3)
19 423
a
14 769
m
6 818
17 349
a
2 713
a
a
m
m
a
x(3)
a
15 506
24 228
a
m
a
10 520
8 166
16 917
a
x(3)
9 560
m

7 097
9 439
7 929
m
5 100
4 953
m
x(3)
10 654
7 813
9 827
5 249
6 836
12 339
6 106
5 021
6 249
7 499
7 814
5 313
20 495
x(3)
8 352
12 209
13 457
6 222
7 099
5 811
7 844
6 596
14 212
m
x(3)
8 957
10 830

7 112
9 824
m
m
5 910
4 953
m
6 514
12 332
7 813
11 122
m
6 835
13 886
6 106
4 185
6 249
7 499
m
m
20 495
2 685
8 352
13 466
17 225
6 222
m
5 811
8 610
6 977
14 917
m
3 591
9 048
m

0.3
0.1
0.1
m
0.4
a
m
x(6)
0.4
a
0.3
m
0.0
0.7
a
0.3
a
a
m
m
a
x(6)
a
0.4
0.9
a
m
a
0.4
0.2
0.6
a
x(6)
0.1
m

0.3
0.5
0.7
m
0.8
0.5
m
x(6)
0.9
0.7
0.6
0.3
0.8
1.1
0.1
0.9
0.5
0.2
0.6
0.8
0.6
x(6)
0.4
0.5
0.9
0.7
0.6
0.6
0.7
0.6
1.4
0.4
x(6)
0.4
0.4

0.6
0.7
0.8
m
1.1
0.5
m
1.2
1.2
0.7
0.9
m
0.9
1.7
0.1
1.1
0.5
0.2
m
m
0.6
0.6
0.4
1.0
1.8
0.7
m
0.6
1.1
0.8
1.9
0.4
0.2
0.5
m

0.1
m
0.6
m
0.5
m
m
m
0.7
0.7
0.5
m
0.8
m
m
0.7
m
0.2
0.1
0.6
m
m
0.4
m
m
0.6
m
0.5
0.6
m
m
0.2
m
m
0.4

0.1
m
0.6
m
0.7
m
m
m
0.8
0.7
0.5
m
m
m
m
0.8
m
0.2
0.3
0.9
m
m
0.4
m
m
0.6
m
0.5
0.7
m
m
0.2
m
m
0.5

0.2
0.5
0.7
m
0.9
0.5
m
1.2
0.9
0.8
0.6
m
m
1.1
0.1
0.8
0.5
0.2
0.5
0.9
0.6
m
0.4
0.6
0.9
0.8
0.6
0.6
0.8
0.6
1.4
0.2
m
0.4
0.4

12 433

8 528

8 759

0.2

0.6

0.8

0.5

0.5

0.6

m

m

m

m

0.6

m

0.5

0.5

0.6

12 249

8 298

8 952

0.2

0.6

0.8

0.6

0.6

0.7

m
m
m
m
m
m
x(3)
5 589
x(3)
m
m

m
m
m
1 250
m
m
x(3)
5 457
x(3)
m
m

m
3 846
m
m
m
m
170
5 479
5 062
m
m

x(6)
m
m
0.1
0.1
m
x(6)
0.1
x(6)
m
m

x(6)
0.7
m
0.4
0.4
m
x(6)
0.7
x(6)
m
m

0.4
m
m
0.5
0.5
m
0.1
0.8
1.0
m
m

m
0.4
m
m
m
m
m
0.5
m
m
m

m
0.4
m
m
m
m
m
0.7
m
m
m

m
0.6
m
0.3
m
m
m
0.6
1.0
m
m

m

m

m

m

m

m

m

m

m

Early
childhood
educational
development
(ISCED 01)

Pre-primary
(ISCED 02)

(1)

Australia
Austria
Belgium1
Canada
Chile
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland2
Turkey
United Kingdom
United States
OECD average
Average for countries
with available data
for all reference years
EU22 average
Argentina2
Brazil2
China
Colombia
Costa Rica2
India
Indonesia
Lithuania
Russian Federation
Saudi Arabia
South Africa
G20 average

ISCED 0

Expenditure
on pre-primary education (ISCED 02)
as a percentage of GDP

2014

1. Public sources only for ISCED 01.
2. Public sources only for ISCED 01 and ISCED 02.
Source: INES ad-hoc survey and OECD/UIS/Eurostat (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933803197

178 Education at a Glance 2018: OECD Indicators   © OECD 2018

Under embargo until 11/09/2018 at 11.00am CEST

Under embargo until 11/09/2018 at 11.00am CEST

WHO IS EXPECTED TO GRADUATE FROM UPPER SECONDARY
EDUCATION?
INDICATOR B3

• On average across OECD countries, women make up 55% of upper secondary graduates in general
programmes, but this figure goes down to 46% for vocational programmes.

• On average across OECD countries, the average age in vocational programmes is higher than in
general programmes (for both men and women).

• Based on current patterns, it is estimated that on average across OECD countries, 81% of today’s
young people will graduate from upper secondary education before the age of 25, compared to 73%
in 2005.

Figure B3.1. Share of women among upper secondary graduates,
by programme orientation (2016)
%

General programmes

Vocational programmes

70
60
50
40
30
20
0

Italy
Czech Republic
Austria
Poland
Slovenia
Slovak Republic
Finland
Norway
Iceland
Switzerland
Estonia
Belgium
Portugal
Brazil
EU22 average
Russian Federation
France
Costa Rica
Spain
OECD average
Denmark
Germany
Colombia
Greece
Sweden
Luxembourg
Lithuania
Mexico
Latvia
Hungary
Netherlands
Turkey
Chile
Japan
Israel
Canada
Australia1
Ireland
New Zealand
United Kingdom
Korea

10

1. Year of reference 2015.
Countries are ranked in descending order of the share of women in general programmes.
Source: OECD / UIS / Eurostat (2018), Education at a Glance Database, http://stats.oecd.org/. See Source section at the end of
this indicator for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933803406

Context
Upper secondary education, which develops students’ basic skills and knowledge through either
academic or vocational pathways, aims to prepare students to enter further levels of education or
the labour market and to become engaged citizens. In many countries, this level of education is not
compulsory and can last from two to five years.
What is crucial, however, is to provide education of good quality that meets the needs of the labour
market and the economy. Given that inequality in upper secondary education is likely to translate into
inequality in tertiary education and in the labour market (see Indicator B7 and Chapter A), it is also
important to ensure that graduation from upper secondary education is not dependent on gender,
socio-economic or demographic background.
Graduating from upper secondary education has become increasingly important in all countries,
as the skills needed in the labour market are becoming more knowledge-based, and workers are
progressively required to adapt to the uncertainties of a rapidly changing global economy. However,
while graduation rates give an indication of the extent to which education systems are succeeding in
preparing students to meet the minimum requirements of the labour market, they do not capture the
quality of education outcomes.

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Other findings

• At the upper secondary level, first-time graduation rates exceed 75% in more than four out of five
countries with available data. At the post-secondary non-tertiary level, this rate is below 15% in
almost three out of four countries with available data.

INDICATOR B3

• In countries for which data are available for 2005, 2010 and 2016, first-time graduation rates
increased by 7 percentage points at the upper secondary level between 2005 and 2016. In contrast,
they remained constant (around 11%) at the post-secondary non-tertiary level.

• For both general and vocational programmes, students with at least one tertiary-educated parent
are more likely to complete upper secondary education than students whose parents have not
attained tertiary education.
Note
Graduation rates, when calculated for all ages, represent the estimated percentage of people from a
given age cohort that is expected to graduate within the country at some point during their lifetime.
This estimate is based on the number of graduates in 2016 and the age distribution of this group.
Graduation rates are based on both the population and the current pattern of graduation and are thus
sensitive to any changes in the education system, such as the introduction of new programmes and
changes in the duration of programmes. Graduation rates can be very high during a period when an
unexpected number of people go back to school.
When the age breakdown is not available, the gross graduation rate is calculated instead. This refers
to the total number of graduates divided by the average cohort of the population at the typical age
provided by the country.
In this indicator, age refers generally to the age of students at the beginning of the calendar year.
Students could be one year older than the age indicated when they graduate at the end of the school
year. Twenty-five is used as the upper age limit for completing secondary education because, across
OECD countries, more than 95% of graduates from upper secondary general programmes in 2016
were under 25 (see Education at a Glance Database). People who graduate from this level at age 25 or
older are usually enrolled in second-chance programmes. At the post-secondary non-tertiary level,
30 is considered to be the upper age limit for graduation.
In this edition of Education at a Glance, the focus is predominately on first-time graduates. The notion
of graduates (i.e. all graduates, not only first-time graduates) is used only when measuring graduates
by field of study (see Definitions section).

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Analysis
Profile of upper secondary graduates

B3

Profile of upper secondary graduates, by programme orientation
Although many countries have developed extensive vocational programmes at the secondary level, in most
countries, most students pursue general programmes. First-time upper secondary graduates are students who
obtained an upper secondary qualification for the first time. On average across OECD countries, 42% of first-time
upper secondary graduates obtained a qualification from a vocational programme. The share of first-time graduates
from vocational programmes is particularly low in Brazil, Canada, Colombia, Costa Rica, Greece, Hungary, Japan,
Korea and Lithuania (below 25%). In contrast, in Austria, the Czech Republic and the Slovak Republic, more than
65% first-time graduates obtained a qualification from a vocational programme.
Vocational education and training (VET) is an important part of upper secondary education in many OECD countries,
and it can play a central role in preparing young people for work, developing adults’ skills and responding to
labour-market needs (see Indicator A1). But in some countries, VET has been neglected and marginalised in
policy discussions, often overshadowed by the increasing emphasis on general academic education. However, an
increasing number of countries are recognising that good initial VET can make a major contribution to economic
competitiveness (OECD, 2015[1]).
Vocational programmes can be offered in combined school-based and work-based programmes, where less than
75% of the curriculum is presented in the school environment or through distance education. These include
apprenticeship programmes that involve concurrent school-based and work-based training, and programmes that
involve alternating periods of attendance at educational institutions and participation in work-based training. In
countries such as Austria, Denmark, Germany, Latvia and Switzerland, this type of dual system attracts at least 30%
of the students enrolled in upper secondary VET programmes (see Indicator B1). Through work-based learning,
students acquire the skills that are valued in the workplace. Work-based learning is also a way to develop publicprivate partnerships and to involve social partners and employers in developing VET programmes, often by defining
curricular frameworks.
Moreover, high-quality VET programmes can be effective in developing skills among those who would otherwise
lack the qualifications to ensure a smooth and successful transition into the labour market. Employment rates
tend to be higher, and inactivity rates lower, among young adults who graduated from vocational training than
among those who pursued an upper secondary general programme as their highest level of educational attainment
(see Education at a Glance Database). However, it is important to ensure that graduates of upper secondary
VET programmes have good employment opportunities, since VET can be more expensive than other education
programmes (see Indicator C1).

Profile of upper secondary graduates, by gender
The share of women tends to be significantly higher in upper secondary general programmes than in vocational
programmes. On average across OECD countries, women make up 55% of upper secondary graduates in general
programmes, compared to 46% in vocational programmes.
In almost all countries with available data, women make up at least half of upper secondary graduates from general
programmes, ranging from 49% in Korea to 60% in the Czech Republic and 62% in Italy. In contrast, women are
under-represented in vocational programmes in more than three-quarters of the countries with available data.
There is, however, significant cross-country variation in vocational programmes. The share of women ranges
from less than 36% in Greece and Lithuania to more than 60% in Ireland and New Zealand. In fact, Ireland and
New Zealand are two of just four countries where women make up a higher share of graduates in vocational
programmes than in general programmes (with around 60% of women among vocational graduates and around
50% among general graduates). In the other two countries, Brazil and Colombia, the difference between the share of
women in vocational and general programmes is much smaller (below 3 percentage points).

Profile of upper secondary vocational graduates, by field of study
On average across OECD countries, 34% of graduates in vocational programmes earn a diploma with a specialisation
in engineering, manufacturing and construction. This drops to 19% for a diploma in business, administration and
law, 17% in services, and 12% in health and welfare. However, this pattern does not hold for every country. In Brazil,
Colombia, Italy, Luxembourg, Switzerland and the United Kingdom, most upper secondary graduates in vocational
programmes obtained a qualification in business, administration and law. In Denmark, the Netherlands and Spain,
the most popular field is health and welfare, and in New Zealand and Portugal, it is services (Table B3.1).

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The percentage of women pursuing a programme in engineering, manufacturing and construction is low at the
upper secondary vocational level: only 12% of graduates in this field of study are women. On the other hand,
women are over-represented in health and welfare, where they make up 77% of the graduates. In fact, in health
and welfare, the share of female graduates exceeds 75% in all countries except Italy (74%), New Zealand (72%),
Poland (68%), Slovenia (73%) and Sweden (73%). Some countries, such as Colombia, Estonia and Latvia, do not
offer such programmes at the upper secondary level. Between these two extremes, there is more gender balance
in the field of services (where, on average, 60% of graduates are women) and in business, administration and law
(where 66% of graduates are women).
The gender gap by fields of study may be due, in part, to social perceptions of what women and men excel at and
the careers they can pursue. For example, the low share of women in the field of engineering, manufacturing and
construction may result from the social perception of science as being a masculine domain, which may discourage
women from pursuing studies in that field (OECD, 2015[2]). From an equity perspective, it is crucial to ensure that
men and women have the same opportunities in their personal and professional lives, and formal education plays an
important role in that regard (OECD, 2014[3]). Gender diversity has also been acknowledged as highly beneficial for the
performance and productivity of teams within the labour market (Hoogendoorn, Oosterbeek and van Praag, 2013[4]).

Profile of upper secondary graduates, by age
Graduation rates vary according to the age of the students. Students’ age at graduation can be related to changes in
the education system, such as whether opportunities become available to complete upper secondary education later
in life or if the duration of general and vocational programmes is altered.

Figure B3.2. Average age of first-time upper secondary graduates,
by programme orientation and gender (2016)
Women in general programmes
Women in vocational programmes

Age

Men in general programmes
Men in vocational programmes

35
33
31
29
27
25
23
21
19

Israel

Colombia

Chile

Turkey

Korea

Greece

Sweden

Mexico

Italy

Costa Rica

Austria

Canada

Slovenia

Belgium

Slovak Republic

Poland

Hungary

Czech Republic

Latvia

Luxembourg

Lithuania

Portugal

EU22 average

Germany

OECD average

Netherlands

Brazil

Spain

Finland

Denmark

United Kingdom

Iceland

Norway

15

Australia1

17

1. Year of reference 2015.
Countries are ranked in descending order of the average age of women in vocational programmes.
Source: OECD / UIS / Eurostat (2018), Education at a Glance Database, http://stats.oecd.org/. See Source section at the end of this indicator for
more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933803425

The average age of upper secondary graduates tends to be higher in vocational programmes than in general
programmes for both men and women. On average across OECD countries, male graduates obtain their qualification
at age 21 in vocational programmes, compared to age 19 in general programmes. Similarly, the average graduation
age for women is 22 in vocational programmes, compared to 18 in general programmes (Figure B3.2). However, there
is some variation across countries. In Denmark, Iceland, the Netherlands, Norway, Spain and the United Kingdom,
the average graduation age is significantly higher in vocational programmes than in general programmes, with a
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In general programmes, the average graduation age is virtually the same for men and women, with a gender gap of
less than one year in all countries with available data. However, there is more variation in vocational programmes.
Although the average graduation age remains similar for both men and women in most countries (with a one‑year
difference on average across OECD countries), women graduate around two years later than men on average
in Finland, three years later in Spain and the United Kingdom, four years later in Iceland, and five years later in
Denmark and Norway.
First-time graduation rates

Upper secondary graduation rates
An upper secondary education is often considered to be the minimum credential for successful entry into the labour
market and necessary for continuing to further education. The costs of not completing this level of education on
time can be considerable to both individuals and society (see Indicators A3 and A4).
Graduation rates offer an indication of whether government initiatives have been successful in increasing the
number of people who graduate from upper secondary education. The large differences in graduation rates among
countries reflect the variety of systems and programmes available, as well as other country-specific factors, such as
current social norms and economic performance.
Current estimates indicate that, on average, 87% of people across OECD countries will graduate from upper
secondary education in their lifetime, and 81% of people will do so before age 25. First-time graduation rates (before
age 25) exceed 80% in more than half of the countries with available data, but values range from less than 60% in
Brazil, Costa Rica and Mexico to over 90% in Greece, Israel, Korea and Slovenia (Table B3.2).
In the majority of countries, first-time graduation rates below age 25 are significantly higher in general programmes
than in vocational programmes. On average across OECD countries, around 50% of young adults are expected to
graduate from upper secondary general programmes before age 25, compared to 31% for vocational programmes.
In fact, Austria, the Czech Republic, Luxembourg, the Netherlands, the Slovak Republic, Slovenia, Turkey and
the United Kingdom are the only countries where first-time graduation rates are higher in vocational programmes –
although the difference in the Netherlands is only 1 percentage point (Figure B3.3).

Figure B3.3. First-time upper secondary graduation rates for students below the age of 25,
by programme orientation (2016)
General programmes
Vocational programmes
All programmes

%

100
80
60
40

Costa Rica

Brazil

Mexico

Colombia

Turkey

Iceland

Portugal

Spain

United Kingdom

Luxembourg

Czech Republic

Sweden

Slovak Republic

Germany

Italy

Austria

Norway

EU22 average

OECD average

Hungary

Denmark

United States

Poland

Lithuania

Netherlands

Chile

Latvia

Canada

New Zealand

Greece

Finland

Israel

0

Korea

20
Slovenia

B3

difference of at least four years for both men and women. In contrast, students graduate from general programmes at
least one year later than from vocational programmes in Chile, Colombia, Poland and Turkey. In Canada, Costa Rica,
Israel, Korea, Mexico and Sweden, the average graduation age is the same in general and vocational programmes
(for both men and women). Differences between the graduation age in vocational and general programmes may
reflect differences in these programmes’ duration. For instance, in Norway, vocational programmes are one year
longer than general programmes, which can contribute to the higher graduation age in vocational programmes
(See Indicator A2 in [OECD, 2014[5]]).

Countries are ranked in descending order of first-time graduation rates in general and vocational programmes combined.
Source: OECD / UIS / Eurostat (2018), Education at a Glance Database, http://stats.oecd.org/. See Source section at the end of this indicator for
more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933803444

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The higher graduation rates in general programmes may reflect the lower share of students enrolled in upper
secondary vocational programmes than in general programmes (see Indicator B1), along with the lower completion
rates in vocational education (OECD, 2017[6]) (Box B3.1).
In countries with available data for 2005, 2010 and 2016, the first-time upper secondary graduation rate below age 25
increased by 9 percentage points between 2005 and 2016 (compared to a 7 percentage-point increase in first-time
graduation rates for all ages). The increase was striking in four countries: Portugal, Turkey (both 23 percentage points),
Spain (22 percentage points) and Slovenia (21 percentage points). In contrast, in Greece and the Slovak Republic, the
first-time graduation rate below age 25 declined by at least 5 percentage points over the period.
Graduation rates, however, do not imply that all graduates will pursue a tertiary degree or enter the labour force
immediately, nor that they will have the right skills to succeed once in employment. Indeed, the number of graduates
who wind up neither employed nor in education or training (NEET) has been growing in about half of OECD countries
(see Indicator A2). For this reason, it is important to have high-quality upper secondary programmes that provide
individuals with the right mix of guidance and education opportunities to ensure that there are no dead ends after
graduation.

Post-secondary non-tertiary graduation rates
Various kinds of post-secondary non-tertiary programmes are offered in OECD countries. These programmes
straddle upper secondary and post-secondary education and may be considered either upper secondary or postsecondary programmes, depending on the country. Although the content of these programmes may not be
significantly more advanced than upper secondary programmes, they broaden the knowledge of individuals who
have already attained an upper secondary qualification.
First-time graduation rates from post-secondary non-tertiary education are low compared to those from upper
secondary programmes. On average, it is estimated that 11% of today’s young people in OECD countries will complete
post-secondary non-tertiary programmes over their lifetime. The only countries where first-time graduation rates
from post-secondary non-tertiary programmes exceed 20% are the Czech Republic, Germany, Hungary, Lithuania,
New Zealand and the United States. For OECD countries with available data for 2005, 2010 and 2016, the first-time
graduation rate (for all ages) remained constant over the past decade (around 11% on average). Nine countries do
not offer this level of education: Chile, Costa Rica, Indonesia, Korea, Mexico, the Netherlands, Slovenia, Turkey and
the United Kingdom (Table B3.2).

Box B3.1. Equity in students’ choice of upper secondary programme
and completion of this level of education
Equity in students’ choice of upper secondary programme orientation.
Across OECD countries, there is an increasing interest in the development of vocational upper secondary
programmes as an alternative for young people seeking to acquire labour-market skills. In addition to providing
technical skills, strong vocational programmes also offer stepping stones for students to succeed in their
working life and to move between different tracks and career options (OECD, 2010[7]). These programmes
are not meant to be seen as a second-best option for low achievers, but as centres of excellence for developing
important skills.
Nevertheless, vocational education also raises equity concerns, especially if the decision to enrol in vocational
programmes is mainly determined by students’ socio-economic background. Figure B3.a shows the composition
of general and vocational programmes by parents’ educational attainment. In all countries with available data,
students whose parents have lower educational attainment are substantially over-represented in vocational
programmes.
In nearly every country with available data, the share of students whose parents have not attained upper
secondary education is at least twice as high among entrants to vocational programmes as among entrants
to general programmes. This gap can be even more striking at the other end of the spectrum, for students
with at least one tertiary-educated parent. In France and the Netherlands, for example, students with at least
one tertiary-educated parent represent about 50% of general programmes, but less than 20% of vocational
programmes.

…

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B3

The magnitude and attractiveness of vocational programmes can, however, vary widely across countries.
Among the countries presented in Figure B3.a, the share of upper secondary graduates who obtain a vocational
degree ranges from about one-third in Norway and Sweden to more than half in Finland and the Netherlands
(Table B3.1). The share is even higher in other OECD countries without data available for Figure B3.a, such as
Austria, the Czech Republic, the Slovak Republic and Switzerland, where over two-thirds of upper secondary
graduates obtain a vocational degree. These are also countries where vocational graduates fare well in the labour
market, suggesting that attaining a vocational education in these countries may be more a deliberate choice
than the result of students’ socio-economic background. These findings suggest caution against generalising
the results presented here, especially as they refer to a limited number of countries.

Figure B3.a. Share of first-time entrants to upper secondary education,
by programme orientation and parents’ educational attainment (2015)
Parents’ highest level of educational attainment:
Tertiary
Upper secondary or post-secondary non-tertiary
Below upper secondary
%

First-time entrants to:
A General upper secondary programmes
B Vocational upper secondary programmes
C All upper secondary programmes

100
90
80
70
60

40

13

16

27

49

51

55

58

64

71

20

33

39

49

58

50
40
30
20
10
0

A

B

Finland

A

B

Norway

1

A

B

Flemish
Comm.
(Belgium)2

A

B

Sweden

A

B

Netherlands

A

B

Israel

A

B

France

1

C
United
States1

1. Year of reference other than 2015. Please see Annex 3 for further information (http://dx.doi.org/10.1787/eag-2018-36-en).
2. Parents’ educational attainment refers to mother’s educational attainment.
Countries and economies are ranked in descending order of share of students in general programmes with at least one tertiary-educated parent.
Source: OECD 2018 ad hoc survey on upper secondary completion rate by equity dimension. See Source section at the end of this indicator
for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933803463

Equity in completion of upper secondary education.
In addition to influencing the choice of upper secondary programme orientation, the socio-economic
background of students can have an important impact on their educational outcomes. Figures B3.b and B3.c
explore the completion rate of upper secondary education by two measures that may indicate disadvantaged
groups: parents’ educational attainment and immigrant background.
Figure B3.b. shows the share of students who complete upper secondary education within the theoretical
duration of the programme in which they entered. The results highlight the fact that for both general and
vocational programmes, students with at least one tertiary-educated parent are more likely to complete upper
secondary education than students whose parents have not attained tertiary education. This is true for every
country with available data, although at varying degrees. The gap in completion between students with at
least one tertiary-educated parent and those whose parents have not attained this level ranges from around
5 percentage points in Israel to over 10 percentage points in Norway.

…

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Figure B3.b. Completion rate of upper secondary education, by parents’ educational
attainment and programme orientation (2015)

B3

Completion of any upper secondary programme within the theoretical duration of the programme
in which the student entered

%

100
90
80
70
60
50
40
30
20
10
0

Student entered a general upper secondary programme:
Parents did not attain tertiary
At least one parent attained tertiary

Israel

Flemish
Comm.
(Belgium)1

Finland

Norway2

Student entered a vocational upper secondary programme:
Parents did not attain tertiary
At least one parent attained tertiary

France2

Sweden

Netherlands

United
States2, 3

Note: France and the United States have provided data based on longitudinal studies whereas the other countries provided data based on
registries. The error bars included for France and the United States correspond to the 95% confidence interval.
1. Parents’ educational attainment refers to mother’s educational attainment.
2. Year of reference other than 2015. Please see Annex 3 for further information (http://dx.doi.org/10.1787/eag-2018-36-en).
3. Data for the United States refer to general and vocational programmes combined.
Countries and economies are ranked in descending order of completion rate in general programmes of students with at least one tertiary-educated parent.
Source: OECD 2018 ad hoc survey on upper secondary completion rate by equity dimension. See Source section at the end of this indicator
for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933806313

In most countries, the gap between these two groups of students is similar across general and vocational
programmes. However, in France and the Netherlands, the gap in general programmes is higher than in
vocational programmes. This indicates that, in these countries, vocational programmes are more successful
than general programmes in decreasing the impact of socio-economic background on students’ graduation.
Figure B3.c shows the completion rate of upper secondary programmes by the theoretical duration of
programmes, disaggregated by students’ immigrant background. In most of the countries with available data,
the completion rate of first-generation immigrants (those born outside the country and whose parents were
both also born in another country, excluding international students) or second-generation immigrants (those
born in the country, but whose parents were both born in another country) was lower than students without
first-generation or second-generation immigrant background.
The largest gap is observed in Italy, where 60% of non-immigrants complete upper secondary education on
time, compared to 32% of first-generation immigrants and 37% of second-generation immigrants. It must
be kept in mind that the share of students with an immigrant background varies across countries. Less than
6% of upper secondary entrants in Italy and Finland have an immigrant background, compared to around
10% in France and Norway and around 15-20% in Israel, the Netherlands, Sweden and the United States.
These percentages represent only the school-age immigrants who enter the educational system, which may
not always be the case. Moreover, immigrant populations may be very different across countries, and it is
important to understand the specificities of each case when designing policies.
The gap between first-generation and second-generation immigrants does not follow a specific pattern in the
countries presented. In some countries, such as Finland, Norway and Sweden, first-generation immigrants are
considerably less likely to complete upper secondary education than second-generation immigrants. A plausible
explanation for the lower outcomes of first-generation immigrants is the language barrier, particularly for
students who arrive in the host country at an older age. In other countries, such as the Netherlands, the gap
in completion between first-generation and second-generation students is quite small.

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Figure B3.c. Completion rate of upper secondary education, by immigration background
(2015)
Completion of any upper secondary programme within the theoretical duration of the programme
in which the student entered
Non-immigrants

%

100
90
80
70
60
50
40
30
20
10
0

United States1

Israel

First-generation immigrants

Sweden

France1

Second-generation immigrants

Finland

Netherlands

Italy

Norway1

Note: France and the United States have provided data based on longitudinal studies whereas the other countries provided data based
on registries. Longitudinal studies would not account for the most recent waves of immigration. The error bars included for France and
the United States correspond to the 95% confidence interval.
1. Year of reference other than 2015. Please see Annex 3 for further information (http://dx.doi.org/10.1787/eag-2018-36-en).
Countries and economies are ranked in descending order of completion rate of students without an immigrant background.
Source: OECD 2018 ad hoc survey on upper secondary completion rate by equity dimension. See Source section at the end of this indicator
for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933806332

Young people who leave school before completing upper secondary education have lower skills, are less
likely to be employed and earn less than their counterparts who attain at least this level of education
(see Indicators A1, A3 and A4). Thus, the lower completion rates associated with students whose parents
have low levels of educational attainment and with those who have an immigrant background can play an
important role in furthering inequalities in society.

Definitions
Graduates in the reference period can be either first-time graduates or repeat graduates. A first-time graduate is a
student who has graduated for the first time at a given level of education in the reference period. Thus, if a student
has graduated multiple times over the years, he or she is counted as a graduate each year, but as a first-time graduate
only once.
Net graduation rates represent the estimated percentage of an age group that will complete upper secondary
education, based on current patterns of graduation.
Typical age is the age at the beginning of the last school/academic year of the corresponding educational level and
programme when the degree is obtained.

Methodology
Unless otherwise indicated, graduation rates are calculated as net graduation rates (i.e. as the sum of age-specific
graduation rates). Gross graduation rates are presented for countries that are unable to provide such detailed
data. In order to calculate gross graduation rates, countries identify the age at which graduation typically occurs
(see Annex 1). The number of graduates, regardless of their age, is divided by the population at the typical graduation
age. In many countries, defining a typical age of graduation is difficult, however, because graduates are dispersed
over a wide range of ages.
Graduates by programme orientation at the upper secondary and post-secondary non-tertiary levels are not counted
as first-time graduates, given that many students graduate from more than one upper secondary or post-secondary
non-tertiary programme. Therefore, graduation rates cannot be added, as some individuals would be counted twice.

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In addition, the typical graduation ages are not necessarily the same for the different types of programmes
(see Annex 1). Vocational programmes include both school-based programmes and combined school-based and
work‑based programmes that are recognised as part of the education system. Entirely work-based education and
training programmes that are not overseen by a formal education authority are not included.
The average age of students is calculated from 1 January for countries where the academic year starts in the second
semester of the calendar year and from 1 July for countries where the academic year starts in the first semester of
the calendar year. As a consequence, the average age of first-time graduates may be underestimated by up to six
months.
Please see Annex 3 for country-specific notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Lithuania was not an OECD member at the time of preparation of this publication. Accordingly, Lithuania does not
appear in the list of OECD members and is not included in the zone aggregates.

Source
Data refer to the academic year 2015/16 and are based on the UNESCO-UIS/OECD/EUROSTAT data collection on
education statistics administered by the OECD in 2017 (for details, see Annex 3 at http://dx.doi.org/10.1787/eag2018-36-en).

Note regarding data from Israel
The statistical data for Israel are supplied by and are under the responsibility of the relevant Israeli authorities. The use
of such data by the OECD is without prejudice to the status of the Golan Heights, East Jerusalem and Israeli settlements
in the West Bank under the terms of international law.

References
Hoogendoorn, S., H. Oosterbeek and M. van Praag (2013), “The impact of gender diversity on the performance of business [4]
teams: Evidence from a field experiment”, Management Science, Vol. 59/7, pp. 1514-1528, http://dx.doi.org/10.1287/
mnsc.1120.1674.
OECD (2017), Education at a Glance 2017: OECD Indicators, OECD Publishing, Paris, http://dx.doi.org/10.1787/eag-2017-en. [6]
OECD (2015), “Focus on vocational education and training (VET) programmes”, Education Indicators in Focus, No. 33, [1]
OECD Publishing, Paris, http://dx.doi.org/10.1787/5jrxtk4cg7wg-en.
OECD (2015), The ABC of Gender Equality in Education: Aptitude, Behaviour, Confidence, PISA, OECD Publishing, Paris, [2]
http://dx.doi.org/10.1787/9789264229945-en.
OECD (2014), PISA 2012 Results: What Students Know and Can Do (Volume I, Revised edition, February 2014): Student [3]
Performance in Mathematics, Reading and Science, PISA, OECD Publishing, Paris, http://dx.doi.org/10.1787/
9789264208780-en.
OECD (2014), Education at a Glance 2014: OECD Indicators, OECD Publishing, Paris, http://dx.doi.org/10.1787/eag-2014-en. [5]
OECD (2010), Learning for Jobs, OECD Reviews of Vocational Education and Training, OECD Publishing, Paris, http:// [7]
dx.doi.org/10.1787/9789264087460-en.

Indicator B3 Tables
1 2 https://doi.org/10.1787/888933803330

Table B3.1 Profile of upper secondary graduates from vocational programmes (2016)
Table B3.2 Upper secondary and post-secondary non-tertiary first-time graduation rates (2016)
Table B3.3 Trends in upper secondary and post-secondary non-tertiary first-time graduation rates (2005, 2010 and 2016)
Cut-off date for the data: 18 July 2018. Any updates on data can be found on line at http://dx.doi.org/10.1787/eag-data-en. More breakdowns can
also be found at http://stats.oecd.org/, Education at a Glance Database.

Education at a Glance 2018: OECD Indicators   © OECD 2018

189

B3

chapter B Access to Education, Participation and Progression
Under embargo until 11/09/2018 at 11.00am CEST
Table B3.1. Profile of upper secondary graduates from vocational programmes (2016)
Distribution of graduates
by field of study

Business,
administration
and law

Engineering,
manufacturing
and construction

Health and welfare

Services

Business,
administration
and law

Engineering,
manufacturing
and construction

Health and welfare

Services

B3

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

Australia1
Austria
Belgium
Canada
Chile
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United Kingdom
United States

m
78
m
6
31
68
30
m
55
m
45
24
24
29
m
42
56
23
18
27
59
36
54
m
32
45
38
67
64
33
34
m
52
63
m

45
46
48
46
49
44
50
38
54
49
41
32
38
41
63
50
39
43
44
43
51
50
50
61
38
39
48
45
46
50
41
45
50
49
m

16
28
20
m
31
19
22
1
17
21
34
20
11
13
m
m
32
31
24
15
30
m
20
16
6
12
17
16
15
13
8
33
17
19
a

37
35
26
m
40
39
27
52
27
34
34
49
47
40
m
m
26
42
44
39
23
m
18
14
45
39
20
37
32
18
45
33
38
15
a

23
3
16
m
6
6
30
0
22
19
11
1
5
10
m
m
6
6
2
0
11
m
24
8
25
0
13
8
14
20
18
15
21
18
a

13
19
19
m
12
19
13
29
20
19
12
5
28
17
m
m
21
8
6
23
6
m
22
19
17
25
25
25
15
13
20
9
8
15
a

66
67
54
m
65
67
65
97
68
64
58
69
76
54
m
m
52
63
75
79
60
m
53
76
78
66
66
72
65
64
60
60
55
62
a

9
13
7
m
19
12
10
20
17
11
9
14
8
8
m
m
15
11
16
9
15
m
9
14
7
12
17
9
10
8
9
12
15
6
a

83
77
82
m
83
89
87
0
84
91
85
93
90
89
m
m
74
83
82
0
77
m
88
72
85
68
86
85
73
77
73
90
85
78
a

59
73
70
m
67
65
42
74
61
64
49
53
56
56
m
m
49
81
68
68
47
m
44
71
40
70
54
60
60
49
64
57
63
52
a

OECD average
EU22 average

42
48

46
46

19
19

34
33

12
12

17
19

66
66

12
11

77
74

60
58

Argentina
Brazil
China
Colombia
Costa Rica
India
Indonesia
Lithuania
Russian Federation
Saudi Arabia
South Africa

m
8
m
24
21
m
m
17
52
m
m

m
58
m
55
54
m
m
35
37
m
m

m
25
m
m
m
m
m
16
m
m
m

m
17
m
m
m
m
m
49
m
m
m

m
10
m
m
m
m
m
1
m
m
m

m
5
m
m
m
m
m
27
m
m
m

m
60
m
m
m
m
m
46
m
m
m

m
32
m
m
m
m
m
3
m
m
m

m
79
m
m
m
m
m
91
m
m
m

m
63
m
m
m
m
m
79
m
m
m

G20 average

m

m

m

m

m

m

m

m

m

m

OECD

Percentage
of first-time
graduates
who
Percentage
obtained
a vocational of female
programmes graduates

Partners

Percentage of female graduates
by field of study

Note: This table does not include data for all fields of study. The data for other fields are available at http://stats.oecd.org/, Education at a Glance Database.
1. Year of reference 2015.
Source: OECD / UIS / Eurostat (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933803349

190 Education at a Glance 2018: OECD Indicators   © OECD 2018

Who is expected to graduate from upper secondary education? – INDICATOR B3

chapter B

Under embargo until 11/09/2018 at 11.00am CEST
Table B3.2. Upper secondary and post-secondary non-tertiary first-time graduation rates (2016)
Sum of age-specific graduation rates, by programme orientation
Upper secondary

Partners

OECD

All programmes

General programmes

All ages

Younger
than
25 years

All ages

Younger
than
25 years

Post-secondary non-tertiary
Vocational programmes
All ages

Younger
than
25 years

All programmes
All ages

Younger
than
30 years

Vocational programmes
All ages

Younger
than
30 years

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

Australia1
Austria
Belgium
Canada
Chile
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United Kingdom
United States

m
86
m
93
91
76
95
m
101
m
84
94
85
89
m
92
94
95
94
90
79
57
89
93
90
88
80
79
95
81
77
m
75
90
84

m
81
m
87
87
75
82
m
89
m
79
92
82
71
m
92
80
m
94
85
77
57
85
87
80
84
74
77
93
74
77
m
71
75
84

m
19
m
87
63
25
67
m
46
m
47
71
65
63
100
54
41
73
78
67
33
37
42
m
62
48
50
26
34
56
51
m
36
34
m

m
19
m
82
59
25
65
m
46
m
47
71
63
57
100
54
41
m
78
63
33
37
42
m
61
45
46
26
34
55
51
m
33
34
m

33
67
m
6
29
52
28
m
55
m
37
22
20
26
m
38
53
22
17
23
46
20
47
m
28
39
30
53
61
25
27
m
39
55
m

14
61
m
5
28
50
17
m
43
m
32
21
19
15
m
38
39
m
17
22
44
20
43
m
19
39
28
51
59
20
27
m
38
41
m

13
8
m
m
a
30
0
m
8
m
24
m
21
10
m
m
1
m
a
9
2
a
a
26
4
15
3
8
a
2
5
m
a
a
22

5
4
m
m
a
m
0
m
1
m
21
m
19
4
m
m
m
m
a
7
1
a
a
15
2
11
3
5
a
1
2
m
a
a
m

13
8
m
m
a
7
0
m
8
m
21
m
21
9
m
1
m
a
9
2
a
a
m
4
15
3
8
a
2
5
m
a
a
22

5
4
m
m
a
m
0
m
1
m
19
m
19
4
m
m
m
m
a
7
1
a
a
m
2
11
3
5
a
1
2
m
a
a
m

OECD average
EU22 average

87
87

81
81

53
49

51
48

36
41

31
36

11
10

m
m

9
8

m
m

Argentina1
Brazil
China
Colombia
Costa Rica
India
Indonesia
Lithuania
Russian Federation
Saudi Arabia
South Africa

63
65
86
77
36
33
72
87
98
m
m

m
58
m
70
34
m
m
84
m
m
m

m
59
m
59
29
m
m
73
46
m
m

m
54
m
52
26
m
m
71
m
m
m

m
6
m
18
8
m
m
14
51
m
m

m
4
m
18
7
m
m
13
m
m
m

m
7
m
1
a
m
a
21
4
m
m

m
4
m
1
a
m
a
16
m
m
m

m
7
m
a
a
m
a
21
4
m
m

m
4
m
a
a
m
a
16
m
m
m

G20 average

79

m

m

m

m

m

m

m

m

m

1. Year of reference 2015.
Source: OECD / UIS / Eurostat (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933803368

Education at a Glance 2018: OECD Indicators   © OECD 2018

191

B3

chapter B Access to Education, Participation and Progression
Under embargo until 11/09/2018 at 11.00am CEST
Table B3.3. Trends in upper secondary and post-secondary non-tertiary first-time graduation rates

(2005, 2010 and 2016)

Sum of age-specific first-time graduation rates

B3

Upper secondary

Partners

OECD

All ages

Post-secondary non-tertiary

Younger than 25 years

All ages

Younger than 30 years

2005

2010

2016

2005

2010

2016

2005

2010

2016

2005

2010

2016

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

Australia1
Austria
Belgium
Canada
Chile
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United Kingdom
United States

m
m
m
80
83
100d
83
m
94
m
78
96
84
m
92
89
85
m
94
m
74
40
m
95
90
m
54
86
85
56
76
m
48
87
74

m
87
m
85
86
100d
85
m
95
m
83
89
86
m
86
91
85
96
92
89
70
45
m
91
87
84
100
86
94
61
75
m
54
88
77

m
86
m
93
91
76
95
m
101
m
84
94
85
89
m
92
94
95
94
90
79
57
89
93
90
88
80
79
95
81
77
m
75
90
84

m
m
m
75
77
m
74
m
85
m
m
96
80
m
90
89
67
m
m
m
72
39
m
86
74
m
51
84
72
53
76
m
48
m
74

m
84
m
81
82
m
76
m
85
m
m
89
82
m
85
91
67
m
m
88
68
44
m
80
75
83
66
84
83
57
75
m
54
m
77

m
81
m
87
87
75
82
m
89
m
79
92
82
71
m
92
80
m
94
85
77
57
85
87
80
84
74
77
93
74
77
m
71
75
84

m
m
m
m
a
x(1)
1
m
6
m
23
m
20
m
14
m
6
m
a
m
m
a
m
26
5
15
m
12
a
a
1
m
a
a
17

16
7
m
m
a
x(2)
1
m
7
m
25
m
18
m
10
m
4
m
a
3
2
a
m
29
10
13
3
10
a
a
3
m
a
a
22

13
8
m
m
a
30
0
m
8
m
24
m
21
10
m
m
1
m
a
9
2
a
a
26
4
15
3
8
a
2
5
m
a
a
22

m
m
m
m
a
m
1
m
1
m
m
m
18
m
14
m
4
m
a
m
m
a
m
12
3
11
m
11
a
a
0
m
a
a
m

7
4
m
m
a
m
0
m
1
m
m
m
16
m
7
m
2
m
a
2
1
a
m
18
7
10
3
8
a
a
2
m
a
a
m

5
4
m
m
a
m
0
m
1
m
21
m
19
4
m
m
m
m
a
7
1
a
a
15
2
11
3
5
a
1
2
m
a
a
m

OECD average
Average for countries
with available data
for all reference years
EU22 average

80

84

87

73

76

81

12

11

11

m

m

m

80

83

86

73

75

81

12

11

11

m

m

m

82

86

87

75

78

81

11

8

10

m

m

m

Argentina1
Brazil
China
Colombia
Costa Rica
India
Indonesia
Lithuania
Russian Federation
Saudi Arabia
South Africa

m
m
m
m
m
m
m
82
89
m
m

m
m
m
m
m
m
m
94
97
m
m

63
65
86
77
36
33
72
87
98
m
m

m
m
m
m
m
m
m
78
m
m
m

m
m
m
m
m
m
m
89
m
m
m

m
58
m
70
34
m
m
84
m
m
m

m
m
m
m
a
m
a
8
7
m
m

m
m
m
m
a
m
a
9
12
m
m

m
7
m
1
a
m
a
21
4
m
m

m
m
m
m
a
m
a
8
m
m
m

m
m
m
m
a
m
a
7
m
m
m

m
4
m
1
a
m
a
16
m
m
m

G20 average

m

m

79

m

m

m

m

m

m

m

m

m

1. Year of reference 2015 instead of 2016.
Source: OECD / UIS / Eurostat (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933803387

192 Education at a Glance 2018: OECD Indicators   © OECD 2018

Under embargo until 11/09/2018 at 11.00am CEST

Under embargo until 11/09/2018 at 11.00am CEST

WHO IS EXPECTED TO ENTER TERTIARY EDUCATION?
INDICATOR B4

• On average, the share of female new entrants into doctoral programmes has increased by
2.5 percentage points between 2005 and 2016, and women now represent almost half of the
doctoral new entrants across OECD.

• In 24 of the 31 countries with available data, the median age of entry into tertiary education is
between 18 and 20 years old.

• In almost all OECD countries, first-time entry rates to tertiary education below age 25 are higher
for women than for men.

Figure B4.1. Share of female new entrants into doctoral programmes
(2005, 2010, 2016)
2016

%

2010

2005

60
55
50
45
40
35

25

Argentina1
Poland
Iceland
Latvia
Ireland
Finland
Estonia
Israel
United States
Lithuania
Italy
Norway
New Zealand
Netherlands
Denmark
Australia
Hungary
Spain
Slovenia
EU22 average
Portugal
Slovak Republic
Mexico
United Kingdom
OECD average
Greece
Austria
Switzerland
Germany
Russian Federation
France
Sweden
Czech Republic
Chile
Turkey
Korea
China
Saudi Arabia
Luxembourg
Indonesia
Colombia
Japan

30

1. Year of reference 2015 instead of 2016.
Countries are ranked in descending order of the share of female new entrants into doctoral (ISCED 8) programmes in 2016.
Source: OECD / UIS / Eurostat (2018), Table B4.1, Education at a Glance Database, http://stats.oecd.org/. See Source section at the
end of this indicator for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933803558

Context
Entry rates estimate the proportion of people who are expected to enter a specific type of tertiary
education programme (including short-cycle tertiary, bachelor’s degrees, master’s degrees, long first
degrees and doctoral programmes) at some point during their life. They provide some indication of the
accessibility of tertiary education and the degree to which a population is acquiring high-level skills
and knowledge. High entry and enrolment rates in tertiary education imply that a highly educated
labour force is being developed and maintained.
By enabling young adults to access higher-quality and better paid jobs, granting equal opportunities
to students of all socio-economic backgrounds to higher education can be a powerful tool to reduce
socio-economic and intergenerational inequalities. Ensuring gender parity in access to higher levels
of tertiary education and fields of study also ensures greater gender equity in the workplace. Several
governments have placed particular emphasis on improving the quality of education in science,
technology, engineering and mathematics (STEM), reflecting the critical importance of these
disciplines for modern society in driving economic progress and supporting innovation. However,
women are still less likely to enrol in these programmes in most OECD countries, despite the fact that
they lead to higher employment rates and higher earnings.

194 Education at a Glance 2018: OECD Indicators   © OECD 2018

Under embargo until 11/09/2018 at 11.00am CEST
A tertiary education system can also provide for equitable outcomes through flexible entrance criteria
that support lifelong learning. Second-chance programmes can offer new opportunities to older
students who might have dropped out of the education system earlier than they had wished or for
those who want to improve the relevance of their skills for the labour market.

INDICATOR B4

Other findings

• Based on current patterns, it is estimated that an average of 58% of young adults in OECD countries
will enter a bachelor’s degree or equivalent programme in their lifetime, and 24% are expected to
enter a master’s or equivalent programme.

• International students represent a large share of first-time entrants into tertiary education in
Luxembourg (47%) and New Zealand (32%), well above the OECD average of 12%.
Note
Compared to enrolment, entry rates measure the inflow to education during a specific period and
represent the percentage of an age cohort that is expected to enter a tertiary programme over a
lifetime. The estimates in this indicator are based on the number of new entrants in 2016 and the age
distribution of this group. Therefore, the entry rates are based on a “synthetic cohort” assumption,
according to which the current pattern of entry constitutes the best estimate of the behaviour of
today’s young adults over their lifetime.
International students are a significant share of the total student population in some countries, and
their numbers can artificially inflate the proportion of today’s young adults who are expected to enter
a tertiary programme. When international students are excluded from the calculation, the percentage
of expected new entrants into tertiary programmes can change significantly.
Entry rates are sensitive to changes in the education system, such as the introduction of new
programmes. The rates can be very high, even greater than 100% (thus clearly indicating that the
synthetic cohort assumption is implausible), during a period when there is an unexpectedly high
number of entrants. In some countries, high entry rates may reflect a temporary phenomenon, such
as the effects of economic cycles and crises, university reforms driven by the Bologna Process or a
surge in the number of international students. Government efforts to encourage older students to
rejoin education through second-chance programmes can also boost entry rates.

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Analysis
Profile of new entrants into tertiary education

B4

Share of new entrants by level of education
Knowing the level at which students first enter tertiary education helps to determine the depth and length of the
studies in which they engage. Most education systems begin tertiary education at the bachelor’s degree level.
In most OECD countries, about three-quarters of first-time entrants into tertiary education enter bachelor’s
programmes, but the relative importance of either short-cycle tertiary programmes or long first degree masters’
programmes varies greatly across countries. In a few countries, such as Austria, Chile, the Russian Federation,
Turkey and the United States, over 40% of both male and female new entrants into tertiary education entered
short-cycle programmes. Long first degrees leading to master’s diplomas are almost non-existent in some countries,
but they attract up to 25% of new entrants in others (see detailed explanation in Indicator B5).
The distribution of male and female new entrants across levels of tertiary education does not always follow the same
pattern within countries. In some of them, more men than women enter short-cycle programmes. The fields of study
offered in such programmes can help explain part of this difference. In Austria, Israel, Mexico, Norway, Slovenia
and Sweden, for instance, at least 30% of new entrants into short-cycle tertiary programmes choose engineering,
manufacturing and construction, a highly male-dominated field.
Among first-time entrants into tertiary education who entered short-cycle tertiary programmes, Japan stands out
as the only country in which women (43%) significantly outnumber men (28%). Many of these programmes are in
health and welfare and in services, both fields that are traditionally dominated by women.

Box B4.1. Applicants and applications to tertiary education
The number of new entrants in tertiary education depends on the potential population with an upper secondary
qualification who can apply to tertiary education (see Indicator A2), the attractiveness of tertiary education
(see Indicators A4 and A5), the potential offer (number of available first-degree tertiary programmes and
places in these programmes), and the selectivity of admission systems to these programmes (see Indicator D6
in Education at a Glance 2017 [OECD, 2017[1]]). In 2017, to shed light on systems for admission to tertiary
education, the OECD carried out a survey on the number of applicants and applications to first-degree tertiary
programmes (see Annex 3 for notes).
Among the 30 countries and economies that responded to the survey, data on the number of applicants and/or
applications are available in only 13 countries. Several factors may explain why data are not available elsewhere.
In some countries data are not centrally compiled/located (for example, in Austria, Germany, New Zealand and
Poland). In other countries, data are not available as there are open admissions systems where all people with
the required attainment level are accepted (for example in the French and Flemish Communities of Belgium
and Switzerland).
Among countries with available data, the number of applications to tertiary education varies largely between
countries, partly reflecting differences in admissions systems. In the ten countries with data on both the number
of applicants and the number of applications for the 2016 reference year, each student (excluding international
students) made, on average, one application in the Netherlands, but about seven applications in France.
Students in France applied through a centralised system, and could make up to 24 applications and received
1 potential offer. In the Netherlands, students also applied through a centralised system, but could make only
up to 3 applications and received the result for each of them. Application fees can also affect the number of
applications. These fees can vary between institutions and fields of study and can reach significant amounts.
In countries with available data, they average USD 100 or less, but they can reach USD 1 000 or more in some
countries for specific institutions or fields (OECD, 2017[1]).
While more than half of countries and economies with available data have open admission systems in public
tertiary institutions (all applicants with the minimum qualification level required are admitted), the other half
operate on a selective system in which enrolment in programmes is limited and decided on the basis of specific
selection criteria. However, nearly all systems, whether open or selective, have limitations in the admission
systems for at least some fields of study (OECD, 2017[1]).

…

196 Education at a Glance 2018: OECD Indicators   © OECD 2018

Who is expected to enter tertiary education? – INDICATOR B4

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The most selective systems may be those with the highest proportions of applicants whose applications were
rejected. Among the 19 countries with data on the number of applicants, only 13 can report the distribution
of applicants by result of their applications (Figure B4.a). The proportion of applicants rejected varies from
less than 5% in Australia to more than 60% in Finland and Sweden. In both these countries, admissions are
restricted for all programmes and fields of study, and the number of admissions results from a negotiation
between tertiary institutions and the central government. These rates may hide larger variations within
countries between different fields of study.

Figure B4.a. Applicants to first-degree tertiary education by application status (2016)
Proportion of applicants rejected
Proportion of applicants accepted, not studying
Proportion of applicants accepted and studying

%

100
80
60
40

Sweden

Finland

Lithuania

Norway

Denmark

Hungary

Slovenia

Israel

Estonia

Slovak Republic

Portugal

Australia

0

France1

20

1. Including applicants to short-cycle tertiary programmes.
Countries are ranked in descending order of the proportion of applicants accepted and studying.
Source: OECD (2018). See Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933806351

However not all applicants who were successful in the admission process enrol in these programmes. In the
13 countries with available data, the proportion of applicants accepted but not studying exceeds 10% in
Denmark, Israel, the Slovak Republic and Slovenia and 25% in Norway. The possibility of deferred enrolment
may explain differences in the number of successful applicants and new entrants.
More generally, there may be delays between upper secondary graduation, application and entry to tertiary
education. Among the ten countries that provided data, the number of applicants is lower than the number of
upper secondary graduates. This is expected, as graduates can stop or delay their studies (to enter the labour
market), and this is not necessarily counterbalanced by people applying several years after graduating from upper
secondary level. However, the number of applicants to tertiary education is higher than the number of upper
secondary graduates in both Finland (by 35%) and Norway (by 75%). This is likely due to delayed entry to tertiary
education combined with the limited number of student positions in tertiary institutions. This is consistent with
the wider age distribution observed among new entrants to tertiary education in these countries, as well as the
lower entry rate of adults under 25. Difficulties in balancing changes in the number of upper secondary graduates
and available positions in tertiary institutions may also explain the difference in some countries.
The different systems of admission to tertiary education combined with the different ways people graduate
from upper secondary level and apply to and enrol in tertiary programmes and challenges in compiling the
data make difficult to estimate the demand for tertiary education in the different countries.

Age of new entrants into tertiary education
National differences in the age at which young people graduate from upper secondary education and the intake capacity
of tertiary education institutions result in significant variations in the age of new entrants into tertiary education
among OECD countries. In particular, admissions with numerus clausus (a fixed maximum number of entrants
admissible to an academic institution), one of many methods used to limit the number of students who may study
at a tertiary institution, may defer the entry of a significant share of students (Box B4.1). Besides, a few countries
implemented mandatory army or civil service, which can also delay entry into tertiary education (e.g. Israel).
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In six countries, the oldest 20% of new entrants are older by 5 years or more than the median age of entry, which
itself is between 18 and 20. The causes of such a wide entry-age distribution are ambiguous. They could reflect the
existence of second-chance and lifelong learning programmes and, therefore, be characteristic of a more flexible
system that allows for re-entry into the education system after having worked. On the other hand, delayed entry
can be the sign of numerus clausus or difficulties in financing tertiary education right after graduating from
upper secondary education. Delayed entry might be a problem from an economic point of view, because it means
that adults take longer to enter the labour market and to start contributing financially to society. However,
second‑chance programmes can also be aimed at adults who, for some reason, were not able to move to tertiary
education and entered the labour market right after graduating from upper secondary education. It is difficult
to determine the right balance between promoting earlier access and graduation from tertiary education and
enabling opportunities for older adults through second-chance programmes. The internationalisation of higher
education can also influence the age distribution at entry. In Austria, Denmark and New Zealand, for instance,
international students represent a higher share of new entrants than on average across OECD countries, and they
are usually older.
Profile of new entrants into doctoral programmes
Among the different levels of tertiary education, graduate-level research, particularly at the doctoral level, plays a
crucial role in innovation and contributes significantly to the national and international knowledge base. Businesses
are attracted to countries that make this level of research readily available (Halse and Mowbray, 2011[2]), while
individuals who attain this level of education benefit from higher employment rates (see Indicator A3).

Figure B4.2. Age distribution of first-time entrants into tertiary education (2016)
80th percentile
Median
20th percentile

Age

29
27
25
23
21
19

Japan

Greece

Belgium

United States

Portugal

United Kingdom

Spain

Mexico

Italy

Netherlands

Austria

Chile

Slovenia

Lithuania

New Zealand

Hungary

EU22 average

Poland

Colombia

Czech Republic

OECD average

Slovak Republic

Turkey

Norway

Finland

Germany

Iceland

Sweden

Denmark

Israel

15

Luxembourg

17
Switzerland

B4

Traditionally, students enter tertiary programmes immediately after completing upper secondary education, and
this remains true in many countries. Indeed, in 24 of the 30 countries with available data, the median age of entry
into tertiary education is between 18 and 20 years old, meaning that half of the new entrants into tertiary education
have entered tertiary programmes by the age of 20. Structural factors, such as admission procedures or the typical
age at which students graduate from upper secondary education, explain the small differences in the median age
of entry across countries. In a few countries, over half of the students enter tertiary education at a later age. This
is the case in Israel, for example, where military service is compulsory, and in Finland, where universities have
implemented a numerus clausus (Figure B4.2).

Countries are ranked in descending order of the median entry age of first-time entrants into tertiary education.
Source: OECD / UIS / Eurostat (2018), Education at a Glance Database, http://stats.oecd.org/. See Source section at the end of this indicator for
more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933803577

198 Education at a Glance 2018: OECD Indicators   © OECD 2018

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International students
Several countries are developing doctoral programmes or changing their funding policy to attract international
students. Attracting the best students from around the world helps to ensure that a country plays a leading role in
research and innovation. Among all tertiary programmes, international students make up the largest share of the
new entrants population at doctoral level. On average across OECD countries, international students account for
28% of the new entrants to programmes at the doctoral level. In 7 of the 33 countries for which data are available,
more than 40% of new entrants to doctoral programmes are international, and the proportion reaches 78% in
Luxembourg (Table B4.2).

Age of entry
On average across OECD countries, 59% of entrants at the doctoral level are under age 30 (Table B4.1). Across
OECD countries, the average age of entry at this level is between 26 (the Netherlands) and 38 (Korea). A larger
share of younger entrants may reflect lower dropout rates and greater emphasis on acquiring specialised skills.
Some countries offer incentives (such as grants, scholarships, international mobility programmes, part-time
jobs and distance learning) to encourage students to pursue advanced studies right after completion of their
first degree in tertiary education. Given that the academic labour market is becoming increasingly competitive,
pursuing doctoral studies as early as possible might increase one’s chances of having a better career in research.
Depending on the type of career one expects after completing a doctorate, gaining a few years of experience on
the labour market before pursuing doctoral studies might also be a relevant choice. By contrast, tuition fees,
availability of scholarships, and country-specific social expectations (such as being expected to enter the labour
force by a certain age or to gain professional experience before entering advanced education) may explain why
some new entrants are older.

Fields of study
New entrants to doctoral programmes are more likely to enrol in STEM fields than any others, reflecting the
differences in employability of doctoral graduates across fields, as well as the research and innovation funding
policies of countries. Quite a few new entrants to doctoral studies also enter health and welfare programmes, while
students are much less likely to enrol in doctoral studies in the humanities, degrees that mainly lead to careers in
academia.

Gender
The share of women in doctoral programmes has increased in the past decade. On average across OECD countries,
the share of female new entrants into doctoral programmes increased by 2.5 percentage points between 2005 and
2016, reaching 48% in 2016. Women accounted for about half of doctoral new entrants (between 48 and 52%) in
20 countries in 2016, displaying a common trend towards a fairer representation of women in doctoral programmes.
However, some strong differences across countries remain, ranging from 55% or more of female new entrants in
Argentina and Poland to under 40% in Colombia, Indonesia, Japan, Luxembourg and Saudi Arabia (Figure B4.1).
International students make up the largest share of new entrants at the doctoral level, but only four out of ten
are women, on average across OECD countries. Women represent less than 50% of international new entrants
into doctoral programmes in all countries except Austria and Chile. Therefore, the gender imbalance observed in
some countries might be influenced by the higher share of international students entering doctoral studies and the
relative under-representation of women among them.
On average across OECD countries, about a third of the women and half of the men who pursue doctoral studies enter
a STEM field of study. Among these fields, men are twice as likely as women to pursue a doctorate in engineering,
manufacturing and construction and three times as likely to enter a doctoral programme in information and
communication technologies (ICT).
These differences in how men and women select their field of study closely reflect those observed at bachelor’s
level. Women are not under-represented in all STEM fields, but mostly in technical fields such as engineering,
manufacturing and construction and ICT. Women are, however, over-represented in the health and welfare field,
which requires just as much scientific knowledge as other fields, but generally leads to jobs that could be qualified
as “care jobs”, in which women are usually over-represented. The gender divide in choice of field of study does not,
therefore, fully correspond to the expected “humanistic-scientific” divide, but rather to what (Barone, 2011[3]) calls
a “care-technical” divide that translates later on in labour market occupations.
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Entry rates to tertiary education
It is estimated that, on average across OECD countries, 66% of young adults will enter tertiary education for the
first time in their life, if current patterns of entry continue. Chile (89%), Denmark (86%) and New Zealand (91%)
have the highest first-time tertiary entry rates among OECD countries. In these countries, these rates are typically
inflated by a larger population of older students and international students or a high rate of entry into short-cycle
tertiary education (Table B4.3).
Comparing the first-time entry rate of adults under age 25 with total first-time entry rates for a population
(excluding international students) provides a sense of general accessibility versus delayed entrance into tertiary
education. For example, first-time entry rates of adults under age 25 are similar in Italy and Sweden (40-41%,
compared to the OECD average of 49%), but the total first-time entry rate in Sweden is 10 percentage points
higher than in Italy, suggesting that the lower entry rate below age 25 is more a question of deferred entrance
in Sweden and of access in Italy. This is also corroborated by the age distribution of new entrants into tertiary
education shown in Figure B4.2.
While 50% of young adults are likely to enter tertiary education for the first time under age 25, in most
OECD countries with data, the trend to enter higher education at an earlier age is driven by women (Figure B4.3).
The difference between the first-time entry rates of women and men under age 25 is 13 percentage points on
average across OECD countries, but is equal to or higher than 17 percentage points in Belgium, Denmark, Iceland,
Israel and Norway. Only in Colombia, Finland, Luxembourg and Mexico do entry rates of men and women under
age 25 differ by 5 percentage points or less. While men may choose to enter higher education at a later age, this
suggests that the already established trend for women to outnumber men in higher education is likely to continue.

Figure B4.3. First-time tertiary entry rates below the age of 25, by gender (2005, 2016)
Women 2016
Women 2005

%

Men 2016
Men 2005

90
80
70
60
50
40
30
20

Countries are ranked in descending order of the first-time entry rates of female students younger than 25 years old in 2016.
Source: OECD / UIS / Eurostat (2018), Education at a Glance Database, http://stats.oecd.org/.
1 2 https://doi.org/10.1787/888933803596

200 Education at a Glance 2018: OECD Indicators   © OECD 2018

Hungary

Luxembourg

Colombia

Mexico

Finland

Italy

United States

Sweden

Germany

Slovak Republic

Czech Republic

Switzerland

EU22 average

Iceland

OECD average

Israel

Netherlands

United Kingdom

Portugal

Greece

Austria

Denmark

Spain

Norway

Chile

Japan

New Zealand

Poland

Slovenia

0

Belgium

10
Lithuania

B4

These two phenomena, however, cannot fully account for the under-representation of women in doctoral studies
in some countries. In some countries, women may choose to apply less often to doctoral programmes, anticipating
the likelihood of lower-paid less prestigious positions in academia (Ginther and Kahn, 2004[4]). As the academic
workforce is often male-dominated, women might be deterred from trying to have a career in academic research,
fearing cultural and gender bias (Bosquet, Combes and García-Peúalosa, 2014[5]). Also, women could tend to
self-select into less competitive career paths because they have been taught to do so earlier in life (Niederle and
Vesterlund, 2007[6]) (Gneezy, Niederle and Rustichini, 2003[7])

Who is expected to enter tertiary education? – INDICATOR B4

chapter B

Under embargo until 11/09/2018 at 11.00am CEST
Indeed, the first-time entry rates under age 25 have increased for both men and women between 2005 and 2016
in almost all countries with available data, but the gender gap has not been significantly reduced. Entry rates have
increased by 9 percentage points on average for women and 8 percentage points for men, across countries for which
data are available for both dates and the trends in entry rates for men and women have followed parallel trajectories.
Germany is an exception, as the entry rates under age 25 were almost equal in 2005 (35% for women and 33% for men),
and they are almost 10 percentage points apart in 2016 (56% for women and 47% for men). Denmark and Lithuania
are the only two countries in which the entry rates under age 25 have increased more for men than for women. In both
Denmark and Lithuania, however, the entry rates remain much higher for women than for men.
International students can significantly affect tertiary entry rates in certain countries. When international students
are excluded, Australia, a strong destination country for international students, sees its entry rate to bachelor’s
programmes drop from 97% to 78%, still remaining, however, the highest entry rate in bachelor’s programmes
across OECD countries. Conversely, Luxembourg has the lowest entry rate across OECD countries, due to the large
proportion of its citizens that study abroad.

Definitions
Entry rate is the sum of age-specific entry rates, calculated by dividing the number of entrants of a certain age in a
certain education level by the total population of that age.
Entry rate adjusted for international students is the entry rate calculated when excluding international students
in the numerator of each age-specific entry rate.
First-time tertiary-level entry rate is an estimated probability, based on current entry patterns, that a young adult
will enter tertiary education for the very first time.
International students are those students who left their country of origin and moved to another country for
the purpose of study. International students enrolling for the first time in a programme are considered first-time
entrants.
New entrants are students who enrol at the relevant level of education for the first time.
Tertiary-level entry rate is an estimated probability, based on current entry patterns, that a young adult will enter
tertiary education during his or her lifetime.

Methodology
The net entry rate for a specific age is obtained by dividing the number of first-time entrants of that age for each
type of tertiary education by the total population in the corresponding age group. The sum of net entry rates is
calculated by adding the rates for each year of age. The result represents an estimate of the probability that a young
person will enter tertiary education in his/her lifetime if current age-specific entry rates continue.
For more information, please see the OECD Handbook for Internationally Comparative Education Statistics 2018:
Concepts, Standards, Definitions and Classification (OECD, 2018[8])and Annex 3 for country-specific notes (http://
dx.doi.org/10.1787/eag-2018-36-en).
Data were collected on applicants and applications to tertiary education for first-degree programmes (i.e. first-degree
bachelor’s programmes/applied higher education programmes [ISCED 665, 666] and first-degree master’s programmes
[ISCED 766]). The population includes new applicants and applications. New applicants include people who applied for
the first time to first-degree tertiary programmes, and people who applied for the second or subsequent time to these
first-degree programmes, excluding applicants who were already enrolled as students and asked to change their field
of study or institution.
Lithuania was not an OECD member at the time of preparation of this publication. Accordingly, Lithuania does not
appear in the list of OECD members and is not included in the zone aggregates.

Source
Data refer to the academic year 2015/16 and are based on the UNESCO-UIS/OECD/EUROSTAT data collection on
education statistics administered by the OECD in 2017 (for details, see Annex 3 at http://dx.doi.org/10.1787/eag2018-36-en).
Data on applicants and applications to tertiary education were collected for the school year 2015/16 through an
ad hoc OECD survey carried out in 2017.
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B4

chapter B Access to Education, Participation and Progression
Under embargo until 11/09/2018 at 11.00am CEST
Note regarding data from Israel

B4

The statistical data for Israel are supplied by and are under the responsibility of the relevant Israeli authorities. The use
of such data by the OECD is without prejudice to the status of the Golan Heights, East Jerusalem and Israeli settlements
in the West Bank under the terms of international law.

References
Barone, C. (2011), “Some things never change”, Sociology of Education, Vol. 84/2, pp. 157-176, http://dx.doi.org/10.1177/ [3]
0038040711402099.
Bosquet, C., P. Combes and C. García-Peúalosa (2014), “Gender and promotions: Evidence from academic economists in [5]
France”, Laboratoire Interdisciplinaire d’Evaluation des Politiques Publiques (LIEPP) Working Paper n°29, www.sciencespo.fr/
liepp (accessed on 02 May 2018).
Ginther, D. and S. Kahn (2004), “Women in economics: Moving up or falling off the academic career ladder?”, Journal of [4]
Economic Perspectives, Vol. 18/3, pp. 193-214, http://dx.doi.org/10.1257/0895330042162386.
Gneezy, U., M. Niederle and A. Rustichini (2003), “Performance in competitive environments: Gender differences”, The [7]
Quarterly Journal of Economics, Vol. 118/3, pp. 1049-1074, http://dx.doi.org/10.1162/00335530360698496.
Halse, C. and S. Mowbray (2011), “The impact of the doctorate”, Studies in Higher Education, Vol. 36/5, pp. 513-525, [2]
http://dx.doi.org/10.1080/03075079.2011.594590.
Niederle, M. and L. Vesterlund (2007), “Do women shy away from competition? Do men compete too much?”, The [6]
Quarterly Journal of Economics, Vol. 122/3, pp. 1067-1101, http://dx.doi.org/10.1162/qjec.122.3.1067.
OECD (2018), OECD Handbook for Internationally Comparative Education Statistics 2018: Concepts, Standards, Definitions [8]
and Classifications, OECD Publishing, Paris, https://doi.org/10.1787/9789264304444-en.
OECD (2017), Education at a Glance 2017 : OECD Indicators, OECD Publishing, http://dx.doi.org/10.1787/eag-2017-en.

[1]

Indicator B4 Tables
1 2 https://doi.org/10.1787/888933803482

Table B4.1 Profile of new entrants into doctoral programmes (2016)
Table B4.2 Profile of first-time entrants into tertiary education (2016)
Table B4.3 First-time entry rates, by tertiary level (2016)
Cut-off date for the data: 18 July 2018. Any updates on data can be found on line at http://dx.doi.org/10.1787/eag-data-en. More breakdowns can
also be found at http://stats.oecd.org/, Education at a Glance Database.

202 Education at a Glance 2018: OECD Indicators   © OECD 2018

Who is expected to enter tertiary education? – INDICATOR B4

chapter B

Under embargo until 11/09/2018 at 11.00am CEST

Average age
of new entrants

Average age of female
new entrants

Percentage of
international new
entrants

Percentage of women
among international
new entrants

Education

Natural sciences,
mathematics
and statistics

Information and
communication
technologies (ICT)

Engineering,
manufacturing
and construction

Health and welfare

Education

Natural sciences,
mathematics
and statistics

Information and
communication
technologies (ICT)

Engineering,
manufacturing
and construction

Health and welfare

Distribution of male new entrants
by field1

Percentage
of new entrants younger
than 30 years old

Distribution of female new entrants
by field1

Percentage of female
new entrants
Partners

OECD

Table B4.1. Profile of new entrants into doctoral programmes (2016)

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

(13)

(14)

(15)

(16)

Australia
Austria
Belgium
Canada
Chile
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United Kingdom
United States

50

49

33

33

39

43

8

20

2

10

23

4

23

6

25

13

47

66

30

30

36

50

5

12

2

13

16

1

17

6

26

12

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

44

45

32

33

21

53

10

32

1

12

10

5

35

2

19

6

45

76

28

28

21

44

6

22

1

14

14

2

18

7

30

8

50

62

30

31

38

45

0

11

0

17

42

0

19

0

34

24

52

66

30

29

19

27

5

28

5

11

11

1

27

15

21

5

52

44

33

34

30

40

10

10

4

8

20

2

12

10

23

15

45

75

28

28

m

m

2

36

3

9

4

1

42

6

14

3

46

71

29

29

14

48

6

25

3

9

18

4

26

6

24

13

48

42

33

33

3

36

8

11

4

13

23

3

12

6

22

24

49

68

30

29

16

40

7

18

1

4

19

3

22

6

9

13

53

39

35

37

46

33

7

11

2

4

31

4

37

6

14

16

52

56

31

31

33

49

7

21

3

9

24

3

23

7

21

15

52

39

34

34

9

48

8

37

3

6

8

2

38

7

17

2

51

72

28

28

15

44

0

22

1

16

21

0

24

4

30

11

31

69

m

m

15

43

5d

9d

x

9d

46d

2d

15d

x

23d

40d

40

41

38

38

m

m

14

10

0

10

22

4

14

2

34

12

53

49

33

33

15

42

7

15

4

14

8

3

15

7

33

4

38

74

28

28

78

40

11

22

6

14

0

2

20

23

18

0

48

m

33

33

2

m

38

13

0

6

3

27

14

1

11

2

50

87

26

26

43

47

m

m

m

m

m

m

m

m

m

m

50

49

32

33

58

45

12

20

3

10

17

5

23

6

27

9

50

46

33

34

31

42

6

22

1

6

34

1

34

2

18

21

55

73

29

28

m

m

4

17

1

11

12

1

14

5

19

6

49

37

35

34

31

43

13

13

1

13

14

7

14

5

19

7

48

67

29

29

9

31

6

17

1

11

20

3

13

5

24

13

49

62

31

31

10

46

6

16

0

13

6

3

20

10

24

4

49

41

35

34

19

46

8

16

1

8

23

5

16

4

17

13

45

56

31

32

38

38

4

14

3

14

45

1

21

7

29

25

47

73

29

29

58

46

3

27

2

9

25

1

30

4

19

17

42

57

30

30

11

31

10

17

0

18

12

7

11

1

28

5

48

66

29

30

44

46

7

28

3

8

18

3

28

6

20

11

51

74

28

30

50

38

24

31

1

6

11

7

36

6

18

3

OECD average
EU22 average

48

59

31

31

28

42

8

19

2

10

19

4

22

6

22

12

49

62

30

30

27

42

6

19

2

11

18

2

20

7

23

11

Argentina2

56

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

Brazil
China
Colombia
Costa Rica
India
Indonesia
Lithuania
Russian Federation
Saudi Arabia
South Africa

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m
m

G20 average

40

m

m

m

m

m

m

m

m

m

m

m

m

m

m

35

30

35

34

6

17

10

24

2

21

11

5

20

2

29

6

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m
m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

37

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

51

66

30

30

9

47

6

23

1

10

17

2

21

4

29

10

45

m

m

m

7

m

m

m

m

m

m

m

m

m

m

m

39

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

45

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

1. The distribution excludes several fields (Agriculture, forestry, fisheries and veterinary; Services; Social sciences; Arts and humanities; and Business and administration).
The data for all fields are available in the Education at a Glance Database, http://stats.oecd.org/.
2. Year of reference 2015.
Source: OECD / UIS / Eurostat (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933803501

Education at a Glance 2018: OECD Indicators   © OECD 2018

203

B4

chapter B Access to Education, Participation and Progression
Under embargo until 11/09/2018 at 11.00am CEST
Table B4.2. Profile of first-time entrants into tertiary education (2016)
Percentage
of female first-time entrants

Percentage
of female first-time entrants
among international
first-time entrants

Average age
of first-time entrants

Average age of female
first-time entrants

Percentage
of international
first-time entrants

Short-cycle tertiary
(2-3 years)

Bachelor’s
or equivalent

Master’s
or equivalent

Short-cycle tertiary
(2-3 years)

Bachelor’s
or equivalent

Master’s
or equivalent

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

Australia
Austria
Belgium
Canada
Chile
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United Kingdom
United States

m
53
56
m
53
55
55
m
53
m
51
54
55
60
m
57
55
51
m
m
53
50
52
55
55
54
53
57
54
53
57
49
47
56
52

m
54
61
m
55
53
51
m
45
m
54
37
50
63
m
m
59
m
m
m
54
m
53
49
55
49
51
56
52
m
49
50
33
54
36

m
22
20
m
22
22
25
m
23
m
22
19
21
24
m
24
20
18
m
m
25
21
20
23
23
21
20
22
20
21
24
25
23
21
20

m
22
20
m
23
22
25
m
23
m
22
19
22
25
m
23
20
18
m
m
25
21
20
23
22
21
20
22
20
21
24
25
23
21
20

m
21
13
m
1
18
16
m
11
m
12
4
10
16
m
m
6
m
m
m
47
0
19
32
4
5
4
7
4
m
12
15
1
12
3

m
44
m
m
46
1
19
m
a
m
0
a
14
5
m
22
1
43
m
m
14
7
1
25
2
m
6
3
14
30
11
3
45
10
44

m
41
m
m
52
86
74
m
95
m
78
100
69
88
m
78
84
55
m
m
47
93
91
75
88
m
81
90
80
58
66
69
53
88
56

m
15
m
m
2
13
7
m
5
m
22
a
18
6
m
a
15
2
m
m
39
a
8
a
10
m
13
7
6
12
23
27
2
1
a

m
46
m
m
45
1
27
m
a
m
0
a
10
6
m
30
2
28
m
m
12
10
1
32
11
m
12
2
24
38
16
2
43
10
47

m
38
m
m
54
87
65
m
93
m
86
100
75
87
m
70
88
70
m
m
47
90
91
68
77
m
73
93
73
52
55
70
56
89
53

m
16
m
m
1
12
8
m
7
m
14
a
16
6
m
a
10
3
m
m
41
a
8
a
12
m
15
5
3
10
29
28
1
1
a

OECD average
EU22 average

54
54

51
52

22
22

22
22

12
13

16
10

74
77

10
13

18
13

73
75

10
12

Argentina
Brazil
China
Colombia
Costa Rica
India
Indonesia
Lithuania
Russian Federation
Saudi Arabia
South Africa

m
m
m
51
m
47
m
53
52
m
m

m
m
m
52
m
m
m
41
m
m
m

m
m
m
23
m
m
m
21
m
m
m

m
m
m
22
m
m
m
21
m
m
m

m
m
m
0
m
m
m
4
m
m
m

m
m
m
38
m
0
m
a
47
m
m

m
m
m
62
m
100
m
93
43
m
m

m
m
m
a
m
0
m
7
10
m
m

m
m
m
45
m
a
m
a
48
m
m

m
m
m
55
m
99
m
97
43
m
m

m
m
m
a
m
1
m
3
9
m
m

G20 average

51

m

m

m

m

23

71

7

23

73

5

OECD

B4

Partners

Distribution of male
first-time entrants
by level of education

Distribution of female
first-time entrants
by level of education

Note: This table refers to students entering tertiary education for the first time regardless of tertiary level.
Source: OECD / UIS / Eurostat (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933803520

204 Education at a Glance 2018: OECD Indicators   © OECD 2018

Who is expected to enter tertiary education? – INDICATOR B4

chapter B

Under embargo until 11/09/2018 at 11.00am CEST
Table B4.3. First-time entry rates, by tertiary level (2016)
Sum of age-specific entry rates, by demographic groups

Partners

OECD

Short-cycle tertiary
(2-3 years)

Bachelor’s
or equivalent

Master’s
or equivalent

Doctoral
or equivalent

First-time tertiary
Excluding
international
students

Excluding
international
students

Excluding
international
students

Excluding
international
students

Excluding
international
students

Total

Younger
than
Total 25 years Total

Younger
than
Total 25 years Total

Younger
than
Total 30 years Total

Younger
than
Total 30 years Total

Total

Younger
than
25 years

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

(13)

(14)

(15)

Australia
Austria
Belgium
Canada
Chile
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United Kingdom
United States

m
35
1
m
47
0
28
a
a
29
0
a
5
7
11
22
1
28
32
26
4
4
2
34
5
0
6
1
24
27
9
2
49
14
38

m
34
1
m
47
0
24
a
a
m
0
a
5
4
11
m
1
m
m
25
4
4
2
24
5
0
5
1
24
m
9
2
49
14
37

m
29
1
m
32
0
10
a
a
m
0
a
4
1
4
m
0
m
m
15
4
m
1
11
3
0
5
1
19
m
3
1
35
8
26

97
45
75
m
58
59
71
64
57
55
49
64
29
65
74
56
41
50
56
76
16
45
59
76
69
69
50
50
71
48
44
62
61
65
m

78
36
67
m
57
52
64
60
53
m
46
62
27
58
70
54
38
m
m
69
11
45
51
55
65
m
48
48
68
47
42
55
60
55
m

62
30
66
m
47
46
47
48
42
m
39
60
25
43
62
36
35
m
m
56
11
m
49
42
54
m
44
42
64
44
30
39
45
48
m

34
24
28
m
11
31
34
27
13
39
29
12
16
35
31
22
18
9
13
27
14
6
23
11
31
42
34
34
33
19
30
22
11
26
13

15
17
24
m
10
26
27
23
9
m
21
12
13
31
25
21
16
m
m
22
4
6
17
8
28
m
31
32
31
16
25
15
10
15
11

8
14
24
m
5
23
23
17
4
m
20
8
11
15
14
9
14
m
m
17
3
m
15
4
22
m
26
29
29
14
19
13
8
9
7

3.4
3.3
m
m
0.4
3.4
3.3
2.0
2.3
2.2
3.8
2.5
1.7
2.2
3.2
1.7
1.3
1.2
3.5
2.3
1.2
0.6
1.5
3.2
2.7
3.2
3.5
2.3
2.2
3.9
2.2
4.7
1.1
4.0
1.2

2.1
2.1
m
m
0.3
2.7
2.1
1.6
1.6
m
3.2
2.4
1.5
1.2
2.2
1.6
1.1
1.0
m
2.0
0.3
0.6
0.9
1.3
1.8
m
2.4
2.1
1.9
3.2
1.4
2.0
1.0
2.3
0.6

0.9
1.5
m
m
0.1
2.1
1.1
1.1
0.6
m
m
1.1
1.0
0.3
1.2
0.5
0.9
0.7
m
1.0
0.2
m
0.7
0.5
0.7
m
1.1
1.5
1.3
1.7
0.6
1.5
0.6
1.4
0.4

m
70
72
m
89
57
86
m
58
m
60
64
41
70
m
69
48
80
m
m
31
49
64
91
75
76
62
54
72
73
62
82
m
64
52

m
56
63
m
89
47
72
m
51
m
53
62
37
59
m
m
45
m
m
m
17
49
52
63
72
72
60
51
69
m
55
70
m
56
50

m
48
62
m
71
42
53
m
42
m
45
60
33
43
m
m
41
m
m
m
15
m
50
49
60
66
56
46
66
m
40
47
m
48
46

OECD average
EU22 average

16
12

13
9

9
6

58
56

53
51

45
44

24
27

19
20

15
17

2.5
2.6

1.7
1.9

0.9
1.1

66
62

57
54

49
48

Argentina1
Brazil
China
Colombia
Costa Rica
India
Indonesia
Lithuania
Russian Federation
Saudi Arabia
South Africa

60
m
38
24
m
a
6
a
45
13
m

m
m
m
24
m
a
m
a
44
m
m

m
m
m
15
m
a
m
a
m
m
m

54
m
34
33
m
45
22
77
63
66
m

m
m
m
33
m
m
m
74
56
m
m

m
m
m
24
m
m
m
66
m
m
m

5
m
4
9
m
10
2
23
20
2
m

m
m
m
9
m
m
m
20
m
m
m

m
m
m
3
m
m
m
17
m
m
m

0.6
m
0.4
0.1
m
m
0.1
1.6
1.5
0.3
m

m
m
m
0.1
m
m
m
1.5
1.4
m
m

m
m
m
0.0
m
m
m
1.0
m
m
m

m
m
m
57
m
63
m
81
83
78
m

m
m
m
57
m
m
m
78
m
m
m

m
m
m
39
m
m
m
70
m
m
m

G20 average

26

m

m

53

m

m

15

m

m

1.8

m

m

65

m

m

Note: Mismatches between the coverage of the population data and the new-entrant data mean that the entry rates for those countries that are net exporters of
students may be underestimated and those that are net importers may be overestimated. The adjusted entry rates seek to compensate for that. Please refer to
Annex 3 for further specific information by country.
1. Year of reference 2015.
Source: OECD / UIS / Eurostat (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933803539

Education at a Glance 2018: OECD Indicators   © OECD 2018

205

B4

Under embargo until 11/09/2018 at 11.00am CEST

WHO IS EXPECTED TO GRADUATE FROM TERTIARY
EDUCATION?
INDICATOR B5

• Tertiary education is marked by a large gender gap by field of study. While a high share of male
graduates obtain a degree in engineering, manufacturing and construction (25% on average across
OECD countries), the proportion of female graduates in this field is low (6% on average). In contrast,
only 5% of male graduates obtained a degree in education, compared to 14% of female graduates.

• Bachelor’s degrees remain the most common tertiary diploma held by graduates in OECD countries.
In 2016, on average across OECD countries, a majority (75%) of first-time tertiary graduates earned
a bachelor’s degree, 11% earned a master’s degree and 15% earned a short-cycle tertiary diploma.

• Based on current patterns of graduation, an average of 49% of today’s young people across
OECD countries is expected to graduate from tertiary education at least once in their lifetime.

Figure B5.1. Distribution of tertiary graduates, by gender and field of study (2016)
On average across OECD countries
Men (%)

30
Engineering,
manufacturing
and construction

25

Business,
administration
and law

20

15
Natural sciences,
mathematics
and statistics

10

Information and
communication
technologies

Arts and humanities
Social sciences, journalism
and information

Health and welfare

Services

5

Education
Agriculture, forestry,
fisheries and veterinary

0
0

5

10

15

20

25

30

Women (%)

Source: OECD / UIS / Eurostat (2018), Education at a Glance Database, http://stats.oecd.org/. See Source section at the end of
this indicator for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933803691

Context
Tertiary graduation rates illustrate a country’s capacity to provide future workers with advanced and
specialised knowledge and skills. Incentives to earn a tertiary degree, including higher salaries and
better employment prospects, remain strong across OECD countries (see Indicators A3, A4 and A5 for
further reading on these themes). Tertiary education varies in structure and scope among countries,
and graduation rates seem to be influenced by the ease of access to and flexibility in programmes, the
supply of spaces available by education level and fields of study, and also the labour-market demand
for higher skills.

206 Education at a Glance 2018: OECD Indicators   © OECD 2018

Under embargo until 11/09/2018 at 11.00am CEST
In recent decades, access to tertiary education has expanded remarkably, with new types of institutions
that offer more choice and new modes of delivery (OECD, 2016[1]) . In parallel, the student population
is becoming increasingly diverse in study pathways chosen. Students are also becoming more likely to
seek a tertiary degree outside their country of origin.

INDICATOR B5

Policy makers are exploring ways to help ease the transition from tertiary education into the labour
market (OECD, 2015[2]). Analysing current graduation patterns can help to understand student
progression through higher education and better anticipate the flow of new tertiary-educated
workers into the labour force. From an equity perspective, given the better labour-market and social
outcomes associated with tertiary education (see Chapter A), governments should also ensure that
graduation from tertiary education is not dependent on gender, socio-economic or demographic
background (see Indicator B7). For instance, to tackle inequity in tertiary education, countries such
as Australia propose scholarships, academic support and alternative entry schemes for students from
disadvantaged socio-economic backgrounds (OECD, 2014[3]).
Other findings

• Advanced tertiary degrees attract more international students (see Definitions section at the end
of this indicator) than bachelor’s or equivalent degrees. Some 26% of students in OECD countries
who graduated for the first time from a doctoral programme in 2016 were international students,
as were 17% of students who earned a master’s degree or the equivalent, and 7% of graduates who
earned a bachelor’s degree for the first time.

• First-time tertiary graduation rates are significantly lower for men than for women in all countries
with available data. On average across OECD countries, 43% of women are expected to obtain a
tertiary degree before the age of 30, compared to only 29% of men.

• Across OECD countries with available data, the average age at which people graduate for the first
time from a tertiary level programme is 26.
Note
Graduation rates are the estimated percentage of an age cohort that is expected to graduate in
their lifetime. This estimate is based on the total number of graduates in 2016 and the age-specific
distribution of graduates. Therefore, graduation rates are based on the current pattern of graduation
and are sensitive to any changes in education systems, such as the introduction of new programmes or
any variations in a programme’s duration (as has occurred in many countries in the European Union
with the implementation of the Bologna Process).
In this indicator, age generally refers to the age of students at the beginning of the calendar year.
Students could be one year older than the age indicated when they graduate at the end of the school
year. Age 30 is used as the upper limit for completing short-cycle tertiary, bachelor’s degrees and firsttime tertiary education overall. At the master’s and doctoral levels, 35 is considered to be the upper
age limit for graduation.

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Analysis

B5

Profile of graduates and first-time graduates from tertiary education
Over the past two decades, tertiary education has changed significantly in OECD countries. The student body is
more international, more women than men are graduating from this level of education, and the fields of study
chosen have evolved. These changes may reflect concerns about competitiveness in the global economy and the
labour market, but they also signal the interests and priorities of a growing student population.

Profile of graduates, by field of study
The distribution of graduates by field of study is related, for instance, to the relative popularity of these fields
among students, the number of study spaces offered in universities and equivalent institutions, and the degree
structure of the various disciplines in each country.
Currently, in most OECD countries, the largest share of graduates across all tertiary education programmes
complete degrees in business, administration and law, with a few exceptions (Table B5.2). In Korea and Portugal the
most popular field among tertiary graduates is engineering, manufacturing and construction; in Belgium, Finland,
Norway and Sweden it is health and welfare; in India it is social sciences, information and journalism; in Argentina
it is education; and in Saudi Arabia and the United States it is arts and humanities. Some of these differences can
be explained by the structure of educational systems and the types of institutions offering qualifications in each
field of study across countries. For example, degrees in fields of study such as nursing (included in the health and
welfare field) are more likely to be offered in tertiary programmes in countries that have integrated most of the
post-secondary vocational education into their tertiary education system.
In most countries, the fields of science, technology, engineering, and mathematics (also known as STEM) are less
popular. In more than half of the OECD and partner countries with available data, the combined share of students
graduating from the fields of natural sciences, mathematics and statistics, engineering, manufacturing and
construction, and information and communication technologies is still lower than the share of students graduating
from business, administration and law. In 2016, 24% of tertiary graduates obtained a degree from STEM fields on
average across OECD countries, although this ranges from 16% in the Netherlands to 36% in Germany.

Profile of graduates, by field of study and gender
The field of business, administration and law attracts an equally high share of male and female tertiary graduates
on average across OECD countries (24% for women and 25% for men) (Figure B5.1). This makes it, by far, the most
popular field among women – the second most popular field being health and welfare, which accounts for 20% of
female graduates.
In contrast, other fields, such as engineering, manufacturing and construction, are significantly more attractive to
men than women. While this is among the most popular fields for men (25% of male graduates on average across
the OECD), only 6% of female graduates obtained a degree in engineering, manufacturing and construction in 2016.
In fact, the only countries where the share of female graduates from engineering, manufacturing and construction
exceeds 10% are Mexico (11%) and Portugal (12%).
The pattern of gender imbalance is reversed in the field of education, with 14% of female graduates, but only 5% of
male graduates on average across OECD countries. Similarly, 20% of female graduates obtained a degree in health
and welfare, compared to 8% of male graduates. This gender gap in the fields of education and health and welfare is
common to all OECD countries with available data.
The relevance of gender balance across fields of study is twofold. First, from an equity perspective, it is important
to ensure that individuals can choose the studies or career paths that appeal to them, without being discouraged
by social perceptions of what constitutes female or male occupations (OECD, 2014[4]). Second, gender imbalances
in fields of study can translate into imbalances in the labour market, and there is evidence of GDP gains from more
equal participation of male and female workers (Elborgh-Woytek et al., 2013[5]).

Profile of first-time graduates, by education level
First-time graduates from tertiary education are defined as students who receive a tertiary degree for the first time
in their life in a given country.
In 2016, the large majority of first-time tertiary graduates were awarded a bachelor’s degree. On average across
OECD countries, 75% of first-time tertiary graduates earned a bachelor’s degree, 11% earned a master’s degree and
15% earned a short-cycle tertiary diploma (Table B5.1).

208 Education at a Glance 2018: OECD Indicators   © OECD 2018

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However, this pattern varies significantly across countries. Over 30% of first-time graduates obtained a master’s
or equivalent degree in Luxembourg, the Russian Federation, Slovenia and Sweden, and over 40% of first-time
graduates obtained a short-cycle tertiary degree in Austria, Chile, Turkey and the United States. Bachelor’s or
equivalent degrees remain the most common tertiary diploma held by first-time graduates in all of these countries,
with two exceptions: Austria, where short-cycle tertiary degrees are the most common tertiary diploma, and the
Russian Federation, where master’s or equivalent degrees are the most common tertiary diploma.
These differences may result from the structure of the tertiary system, the attractiveness of the programmes to
international students (particularly at master’s level, long first degrees), or more vigorous promotion of certain
programmes in some countries (such as short-cycle tertiary diplomas).

Profile of first-time graduates, by gender
Recognising the impact that education has on participation in the labour market, occupational mobility and quality
of life, policy makers and educators are emphasising the importance of reducing differences between men and
women in educational opportunities and outcomes.
In 2016, more women than men graduated from tertiary education: on average, 57% of first-time graduates
from tertiary education in OECD countries were women, ranging from 49% in Switzerland to 65% in Latvia
(Table B5.1). In addition, the share of female graduates was higher than the share of female first-time entrants
into tertiary education (see Indicator B4) in almost all OECD and partner countries with available data. The gap
between first-time graduates and first-time entrants is particularly important in the Czech Republic, Lithuania
and the Slovak Republic, with a difference of over 6 percentage points. This confirms previous findings that
women are more likely to complete tertiary education than their male counterparts (see Indicator A9 in [OECD,
2016[6]]).
Although most tertiary graduates in 2016 were women, men still have better labour market outcomes. Earnings for
tertiary-educated men are higher, on average, than those for tertiary-educated women, and tertiary-educated men
tend to have higher employment rates than women with the same level of education (see Indicators A3 and A4).

Profile of first-time graduates, by age
For some years now, many OECD countries have been concerned about the length of time tertiary students take to
complete their studies. They have developed policies to encourage students to graduate more quickly in order to get
more workers into the labour market at an earlier age. For example, the reforms following the Bologna Declaration
in 1999 (which introduced a new degree structure in European countries) were explicitly motivated by a policy
objective to reduce the length of studies.
Across OECD countries in 2016, 82% of first-time tertiary graduates graduated before age 30, and the average age
of graduation was 26 (Table B5.1). The variation among countries is large, however, ranging from 23 in Lithuania
and the United Kingdom, to 28 in Luxembourg, Sweden and Switzerland. The average age at which most students
graduate reflects a combination of average age at entry and programme duration. Entrance to tertiary education can
be delayed by the structure of upper secondary education systems, processes for entry and admission into tertiary
education, conscription requirements, or diverse pathways to transition from study to work. Programme duration
depends on the structure of the educational programme, or on the intensity of enrolment, i.e. full time or part time.
In Luxembourg, Sweden and Switzerland, students graduate later but the average age of entry is two to three years
older than the OECD average (age 24-25 compared to the average of 22). The older age at both graduation and entry
in these countries reflects students’ various trajectories before entering higher education, the flexibility of the
education system to accommodate transitions between educational programmes or between work and study, and
adults’ lifelong learning (see Indicator B4). The higher enrolment in part-time studies, as observed in Sweden and
Switzerland, also tends to delay the average graduation age (see Indicator B1).
The difference between entry and graduation age can be very small in some countries and can be driven in part
by the prevalence of short-cycle tertiary degrees, as these programmes generally take only two years, compared
to three or four years for a bachelor’s degree. Moreover, in some countries, short-cycle tertiary programmes are
specifically designed for older students, who may take longer to graduate, increasing the entry age compared to the
graduation age at this level.
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First-time graduation rates, by levels of education
More young people are expected to graduate from a bachelor’s degree programme in their lifetime than from any other
level of tertiary education. Based on patterns of graduation prevailing in 2016, on average across OECD countries,
38% of young people are expected to graduate with a bachelor’s degree, 18% are expected to earn a master’s degree,
10% are expected to graduate from a short-cycle tertiary programme, and roughly 2% are expected to graduate from
a doctoral programme in their lifetime (Table B5.3).
Although bachelor’s degrees remain the most commonly held tertiary diploma, OECD countries are also promoting
other levels of tertiary education. In an effort to improve employability and the transition into the labour market,
some countries are encouraging participation in short-cycle tertiary programmes. The probability of a person
in Chile, China, Japan, New Zealand, the Russian Federation and Turkey graduating from a short-cycle tertiary
programme in his or her lifetime is 25% or higher. Other ways of boosting employability and easing the transition
into the labour market include promoting professional or vocational programmes at bachelor’s and master’s levels.

First-time graduation rates, excluding international students
International students (see Definitions section at the end of this indicator) can have a marked impact on graduation
rates by inflating the estimate of graduate students compared to the national population. In countries with a high
proportion of international students, such as Australia and New Zealand, the difference can be significant. When
international students are excluded, first-time tertiary graduation rates drop by 31 percentage points for Australia
and 24 percentage points for New Zealand (Table B5.3).
The share of first-time international graduates varies significantly across countries. It is particularly high in
Australia, Luxembourg and New Zealand, with at least 20% of international graduates in bachelor’s or equivalent
programmes, at least 30% in master’s or equivalent programmes, and at least 40% in doctoral or equivalent
programmes. In contrast, the lowest shares of international graduates are found in Chile, Greece and Slovenia, with
less than 5% of international graduates in all levels of tertiary education (Figure B5.2).

Figure B5.2. Share of first-time international graduates, by level of education (2016)
Bachelor’s or equivalent

%

Master’s or equivalent

Doctoral or equivalent

100
90
80
70
60
50
40
30
20

Chile

Spain

Turkey

Iceland

Slovenia

Portugal

Japan

Sweden

Israel

Greece

Norway

Latvia

Germany

Hungary

Italy

United States

Finland

Slovak Republic

Denmark

Switzerland

EU22 average

Czech Republic

OECD average

Belgium

Canada

Netherlands

United Kingdom

Austria

New Zealand

0

Australia

10
Luxembourg

B5

First-time graduation rates from tertiary education
Based on 2016 patterns of graduation, 49% of today’s young people (including international students) can expect to
graduate from tertiary education at least once in their lifetime on average across OECD countries. The proportion
ranges from 18% in Luxembourg (although this percentage is negatively biased by the 74% of secondary graduates
who pursue tertiary studies abroad) to 70% or more in Australia, Denmark, Japan and New Zealand (Table B5.3).

Countries are ranked in descending order of the share of international graduates at bachelor’s or equivalent level.
Source: OECD / UIS / Eurostat (2018), Education at a Glance Database, http://stats.oecd.org/. See Source section at the end of this indicator for
more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933803710

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In spite of these cross-country differences, there is a common pattern across countries with available data: advanced
tertiary degrees attract more international students than bachelor’s or equivalent degrees. Some 26% of students in
OECD countries who graduated for the first time from a doctoral programme in 2016 were international students,
compared to 17% of students who were awarded a master’s degree or equivalent, and 7% of students who earned a
bachelor’s degree for the first time (Figure B5.2).
The high share of international students in advanced tertiary degrees may be due, in part, to the emergence of
knowledge-based economies (economies directly based on the production, distribution and use of knowledge and
information). This phenomenon has contributed to the internationalisation of research. As a consequence, many
students are seeking opportunities to study abroad at the master’s or doctoral level. From the point of view of host
countries, attracting international students can be beneficial for several reasons, such as the fees and other living
expenses the students pay, and the social and business networks that they help to build with their home countries.
In addition, international students, particularly at the master’s or doctoral or equivalent level, can contribute to
research and development (R&D) in the host country, initially as students and later on potentially as researchers
or highly qualified professionals. Doctoral students, in particular, form an integral part of the research staff of a
country (OECD, 2016[7]).

First-time graduation rates among people under age 30
The first-time graduation rate from tertiary education among people under the age of 30 is an indicator of how
many young people are expected to enter the labour force for the first time with a tertiary qualification. On average
across the 23 countries with available data, 36% of young people (excluding international students) are expected
to obtain a tertiary diploma for the first time before age 30 (Table B5.3). This rate ranges from 9% in Luxembourg
(although this value is negatively biased by the three-quarters of secondary graduates pursuing tertiary studies
abroad) to 50% in Denmark and Spain.
Men are less likely than women to graduate from tertiary education. On average across OECD countries, 43% of
women are expected to obtain a tertiary degree before age 30, compared to only 29% of men (Figure B5.3). There is
significant cross-country variation, especially for women – with graduation rates ranging from 9% in Luxembourg
to 58% in Denmark for women, and from 8% in Luxembourg to 46% in Turkey for men.
In all countries with available data, first-time tertiary graduation rates are lower for men than for women, but the
magnitude of the gender gap varies significantly across countries. The difference between men and women goes
from less than 5 percentage points in Luxembourg and Switzerland to more than 20 percentage points in Latvia.

Figure B5.3. First-time tertiary graduation rates for national students younger than 30,
by gender (2016)
Women

%

Men

70
60
50
40
30
20
10
Luxembourg

Sweden

Hungary

Germany

Italy

Switzerland

Czech Republic

Austria

EU22 average

United Kingdom

OECD average

Slovak Republic

Finland

Netherlands

Portugal

Australia

New Zealand

Latvia

Norway

Greece

Iceland

Chile

Spain

Turkey

Denmark

0

Countries are ranked in descending order of first-time graduation rates for women.
Source: OECD / UIS / Eurostat (2018), Education at a Glance Database, http://stats.oecd.org/. See Source section at the end of this indicator for
more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933803729

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B5

Some education systems accommodate a wider range of ages among their students than others. In Chile, Denmark,
Latvia, New Zealand, Sweden, Switzerland and Turkey, first-time graduation rates at the tertiary level drop by
10 percentage points or more when restricted to young people under age 30 (excluding international students).
This suggests that these education systems are more flexible in terms of access to programmes and their duration,
particularly for students outside the typical age of study. It may also reflect the different policies and attitudes
towards adult and lifelong learning. Indeed, with the exception of Turkey, the average age of first-time graduates in
these countries is typically higher than the OECD average, mainly driven by entrance at a later age.

Definitions
First-time graduate is a student who has graduated for the first time at a given level of education during the
reference period. Therefore, if a student has graduated multiple times over the years, he or she is counted as a
graduate each year, but as a first-time graduate only once.
First-time tertiary graduate is a student who graduates for the first time with a tertiary diploma, regardless of the
education programme in which he or she is enrolled. This definition is applied in Tables B5.1 and B5.3 (Columns 13
to 15).
First-time graduate from a given programme or level of tertiary education is a first-time graduate from the given
programme, but may have a diploma from another programme. For example, a first-time graduate at the master’s
level has earned a master’s degree for the first time, but may have previously graduated with a bachelor’s degree.
This definition is applied in Tables B5.1 (Columns 5 to 7) and B5.3 (Columns 1 to 12).
International students are those students who left their country of origin and moved to another country for the
purpose of study. In the majority of countries, international students are considered first-time graduates, regardless
of their previous education in other countries. In the calculations described here, when countries could not report
the number of international students, foreign students have been used as an approximation. Foreign students are
students who do not have the citizenship of the country in which they studied (for more details, please refer to
Annex 3, http://dx.doi.org/10.1787/eag-2018-36-en).
Net graduation rates represent the estimated percentage of people from a specific age cohort who will complete
tertiary education in their lifetime, based on current patterns of graduation.

Methodology
Unless otherwise indicated, graduation rates are calculated as net graduation rates (i.e. as the sum of age‑specific
graduation rates).
Gross graduation rates are used when data by age are missing. In order to calculate gross graduation rates, countries
identify the age at which graduation typically occurs (see Annex 1). The typical age of graduation for a given
education level is defined in Education at a Glance as the age range comprising at least half of the graduate population.
The number of graduates of which the age is unknown is divided by the population at the typical graduation age.
However, in many countries, defining a typical age at graduation is difficult, because graduates are dispersed over a
wide range of ages.
Some of the outliers were removed from Table B5.3 and Figure B5.3 due to comparability issues. They are, however,
presented in Annex 3 (http://dx.doi.org/10.1787/eag-2018-36-en)
The average age of students is calculated from 1 January for countries where the academic year starts in the second
semester of the calendar year and 1 July for countries where the academic year starts in the first semester of the
calendar year. As a consequence, the average age of first-time graduates may be underestimated by up to six months.
Please see Annex 3 for country-specific notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Lithuania was not an OECD member at the time of preparation of this publication. Accordingly, Lithuania does not
appear in the list of OECD members and is not included in the zone aggregates.

Source
Data refer to the academic year 2015/16 and are based on the UNESCO-UIS/OECD/EUROSTAT data collection on
education statistics administered by the OECD in 2017 (for details, see Annex 3 at http://dx.doi.org/10.1787/eag2018-36-en).

212 Education at a Glance 2018: OECD Indicators   © OECD 2018

Who is expected to graduate from tertiary education? – INDICATOR B5

chapter B

Under embargo until 11/09/2018 at 11.00am CEST
Note regarding data from Israel
The statistical data for Israel are supplied by and are under the responsibility of the relevant Israeli authorities. The use
of such data by the OECD is without prejudice to the status of the Golan Heights, East Jerusalem and Israeli settlements
in the West Bank under the terms of international law.

References
Elborgh-Woytek, K. et al. (2013), “Macroeconomic gains from gender equity”, IMF Staff Discussion Note, www.imf.org/ [5]
external/pubs/ft/sdn/2013/sdn1310.pdf.
OECD (2016), Education at a Glance 2016 : OECD Indicators, OECD Publishing, Paris, http://dx.doi.org/10.1787/eag-2016-en [6]
(accessed on 12 January 2018).
OECD (2016), OECD Science, Technology and Innovation Outlook 2016, OECD Publishing, http://dx.doi.org/10.1787/sti_ [1]
in_outlook-2016-en.
OECD (2016), “The internationalisation of doctoral and master’s studies”, Education Indicators in Focus, No. 39, OECD [7]
Publishing, Paris, http://dx.doi.org/10.1787/5jm2f77d5wkg-en.
OECD (2015), Education Policy Outlook 2015: Making Reforms Happen, OECD Publishing, Paris, http://dx.doi.org/10.1787/ [2]
9789264225442-en.
OECD (2014), Fostering Equity in Higher Education, Compendium of Practical Case Studies: Fostering inclusion of [3]
disadvantaged students, www.oecd.org/education/imhe/Fostering-inclusion-of-disadvantaged-students.pdf (accessed on
20 June 2018).
OECD (2014), PISA 2012 Results: What Students Know and Can Do (Volume I, Revised edition, February 2014): Student [4]
Performance in Mathematics, Reading and Science, PISA, OECD Publishing, Paris, http://dx.doi.org/10.1787/9789264
208780-en.

Indicator B5 Tables
1 2 https://doi.org/10.1787/888933803615

Table B5.1 Profile of a first-time tertiary graduate (2016)
Table B5.2 Distribution of tertiary graduates, by field of study (2016)
Table B5.3 First-time graduation rates, by tertiary level (2016)
Cut-off date for the data: 18 July 2018. Any updates on data can be found on line at http://dx.doi.org/10.1787/eag-data-en. More breakdowns can
also be found at http://stats.oecd.org/, Education at a Glance Database.

Education at a Glance 2018: OECD Indicators   © OECD 2018

213

B5

chapter B Access to Education, Participation and Progression
Under embargo until 11/09/2018 at 11.00am CEST
Table B5.1. Profile of a first-time tertiary graduate (2016)

Partners

OECD

B5

Share of female
graduates

Share
of graduates
below the typical
age of 30

Share of first-time tertiary graduates by level of education

Average
age

Share
of international
graduates

Short-cycle tertiary
(2-3 years)

Bachelor’s
or equivalent

Master’s
or equivalent

(1)

(2)

(3)

(4)

(5)

(6)

(7)

Australia
Austria
Belgium
Canada
Chile
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United Kingdom
United States

56
56
m
m
57
64
56
m
57
m
52
60
60
62
m
m
58
52
m
65
53
53
56
56
60
m
59
64
58
55
63
49
51
56
58

83
83
m
m
76
86
85
m
80
m
87
92
79
78
m
m
91
m
m
78
74
90
94
79
83
m
90
87
57
84
75
76
83
91
m

26
24
m
m
27
26
26
m
27
m
26
25
26
27
m
m
25
m
m
27
28
24
24
26
26
m
25
24
m
25
28
28
25
23
m

41
17
m
m
0
9
15
m
10
m
3
2
5
2
m
m
4
4
m
3
50
m
16
33
2
m
2
6
2
4
10
7
1
13
3

8
46
m
m
45
1
18
m
a
m
0
a
5
2
m
m
1
35
m
29
12
8
2
33
8
m
0
3
8
34
2
1
42
13
41

74
34
m
m
53
90
73
m
90
m
84
100
81
98
m
m
81
63
m
66
52
92
90
67
83
m
83
91
59
49
64
99
56
85
59

19
20
m
m
2
9
9
m
10
m
16
a
14
0
m
m
18
2
m
5
36
a
8
a
9
m
16
6
33
17
34
0
2
1
a

OECD average
EU22 average

57
58

82
83

26
26

10
10

15
10

75
75

11
15

Argentina
Brazil
China
Colombia
Costa Rica
India
Indonesia
Lithuania
Russian Federation
Saudi Arabia
South Africa

m
m
m
m
m
m
m
61
57
m
m

m
m
m
m
m
m
m
94
m
m
m

m
m
m
m
m
m
m
23
m
m
m

m
m
m
m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
a
27
m
m

m
m
m
m
m
m
m
93
34
m
m

m
m
m
m
m
m
m
7
39
m
m

G20 average

m

m

m

m

m

m

m

Source: OECD/UIS/Eurostat (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933803634

214 Education at a Glance 2018: OECD Indicators   © OECD 2018

Who is expected to graduate from tertiary education? – INDICATOR B5

chapter B

Under embargo until 11/09/2018 at 11.00am CEST
Table B5.2. Distribution of tertiary graduates, by field of study (2016)

Partners

OECD

Agriculture,
Social
forestry,
Engineering,
Information
Natural
sciences,
Health
manufacturing fisheries
and
sciences,
Business,
journalism
Arts
and
and
and
administration mathematics communication
and
and
veterinary welfare Services
construction
technologies
and statistics
and law
Education humanities information
(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

Australia
Austria
Belgium
Canada
Chile
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel1
Italy
Japan2
Korea
Latvia
Luxembourg
Mexico
Netherlands3
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United Kingdom
United States

9
12
9
8
15
10
6
8
6
4
10
7
17
14
6
17
4
10d
7
7
9
14
10
10
17
14
5
13
11
17
12
10
10
9
7

11
7
10
10
3
9
13
12
12
9
12
13
10
10
14
9
18
15d
17
8
11
4
9
11
8
7
9
7
11
9
6
8
11
15
20

7
11
11
16
4
11
11
9
7
8
7
12
10
16
6
21
14
8d
6
10
12
9
15
9
11
10
11
12
11
7
13
7
8
12
12

34
22
22
26
24
22
25
24
18
33
23
21
24
22
25
24
21
20d
16
31
40
35
29
26
16
24
19
20
23
19
17
29
35
22
19

6
6
4
7
1
5
6
7
5
8
9
8
4
5
8
6
8
3d
5
3
6
3
6
6
5
4
7
6
5
5
5
7
3
14
7

4
4
2
3
3
4
5
6
7
3
5
3
4
5
7
4
1
x
2
5
6
2
2
7
3
3
1
3
3
4
4
2
2
4
4

8
21
12
12
16
16
10
14
18
15
22
17
14
10
10
9
16
18d
22
13
7
21
8
8
13
16
21
12
17
15
18
16
14
9
7

1
2
2
2
2
3
1
2
2
1
2
2
3
1
2
1
3
3d
1
2
2
2
1
2
1
1
2
2
3
1
1
2
2
1
1

18
7
27
14
21
12
20
12
20
15
7
12
8
15
17
10
15
16d
14
14
6
10
16
15
21
13
18
18
8
16
22
15
10
13
17

2
8
2
2
10
7
3
6
4
3
3
4
5
3
5
0
0
8d
9
8
2
1
5
6
6
7
6
6
7
7
2
5
5
0
6

OECD average
EU22 average

10
9

11
11

10
10

24
24

6
6

4
4

14
15

2
2

15
14

5
5

Argentina4
Brazil
China
Colombia
Costa Rica
India
Indonesia
Lithuania
Russian Federation
Saudi Arabia
South Africa4

21
20
m
8
22
9
m
7
7
15
18

13
3
m
4
3
6
m
9
4
23
5

7
4
m
7
7
31
m
12
10
9
15

17
36
m
46
36
18
m
30
33
21
33

8
3
m
1
2
13
m
4
3
9
8

1
3
m
5
5
7
m
2
5
7
3

5
11
m
17
7
12
m
18
23
8
9

2
3
m
2
1
1
m
2
1
0
2

21
14
m
7
14
3
m
14
6
7
7

4
4
m
3
2
0
m
2
7
2
0

G20 average

11

11

11

26

7

3

14

2

12

4

1. Excludes short-cycle tertiary graduates.
2. Data on Information and communication technologies are included in other fields.
3. Excludes doctoral graduates.
4. Year of reference 2015.
Source: OECD/UIS/Eurostat (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933803653

Education at a Glance 2018: OECD Indicators   © OECD 2018

215

B5

chapter B Access to Education, Participation and Progression
Under embargo until 11/09/2018 at 11.00am CEST
Table B5.3. First-time graduation rates, by tertiary level (2016)
Sum of age-specific graduation rates, by demographic group

Partners

OECD

B5

Short-cycle tertiary
(2-3 years)

Bachelor’s or equivalent

Master’s or equivalent

Doctoral or equivalent

Excluding
international
students

Excluding
international
students

Excluding
international
students

Excluding
international
students

First-time tertiary
Excluding
international
students

Total

Total

Younger
than 30

Total

Total

Younger
than 30

Total

Total

Younger
than 35

Total

Total

Younger
than 35

Total

Total

Younger
than 30

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

(13)

(14)

(15)

Australia
Austria
Belgium
Canada
Chile
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United Kingdom
United States

13
24
m
22
28
0
13
a
a
m
0
a
2
1
m
m
0
25
m
14
2
2
1
27
4
0
0
1
7
22
7
0
25
8
23

9
24
m
18
28
0
11
a
a
m
0
a
2
1
m
m
0
24
m
13
2
m
1
16
4
0
0
1
7
22
6
0
25
7
23

5
23
m
14
19
0
9
a
a
m
0
a
2
0
m
m
0
m
m
9
2
m
1
9
3
0
0
1
5
19
4
0
20
5
m

60
25
44
38
36
35
57
m
48
m
32
45
26
51
m
42
30
45
m
31
10
28
44
54
40
m
34
35
m
33
26
47
34
46
40

44
21
40
34
36
32
53
m
45
m
31
44
25
50
m
41
28
44
m
30
7
m
40
40
39
m
33
33
m
33
26
44
34
38
39

35
18
39
31
27
27
44
m
35
m
28
41
20
38
m
31
26
m
m
25
6
m
38
31
33
m
30
30
m
30
19
34
28
34
m

21
20
27
12
10
24
37
m
24
m
18
10
16
29
m
20
20
8
m
15
8
5
19
9
18
m
15
32
m
19
20
18
5
22
20

9
16
23
9
10
22
30
m
22
m
15
10
14
27
m
19
19
7
m
14
2
m
14
6
16
m
15
30
m
17
16
14
4
11
17

6
14
22
7
6
19
27
m
16
m
15
7
12
15
m
11
18
m
m
12
2
m
13
4
13
m
14
27
m
15
13
12
3
8
m

2.6
1.9
m
1.6
0.3
1.6
3.2
m
2.7
m
2.8
1.4
0.9
1.6
m
1.4
1.5
1.2
1.8
0.7
1.2
0.5
2.4
2.1
1.8
m
1.7
2.1
m
2.2
2.3
3.3
0.5
3.1
1.6

1.6
1.3
m
1.1
0.3
1.3
2.1
m
2.0
m
2.3
1.3
0.9
1.0
m
1.4
1.3
1.0
m
0.6
0.2
m
1.4
1.0
1.3
m
1.4
2.0
m
m
1.4
1.4
0.5
1.7
1.2

0.7
1.0
m
0.7
0.1
0.9
1.4
m
0.8
m
1.9
0.6
0.6
0.4
m
0.5
1.2
m
m
0.4
0.1
m
1.2
0.5
0.5
m
0.7
1.6
m
m
0.7
1.1
0.3
1.2
m

77
47
m
m
60
39
70
m
51
m
38
45
31
51
m
m
36
72
m
46
18
31
49
73
47
m
40
38
m
58
40
48
60
45
56

46
40
m
m
60
35
60
m
46
m
37
44
30
50
m
m
35
69
m
45
9
m
41
49
45
m
40
36
m
56
36
44
60
40
54

37
34
m
m
44
30
50
m
38
m
33
41
24
38
m
m
31
m
m
35
9
m
39
37
38
m
37
33
m
50
26
34
49
36
m

OECD average
EU22 average

10
6

9
6

6
6

38
35

36
33

30
29

18
20

15
17

13
15

1.8
2.0

1.3
1.4

0.8
0.9

49
43

44
39

36
34

Argentina1
Brazil
China
Colombia
Costa Rica
India
Indonesia
Lithuania
Russian Federation
Saudi Arabia
South Africa1

19
m
32
17
6
a
6
a
31
m
6

m
m
m
m
m
a
6
a
m
m
m

m
m
m
m
m
a
m
a
m
m
m

13
m
31
24
46
28
19
50
34
m
13

m
m
m
m
m
m
19
m
m
m
m

m
m
m
m
m
m
m
m
m
m
m

2
m
3
12
5
7
2
18
36
m
1

m
m
m
m
m
m
2
m
m
m
m

m
m
m
m
m
m
m
m
m
m
m

0.4
m
0.2
0.1
0.2
0.1
0.1
0.9
1.1
m
0.2

m
m
m
m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
53
m
m
m

m
m
m
m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m
m
m
m

G20 average

16

m

m

33

m

m

12

m

m

1.3

m

m

m

m

m

1. Year of reference 2015.
Source: OECD/UIS/Eurostat (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933803672

216 Education at a Glance 2018: OECD Indicators   © OECD 2018

Under embargo until 11/09/2018 at 11.00am CEST

Under embargo until 11/09/2018 at 11.00am CEST

WHAT IS THE PROFILE OF INTERNATIONALLY MOBILE
STUDENTS?
INDICATOR B6

• Students become more mobile as they reach more advanced levels of education. International
students account for only 6% of total enrolment in tertiary education, but they represent 26% of
enrolment in doctoral programmes.

• International tertiary students favour fields in science, technology, engineering and mathematics
(STEM): one-third of them enrolled in these fields in 2016. International students represent at
least 9% of tertiary enrolment in natural sciences, mathematics and statistics, and information and
communication technologies, and 7% in engineering, manufacturing and construction.

• Asian students are more internationally mobile at short-cycle tertiary and master’s level, while
European students tend to be more mobile at bachelor’s and doctoral level. Student mobility
increases at the doctoral level for all other regions of origin of international students.

Figure B6.1. Incoming student mobility in tertiary education,
by level of education (2016)
International or foreign student enrolment as a percentage of total tertiary education
Total tertiary

Bachelor’s or equivalent

Master’s or equivalent

Doctoral or equivalent

Luxembourg
New Zealand
United Kingdom
Switzerland
Australia
Austria
Belgium
Canada
Czech Republic1
Denmark
Netherlands
France
Hungary
EU22 total
Ireland
Germany
Finland
Latvia
Estonia
Iceland
Sweden
Slovak Republic1
Portugal
OECD total
Italy1
United States
Saudi Arabia1
South Africa1, 2
Lithuania
Russian Federation1
Norway
Japan
Poland
Greece1
Slovenia
Spain
Korea1
Turkey1
Chile
China1
Mexico
Brazil1
Colombia1
India1
Israel1

%

90
80
70
60
50
40
30
20
10
0

1. Share of foreign rather than international students.
2. Year of reference 2015.
Countries are ranked in descending order of the percentage of international or foreign students in tertiary education.
Source: OECD (2018), Table B6.1. See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/
eag-2018-36-en).
1 2 https://doi.org/10.1787/888933803824

Context
Studying abroad has become a key differentiating experience for young adults enrolled in tertiary
education, and international student mobility has received increasing policy attention in recent years.
Studying abroad is an opportunity to access quality education, acquire skills that may not be taught at
home and get closer to labour markets that offer higher returns on education. Studying abroad is also
seen as a way to improve employability in increasingly globalised labour markets. Other motivations
include the desire to expand knowledge of other societies and to improve language skills, particularly
English.
For host countries, mobile students may be an important source of income and have a disproportionate
impact on economic and innovation systems (OECD, 2016[1]). In the short run, international students
often pay higher tuition fees than domestic students and, in some countries, incur higher registration
fees (see Indicator C5). They also contribute to the local economy through their living expenses. In
the longer run, highly educated mobile students are likely to integrate into domestic labour markets,
contributing to knowledge creation, innovation and economic performance.

218 Education at a Glance 2018: OECD Indicators   © OECD 2018

Under embargo until 11/09/2018 at 11.00am CEST
Attracting mobile students, especially if they stay permanently, is therefore a way to tap into a global
pool of talent, compensate for weaker capacity at lower educational levels, support the development
of innovation and production systems and, in many countries, to mitigate the impact of an ageing
population on future skills supply (OECD, 2016[2]). There is, however, a risk of squeezing out qualified
national students from domestic tertiary educational institutions that differentiate tuition fees by
student origin, as they may tend to give preference to international students who generate higher
revenues through higher tuition fees.

INDICATOR B6

For their countries of origin, mobile students might be viewed as lost talent. However, mobile students
can contribute to knowledge absorption, technology upgrading and capacity building in their home
country, provided they return home after their studies or maintain strong links with nationals at
home. Mobile students gain tacit knowledge that is often shared through direct personal interactions
and can enable their home country to integrate into global knowledge networks. Recent data suggest
that students leaving to study overseas are a good predictor of future scientist flows in the opposite
direction, providing evidence of a significant brain circulation effect (Appelt et al., 2015[3]). In addition,
student mobility appears to shape future international scientific co-operation networks more deeply
than either a common language or geographical or scientific proximity.
For increasingly autonomous educational institutions, competition for talent has become more
intense and global, prompting them to access a wider pool of high-potential students, with a view to
increasing their reputation and revenues and promoting cross-faculty fertilisation (Hénard, Diamond
and Roseveare, 2012[4]); (OECD, 2016[2]). In that respect, the popularity of university league tables and
other institutional rankings has reinforced a perception of differences in quality across institutions
and the value of enrolling at prestigious institutions (Perkins and Neumayer, 2014[5]). As part of their
internationalisation strategy, more and more institutions are creating offshore satellite campuses
or double degrees, changing admission rules for foreign students, revising curricula to encourage
teaching in foreign languages, or offering online courses and international internships. For example,
massive open online courses (MOOCs) have expanded the reach of existing campuses (see Box C6.1 in
Education at a Glance 2017 [OECD, 2017[6]]). As a consequence, the international activities of tertiary
educational institutions have not only expanded in volume and scope, but also in complexity.
Other findings

• The number of foreign students engaged in tertiary education programmes worldwide has exploded
in past few decades, rising from 2 million in 1999 to 5 million 17 years later. In the OECD area,
there were 3.5 million international or foreign students for study purposes in 2016 (see Definitions
section at the end of this indicator).

• Incoming student mobility has increased for almost all OECD and partner destination countries,
and it has almost doubled between 2013 and 2016 in Estonia, Latvia and Poland. Outward mobility
towards OECD destination countries is more varied: the number of nationals leaving their country
for study purposes increased the most for Hungary, India, Italy, Spain and Saudi Arabia, but it
decreased in some countries.

Education at a Glance 2018: OECD Indicators   © OECD 2018

219

chapter B Access to Education, Participation and Progression
Under embargo until 11/09/2018 at 11.00am CEST

Analysis
Profiles of internationally mobile students

B6

The relative concentration of international and foreign students in different levels of tertiary education gives a fair
indication of the attractiveness of educational programmes across countries.
The more advanced education programmes are, the more internationally open they are likely to be. In all but a few
countries, the share of international students enrolled in tertiary programmes increases gradually with education
level. On average across OECD countries, international students account for 6% of total enrolment in tertiary
programmes, but 26% of all enrolments at doctoral level.
Several factors could account for these trends, including capacity constraints in the countries of origin at higher
levels of education levels; higher returns on investing in international studies, especially in prestigious institutions
or the existence of narrow specialisations in the host countries or post-migration programmes. Students who are
more likely to travel and live abroad because of their socio-economic background are also more likely to access more
advanced educational programmes. For host countries, there are strong incentives to invest in these later stages
of education, especially at doctoral level, because graduates at that level make a large contribution to research and
development (R&D) and innovation, and to addressing socio-economic challenges.
International enrolment in bachelor’s programmes remains relatively low (below 5% in half of the countries for
which data are available and below 10% in more than 80% of the countries under review) (Figure B6.1). However,
a few countries show a more international profile at this level (10% or more of international students). In Austria,
Luxembourg and New Zealand, more than 15% of students at bachelor’s level are international.
International enrolment increases significantly at master’s level. On average across the OECD, there is more than
one international student for every ten students enrolled at this level. The proportion of incoming students at least
doubles between bachelor’s and master’s levels in two-thirds of OECD countries. Spain and Sweden host at least
four times more international students at master’s than bachelor’s level, while Australia (46% vs. 14%), Denmark
(19% vs. 6%) and Norway (7% vs. 2%) host at least three times more. The most striking increases in inflows of
students at master’s level occur in Australia (46% vs. 14%) and the United Kingdom (36% vs. 14%), as both are
already large recipients of international students at bachelor’s level. Austria, on the other hand, seems relatively
less attractive to master’s students, as its inflows are fairly similar to those at bachelor’s level. Data based on foreign
students’ citizenship show a similar trend. In Korea (7% vs. 2%) and Turkey (4% vs. 1%), the increase in student
inflows is noticeable between bachelor’s and master’s programmes.
International enrolment is much higher at doctoral level in the OECD area. The proportion of international students
in doctoral programmes in Iceland and the United States is much larger than in master’s programmes, and it reaches
40% in the United States. However, the increase of student inflows from master’s to doctoral programmes is much
less homogenous across countries than the increase from bachelor’s to master’s programmes. This is particularly
striking in Australia (decreasing from 46% at master’s level to 34% at doctoral level), Germany (from 13% to 9%),
Hungary (from 16% to 12%), Latvia (from 16 to 11%), Lithuania (from 8% to 5%) and Poland (from 4% to 2%).
Doctoral programmes in the United States attract a large share of international students, as do those in some
small countries such as Belgium, Ireland, Norway and Sweden. In Luxembourg and Switzerland, there are more
international students in doctoral programmes than national students (85% of enrolments in Luxembourg and
55% of enrolments in Switzerland come from overseas at this level). France, Iceland, Norway, Portugal, Sweden
and the United States host three times more students from abroad in doctoral programmes than in master’s
programmes. This is also the case for doctoral programmes in Chile, Colombia and Mexico, although incoming
international mobility in tertiary education is generally low in these countries (Figure B6.1).

Preference for studies in science technology, engineering and mathematics
International students tend to mainly enrol in science, technology, engineering and mathematics (STEM) fields
of study, as well as in business, administration and law. About one-third of OECD mobile students at all tertiary
levels are enrolled in STEM fields of study, with the following break-down: engineering, manufacturing and
construction (17%); natural sciences, mathematics and statistics (10%); and information and communication
technologies (6%). In the fields of natural sciences, mathematics and statistics, as well as in information and
communication technologies, international or foreign students represent at least 9% of total tertiary enrolment
across the OECD. This percentage reaches 7% in the fields of engineering, manufacturing and construction.

220 Education at a Glance 2018: OECD Indicators   © OECD 2018

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The lower language proficiency required to perform in STEM fields could partly explain the internationalisation of
these fields of study. But the central role played by science, engineering and business management in innovation
processes and value creation (Hénard, Diamond and Roseveare, 2012[4]), (OECD, 2014[7]) and the wage premium and
better career opportunities associated with graduating in these disciplines (see Indicator A4) are probably of greater
importance.
Across the OECD, international or foreign students represent 7% of all students enrolled in social sciences, journalism
and information and 6% of those enrolled in arts, humanities, business, administration and law. International students
represent the majority, or a high share (at least 19%), of total enrolment in tertiary education in most fields of study
in Luxembourg. International students also account for more than one-third of all students in Australia in information
and communication technologies, in New Zealand in the fields of services, business, administration, law, information
and communication technologies, and in Switzerland in the fields of natural sciences, mathematics and statistics.
International student flows in tertiary education
In 2016, there were 3.5 million international students enrolled in tertiary education programmes across
OECD countries. The pools and flows of this mobile talent remain very concentrated worldwide, and mobility
pathways are deeply rooted in historical patterns.

Origin and destination of mobile students studying in OECD countries
Data on international student flows illustrate the strength of proximity factors, such as language, historical
ties, geographical distance, bilateral relationships and political framework conditions (e.g. the European Higher
Education Area) as key determinants for mobility.
Students from Asia form the largest group of international students enrolled in OECD tertiary education programmes
at all levels (1.9 million, 55% of all international students in 2016, Figure B6.2). Of these, over 860 000 come from China.
Two-thirds of Asian students converge towards only three countries: Australia (15%), the United Kingdom (11%)
and the United States (38%).
The second major region of origin of international students is Europe, with 845 000 European students crossing
borders for the purpose of studying (24% of all mobile students enrolled in OECD countries). European students
prefer to stay in Europe: 80% of them enrol in tertiary studies in another European country. This is partly explained
by the existence and popularity of the Erasmus student exchange programme within the European Union.
Africa and the Americas (North America, South America and the Caribbean) – both with fewer than
300 000 international students – remain far behind as sending regions. Three-quarters of African students enrolled
in OECD countries study in Europe, especially France (35%), the United Kingdom (12%) and Germany (7%),
whereas North and Latin American students are divided between the United States (37%) and Europe (45%).
Among Latin American students in OECD countries, 12% choose to study in Spain. This reflects their stronger
cultural, linguistic and historical connections, as does North American students’ tendency to gravitate towards
the United Kingdom (22%).
The United States is the top OECD destination country for mobile tertiary students. Of the 3.5 million international
students in the OECD area, 971 000 enrol in programmes in the United States. English-speaking countries are
the most attractive overall, with four countries receiving over half the mobile students. After the United States,
the United Kingdom accounts for 432 000 international students, Australia 336 000 and Canada 189 000.
International students in these countries mainly originate from Asia, accounting for 87% of international students
in Australia, 77% in the United States, 61% in Canada and 52% in the United Kingdom.
The European Union is another key geographical area of inward mobility, with 1.6 million international students
enrolled in European programmes. France and Germany (both at 245 000) are major host countries for international
students, far ahead of Italy (93 000), the Netherlands (90 000) and Austria (70 000). But mobility channels differ
significantly between these two large players. While a majority of mobile students entering France come from
Africa (42%), other European countries remain the main source of international enrolment for Germany (40%). For
both countries, Asia comes second as a region of origin, accounting for 21% of total incoming mobile students in
France and 36% in Germany. International students in Austria, Italy and the Netherlands are also mainly European,
while inflows from Latin American countries make a significant contribution to Spanish tertiary cohorts, as well
as to those of smaller receiving countries, such as Portugal. Small European countries particularly rely on intraEuropean mobility. More than 80% of students entering the Czech Republic, Denmark, Luxembourg, Poland,
the Slovak Republic and Slovenia travel from inside Europe.
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The Russian Federation is also a major destination country, with 250 000 students enrolled from abroad. It is
also a regional catalyst of student inflows, with two-thirds of them coming from neighbouring countries that have
historical links with the former Soviet Union: Azerbaijan (6%), Belarus (6%), Kazakhstan (28%), Turkmenistan (7%),
Ukraine (9%) and Uzbekistan (8%).
Asian students (55% of OECD international students) enrolled in short-cycle tertiary and master’s programmes
are more mobile than those enrolled in bachelor’s or doctoral programmes. They represent 66% of the number
of international students at short-cycle tertiary level and 57% at master’s level. By contrast, European students
(who represent 24% of the OECD international enrolment in tertiary education) tend to be more mobile at
bachelor’s (25%) and doctoral level (32%). Student mobility increases at the doctoral level for all the other regions of
origin of international students, with students from Africa, the Americas and Oceania representing a higher share
of international students than at lower educational levels (Figure B6.2).

Figure B6.2. Distribution of international students studying in OECD countries,
by region of origin and level of education (2016)
Percentage of international or mobile students enrolled in OECD countries
By region of origin

%

100

Europe
Africa
North America
Rest of the World
(non allocated geographically)

By level of education

Asia
Latin America & Carribean
Oceania
Doctoral
or equivalent
7%

90

Short-cycle
tertiary
6%

80
70
60

Master’s
or equivalent
37%

50
40

Bachelor’s
or equivalent
50%

30
20
10
0

Total
tertiary

Short-cycle
tertiary

Bachelor’s
Master’s
Doctoral
or equivalent or equivalent or equivalent

Source: OECD (2018), Education at a Glance Database, http://stats.oecd.org. See Source section at the end of this indicator for more information
and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933803843

Brain circulation: the state of play
The growth in international student mobility and its impact on national talent pools also vary significantly across
countries.
Some countries experience an outward flow of students, measured by the percentage of all national students studying
abroad. This percentage reaches at least 7% in several European countries, such as Estonia, Iceland, Ireland, Latvia,
Lithuania, Norway and the Slovak Republic. Luxembourg is a particularly stark example, with nearly three-quarters
of its students enrolled in foreign tertiary programmes (seven out of ten national students abroad are enrolled in
neighbouring countries). In these countries, the percentage of national students enrolled abroad significantly exceeds
the share of international students enrolled in national institutions, with the exception of Ireland and Latvia.
In some countries, large cohorts of international students outnumber their own national talent. This inflow of
students is measured by the number of international (or foreign) students on a country’s soil for every hundred
national students enrolled in tertiary education programmes (at home or abroad). The top destinations for
international students are mainly, but not exclusively, English‑speaking countries. The countries where the ratio
between incoming international students and national students is the highest are Australia (21), New Zealand (24)
and the United Kingdom (22), but also Luxembourg (23) and Switzerland (20) (Table B6.3).

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Determinants of international mobility
Identifying the determinants of international student mobility is key for designing efficient policies to encourage
brain circulation. Student migration is mainly driven by differentials in education capacity (i.e. a lack of educational
facilities in the country of origin or the prestige of educational institutions in the country of destination). It is also
driven by differentials between origin and destination countries in the returns to or rewards for education and
skills. Economic factors include: 1) higher economic performance in the host country; 2) exchange rate differentials
that could influence mobility and education cost differentials; and 3) more affordable mobility and education costs
in the host country (due, for instance, to lower tuition fees or higher education subsidies). In addition, the decision
to study abroad may be determined by non-economic factors, such as political stability and the robustness of
institutions in the receiving country, or cultural and religious proximity between origin and destination countries
(Guha, 1977[8]), (UNESCO, 2013[9]) (Weisser, 2016[10]).
Fixing appropriate tuition fees remains one of the most debated topics in education policy, in a context in which
policy makers aim to increase participation in higher education and achieve greater equity in education. The cost
of education for individuals varies substantially across countries, as a result of different systems of tuition fees and
costs of ancillary services, combined with different levels of public allocations for tertiary education and public
support for students (see Indicator C5). The perceived quality of instruction abroad and the perceived value of host
institutions are key criteria for international students when selecting their country of destination (Abbott and
Silles, 2016[11]); (Beine, Noël and Ragot, 2014[12]); (Marconi, 2013[13]). Top destinations for internationally mobile
students include a large number of top-ranked higher education institutions.
Students worldwide are increasingly aware of differences in quality among tertiary education systems, as university
league tables and other international university rankings are widely diffused. At the same time, the ability to
attract international students has become a criterion in assessing the performance and quality of institutions.
As governments seek to encourage the internationalisation of higher education, they have revised performance
agreements with domestic institutions, for example by taking into account the inflows of international students in
university funding formulas.
The language of instruction is a strong determinant of students’ choice of destination. Countries where the language
of instruction is widely spoken and read, such as English, French, German, Russian and Spanish, can be particularly
attractive to international students.
English is the lingua franca of the globalised world, with one in four people using it worldwide (OECD, 2016[2])
(Sharifian, 2013[14]). Not surprisingly, countries where English is an official language (either legally or de facto),
such as Australia, Canada, New Zealand, the United Kingdom and the United States, are top OECD destination
countries for international students. In many countries, English has increasingly been included in the mandatory
school curriculum, even at early education levels, and many students aim to improve their English-language skills
through immersion in a native context. In addition, an increasing number of institutions in non-English-speaking
countries offer tertiary-education programmes taught in English. In Europe, the diffusion of English as a medium
of instruction is especially noticeable in the Nordic countries (see [Wächter and Maiworm, 2015[15]] and Box C4.1
in [OECD, 2015[16]]).
Trends in the number of international students
The increase in foreign enrolment has been driven by a variety of domestic and external factors, both push
(encouraging outward mobility) and pull (encouraging inward mobility) (UNESCO, 2013[9]). The skills’ needs of
increasingly knowledge-based and innovation-driven economies have spurred demand for tertiary education
worldwide, while local education capacities have not always evolved fast enough to meet growing domestic demand.
Rising wealth in emerging economies has further prompted children in a growing middle class to seek educational
opportunities abroad. At the same time, economic factors (e.g. costs of international flights), technological factors
(e.g. the spread of the Internet and social media to maintain contacts across borders) and cultural factors (e.g. use
of English as a common working and teaching language) have contributed to making international mobility
substantially more affordable and less irreversible than in the past.
Initiatives at national, regional, local, supranational or institutional level have also contributed to cross-border
mobility. In 2011, the European Union set the ambitious goal of increasing the proportion of EU graduates from
higher education who complete study or training abroad to 20% by 2020 (Council of the European Union, 2011[17]).
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In Europe, many students benefitted from the Erasmus programme. In addition, the Nordic and Baltic countries
operate the Nordplus Higher Education Programme, a broad mobility and network programme that aims to reinforce
collaboration, joint curriculum planning, student and teacher mobility and the sharing of best practices between
institutions. Most countries have implemented reforms aiming to lower barriers to migration of the highly skilled,
beyond education purposes, and most countries operate funding programmes to support inward, outward or return
mobility. While their conditions of migration differ (e.g. short-term vs. long-term settlement), the most common
target populations of these programmes are pre-doctoral students and early stage researchers (both doctoral and
postdoctoral).
Box B6.1. Long-term growth in the global number of mobile students
The number of foreign students enrolled in tertiary education programmes worldwide has exploded over the
past two decades. It rose from 2 million in 1999 to 5 million in 2016, at an average annual rate of 5.1% among
OECD countries and 6.4% among non-OECD countries. This increase was exponential until early 2010, when
data show a levelling off in long-term trends (Figure B6.a). However, the number of international students
began increasing strongly again in 2014 (an increase of 9% compared to 2013) and the following years (an
increase of 7% in 2015 and 6% in 2016) (Figure B6.a).

Figure B6.a. Growth in international or foreign enrolment in tertiary education worldwide
(1998 to 2016)
Number of foreign students enrolled in OECD and non-OECD countries
OECD

Millions of mobile students

5.5
5.0
4.5
4.0
3.5
3.0
2.5
2.0
1.5
1.0
0.5
0.0

Non-OECD
Total 5.0
Non-OECD 1.5
OECD 3.5

1998

2000

2002

2004

2006

2008

2010

2012

2014

2016 Year

Note: The data sources use similar definitions, thus making their combination possible. Missing data were imputed with the closest data
reports to ensure that breaks in data coverage do not result in breaks in time series.
Source: OECD / UIS / Eurostat (2018). See Source section at the end of this indicator for more information and Annex 3 for notes (http://
dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933803881

Student migration into the OECD area remains dynamic, but new migration poles are consolidating in developing
economies. Data on the students who cross borders for the sole purpose of study (also defined as international
students, see Definitions section at the end of this indicator) between 2013 and 2016 show an estimated 19% increase
in international student flows towards the OECD area. The largest increases in incoming student numbers have
been observed in Estonia, Latvia, Poland and the Russian Federation, where the number of international students
enrolled in national tertiary programmes nearly doubled over the period. Other attracting poles include Chile
(an increase of 52%), Mexico (58%) and Turkey (62%). Conversely, Austria and the Slovak Republic experienced a
slight decline (a decrease of 1%) in the number of international enrolments between 2013 and 2016.
Outward student mobility towards OECD countries also increased between 2013 and 2016 for many origin countries,
but to a more limited extent. The largest increase was observed for students coming from India (an increase of
78% compared to 2013), far ahead of students coming from OECD countries, such as Finland, Hungary, Italy,
the Netherlands, Spain and the United Kingdom (increases between 22% and 37% over the same period) and from
China and Saudi Arabia. Conversely, outward mobility decreased by 10% or more for students coming from Ireland,
Korea, Latvia and Lithuania.

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Figure B6.3. Change in the outflow compared to the inflow of mobile students (2013 to 2016)
Indices of change of inward and outward mobility (2013 = 100)

B6

Incoming mobile students
(2013 = 100)

200

Poland

190

Estonia

Latvia

Russian Federation

180
170

Turkey

160
Mexico

Chile

150
Lithuania

140

Ireland

130

New Zealand

Germany

120

Canada

Slovak Republic
Denmark
Japan

Iceland

100

Israel

90

Portugal

Belgium
China

Netherlands

United States

Norway

Sweden

Korea

110

Australia

Hungary

Spain

Saudi
Arabia

India
X=178
y=130

Luxembourg
Chile
Austria

France
Slovenia

Czech Republic

Finland

Italy

United Kingdom

80
80

90

100

110

120

130

140

National students enrolled in other OECD
and partner countries (2013 = 100)

Note: Excludes incoming mobile students in short-cycle tertiary education for Italy and Spain. The black diagonal line represents where the inward
mobility change equals the outward mobility change.
Source: OECD (2018), Education at a Glance Database, http://stats.oecd.org. See Source section at the end of this indicator for more information
and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933803862

Definitions
Foreign students are those who are not citizens of the country in which they are enrolled and where the data are
collected. Although they are counted as internationally mobile, they may be long-term residents or even be born in
the “host” country. While pragmatic and operational, this classification may be inappropriate for capturing student
mobility because of differing national policies regarding the naturalisation of immigrants. For instance, Australia
has a greater propensity than Switzerland to grant permanent residence to its immigrant populations. This implies
that even when the proportion of foreign students in tertiary enrolment is similar for both countries, the proportion
of international students in tertiary education is smaller in Switzerland than in Australia. Therefore, for student
mobility and bilateral comparisons, interpretations of data based on the concept of foreign students should be made
with caution. In general, international students are a subset of foreign students.
International students are those who left their country of origin and moved to another country for the purpose of
study. The country of origin of a tertiary student is defined according to the criterion of “country of upper secondary
education”, “country of prior education” or “country of usual residence” (see below). Depending on country-specific
immigration legislation, mobility arrangements (such as the free mobility of individuals within the European Union
and the European Economic Area) and data availability, international students may be defined as students who are
not permanent or usual residents of their country of study, or alternatively as students who obtained their prior
education in a different country.
The country of prior education is the country in which students obtained their upper secondary qualification
(upper secondary or post-secondary non-tertiary completion with access to tertiary education programmes) or the
qualification required to enrol in their current level of education. Where countries are unable to operationalise this
definition, it is recommended that they use the country of usual or permanent residence to determine the country of
origin. Where this too is not possible and no other suitable measure exists, the country of citizenship may be used.
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B6

Permanent or usual residence in the reporting country is defined according to national legislation. In practice, this
means holding a student visa or permit, or electing a foreign country of domicile in the year prior to entering the
education system of the country reporting the data.
Country-specific operational definitions of international students are indicated in the tables as well as in Annex 3
(http://dx.doi.org/10.1787/eag-2018-36-en).

Methodology
Defining and identifying mobile students, as well as their types of learning mobility, are a key challenge for developing
international education statistics, since current international and national statistical systems only report domestic
educational activities undertaken within national boundaries (OECD, 2018[18]).
Data on international and foreign students are therefore obtained from enrolments in their countries of destination.
This is the same method used for collecting data on total enrolments, i.e. records of regularly enrolled students in an
education programme. Students enrolled in countries that did not report to the OECD or to the UNESCO Institute
for Statistics are not included and, for their countries of origin, the total number of national students enrolled
abroad may be underestimated.
The total number of students enrolled abroad refers to the count of international students, unless data are not
available and the count of foreign students is used instead. Enrolment numbers are computed using a snapshot
method, i.e. counting enrolled students at a given period of time (e.g. a specific day or period of the year).
This methodology has some limits. OECD international statistics on education tend to overlook the impact of
distance and e-learning, especially fast-developing MOOCs, students who commute from one country to another
on a daily basis and short-term exchange programmes that take place within an academic year and are, therefore,
under the radar. Other concerns arise from the classification of students enrolled in foreign campuses and European
schools in host countries’ student cohorts.
Current data for international students can only help track student flows involving OECD and partner countries
as receiving countries. It is not possible to assess extra-OECD flows and, in particular, the contributions of SouthSouth exchanges to global brain circulation.
For more information, please see the OECD Handbook for Internationally Comparative Education Statistics 2018:
Concepts, Standards, Definitions and Classifications (OECD, 2018[18]) and Annex 3 for country-specific notes (http://
dx.doi.org/10.1787/eag-2018-36-en).
Lithuania was not an OECD member at the time of preparation of this publication. Accordingly, Lithuania does not
appear in the list of OECD members and is not included in the zone aggregates.

Source
Data refer to the academic year 2015/16 and are based on the UNESCO-UIS/OECD/EUROSTAT data collection on
education statistics administered by the OECD in 2017 (for details, see Annex 3 at http://dx.doi.org/10.1787/eag2018-36-en).
Data from Argentina, China, India, Indonesia, Saudi Arabia and South Africa are from the UNESCO Institute of
Statistics (UIS).

Note regarding data from Israel
The statistical data for Israel are supplied by and are under the responsibility of the relevant Israeli authorities. The use
of such data by the OECD is without prejudice to the status of the Golan Heights, East Jerusalem and Israeli settlements
in the West Bank under the terms of international law.

References
Abbott, A. and M. Silles (2016), “Determinants of international student migration”, The World Economy, Vol. 39/5, [11]
pp. 621-635, http://dx.doi.org/10.1111/twec.12319.
Appelt, S. et al. (2015), “Which factors influence the international mobility of research scientists?”, OECD Science, Technology [3]
and Industry Working Papers, No. 2015/2, OECD Publishing, Paris, http://dx.doi.org/10.1787/5js1tmrr2233-en.

226 Education at a Glance 2018: OECD Indicators   © OECD 2018

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Beine, M., R. Noël and L. Ragot (2014), “Determinants of the international mobility of students”, Economics of Education [12]
Review, Vol. 41, pp. 40-54, http://dx.doi.org/10.1016/J.ECONEDUREV.2014.03.003.
Council of the European Union (2011), “Council conclusions on the modernisation of higher education”, 3128th [17]
Education, Youth, Culture and Sport Council Meeting, Brussels, 28 and 29 November 2011, Council of the European Union,
Brussels.
Guha, A. (1977), “Brain-drain issue and indicators on brain-drain”, International Migration, Vol. 15/1, pp. 3-20, http:// [8]
dx.doi.org/10.1111/j.1468-2435.1977.tb00953.x.
Hénard, F., L. Diamond and D. Roseveare (2012), Approaches to Internationalisation and Their Implications for Strategic [4]
Management and Institutional Practice: A Guide for Higher Education Institutions, OECD, www.oecd.org/education/imhe/
Approaches%20to%20internationalisation%20-%20final%20-%20web.pdf (accessed on 29 April 2018).
Marconi, G. (2013), “Rankings, accreditations, and international exchange students”, IZA Journal of European Labor [13]
Studies, Vol. 2/1, p. 5, http://dx.doi.org/10.1186/2193-9012-2-5.
OECD (2018), OECD Handbook for Internationally Comparative Education Statistics 2018: Concepts, Standards, Definitions [18]
and Classifications, OECD Publishing, Paris, https://doi.org/10.1787/9789264304444-en.
OECD (2017), Education at a Glance 2017: OECD Indicators, OECD Publishing, Paris, http://dx.doi.org/10.1787/eag-2017-en. [6]
OECD (2016), “International mobility of highly skilled”, in OECD Science, Technology and Innovation Outlook 2016, OECD [1]
Publishing, Paris, http://dx.doi.org/10.1787/sti_in_outlook-2016-17-en.
OECD (2016), OECD Science, Technology and Innovation Outlook 2016, OECD Publishing, Paris, http://dx.doi.org/10.1787/ [2]
sti_in_outlook-2016-en.
OECD (2015), Education at a Glance 2015: OECD Indicators, OECD Publishing, Paris, http://dx.doi.org/10.1787/eag-2015-en. [16]
OECD (2014), OECD Science, Technology and Industry Outlook 2014, OECD Publishing, Paris, http://dx.doi.org/10.1787/ [7]
sti_outlook-2014-en.
Perkins, R. and E. Neumayer (2014), “Geographies of educational mobilities: Exploring the uneven flows of international [5]
students”, The Geographical Journal, Vol. 180/3, pp. 246-259, http://dx.doi.org/10.1111/geoj.12045.
Sharifian, F. (2013), “Globalisation and developing metacultural competence in learning English as an International [14]
Language”, Multilingual Education, Vol. 3/1, p. 7, http://dx.doi.org/10.1186/2191-5059-3-7.
UNESCO (2013), The International Mobility of Students in Asia and the Pacific, UNESCO, http://unesdoc.unesco.org/ [9]
images/0022/002262/226219E.pdf (accessed on 03 July 2018).
Wächter, L. and F. Maiworm (2015), “English-taught programmes in European higher education: The state of play in 2014”, [15]
ACA Papers on International Cooperation in Education , www.aca-secretariat.be/fileadmin/aca_docs/images/members/ACA2015_English_Taught_01.pdf (accessed on 07 May 2018).
Weisser, R. (2016), “Internationally mobile students and their post-graduation migratory behaviour: An analysis of [10]
determinants of student mobility and retention rates in the EU”, OECD Social, Employment and Migration Working Papers,
No. 186, OECD Publishing, Paris, http://dx.doi.org/10.1787/5jlwxbvmb5zt-en.

Indicator B6 Tables
1 2 https://doi.org/10.1787/888933803748

Table B6.1

International student mobility and foreign students in tertiary education (2016)

Table B6.2

Share of international and foreign students among tertiary students and distribution by field of
education (2016)

Table B6.3

Mobility patterns of foreign and international students (2016)

WEB Table B6.4 Distribution of international and foreign students in tertiary education, by country of origin (2016)
WEB Table B6.5 Distribution of international and foreign students in tertiary education, by country of destination (2016)
Cut-off date for the data: 18 July 2018. Any updates on data can be found on line at http://dx.doi.org/10.1787/eag-data-en. More breakdowns can
also be found at http://stats.oecd.org/, Education at a Glance Database.

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Under embargo until 11/09/2018 at 11.00am CEST
Table B6.1. International and foreign student mobility in tertiary education (2016)
International or foreign student enrolment as a percentage of total tertiary enrolment

B6

Reading the first column of the upper section of the table (international): 17% of all students in tertiary education in Australia are international students
and 18% of all students in tertiary education in Switzerland are international students. The data presented in this table on international student mobility
represent the best available proxy of student mobility for each country.
Reading the first column of the lower section of the table (foreign): 12% of all students in tertiary education in the Czech Republic are not Czech citizens, and
2% of all students in tertiary education in Korea are not Korean citizens.
Share of international or foreign students by level of tertiary education
Total tertiary
education

Short-cycle tertiary
programmes

Bachelor’s or
equivalent level

(1)

(2)

(3)

Master’s or
equivalent level

Doctoral or
equivalent level

Number
of international
or foreign students
(in thousands)

(4)

(5)

(6)

International students

Australia
Austria
Belgium1
Canada
Chile
Denmark
Estonia
Finland
France
Germany
Hungary
Iceland
Ireland
Japan
Latvia
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovenia
Spain
Sweden
Switzerland
United Kingdom
United States

17
16
12
12
0
11
7
8
10
8
9
7
8
4
8
47
0
11
20
4
3
6
3
3
7
18
18
5

9
1
7
10
0
16
a
a
5
0
1
25
2
5
2
9
0
1
27
1
0
2
1
2
0
0
4
2

14
18
9
10
0
6
5
5
7
5
7
4
7
2
6
27
0
9
16
2
3
3
3
1
2
10
14
4

46
20
20
18
1
19
10
12
13
13
16
9
15
7
16
73
1
17
26
7
4
7
5
8
11
29
36
10

34
28
44
32
8
34
12
21
40
9
12
36
27
18
11
85
3
40
48
22
2
26
10
15
35
55
43
40

336
70
61
189
5
34
3
23
245
245
26
1
18
143
6
3
13
90
54
11
55
20
3
53
28
52
432
971

Foreign students

OECD

Czech Republic
Greece
Israel
Italy
Korea
Slovak Republic
Turkey

12
3
m
5
2
6
1

6
a
m
7
0
1
0

10
4
3
5
2
5
1

13
1
4
5
7
8
4

16
1
6
14
9
9
7

43
24
10
93
62
10
88

OECD total
EU22 total

6
9

3
4

4
7

12
13

26
23

3 520
1 585

Lithuania

4

a

3

8

5

5

Argentina
Brazil
China
Colombia
Costa Rica
India
Indonesia
Russian Federation
Saudi Arabia
South Africa2

m
0
0
0
m
0
m
4
5
4

m
0
x(1)
0
m
a
m
3
x(1)
x(1)

m
0
x(1)
0
m
x(1)
m
x(4)
x(1)
x(1)

m
1
x(1)
1
m
x(1)
m
4d
x(1)
x(1)

m
2
x(1)
3
m
x(1)
m
5
x(1)
x(1)

m
20
138
4
m
45
m
250
80
43

Foreign students

International
students

Partners

1. Data on short-cycle tertiary programmes are based on nationality and refer to the Flemish Community only.
2. Year of reference 2015.
Source: OECD / UIS / Eurostat (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933803767

228 Education at a Glance 2018: OECD Indicators   © OECD 2018

What is the profile of internationally mobile students? – INDICATOR B6

chapter B

Under embargo until 11/09/2018 at 11.00am CEST
Table B6.2. Share of international and foreign students among tertiary students and distribution

by field of education (2016)

Total tertiary education

Health and welfare

Services

(8)

Engineering, manufacturing
and construction

Health and welfare

(7)

Information and
communication technologies

Engineering, manufacturing
and construction

(6)

Natural sciences,
mathematics and statistics

Information and
communication technologies

(5)

Business, administration
and law

Natural sciences,
mathematics and statistics

(4)

Social sciences, journalism
and information

Business, administration
and law

(3)

Arts and humanities

Social sciences, journalism
and information

(2)

Education

Arts and humanities

(1)

B6

Distribution of international and foreign students,
by field of education

Services

Education

Share of international and foreign students among all students,
by field of education

(9)

(10)

(11)

(12)

(13)

(14)

(15)

(16)

(17)

(18)

International students

Australia
Austria
Belgium
Canada
Chile
Denmark
Estonia
Finland
France
Germany
Hungary
Iceland
Ireland
Japan1
Latvia
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovenia
Spain
Sweden
Switzerland
United Kingdom
United States2

3
7
5
3
0
3
0
4
5
2
2
7
1
1d
2
19
m
2
9
1
1
11
2
2
1
9
6
2

10
23
17
10
0
11
7
7
13
10
8
24
6
5d
5
37
m
15
12
7
3
7
4
3
7
25
15
4d

9
28
15
10
0
10
10
5
13
8
9
4
9
12d
8
46
m
17
13
4
7
6
5
3
7
24
20
5

28
12
8
15
1
14
12
10
10
6
3
4
9
2d
8
61
m
12
34
3
4
7
3
3
6
14
32
7

17
21
20
15
1
12
3
9
13
7
5
18
8
2d
3
61
m
11
18
11
2
6
5
2
17
35
13
10

37
17
6
20
0
17
8
15
19
10
5
2
9
x
7
59
m
8
33
6
5
7
5
2
10
19
19
8

26
15
14
19
0
20
5
8
11
11
4
4
11
4d
5
33
m
13
25
5
1
5
4
2
9
20
29
12

8
18
16
4
0
4
2
4
4
7
29
2
13
1d
16
22
m
6
7
3
5
4
3
4
4
9
8
2d

6
4
13
4
0
18
0
9
4
3
2
2
4
2d
8
74
m
12
44
2
4
4
2
2
3
12
0
2

2
6
4
1
9
2
0
2
2
2
3
8
1
2d
2
5
m
2
3
5
2
7
5
7
3
5
2
3

6
15
13
11
5
12
13
10
17
17
10
44
11
25d
5
10
m
12
7
18
9
11
12
11
13
15
13
13d

3
20
11
13
6
9
11
5
11
8
10
9
6
32d
8
10
m
17
7
12
21
12
15
11
12
12
12
11

51
16
13
29
34
29
42
23
28
18
9
12
21
12
33
45
m
32
38
14
26
25
16
24
12
20
34
24

5
10
6
12
6
6
3
6
13
8
2
13
9
2
1
8
m
5
8
15
2
6
8
4
14
17
11
13

9
5
2
6
3
7
9
17
5
8
2
2
8
x
5
7
m
2
10
6
6
2
7
3
7
3
4
6

13
15
12
20
15
19
12
20
16
29
10
5
14
19d
9
6
m
11
11
15
8
21
20
11
26
18
15
17

9
9
33
5
13
8
4
10
6
6
43
4
27
3d
28
3
m
9
5
11
15
11
9
23
12
8
7
9d

1
1
2
1
8
5
0
5
1
1
2
1
2
3d
9
3
m
7
9
3
9
4
5
4
1
2
0
2

Foreign students

OECD

Czech Republic
Greece
Israel
Italy
Korea
Slovak Republic
Turkey

2
4
m
2
1
4
1

12
5
m
8
2
5
1

14
4
m
4
4
2
2

13
2
m
4
4
4
1

14
4
m
3
1
2
3

22
4
m
7
1
2
1

11
2
m
6
1
3
3

17
4
m
4
1
19
2

7
3
m
2
1
2
1

2
5
m
2
3
8
6

10
20
m
26
21
7
13

11
15
m
11
14
4
15

21
15
m
20
30
11
19

8
10
m
5
4
2
6

9
4
m
2
2
1
1

15
15
m
21
16
6
25

18
11
m
12
4
56
11

4
3
m
0
6
2
3

OECD total
EU22 total

2
3

6
10

7
10

6
10

9
9

10
11

7
10

3
7

2
4

3
3

14
15

12
12

27
25

10
9

6
5

17
17

9
11

2
2

Lithuania

2

6

7

4

1

4

3

5

2

3

12

18

28

1

3

15

18

1

Argentina
Brazil
China
Colombia
Costa Rica
India
Indonesia
Russian Federation
Saudi Arabia
South Africa

m
0
m
0
m
m
m
m
m
m

m
1
m
0
m
m
m
m
m
m

m
0
m
0
m
m
m
m
m
m

m
0
m
0
m
m
m
m
m
m

m
1
m
0
m
m
m
m
m
m

m
0
m
0
m
m
m
m
m
m

m
0
m
0
m
m
m
m
m
m

m
0
m
0
m
m
m
m
m
m

m
0
m
0
m
m
m
m
m
m

m
10
m
7
m
m
m
m
m
m

m
8
m
10
m
m
m
m
m
m

m
8
m
13
m
m
m
m
m
m

m
19
m
25
m
m
m
m
m
m

m
8
m
2
m
m
m
m
m
m

m
4
m
3
m
m
m
m
m
m

m
23
m
16
m
m
m
m
m
m

m
12
m
19
m
m
m
m
m
m

m
4
m
3
m
m
m
m
m
m

Foreign students

International
students

Partners

Note: The distribution excludes one field (Agriculture, forestry, fisheries and veterinary) which tends to represent a lower share of international enrolment in
tertiary education. Data for all fields are available at http://stats.oecd.org/, Education at a Glance Database.
1. Data on Information and communication technologies are included in other fields.
2. Columns 2 and 11 include all interdisciplinary programmes, columns 8 and 17 include public administration.
Source: OECD / UIS / Eurostat (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933803786

Education at a Glance 2018: OECD Indicators   © OECD 2018

229

chapter B Access to Education, Participation and Progression
Under embargo until 11/09/2018 at 11.00am CEST
Table B6.3. Mobility patterns of foreign and international students (2016)
Percentage of national students enrolled abroad and balance of cross-border mobility in total tertiary education

B6

Partners

OECD

Percentage of national
tertiary students
enrolled abroad

Number of international
or foreign students
per national student abroad

Number of international
or foreign students for every
hundred national students
home and abroad

Percentage of international
or foreign students coming
from neighbouring countries1

(1)

(2)

(3)

(4)

Australia
Austria
Belgium
Canada
Chile
Czech Republic2
Denmark
Estonia
Finland
France
Germany
Greece2
Hungary
Iceland
Ireland
Israel2, 3
Italy2
Japan
Korea2
Latvia
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic2
Slovenia
Spain
Sweden
Switzerland
Turkey2
United Kingdom
United States

1
5
3
3
1
4
2
8
4
4
4
5
4
13
7
4
4
1
3
7
74
1
2
3
7
2
4
17
4
2
4
5
1
2
0

26
4
4
4
0
3
7
1
2
3
2
1
2
0
1
1
1
5
1
1
0
0
5
10
1
2
2
0
1
1
2
4
2
13
14

21
19
13
13
0
13
12
7
8
11
8
3
9
6
8
3
5
4
2
8
23
0
12
24
4
3
6
5
3
3
7
20
1
22
5

4
59
40
4
37
55
38
50
16
16
15
66
27
8
10
2
21
63
65
18
58
m
31
6
19
72
5
56
36
29
20
55
44
11
5

OECD total
EU22 total

2
4

3
3

6
9

~
~

Argentina2, 4
Brazil2
China2
Colombia2
Costa Rica2
India2
Indonesia2
Lithuania
Russian Federation2
Saudi Arabia
South Africa2, 4

m
1
2
1
m
1
m
8
1
6
1

0
0
0
0
1
0
0
1
4
1
6

m
0
0
0
m
0
m
4
4
5
4

m
37
m
54
m
43
m
27
55
32
46

1. Neighbouring countries are considered to be those with land or maritime borders with the host country.
2. National tertiary students are calculated as total enrolment minus foreign students instead of total enrolment minus international students.
3. Excluding internationally mobile students enrolled in short-cycle tertiary programmes.
4. Year of reference 2015.
Source: OECD / UIS / Eurostat (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933803805

230 Education at a Glance 2018: OECD Indicators   © OECD 2018

Under embargo until 11/09/2018 at 11.00am CEST

Under embargo until 11/09/2018 at 11.00am CEST

HOW EQUITABLE ARE ENTRY AND GRADUATION
IN TERTIARY EDUCATION?
INDICATOR B7

• Individuals whose parents have not attained tertiary education are under-represented among new
entrants and first-time graduates from bachelor’s, long first degree or equivalent programmes.

• Men whose parents are not tertiary-educated are less likely than their female counterparts to enter
and graduate from bachelor’s, long first degree or equivalent programmes.

• The share of first- or second-generation immigrants is lower among new entrants to bachelor’s,
long first degree or equivalent programmes than in the population.

Figure B7.1. Share of 18-24 year-olds whose parents have not attained
tertiary education among new entrants to bachelor’s, long first degree
or equivalent programmes and in the population (2015)

Finland

Estonia

Austria

Israel

Latvia

Norway

Sweden

Lithuania

Switzerland

New entrants

France

United Kingdom

Australia

Slovenia

Netherlands

Greece

Portugal

Chile

Italy

Average

Population

%

100
90
80
70
60
50
40
30
20
10
0

How to read this figure
In Italy, 18-24 year-olds without tertiary-educated parents represent 82% of the total population of that age group, but only
71% of new entrants to bachelor’s, long first degree or equivalent programmes.
Note: Reference years may be different from 2015. Please see Annex 3 for details.
Countries are ranked in descending order of the share of individuals whose parents have not attained tertiary education among new entrants.
Source: OECD (2018), Table B7.1; ad-hoc survey on equity in tertiary education. See Source section at the end of this indicator for
more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933803995

Context
Growing evidence that a tertiary education leads to better labour-market and social outcomes (see
Chapter A) has raised a number of questions around access to higher education and brought equity
to the forefront of the policy debate on tertiary education. Across OECD and partner countries,
governments are increasingly committed to ensuring that access to tertiary education is not dependent
on socio-economic or demographic background.
This indicator measures the extent to which entry to and graduation from tertiary programmes
differ for individuals from potentially disadvantaged backgrounds. Two characteristics are used
to identify potentially disadvantaged groups: 1) parents’ highest level of educational attainment;
and 2) immigrant background. Parental education is linked to income and wealth, and evidence
shows that it is highly correlated with a variety of educational outcomes, such as attainment levels
(see Indicator A1), choice of programme orientation (see Indicator B3) and skills acquisition (OECD,
2013[1]). Immigrant background, although not always indicative of a disadvantage, is also correlated
with lower student performance (OECD, 2018[2]). Students with an immigrant background must
often overcome adversities associated with displacement, socio-economic disadvantage and language
barriers.

232 Education at a Glance 2018: OECD Indicators   © OECD 2018

Under embargo until 11/09/2018 at 11.00am CEST
Inequalities observed at the tertiary level may not only reflect barriers to entry to tertiary education,
but also differences in study and career choices. Moreover, inequalities can stem from earlier levels of
education. Many disadvantaged students leave the education system before even reaching the point at
which they could enter a tertiary programme (Box B7.1). In order to design effective policies to tackle
inequality, it is important to better understand when and how these observed inequalities start to
accumulate.

INDICATOR B7

Other findings

• Lower parental educational attainment tends to be associated with a delay in entering a bachelor’s,
long first degree or equivalent programme.

• Among countries with data, students without tertiary-educated parents represent an increasingly
smaller share at each step when comparing upper secondary entrants, upper secondary graduates
and tertiary entrants. The under-representation of students from potentially disadvantaged
backgrounds in tertiary education may reflect inequities at earlier levels of education, not
necessarily barriers to entry at the tertiary level.

• The patterns of inequality observed for first or second- generation immigrants in tertiary education
varies widely across countries, reflecting the heterogeneity of the immigrant populations in these
countries.

Education at a Glance 2018: OECD Indicators   © OECD 2018

233

chapter B Access to Education, Participation and Progression
Under embargo until 11/09/2018 at 11.00am CEST

Analysis

Analysis by parents’ educational attainment
In all countries with available data, individuals whose parents have not attained tertiary education are underrepresented among new entrants to bachelor’s, long first degree or equivalent programmes. On average across
countries with available data, people whose parents are not tertiary-educated represent 65% of the population
aged 18-24, but only 47% of 18-24 year-old new entrants. There is, however, significant variation across countries.
In Italy, the share of 18-24 year-olds without tertiary-educated parents is 82% in the population and 71% among
new entrants, while the share in Finland is 46% in the population and 29% among new entrants (Figure B7.1).
Individuals without tertiary-educated parents tend to be disadvantaged not only in entry to tertiary education,
but also in graduation from tertiary education. In fact, in all countries with available data, they are also underrepresented among first-time graduates from bachelor’s, long first degree or equivalent programmes (Table B7.2).
On average in countries with available data, 61% of 20-29 year-olds in the overall population have parents who are
not tertiary-educated, but this share goes down to 44% among first-time graduates aged 20-29.

Analysis by immigrant background
Immigrant background also appears to affect individuals’ entry to and graduation from tertiary education. In
all countries with available data, first- or second- generation immigrants are less likely to enter bachelor’s, long
first degree or equivalent programmes than their non-immigrant counterparts (Figure B7.2). First-generation
immigrants refer to individuals born abroad and whose both parents were also born abroad, and second-generation
immigrants refer to those born in the country, but whose both parents were born abroad. The analysis throughout
this indicator does not disaggregate between first- and second- generation immigrants. Both definitions exclude
international students.

Figure B7.2. Share of 18-24 year-olds who are first- or second- generation immigrants
among new entrants to bachelor’s, long first degree or equivalent programmes
and in the population (2015)

Finland

Slovenia

Estonia

Latvia

New entrants

Greece

Norway

Sweden

Israel

Netherlands

Population

%

40
35
30
25
20
15
10
5
0

Switzerland

B7

Representativeness of potentially disadvantaged groups among tertiary students
Inequality in tertiary education can be measured by comparing the share of young adults from potentially
disadvantaged groups among tertiary students and in the overall population. In a perfectly equal society, these two
shares should coincide, i.e. the share of individuals from a potentially disadvantaged group in the population should
match their share among tertiary entrants and graduates. For instance, a lower share among entrants than in the
overall population signals under-representation and lower access of this demographic group to higher education.

How to read this figure
In Switzerland, 18-24 year-olds who are first- or second-generation immigrants represent 27% of the total population of that age group, but
only 21% of new entrants to bachelor’s, long first degree or equivalent programmes.
Note: International students are excluded from the immigrant data. The definition of international students and the year of reference may differ
across countries. Please see Annex 3 for details.
Countries are ranked in descending order of the share of individuals who are first- or second-generation immigrants among new entrants.
Source: OECD (2018), Table B7.3; ad-hoc survey on equity in tertiary education. See Source section at the end of this indicator for more information
and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933804014

234 Education at a Glance 2018: OECD Indicators   © OECD 2018

How equitable are entry and graduation in tertiary education? – INDICATOR B7

chapter B

Under embargo until 11/09/2018 at 11.00am CEST
In Norway, first- or second- generation immigrants age 18-24 make up 15% of the population, compared to 10% of new
entrants to bachelor’s, long first degree or equivalent programmes, while in Greece they make up 19% of the population
and 9% of new entrants. These differences may reflect, in part, differences in the level of education of the immigrant
population of these countries (see Indicator A1). In a few countries, the share of immigrants in the population is quite
low (e.g. 6% in Finland and Slovenia), which should be taken into account when analysing these results.
A similar pattern of under-representation of first- or second- generation immigrants is observed among first-time
graduates (Table B7.4). However, the extent of this under-representation varies across countries. In Switzerland,
33% of the population aged 20-29 are immigrants, and this share goes down to 14% among first-time graduates,
while in Israel, 27% of the 20-29 year-olds are immigrants, compared to 25% of first-time graduates. It is important
to exercise caution when comparing the share of immigrants among graduates with their share in the population
because immigrants of this age group may arrive in the host country having already attained tertiary education, or
may not have enough time to attain it before the age of 29 (see Indicator A1).
The under-representation of first- or second- generation immigrants in bachelor’s, long first degree or equivalent
programmes may be due to several factors, including potential language barriers (in particular for individuals who
entered the country at a later age), or systematic differences in the socio-economic background of the immigrant
population (OECD, 2018[2]). It is, therefore, important to take into account the particularities of the immigrant
population of each country when drawing policy conclusions.

The compounded effect of gender
There is a general pattern showing that men whose parents have not attained tertiary education are even less likely
to enter and graduate from a bachelor’s, long first degree or equivalent programme than their female counterparts.
On average in countries with available data, 64% of 18-24 year-old men and women have parents who have not
attained tertiary education. However, only 43% of male new entrants have parents who have not attained this
level, compared to 49% of female new entrants (Figure B7.3). This means that individuals with lower-educated
parents are more under-represented among male new entrants than among female new entrants. This may be at
least partly explained by the higher opportunity cost of entering tertiary education for men. Although men benefit
from higher financial returns to tertiary education (see Indicator A5), they may decide to enter the labour market
earlier because, in the short-term, pursuing tertiary education implies higher foregone earnings for them than for
women (see Indicator A3). Men also have lower completion rates from upper secondary education (see Indicator A9
in [OECD, 2017[3]]), which can contribute to their lower entry rates to tertiary education.
The pattern observed for first-time graduates of bachelor’s, long first degree or equivalent programmes is similar. In
all countries with available data, the share of 20-29 year-olds without tertiary-educated parents is similar for men
and women, but it is higher among female first-time graduates than among male first-time graduates (Table B7.2).
On average, 62% of the female population aged 20-29 and 61% of their male counterparts do not have tertiaryeducated parents, but this share goes down to 47% among female first-time graduates and only 39% among male
first-time graduates.
While greater inequalities linked to parental education are observed with men, strong gender differences do not
exist in inequalities linked to immigrant background. In most countries with available data, the share of first- or
second- generation immigrants is similar for men and women, both in the overall population and among students.

Relationship between parents’ educational attainment and the age of entry to tertiary education
Previous figures have indicated that individuals whose parents have not attained tertiary education tend to be underrepresented among new entrants to bachelor’s and long first degree programmes. However, it is also interesting to
investigate whether parents’ educational attainment can affect decisions on when to enter such programmes.
Figure B7.4 shows that lower parental educational attainment is associated with delayed entrance to bachelor’s, long
first degree or equivalent programmes. On average across countries with available data, 82% of new entrants whose
parents are not tertiary-educated enter before age 25, compared to as high as 90% of new entrants with at least one
tertiary-educated parent. In fact, this pattern of delayed entrance to tertiary education is observed in all countries
with available data, with the exception of Italy, where all students enter before age 25.
Several factors may contribute to the delayed entrance of individuals whose parents have not attained tertiary
education, and this may differ across countries. Entrance may occur at a later age due to time spent in the labour
force, delays in completing upper secondary education or, in the case of first-generation immigrants, to late arrival
in the host country. This delay in entrance may pose equity concerns, particularly if it is not the result of a deliberate
choice by the student and if it later translates into disadvantages in the labour market.
Education at a Glance 2018: OECD Indicators   © OECD 2018

235

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Under embargo until 11/09/2018 at 11.00am CEST

Finland

Estonia

Austria

Israel

Norway

Sweden

Latvia

Lithuania

Switzerland

Male new entrants

Average

Female new entrants

Male population

Australia

Female population

France

Slovenia

Netherlands

Greece

Chile

%

100
90
80
70
60
50
40
30
20
10
0

Italy

B7

Figure B7.3. Share of 18-24 year-olds whose parents have not attained tertiary education
among new entrants to bachelor’s, long first degree or equivalent programmes
and in the population, by gender (2015)

How to read this figure
In Italy, 82% of the female population and 83% of the male population (age 18-24) have no tertiary-educated parent. This share goes down to
73% among female new entrants and 67% among male new entrants.
Note: Reference years may be different from 2015. Please see Annex 3 for details.
Countries are ranked in descending order of the proportion of individuals whose parents have not attained tertiary education among female new entrants.
Source: OECD (2018), Table B7.1; ad-hoc survey on equity in tertiary education. See Source section at the end of this indicator for more information
and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933804033

Box B7.1 Inequalities at the tertiary level may stem from earlier levels of education
The tables and figures in this indicator show a general pattern across OECD countries of under-representation
of potentially disadvantaged groups in tertiary education. However, when interpreting inequality in entry
to tertiary education, it is important to take into account the fact that inequalities tend to accumulate
throughout an individual’s educational path. Under-representation of disadvantaged students in tertiary
programmes could thus be due to obstacles in entering tertiary education itself or to obstacles that have kept
these individuals from progressing at earlier levels.
This box addresses this issue by combining data disaggregated by parental educational attainment for tertiary
and upper secondary education. This analysis only provides a limited view of the accumulation of inequalities
throughout education, which actually begin as soon as early childhood education, but it does help shed light
on the problem.
Figure B7.a shows the student composition by parents’ educational attainment at three different stages:
1) entry to upper secondary education; 2) graduation from upper secondary education within the theoretical
duration; and 3) entry to tertiary education. In most countries, the shares decrease at each step, highlighting
the fact that potentially disadvantaged students are less likely to advance through education.
This figure also helps determine the extent to which the inequality observed in tertiary education stems from
an earlier level. In Norway, for example, students whose parents have not attained tertiary education seem to
face particular obstacles to graduate from upper secondary education. However, those who do graduate from this
level are almost equally likely to move on to tertiary education as students with at least one tertiary-educated
parent. This finding suggests that there are no significant barriers to entry at the tertiary level in Norway, and
that the inequalities observed at this level are instead a reflection of fewer students without tertiary-educated
parents graduating upper secondary education than their peers with at least one tertiary-educated parent.

…

236 Education at a Glance 2018: OECD Indicators   © OECD 2018

chapter B

How equitable are entry and graduation in tertiary education? – INDICATOR B7

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The pattern is different in Israel, where most of the students whose parents have not attained tertiary education
are almost equally likely to graduate upper secondary education as those with at least one tertiary-educated
parent. However, their representativeness within entrants to tertiary education drops 15 percentage points,
from 54% of upper secondary graduates to 39% of tertiary entrants. This result suggests that there are particular
barriers to entry into tertiary education that may be disproportionately impacting disadvantaged students.
The barriers to entry at the tertiary level can also be a reflection of the student’s upper secondary degree.
In many countries there are upper secondary programmes that do not offer access to tertiary education.
So although students from a disadvantaged background may be an upper secondary graduate, he or she may
not have obtained the necessary credentials to enter tertiary education.
This is the case in the Netherlands, where about 40% of students enter upper secondary education in two‑year
or three-year vocational programmes that do not grant access to tertiary education. If only programmes
that provide access to tertiary education were considered, the gap between upper secondary graduates and
tertiary entrants in the Netherlands would drop from the 12 percentage points shown in Figure B7.a to only
4 percentage points. This indicates that the under-representation of disadvantaged groups in tertiary education
in the Netherlands is more likely a result of inequalities when choosing upper secondary programmes than
barriers in access to tertiary education.
The fact that inequalities observed in tertiary education may stem from earlier levels of education does not
fully explain the issues with access to tertiary education and does not diminish the problem itself. However,
understanding what factors contribute to the problem is essential to designing better policies.

Figure B7.a. Upper secondary entrants, upper secondary graduates and tertiary entrants
aged 18-24, by parents’ educational attainment
Upper secondary entrants 2010-12; upper secondary graduates by the theoretical duration
of the programme 2013/14; tertiary entrants 2015
A Upper secondary entrants
B Upper secondary graduates

At least one tertiary-educated parent
Parents have not attained
tertiary education

C Tertiary entrants

%

100
90
80
70
60
50
40
30
20
10
0

A

B

C

Netherlands1

A

B
France

C

A

B

C

Flemish Comm.
(Belgium)2

A

B

C

Israel1, 3

A

B

C

Sweden

A

B

C

Norway

A

B

C

Finland3

A

B

C

United States

How to read this figure
The stacked bars show the composition of upper secondary entrants, upper secondary graduates and tertiary entrants by parents’
educational attainment. In Finland, students whose parents have not attained tertiary education make up 48% of upper secondary
entrants, 44% of upper secondary graduates and 29% of tertiary entrants.
Note: Tertiary entrants refer to the 18-24 year-old age group, and educational programmes ISCED 5, ISCED 6 and ISCED 7 long first degree
programmes.
1. Tertiary entrants do not include short-cycle tertiary programmes.
2. Parents’ educational attainment refers to mother’s educational attainment.
3. For Israel, year of reference for entrants in upper secondary education is 2013 and for upper secondary graduates it is 2015. For Finland,
year of reference for tertiary entrants is 2016.
Countries and economies are ranked in descending order of the share of upper secondary entrants with no tertiary-educated parent.
Source: OECD (2018). Upper secondary data from the ad-hoc survey on upper secondary completion rate by equity dimension and tertiary
data from the pilot survey on equity in tertiary education. See Source section at the end of this indicator for more information and Annex 3
for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933804090

Education at a Glance 2018: OECD Indicators   © OECD 2018

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Figure B7.4. Share of new entrants to bachelor’s, long first degree or equivalent programmes
who are below the age of 25, by parents’ educational attainment (2015)

Finland

Estonia

Australia

Israel

Sweden

Switzerland

Norway

Austria

United Kingdom

Average

Portugal

Lithuania

Slovenia

Greece

Netherlands

100
90
80
70
60
50
40
30
20
10
0

Chile

New entrants whose parents have not attained tertiary education
New entrants with at least one tertiary-educated parent

%

Italy

B7

How to read this figure
In Finland, 87% of tertiary new entrants with at least one tertiary-educated parent entered before age 25. This share goes down to 64%
for new entrants whose parents have not attained tertiary education.
Note: Reference years may be different from 2015. Please see Annex 3 for details.
Countries are ranked in descending order of the share of new entrants below the age of 25 whose parents have not attained tertiary education.
Source: OECD (2018); ad-hoc survey on equity in tertiary education. See Source section at the end of this indicator for more information and
Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933804052

Figure B7.5. Share of 18-24 year-olds who entered short-cycle programmes versus bachelor’s,
long first degree or equivalent programmes, by parents’ educational attainment (2015)
%

100
90
80
70
60
50
40
30
20
10
0

Bachelor’s, long first degree or equivalent
Short-cycle tertiary

49
65

A

B

France

A Parents have not attained tertiary education
B At least one tertiary-educated parent

58
78

A

B

Chile

73

A

85

B

Slovenia

90

95

A

B

Sweden

93

96

A

B

Norway

93

95

A

B

United
Kingdom

How to read this figure
The stacked bars show the distribution of tertiary entrants between short-cycle tertiary programmes and bachelor’s, long first degree or
equivalent programmes, by parental educational attainment. In Slovenia, among new entrants whose parents have not attained tertiary
education, 27% enter a short-cycle tertiary programme, and 73% enter a bachelor’s, long first degree or equivalent programme. Among new
entrants with at least one tertiary-educated parent, 15% enter a short-cycle tertiary programme, and 85% enter a bachelor’s, long first degree
or equivalent programme.
Note: Reference years may be different from 2015. Please see Annex 3 for details.
Countries are ranked in descending order of the share of new entrants whose parents have not attained tertiary education and who entered a short-cycle tertiary
programme.
Source: OECD (2018); ad-hoc survey on equity in tertiary education. See Source section at the end of this indicator for more information and
Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933804071

238 Education at a Glance 2018: OECD Indicators   © OECD 2018

How equitable are entry and graduation in tertiary education? – INDICATOR B7

chapter B

Under embargo until 11/09/2018 at 11.00am CEST
Relationship between parents’ educational attainment and the choice of tertiary programme
Parents’ educational attainment may affect not only the decision on whether to pursue tertiary education, but also
the choice of tertiary programme to enter.
Figure B7.5 shows that in all countries with available data, new entrants to tertiary education whose parents have
not attained this level are more likely to enter a short-cycle tertiary programme than a bachelor’s or long first degree
programme, compared to new entrants with at least one tertiary-educated parent. For instance, in Slovenia, among
new entrants whose parents have not attained tertiary education, 27% enter a short-cycle tertiary programme, and
73% enter a bachelor’s, long first degree or equivalent programme. Among new entrants with at least one tertiaryeducated parent, only 15% enter a short-cycle tertiary programme, and 85% enter a bachelor’s, long first degree or
equivalent programme.
Graduates from bachelor’s, long first degree or equivalent programmes tend to have higher earnings and higher
employment rates than graduates from short-cycle tertiary programmes (see Indicators A3 and A4). Therefore, if
disadvantaged groups are under-represented in bachelor’s, long first degree or equivalent programmes, this may
accentuate inequalities in the labour market. The potential for short-cycle tertiary programmes to contribute to
improving educational equality will relate to their ability to provide students with the relevant skill sets to succeed
in the labour market or in their further education.

Definitions
New entrants to bachelor’s, long first degree or equivalent programmes are students who enrol in this level of
education for the first time. For this indicator, we only consider new entrants age 18-24.
First-time graduates from bachelor’s, long first degree or equivalent programmes are students who graduate
from this level of education for the first time. For this indicator, we only consider first-time graduates age 20-29.
Parents have not attained tertiary education means that neither parent has attained ISCED 2011 levels 5 to 8.
First-generation immigrants are foreign-born of two parents who are also foreign-born. This definition excludes
international students.
Second-generation immigrants are native-born of two foreign-born parents.

Methodology
For each age group, gender and critical group (individuals without tertiary-educated parents and with an immigrant
background), the share of new entrants/first-time graduates is calculated as the number of new entrants/firsttime graduates who belong to the critical group divided by the total number of new entrants/first-time graduates
(Tables B7.1, B7.2, B7.3 and B7.4, and Figures B7.1, B7.2 and B7.3).
The share of new entrants below age 25 is computed as the number of new entrants below age 25 divided by the
total number of entrants of all ages (Figure B7.4).
The share of 18-24 year-olds who entered short-cycle tertiary programmes is computed as the number of new
entrants to short-cycle tertiary programme divided by the total number of entrants to all tertiary education
programmes (both short-cycle tertiary programmes and bachelor’s, long first degree or equivalent programmes).
Similarly, the share of 18-24 year-olds who entered bachelor’s, long first degree or equivalent programmes is
computed as the number of new entrants to bachelor’s, long first degree or equivalent programme divided by the
total number of entrants to all tertiary education programmes (Figure B7.5).
Lithuania was not an OECD member at the time of preparation of this publication. Accordingly, Lithuania does not
appear in the list of OECD members and is not included in the zone aggregates.

Source
Data refer to the academic year 2014/15 and were collected through an ad-hoc survey undertaken in 2017 and 2018.

Note regarding data from Israel
The statistical data for Israel are supplied by and are under the responsibility of the relevant Israeli authorities. The use
of such data by the OECD is without prejudice to the status of the Golan Heights, East Jerusalem and Israeli settlements
in the West Bank under the terms of international law.

Education at a Glance 2018: OECD Indicators   © OECD 2018

239

B7

chapter B Access to Education, Participation and Progression
Under embargo until 11/09/2018 at 11.00am CEST
References

B7

OECD (2018), The Resilience of Students with an Immigrant Background: Factors that Shape Well-being, OECD Publishing, [2]
Paris, http://dx.doi.org/10.1787/9789264292093-en.
OECD (2017), Education at a Glance 2017: OECD Indicators, OECD Publishing, Paris, http://dx.doi.org/10.1787/eag-2017-en. [3]
OECD (2013), OECD Skills Outlook 2013: First Results from the Survey of Adult Skills, OECD Publishing, Paris, http://dx.doi. [1]
org/10.1787/9789264204256-en.

Indicator B7 Tables
1 2 https://doi.org/10.1787/888933803900

Table B7.1 Share of 18-24 year-olds whose parents have not attained tertiary education among new entrants to
bachelor’s, long first degree or equivalent programmes and in the population, by gender (2015)
Table B7.2 Share of 20-29 year-olds whose parents have not attained tertiary education among first-time graduates from
bachelor’s, long first degree or equivalent programmes and in the population, by gender (2015)
Table B7.3 Share of 18-24 year-olds who are first- or second- generation immigrants among new entrants to bachelor’s,
long first degree or equivalent programmes and in the population, by gender (2015)
Table B7.4 Share of 20-29 year-olds who are first- or second- generation immigrants among first-time graduates from
bachelor’s, long first degree or equivalent programmes and in the population, by gender (2015)
Cut-off date for the data: 18 July 2018. Any updates on data can be found on line at http://dx.doi.org/10.1787/eag-data-en. More breakdowns can
also be found at http://stats.oecd.org/, Education at a Glance Database.

240 Education at a Glance 2018: OECD Indicators   © OECD 2018

How equitable are entry and graduation in tertiary education? – INDICATOR B7

chapter B

Under embargo until 11/09/2018 at 11.00am CEST
Table B7.1. Share of 18-24 year-olds whose parents have not attained tertiary education among
new entrants to bachelor’s, long first degree or equivalent programmes and in the population,
by gender (2015)
Women

Countries

New entrants

Men
Population

New entrants

Total
Population

New entrants

Population

(1)

(2)

(3)

(4)

(5)

(6)

Australia
Austria
Chile
Estonia
Finland
France
Greece
Israel
Italy
Latvia
Lithuania
Netherlands
Norway
Portugal
Slovenia
Sweden
Switzerland
United Kingdom

51
39
71
32
30
51
61
42
73
44
47
58
43
m
56
43
47
m

64
61
79
47
46
64
74
56
82
65
75
72
53
m
65
61
58
m

46
35
64
30
27
41
58
32
67
34
39
54
35
m
48
36
41
m

66
61
79
45
46
63
76
56
83
64
76
71
53
m
65
61
58
m

49
37
67
31
29
47
60
39
71
39
44
56
39
61
53
40
45
47

65
61
79
46
46
63
75
56
82
65
76
72
53
78
65
61
58
64

Average

49

64

43

64

47

65

Note: Tables B7.1 and B7.2 refer to different cohorts and may have different sources so the data presented should not be compared across tables. Reference years may
be different from 2015. Please see Annex 3 for more details.
Source: OECD (2018), ad-hoc survey on equity in tertiary education. See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/
eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933803919

Table B7.2. Share of 20-29 year-olds whose parents have not attained tertiary education among
first‑time graduates from bachelor’s, long first degree or equivalent programmes and in the population,
by gender (2015)

Countries

Women

Men

Total

First-time graduates

Population

First-time graduates

Population

First-time graduates

(1)

(2)

(3)

(4)

(5)

Population
(6)

Australia
Austria
Canada1
Finland
France2
Israel
Italy
Netherlands
Norway
Slovenia
Sweden
Switzerland
United Kingdom
United States

52
39
29
32
69
39
72
57
44
55
42
42
m
35

65
66
42
50
71
55
82
73
56
68
65
62
m
51

50
37
25
29
31
31
65
54
35
45
34
39
m
29

66
62
40
50
65
55
83
73
56
68
65
59
m
47

52
38
28
31
50
36
69
55
41
51
39
41
46
32

65
64
41
50
68
55
83
73
56
68
65
60
61
49

Average

47

62

39

61

44

61

Note: Tables B7.1 and B7.2 refer to different cohorts and may have different sources so the data presented should not be compared across tables. Reference years may
be different from 2015. Please see Annex 3 for more details.
1. Values for first-time graduates are based on a small sample and should be interpreted with caution.
2. Age group for first-time graduates refers to 20-24 year-olds instead of 20-29 year-olds.
Source: OECD (2018), ad-hoc survey on equity in tertiary education. See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/
eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933803938

Education at a Glance 2018: OECD Indicators   © OECD 2018

241

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chapter B Access to Education, Participation and Progression
Under embargo until 11/09/2018 at 11.00am CEST
Table B7.3. Share of 18-24 year-olds who are first- or second- generation immigrants among
new entrants to bachelor’s, long first degree or equivalent programmes and in the population,
by gender (2015)

B7
Countries

Women

Estonia
Finland
Greece
Israel
Latvia
Netherlands
Norway
Slovenia
Sweden
Switzerland

Men

Total

New entrants

Population

New entrants

Population

New entrants

Population

(1)

(2)

(3)

(4)

(5)

(6)

4
3
11
20
6
14
9
5
18
20

9
6
18
22
24
18
15
6
22
29

6
2
8
20
11
12
10
4
19
22

9
6
20
22
24
18
15
6
23
26

5
3
9
20
9
13
10
5
18
21

9
6
19
22
24
18
15
6
22
27

Notes: International students are excluded from the immigrant data. The definitions of international students and the year of reference may differ across countries.
Tables B7.3 and B7.4 refer to different cohorts and may have different sources so the data presented should not be compared across tables. Please see Annex 3 for
more details.
Source: OECD (2018), ad-hoc survey on equity in tertiary education. See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/
eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933803957

Table B7.4. Share of 20-29 year-olds who are first- or second- generation immigrants among first‑time

graduates from bachelor’s, long first degree or equivalent programmes and in the population,
by gender (2015)

Countries

Women

Finland
Germany
Israel
Netherlands
Norway
Slovenia
Sweden
Switzerland
United States

Men

Total

First-time graduates

Population

First-time graduates

Population

First-time graduates

Population

(1)

(2)

(3)

(4)

(5)

(6)

2
7
25
11
6
5
14
14
14

8
19
28
21
21
8
24
33
21

2
5
25
9
7
5
13
13
15

8
18
27
20
20
8
24
33
24

2
7
25
10
7
5
14
14
14

8
18
27
21
21
8
24
33
23

Notes: International students are excluded from the immigrant data. The definitions of international students and the year of reference may differ across countries.
Tables B7.3 and B7.4 refer to different cohorts and may have different sources so the data presented should not be compared across tables. Please see Annex 3 for
more details.
Source: OECD (2018), ad-hoc survey on equity in tertiary education. See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/
eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933803976

242 Education at a Glance 2018: OECD Indicators   © OECD 2018

Under embargo until 11/09/2018 at 11.00am CEST

Chapter

C

Financial Resources
Invested In Education

Indicator C1 How much is spent per student on educational institutions?
1 2 https://doi.org/10.1787/888933804109

Indicator C2 What proportion of national wealth is spent on educational institutions?
1 2 https://doi.org/10.1787/888933804242

Indicator C3 How much public and private investment on educational institutions is there?
1 2 https://doi.org/10.1787/888933804375

Indicator C4 What is the total public spending on education?
1 2 https://doi.org/10.1787/888933804508

Indicator C5 How much do tertiary students pay and what public support do they receive?
1 2 https://doi.org/10.1787/888933804641

Indicator C6 On what resources and services is education funding spent?
1 2 https://doi.org/10.1787/888933804774

Indicator C7 Which factors influence teachers’ salary cost?
1 2 https://doi.org/10.1787/888933804888

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243

Under embargo until 11/09/2018 at 11.00am CEST

The framework for educational finance indicators

CHAPTER C

International indicators on education finance are defined in terms of the educational goods and
services purchased in relation to the educational programmes. In practice, educational institutions
are most commonly used as defining units rather than educational goods and services, reflecting the
traditional interest in how much schools, colleges and universities cost. But while an institutional
dimension is important, spending, particularly from public sources, outside of educational institutions
helps support the learning and access to education within institutions. Differentiating the spending
devoted to educational and non-educational goods and services offered by institutions also provides
for an analysis of the expenditure devoted to core educational purposes. Finally the source of funds
dedicated to education spending assesses who the major contributors are and the impact this may
have on the access and provision of education.
It is therefore important to consider a framework for educational expenditure that is built around
three dimensions:

• the location of service providers (within or outside of institutions)

• the goods and services provided or purchased (core and peripheral goods)
• the source of funds that finance the provision or purchase of these goods and services (from public,
private and international sources).

Classification of educational expenditure
Educational expenditure in this chapter is classified through three dimensions:

• The first dimension – represented by the horizontal axis in the diagram below – relates to the
location where spending occurs. Spending on educational institutions includes spending on teaching
institutions such as schools and universities, and non-teaching institutions such as education
ministries and other agencies directly involved in providing and supporting education. Spending
on education outside these institutions covers expenditure on educational good and services
purchased outside institutions, such as books, computers and fees for private tutoring. It also deals
with student living costs and costs of student transport not provided by educational institutions.

• The second dimension – represented by the vertical axis in the diagram below – classifies the goods
and services that are purchased. Educational core goods and services include all expenditure directly
related to instruction and education. It covers all expenditure on teachers, maintenance of school
buildings, teaching materials, books, tuition outside schools and administration of schools. However,
not all expenditure on educational institutions can be classified as direct educational or instructional
expenditure. Educational institutions in many OECD countries offer various ancillary services – such
as meals, transport, housing, etc. – in addition to teaching services to support students and their
families. At the tertiary level, spending on research and development can be significant. Additionally,
not all spending on educational goods and services occurs within educational institutions. For example,
families may purchase textbooks and materials themselves or seek private tutoring for their children.
In this sense, “non-instruction” expenditure covers all expenditure broadly related to student living
costs or services provided by institutions for the general public.

• The third dimension – represented by the colours in the diagram below – distinguishes among the
sources from which funding originates. These include the public sector and international agencies
(indicated by light blue), and households and other private entities (indicated by medium-blue).
Where private expenditure on education is subsidised by public funds, this is indicated by cells in
the grey colour. The uncoloured cells indicate the parts of the framework that are excluded from the
coverage of the finance indicators in Education at a Glance.

Educational finance indicators
This chapter provides a comprehensive and comparative analysis on education expenditure across
OECD countries, focusing on seven aspects of educational spending:

• Financial resources invested on educational institutions, relative to the number of students
(Indicator C1), and relative to national wealth (Indicator C2).

244 Education at a Glance 2018: OECD Indicators   © OECD 2018

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• The source of funds devoted on educational institutions (Indicator C3).
• Total public resources invested on education, both inside and outside of educational institutions,
relative to total government spending (Indicator C4).

• The students’ cost and the financial support of tertiary studies (Indicator C5).
• The distribution of educational expenditure across resource categories (Indicator C6).

CHAPTER C

• The contribution of various factors to the salary cost of teachers per student in public institutions
(Indicator C7).
Public and international funds
Private funds
Publicly subsidised private funds

Location of service providers
Spending on educational
institutions
(e.g. schools, universities,
educational administration
and student welfare services)

Spending on education outside
educational institutions
(e.g. private purchases of educational
goods and services, including
private tutoring)

Public and international funds
e.g. public spending on instructional
services in educational institutions

Publicly subsidised private funds
e.g. subsidised private spending on books,
materials or fees for private tutoring

Publicly subsidised private funds
Spending on core educational
e.g. subsidised private spending on
goods and services
instructional services in educational
institutions

Private funds
e.g. private spending on books and other
school materials or private tutoring

Types of goods and services

Private funds
e.g. private spending on tuition fees
Public and international funds
e.g. public spending on university research

Spending on
research and Private funds
development e.g. funds from private industry for
research and development in educational
institutions
Educational
peripheral
goods and
services

Spending
on
educational
services
other than
instruction

Public and international funds
e.g. public spending on ancillary services
such as meals, transport to schools, or
housing on the campus

Publicly subsidised private funds
e.g. subsidised private spending on
student living costs or reduced prices
for transport

Publicly subsidised private funds
e.g. public subsidies for lodging, meals,
health services, or other welfare services
furnished to students by the educational
institutions
Private funds
Private funds
e.g. private spending on fees for ancillary e.g. private spending on student living
costs or transport
services

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Under embargo until 11/09/2018 at 11.00am CEST

HOW MUCH IS SPENT PER STUDENT ON EDUCATIONAL
INSTITUTIONS?
• On average, OECD countries spend USD 10 500 a year on educational institutions to educate

INDICATOR C1

each student from primary to tertiary education. This represents about USD 8 600 per student at
primary level, USD 10 000 at secondary level and USD 15 700 at tertiary level.

• In non-tertiary education (primary, secondary and post-secondary non-tertiary levels), 94% of
institutions’ expenditure per student is devoted to core educational services (such as teaching
costs), and the remaining is devoted to ancillary services (such as student welfare). At the tertiary
level, a much lower share of institutional expenditure goes to core services (68%), while roughly
30% of total educational expenditure per student is on research and development.

• Across OECD countries, students enrolled at primary or secondary school between the age of 6 and
15 add up to a total cumulative expenditure of around USD 91 000 per student.

Figure C1.1. Total expenditure on educational institutions per student,
by type of service (2015)
In equivalent USD converted using PPPs, based on full-time equivalents,
from primary to tertiary education
R&D
Ancillary services
Core services

In equivalent USD
converted using PPPs

25 000
20 000
15 000
10 000

Turkey

Hungary

Lithuania

Latvia

Poland

Estonia

Czech Republic

Slovak Republic

Spain

Slovenia

Italy

Portugal

OECD average

France

EU22 average

Korea

Iceland

Finland

Germany

Netherlands

Belgium

Australia

Sweden

Austria

United Kingdom

Norway

United States

0

Luxembourg

5 000

Countries are ranked in descending order of total expenditure per student on educational institutions.
Source: OECD / UIS / Eurostat (2018), Table C1.2. See Source section for more information and Annex 3 for notes (http://dx.doi.
org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933804185

Context
The willingness of policy makers to expand access to educational opportunities and to provide highquality education can translate into higher costs per student and must be balanced against other
demands on public expenditure and the overall tax burden. As a result, the question of whether the
resources devoted to education yield adequate returns features prominently in the public debate.
Although it is difficult to assess the optimal volume of resources needed to prepare each student for
life and work in modern societies, international comparisons of spending on educational institutions
per student can provide useful reference points (see Definitions and Methodology sections).
This indicator provides an assessment of the investment in each student. Expenditure per student
on educational institutions is largely influenced by teachers’ salaries (see Indicators C7 and D3),
pension systems, instructional and teaching hours (see Indicator C7), the cost of teaching materials
and facilities (see Indicator C6), the programme provided (e.g. general or vocational) and the number
of students enrolled in the education system (see Indicator B1). Policies to attract new teachers,

246 Education at a Glance 2018: OECD Indicators   © OECD 2018

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reduce average class size or change staffing patterns (see Indicator D2) have also affected per-student
expenditure. Ancillary services and research and development (R&D) activities can also influence the
level of expenditure per student.
At primary and secondary levels, educational expenditure is dominated by spending on instructional
services. At the tertiary level, other services, particularly those related to ancillary services or R&D
activities, can account for a significant proportion of educational spending. Indicator C6 provides
further information on how spending is distributed by the different types of services provided.

INDICATOR C1

Other findings

• In almost all countries, expenditure on educational institutions per student increases at each
educational level, with the exception of post-secondary non-tertiary education, where the average
expenditure per student is around the level in primary education or lower than in other levels.

• On average, private sources in OECD countries spend more than USD 4 600 per student in tertiary
levels of education. This share represents around 40% of the investment per student made by
governments at the same level (USD 11 100).

• From 2010 to 2015, expenditure on non-tertiary educational institutions increased by 4% on
average across OECD countries, while the number of students decreased by 1%, resulting in an
increase of 5% in expenditure per student over the same period.

• The orientation of secondary school programmes influences expenditure on educational
institutions per student in most countries. On average, across the 27 OECD countries with separate
data on expenditure per student for general and vocational programmes at upper secondary levels,
the cost per student in a vocational programme was almost USD 2 000 more than in a general
programme in 2015.

• Excluding activities peripheral to instruction (R&D and ancillary services, such as student welfare
services), OECD countries annually spend an average of USD 9 800 per student from primary to
tertiary education.

• Annual expenditure per student on educational institutions as a share of GDP per capita amounts
to 22% at primary level and 25% at secondary level on average across OECD countries. The figure is
much higher at tertiary level, where countries spend on average 38% of GDP per capita on funding
short-cycle, bachelor’s, master’s and doctoral degrees.

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Analysis

C1

Expenditure per student on educational institutions at different levels of education
Annual expenditure per student on educational institutions between primary and tertiary education provides an
assessment of the investment made in each student. In 2015, annual spending per student from primary to tertiary
education ranged from around USD 3 000 or slightly more in Colombia and Mexico to more than USD 15 000 in
Austria, Norway and the United States and nearly USD 22 000 in Luxembourg (Table C1.1 and Figure C1.1). Across
the OECD, countries spend on average USD 10 500.
Methods of resource allocation across the different levels of education vary widely and are largely a reflection of the
mode of educational provision. Education still essentially takes place in settings with generally similar organisation,
curriculum, teaching style and management. These shared features have tended to result in similar patterns of unit
expenditure from primary through post-secondary non-tertiary levels. In recent decades, however, greater use of
private funds for tertiary education has modified the allocation pattern of expenditure at this level compared to
lower ones (see Indicator C3, and Table C1.5, available on line). In 2015, OECD countries on average spent around
USD 8 600 per student at the primary level, USD 10 000 at the secondary level and USD 15 700 at the tertiary level,
although at this level, the average is affected by high expenditure in a few OECD countries, most notably Australia,
Luxembourg, Norway, Sweden, the United Kingdom and the United States (Table C1.1 and Figure C1.1). These
differences in annual expenditure on educational institutions per student at each level of education can also lead to
large differences in the cumulative expenditure per student over the duration of studies (Table C1.6, available on
line). Significant differences are also observed at the subnational level (Box C1.1).
Comparisons of the distribution of expenditure at different levels of education reflect the relative emphasis
of governments at these levels as well as the relative costs of education provision. Expenditure per student on
educational institutions rises with the level of education in almost all countries, but the range varies markedly across
countries (Table C1.1). OECD countries spend on average 15% more per secondary student than they do per primary
student. This percentage is around 60% in the Czech Republic and France, and slightly over 50% in the Netherlands,
but countries invest more per primary student than they do per secondary student in Chile, Colombia, Iceland,
Lithuania, Luxembourg, the Slovak Republic, Slovenia, Turkey and the United Kingdom. Similarly, educational
institutions in OECD countries spend an average of 30% more on each tertiary student (excluding R&D) than
on each primary student mostly because education policies vary more at the tertiary level (see Indicator C5). For
example, Mexico and the United States spend at least 120% more on a tertiary student (excluding R&D) than on a
primary student (Table C1.1).
Box C1.1. Subnational variation in annual expenditure per student on educational institutions
Annual expenditure per student is not homogeneous within countries. Among the four countries providing
data, large differences are observed across regions within a country in 2015. The Russian Federation is the
country with the highest subnational range in terms of annual expenditure per student on educational
institutions at primary and secondary levels combined with a ratio of 9 between the region with the highest
and the region with the lowest value, ranging from around USD 2 700 to USD 25 000. Canada is the country
with the second-largest subnational range, with a ratio of almost 3 between the top and bottom regions in
terms of expenditure per student at primary and secondary levels. Regional differences are the smallest in
Belgium and Germany (countries with few subnational regions) (OECD/NCES, 2018[1]).
An examination of homogeneity in spending at primary and secondary levels within countries show that 57 out
of 85 regions in the Russian Federation devoted a lower annual expenditure per student than the national
average, indicating that the peak values benefit a select minority of regions. This is contrast to Canada where
less than 50% of the 13 provinces and territories provide a lower level of expenditure than the national average.
In Germany, 6 out of the 9 Länder that spend less than the national average are mainly located in the western part
of the country. This could be explained by the sharp demographic downturn in the eastern Länder (OECD/ NCES,
2018[1]).
To make these comparisons across countries, expenditure figures were converted into common currency (USD)
using national purchasing power parities (PPPs). However, differences in the cost of living within countries
were not taken into account.

248 Education at a Glance 2018: OECD Indicators   © OECD 2018

How much is spent per student on educational institutions? – INDICATOR C1

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Expenditure per student on core education services, ancillary services and R&D
On average across OECD countries, expenditure on core education services (such as teaching costs) represents 86%
of total expenditure per student from primary to tertiary educational institutions and it exceeds 90% in Iceland,
Latvia, Luxembourg and Poland. In 9 of the 25 OECD and partner countries for which data are available, annual
expenditure on R&D and ancillary services per student from primary to tertiary education accounts for around
15%-30% of the total annual expenditure per student and can influence the ranking of countries for all services
combined.
However, this overall picture masks large variations among levels of education (Table C1.2). At non-tertiary levels
(primary, secondary and post-secondary non-tertiary), expenditure is dominated by spending on core education
services. On average, OECD countries for which data are available spend 94% of the total per-student expenditure
(USD 9 400) on core educational services. However, in Finland, France, Hungary, the Slovak Republic, Sweden and
the United Kingdom, ancillary services account for 10% or slightly more of the expenditure per student (Table C1.2).
Greater differences are observed in the proportion of total expenditure on educational institutions per student
devoted to core services at the tertiary level, partly because R&D expenditure can account for a significant
proportion of educational spending (Table C1.2). Across OECD countries, 68% of total expenditure on educational
institutions at tertiary level goes to core services, while almost 30% of total educational expenditure is on research
and development. The OECD countries in which most R&D is performed in tertiary education institutions tend to
report higher expenditure per student than those in which a large proportion of R&D is performed in other public
institutions or in industry. Excluding R&D activities, average expenditure per student in all countries accounts
for over USD 11 200, ranging from around USD 2 600 in Greece to more than USD 40 000 in Luxembourg. On
average across OECD countries, expenditure on R&D and ancillary services at the tertiary level represents 32%
of all tertiary expenditure on educational institutions per student. In 7 of the OECD and partner countries for
which data are available, expenditure on R&D and ancillary services in tertiary institutions is at least 40% of total
expenditure on educational institutions per student, with the Slovak Republic (50%) and Sweden (54%) the countries
with the highest shares. Ancillary services are even less important in tertiary education than at lower levels. On
average, only 4% of expenditure on tertiary institutions targets ancillary services, and the amount is negligible in
the Czech Republic, Estonia, Finland, Iceland, Israel, Korea and Sweden. The United Kingdom and the United States
stand out for spending over USD 2 000 per student on ancillary services in their tertiary institutions.
Cumulative expenditure over the expected duration of studies
Policy makers are interested in the relationship between the resources devoted to education and the outcomes
of education systems (Box B1.1 in Education at a Glance 2017 [OECD, 2017[2]]). In order to compare the cost of
education across countries, it is important to consider not only the yearly expenditure per student, but also the
cumulative expenditure for students over the total period they are expected to spend at that educational level. High
expenditure per student, for example, might be offset by short programmes or weaker access to education at certain
levels. On the other hand, a seemingly inexpensive education system per student can prove to be costly overall, if
enrolment is high and students spend more time in school.
Primary and secondary education are usually compulsory across the OECD, and the theoretical cumulative
expenditure per student aged between 6 and 15 at these levels shows how much it costs to teach a student on
average based on current compulsory education (Figure C1.2 and Table C1.6, available on line). On average across
OECD countries, students aged between 6 and 15 adds up to a total cumulative expenditure of around USD 92 000
per student. Theoretical cumulative expenditure on educational institutions per student varies considerably among
countries, Austria, Luxembourg, Norway and the United States spend over USD 120 000 per student across those
two levels, while the figure is below USD 40 000 in Mexico and Turkey.
Expenditure per student on educational institutions relative to per capita GDP
Expenditure on educational institutions per student relative to GDP per capita is a spending measure that takes
into account the relative worth of OECD countries. Since access to education in most OECD countries is universal
(and usually compulsory) at the lower levels of schooling, the quotient between the amount spent per student and
the per capita GDP can be indicative of whether the resources spent per student are correlated to the country’s
ability to pay. At higher levels of education, where student enrolments vary sharply among countries, the link is
less clear. At tertiary level, for example, OECD countries may rank relatively high on this measure, even when a large
proportion of their wealth is spent on educating a relatively small number of students.
Education at a Glance 2018: OECD Indicators   © OECD 2018

249

C1

chapter C Financial Resources Invested In Education
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Figure C1.2. Cumulative expenditure per student on educational institutions
between the age of 6 and 15 (2015)
Annual expenditure on educational institutions per student multiplied by the theoretical duration of studies
in equivalent USD converted using PPPs
Upper secondary
Lower secondary
Primary

In equivalent USD
converted using PPPs

250 000
200 000
150 000
100 000

Greece
Hungary
Chile3
Brazil
Turkey
Mexico

Latvia2
Slovak Republic
Estonia2

Israel
Spain1
France
Czech Republic
Poland1, 2

New Zealand
Slovenia
Italy
Portugal1

Australia
Netherlands
Germany
Japan1
Canada1
EU22 average
OECD average
Ireland

0

Korea
United Kingdom
Sweden2
Finland1, 2

50 000
Luxembourg
Austria
Norway
United States
Iceland
Belgium1

C1

Note: Cumulative expenditure per student on educational institutions is calculated using expected years in education.
1.Some levels of education are included with others. Refer to “x” code in Table C1.1 for details.
2. Includes one year of pre-primary education as part of core education.
3. Year of reference 2016.
Countries are ranked in descending order of the total expenditure on educational institutions per student over the theoretical duration of primary and secondary
studies between the age of 6 and 15.
Source: OECD / UIS / Eurostat (2018), Table C1.6. See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag2018-36-en).
1 2 https://doi.org/10.1787/888933804204

In OECD countries, overall expenditure per student on educational institutions from primary to tertiary levels
averages 26% of per capita GDP, broken down into 22% at primary level, 25% at lower secondary level, 26% at upper
secondary level, 22% at post-secondary non-tertiary level and 39% at tertiary level (Table C1.4, available on line and
Figure C1.3). Countries with low levels of expenditure per student may nonetheless invest relatively higher amounts
as a share of per capita GDP. For example, although Latvia’s expenditure per student at all educational levels and per
capita GDP are both below the OECD average, it spends per student an above-average share of its per capita GDP
on each educational level.
The relationship between per capita GDP and expenditure per student on educational institutions is difficult to
interpret. However, there is a clear positive relationship between the two at non-tertiary educational levels. In other
words, less wealthy countries tend to spend less per student than richer countries. Although the relationship is
generally positive at these levels, there are variations, even among countries with similar levels of per capita GDP,
and especially in those in which per capita GDP exceeds USD 30 000. Austria and the Netherlands, for example,
have similar levels of per capita GDP (around USD 50 000) (see Table X2.1 in Annex 2) but they allocate very
different shares of their wealth to primary and secondary education. Austria spends 23% of per capita GDP on
primary institutions (above the OECD average of 22%) and 31% on secondary institutions (above the OECD average
of 25%), while the Netherlands spends less with 17% at primary level and 26% at secondary level (Table C1.4,
available on line and Figure C1.3).
At tertiary level, there is more cross-country variation in spending and in the relationship between countries’ relative
wealth and their level of tertiary expenditure. Spending by tertiary institutions in Brazil, the Slovak Republic,
Sweden, the United Kingdom and the United States represents more than 50% of per capita GDP for each student
(Table C1.4, available on line and Figure C1.3). The high share for Sweden, for example, is clearly explained by its
extremely high expenditure on R&D, which accounts for over half of total expenditure per student at this level
(Table C1.2).

250 Education at a Glance 2018: OECD Indicators   © OECD 2018

How much is spent per student on educational institutions? – INDICATOR C1

chapter C

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Figure C1.3. Expenditure on educational institutions per student
relative to GDP per capita (2015)
Annual expenditure on educational institutions per student versus GDP per capita in equivalent USD
converted using PPPs, by level of education
Expenditure per student
(equivalent USD converted
using PPPs)

C1

Primary, secondary and post-secondary non-tertiary
Tertiary

50 000
45 000

y = 0.4101x - 648.6
R² = 0.7012

40 000
35 000
30 000
25 000

y = 0.1928x + 1432.7
R² = 0.7865

20 000
15 000
10 000
5 000
0
10 000

20 000

30 000

40 000

50 000

60 000

70 000

80 000

90 000

100 000

110 000

GDP per capita (equivalent USD converted using PPPs)

Source: OECD / UIS / Eurostat (2018), Table C1.1 and OECD.Stat. See Source section for more information and Annex 3 for notes (http://dx.doi.
org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933804223

Changes in expenditure per student on educational institutions between 2010 and 2015
Changes in expenditure on educational institutions largely reflect changes in the size of the school-age population
and in teachers’ salaries, both of which tend to increase over time. Teachers’ salaries, the main component of costs,
have increased in the majority of countries over the past decade (see Indicator D3). The size of the school-age
population influences both enrolment levels and the amount of resources and organisational effort a country must
invest in its education system. The larger this population, the greater the potential demand for education services.
Changes in expenditure per student over the years may also vary between levels of education within countries, as
both enrolment and expenditure may follow different trends at different levels of education.
Changes in enrolment do not seem to have been the main factor behind changes in expenditure on educational
institutions per non-tertiary student. Expenditure by non-tertiary educational institutions increased in most countries
by an average of 4% between 2010 and 2015 (Table C1.3). Over the same period, enrolment at those levels decreased
slowly, with a total decline of 1% over the five-year period. Falling enrolment together with increasing expenditure
resulted in greater expenditure per student at those levels – 5% higher in 2015 than in 2010. Most countries were
spending more per student in 2015 than they did in 2010, with the exception of the United States and some European
countries that were hard hit by the economic crisis of 2008: Estonia, France, Ireland, Slovenia and Spain. On the other
hand, expenditure per student increased significantly between 2010 and 2015 in several countries and by 20% in Chile,
24% in Korea, 30% in Latvia and 22% in the Slovak Republic. In Chile, Korea, Latvia, Poland and the Slovak Republic
a decrease in enrolments of more than 5% coincided with significant increases in spending on educational institutions
per student between 2010 and 2015. On the contrary, in Ireland, Slovenia and Spain the increase in enrolments was
accompanied by a reduction in spending on educational institutions.
Expenditure at tertiary level increased much more quickly than at lower levels of education, rising on average
by 12% between 2010 and 2015. This results, in part, from growth in enrolment of 3% over the same period.
OECD countries recorded on average an increase of 11% in the expenditure per student over this five-year period.
Of the 26 OECD and partner countries with available data, Chile, Finland, France, Germany, Ireland, Israel, Mexico
and Spain recorded a decrease in expenditure on tertiary education per student. In most of these countries,
the decline was mainly the result of a rapid increase in the number of tertiary students. In countries such as Estonia
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chapter C Financial Resources Invested In Education
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and the Slovak Republic, for example, increases in expenditure per student were mainly due to an increase in total
expenditure and a decrease in the number of students at tertiary level. However, as is the case in Australia, Belgium,
the Netherlands and Norway, large increases in the number of tertiary students do not necessarily lead to a decrease
in expenditure per student (Table C1.3).

C1

Definitions
Ancillary services are services provided on educational institutions that are peripheral to their main educational
mission. The main component of ancillary services is student welfare. In primary, secondary and post-secondary
non-tertiary education, student welfare services include meals, school health services and transportation to and
from school. At the tertiary level, they include residence halls (dormitories), dining halls and health care.
Core educational services include all expenditures that are directly related to instruction in educational institutions,
including teachers’ salaries, construction and maintenance of school buildings, teaching materials, books and
administration of schools.
Research and development includes research performed at universities and other tertiary educational institutions,
regardless of whether the research is financed from general institutional funds or through separate grants or
contracts from public or private sponsors.

Methodology
Expenditure per student on educational institutions at a particular level of education is calculated by dividing
total expenditure on educational institutions at that level by the corresponding full-time equivalent enrolment. Only
educational institutions and programmes for which both enrolment and expenditure data are available are taken
into account. Expenditure in national currency is converted into equivalent USD by dividing the national currency
figure by the purchasing power parity (PPP) index for GDP. The PPP conversion factor is used because the market
exchange rate is affected by many factors (interest rates, trade policies, expectations of economic growth, etc.) that
have little to do with current relative domestic purchasing power in different OECD countries (see Annex 2 for
further details).
Expenditure per student on educational institutions relative to per capita GDP is calculated by dividing
expenditure per student on educational institutions by the percentage of per capita GDP. In cases where the
educational expenditure data and the GDP data pertain to different reference periods, the expenditure data are
adjusted to the same reference period as the GDP data, using inflation rates for the OECD country in question
(see Annex 2).
Full-time equivalent student: The ranking of OECD countries by annual expenditure on educational services per
student is affected by differences in how countries define full-time, part-time and full-time equivalent enrolment.
Some OECD countries count every participant at the tertiary level as a full-time student, while others determine a
student’s intensity of participation by the credits that he/she obtains for successful completion of specific course
units during a specified reference period. OECD countries that can accurately account for part-time enrolment have
higher apparent expenditure per full-time equivalent student on educational institutions than OECD countries that
cannot differentiate among the different types of student attendance.
Data on subnational regions on how much is spent per student are adjusted using national purchasing power parities
(PPPs). Future work on cost of living at subnational level is required to fully adjust expenditure per student used in
this section.
For more information please see the OECD Handbook for Internationally Comparative Education Statistics 2018 (OECD,
2018[3]) and Annex 3 for country-specific notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Lithuania was not an OECD member at the time of preparation of this publication. Accordingly, Lithuania does not
appear in the list of OECD members and is not included in the zone aggregates.

Source
Data refer to the financial year 2015 (unless otherwise specified) and are based on the UNESCO, OECD and Eurostat
(UOE) data collection on education statistics administered by the OECD in 2017 (for details see Annex 3 at http://
dx.doi.org/10.1787/eag-2018-36-en). Data from Argentina, China, Colombia, India, Indonesia, Saudi Arabia and
South Africa are from the UNESCO Institute of Statistics (UIS).

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The data on expenditure for 2005, 2011 to 2015 were updated based on a survey in 2017-18, and expenditures
for 2005 to 2014 were adjusted to the methods and definitions used in the current UOE data collection.
Data on subnational regions for selected indicators have been released by the OECD, with the support from the
US National Centre for Education Statistics (NCES) and are currently available for four countries: Belgium, Canada,
Germany and the Russian Federation. Subnational estimates were provided by countries using national data sources.

Note regarding data from Israel
The statistical data for Israel are supplied by and are under the responsibility of the relevant Israeli authorities. The use
of such data by the OECD is without prejudice to the status of the Golan Heights, East Jerusalem and Israeli settlements
in the West Bank under the terms of international law.

References
OECD (2018), OECD Handbook for Internationally Comparative Education Statistics 2018: Concepts, Standards, Definitions [3]
and Classifications, OECD Publishing, Paris, https://doi.org/10.1787/9789264304444-en.
OECD (2017), Education at a Glance 2017: OECD Indicators, OECD Publishing, Paris, http://dx.doi.org/10.1787/eag-2017-en. [2]
OECD/NCES (2018), Education at a Glance Subnational Supplement, OECD/National Center for Education Statistics, Paris and [1]
Washington DC, https://nces.ed.gov/surveys/annualreports/oecd/index.asp.

Indicator C1 Tables
1 2 https://doi.org/10.1787/888933804109

Table C1.1 Total expenditure on educational institutions per full-time equivalent student (2015)
Table C1.2 Total expenditure on educational institutions per full-time equivalent student for core educational
services, ancillary services and R&D (2015)
Table C1.3 Change in total expenditure per student on educational institutions (2005, 2011 and 2015)
WEB Table C1.4 Total expenditure on educational institutions per full-time equivalent student relative to GDP
per capita (2015)
WEB Table C1.5 Total expenditure on educational institutions per full-time equivalent student, by source of funds
(2015)
WEB Table C1.6 Cumulative expenditure per student on educational institutions between ages 6 and 15 (2015)
Cut-off date for the data: 18 July 2018. Any updates on data can be found on line at http://dx.doi.org/10.1787/eag-data-en. Data can also be found
at http://stats.oecd.org/, Education at a Glance Database.

Education at a Glance 2018: OECD Indicators   © OECD 2018

253

C1

chapter C Financial Resources Invested In Education
Under embargo until 11/09/2018 at 11.00am CEST
Table C1.1. Total expenditure on educational institutions per full-time equivalent student (2015)
In equivalent USD converted using PPPs for GDP, direct expenditure within educational institutions,
by level of education, based on full-time equivalents

(9)

(10)

(11)

(12)

(13)

(14)

9 343
4 876
x(3, 4, 5, 6)
x(8)
a
2 399
m
7 929
x(4, 5, 6)
9 286
10 736
m
12 301
13 860
m
m
m
x(5, 6, 9, 10, 11)
a
8 235
1 588
a
12 655
9 990
16 962
4 424
x(5, 6, 11)
7 774
a
x(4, 5, 6)
5 102
m
a
a
14 294

10 766
13 931
11 856
10 468d
4 996
7 075
m
6 663
10 025
9 897
10 863
6 191
5 852
11 207
8 671
m
8 831
10 167
11 688
6 824
20 451
2 998
10 960
9 266
14 353
6 725
8 533
6 747
8 406
8 189
11 052
m
3 715
11 028
12 424

21 290
16 700
11 577
m
4 103
18 635
m
a
a
14 093
10 149
a
4 102
8 918
x(11)
5 267
4 120
13 806d
5 817
10 693
24 769
x(11)
10 543
11 494
16 399
16 373
x(11)
8 263
3 129
9 088
6 777
m
x(11)
8 421
x(11)

20 122
17 718
17 538
m
10 164
10 870
m
12 867
17 591
16 805
17 036
4 095
8 952
12 754
x(11)
13 865
11 285
20 758d
11 310
10 046
51 625
x(11)
19 323
16 015
21 129
9 678
x(11)
15 998
11 140
13 487
25 889
m
x(11)
27 931
x(11)

20 344
17 555
17 320
m
8 406
10 891
m
12 867
17 591
16 145
17 036
4 095
8 761
12 671
13 229
11 003
11 257
19 289d
10 109
10 137
48 907
8 170
19 286
15 166
20 973
9 687
11 766d
15 874
10 208
12 605
24 417
m
8 901
26 320
30 003

14 159
13 138
11 627
m
8 067
6 365
m
8 404
10 391
10 638
10 018
2 601
7 068
x(11)
9 747
7 109
7 352
x(11)
8 141
8 208
41 905
6 404
12 107
12 207
12 363
7 647
7 477d
9 845
8 075
9 328
11 297
m
7 018
20 526
26 817

12 829
15 043
12 900
m
5 986
7 919
m
8 133
11 518
11 106
12 139
5 470
6 346
11 499
9 439
m
9 308
12 120
11 143
7 595
22 430
3 611
12 730
10 392
15 705
7 400
9 153
8 477
8 778
9 130
13 289
m
4 652
13 355
16 518

11 497
13 688
11 812
m
5 888
6 918
m
7 076
10 098
10 040
10 689
4 957
6 058
x(13)
8 852
m
8 539
x(13)
10 464
7 146
21 943
x(13)
11 204
x(13)
13 947
6 935
8 331
7 334
8 338
8 432
11 093
m
4 312
12 473
15 776

OECD average
EU22 average

8 631

9 941

9 119

11 037

10 196

10 010

8 927

9 401

11 022

16 518

15 656

11 202

10 520

9 772

8 656

10 175

9 445

11 428

10 230

10 105

m

9 465

11 090

16 835

15 998

11 132

10 555

9 617

Argentina
Brazil
China
Colombia2
Costa Rica
India
Indonesia
Lithuania
Russian Federation
Saudi Arabia
South Africa

m
3 762
m
3 178
m
m
m
5 500
x(8)
m
m

m
3 789
m
2 909
m
m
m
5 135
x(8)
m
m

m
x(5)
m
x(5)
m
m
m
5 244
x(8)
m
m

m
x(5)
m
x(5)
m
m
m
5 484
x(8)
m
m

m
3 986d
m
2 586d
m
m
m
5 310
x(8)
m
m

m
3 872d
m
2 817d
m
m
m
5 188
x(8)
m
m

m
x(5, 6)
m
x(5, 6)
m
m
m
5 483
x(8)
m
m

m
3 829
m
2 987
m
m
m
5 292
4 473d
m
m

m
x(11)
m
x(11)
m
m
m
a
4 249
m
m

m
m
x(11) 14 261
m
m
x(11) 6 369
m
m
m
m
m
m
9 657
9 657
9 554
8 369
m
m
m
m

m
x(11)
m
x(11)
m
m
m
6 457
7 527
m
m

m
4 451
m
3 683
m
m
m
6 393
5 409
m
m

m
x(13)
m
x(13)
m
m
m
5 585
x(13)
m
m

m

m

m

m

m

m

m

m

m

m

m

m

G20 average

m

m

Primary
to tertiary

(8)

12 303
15 477
13 070d
12 900
4 930
8 476
m
6 861
10 482d
11 747
11 791
6 786
5 870
11 149
10 111
7 987d
9 079
11 147d
12 202
6 930
20 413
3 129
12 850
10 383
15 401
6 806
9 518d
6 660
8 290
9 020d
11 402
m
3 511
10 569
13 084

All
tertiary

(7)

12 028
15 432
13 352d
12 900
4 909
8 251
m
7 090
8 543d
13 799
13 652
6 490
6 966
10 023
10 259
7 987d
8 969
11 715d
13 247
7 123
19 808
4 224
13 241
11 509
16 095
6 655
9 469d
7 092
7 230
9 269d
11 331
m
3 528
10 798
13 474

Long-cycle
tertiary

(6)

9 328
16 696
13 497d
x(5)
5 054
8 566
m
8 048
8 587d
14 963
15 943
8 513
9 794
14 821
a
15 400d
x(5)
x(5)
x(5)
7 233
20 587
4 429
14 698
12 544
15 768
7 346
x(5)
7 658
6 846
10 408d
16 873
m
3 919
9 440
x(5)

Short-cycle
tertiary

Post-secondary
non‑tertiary

(5)

12 826
13 514
13 138d
x(5)
4 852
7 368
m
6 514
8 425
13 131
11 423
5 678
6 110
8 142
10 259
6 025d
x(5)
x(5)
x(5)
7 049
18 580
4 098
10 329
11 206
16 429
5 775
x(5)
6 069
7 971
8 716
7 749
m
3 175
11 660
x(5)

All
programmes

(4)

9 546 12 466
11 689 15 514
10 211 12 538
9 249d
x(1)
5 064
4 974
5 207
8 714
m
m
6 327
6 614
9 305 14 682
7 395 10 268
8 619 10 680
5 810
7 099
5 089
4 711
11 215 12 872
8 288
9 983
7 971 x(3, 4, 5)
8 426
9 258
9 105 10 562
11 047 11 025
6 672
6 723
20 892 21 124
2 874
2 514
8 478 12 491
7 849
9 409
13 275 14 486
6 757
6 985
7 380
9 568
6 877
6 282
8 542
9 925
7 320
8 765
10 853 11 493
m
m
4 134
3 491
11 630 10 249
11 727 12 693

Vocational
programmes

(3)

Australia
Austria
Belgium
Canada1
Chile2
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United Kingdom
United States

General
programmes

All
secondary

OECD
Partners

Primary to tertiary
(excluding R&D)

(2)

Upper secondary

All tertiary
(excluding R&D)

Lower secondary

(1)

C1

Tertiary
Primary, secondary,
and post-secondary
non-tertiary

Primary

Secondary

Note: See Definitions and Methodology sections for more information. Data and more breakdowns available at http://stats.oecd.org/, Education at a Glance Database.
1. Primary education includes data from pre-primary and lower secondary education.
2. Year of reference 2016.
Source: OECD / UIS / Eurostat (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933804128

254 Education at a Glance 2018: OECD Indicators   © OECD 2018

chapter C

How much is spent per student on educational institutions? – INDICATOR C1

Under embargo until 11/09/2018 at 11.00am CEST
Table C1.2. Total expenditure on educational institutions per full-time equivalent student

for core educational services, ancillary services and R&D (2015)

In equivalent USD converted using PPPs for GDP, direct expenditure within educational institutions,
by level of education, based on full-time equivalents
Primary, secondary and
post‑secondary non-tertiary

Tertiary

Partners

OECD

Core Ancillary
All
Core Ancillary
services services services services services

R&D

Primary to tertiary
All
services
excluding Core Ancillary
All
R&D
services services
services

R&D

All
services
excluding
All
R&D
services

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

(13)

Australia
Austria
Belgium
Canada1
Chile2
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy3
Japan
Korea
Latvia
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United Kingdom
United States

10 541
13 261
11 452
x(3)
x(3)
6 624
m
6 567
9 023
8 643
10 573
x(3)
5 193
10 971
x(3)
m
8 452
x(3, 7)
10 751
6 714
19 571
x(3)
10 960
x(3)
13 850
6 551
7 974
5 822
7 719
7 564
9 888
m
3 426
9 871
11 410

225
670
404
x(3)
x(3)
451
m
96
1 003
1 254
290
x(3)
658
236
x(3)
m
378
x(3, 7)
938
110
880
x(3)
a
x(3)
503
175
560
925
687
625
1 165
m
289
1 157
1 014

10 766
13 931
11 856
10 468
4 996
7 075
m
6 663
10 025
9 897
10 863
6 191
5 852
11 207
8 671
m
8 831
10 167
11 688
6 824
20 451
2 998
10 960
9 266
14 353
6 725
8 533
6 747
8 406
8 189
11 052
m
3 715
11 028
12 424

13 370
12 963
10 654
m
7 961
6 287
m
8 401
10 391
9 870
9 137
x(7)
6 452
12 671
9 747
7 069
6 945
x(7)
8 054
8 080
40 800
x(7)
12 107
x(7)
12 120
7 437
6 868 d
7 990
7 755
8 807
11 297
m
6 296
18 429
23 448

788
175
973
m
106
78
m
3
0
768
880
x(7)
615
0
a
40
406
x(7)
86
128
1 105
x(7)
a
x(7)
243
210
608 d
1 855
320
521
0
m
722
2 096
3 370

6 186
4 417
5 693
m
339
4 526
m
4 463
7 200
5 507
7 018
1 493
1 694
0
3 483
3 894
3 906
x(7)
1 968
1 928
7 002
1 766
7 179
2 959
8 610
2 040
4 289 d
6 029
2 133
3 278
13 120
14 282
1 882
5 794
3 186

20 344
17 555
17 320
m
8 406
10 891
m
12 867
17 591
16 145
17 036
4 095
8 761
12 671
13 229
11 003
11 257
19 289 d
10 109
10 137
48 907
8 170
19 286
15 166
20 973
9 687
11 766 d
15 874
10 208
12 605
24 417
m
8 901
26 320
30 003

14 159
13 138
11 627
m
8 067
6 365
m
8 404
10 391
10 638
10 018
2 601
7 068
12 671
9 747
7 109
7 352
x(7)
8 141
8 208
41 905
6 404
12 107
12 207
12 363
7 647
7 477 d
9 845
8 075
9 328
11 297
m
7 018
20 526
26 817

11 151
13 169
11 299
m
x(12)
6 550
m
7 002
10 098
8 881
10 276
x(12)
5 407
11 310
x(12)
m
8 156
x(12)
9 820
7 032
21 048
x(12)
11 204
x(12)
13 497
6 752
7 762
6 233
7 727
7 828
10 124
m
3 944
11 173
14 213

347
518
513
m
x(12)
368
m
74
0
1 160
412
x(12)
651
189
x(12)
m
384
x(12)
644
114
896
x(12)
a
x(12)
450
183
569
1 101
611
603
970
m
367
1 300
1 563

1 332
1 355
1 088
m
98
1 001
m
1 057
1 420
1 065
1 450
513
288
0
586
m
769
x(12)
679
449
487
x(12)
1 526
x(12)
1 759
465
822
1 142
440
698
2 196
2 679
340
882
742

12 829
15 043
12 900
m
5 986
7 919
m
8 133
11 518
11 106
12 139
5 470
6 346
11 499
9 439
m
9 308
12 120
11 143
7 595
22 430
3 611
12 730
10 392
15 705
7 400
9 153
8 477
8 778
9 130
13 289
m
4 652
13 355
16 518

11 497
13 688
11 812
m
5 888
6 918
m
7 076
10 098
10 040
10 689
4 957
6 058
11 499
8 852
m
8 539
x(12)
10 464
7 146
21 943
x(12)
11 204
x(12)
13 947
6 935
8 331
7 334
8 338
8 432
11 093
m
4 312
12 473
15 776

OECD average
EU22 average

8 822
8 843

579
622

9 401
9 465

10 654
10 696

593
579

4 409
4 723

15 656
15 998

11 249
11 132

9 086
9 082

548
562

886
911

10 520
10 555

9 834
9 617

m
x(3)
m
x(3)
m
m
m

m
x(3)
m
x(3)
m
m
m

m
3 829
m
2 987
m
m
m

m
x(7)
m
x(7)
m
m
m

m
x(7)
m
x(7)
m
m
m

m
x(7)
m
x(7)
m
m
m

m
14 261
m
6 369
m
m
m

m
x(7)
m
x(7)
m
m
m

m
x(12)
m
x(12)
m
m
m

m
x(12)
m
x(12)
m
m
m

m
x(12)
m
x(12)
m
m
m

m
4 451
m
3 683
m
m
m

m
x(12)
m
x(12)
m
m
m

Argentina
Brazil
China
Colombia2
Costa Rica
India
Indonesia
Lithuania

5 041

250

5 292

5 795

662

3 200

9 657

6 457

5 232

354

807

6 393

5 585

Russian Federation

x(3)

x(3)

4 473 d

x(7)

x(7)

842

8 369

7 527

x(12)

x(12)

x(12)

5 409

x(12)

Saudi Arabia

m

m

m

m

m

m

m

m

m

m

m

m

m

South Africa

m

m

m

m

m

m

m

m

m

m

m

m

m

G20 average

m

m

m

m

m

m

m

m

m

m

m

m

m

Note: Data on early childhood education are available in Indicator B2. See Definitions and Methodology sections for more information. Data and more breakdowns
available at http://stats.oecd.org/, Education at a Glance Database.
1. Primary education includes data from pre-primary and lower secondary education.
2. Year of reference 2016.
3. Data from post-secondary non-tertiary is excluded from the computations.
Source: OECD / UIS / Eurostat (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933804147

Education at a Glance 2018: OECD Indicators   © OECD 2018

255

C1

chapter C Financial Resources Invested In Education
Under embargo until 11/09/2018 at 11.00am CEST
Table C1.3. Change in total expenditure per student on educational institutions (2005, 2011 and 2015)
Index of change (GDP deflator 2010 = 100, constant prices)
Primary, secondary and post-secondary non-tertiary
Change in total
expenditure
(2010=100)

Partners

OECD

C1

Tertiary

Change in number
of students
(2010=100)

Change in expenditure
per student
(2010=100)

Change in total
expenditure
(2010=100)

Change in number
of students
(2010=100)

Change in expenditure
per student
(2010=100)

2005

2011

2015

2005

2011

2015

2005

2011

2015

2005

2011

2015

2005

2011

2015

2005

2011

2015

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

(13)

(14)

(15)

(16)

(17)

(18)

Australia
Austria
Belgium
Canada1
Chile2
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United Kingdom
United States

76
m
88
83d
88
91
92
92
90
94
93
m
m
107
70
76
103
97
71
100
m
91
88
m
91
82
93
74
97
84
98
m
m
92
92

98
m
101
98d
104
103
92
93
101
99
100
m
m
103
100
111
96
100
103
96
96
104
99
m
95
98
94
93
98
98
100
m
m
102
98

104
m
105
104d
113
107
m
93
101
100
98
m
m
112
85
135
99
100
105
118
98
115
99
m
109
105
101
108
87
95
107
m
m
114
100

99
m
105
m
108
113
95
118
100
100
106
m
107
99
93
92
98
104
108
129
m
95
98
m
98
120
m
118
111
95
110
m
m
100
101

102
m
100
99d
98
98
105
98
99
100
98
m
99
100
101
102
101
99
97
96
m
101
100
m
101
98
m
97
99
101
99
m
110
101
101

103
m
103
104d
94
97
m
95
99
102
93
m
92
98
109
m
99
96
84
91
m
105
97
m
102
94
m
89
101
106
106
m
115
106
103

76
m
84
m
82
81
97
78
89
94
88
m
m
108
75
83
105
92
66
78
m
96
90
m
93
68
m
63
88
88
89
m
m
92
91

96
m
101
99d
106
105
88
95
102
98
101
m
m
103
99
109
95
101
106
100
m
103
99
m
94
101
m
96
99
96
101
m
m
101
97

100
m
102
100d
120
110
m
98
102
97
105
m
m
114
78
m
100
104
124
130
m
109
102
m
107
111
m
122
87
89
101
m
m
108
97

79
m
83
83
70
72
90
74
86
85
80
m
m
98
72
83
89
92d
m
105
m
79
84
m
m
85
88
78
93
79
86
m
m
m
86

102
m
102
97
111
117
102
114
104
101
104
m
m
97
98
111
102
104d
m
116
m
96
104
m
97
93
94
111
104
98
102
m
m
m
104

144
m
113
104
108
107
m
135
94
105
111
m
m
126
79
113
93
100d
m
131
m
121
111
m
122
109
88d
197
85
97
108
m
m
m
107

80
m
90
m
67
76
93
100
101
98
93
m
114
86
98
84
102
104d
98
119
m
86
84
m
94
106
80
81
96
90
97
m
m
95
85

103
m
103
m
107
101
94
100
101
101
105
m
107
103
100
101
99
100d
101
95
m
105
103
m
103
98
101
98
98
103
103
m
m
105
104

120
m
113
m
124
87
m
78
101
108
126
m
88
99
113
122
92
99d
98
84
m
130
110
m
114
87
85d
94
83
111
99
m
m
111
99

99
m
93
m
104
95
97
75
85
86
86
m
m
115
73
99
88
88d
m
89
m
92
100
m
m
80
110
97
96
88
89
m
m
m
101

99
m
99
m
103
116
109
113
103
100
99
m
m
94
98
110
103
104d
m
123
m
92
101
m
94
95
93
113
106
95
99
m
m
m
100

120
m
100
m
87
122
m
174
92
97
88
m
m
127
71
93
101
101d
m
156
m
93
101
m
107
125
104d
210
101
87
109
m
m
m
107

OECD average
EU22 average

89
90

99
98

104
101

104
106

100
100

99
99

86
85

100
99

105
102

84
84

103
104

112
110

93
95

102
101

103
98

93
90

102
104

111
115

Argentina
Brazil
China
Colombia2
Costa Rica
India
Indonesia
Lithuania

m
m
m
m
m
m
m

m
m
m
m
m
m
m

m
m
m
m
m
m
m

m
m
m
m
m
m
m

m
m
m
m
m
m
m

m
m
m
m
m
m
m

m
m
m
m
m
m
m

m
m
m
m
m
m
m

m
m
m
m
m
m
m

m
m
m
m
m
m
m

m
m
m
m
m
m
m

m
m
m
m
m
m
m

m
m
m
m
m
m
m

m
m
m
m
m
m
m

m
m
m
m
m
m
m

m
m
m
m
m
m
m

m
m
m
m
m
m
m

m
m
m
m
m
m
m

m

94

87

126

95

83

m

100

105

78

119

111

102

98

92

76

121

121

Russian Federation

77

104

110 d

m

m

m

m

m

m

43

93

86

m

94

77

m

99

111

Saudi Arabia

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

South Africa

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

G20 average

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

Note: See Definitions and Methodology sections for more information. Data and more breakdowns available at http://stats.oecd.org/, Education at a Glance Database.
1. Primary education includes data from pre-primary and lower secondary education.
2. Year of reference 2016.
Source: OECD / UIS / Eurostat (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933804166

256 Education at a Glance 2018: OECD Indicators   © OECD 2018

Under embargo until 11/09/2018 at 11.00am CEST

Under embargo until 11/09/2018 at 11.00am CEST

WHAT PROPORTION OF NATIONAL WEALTH IS SPENT ON
EDUCATIONAL INSTITUTIONS?
• In 2015, OECD countries spent an average of 5% of their gross domestic product (GDP) on

INDICATOR C2

educational institutions from primary to tertiary levels, with large variations across OECD and
partner countries.

• Across OECD countries, the share of national resources devoted to educational institutions in
non-tertiary education (primary, secondary and post-secondary non-tertiary levels) is 3.5% of
GDP, much larger than the share devoted to tertiary education (1.5% of GDP). However, private
sources play a crucial role in financing tertiary education accounting on average for around 25% of
expenditure on educational institutions (0.4% of GDP).

• Between 2010 and 2015, total expenditure on educational institutions from primary to tertiary
levels as a share of GDP decreased in more than two thirds of OECD and partner countries, mainly
due to the slower increase of public expenditure on educational institutions compared to GDP.

Figure C2.1. Total expenditure on educational institutions
as a percentage of GDP (2015)
From public, private and international sources, by level of education

7
6
5
4
3
2
1
0

Tertiary
Primary, secondary and post-secondary non-tertiary

Norway
New Zealand
United Kingdom
Colombia1
Chile1
United States
Israel
Australia
Canada2
Iceland
Korea
Belgium
Finland
Netherlands
Mexico
Sweden
Portugal
France
OECD average
Brazil
Austria
Latvia
Turkey
Estonia
EU22 average
Poland
Slovak Republic
Spain
Slovenia
Germany
Japan
Lithuania
Italy
Greece
Czech Republic
Hungary
Luxembourg
Ireland
Russian Federation

% of GDP

1. Year of reference 2016.
2. Primary education includes data from pre-primary and lower secondary education.
Countries are ranked in descending order of total expenditure on primary to tertiary educational institutions.
Source: OECD / UIS / Eurostat (2018), Table C2.1. See Source section for more information and Annex 3 for notes (http://dx.doi.
org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933804318

Context
Countries invest in educational institutions to help foster economic growth, enhance productivity,
contribute to personal and social development, and reduce social inequality, among other reasons.
The level of expenditure on educational institutions is affected by the size of a country’s schoolage population, enrolment rates, levels of teachers’ salaries, and the organisation and delivery of
instruction. At primary and lower secondary levels (which correspond broadly to the population
age 5 to age 14), enrolment rates are close to 100% in most OECD countries. Changes in the number
of students are, therefore, closely related to demographic changes. This is less the case in upper
secondary and tertiary education, as part of the concerned population has left the education system
(see Indicator B1).
In order to account for these issues, this indicator measures expenditure on educational institutions
relative to a nation’s wealth and demonstrates the priority given to education as a function of countries’
overall resources. National wealth is based on GDP, while expenditure on educational institutions

258 Education at a Glance 2018: OECD Indicators   © OECD 2018

Under embargo until 11/09/2018 at 11.00am CEST
includes spending by governments, enterprises, and individual students and their families. This
indicator covers expenditure on schools, universities and other public and private institutions
involved in delivering or supporting educational services.
Public budgets are highly scrutinised by governments, and during economic downturns, even core
sectors like education can be subject to budget cuts. This indicator provides a point of reference,
by showing how the volume of spending on educational institutions, relative to national GDP, has
evolved over time in OECD countries. In deciding how much to allocate to educational institutions,
governments must balance demands for increased spending in areas such as teachers’ salaries and
educational facilities with other areas of investment.

INDICATOR C2

Other findings

• The largest share of expenditure on educational institutions is devoted to primary and lower
secondary levels (48% of all OECD educational expenditure or 2.4% of GDP), and is a function of
the total number of students enrolled.

• The private sector in OECD countries directly funds 13% of total expenditure on educational
institutions from primary to tertiary educational levels (before transfers to the private sector),
representing 0.7% of GDP.

• Between 2010 and 2015, expenditure on educational institutions as a share of GDP remained rather
stable at tertiary levels and decreased slightly at non-tertiary levels by just over 6% on average
across OECD countries.

Education at a Glance 2018: OECD Indicators   © OECD 2018

259

chapter C Financial Resources Invested In Education
Under embargo until 11/09/2018 at 11.00am CEST

Analysis

C2

Overall investment relative to GDP
The share of national wealth devoted to educational institutions is substantial in all OECD and partner countries.
In 2015, OECD countries spent on average 5% of their GDP on educational institutions from primary to tertiary
levels (Table C2.1).
Expenditure on primary to tertiary educational institutions relative to GDP varies between 6% in Australia,
Colombia, Canada, Chile, Israel, New Zealand, Norway, the United Kingdom and the United States to 3%-4% in
the Czech Republic, Greece, Hungary, Ireland, Italy, Lithuania, Luxembourg and the Russian Federation (Figure C2.1
and Table C2.1). Many factors influence the relative position of countries on this measure including number of
students enrolled, duration of studies, and the effective allocation of funds. At the tertiary level, spending may be
influenced by the criteria to access higher levels of education, the number of students enrolled across sectors and
fields of study as well as the scale of investments in research activities.
Expenditure on educational institutions, by level of education
In all OECD and partner countries with available data, the share of national resources devoted to educational
institutions in non-tertiary education (primary, secondary and post-secondary non-tertiary levels) is much larger
than the share devoted to tertiary education (Table C2.1 and Figure C2.1). On average across OECD countries, 70%
of expenditure on educational institutions (3.5% of GDP) is directed to non-tertiary levels, due to the high levels of
enrolment at these levels. The share of resources devoted to educational institutions at non-tertiary levels is around
4.5% of GDP in Iceland, Israel, New Zealand, Norway and the United Kingdom while it accounts for slightly less than
3% of GDP in the Czech Republic, Greece, Hungary, Ireland, Japan, Lithuania, Luxembourg, the Russian Federation
and the Slovak Republic.
On average across OECD countries, expenditure on educational institutions amounts to 1.5% of GDP at the primary
level and 0.9% at lower secondary level. However, the share of expenditure on educational institutions is strongly
influenced by the demographic composition of the country. Countries with relatively high fertility rates are more
likely to spend a larger share of their wealth on primary and lower secondary education. Indeed, all the countries
where investment in primary education is below 1% of GDP are Central and East European countries with low birth
rates (Austria, the Czech Republic, Germany, Hungary and Lithuania) (Table C2.1). At the upper secondary level,
expenditure on educational institutions makes up 0.5% of GDP in vocational programmes and 0.6% of GDP in general
programmes, on average across OECD countries. However, these figures vary widely between countries. Of the
29 countries for which data are available, 12 spend more on vocational programmes than on general programmes,
with the largest differences found in Finland (0.7 percentage points) and the Netherlands (0.6 percentage points).
Post-secondary non-tertiary education, which often has vocational components, is the object of considerably less
expenditure across the OECD, representing about 0.1% of GDP on average.
Tertiary education accounts for 1.5% of GDP on average. At this level, there is great variation among OECD countries
in the pathways available to students, the duration of programmes, the organisation of teaching and the expenditure
devoted to research and development (R&D), resulting in significant differences in expenditure. In 2015, Canada,
Chile and the United States were the countries that spent the largest share of GDP on tertiary educational institutions
(around 2.5%). Unsurprisingly, these countries also have some of the strongest participation by private sources of
educational funding (after transfers to the private sector) at this level (1.2% of GDP for Canada and 1.7% for Chile
and the United States; Table C2.2 and Figure C2.2).
R&D spending in tertiary educational institutions can represent a significant share of total spending at this level
and is a function of the type and nature of research activities as well as the infrastructure and facilities available.
OECD countries in which most R&D is performed by tertiary educational institutions tend to report higher share
of expenditure on educational institutions over GDP than countries where R&D is mostly performed in other public
institutions or by the industrial sector. Excluding R&D activities decreases expenditure in tertiary educational
institutions as a share of GDP by 0.4 percentage points on average across OECD, though the difference is at least
0.7 percentage points in Finland, Norway, and Sweden (Table C2.1).
Expenditure on educational institutions, by source of funds
Government spending remains the main source of educational funding in OECD countries. On average, direct public
expenditure on educational institutions from primary to tertiary educational levels (before transfers to the private
sector) accounts for 4.2% of GDP. However, large differences are observed across countries with available data.

260 Education at a Glance 2018: OECD Indicators   © OECD 2018

chapter C

What proportion of national wealth is spent on educational institutions? – INDICATOR C2

Under embargo until 11/09/2018 at 11.00am CEST

Figure C2.2. Total expenditure on educational institutions as a percentage of GDP,
by source of funds (2015)
From public, private and international sources, by level of education
Public expenditure

C2

Lithuania

Czech Republic

Japan

Ireland

Slovak Republic

Hungary

Luxembourg

Italy

Estonia

Spain

Turkey

Austria

Poland

Slovenia

Latvia

EU22 average

OECD average

United States2

Chile1

France

Sweden

Mexico

Portugal

Australia

Korea

Finland

Belgium

Colombia1

Israel

Iceland

United Kingdom

Poland

EU22 average

Portugal

Iceland

Spain

Czech Republic

Slovenia

Italy

Hungary

Ireland

EU22 average

Poland

Slovak Republic

Spain

Slovenia

Lithuania

Italy

Czech Republic

Hungary

Luxembourg

Luxembourg

Mexico

France

Belgium

Lithuania

Latvia

OECD average

Estonia

% of GDP

Slovak Republic

Sweden

Finland

Norway

Austria

New Zealand

Estonia

Korea

United Kingdom

Chile

Australia

Tertiary

1

United States2

% of GDP

3.0
2.5
2.0
1.5
1.0
0.5
0.0

Private expenditure

Primary, secondary and post-secondary non-tertiary

New Zealand

5.0
4.5
4.0
3.5
3.0
2.5
2.0
1.5
1.0
0.5
0.0

Norway

% of GDP

Public to private transfer

Primary to tertiary

7.0
6.0
5.0
4.0
3.0
2.0

Ireland

Latvia

Austria

OECD average

France

Portugal

Sweden

Mexico

Finland

Belgium

Korea

Iceland

Australia

United States2

Chile1

United Kingdom

New Zealand

0.0

Norway

1.0

Note: International expenditure is aggregated with public expenditure for display purposes.
1. Year of reference 2016.
2. Net student loans rather than gross, thereby underestimating public transfers.
Countries are ranked in descending order of total expenditure on educational institutions per student.
Source: OECD / UIS / Eurostat (2018), Table C2.2. See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag2018-36-en).
1 2 https://doi.org/10.1787/888933804337

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chapter C Financial Resources Invested In Education
Under embargo until 11/09/2018 at 11.00am CEST
In the Czech Republic, Greece, Hungary, Ireland, Italy, Japan, Lithuania, Luxembourg and the Russian Federation,
public direct investment represents around 3% of GDP, while Nordic countries, such as Finland and Norway, and
Costa Rica devote around 6% of their GDP in public direct expenditure on educational institutions (Figure C2.2).

C2

From primary to tertiary education, public transfers to households (such as scholarships and loans to students for
tuition and other fees) and subsidies to other private entities for education (e.g. to firms or labour organisations
that operate apprenticeship programmes) comprise 0.2% of GDP on average across OECD countries, and they
account for more than 0.4% of GDP in Australia, Chile and New Zealand and reaching 0.6% in the United Kingdom
(Figure C2.2).
With tightening public budgets, many educational systems are turning more towards the private sector for additional
investment. Particularly for tertiary education, rewarded by stronger premiums in the labour market, financial
mechanisms are being used to leverage the participation of learners and third-party payers. The private sector,
net of public transfers, is the direct source of 13% of total expenditure on educational institutions from primary
to tertiary levels, accounting for 0.7% of GDP. Countries nevertheless differ considerably in the degree of direct
private payments to educational institutions ranging from 0.1% or less of national GDP in Finland, Luxembourg
and Norway, to 1.5%-2% in Australia, Chile and the United States (Figure C2.2).
At non-tertiary levels of education, direct private investment is low and accounts for 0.3% of GDP on average across
OECD countries, but is at least 0.7% of GDP in Australia, Colombia and New Zealand which have the largest relative
shares of private funds invested in non-tertiary education. At the tertiary level, however, direct private investment
play a more crucial role, accounting on average for around 25% of expenditure on educational institutions, or 0.4%
of GDP before even public to private transfers are accounted for. In some countries, private sources contribute to
a large share of investment in tertiary education. Chile and the United States stand out for spending the largest
percentage of GDP on tertiary educational institutions (at least 2.5% of GDP). This is partly driven by having the
highest shares of private sources, even before accounting for public transfers to private entities (1.2% in Chile
and 1.6% in the United States). In Australia and the United Kingdom, public transfers support about 25% of total
expenditure for tertiary educational institutions, and around 20% in Chile, Ireland and New Zealand (Table C2.2
and Figure C2.2).
Changes in educational expenditure between 2010 and 2015
The effects of the global economic crisis that began in 2008 are currently reflected in the adjustments of public
budgets and, therefore, in the expenditure on educational institutions across all levels of education. Public
expenditure on educational institutions started to increase back in 2010 but at a slower pace than GDP, as a result
of the time needed to adjust public budgets (Table C2.4, available on line). However, across OECD countries, total
average expenditure on educational institutions at all levels as a percentage of GDP decreased by 4.1% between
2010 and 2015 (Table C2.3). Among the 28 countries with available data for this period, 20 of them experienced
a reduction of the total expenditure on educational institutions as a share of GDP. Estonia, Ireland, Lithuania and
Slovenia were among the countries with the largest negative adjustments, while the Slovak Republic was one of the
major exceptions, with an increase of 14% (Figure C2.3).
Spending on the various levels of education evolved quite differently between 2010 and 2015. While expenditure on
educational institutions relative to GDP remained rather stable at tertiary level, it decreased slightly at non‑tertiary
level (by just over 6%). However, this average masks significant changes in some countries. In Australia, Estonia,
Ireland, Lithuania, Luxembourg, Slovenia and the United States, for example, expenditure on non-tertiary education
as a share of GDP decreased by at least 10% over the five-year period. The reduction observed in Ireland (40%) can
be mainly explained by a revision in its 2015 GDP data. Over the same period, Israel experienced one of the highest
increases in the share of expenditure on these educational levels (13%).
At the tertiary level, stable investments are observed between 2010 and 2015 on average across OECD countries.
Indeed, about a third of countries with available data increased their investments in tertiary education between
2010 and 2015, although their spending at non-tertiary levels has declined. Some clear examples are Australia
and the Slovak Republic who increased their share of GDP invested on tertiary educational institutions by
21% and 74% but decreased their investments in non-tertiary educational institutions by at least 4% during
this period. The increase in total tertiary spending as a share of GDP in the Slovak Republic, the largest across
OECD and partner countries, is mainly driven by a substantial increase in both public and private investment
on education.

262 Education at a Glance 2018: OECD Indicators   © OECD 2018

What proportion of national wealth is spent on educational institutions? – INDICATOR C2

chapter C

Under embargo until 11/09/2018 at 11.00am CEST

Figure C2.3. Change in total expenditure on educational institutions as a percentage of GDP
between 2010 and 2015
From public, private and international sources, by level of education, reference year 2010=100
Primary, secondary and post-secondary non-tertiary
Tertiary
Primary to tertiary

Index of change
(2010 = 100)

190

C2

170
150
130
110
90
70

Ireland

Lithuania

Slovenia

Poland

Estonia

Chile2

United States

Russian Federation

Germany

Japan

Canada1

EU22 average

France

OECD average

Spain

Sweden

Australia

Czech Republic

Norway

Finland

Netherlands

Brazil

Italy

Iceland

Mexico

Belgium

Portugal

Latvia

Israel

Slovak Republic

50

1. Primary education includes data from pre-primary and lower secondary education.
2. Year of reference 2016.
Countries are ranked in descending order of the change in total expenditure on educational institutions as a percentage of GDP for primary to tertiary educational
levels.
Source: OECD / UIS / Eurostat (2018), Table C2.3. See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag2018-36-en).
1 2 https://doi.org/10.1787/888933804356

Definitions
Expenditure on educational institutions refers to public, private and international expenditure on entities that
provide instructional services to individuals or education-related services to individuals and other educational
institutions (schools, universities and other public and private institutions).
Initial public, private and international shares of educational expenditure are the percentages of total education
spending originating in, or generated by, the public, private and international sectors before the flow of transfers. Initial
public spending includes both direct public expenditure for educational institutions and transfers to the private sector
and excludes transfers from the international sector. Initial private spending includes tuition fees and other student
or household payments to educational institutions, minus the portion of such payments offset by public subsidies.
Initial international spending includes both direct international expenditure for educational institutions (for example
a research grant from a foreign corporation to a public university) and international transfers to governments.
Final public, private and international shares are the percentages of educational funds expended directly by public,
private and international purchasers of educational services after the flow of transfers. Final public spending
includes direct public purchases of educational resources and payments to educational institutions. Final private
spending includes all direct expenditure on educational institutions (tuition fees and other private payments
to educational institutions), whether partially covered by public subsidies or not. Private spending also includes
expenditure by private companies on the work-based element of school- and work-based training of apprentices and
students. Final international spending includes direct international payments to educational instructions such as
research grants or other funds from international sources paid directly to educational institutions.
Public subsidies to households and other private entities for educational institutions include public and
international transfers, such as scholarships and other financial aid to students, plus certain subsidies to other
private entities. Therefore, they are composed of government transfers and certain other payments to households,
Education at a Glance 2018: OECD Indicators   © OECD 2018

263

chapter C Financial Resources Invested In Education
Under embargo until 11/09/2018 at 11.00am CEST
insofar as these translate into payments to educational institutions for educational services (for example, fellowships,
financial aid or student loans for tuition). They also include government transfers and some other payments (mainly
subsidies) to other private entities, including subsidies to firms or labour organisations that operate apprenticeship
programmes and interest subsidies to private financial institutions that provide student loans, etc.

C2

Direct public expenditure on educational institutions can take the form of either purchases by the government
agency itself of educational resources to be used by educational institutions or payments by the government agency
to educational institutions that have responsibility for purchasing educational resources.
Direct private (from households and other private entities) expenditure on educational institutions includes
tuition fees and other private payments to educational institutions, whether partially covered by public subsidies
or not.

Methodology
Data appearing in earlier editions of this publication may not always be comparable to data shown in the 2018
edition due to changes in definitions and coverage.
Expenditure on educational institutions as a percentage of GDP at a particular level of education is calculated by
dividing total expenditure on educational institutions at that level by GDP. Expenditure and GDP values in national
currency are converted into equivalent USD by dividing the national currency figure by the purchasing power parity
(PPP) index for GDP. The PPP conversion factor is used because the market exchange rate is affected by many factors
(interest rates, trade policies, expectations of economic growth, etc.) that have little to do with current relative
domestic purchasing power in different OECD countries (see Annex 2 for further details).
All entities that provide funds for education, either initially or as final payers, are classified as either governmental
(public) sources, non-governmental (private) sources or international sources, such as international agencies and
other foreign sources. Figures presented here group together public and international expenditure for display
purposes. As the share of international expenditure is relatively small compared to other sources, its integration
into the public sources does not affect the analysis of the share of public spending.
Not all spending on instructional goods and services occurs within educational institutions. For example, families
may purchase commercial textbooks and materials or seek private tutoring for their children outside educational
institutions. At the tertiary level, students’ living expenses and foregone earnings can also account for a significant
proportion of the costs of education. All expenditure outside educational institutions, even if publicly subsidised,
is excluded from this indicator. Public subsidies for educational expenditure outside institutions are discussed in
Indicators C4 and C5.
A portion of the budgets of educational institutions is related to ancillary services offered to students, including
student welfare services (student meals, housing and transport). Part of the cost of these services is covered by fees
collected from students and is included in the indicator.
Expenditure on educational institutions is calculated on a cash-accounting basis and, as such, represents a snapshot
of expenditure in the reference year. Many countries operate a loan payment/repayment system at the tertiary level.
While public loan payments are taken into account, loan repayments from private individuals are not, and so the
private contribution to education costs may be under-represented.
It should be noted that student loans provided by private financial institutions (rather than directly by a government)
are counted as private expenditure, although any interest rate subsidies or government payments on account of loan
defaults are captured as under public funding.
For more information please see the OECD Handbook for Internationally Comparative Education Statistics 2018 (OECD,
2018[1]) and Annex 3 for country-specific notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Lithuania was not an OECD member at the time of preparation of this publication. Accordingly, Lithuania does not
appear in the list of OECD members and is not included in the zone aggregates.

Source
Data refer to the financial year 2015 (unless otherwise specified) and are based on the UNESCO, OECD and Eurostat
(UOE) data collection on education statistics administered by the OECD in 2017 (for details see Annex 3 at http://
dx.doi.org/10.1787/eag-2018-36-en). Data from Argentina, China, Colombia, India, Indonesia, Saudi Arabia and
South Africa are from the UNESCO Institute of Statistics (UIS).

264 Education at a Glance 2018: OECD Indicators   © OECD 2018

What proportion of national wealth is spent on educational institutions? – INDICATOR C2

chapter C

Under embargo until 11/09/2018 at 11.00am CEST
The data on expenditure for 2005, 2011 to 2015 were updated based on a survey in 2017-18, and expenditure
for 2005 to 2014 were adjusted to the methods and definitions used in the current UOE data collection.

Note regarding data from Israel
The statistical data for Israel are supplied by and are under the responsibility of the relevant Israeli authorities. The use
of such data by the OECD is without prejudice to the status of the Golan Heights, East Jerusalem and Israeli settlements
in the West Bank under the terms of international law.

References
OECD (2018), OECD Handbook for Internationally Comparative Education Statistics 2018: Concepts, Standards, Definitions [1]
and Classifications, OECD Publishing, Paris, https://doi.org/10.1787/9789264304444-en.

Indicator C2 Tables
1 2 https://doi.org/10.1787/888933804242

Table C2.1 Total expenditure on educational institutions as a percentage of GDP (2015)
Table C2.2 Total expenditure on educational institutions as a percentage of GDP, by source of funds (2015)
Table C2.3 Change in total expenditure on educational institutions as a percentage of GDP (2005 to 2015)
WEB Table C2.4 Change in public expenditure on educational institutions (final source of funds) as a percentage of GDP
(2005 to 2015)
Cut-off date for the data: 18 July 2018. Any updates on data can be found on line at http://dx.doi.org/10.1787/eag-data-en. Data can also be found
at http://stats.oecd.org/, Education at a Glance Database.

Education at a Glance 2018: OECD Indicators   © OECD 2018

265

C2

chapter C Financial Resources Invested In Education
Under embargo until 11/09/2018 at 11.00am CEST
Table C2.1. Total expenditure on educational institutions as a percentage of GDP (2015)
Direct expenditure within educational institutions, by level of education
Secondary

All
programmes

All
secondary

Primary, secondary,
and post-secondary
non-tertiary

Short-cycle
tertiary

Long-cycle
tertiary

All
tertiary

All tertiary
(excluding R&D)

Primary
to tertiary

Primary to tertiary
(excluding R&D)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

(13)

(14)

Australia
Austria
Belgium
Canada1
Chile2
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United Kingdom
United States

1.8
1.3
0.9
1.2
1.6
0.9
2.1d
x(1)
1.8
0.6
0.8
0.9
m
m
1.4
0.7
1.4
1.1
1.2
1.3
0.6
1.2
1.3
0.8
0.8
0.7
2.2
1.0
1.4
0.6
2.4 x(3, 4, 5)
1.1
0.7
1.2
0.7
1.7
1.0
1.6
0.8
1.3
0.8
1.9
1.0
1.2
1.2
1.7
1.3
2.1
1.0
1.6
0.8
1.6
1.2
1.0
0.9
1.5
0.8
1.3
0.8
1.8
0.8
m
m
1.1
0.9
2.0
1.0
1.6
0.9

0.6
0.3
0.7d
x(5)
0.9
0.2
m
0.4
0.4
0.8
0.4
0.5
0.7
0.7
0.5
1.3d
x(5)
x(5)
x(5)
0.5
0.3
0.6
0.3
1.0
0.7
0.3
x(5)
0.3
0.3
0.6
0.4
m
0.5
0.9
x(5)

0.1
0.6
1.1d
x(5)
0.4
0.7
m
0.3
1.0d
0.5
0.5
0.3
0.4
0.5
a
0.9d
x(5)
x(5)
x(5)
0.4
0.6
0.4
0.9
0.3
0.7
0.5
x(5)
0.6
0.6
0.3d
0.6
m
0.6
0.5
x(5)

0.7
1.0
1.8d
1.4
1.2
0.9
m
0.8
1.4d
1.3
0.9
0.8
1.1
1.2
0.5
2.1d
1.1
0.8d
1.3
0.9
0.9
0.9
1.2
1.4
1.5
0.8
1.2d
0.9
0.9
0.9d
1.0
m
1.1
1.4
1.0

2.0
0.1
2.2
0.0
2.7d
x(3, 4, 5, 6)
1.4
m
1.8
a
1.8
0.0
m
m
1.4
0.2
2.6d
x(4, 5, 6)
2.5
0.0
2.2
0.2
1.5
m
1.8
0.3
2.3
0.1
1.1
m
2.1
0.0
1.9
0.1
1.5d x(5, 6, 9, 10, 11, 12)
2.3
a
1.6
0.1
1.7
0.0
2.0
a
2.4
0.0
2.7
0.2
2.5
0.0
1.6
0.1
2.4d
x(5, 6, 10, 11, 12)
1.9
0.0
1.7
a
1.7d
x(4. 5. 6)
1.9
0.0
m
m
2.0
a
2.4
a
1.8
0.0

3.9
3.1
4.3
3.5d
3.6
2.6
m
3.0
4.0
3.7
3.0
2.9
2.9
4.5
2.7
4.5
3.0
2.7
4.0
3.3
2.9
3.9
3.6
4.5
4.6
3.2
3.9
2.9
3.3
3.1
3.6
m
3.1
4.4
3.5

0.4
0.3
0.0
0.9
0.4
0.0
m
a
a
0.3
0.0
a
0.0
0.0
x(11)
0.2
0.0
0.2d
0.2
0.2
0.0
x(11)
0.0
0.2
0.0
0.0
a
0.0
0.0
0.2
0.0
m
x(11)
0.0
x(11)

1.6
1.5
1.4
1.5
2.1
1.2
m
1.8
1.7
1.2
1.2
1.0
0.9
1.3
x(11)
1.2
0.9
1.2d
1.6
1.3
0.5
x(11)
1.7
1.5
1.7
1.4
1.3d
1.6
1.0
1.1
1.6
m
x(11)
1.8
x(11)

2.0
1.7
1.5
2.4
2.5
1.2
m
1.8
1.7
1.5
1.2
1.0
0.9
1.3
0.8
1.5
0.9
1.4d
1.8
1.5
0.5
1.4
1.7
1.8
1.7
1.4
1.3d
1.6
1.0
1.3
1.6
m
1.7
1.9
2.6

1.4
1.3
1.0
1.8
2.4
0.7
m
1.2
1.0
1.0
0.7
0.6
0.7
x(11)
0.6
0.9
0.6
x(11)
1.5
1.2
0.5
1.1
1.1
1.4
1.0
1.1
0.8d
1.0
0.8
0.9
0.7
m
1.3
1.5
2.3

6.0
4.9
5.7
6.0
6.1
3.8
m
4.7
5.7
5.2
4.2
3.8
3.8
5.8
3.5
6.0
3.9
4.1
5.8
4.9
3.5
5.3
5.4
6.3
6.4
4.6
5.2
4.4
4.3
4.4
5.3
m
4.8
6.2
6.1

5.3
4.4
5.3
x(13)
6.0
3.3
m
4.1
5.0
4.7
3.7
3.5
3.6
x(13)
3.3
5.5
3.6
x(13)
5.4
4.6
3.4
x(13)
4.7
x(13)
5.7
4.3
4.8
3.8
4.1
4.0
4.4
m
4.4
5.8
5.8

OECD average
EU22 average

1.5

0.9

0.6

0.5

1.1

2.0

0.1

3.5

0.2

1.4

1.5

1.1

5.0

4.5

1.3

0.9

0.5

0.6

1.0

2.0

0.1

3.3

0.1

1.3

1.3

0.9

4.6

4.2

m
m
Argentina
1.6
1.4
Brazil
m
m
China
2.1
1.4
Colombia2
m
m
Costa Rica
m
m
India
m
m
Indonesia
0.7
1.1
Lithuania
Russian Federation x(3,4,5,6) x(3,4,5,6)
m
m
Saudi Arabia
m
m
South Africa

m
x(5)
m
x(5)
m
m
m
0.4
1.8d
m
m

m
x(5)
m
x(5)
m
m
m
0.1
0.2d
m
m

m
1.1d
m
0.5d
m
m
m
0.5
1.9d
m
m

m
2.5d
m
2.0d
m
m
m
1.6
1.9d
m
m

m
x(5, 6)
m
x(5, 6)
m
m
m
0.1
x(3, 4, 5, 6)
m
m

m
4.1
m
4.0
m
m
m
2.4
1.9d
m
m

m
x(11)
m
x(11)
m
m
m
a
0.1
m
m

m
x(11)
m
x(11)
m
m
m
1.5
1.0
m
m

m
1.0
m
2.2
m
m
m
1.5
1.1
m
m

m
x(11)
m
x(11)
m
m
m
1.0
1.0
m
m

m
5.0
m
6.2
m
m
m
3.9
3.1
m
m

m
x(13)
m
x(13)
m
m
m
3.4
x(13)
m
m

G20 average

m

m

m

m

m

m

m

m

m

m

m

m

(2)

m

m

OECD

Vocational
programmes

(1)

General
programmes

Lower secondary

Post-secondary
non‑tertiary

Primary

C2

Partners

Tertiary

Upper secondary

Note: See Definitions and Methodology sections for more information. Data and more breakdowns available at http://stats.oecd.org/, Education at a Glance Database.
1. Primary education includes data from pre-primary and lower secondary education.
2. Year of reference 2016.
Source: OECD / UIS / Eurostat (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933804261

266 Education at a Glance 2018: OECD Indicators   © OECD 2018

What proportion of national wealth is spent on educational institutions? – INDICATOR C2

chapter C

Under embargo until 11/09/2018 at 11.00am CEST
Table C2.2. Total expenditure on educational institutions as a percentage of GDP,

by source of funds (2015)

Direct expenditure within educational institutions, by level of education
Primary, secondary and post-secondary
non-tertiary

Tertiary

Primary to tertiary

International

Government

Private

International

Government

Private

International

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

(13)

(14)

(15)

(16)

(17)

(18)

0.0
a
0.0
m
m
0.0
m
0.4
x(1)
0.0
m
0.1
0.0
0.0
0.0
0.0
0.1
0.0
m
0.3
0.1
0.0
0.0
0.0
0.0
0.1
0.1
0.2
0.0
0.0
m
m
0.0
0.0
m

3.2
3.0
4.1
3.2d
3.0
2.4
m
2.7
4.0
3.4
2.6
2.7
2.7
4.4
2.5
4.0
2.8
2.5
3.5
3.3
2.8
3.2
3.2
3.8
4.6
2.9
3.4
2.6
3.0
2.7
3.6
3.2
2.5
3.8
3.2

0.7
0.1
0.1
0.3d
0.6
0.2
m
0.2
0.0
0.3
0.4
0.2
0.2
0.2
0.1
0.5
0.2
0.2
0.5
0.1
0.1
0.7
0.5
0.8
0.0
0.3
0.4
0.3
0.3
0.4
a
m
0.6
0.6
0.3

0.0
a
0.0
m
m
0.0
m
0.0
x(4)
0.0
0.0
0.0
0.0
0.0
a
0.0
0.1
0.0
m
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
a
a
0.0
0.0
a

1.3
1.6
1.3
m
m
0.8
m
1.2
1.6
1.2
m
m
0.6
1.1
0.7
m
0.7
m
m
1.0
0.5
1.0
m
1.3
1.7
1.2
0.7
0.8
0.8
0.9
1.4
1.3
m
1.0
1.0

0.7
0.1
0.1
m
1.2
0.2
m
0.4
0.1
0.3
m
m
0.3
0.1
0.1
m
0.2
m
0.9
0.3
0.0
0.4
m
0.5
0.0
0.1
0.4
0.3
0.1
0.4
0.2
m
m
0.8
1.6

m
a
0.0
m
m
0.2
m
0.1
x(7)
0.0
m
0.3
0.0
0.0
0.0
0.0
0.0
0.0
m
0.2
0.0
0.0
0.1
0.0
0.0
0.1
0.1
0.5
0.1
0.0
0.1
m
0.0
0.1
m

0.8
1.6
1.2
1.2
0.8
0.8
m
1.3
1.6
1.1
1.0
0.7
0.6
1.1
0.6
0.9
0.6
0.4
0.7
1.1
0.5
1.0
1.2
0.9
1.7
1.1
0.7
1.2
0.9
0.8
1.4
1.3
1.2
0.5
0.9

1.3
0.1
0.2
1.2
1.7
0.2
m
0.4
0.1
0.3
0.2
0.1
0.3
0.1
0.2
0.6
0.3
0.9
1.2
0.3
0.0
0.4
0.5
0.9
0.1
0.2
0.4
0.3
0.1
0.4
0.2
m
0.4
1.3
1.7

m
a
0.0
0.0
m
0.2
m
0.1
0.1
0.0
0.0
0.1
0.0
0.0
a
0.0
0.0
0.0
m
0.1
0.0
0.0
0.1
0.0
0.0
0.1
0.1
0.0
0.0
0.0
0.1
a
0.0
0.1
a

4.5
4.7
5.5
m
m
3.2
m
3.5
5.6
4.7
m
m
3.2
5.5
3.2
m
3.4
m
m
3.9
3.3
4.3
m
5.1
6.3
4.1
4.1
3.2
3.8
3.5
5.0
4.5
m
4.9
4.2

1.5
0.2
0.2
m
1.9
0.5
m
0.6
0.1
0.5
m
m
0.5
0.3
0.2
m
0.4
m
1.4
0.4
0.1
1.0
m
1.2
0.0
0.4
0.9
0.5
0.4
0.8
0.2
m
m
1.3
1.9

m
a
0.0
m
m
0.2
m
0.6
x(13)
0.0
m
0.4
0.0
0.0
0.0
0.0
0.1
0.0
m
0.5
0.1
0.0
0.1
0.0
0.0
0.1
0.2
0.7
0.1
0.0
0.1
m
0.0
0.1
m

4.0
4.6
5.4
4.4
3.8
3.2
m
4.0
5.6
4.5
3.6
3.4
3.2
5.5
3.1
4.9
3.3
2.9
4.1
4.3
3.3
4.2
4.3
4.7
6.3
4.0
4.1
3.8
3.8
3.5
5.0
4.5
3.8
4.2
4.1

2.0
0.3
0.3
1.6
2.3
0.5
m
0.6
0.1
0.6
0.6
0.3
0.5
0.3
0.4
1.1
0.5
1.1
1.7
0.4
0.1
1.1
1.0
1.6
0.1
0.5
0.9
0.6
0.5
0.8
0.2
m
1.0
1.9
2.0

m
a
0.0
m
m
0.2
m
0.1
x(16)
0.0
0.0
0.1
0.0
0.0
a
0.0
0.1
0.0
m
0.1
0.1
0.0
0.1
0.0
0.0
0.1
0.2
0.0
0.0
0.0
0.1
a
0.0
0.1
a

OECD average
EU22 average

3.2
3.1

0.3
0.2

0.1
0.1

3.2
3.0

0.3
0.3

0.0
0.0

1.1
1.0

0.4
0.2

0.1
0.1

1.0
1.0

0.5
0.3

0.0
0.1

4.3
4.0

0.7
0.5

0.1
0.2

4.2
4.0

0.8
0.5

0.1
0.1

Argentina
Brazil
China
Colombia2
Costa Rica
India
Indonesia
Lithuania

m
m
m
3.1
m
m
m
2.3

m
m
m
0.9
m
m
m
0.1

m
m
m
0.0
m
m
m
0.1

m
4.1
m
3.1
4.7
m
m
2.3

m
m
m
0.9
m
m
m
0.1

m
m
m
0.0
m
m
m
0.0

m
m
m
m
m
m
m
0.8

m
m
m
m
m
m
m
0.4

m
m
m
0.0
m
m
m
0.3

m
1.0
m
0.8
1.6
m
m
1.1

m
m
m
1.4
m
m
m
0.4

m
m
m
0.0
m
m
m
0.0

m
m
m
m
m
m
m
3.1

m
m
m
m
m
m
m
0.5

m
m
m
0.0
m
m
m
0.4

m
5.0
m
3.9
6.3
m
m
3.4

m
m
m
2.4
m
m
m
0.5

m
m
m
0.0
m
m
m
0.1

Russian Federation

m

m

m

1.8d

0.1d

0.0d

m

m

m

0.7

0.4

0.0

m

m

m

2.6

0.5

0.0

Saudi Arabia

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

South Africa

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

G20 average

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

Government

(2)

0.7
0.1
0.1
m
0.6
0.2
m
0.2
0.0
0.3
m
m
0.2
0.2
0.1
0.4
0.2
m
0.5
0.1
0.1
0.6
m
0.7
0.0
0.3
0.4
0.2
0.3
0.4
a
m
0.6
0.5
0.3

Private

(1)

Government

Private

Final funds (after
transfers between
government and
private sectors)

Government

Initial funds (before
transfers between
government and
private sectors)

International

Final funds (after
transfers between
government and
private sectors)

Private

Initial funds (before
transfers between
government and
private sectors)

3.2
3.0
4.2
m
m
2.4
m
2.3
4.0
3.5
m
m
2.7
4.4
2.5
4.1
2.8
m
m
3.0
2.8
3.2
m
3.9
4.6
2.9
3.4
2.4
2.9
2.7
3.6
3.2
2.5
3.9
3.2

Private

International

Final funds (after
transfers between
government and
private sectors)

Australia
Austria
Belgium
Canada1
Chile2
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United Kingdom
United States3

Government
OECD
Partners

International

Initial funds (before
transfers between
government and
private sectors)

Note: Some levels of education are included with others. Refer to “x” code in Table C2.1 for details. See Definitions and Methodology sections for more information.
Data and more breakdowns available at http://stats.oecd.org/, Education at a Glance Database.
1. Primary education includes data from pre-primary and lower secondary education.
2. Year of reference 2016.
3. The figures for the United States are for net student loans rather than gross, thereby underestimating public transfers.
Source: OECD / UIS / Eurostat (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933804280

Education at a Glance 2018: OECD Indicators   © OECD 2018

267

C2

chapter C Financial Resources Invested In Education
Under embargo until 11/09/2018 at 11.00am CEST
Table C2.3. Change in total expenditure on educational institutions as a percentage of GDP (2005 to 2015)
Index of change (GDP deflator 2010 = 100, constant prices), direct expenditure within educational institutions,
by level of education

Partners

OECD

C2

Primary, secondary, and post-secondary
non-tertiary

Tertiary

Primary to tertiary

Change in expenditure as a share of GDP
(2010 = 100)

Change in expenditure as a share of GDP
(2010 = 100)

Change in expenditure as a share of GDP
(2010 = 100)

2005

2011

2015

2005

2011

2015

2005

2011

2015

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

Australia
Austria
Belgium
Canada1
Chile2
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United Kingdom
United States

86.4
m
94.9
87.6d
106.3
102.4
93.4
90.3
93.4
98.2
98.8
m
m
112.5
72.8
94.3
101.8
96.4
86.8
97.6
m
98.2
93.7
m
100.6
103.5
95.6
93.7
105.6
88.4
105.8
m
m
m
96.4

93.3
m
99.2
95.5d
98.2
100.7
91.2
86.2
98.7
96.7
96.1
m
m
101.1
97.1
105.5
95.5
99.8
98.9
90.1
93.2
99.9
97.7
m
97.3
93.7
95.3
90.6
97.3
98.6
97.6
m
m
m
96.8

87.4
m
99.5
94.0d
93.6
98.1
m
77.7
101.1
95.0
90.3
m
m
97.8
59.6
113.4
101.8
94.4
90.4
99.1
84.7
99.1
95.1
m
95.3
90.2
105.5
95.5
85.5
95.9
96.5
m
m
m
89.9

90.6
m
89.2
88.4
84.2
81.0
90.7
72.7
89.9
88.0
85.5
m
m
103.3
74.7
102.7
88.1
91.4d
m
102.8
m
85.0
89.8
m
m
107.3
91.0d
98.8
101.1
83.2
92.7
m
m
m
90.1

97.2
m
100.5
95.0
104.2
115.3
101.0
105.6
101.1
99.0
100.7
m
m
95.3
95.2
105.5
100.9
103.2d
m
109.2
m
93.0
101.8
m
99.1
88.3
95.5d
107.6
103.5
98.6
99.3
m
m
m
102.0

121.0
m
107.5
93.9
88.9
98.2
m
112.8
93.7
99.7
102.1
m
m
110.0
55.8
95.0
96.3
94.5d
m
110.3
m
104.8
106.6
m
107.1
93.8
92.4d
173.9
83.0
97.9
97.2
m
m
m
95.8

87.5
m
93.5
88.0d
97.4
95.9
92.6
85.1
92.3
95.4
95.3
m
m
110.6
73.3
96.7
98.4
94.7
m
99.1
m
94.8
92.6
m
m
104.6
94.4
94.9
104.5
86.9
101.8
m
m
m
93.8

94.3
m
99.5
95.3d
100.6
105.2
93.9
91.9
99.5
97.3
97.3
m
m
99.9
96.6
105.5
96.8
101.0
m
95.6
m
98.1
98.9
m
97.7
92.1
95.4
94.5
98.8
98.6
98.1
m
m
m
98.9

96.5
m
101.4
93.9d
91.7
98.1
m
87.9
98.7
96.3
93.5
m
m
100.3
58.6
108.2
100.4
94.4
m
102.3
m
100.5
98.5
m
98.2
91.3
101.9
113.7
84.8
96.4
96.7
m
m
m
92.3

OECD average
EU22 average

96.1
95.9

96.5
95.3

93.6
92.4

90.5
89.8

100.7
101.4

101.3
101.3

94.6
94.2

97.7
97.1

95.9
95.0

Argentina
Brazil
China
Colombia2
Costa Rica
India
Indonesia
Lithuania

m
76.1
m
m
m
m
m

m
99.6
m
m
m
m
m

m
96.7
m
m
m
m
m

m
87.4
m
m
m
m
m

m
108.8
m
m
m
m
m

m
112.0
m
m
m
m
m

m
78.0
m
m
m
m
m

m
101.1
m
m
m
m
m

m
99.3
m
m
m
m
m

m

88.9

72.5

82.5

112.0

92.3

m

96.4

78.9

Russian Federation

91.5

99.6

101.7

51.0

89.3

79.4

74.1

95.2

92.1

Saudi Arabia

m

m

m

m

m

m

m

m

m

South Africa

m

m

m

m

m

m

m

m

m

G20 average

m

m

m

m

m

m

m

m

m

Note: Some levels of education are included with others. Refer to “x” code in Table C2.1 for details. See Definitions and Methodology sections for more information.
Data and more breakdowns available at http://stats.oecd.org/, Education at a Glance Database.
1. Primary education includes data from pre-primary and lower secondary education.
2. Year of reference 2016.
Source: OECD / UIS / Eurostat (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933804299

268 Education at a Glance 2018: OECD Indicators   © OECD 2018

Under embargo until 11/09/2018 at 11.00am CEST

Under embargo until 11/09/2018 at 11.00am CEST

HOW MUCH PUBLIC AND PRIVATE INVESTMENT
ON EDUCATIONAL INSTITUTIONS IS THERE?
• On average, across OECD countries, educational institutions are mainly publicly funded, with

INDICATOR C3

government funds accounting for 90% at primary, secondary and post-secondary non-tertiary and
66% for tertiary education.

• The share of private investment on tertiary educational institutions varies significantly across
countries, mainly as a function of the tuition fees charged by tertiary institutions. Countries such
as Colombia, Chile, Japan, the United Kingdom and the United States account for the largest shares
(around 70%).

• Public transfers to the private sector play an important role in the financing of tertiary education
representing 5% of total funds across OECD countries. Australia, New Zealand and the United Kingdom
are the countries with the highest public-to-private transfers (between 20% and 35% of the total funds
devoted to tertiary educational institutions).

Figure C3.1. Distribution of transfers and public and private expenditure
on educational institutions (2015)
Tertiary educational levels

Portugal

Iceland

Hungary

Estonia

Czech Republic

Austria

Lithuania

Sweden

Latvia

Slovenia

Luxembourg

Slovak Republic

Mexico

Spain

Norway

France

Belgium

EU22 average

OECD average

Poland

Italy

Ireland

Australia

New Zealand

United Kingdom

%

100
90
80
70
60
50
40
30
20
10
0

United States

Private expenditure
Public to private transfers
Public expenditure

Note: International expenditure is aggregated with public expenditure for display purposes.
1. Net student loans rather than gross, thereby underestimating public transfers.
Countries and economies are ranked in descending order of the proportion of public-to-private transfers.
Source: OECD / UIS / Eurostat (2018), Table C3.2. See Source section for more information and Annex 3 for notes (http://dx.doi.
org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933804451

Context
Today, more people than ever before are participating in a wide range of educational programmes
offered by an increasing number of providers. As a result, increasingly more importance is accorded
to the question of whether governments or the individuals themselves should support these efforts
to acquire more education. In the current economic environment, many governments are finding it
difficult to provide the necessary resources to support this increased demand for education through
public funds alone. In addition, some policy makers assert that those who benefit the most from
education, the individuals who receive it, should bear at least some of the costs. While public funding
still represents a large part of countries’ investment in education, the role of private sources of funding
is becoming increasingly prominent at some educational levels.
Public sources dominate much of the funding of non-tertiary levels, which are usually compulsory in
most countries. Across OECD countries, the balance between public and private financing varies at
pre-primary (see Indicator B2) and tertiary levels of education, as full or nearly full public funding is

270 Education at a Glance 2018: OECD Indicators   © OECD 2018

Under embargo until 11/09/2018 at 11.00am CEST
less common. At these levels, private funding comes mainly from households, raising concerns about
equity in access to education. The debate is particularly intense over funding for tertiary education.
Some stakeholders are concerned that the balance between public and private funding should not
discourage potential students from entering tertiary education. Others believe that countries should
significantly increase public support to students, while still others support efforts to increase the
amount of funding to tertiary education provided by private enterprises.
This indicator examines the proportion of public, private and international funding allocated to
educational institutions at different levels of education. It also breaks down private funding by
households and expenditures by private entities other than households. It sheds some light on the
widely debated issue of how the financing of educational institutions should be shared between public
and private entities, particularly at the tertiary level. Finally, it looks at the relative share of public
transfers provided to private institutions and individual students and their families to meet the costs
of tertiary education.

INDICATOR C3

Other findings

• Households account for the largest share of private expenditure devoted to tertiary educational
institutions (70% on average across OECD countries).

• Between 2010 and 2015, the share of private sources of expenditure on educational institutions
from primary to tertiary increased by 11%, while the share of public sources decreased by 1%,
on average across OECD countries.

• The share of private expenditure on educational institutions varies across non-tertiary education
levels. At the primary and secondary levels, around 8% of expenditure on educational institutions
comes from private sources. This share reaches 13% at upper secondary education.

Education at a Glance 2018: OECD Indicators   © OECD 2018

271

chapter C Financial Resources Invested In Education
Under embargo until 11/09/2018 at 11.00am CEST

Analysis

C3

Public versus private expenditure on educational institutions
Educational institutions in OECD countries are mainly publicly funded, although private funding at the tertiary
level is substantial. Within this overall average, however the share of public, private and international funding varies
widely among countries.
On average across OECD countries, 83% of all funds for primary to tertiary educational institutions come directly
from public sources (Table C3.1). In OECD countries, private funding on educational institutions represents on
average 16% of all expenditure. Around half of the countries with data available report a share of private funding
above the OECD average. In Finland, Luxembourg, Norway and Sweden, private funds constitute 3% or less of all
educational expenditure. In contrast, private funds constitute around one-third of all educational expenditure in
Australia, Chile, Colombia, Korea, the United Kingdom and the United States. International sources represent on
average 1% of the expenditure on educational institutions, reaching around 4% in the Czech Republic, Greece and
Portugal. In around 30% of all OECD and partner countries with data available, international sources exceed the
OECD average,

Public versus private expenditure on non-tertiary educational institutions
Public funding dominates non-tertiary education in all countries. Around 9% of funding for these levels of education
comes from private sources, and the share of private funding exceeds 20% in Colombia (Table C3.1 and Figure C3.2).
In most countries, the largest share of private expenditure at these levels comes from households and goes mainly
towards tuition fees.
The share of private expenditure on educational institutions varies across countries and according to the level of
education (OECD, 2018[1]). At the primary level, on average, 7% of expenditure on educational institutions comes
from private sources. In Finland, Norway and Sweden, all educational funding for this level is public, while in
Chile (17%) and Colombia (24%) a large share of funding comes from private sources – the highest of all countries
for which data are available (OECD, 2018[1]).
At the lower secondary level, private funding corresponds to 8% of total educational expenditure on average. In 23 of
the 32 OECD countries for which data are available, public expenditure accounts for over 90% of the total. However,
Australia and Colombia source just over 20% of expenditure from private sources at this level (OECD, 2018[1]).
Upper secondary education relies more on private funding than the primary and lower secondary levels, reaching
an average of 13% across OECD countries. Private sources play a slightly stronger role in vocational programmes
(contributing 14% of expenditure) than in general programmes (12%). In Germany, the Netherlands and New Zealand,
vocational upper secondary education receives at least 25 percentage points more private funding than general
education tracks. On the other hand, in Chile, Turkey and the United Kingdom the share of private funding in general
programmes exceeds that of vocational programmes by 15 or more percentage points (OECD, 2018[1]).
The level of public funding in post-secondary non-tertiary education stands at only 75% on average. Unlike the
three lower levels presented above, in post-secondary non-tertiary education, Israel, New Zealand, Poland and
the United States rely more on private than public sources of funding (OECD, 2018[1]).

Public versus private expenditure on tertiary educational institutions
The high private returns to tertiary education (see Indicator A5) have led a number of countries to expect a higher
financial contribution from the private sector to finance tertiary education, provided that financial support
mechanisms are in place to support students from various economic backgrounds (see Indicator C5). In all countries,
the proportion of private expenditure on education is far higher for tertiary education (an average of nearly 31% of
total expenditure at this level) than it is at lower levels of education (Table C3.1 and Figure C3.2).
The proportion of expenditure on tertiary institutions covered by individuals, businesses and other private sources
(including subsidised private payments such as tuition fee loans) ranges from less than 10% in Austria, Finland,
Iceland, Luxembourg and Norway (where tuition fees charged by tertiary institutions are low or negligible) to around
70% in Chile, Japan, the United Kingdom and the United States. The share of private funding is related to the level
of tuition fees charged by tertiary institutions (Figure C3.2 and Table C3.1, and see Indicator C5). On average across
OECD countries, household expenditure accounts for 70% of private expenditure. While household expenditure
is the biggest source of private funds in the majority of OECD countries, almost all private funding comes from
other private entities (mainly for research and development) in Finland and Sweden, and the share of household
expenditure is either zero or very low (Figure C3.2).

272 Education at a Glance 2018: OECD Indicators   © OECD 2018

How much public and private investment on educational institutions is there? – INDICATOR C3

chapter C

Under embargo until 11/09/2018 at 11.00am CEST

Figure C3.2. Distribution of public and private expenditure on educational institutions (2015)
Final source of funds, by level of education
Public expenditure
Household expenditure
Expenditure from other private entities
All private sources

Sweden
Norway
Finland1
Latvia
Luxembourg
Belgium
Iceland
Lithuania
Austria
Russian Federation
Italy
Ireland
Greece
Estonia
Hungary
EU22 average
Japan
Czech Republic
Poland
United States
OECD average
France
Canada1, 2
Slovenia
Israel
Slovak Republic
Portugal
Netherlands
Korea1
Germany
United Kingdom
Spain
Chile1, 3
New Zealand
Mexico
Australia
Turkey
Colombia3
Japan

United Kingdom

Chile1, 3

United States

Colombia3

Korea1

Australia1

Canada1

Israel

New Zealand

Italy

Hungary

Spain

Russian Federation

Portugal

Netherlands

OECD average

Ireland

Mexico

Turkey

Latvia

Estonia

France

EU22 average

Czech Republic

Poland

Slovak Republic

Belgium

Germany

Greece

Slovenia

Iceland

Sweden

Austria

Norway

Luxembourg

Finland1

Lithuania

Tertiary

%

100
90
80
70
60
50
40
30
20
10
0

C3

Primary, secondary and post-secondary non-tertiary

%

100
90
80
70
60
50
40
30
20
10
0

1. Excluding international sources.
2. Primary education includes data from pre-primary and lower secondary education.
3. Year of reference 2016.
Note: International expenditure is aggregated with public expenditure for display purposes.
Countries are ranked in descending order of the proportion of public and international expenditure on educational institutions.
Source: OECD / UIS / Eurostat (2018), Table C3.1. See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag2018-36-en).
1 2 https://doi.org/10.1787/888933804470

Changes in the share of public and private expenditure on educational institutions
Educational institutions from primary to tertiary education are still predominantly publicly funded, although there
is a substantial and growing degree of private funding devoted to cover expenses from educational institutions
(Table C3.3). Between 2010 and 2015, the share of private spending on primary to tertiary educational institutions
increased by 11% on average across OECD countries, while the share of public sources decreased by about 1%.
Increases in the share of private funding were observed in 62% of countries, with Estonia (77%) and Spain (56%)
showing the largest increases. On the contrary, Chile and Latvia experienced the largest decreases in the share of
private spending supported by increases from the public sector.
In many OECD countries, greater student enrolment in non-tertiary education (see Indicator B1) reflects strong
individual and social demand. Increases in enrolment have been accompanied by increased investment mainly from
private sources and changes in the proportions of public and private expenditure. The increase in the share of funding
from private sources between 2010 and 2015 was stronger (30%) than for public sources (5%). These figures, however,
Education at a Glance 2018: OECD Indicators   © OECD 2018

273

chapter C Financial Resources Invested In Education
Under embargo until 11/09/2018 at 11.00am CEST
are strongly influenced by outliers like Estonia, Israel and Spain, where the share of private funding for non-tertiary
education increased by more than 50% between 2010 and 2015. Also large increases were observed during the same
period in the share of public funds, notably in Turkey and the United Kingdom (between 25% and 50%).

Figure C3.3. Change in relative share of public and private expenditure
on tertiary educational institutions (between 2010 and 2015)
Final source of funds, 2010 = 100
Public sources

Index of change

Private sources

160
140
120
100
80

Poland

Latvia

Slovak Republic

Chile

Lithuania

Finland

Slovenia

Israel2

Iceland

Russian Federation

Mexico

Czech Republic

Estonia

EU22 average

Norway

Portugal

OECD average

Japan

Netherlands

Italy

United States

France

Germany

Australia

Canada1

Sweden

40

Spain

60

Ireland

C3

Although the share of public funding on tertiary institutions increased in some countries, others have fallen behind
their 2010 levels. However, these reductions have been compensated by an increase of the private funding. This is
the case for example for Australia, Canada and Spain, where the share of public funds decreased by 10 to 20%
in 2015 compared to 2010 but the share of private funds increased by 15% to 50% (Table C3.3 and Figure C3.3).

1. Primary education includes pre-primary programmes.
2. Private expenditure on government-dependent private institutions is included under public institutions.
Countries are ranked in descending order of the change in the share of private expenditure on tertiary educational institutions between 2010 and 2015.
Source: OECD / UIS / Eurostat (2018), Education at a Glance Database, http://stats.oecd.org/. See Source section for more information and Annex 3
for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933804489

Public transfers to the private sector
The financial resources devoted to covering expenses from educational institutions combine contributions from
governments, international institutions, private institutions and individual students and their families. A large
share of government spending goes directly to educational institutions, but governments also transfer funds to
educational institutions through various other allocation mechanisms (through tuition subsidies or direct public
funding of institutions based on student enrolments or credit hours) or by subsidising students, households and
other private entities (through scholarships, grants or loans attributable for tuition fees to educational institutions).
Governments use transfers to provide institutions with incentives to organise their educational programmes and
teaching to better meet student requirements, as well as to increase access to education and reduce social inequalities.
Channelling funding for institutions through students helps increase competition among institutions and results
in greater efficiency in the funding of education. Since aid for student living costs can also serve as a substitute for
labour income, public transfers may enhance educational attainment by enabling students to study full time.
Public transfers to the private sector play an important role in the financing of tertiary education (Table C3.2 and
Figure C3.1). In countries where tertiary education is expanding, and particularly in those in which students are charged
tuition fees, public-to-private transfers of funds are often seen as a means to expand access for lower-income students.
However, there is no single allocation model across OECD countries (OECD, 2017[2]). Despite the considerable impact
of public transfers on reducing the financial burden of access to tertiary education, government and international

274 Education at a Glance 2018: OECD Indicators   © OECD 2018

How much public and private investment on educational institutions is there? – INDICATOR C3

chapter C

Under embargo until 11/09/2018 at 11.00am CEST
support seems to cover only a relatively small share of the private costs of tertiary education in some countries while
in other countries private spending is largely covered by public transfers. This creates challenges for access and learning
as higher private spending could deter students from participating in tertiary education.
On average across OECD countries, 5% of the total funds are transfers from the public sector to the private sector
to cover expenditures on tertiary educational institutions. In 2015, in 3 of the 24 countries with available data,
between 20% and 30% of the total funds devoted to tertiary educational institutions were transferred to households
or private entities from the government or international sources. Conversely, public transfers were below 1% in
countries such as Austria, the Czech Republic, Estonia, Hungary, Iceland and Portugal. Those countries with the
highest transfers are also those with the highest tuition fees. However, some countries have high private spending
without a large support from the government (OECD, 2017[2]).

Definitions
Initial public, private and international shares of educational expenditure are the percentages of total education
spending originating in, or generated by, the public, private and international sectors before the flow of transfers.
Initial public spending includes both direct public expenditure for educational institutions and transfers to the
private sector and excludes transfers from the international sector. Initial private spending includes tuition fees
and other student or household payments to educational institutions, minus the portion of such payments offset
by public subsidies. Initial international spending includes both direct international expenditure for educational
institutions (for example a research grant from a foreign corporation to a public university) and international transfers
to governments.
Final public, private and international shares are the percentages of educational funds expended directly by public,
private and international purchasers of educational services after the flow of transfers. Final public spending
includes direct public purchases of educational resources and payments to educational institutions. Final private
spending includes all direct expenditure on educational institutions (tuition fees and other private payments
to educational institutions), whether partially covered by public subsidies or not. Private spending also includes
expenditure by private companies on the work-based element of school- and work-based training of apprentices and
students. Final international spending includes direct international payments to educational instructions such as
research grants or other funds from international sources paid directly to educational institutions.
Households refer to students and their families.
Other private entities include private businesses and non-profit organisations (e.g. religious organisations,
charitable organisations, and business and labour associations).
Public subsidies include public and international transfers such as scholarships and other financial aid to students
plus certain subsidies to other private entities.

Methodology
Data appearing in earlier editions of this publication may not always be comparable to data shown in the 2018
edition due to changes in definitions and coverage.
All entities that provide funds for education, either initially or as final payers, are classified as either governmental
(public) sources, non-governmental (private) sources or international sources such as international agencies and
other foreign sources. Figures presented here grouped together public and international expenditures for display
purposes. As the share of international expenditures is relatively small compared to other sources, its integration
into the public sources does not impact the analysis of the share of public spending.
Not all spending on instructional goods and services occurs within educational institutions. For example, families
may purchase commercial textbooks and materials or seek private tutoring for their children outside educational
institutions. At the tertiary level, students’ living expenses and foregone earnings can also account for a significant
proportion of the costs of education. All expenditure outside educational institutions, even if publicly subsidised,
is excluded from this indicator. Public subsidies for educational expenditure outside institutions are discussed in
Indicators C4 and C5.
A portion of the budgets of educational institutions is related to ancillary services offered to students, including
student welfare services (student meals, housing and transport). Part of the cost of these services is covered by fees
collected from students and is included in the indicator.
Education at a Glance 2018: OECD Indicators   © OECD 2018

275

C3

chapter C Financial Resources Invested In Education
Under embargo until 11/09/2018 at 11.00am CEST
Expenditure on educational institutions is calculated on a cash-accounting basis and, as such, represents a snapshot
of expenditure in the reference year. Many countries operate a loan payment/repayment system at the tertiary level.
While public loan payments are taken into account, loan repayments from private individuals are not, and so the
private contribution to education costs may be under-represented.

C3

It should be noted that student loans provided by private financial institutions (rather than directly by a government)
are counted as private expenditure, although any interest rate subsidies or government payments on account of loan
defaults are captured as under public funding.
For more information please see the OECD Handbook for Internationally Comparative Education Statistics 2018 (OECD,
2018[3]) and Annex 3 for country-specific notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Lithuania was not an OECD member at the time of preparation of this publication. Accordingly, Lithuania does not
appear in the list of OECD members and is not included in the zone aggregates.

Source
Data refer to the financial year 2015 (unless otherwise specified) and are based on the UNESCO, OECD and Eurostat
(UOE) data collection on education statistics administered by the OECD in 2017 (for details see Annex 3 at http://
dx.doi.org/10.1787/eag-2018-36-en). Data from Argentina, China, Colombia, India, Indonesia, Saudi Arabia and
South Africa are from the UNESCO Institute of Statistics (UIS).
The data on expenditure for 2005, 2011 to 2015 were updated based on a survey in 2017-18, and expenditures
for 2005 to 2014 were adjusted to the methods and definitions used in the current UOE data collection.

Note regarding data from Israel
The statistical data for Israel are supplied by and are under the responsibility of the relevant Israeli authorities. The use
of such data by the OECD is without prejudice to the status of the Golan Heights, East Jerusalem and Israeli settlements
in the West Bank under the terms of international law.

References
OECD (2018), Education at a Glance Database, https://stats.oecd.org/ (accessed on 06 July 2018).

[1]

OECD (2018), OECD Handbook for Internationally Comparative Education Statistics 2018: Concepts, Standards, Definitions [3]
and Classifications, OECD Publishing, Paris, https://doi.org/10.1787/9789264304444-en.
OECD (2017), “Who really bears the cost of education? : How the burden of education expenditure shifts from the public to [2]
the private sector”, Education Indicators in Focus, No. 56, OECD Publishing, Paris, http://dx.doi.org/10.1787/4c4f545b-en.

Indicator C3 Tables
1 2 https://doi.org/10.1787/888933804375

Table C3.1 Relative proportions of disaggregated public, private and international expenditure on educational institutions
(2015)
Table C3.2 Distribution of public, private and international sources of funds for educational institutions before and
after transfers (2015)
Table C3.3 Trends in the relative proportion of public expenditure on educational institutions and index of change in the
relative share of public, private and international expenditure from primary to tertiary levels (2005 to 2015)
Cut-off date for the data: 18 July 2018. Any updates on data can be found on line at http://dx.doi.org/10.1787/eag-data-en. More breakdowns can
also be found at http://stats.oecd.org/, Education at a Glance Database.

276 Education at a Glance 2018: OECD Indicators   © OECD 2018

How much public and private investment on educational institutions is there? – INDICATOR C3

chapter C

Under embargo until 11/09/2018 at 11.00am CEST
Table C3.1. Relative proportions of disaggregated public, private and international expenditure

on educational institutions (2015)

Expenditure
by other private
entities

All private
sources

International sources

Public sources

Household
expenditure

Expenditure
by other private
entities

All private
sources

International sources

Household
expenditure

Private sources

Public sources

Private sources

International sources

Private sources

All private
sources

Primary to tertiary

Expenditure
by other private
entities

Tertiary

Household
expenditure

Primary, secondary and post-secondary
non-tertiary

Public sources
Partners

OECD

Distribution of public, private and international sources of funds for educational institutions
after tranfers from public sources (final source of funds), by level of education

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

(13)

(14)

(15)

Australia
Austria
Belgium
Canada1, 2
Chile1, 3
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea1
Latvia
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United Kingdom
United States

81
95
97
90d
83
92
m
93
99
91
87
93
93
96
95
90
92
92
87
97
95
83
87
83
99
91
86
89
90
86
100
m
81
87
91

17
3
3
4d
16
7
m
6
1
8
x(4)
7
x(4)
3
5
7
5
5
12
2
2
17
5
12
1
8
11
6
9
13
a
m
14
11
9

2
1
0
5d
1
2
m
1
0
1
x(4)
0
x(4)
0
a
3
0
2
1
0
0
0
8
5
0
0
0
5
0
1
a
m
5
3
0

19
5
3
10d
17
8
m
7
1
9
13
7
7
4
5
10
5
8
13
2
3
17
12
17
1
8
11
11
10
14
a
m
19
13
9

0
a
0
m
m
0
m
0
x(1)
0
0
0
0
0
a
0
2
0
a
1
3
0
0
0
0
1
3
0
0
0
a
m
0
0
a

38
94
83
49
32
65
m
71
93
78
83
73
63
89
74
58
62
32d
36
73
92
71
68
52
96
79
58d
79
83
66
85
m
75
25
35

50
3
9
28
57
8
m
6
0
11
x(9)
x(10)
x(10)
8
22
26
28
52d
45
21
2
29
16
34
4
14
26d
10
11
29
1
m
12
48
46

12
3
6
22
10
12
m
17
3
10
x(9)
x(10)
x(10)
1
5
16
7
16d
18
1
2
0
13
15
0
2
6d
9
2
3
10
m
12
23
18

62
6
14
51
68
20
m
24
3
20
15
12
37
8
26
42
35
68d
64
23
4
29
29
48
4
16
32d
20
13
32
11
m
25
71
65

x(6)
a
3
0
m
15
m
5
4
2
2
15
0
2
a
0
3
0d
a
5
3
0
3
0
0
5
10d
1
4
2
4
m
0
4
a

66
95
93
74d
63
84
m
85
98
87
86
88
86
95
90
82
85
72
71
90
94
80
81
74
99
87
79
85
88
81
95
m
79
68
68

28
3
5
14d
33
7
m
6
1
9
x(14)
x(14)
x(14)
4
9
12
11
21
22
8
2
20
8
18
1
10
15
8
10
17
0
m
13
22
25

6
2
2
12d
4
5
m
7
1
4
x(14)
x(14)
x(14)
0
1
6
2
7
7
0
0
0
10
8
0
1
1
6
1
2
3
m
8
9
8

34
5
6
26d
37
12
m
13
2
12
14
8
14
5
10
18
12
28
29
9
3
20
18
26
1
11
16
14
10
19
3
m
21
31
32

x(11)
a
1
m
m
4
m
2
x(11)
1
1
4
0
1
a
0
2
0
a
2
3
0
1
0
0
2
4
1
1
1
1
m
0
1
a

OECD average
EU22 average

90
92

8
6

2
1

9
8

0
1

66
73

22
15

9
8

31
22

3
5

83
87

12
8

4
3

16
11

1
2

Argentina
Brazil
China
Colombia3
Costa Rica
India
Indonesia
Lithuania
Russian Federation
Saudi Arabia
South Africa

m
m
m
77
m
m
m
95
95
m
m

m
m
m
23
m
m
m
3
4
m
m

m
m
m
0
m
m
m
2
1
m
m

m
m
m
23
m
m
m
5
5
m
m

m
m
m
0
m
m
m
1
0
m
m

m
m
m
36
m
m
m
72
64
m
m

m
m
m
64
m
m
m
18
23
m
m

m
m
m
0
m
m
m
7
12
m
m

m
m
m
64
m
m
m
25
35
m
m

m
m
m
0
m
m
m
3
1
m
m

m
m
m
62
m
m
m
86
83
m
m

m
m
m
38
m
m
m
8
11
m
m

m
m
m
0
m
m
m
4
5
m
m

m
m
m
38
m
m
m
12
16
m
m

m
m
m
0
m
m
m
2
0
m
m

G20 average

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

Note: Some levels of education are included with others. Refer to “x” code in Table C1.1 for details. Private expenditure figures include tuition fee loans and scholarships
(subsidies attributable to payments to educational institutions received from public sources). Loan repayments from private individuals are not taken into account, and
so the private contribution to education costs may be under-represented. Public expenditure figures presented here exclude undistributed programmes. See Definitions
and Methodology sections for more information. Data and more breakdowns available at http://stats.oecd.org/, Education at a Glance Database.
1. Excluding international sources.
2. Primary education includes data from pre-primary and lower secondary education.
3. Year of reference 2016.
Source: OECD / UIS / Eurostat (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933804394

Education at a Glance 2018: OECD Indicators   © OECD 2018

277

C3

chapter C Financial Resources Invested In Education
Under embargo until 11/09/2018 at 11.00am CEST
Table C3.2. Distribution of public, private and international sources of funds for educational institutions

before and after transfers (2015)

By level of education and source of funding

C3

Tertiary

Primary to tertary

International

Public

Private

International

Public

Private

International

Public

Private

International

Public

Private

Final funds
(after transfers
between public and
private sectors)

Private

Initial funds
(before transfers
between public and
private sectors)

Public

Final funds
(after transfers
between public and
private sectors)

International

Initial funds
(before transfers
between public and
private sectors)

Private

Final funds
(after transfers
between public and
private sectors)

Public
Partners

OECD

Initial funds
(before transfers
between public and
private sectors)

International

Primary, secondary and post-secondary
non-tertiary

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

(13)

(14)

(15)

(16)

(17)

(18)

Australia
Austria
Belgium
Canada1
Chile2
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United Kingdom
United States3

81
97
98
m
m
92
m
78
m
93
m
m
m
96
95
m
92
m
m
89
95
84
m
85
100
90
86
85
90
86
100
m
m
89
91

19
3
2
m
m
8
m
7
m
7
m
m
m
4
5
m
5
m
m
2
3
16
m
15
0
8
11
8
10
14
a
m
m
11
9

0
a
0
m
m
0
m
15
x(1)
0
m
m
m
0
a
m
2
m
m
8
3
0
m
0
0
2
3
7
1
0
a
m
m
0
a

81
95
97
90d
83
92
m
93
99
91
87
93
93
96
95
90
92
92
87
97
95
83
87
83
99
91
86
89
90
86
100
m
81
87
91

19
5
3
10d
17
8
m
7
1
9
13
7
7
4
5
10
5
8
13
2
3
17
12
17
1
8
11
11
10
14
a
m
19
13
9

0
a
0
m
m
0
m
0
x(4)
0
0
0
0
0
a
0
2
0
a
1
3
0
0
0
0
1
3
0
0
0
a
m
0
0
a

63
94
87
m
m
65
m
69
m
81
m
m
63
89
90
m
72
m
m
63
93
73
m
72
99
88
57d
48
78
69
85
m
m
52
38

37
6
10
m
m
20
m
24
m
18
m
m
37
8
7
m
25
m
m
22
4
27
m
28
1
7
32d
18
13
29
1
m
m
44
62

x(7)
a
3
m
m
15
m
7
x(7)
2
m
m
0
2
4
m
3
m
m
15
3
0
m
0
0
5
11d
34
9
2
4
m
m
4
a

38
94
83
49
32
65
m
71
93
78
83
73
63
89
74
58
62
32d
36
73
92
71
68
52
96
79
58d
79
83
66
95
m
75
25
35

62
6
14
51
68
20
m
24
3
20
15
12
37
8
26
42
35
68d
64
23
4
29
29
48
4
16
32d
20
13
32
3
m
25
71
65

x(10)
a
3
0
m
15
m
5
4
2
2
15
0
2
a
0
3
0d
a
5
3
0
3
0
0
5
10d
1
4
2
1
m
0
4
a

75
96
95
m
m
84
m
75
m
90
m
m
86
95
93
m
88
m
m
81
95
81
m
81
100
89
79
72
87
81
95
m
m
78
69

25
4
4
m
m
12
m
13
m
10
m
m
14
5
6
m
10
m
m
8
3
19
m
19
0
8
16
11
10
18
3
m
m
21
31

x(13)
a
1
m
m
4
m
12
x(13)
1
m
m
0
1
1
m
2
m
m
10
3
0
m
0
0
3
5
17
3
1
1
m
m
1
a

66
95
93
74
63
84
m
85
98
87
86
88
86
95
90
82
85
72
71
90
94
80
81
74
99
87
79
85
88
81
95
m
79
68
68

34
5
6
26
37
12
m
13
2
12
14
8
14
5
10
18
12
28
29
9
3
20
18
26
1
11
16
14
10
19
3
m
21
31
32

x(16)
a
1
m
m
4
m
2
x(16)
1
1
4
0
1
a
0
2
0
a
2
3
0
1
0
0
2
4
1
1
1
1
m
0
1
a

OECD average
EU22 average

91
91

8
7

2
3

90
92

9
8

0
1

73
74

21
19

6
8

66
73

31
22

3
5

85
86

12
10

3
4

83
87

16
11

1
2

Argentina
Brazil
China
Colombia
Costa Rica
India
Indonesia
Lithuania
Russian Federation
Saudi Arabia
South Africa

m
m
m
77
m
m
m
93
m
m
m

m
m
m
23
m
m
m
4
m
m
m

m
m
m
0
m
m
m
3
m
m
m

m
m
m
77
m
m
m
95
95
m
m

m
m
m
23
m
m
m
5
5
m
m

m
m
m
0
m
m
m
1
0
m
m

m
m
m
m
m
m
m
52
m
m
m

m
m
m
m
m
m
m
25
m
m
m

m
m
m
m
m
m
m
23
m
m
m

m
m
m
36
m
m
m
72
64
m
m

m
m
m
64
m
m
m
25
35
m
m

m
m
m
0
m
m
m
3
1
m
m

m
m
m
m
m
m
m
78
m
m
m

m
m
m
m
m
m
m
12
m
m
m

m
m
m
m
m
m
m
10
m
m
m

m
m
m
62
m
m
m
86
83
m
m

m
m
m
38
m
m
m
12
16
m
m

m
m
m
0
m
m
m
2
0
m
m

G20 average

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

Note: Some levels of education are included with others. Refer to “x” code in Table C1.1 for details. See Definitions and Methodology sections for more information.
Data and more breakdowns available at http://stats.oecd.org/, Education at a Glance Database.
1. Primary education includes data from pre-primary and lower secondary education.
2. Year of reference 2016.
3. The figures for the United States are for net student loans rather than gross, thereby underestimating public transfers.
Source: OECD / UIS / Eurostat (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933804413

278 Education at a Glance 2018: OECD Indicators   © OECD 2018

chapter C

How much public and private investment on educational institutions is there? – INDICATOR C3

Under embargo until 11/09/2018 at 11.00am CEST
Table C3.3. Trends in the relative proportion of public expenditure on educational institutions

and index of change in relative share of public, private and international expenditure
from primary to tertiary levels (2005 to 2015)

Index of change of public, private and international sources of funds for educational institutions (final source of funds), by year
Primary to tertiary
Index of change in relative share of expenditure on educational institutions (2010 = 100)

Partners

OECD

Share of public expenditure
on educational institutions (%)

Public sources

Private sources

International sources

2005

2011

2015

2005

2011

2015

2005

2011

2015

2005

2011

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

2015
(12)

Australia
Austria
Belgium
Canada1
Chile
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel2
Italy
Japan
Korea
Latvia
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United Kingdom
United States

73
m
93
75d
50
88
98
92
98
89
86
94
91
95
94
82
91
72
m

73
m
94
76d
55
88
96
93
98
88
87
m
m
95
92
78
89
73
m

66
95
93
74d
63
84
m
85
98
87
86
88
86
95
90
82
85
72
71

98
m
99
99d
90
101
101
99
100
101
99
m
m
100
101
100
102
98
m

98
m
100
100d
98
100
100
101
100
99
100
m
m
100
100
96
99
99
m

89
m
99
96d
115
96
m
92
100
99
99
m
m
99
97
100
95
98
m

106
m
m
104d
113
97
78
109
97
94
106
m
m
101
83
98
85
106
m

105
m
m
101d
103
97
115
90
100
104
99
m
m
100
103
119
109
102
m

131
m
m
112d
81
94
m
177
89
110
105
m
m
99
134
99
122
104
m

x(4)
m
89
m
m
m
m
m
m
72
66
m
m
m
m
m
m
m
m

x(5)
m
120
m
m
m
m
m
m
117
89
m
m
m
m
m
m
m
m

x(6)
m
121
m
m
m
m
m
m
143
111
m
m
m
m
m
m
m
m

83

84

90

99

101

108

126

110

72

44

52

39

m
80
83
m
m
91
m
84
88
89
96
m
m
m
72

m
79
81
m
99
89
m
86
90
87
96
m
82
m
69

94
80
81
74
99
87
79
85
88
81
95
m
79
68
68

m
100
101
m
m
104
m
100
98
101
100
m
m
m
102

m
99
99
m
100
102
m
102
100
99
100
m
m
m
98

m
100
99
m
100
100
m
102
99
92
99
m
m
m
95

m
99
97
m
m
72
m
99
114
89
115
m
m
m
96

m
103
103
m
104
89
m
90
101
106
112
m
m
m
105

m
98
103
m
147
86
m
87
102
156
124
m
m
m
112

m
m
62
m
m
m
m
m
m
m
80
m
m
m
a

m
m
105
m
m
m
m
m
m
m
103
m
m
m
a

m
m
138
m
m
m
m
m
m
m
101
m
m
m
a

OECD average
EU22 average

86
90

85
90

83
87

100
100

100
100

99
98

99
97

103
102

111
111

m
m

m
m

m
m

Argentina
Brazil
China
Colombia
Costa Rica
India
Indonesia
Lithuania

m
m
m
m
m
m
m

m
m
m
m
m
m
m

m
m
m
64
m
m
m

m
m
m
m
m
m
m

m
m
m
m
m
m
m

m
m
m
m
m
m
m

m
m
m
m
m
m
m

m
m
m
m
m
m
m

m
m
m
m
m
m
m

m
m
m
m
m
m
m

m
m
m
m
m
m
m

m
m
m
m
m
m
m

m

87

86

m

100

99

m

99

107

m

104

127

Russian Federation
Saudi Arabia
South Africa

m

83

83

m

101

102

m

97

89

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

G20 average

m

m

m

m

m

m

m

m

m

m

m

m

Note: Some levels of education are included with others. Refer to “x” code in Table C1.1 for details. Private expenditure figures include tuition fee loans and scholarships
(subsidies attributable to payments to educational institutions received from public sources). Loan repayments from private individuals are not taken into account, and
so the private contribution to education costs may be under-represented. Public expenditure figures presented here exclude undistributed programmes. See Definitions
and Methodology sections for more information. Data and more breakdowns available at http://stats.oecd.org/, Education at a Glance Database.
1. Primary education includes pre-primary programmes.
2. Private expenditure on government-dependent private institutions is included under public institutions.
Source: OECD / UIS / Eurostat (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933804432

Education at a Glance 2018: OECD Indicators   © OECD 2018

279

C3

Under embargo until 11/09/2018 at 11.00am CEST

WHAT IS THE TOTAL PUBLIC SPENDING ON EDUCATION?
• Total public spending on primary to tertiary education as a percentage of total government
expenditure averages 11% across OECD countries, and it ranges from around 6% to around 17%.

INDICATOR C4

• Between 2011 and 2015, the average share of total government expenditure devoted to public
spending on primary to tertiary education remained relatively stable across OECD countries, at
around 11%. In half of OECD countries, the share decreased, while in others the share increased by
more than 10% over the same period.

• In non-tertiary education (primary, secondary and post-secondary non-tertiary levels), spending
is decentralised, with 58% of final funds managed by regional and local governments. In tertiary
education, on average, 85% of final public funds (after transfers between levels of government)
come from the central government.

Figure C4.1. Change in total public expenditure on education as a share
of total government expenditure between 2011 and 2015
Primary to tertiary education (2011 = 100, constant prices)
Change in public expenditure on education
Change in total government expenditure for all services
Change in total public expenditure on education as a percentage of total government expenditure

%

140
130
120
110
100

Estonia

Slovenia

Hungary

Norway

Canada1

Finland

Czech Republic

Switzerland

Spain

Germany

Italy

Japan

Australia

Brazil

France

Portugal

Lithuania

EU22 average

Mexico

OECD average

Sweden

Chile

Turkey

Belgium

Netherlands

Poland

United States

Ireland

Iceland

Israel

Slovak Republic

80

Latvia

90

1. Primary education includes pre-primary.
Countries are ranked in descending order of the change in total public expenditure on primary to tertiary education as a percentage of total
government expenditure.
Source: OECD / UIS / Eurostat (2018), Table C4.3. See Source section for more information and Annex 3 for notes (http://dx.doi.
org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933804584

Context
Decisions concerning budget allocations to various sectors (including education, healthcare, social
security and defence) depend on countries’ priorities and the options for private provision of these
services. Government funding is necessary in situations where the public benefit is high but private
costs are greater than private benefits. Education is one area in which all governments intervene to
fund or direct the provision of services. As there is no guarantee that markets will provide equal access
to educational opportunities, government funding of educational services is necessary to ensure that
education is not beyond the reach of some members of society.
The economic crisis has put pressure on public budgets with the result that less public funding has
been allocated to education. Budget cuts can represent better allocation of government funds and
may generate gains in efficiency and economic dynamism, but they can also affect the quality of
government-provided education, particularly at a time when investment in education is important to
support economic growth.

280 Education at a Glance 2018: OECD Indicators   © OECD 2018

Under embargo until 11/09/2018 at 11.00am CEST
This indicator compares total public spending on education with total government expenditure
across OECD and partner countries. It also includes data on the different sources of public funding in
education (central, regional and local governments) and on transfers of funds between these levels of
government.
Other findings

• In 2015, public transfers and payments to the non-educational private sector for primary to

INDICATOR C4

tertiary education represented 1% of total government expenditure and accounted for 9% of
public expenditure on education, with the remaining 91% corresponding to direct expenditure on
educational institutions.

• OECD and partner countries spend more than twice as much on non-tertiary education (primary,
secondary and post-secondary non-tertiary levels) as they do on tertiary education, mainly as a
result of near-universal education at lower levels.

• The proportion of government expenditure devoted to primary to tertiary education decreased
between 2005 and 2015 in more than 70% of the countries with available data for both years.
It remained stable in most other countries and increased in a number of countries, most notably
in Chile, Brazil and Israel, where the increase was just over 2.5 percentage points.

• On average across OECD and partner countries, the funds transferred from central to regional
and local levels of government at non-tertiary levels of education are larger than at tertiary level.
On average across OECD countries, the 56% of public funds for non-tertiary education provided
by the central government drop to 42% after transfers between levels of government are accounted
for. As a result, the share of local funds rises from 24% to 39%.

Education at a Glance 2018: OECD Indicators   © OECD 2018

281

chapter C Financial Resources Invested In Education
Under embargo until 11/09/2018 at 11.00am CEST

Analysis

Overall, significant government funding is devoted to non-tertiary levels of education. In most countries, and
on average across OECD countries, roughly three-quarters of the total public expenditure on primary to tertiary
education (about 8.1% of total government expenditure) was devoted to non-tertiary education. This is largely
explained by the near-universal enrolment rates at non-tertiary levels of education (see Indicator B1), the
demographic structure of the population (Table C4.1), and the fact that in many OECD countries, the funding
structure for tertiary education is largely private.
The total public expenditure devoted to tertiary education varies widely among countries. On average across
OECD countries, total public expenditure on tertiary education amounts to 27% of total public expenditure from
primary to tertiary education. Percentages range from 15%-20% in Hungary, Israel, Luxembourg and Portugal to
around 35% in Austria, Estonia, the Slovak Republic and Turkey (Table C4.1).

Figure C4.2. Composition of total public expenditure on education as a percentage
of total government expenditure (2015)
Primary to tertiary education
%

35

Public transfers and payments to the non-educational private sector
Direct public expenditure on educational institutions

30
25
20
15
10
5
0

Costa Rica1
New Zealand
Chile1
Brazil
Mexico
Korea
Iceland
Switzerland
Australia
Colombia1
Ireland
Israel
United Kingdom
Norway
Latvia
Canada2
United States
Turkey
Sweden
Netherlands
OECD average
Belgium
Finland
Estonia
Lithuania
Poland
Austria
EU22 average
Germany
Portugal
Slovak Republic
Slovenia
France
Spain
Luxembourg
Japan
Czech Republic
Russian Federation
Italy
Hungary
Greece

C4

Overall level of public resources invested in education
Countries differ in the share of total public expenditure devoted to education. In 2015, total public expenditure
on primary to tertiary education as a percentage of total government expenditure for all services averaged 11% in
OECD countries. However this share varies across OECD and partner countries, ranging from around 6% in Greece
and Hungary to at least 17% in Chile, Mexico and New Zealand, and around 30% in Costa Rica (Table C4.1 and
Figure C4.2).

1. Year of reference 2016.
2. Primary education includes pre-primary programmes.
Countries are ranked in descending order of total public expenditure on primary to tertiary education as a percentage of total government expenditure.
Source: OECD / UIS / Eurostat (2018), Table C4.1. See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag2018-36-en).
1 2 https://doi.org/10.1787/888933804603

Total public expenditure on education includes direct expenditure on institutions (such as operating costs of
public schools), transfers to the non-educational private sector that are attributable to educational institutions,
and public subsidies to households for living costs that are not spent in educational institutions. Public transfers
and payments to the non-educational private sector for primary to tertiary education (such as public student
loans, grants, scholarships and subsidies to private student loans) represent a small share of total government
expenditure in OECD and partner countries, but significant differences are observed across countries (Figure C4.2).
In 2015, these public expenditures represented 1% of total government expenditure and accounted for 9% of public
expenditure on education, with the remaining 91% corresponding to direct expenditure on educational institutions.

282 Education at a Glance 2018: OECD Indicators   © OECD 2018

What is the total public spending on education? – INDICATOR C4

chapter C

Under embargo until 11/09/2018 at 11.00am CEST
However, the percentage varies by country: public transfers and payments to the non-educational private sector
represent between 2% and 3% of total government expenditure in countries such as Australia, Chile, Ireland,
New Zealand and the United Kingdom, and less than 0.3% in the Czech Republic, Greece and Luxembourg.
The relative size of public budgets must be taken into account when considering public spending on education as a
share of total government expenditure. Total public expenditure on education as a share of gross domestic product
(GDP) presents quite a different picture. In 2015, total public expenditure on primary to tertiary education as a
share of GDP was 4.5% on average across OECD countries. Across OECD and partner countries, it ranged from
3.3% or below in the Czech Republic, Japan and the Russian Federation to around 7% in Norway.
The share of total government expenditure as a proportion of GDP varies greatly among countries (Table C4.1).
In 2015, almost one-third of countries with available data reported that total government expenditure on all
services was more than 50% of GDP, including Finland (57%) and Norway (58%) with the highest shares. As
noted above, a high share of total government expenditure devoted to public expenditure on education does not
necessarily translate into a high share when compared to a country’s GDP. For example, Ireland allocates 13% of its
total government expenditure to education (more than the OECD average of 11%), but total public expenditure on
education as a share of GDP is relatively low (3.7% compared to the OECD average of 4.5%). This can be explained
by the relatively low level of total government expenditure compared to GDP in Ireland (29%).
Changes in total public expenditure on education as a percentage of total government
expenditure, 2005-15
OECD spending patterns remained relatively stable between 2005 and 2015 (Table C4.3), at around 11% on
primary to tertiary education. However, over this period, the share of total government expenditure on primary
to tertiary education within total government expenditure decreased by 0.5 percentage points on average across
OECD countries and in more than 70% of countries with available data, for both 2005 and 2015. The decrease was
especially substantial (3.0 percentage points) in Mexico and Slovenia, while Brazil, Chile and Israel experienced the
largest increases (just over 2.5 percentage points).
Total expenditure dropped slightly between 2005 and 2011, mainly due to the 2008 financial crisis. During this
period, total public expenditure on primary to tertiary education as a percentage of total public expenditure decreased
in two-thirds of OECD countries (20 of 30 countries with available data for this period), and by 0.4 percentage
points on average. Countries such as Mexico, Iceland and Lithuania were severely hit during this period and the
share of total public expenditure on primary to tertiary education as a percentage of total public expenditure fell by
just over 2 percentage points. Exceptions to that trend included Brazil, Chile and Israel, which showed increases just
over 2 percentage points (Table C6.3).
A similar tendency has been observed in the years following the crisis, between 2011 and 2015, likely due in part
to countries facing pressure to pursue fiscal consolidation (Table C6.3 and Figure C4.1). Despite the fact that public
expenditure on primary to tertiary education increased over that period in a large number of countries, high increases
were also observed in total government expenditure. Over this four-year period, only about 40% of countries with
available data increased their share of public expenditure on education within total government expenditure, with
Israel and Latvia showing the greatest increase (around 1 percentage point) whereas 80% of them increased total
government expenditure for all goods and services. However, in 18 OECD and partner countries the increase in
public expenditure on education was lower than the increase in government spending overall. Notable cases are
Estonia, Norway and Slovenia, where the relative increase in total government expenditure was between 10 and
20 percentage points higher than the increase in public expenditure on education. In 6 out of these 18 countries,
public expenditure on education actually declined between 2011 and 2015, while total government expenditure rose
(Table C4.3 and Figure C4.1).
Sources of public funding invested in education
The division of responsibility for education funding between levels of government (central, regional and local) is an
important factor in education policy. Indeed, important decisions regarding education funding are made both at the
level of government where the funds originate and the level of government at which they are finally spent. At the
initial sources of education funding, decisions are made on the volume of resources allocated and any restrictions
on how that money can be spent. At the final level of government education funding, additional restrictions may
be attached to the funds, or this level of government may even pay directly for educational resources (e.g. teachers’
salaries).
Education at a Glance 2018: OECD Indicators   © OECD 2018

283

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chapter C Financial Resources Invested In Education
Under embargo until 11/09/2018 at 11.00am CEST

C4

In some countries, education funding is centralised, while in others it can be decentralised, with funds transfers
between levels of government. Complete centralisation can cause delays in decision making. Decisions that are far
removed from those affected also can fail to address changes in local needs and desired practices. Under complete
decentralisation, however, units of government may differ in the level of educational resources they spend on
students, due to either differences in priorities related to education or differences in the ability to raise education
funds. Wide variability in education standards and resources can also lead to inequality of educational opportunity
and insufficient attention to long-term national requirements.
In recent years, many schools have become more autonomous and decentralised, as well as more accountable to
students, parents and the public at large for their outcomes. The results of the OECD Programme for International
Student Assessment (PISA) suggest that when autonomy and accountability are intelligently combined, they tend
to be associated with better student performance (OECD, 2016[1]).
The levels of government responsible for funding education differ between levels of education. Typically, public
funding is more centralised at the tertiary level than at lower levels of education. In 2015, on average across
OECD countries, 56% of the public funds for non-tertiary education came from the central government before
transfers to the various levels of government, compared to 86% of the funds for tertiary education (Table C4.2).
The division of responsibility for funding in non-tertiary levels of education varies greatly among countries
(Table C4.2 and Figure C4.3):

• On average, central and regional governments are the main initial and final sources of funds in non-tertiary
education. However, the central government is the only main initial source of funds and the only final purchaser
of educational services in Costa Rica and New Zealand. In countries such as Chile, Colombia, France, Greece,
Hungary, Ireland, Israel, Italy, Luxembourg, the Netherlands, Portugal, Slovenia and Turkey, the central
government is still the source of the majority of initial funds and the main final purchaser of educational goods
and services. In contrast, in Canada, Germany, Norway, Poland, Sweden, Switzerland and the United States, the
central government generates and spends less than 10% of education funds.

• In Austria, Estonia, Korea, Lithuania, Mexico and the Slovak Republic, the central government is the main initial
source of funds, but regional and local authorities are the main final purchasers of educational services.

• Regional governments are both the main initial source and the main final spender of education funds in Australia,
Belgium, the Czech Republic, Germany, Spain and Switzerland. In Brazil and Canada, regional governments are
the predominant source of initial funds, but local authorities are the main final purchasers of educational services.

• In Finland, Norway, the United Kingdom and the United States, local authorities are both the main initial source
of funds as well as the main final purchasers of educational services.
On average across OECD countries, more funds are transferred from central to regional and local levels of government
in non-tertiary education than in tertiary education. This extends the scope for decentralisation at non-tertiary levels
of education. On average across OECD countries, the 56% of public funds for non-tertiary education provided by
the central government drop to 42% after transfers to other levels of government are accounted for, while the share
of local funds rises as a result from 24% to 39%. There is great variation between countries in the source of funds
after transfers from central to lower levels of government. In Korea, Lithuania, Mexico and the Slovak Republic, the
difference is more than 50 percentage points after transfers to regional and local governments, while in Australia,
Austria, Chile, Estonia, Finland and Latvia, the difference is between 25 and 40 percentage points. In Canada and
the United States, the share of regional funding decreases by 40 percentage points or more after transfers to local
levels of government (Table C4.2 and Figure C4.3).
Tertiary education, however, is much more centralised than non-tertiary education, as the proportion of public funds
coming from the central government is relatively large, both before and after transfers among levels of government
(Table C4.2). Across the OECD on average, 86% of funds before transfers are managed by the central government and
this barely changes when intergovernmental transfers are taken into account. In most OECD and partner countries
with data available, the central government provides directly for more than 60% of public funds in tertiary education
and in 15 countries, the central government is the only source of initial funding and there are no transfers to regional
or local governments. In contrast, countries such as Belgium, Germany, Spain and Switzerland source over 60% of
tertiary-level funding from regional governments with very little or nothing transferred down to local governments.
Local authorities typically do not have an important role in financing tertiary education, with the exception of Ireland
and the United States, where around 10% of the funds are generated and spent by local governments.

284 Education at a Glance 2018: OECD Indicators   © OECD 2018

What is the total public spending on education? – INDICATOR C4

chapter C

Under embargo until 11/09/2018 at 11.00am CEST

Figure C4.3. Distribution of initial sources of public funds for education and change
in government levels’ share of funds after intergovernmental transfers (2015)
Primary, secondary and post-secondary non-tertiary education
Distribution of initial sources of public funds for education, by level of government

Costa Rica1
New Zealand
Greece
Turkey
Ireland
Chile1
Netherlands
Slovenia
Colombia1
Hungary
Israel
Luxembourg
Slovak Republic
Italy
Portugal
Mexico
Lithuania
Austria
France
Latvia
Korea
Estonia
EU22 average
OECD average
United Kingdom
Australia
Finland
Iceland
Belgium
Brazil
Japan2
Czech Republic
Spain
United States
Norway
Germany
Sweden
Canada3
Switzerland

%

100
80
60
40
20
0

C4

Initial funds from the local level of government
Initial funds from the regional level of government
Initial funds from the central level of government

Change in government levels’ share of funds before and after intergovernmental transfers

Costa Rica1
New Zealand
Greece
Turkey
Ireland
Chile1
Netherlands
Slovenia
Colombia1
Hungary
Israel
Luxembourg
Slovak Republic
Italy
Portugal
Mexico
Lithuania
Austria
France
Latvia
Korea
Estonia
EU22 average
OECD average
United Kingdom
Australia
Finland
Iceland
Belgium
Brazil
Japan2
Czech Republic
Spain
United States
Norway
Germany
Sweden
Canada3
Switzerland

Percentage points

100
80
60
40
20
0
-20
-40
-60
-80

Change in local governments’ share of funds after intergovernmental transfers
Change in regional governments’ share of funds after intergovernmental transfers
Change in central governments’ share of funds after intergovernmental transfers

1. Year of reference 2016.
2. Central transfers to regional governments include local initial funds, and regional final funds also include local final funds.
3. Primary education includes pre-primary programmes.
Countries are ranked in descending order of the share of initial sources of funds from the central level of government.
Source: OECD / UIS / Eurostat (2018), Table C4.2. See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag2018-36-en).
1 2 https://doi.org/10.1787/888933804622

Definitions
Intergovernmental transfers are transfers of funds designated for education from one level of government to
another. They are defined as net transfers from a higher to a lower level of government. Initial funds refer to the
funds before transfers between levels of government, while final funds refer to the funds after such transfers.
Public expenditure on education covers expenditure on educational institutions and expenditure outside educational
institutions such as support for students’ living costs and other private expenditure outside institutions, contrary
to previous indicators C1, C2 and C3 that focused only on spending in educational institutions. Public expenditure
on education includes expenditure by all public entities, including the ministry of education and other ministries,
local and regional governments, and other public agencies. OECD countries differ in the ways in which they use
public money for education. Public funds may flow directly to institutions or may be channelled to institutions via
government programmes or via households. Public funds may be restricted to the purchase of educational services
or may be used to support students’ living costs.
Education at a Glance 2018: OECD Indicators   © OECD 2018

285

chapter C Financial Resources Invested In Education
Under embargo until 11/09/2018 at 11.00am CEST

C4

All government sources of expenditure on education, apart from international sources, can be classified under
three levels of government: 1) central (national) government; 2) regional government (province, state, Bundesland,
etc.); and 3) local government (municipality, district, commune, etc.). The terms “regional” and “local” apply to
governments with responsibilities are exercised within certain geographical subdivisions of a country. They do
not apply to government bodies with roles defined in terms of responsibility for particular services, functions or
categories of students that are not geographically circumscribed.
Total government expenditure corresponds to non-repayable current and capital expenditure on all functions
(including education) of all levels of government (central, regional and local), non-market institutions that are
controlled by government units, and social security funds. It does not include expenditure derived from public
corporations, such as publicly owned banks, harbours and airports. It includes direct public expenditure on
educational institutions (as defined above), as well as public support to households (e.g. scholarships and loans
to students for tuition fees and student living costs) and to other private entities for education (e.g. subsidies to
companies or labour organisations that operate apprenticeship programmes).

Methodology
Figures for total government expenditure and GDP have been taken from the OECD National Accounts Database
(see Annex 2).
Public expenditure on education is expressed as a percentage of a country’s total government expenditure. The
statistical concept of total government expenditure by function is defined by the National Accounts’ Classification
of the Functions of Government (COFOG). There are strong links between the COFOG classification and the
UNESCO, OECD and Eurostat (UOE) data collection, although the underlying statistical concepts differ to some
extent (Eurostat [European Commission], 2011[2]).
Expenditure on debt servicing (e.g. interest payments) is included in total government expenditure, but it is excluded
from public expenditure on education, because some countries cannot separate interest payments for education
from those for other services. This means that public expenditure on education as a percentage of total government
expenditure may be underestimated in countries in which interest payments represent a large proportion of total
government expenditure on all services.
For more information please see the OECD Handbook for Internationally Comparative Education Statistics 2018 (OECD,
2018[3]) and Annex 3 for country-specific notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Lithuania was not an OECD member at the time of preparation of this publication. Accordingly, Lithuania does not
appear in the list of OECD members and is not included in the zone aggregates.

Source
Data refer to the financial year 2015 (unless otherwise specified) and are based on the UOE data collection on
education statistics administered by the OECD in 2017 (for details see Annex 3 at http://dx.doi.org/10.1787/eag2018-36-en). Data from Argentina, China, Colombia, India, Indonesia, Saudi Arabia and South Africa are from the
UNESCO Institute of Statistics (UIS).
Note regarding data from Israel
The statistical data for Israel are supplied by and are under the responsibility of the relevant Israeli authorities. The use
of such data by the OECD is without prejudice to the status of the Golan Heights, East Jerusalem and Israeli settlements
in the West Bank under the terms of international law.

References
Eurostat (European Commission) (2011), “Manual on sources and methods for the compilation of COFOG Statistics – [2]
EU Law and Publications”, Methodologies and Working papers, Eurostat, Luxembourg, http://dx.doi.org/10.2785/16355.
OECD (2018), OECD Handbook for Internationally Comparative Education Statistics 2018: Concepts, Standards, Definitions [3]
and Classifications, OECD Publishing, Paris, https://doi.org/10.1787/9789264304444-en.
OECD (2016), PISA 2015 Results (Volume II): Policies and Practices for Successful Schools, PISA, OECD Publishing, Paris, [1]
http://dx.doi.org/10.1787/9789264267510-en.

286 Education at a Glance 2018: OECD Indicators   © OECD 2018

What is the total public spending on education? – INDICATOR C4

chapter C

Under embargo until 11/09/2018 at 11.00am CEST
Indicator C4 Tables
1 2 https://doi.org/10.1787/888933804508

Table C4.1 Total public expenditure on education as a percentage of total government expenditure (2015)
Table C4.2 Share of sources of total public funds devoted to education (2015)

C4

Table C4.3 Trends in total public expenditure on education as a percentage of total government expenditure
(initial sources of funds, 2005, 2011 and 2015)
Cut-off date for the data: 18 July 2018. Any updates on data can be found on line at http://dx.doi.org/10.1787/eag-data-en. More breakdowns can
also be found at http://stats.oecd.org/, Education at a Glance Database.

Education at a Glance 2018: OECD Indicators   © OECD 2018

287

chapter C Financial Resources Invested In Education
Under embargo until 11/09/2018 at 11.00am CEST
Table C4.1. Total public expenditure on education as a percentage

of total government expenditure (2015)

Direct public expenditure on educational institutions plus public transfers and payments to the non-educational private
sector, as a percentage of total government expenditure, by level of education

Lower secondary

General programmes

Vocational programmes

All programmes

All secondary

Post-secondary non-tertiary

Primary, secondary and
post‑secondary non-tertiary

Short-cycle tertiary

Long-cycle tertiary

All tertiary

All tertiary (excluding R&D)

Total

Of which: public transfers
and payments to the noneducational private sector

Tertiary

Primary

Secondary

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

(13)

(14)

Partners

OECD

Upper secondary

Primary to tertiary
(excluding R&D)

C4

Primary
to tertiary
(including R&D)

(15)

Australia
Austria
Belgium
Canada1
Chile2
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United Kingdom
United States

4.6
2.8
1.8
2.3
2.9
1.6
d
5.2
x(1)
5.9
2.1
1.8
2.1
m
m
3.1
1.6
2.5
2.0
2.0
2.2
1.4
2.7
2.3
1.4
1.5
1.3
5.2
2.4
4.8
2.2
5.7 x(3, 4, 5)
2.0
1.4
2.9
1.7
4.9
2.9
4.3
2.0
3.0
1.8
6.4
3.4
2.7
2.6
5.3
3.9
3.7
1.7
3.6
1.7
2.9
2.3
2.0
1.9
2.9
1.6
2.6
1.7
3.6
1.7
4.3
2.7
2.9
2.3
4.4
2.0
4.0
2.1

1.3
0.6
1.3d
x(5)
2.7
0.5
m
1.0
0.7
1.3
1.0
0.8
1.4
1.6
2.2
2.9d
x(5)
x(5)
x(5)
1.5
0.7
1.8
0.6
3.0
1.4
0.7
x(5)
0.6
x(5)
1.1
1.0
1.1d
0.9
1.7
x(5)

0.4
1.3
2.1d
x(5)
1.3
1.5
m
0.8
2.0d
0.8
0.9
0.5
0.7
1.1
a
1.7d
x(5)
x(5)
x(5)
1.0
1.3
1.2
1.6
0.9
1.4
1.2
x(5)
1.4
x(5)
0.7d
1.4
1.6d
1.5
1.2
x(5)

1.7
1.9
3.4d
3.6
4.0
2.0
m
1.8
2.7d
2.0
1.9
1.3
2.1
2.7
2.2
4.5d
2.1
1.7d
3.2
2.5
2.0
3.0
2.3
3.9
2.8
1.9
2.1d
2.0
2.0
1.9d
2.5
2.6d
2.4
2.9
2.2

4.4
0.3
4.3
0.0
d
5.1
x(3, 4, 5, 6)
x(13)
0.0
6.1
a
4.1
0.0
m
m
3.4
0.5
4.7d
x(4, 5, 6)
4.2
0.0
4.6
0.4
2.7
0.0
3.5
0.6
5.1
0.1
4.4
m
4.5
0.0
3.5
0.2
3.4d x(5, 6, 9, 10, 11)
6.2
a
4.5
0.2
3.8
0.0
6.4
a
4.9
0.0
7.8
0.5
4.5
0.1
3.6
0.0
4.3d x(5, 6, 10, 11, 12)
3.9
0.1
3.5
a
3.6d
x(4, 5, 6)
4.1
0.1
5.3d
x(3, 4, 5, 6)
4.7
a
4.9
a
4.4
0.0

9.3
6.1
7.9
8.8d
12.1
6.0
m
6.9
7.2
6.2
6.4
5.0
5.6
10.4
9.8
10.3
5.7
6.3
11.1
9.0
6.8
12.8
7.6
13.6
8.3
7.2
7.3
6.0
6.5
6.2
7.8
9.6
7.6
9.3
8.4

1.1
0.6
0.1
x(11)
0.6
0.0
m
a
a
0.5
0.0
a
0.0
0.1
x(11)
0.5
0.0
0.2d
0.3
0.5
0.1
x(11)
0.0
0.6
0.1
0.0
a
0.0
x(11)
0.4
0.2
x(11)
x(11)
0.0
x(11)

3.1
2.9
2.6
x(11)
4.7
1.8
m
3.5
3.3
1.7
2.8
1.4
1.3
3.4
x(11)
1.9
1.5
1.5d
2.6
2.7
1.2
x(11)
3.6
4.9
3.9
2.9
1.9d
3.0
x(11)
1.8
3.6
x(11)
x(11)
3.1
x(11)

4.2
3.5
2.7
3.4
5.4
1.9
m
3.5
3.3
2.2
2.8
1.4
1.3
3.4
3.1
2.4
1.5
1.7d
2.9
3.2
1.2
4.2
3.6
5.5
4.0
2.9
1.9d
3.1
2.0
2.2
3.8
3.9
4.3
3.2
3.5

2.6
2.6
2.0
2.2
5.0
1.1
m
2.3
2.3
1.5
1.9
1.0
1.0
m
2.3
m
0.9
m
2.1
2.4
1.1
3.1
2.5
4.8
2.9
2.5
1.1d
1.8
1.7
1.5
2.5
2.3
3.4
2.5
3.1

13.5
9.6
10.6
12.1d
17.5
7.8
m
10.4
10.5
8.4
9.2
6.3
6.9
13.9
12.8
12.7
7.2
8.0
14.0
12.2
8.1
17.0
11.2
19.1
12.3
10.1
9.1
9.0
8.5
8.4
11.6
13.6
11.9
12.4
11.9

2.6
0.5
0.7
x(13)
2.5
0.2
m
0.5
0.7
0.4
1.0
0.0
0.4
0.9
2.0
0.4
0.5
0.5
1.2
0.5
0.2
1.2
1.6
2.9
1.5
0.5
0.5
0.7
0.5
0.4
1.4
0.3
0.9
2.3
1.2

12.0
8.7
10.0
x(13)
17.1
7.1
m
9.2
9.4
7.7
8.3
6.0
6.6
m
12.1
m
6.6
m
13.2
11.5
7.9
15.9
10.1
18.4
11.2
9.6
8.4
7.8
8.2
7.7
10.2
11.9
11.0
11.8
11.5

OECD average
EU22 average

3.5
2.8

2.1
1.9

1.3
1.0

1.2
1.2

2.5
2.2

4.5
4.1

0.2
0.2

8.1
7.0

0.3
0.2

2.7
2.5

3.0
2.6

2.3
1.8

11.1
9.5

1.0
0.7

10.2
8.8

m
m
5.0
4.5
m
m
5.6
4.1
12.1
7.5
m
m
m
m
2.0
3.1
x(3, 5, 6) x(3, 5, 6)
m
m
m
m

m
x(5)
m
x(5)
2.5
m
m
1.0
5.0d
m
m

m
x(5)
m
x(5)
1.4
m
m
0.4
0.4d
m
m

m
3.6d
m
1.4
3.8
m
m
1.4
5.3d
m
m

m
8.1d
m
5.4
11.3
m
m
4.4
5.3d
m
m

m
m
m
x(11)
a
m
m
0.4
x(4, 5, 6)
m
m

m
13.1
m
x(13)
23.4
m
m
6.8
5.3
m
m

m
m
m
x(11)
x(11)
m
m
a
0.3
m
m

m
m
m
x(11)
x(11)
m
m
3.4
1.8
m
m

m
4.2
m
3.6d
8.1
m
m
3.4
2.1
m
m

m
m
m
m
m
m
m
2.6
2.0
m
m

m
17.3
m
14.6
31.5
m
m
10.2
7.5
m
m

m
1.6
m
1.2
a
m
m
0.4
m
m
m

m
m
m
m
m
m
m
9.4
m
m
m

m

m

m

m

m

m

m

m

m

m

m

m

m

Argentina
Brazil
China
Colombia2
Costa Rica2
India
Indonesia
Lithuania
Russian Federation
Saudi Arabia
South Africa
G20 average

m

m

Note: Public expenditure presented in this table includes both public transfers/payments to the non-educational private sector which are attributable to educational
institutions and those to households for living costs, which are not spent in educational institutions. Therefore, the data presented here (before transfers) exceed
those from public spending on institutions found in Tables C1.2 and C2.2.
1. Primary education includes pre-primary programmes.
2. Year of reference 2016.
Source: OECD / UIS / Eurostat (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933804527

288 Education at a Glance 2018: OECD Indicators   © OECD 2018

What is the total public spending on education? – INDICATOR C4

chapter C

Under embargo until 11/09/2018 at 11.00am CEST
Table C4.2. Share of sources of total public funds devoted to education (2015)
Before and after transfers, by level of education
Primary, secondary and post-secondary
non-tertiary

Final funds
(after transfers
between levels
of government)

Initial funds
(before transfers
between levels
of government)

Regional

Local

Central

Regional

Local

Central

Regional

Local

Central

Regional

Local

Central

Regional

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

(13)

(14)

(15)

(16)

(17)

(18)

Australia
Austria
Belgium
Canada1
Chile2
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan3
Korea
Latvia
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United Kingdom
United States

34
74
23
4d
97
14
m
62
34
73
7
100
89
28
99
87
81
16
65
69
86
80
93
100
7
m
80
82
90
13
6
4
99
43
10

66d
14
74
75d
a
59
m
a
a
16
75
a
a
a
a
a
8
66
32
a
a
20
0
a
a
m
7
a
a
81
a
62
a
a
41

x(2)
11
3
22d
3
26
m
38
66
11
18
0
11
72
1
13
10
18
3
31
14
0
7
a
93
m
13
18
10
6
94
35
1
57
49

4
38
23
3d
64
13
m
33
9
72
6
95
88
27
99
70
81
2
1
31
85
29
90
100
5
4
80
29
90
13
6
1
99
43
1

96d
50
74
11d
a
61
m
a
a
16
72
a
a
a
a
a
7
80
40
a
a
71
0
a
a
2
7
a
a
81
a
61
a
a
2

x(5)
12
3
86d
36
26
m
67
91
12
22
5
12
73
1
30
12
18
58
69
15
0
10
a
95
95
13
71
10
6
94
39
1
57
97

93
97
15
m
100
96
m
100
100
85
28
100
100
100
87
98
87
92d
97
100
100
79
100
100
98
m
100d
100
99
19
98
33
100
100
50

7d
3
83
m
a
2
m
a
a
10
70
a
a
a
a
a
12
8d
2
a
a
21
0
a
a
m
0d
a
a
80
2
67
a
a
39

x(8)
0
1
m
0
2
m
0
0
5
2
0
0
a
13
2
0
0d
1
0
0
0
a
a
2
m
0d
0
1
1
0
0
0
0
11

90
97
14
m
100
96
m
100
100
85
18
100
100
100
87
97
86
92d
97
100
100
77
100
100
98
100
100d
100
99
19
98
17
100
100
50

10d
3
85
m
a
2
m
a
a
10
79
a
a
a
a
a
14
8d
2
a
a
23
0
a
a
0
0d
a
a
80
2
83
a
a
39

x(11)
0
1
m
0
2
m
0
0
5
2
0
0
a
13
3
0
0d
1
0
0
0
a
a
2
0
0d
0
1
1
0
0
0
0
11

52
83
21
m
98
34
m
75
55
76
13
100
91
46
96
89
83
32
71
77
88
80
95
100
37
m
84
88
92
15
37
12
99
57
22

48d
10
76
m
a
46
m
a
a
15
74
a
a
a
a
a
9
54
26
a
a
20
0
a
a
m
5
a
a
81
1
63
a
a
40

x(14)
7
3
m
2
21
m
25
45
9
13
0
9
54
4
11
8
14
3
23
12
0
5
a
63
m
10
12
8
5
63
25
1
43
38

31
59
21
m
75
32
m
56
38
76
10
96
91
45
96
75
82
21
21
49
87
41
94
100
36
31
84
53
92
15
37
5
99
57
15

69d
33
77
m
a
47
m
a
a
14
74
a
a
a
a
a
8
65
32
a
a
59
0
a
a
1
5
a
a
81
1
67
a
a
13

x(17)
8
3
m
25
21
m
44
62
10
16
4
9
55
4
25
9
14
46
51
13
0
6
a
64
67
10
47
8
5
63
27
1
43
72

OECD average
EU22 average

56
61

20
17

24
22

42
49

19
37

39
34

86
86

12
13

2
1

85
86

13
25

2
1

65
68

17
16

18
16

55
60

18
31

27
24

Argentina
Brazil
China
Colombia2
Costa Rica2
India
Indonesia
Lithuania

m
20
m
89
100
m
m
75

m
42
m
4
a
m
m
a

m
38
m
6
a
m
m
25

m
8
m
89
100
m
m
24

m
44
m
4
a
m
m
a

m
48
m
6
a
m
m
76

m
80
m
97
100
m
m
99

m
20
m
3
a
m
m
a

m
1
m
0
a
m
m
1

m
79
m
97
100
m
m
99

m
20
m
3
a
m
m
a

m
1
m
0
a
m
m
1

m
35
m
91
100
m
m
83

m
36
m
4
a
m
m
a

m
29
m
5
a
m
m
17

m
25
m
91
100
m
m
49

m
38
m
4
a
m
m
a

m
36
m
5
a
m
m
51

Russian Federation

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

Saudi Arabia

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

South Africa

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

G20 average

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

Local

Central

Final funds
(after transfers
between levels
of government)

Local

Initial funds
(before transfers
between levels
of government)

Regional

Final funds
(after transfers
between levels
of government)

Primary to tertiary

Central
Partners

OECD

Initial funds
(before transfers
between levels
of government)

Tertiary

Note: Some levels of education are included with others. Refer to “x” code in Table C4.1 for details.
1. Primary education includes pre-primary programmes.
2. Year of reference 2016.
3. Central transfers to regional governments include local initial funds, and Regional final funds also include local final funds.
Source: OECD / UIS / Eurostat (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933804546

Education at a Glance 2018: OECD Indicators   © OECD 2018

289

C4

chapter C Financial Resources Invested In Education
Under embargo until 11/09/2018 at 11.00am CEST
Table C4.3. Trends in total public expenditure on education as a percentage
of total government expenditure (initial sources of funds, 2005, 2011 and 2015)

Direct public expenditure on educational institutions plus public subsidies to households and other private entities,
as a percentage of total government expenditure, by level of education, by year
Primary, secondary
and post-secondary
non‑tertiary

Tertiary

Public expenditure as
a percentage of total
government expenditure

Public expenditure as
a percentage of total
government expenditure

Public expenditure as
a percentage of total
government expenditure

2005

2011

2015

2005

2011

2015

2005

2011

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

Australia
Austria
Belgium
Canada1
Chile
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United Kingdom
United States

10.6
m
7.7
m
11.2
m
m
m
7.7
m
6.5
m
6.8
m
m
7.8
m
m
10.2
9.8
m
16.2
8.0
m
m
8.4
m
m
m
m
8.1
10.4
m
m
9.2

10.6
m
7.8
8.7
11.6
m
m
m
7.4
6.5
6.8
m
5.4
m
m
9.3
m
m
11.5
8.0
m
13.6
7.5
m
m
7.3
m
m
m
m
7.8
9.9
7.2
m
8.2

9.3
6.1
7.9
8.8d
10.8
6.0
m
6.9
7.2
6.2
6.4
5.0
5.6
10.4
9.8
10.3
5.7
6.3
11.1
9.0
6.8
12.8
7.6
13.6
8.3
7.2
7.3
6.0
6.5
6.2
7.8
9.6
7.6
9.3
8.4

3.1
m
2.5
m
2.0
m
m
m
3.9
2.2
2.4
m
2.0
m
m
2.1
m
m
m
2.4
m
4.1
3.3
m
m
2.6
m
m
m
m
3.4
4.1
m
m
3.5

3.4
m
2.6
4.6
3.9
m
m
m
3.8
2.2
3.0
m
2.2
m
m
2.2
m
m
m
2.6
m
3.7
3.4
m
m
2.5
m
m
m
m
3.8
4.5
4.5
m
3.4

4.2
3.5
2.7
3.4
5.0
1.9
m
3.5
3.3
2.2
2.8
1.4
1.3
3.4
3.1
2.4
1.5
1.7d
2.9
3.2
1.2
4.2
3.6
5.5
4.0
2.9
1.9d
3.1
2.0
2.2
3.8
3.9
4.3
3.2
3.5

13.7
m
10.2
m
13.3
8.1
14.1
13.1
11.6
9.1
8.9
8.7
8.9
15.6
13.6
9.9
8.1
8.6
m
12.2
m
20.3
11.3
m
15.0
11.0
9.7
8.2
11.5
9.4
11.5
14.5
m
m
12.7

14.0
m
10.4
13.3
15.4
8.5
12.4
12.3
11.2
8.7
9.7
m
7.6
13.1
12.4
11.6
7.5
8.3
m
10.5
m
17.3
10.9
m
13.4
9.8
9.3
8.4
9.9
8.8
11.5
14.3
11.6
m
11.6

13.5
9.6
10.6
12.1d
15.8
7.8
m
10.4
10.5
8.4
9.2
6.3
6.9
13.9
12.8
12.7
7.2
8.0
14.0
12.2
8.1
17.0
11.2
19.1
12.3
10.1
9.1
9.0
8.5
8.4
11.6
13.6
11.9
12.4
11.9

113.2
m
104.7
95.6d
128.3
95.7
m
101.6
95.6
100.9
97.4
m
99.8
111.4
89.3
121.3
93.5
97.6
m
123.0
m
117.2
100.4
m
110.3
108.2
91.7
130.6
83.3
90.7
106.8
104.5
126.6
m
101.4

117.2
102.8
102.0
104.6
125.4
103.5
101.4
119.6
102.3
104.1
102.7
89.6
109.8
105.1
86.1
110.6
98.2
101.4
111.6
106.2
110.0
118.7
97.9
101.0
120.4
104.7
93.9
122.0
96.8
95.6
106.8
110.4
124.1
100.2
98.6

96.6
m
102.7
91.4d
102.3
92.5
m
85.0
93.5
96.9
94.8
m
90.9
106.0
103.7
109.6
95.2
96.3
m
115.8
m
98.7
102.6
m
91.6
103.4
97.6
107.0
86.1
94.9
100.0
94.6
102.0
m
102.8

OECD average
EU22 average

m
m

m
m

8.0
7.0

m
m

m
m

3.0
2.6

11.5
10.5

11.2
10.0

11.1
9.5

105.0
100.8

105.9
102.6

98.4
97.8

m
11.7
m
m
m
m
m
9.6

m
14.3
m
m
m
m
m
7.0

m
13.1
m
9.9
15.2
m
14.4
6.8

m
3.0
m
m
m
m
m
3.0

m
3.4
m
m
m
m
m
3.4

m
4.2
m
2.9d
4.8
m
3.3
3.4

m
14.7
m
m
m
m
m
12.6

m
17.7
m
m
m
m
m
10.4

m
17.3
m
12.8
20.0
m
17.6
10.2

m
106.9
m
m
m
m
m
91.0

121.0
109.6
158.7
127.1
m
130.0
120.9
93.3

m
97.5
m
m
m
m
m
97.5

Russian Federation

m

m

5.3

m

m

2.1

m

m

7.5

m

100.8

m

Saudi Arabia

m

m

m

m

m

m

m

m

m

m

143.0

m

South Africa

m

m

m

m

m

m

m

m

m

m

114.9

m

G20 average

m

m

m

m

m

m

m

m

m

m

113.8

m

Partners

OECD

C4

Argentina
Brazil
China
Colombia
Costa Rica
India
Indonesia
Lithuania

Primary to tertiary

2015

Index of change between 2011 and 2015
Total public expenditure
on education as a
Total
Total public
percentage of total
expenditure government
on education expenditure government expenditure

Note: Public expenditure presented in this table includes both public transfers/payments to the non-educational private sector which are attributable to educational
institutions and those to households for living costs, which are not spent in educaitonal institutions. Therefore, the data presented here (before transfers) exceed
those from public spending on institutions found in Tables C1.2 and C2.2. Some levels of education are included with others. Refer to “x” code in Table C4.1 for details.
1. Primary education includes pre-primary programmes.
Source: OECD / UIS / Eurostat (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933804565

290 Education at a Glance 2018: OECD Indicators   © OECD 2018

Under embargo until 11/09/2018 at 11.00am CEST

Under embargo until 11/09/2018 at 11.00am CEST

HOW MUCH DO TERTIARY STUDENTS PAY AND WHAT PUBLIC
SUPPORT DO THEY RECEIVE?
• In about one-third of the OECD countries with available data, public educational institutions do

INDICATOR C5

not charge any tuition fees for full-time national students enrolled in bachelor’s or equivalent
programmes. In a similar number of countries, tuition fees are moderate, at below USD 2 400 per
year. In the remaining countries, tuition fees range from USD 3 000 to over USD 8 000 per year.

• Even if the earnings advantage for completing a master’s programme or a doctorate is higher than
that for attaining tertiary education at bachelor’s level, public institutions in the majority of OECD
countries with available data charge similar tuition fees regardless of the level of the programme.
The additional charges that master’s and doctoral students face are limited to the additional years
of education and the delayed entry into the labour market.

• In about half of the countries with available data, foreign students are charged higher tuition fees
than national students enrolled in the same programme in public institutions. On average, the
difference in fees for foreign students in public institutions is over USD 7 500 per year in Australia,
Canada, New Zealand and Sweden.

Figure C5.1. Tuition fees charged by public tertiary educational institutions
to national students, by level of education (2015/16)
Average annual tuition fees charged to full-time national students,
in equivalent USD converted using PPPs for GDP

Turkey

Sweden

Slovenia

Slovak Republic

Poland

Finland

Norway

Estonia

Denmark

French Comm. (Belgium)

Luxembourg

Flemish Comm. (Belgium)

Hungary

Austria2

Switzerland2

Italy

Portugal

Netherlands

Israel6

New Zealand5

Korea4

Canada

Australia2

Chile

Japan

United States3

England (UK)1, 2

16 000
14 000
12 000
10 000
8 000
6 000
4 000
2 000
0

Spain

Bachelor’s or equivalent level
Master’s or equivalent level
Doctoral or equivalent level

USD converted
using PPPs

Note: This figure does not take into account grants, subsidies or loans that partially or fully offset the student’s tuition fees. Tuition
fees should be interpreted with caution as they do not cover all educational institutions, but they can be considered as good proxies
and show the difference among countries in tuition fees charged at different educational levels for the majority of students.
1. Government-dependent institutions. Figures are based on ISCED 5 and 6 programmes combined.
2. Year of reference 2014/15.
3. Year of reference 2011/12.
4. Year of reference 2016.
5. Estimates include universities only and are based on ISCED 5 and 6 programmes combined (excluding second programmes at
ISCED 6).
6. Year of reference 2013/14.
Countries and economies are ranked in descending order of their tuition fees charged at bachelor’s or equivalent level.
Source: OECD (2018), Table C5.1. See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/
eag-2018-36-en).
1 2 https://doi.org/10.1787/888933804717

292 Education at a Glance 2018: OECD Indicators   © OECD 2018

Under embargo until 11/09/2018 at 11.00am CEST
Context
With participation in upper secondary education close to universal in most OECD countries, national
policies are increasingly focusing on the expansion of tertiary education. Meeting the demand while
maintaining high quality creates pressure on budgets and pushes countries to increase their current
level of spending or the efficiency of their expenditure on education. OECD and partner countries have
different approaches to providing financial support to students and to sharing the costs of tertiary
education among governments, students and their families, and other private entities. All countries
would like students to be able to afford to enter and graduate from tertiary education, but some
countries prefer to invest the resources they dedicate to this goal in lower tuition fees, while others
decide to offer student loans and grants to cover tuition fees and/or living costs.

INDICATOR C5

Tuition fees bridge the gap between the costs incurred by tertiary educational institutions and
the revenues they receive from sources other than students and their families. Many factors may
influence the level of costs, including: 1) salaries of teachers and researchers (especially for institutions
competing to hire the best in a global academic market); 2) development of digital learning and nonteaching services (e.g. employment services and relations with companies); 3) changes in demand for
tertiary education; 4) investments to support internationalisation; and 5) the amount and type of
research activities undertaken by faculty and staff. Tertiary educational institutions partly cover their
costs through internal resources (endowments) or revenue from private sources other than students
and their families (see Indicator C3). The remainder of the costs is covered by student tuition fees or
from public sources.
Hence, policy decisions on tuition fees can affect the cost to students of tertiary education, as well
as the amount of resources available to tertiary institutions. Some countries, therefore, prefer to
let tertiary educational institutions charge higher tuition fees and to provide financial support to
students in other ways, particularly through grants and public loans. In a number of countries, loans
and grants are extended to cover also students’ living costs during their studies. Public loans are often
available to students at better conditions than they could find on the private market, typically with
lower interest rates and/or conditions under which the loan is remitted or forgiven.
Public support to students and their families enables governments to encourage participation in
education, while also indirectly funding tertiary institutions. Channelling funding to institutions
through students may also help to increase competition among institutions and better respond to student
needs. Student support comes in many forms, including means-based subsidies, family allowances for
students, tax allowances for students or their parents, or other household transfers. The trade-offs
between different ways to fund tertiary education have been widely discussed in the literature, from
different points of view (Barr, 2004[1]) (Borck and Wimbersky, 2014[2]). Governments strive to strike
the right balance among these different subsidies, especially in periods of financial crisis. Based on a
given amount of subsidies, public support, such as tax reductions or family allowances, may provide less
support for low-income students than means-tested subsidies, as tax reductions or family allowances
are not targeted specifically to low-income students. However, such measures may still help to reduce
financial disparities between households with and without children in education.
Other findings

• Financial mechanisms to support students enrolled in tertiary education such as grants,
scholarships and loans are more developed in countries that charge either relatively high tuition
fees or no tuition fees at all.

• Across OECD countries, those with a larger proportion of tertiary students benefitting from
public loans also tend to be those in which the average annual amount of individual student loans
is largest. In these countries, students borrow an annual amount that ranges on average from
USD 2 000 to over USD 15 000 and receive financial support during their studies in the form of
interest rate subsidies.

Education at a Glance 2018: OECD Indicators   © OECD 2018

293

chapter C Financial Resources Invested In Education
Under embargo until 11/09/2018 at 11.00am CEST

Analysis

C5

Differentiation of tuition fees across tertiary educational levels
Entry into tertiary education often implies costs for students and their families, in terms of both tuition fees
and living expenses, although they may also receive financial support to be able to afford tertiary education.
Most national entrants into tertiary programmes enrol at bachelor’s or equivalent level in OECD countries (see
Indicator B4). They pay no tuition fees in public institutions in about one-third of the countries, including Denmark,
Estonia, Finland, Norway, Poland, the Slovak Republic, Slovenia, Sweden and Turkey (Figure C5.1). In a similar
number of countries, tuition fees are moderate, with an average cost for students below USD 2 400. In the remaining
countries, tuition fees range from USD 3 000 to over USD 8 000 per year. They exceed USD 10 000 in England
(United Kingdom), where the majority of students enrol in government private institutions.
Higher tertiary education after a bachelor’s degree leads to better labour outcomes. Graduates with a master’s,
doctorate or equivalent degree have better employment opportunities, and those who attain a tertiary education
at master’s level have higher earnings prospects (see Indicator A4). However, even if the earnings advantage for
completing a master’s programme or a doctorate is higher, tuition fees in public institutions for full-time national
students in master’s and doctoral programmes are similar to those for bachelor’s programmes in the majority of
OECD countries (Table C5.1). The additional charges that master’s and doctoral students face are limited to the
additional years of education and the delayed entry into the labour market.
Tuition is also free of charge at master’s and doctoral levels in the countries with no tuition fees at bachelor’s level,
except for Slovenia, where doctoral students are charged about USD 6 550 on average. In another group of countries,
similar (or lower) tuition fees are charged on average across the different levels of tertiary education, as in Austria,
Canada, the Flemish Community of Belgium, Hungary, Italy, Japan, Luxembourg, the Netherlands and Switzerland
(Table C5.1).
Even if the earnings advantage for completing a master’s programme or a doctorate is higher than that for attaining
tertiary education at bachelor’s level, public institutions in the majority of OECD countries with available data
charge similar tuition fees regardless of the level of the programme. Tuition fees for master’s programmes in public
institutions are about 30% higher than for bachelor’s programmes in Chile, Korea and the United States, while
in Australia and Spain they are over 50% higher. In these countries, the difference in fees between master’s and
bachelor’s programmes ranges from USD 1 000 to USD 3 100 (Table C5.1). These higher fees may limit participation
at this level: in Chile, Korea, Spain and the United States tertiary entry rates in master’s programmes are much
lower than the OECD average (see Indicator B4). In a few countries (e.g. Australia, Hungary, Italy and Switzerland),
public institutions charge lower fees for doctoral programmes than for bachelor’s and master’s programmes. In
Australia, for example, annual average tuition fees in public institutions for doctoral programmes are about 15 times
lower than for bachelor’s programmes (about USD 320 compared to USD 4 785). In fact, very few national doctoral
students pay any fee in Australia (less than 5% of doctoral students in public institutions). By contrast, public
institutions in Chile, Korea, New Zealand, Slovenia and the United States charge higher tuition fees for doctoral
programmes than for bachelor’s and master’s programmes.
Tuition fees for short-cycle tertiary programmes in public institutions are generally much lower. In most cases,
they amount to half or less of the tuition fees in bachelor’s programmes (Table C5.1). For example, in Chile and
the United States, average annual tuition fees for a short-cycle tertiary programme are at least USD 4 000 less than
for a bachelor’s programme, while the difference ranges from USD 1 400 to USD 2 000 in Japan, Korea and Spain
(in Spain tuition in short-cycle tertiary programmes is free of charge for the majority of students). The lower tuition
fees in Chile, Korea and the United States can be explained by the lower earnings advantage of attaining a shortcycle tertiary qualification rather than continuing with a bachelor’s or higher level programme. Tuition fees for
short-cycle tertiary programmes are at the same level as bachelor’s and master’s programmes in the Netherlands, as
well as in those countries where higher education is generally free at all levels (Denmark, Estonia, Norway, Poland,
Slovenia, Sweden and Turkey).
Differentiation of tuition fees by type of institution
Ensuring an affordable education for everyone is a goal that may clash with educational institutions’ need for financial
resources. The way OECD countries and their education systems deal with policies on tuition fees leads to different
levels of tuition fees according to the type of institution. Relying less on public funds than public institutions,
independent private institutions are less affected by government regulations and may be more pressed by competition
in terms of quality of services provided to students. As a result, they may charge higher annual tuition fees than public
institutions for bachelor’s or equivalent programmes in all OECD countries with available data.

294 Education at a Glance 2018: OECD Indicators   © OECD 2018

How much do tertiary students pay and what public support do they receive? – INDICATOR C5

chapter C

Under embargo until 11/09/2018 at 11.00am CEST
The difference in fees between public and private institutions is significant in several countries (Table C5.1).
For national students in Australia, Japan and Korea, average tuition fees in bachelor’s programmes are above
USD 8 000 in independent private institutions, compared to between USD 4 500 and USD 5 300 in public
institutions. In the United States, one-third of students enrol in independent private institutions, where the
average annual tuition fees for a bachelor’s or equivalent programme are almost two-and-a-half times higher than
in public institutions, exceeding USD 20 000. In Italy, tuition fees in independent private institutions are about
three times as high as in public institutions, while they are twice as high in Hungary and Israel. The tuition fees in
government-dependent private institutions in the French Community of Belgium are moderate, but they are higher
than in public institutions. The average annual tuition fees in independent private institutions are about USD 6 300
in Norway, about USD 2 200 in Poland, and close to USD 2 800 in the Slovak Republic, while public institutions in
these three countries do not charge tuition fees at all.
In some countries the difference in fees between public and private institutions for national students at bachelor’s
or equivalent level is much smaller. Public and private institutions do not charge tuition fees in Finland, Slovenia
and Sweden, while government-dependent private institutions charge similar tuition fees on average in the Flemish
Community of Belgium and Switzerland. However, the share of students enrolled in private institutions is relatively
low in some of these countries (less than 20% in Slovenia, Sweden and Switzerland). Tuition fees are capped in public
and government-dependent private institutions in Austria and in government-dependent private institutions in
Norway, whereas in independent private institutions they are at the discretion of each institution.
Tuition fees for foreign students
National policies on tuition fees and financial aid to students generally cover all students studying in the country’s
educational institutions, including non-national students (see Definitions section at the end of this indicator).

Figure C5.2. Annual average tuition fees charged by public tertiary educational institutions
to national and foreign students at bachelor’s or equivalent level (2015/16)
Average annual tuition fees charged to full-time students, in equivalent USD converted using PPPs for GDP

Sweden6

Slovenia

Slovak Republic

Poland6

Norway

Finland

Denmark6

French Comm. (Belgium)

Luxembourg

Hungary

Austria2

Foreign students

Switzerland2

Portugal

Italy

Spain

Israel5

New Zealand4

Korea3

Australia2

Canada

Japan

National students

Chile

20 000
18 000
16 000
14 000
12 000
10 000
8 000
6 000
4 000
2 000
0

United States1

USD converted
using PPPs

1. Year of reference 2011/12.
2. Year of reference 2014/15.
3. Year of reference 2016.
4. Estimates include universities only and exclude second programmes at ISCED 6, such as postgraduate certificates and diplomas.
5. Year of reference 2013/14.
6. Tuition fees for foreign students refer to students from outside the European Economic Area or the European Union (see Table C5.1).
Countries and economies are ranked in descending order of tuition fees charged to national students.
Source: OECD (2018), Table C5.1. See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933804736

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C5

However, tuition fees may be higher for internationally mobile students, and differences between national and
non-national students in fees or financial support can have an impact on the international flows of students, as
can other factors, such as public support from their home countries (OECD, 2017[3]). These differences can attract
students to study in some countries and discourage them from studying in others (see Indicator B6), especially in a
context where an increasing number of OECD countries are charging higher tuition fees for non-national students
than for national ones. However, tertiary education in countries with higher fees for foreign students can still
be attractive because of the quality and prestige of their educational institutions or the expected labour market
opportunities in the country after graduation.
National and foreign students generally pay similar tuition fees in Chile, Israel, Italy, Japan, Korea, Latvia,
Luxembourg, Mexico, Portugal, Spain and Switzerland, as well as in other countries that charge no tuition fees
to national or foreign students (Finland, Norway, the Slovak Republic and Slovenia) (Table C5.1). By contrast, in
about half of the countries with available data, national and foreign students enrolled in the same programme
in public institutions are charged different tuition fees. However, European Union (EU) and European Economic
Area (EEA) countries charge the same tuition fees to nationals and students from other EU and EEA countries.
The difference in fees for foreign students in public institutions is, on average, over USD 7 500 per year in
Australia, Canada, New Zealand and the United States (Table C5.1). In the United States, all foreign and national
students who study outside their state also pay higher tuition fees than in-state students. In Austria, the average
tuition fees charged by public institutions to students who are not citizens of EU or EEA countries are twice as
high as those for national students (for bachelor’s, master’s and doctorate or equivalent programmes). In Poland
and Sweden, tuition is free for national students and those from the European Union, while non-EU students pay
over USD 4 500 at bachelor’s level.
Distribution of financial support to students
A robust financial support system and the type of aid on which this is based are important factors in ensuring good
outcomes for students in higher education (OECD, 2008[4]). A key question that many educational systems face is
whether financial support for students in tertiary education should be provided primarily in the form of loans or
in the form of grants and scholarships. OECD governments support students’ living or educational costs through
different combinations of these two types of support.
On the one hand, advocates of student loans argue that they allow for scaling up of the number of students that
can benefit from the available resources (OECD, 2014[5]). If the amount spent on scholarships and grants were used
to guarantee and subsidise loans, the same public resources could target a larger number of students, and overall
access to higher education would increase. Loans also shift some of the cost of education to those who benefit most
from higher education, individual students, reflecting the high private returns of completing tertiary education
(see Indicator A5).
On the other hand, student loans are less effective than grants in encouraging low-income students to access tertiary
education. Opponents of loans argue that high levels of student debt at graduation may have adverse effects for
both students and governments if large numbers of students are unable to repay their loans (OECD, 2014[5]). A high
share of graduates with debt could be a problem if employment prospects are not sufficient to guarantee student
loan repayments.
In Australia, England (United Kingdom), Norway and the United States, at least 80% of students in bachelor’s or
equivalent-level programmes benefit from public loans or scholarships/grants. With the exception of Norway, where
tuition is free in public institutions and public support covers students’ living costs, these countries also have some
of the highest tuition fees among OECD countries. In Austria, the Flemish and French Communities of Belgium,
Italy and Switzerland, tuition fees are moderate, and public financial support only targets a limited number of
students. Those who benefit from public financial aid usually receive such support in the form of scholarships
and grants. In Finland and Turkey, public institutions do not charge tuition fees, and most students benefit from
scholarships/grants (Finland) or loans (Turkey) (Table C5.5, available on line).
Country approaches to funding tertiary education
OECD countries have different and evolving approaches to providing financial support to students enrolled in
tertiary education. Reforms related to the level of tuition fees and the availability of scholarships, grants and loans
are highly debated in national education policy, often in combination, as countries seek to improve or adjust how the
public and private sectors (including students and their families) share the costs of tertiary education.

296 Education at a Glance 2018: OECD Indicators   © OECD 2018

How much do tertiary students pay and what public support do they receive? – INDICATOR C5

chapter C

Under embargo until 11/09/2018 at 11.00am CEST
Despite the policy changes over time within individual countries and differences across countries, national financing
systems for higher education can be grouped and classified according to a number of common characteristics.
Countries can be roughly divided into four groups, depending on their level of tuition fees and the financial support
available through the country’s student financial aid system for tertiary education (OECD, 2015[6]):

Figure C5.3. Tuition fees charged by public institutions related to the share of students
benefiting from public loans, scholarships or grants, at bachelor’s or equivalent level (2015/16)
Tuition fees charged by public institutions
(USD converted using PPPs)

12 000

Group 3

Group 2

England (UK)

10 000
United States

8 000
Chile

6 000
Australia

4 000

Israel

Group 4

Italy

2 000

French Comm. (Belgium)
Spain
Flemish Comm. (Belgium)
Denmark

Austria
Switzerland

0
0

Group 1

10

20

30

40

50

Luxembourg
Norway

Turkey

Finland

60

70

80

90

100

Share of students benefiting from
public loans, scholarships or grants

Note: The share of students receiving financial support for Denmark includes only students benefiting from loans, while the value for Luxembourg
includes all students eligible for support. For other specific country notes, please refer to figures reported in Table C5.1 and Table C5.5, available on
line.
Source: OECD (2018), Table C5.1 and Table C5.5, available on line. See Source section for more information and Annex 3 for notes (http://dx.doi.
org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933804755

• Group 1 includes Finland, Norway, Luxembourg and Turkey (Figure C5.3), where students are charged low

or no tuition fees and the majority of students benefit from public financial support when enrolled in higher
education. In these countries, the majority of students benefit from public grants, scholarships and/or loans.
Turkey has recently moved to Group 1, as no tuition fees have been charged since 2012/13. Finland, however, has
recently decided to introduce tuition fees for students coming from outside the EEA, which may discourage them
from entering tertiary education in the country.

• Group 2 includes Australia, Canada, England (United Kingdom), New Zealand and the United States

(Figure C5.3 and Figure B5.1 in [OECD, 2014[5]]). In these countries, annual tuition fees charged by public
and private institutions for bachelor’s programmes are relatively high, exceeding USD 4 000. In Australia,
England (United Kingdom) and the United States, at least 80% of tertiary students receive support in the
form of public loans or scholarships/grants (Figure C5.3). New Zealand is gradually moving towards Group 1,
progressively eliminating fees for national students entering tertiary education for the first-time from 2018
onwards. By 2024, three years of tertiary education will be free to all national first-time students. Since 1995,
England (United Kingdom) moved to this group of countries, as tuition fees and financial support to students
increased significantly. The Netherlands are gradually moving towards this group from Group 1, as tuition fees
have increased while the student-support system has developed (see Figure B5.1 in [OECD, 2014[5]]). Israel
lies between Group 1 and Group 2, as participation in tertiary education is based on relatively high student
support (two-thirds of students benefit from grants, scholarships or loans), with tuition fees reaching around
USD 3 000 in public institutions at bachelor’s level.
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• Group 3 includes Chile (Figure C5.3), Japan and Korea (OECD, 2015[6]), where most students pay high tuition

C5

fees for bachelor’s programmes in public institutions, but student-support systems are somewhat less developed
than in the groups listed above. Tuition fees range from around USD 4 700 in Korea to around USD 5 200 in Japan
and over USD 7 300 in Chile. However, Japan has recently implemented reforms to improve the financial support
system to students, including a grant-type scholarship programme, increased interest-free student loans and an
income-based repayment system (a flexible monthly repayment system after graduation).

• Group 4 includes most other European countries for which data are available: Austria, Belgium, France, Italy,
Spain and Switzerland (OECD, 2015[6]). Financial support to students is somewhat limited, targeting a minority
of students, and tuition in public institutions is not free of charge, although it is not as high as in Australia,
England (United Kingdom) and the United States (OECD, 2015[6]).

In the last decade, tuition fees for bachelor’s or equivalent programmes increased by 8% in Japan and by 13% to
17% in Australia, Italy and the Netherlands (Table C5.2). Tuition fees also increased in Canada, New Zealand and
the United States by 20% to 23% and in England (United Kingdom) to a much larger extent. By contrast, tuition fees
at this level of education decreased in real terms in Austria, Latvia and Luxembourg.
Amount of public loans and debt at graduation
Across OECD countries with available data, countries with a larger proportion of tertiary students benefitting
from public loans also tend to be those in which the average annual amount of individual student loans is largest.
These include countries in which tuition fees are relatively high (Group 2), such as Australia, Canada, England
(United Kingdom) and the United States, as well as countries where tuition is free of charge (Group 1), such as
Norway and Sweden, where the majority of students take student loans mostly to cover their living expenses.
In these countries, students annually borrow on average an amount ranging from USD 4 200 (Australia) to over
USD 15 000 (England [United Kingdom] at bachelor’s level and the United States at master’s level). The majority of
these countries have however introduced income-contingent (or hybrid) loan systems, which are considered more
equitable and efficient in terms of use of resources and ensure that students do not have to face unsustainable
amounts of debt. With this type of loan, only graduates/students with earnings above a certain threshold are
required to pay back their student loans: for example in England (United Kingdom) up to 45% of loans are not
expected to be repaid (Table C5.3).
By contrast, among countries where only a smaller proportion of students benefit from a loan, in Finland (29%,
government-guaranteed private loans), the French Community of Belgium (less than 1%) and Latvia (9%) the
average annual gross amount borrowed by students is lower and ranges from about USD 1 500 to over USD 3 700.
However, there are also countries in which less than half of the students takes a loan, such as Chile (4%), Japan
(45%), Mexico (2%), the Netherlands (33%) and Switzerland (1%), where the average annual amount available
per student exceeds USD 5 000 (Table C5.3).
As a result of taking loans, at least 50% of students are in debt at graduation in Finland (at bachelor’s level only),
Mexico (at master’s and doctoral levels only), the Netherlands, New Zealand, Sweden (at bachelor’s and master’s
levels) and the United Kingdom (OECD, 2015[6]). The extent to which debt can be an issue for graduates mostly
depends on the amount borrowed and the underlying loan conditions compared to graduates’ labour market
prospects, in terms of earnings and uncertainty of employment. Countries whose tertiary institutions charge high
tuition fees are also those whose students have the highest levels of debt at graduation from public loans or loans
guaranteed by the state. In countries with a relatively small proportion of students taking public loans, the debt
burden also tends to be lighter. For example, in Finland, where about 29% of students benefit from governmentguaranteed private loans, the average debt at graduation exceeds USD 9 000, while in Japan, Mexico (for master’s
and doctoral students only), Norway, Sweden and the United States, where at least 40% of students benefit from
public loans, debt at graduation can exceed USD 20 000 at bachelor’s level (Table C5.3).
Financial support through interest rates
Students often benefit from special conditions on their public loans or private loans guaranteed by the government,
for example in interest rates, repayment system or remission/forgiveness mechanisms (Table C5.3). Governments
often introduce these special conditions to reduce the cost of loans for students and, in case of income-contingent
loans, to protect students from the uncertainty of the labour market after graduating. By doing so, governments
take on a considerable part of the cost themselves and bear the risk of lending to students, who can then access
capital at a cost lower than market conditions.

298 Education at a Glance 2018: OECD Indicators   © OECD 2018

How much do tertiary students pay and what public support do they receive? – INDICATOR C5

chapter C

Under embargo until 11/09/2018 at 11.00am CEST
As the structure of interest rates offered to students, for both public and private loans, differs to some extent across
countries, the cross-country comparison of interest rates offered on public loans must be treated with caution.
Governments use a variety of strategies to reduce the financial burden on students, including reduced interest rates
before and/or after the end of studies. Some countries charge no nominal interest rate at all on loans, while others
link the interest rate to indices lower than market rates, such as the cost of government borrowing or an inflation
index (Table C5.3).
In about half of the OECD countries with available data, there is no nominal interest rate on a public loan during the
studies, but after this period, graduates may incur an interest charge related to the cost of government borrowing
or even higher. For example, graduates are charged an interest rate after their studies in the French Community
of Belgium, Canada, Chile, Japan, New Zealand (if they reside overseas), Norway, Poland and the Slovak Republic,
although interest rates are usually still relatively low.
In Australia, Denmark, England (United Kingdom), Estonia, Korea, New Zealand (if graduates are still residing in
the country), Sweden and the United States, the interest rate charged on student loans after the period of studies
does not exceed or is lower than the rate charged during the studies.
Repayment of loans
The current reporting of public and household expenditure on tertiary education (see Indicator C3) only takes
into account the gross amount of loans, without regard to the repayment of public loans extended to students by
previous governments. The repayment period varies among countries, ranging from 10 years or less in Australia,
Canada, Denmark, Finland, the French Community of Belgium, Luxembourg, New Zealand, the Slovak Republic and
Turkey to 20 years or more in England (United Kingdom), Norway, Sweden and the United States (for income-based
repayments).
Repayment systems that are dependent on the level of graduates’ income exist in almost half of the countries with
data available, while the other countries have traditional mortgage-style repayment systems. The income threshold
for loan repayments exceeds USD 30 000 in Australia and England (United Kingdom) and is between USD 13 000
and USD 22 000 in Korea, the Netherlands and New Zealand (Table C5.3).
In addition to repayment, conditions for remission and forgiveness of student loans exist in nearly all countries with
student loan systems. Among countries with available information, the proportion of students benefitting from
remission and/or forgiveness varies from 5% or less in Australia, Estonia, Finland, Japan, Latvia, New Zealand,
Norway and Sweden to over 10% in England (United Kingdom), the Netherlands and Poland. This translates
into significant proportions of loans that are not repaid and additional cost for the public sector that extends or
guarantees the loans.
The conditions to benefit from such mechanisms vary between countries. Death, disability or poor financial
situation of the graduate who took the loan are common conditions for remission or forgiveness. Conditions for
remission or forgiveness can also be linked to the labour market situation or to students’ results. For example, in
the United States, teachers and individuals in public service may apply for loan forgiveness. In Australia, graduates
of specific fields (and employed in a related occupation) and graduates who take up related occupations or work in
specified locations benefit from remission through a reduction of their repayments (Table C5.3).

Definitions
In this chapter, national students are defined as the citizens of a country who are studying within that country.
Foreign students are those who are not citizens of the country in which the data are collected. While pragmatic and
operational, this classification is inappropriate for capturing student mobility because of differing national policies
regarding the naturalisation of immigrants. For countries that are members of the European Union (EU), citizens
from other EU countries usually have to pay the same fees as national students. In these cases, foreign students
refer to students that are citizens from countries outside the European Union. Further details on definitions are
available in Indicator B6.

Methodology
Amounts of tuition fees and amounts of loans in national currency are converted into equivalent USD by dividing
the national currency by the purchasing power parity (PPP) index for GDP. Amounts of tuition fees and associated
proportions of students should be interpreted with caution, as they represent the weighted averages of the main
tertiary programmes and may not cover all educational institutions.
Education at a Glance 2018: OECD Indicators   © OECD 2018

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C5

Student loans include the full range of student loans extended or guaranteed by governments, in order to provide
information on the level of support received by students. The gross amount of loans provides an appropriate
measure of the financial aid to current participants in education. Interest payments and repayments of principal by
borrowers should be taken into account when assessing the net cost of student loans to public and private lenders.
In most countries, loan repayments do not flow to education authorities, and the money is not available to them to
cover other expenditures on education.
OECD indicators take the full amount of scholarships and loans (gross) into account when discussing financial aid
to current students. Some OECD countries have difficulty quantifying the amount of loans to students. Therefore,
data on student loans should also be treated with caution.
For more information please see the OECD Handbook for Internationally Comparative Education Statistics 2018 (OECD,
2018[7]) and Annex 3 for country-specific notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Lithuania was not an OECD member at the time of preparation of this publication. Accordingly, Lithuania does not
appear in the list of OECD members and is not included in the zone aggregates.

Source
Data refer to the school year 2015/16 and are based on a special survey administered by the OECD in 2017 (for details
see Annex 3 at http://dx.doi.org/10.1787/eag-2018-36-en).

Note regarding data from Israel
The statistical data for Israel are supplied by and are under the responsibility of the relevant Israeli authorities. The use
of such data by the OECD is without prejudice to the status of the Golan Heights, East Jerusalem and Israeli settlements
in the West Bank under the terms of international law.

References
Barr, N. (2004), “Higher education funding”, Oxford Review of Economic Policy, Vol. 20/2, http://dx.doi.org/10.1093/ [1]
oxrep/grh015.
Borck, R. and M. Wimbersky (2014), “Political economics of higher education finance”, Oxford Economic Papers, Vol. 66/1, [2]
http://dx.doi.org/10.1093/oep/gps042.
OECD (2018), OECD Handbook for Internationally Comparative Education Statistics 2018: Concepts, Standards, Definitions [7]
and Classifications, OECD Publishing, Paris, https://doi.org/10.1787/9789264304444-en.
OECD (2017), “Tuition fee reforms and international mobility”, Education Indicators in Focus, No. 51, OECD Publishing, [3]
Paris, http://dx.doi.org/10.1787/2dbe470a-en.
OECD (2015), Education at a Glance 2015: OECD Indicators, OECD Publishing, Paris, http://dx.doi.org/10.1787/eag-2015-en. [6]
OECD (2014), Education at a Glance 2014 : OECD Indicators, OECD Publishing, Paris, http://dx.doi.org/10.1787/eag-2014-en. [5]
OECD (2008), “Tertiary education for the knowledge society, Volume 1, Special features: governance, funding, quality”, [4]
www.oecd.org/education/skills-beyond-school/41266690.pdf (accessed on 15 May 2018).

Indicator C5 Tables
1 2 https://doi.org/10.1787/888933804641

Table C5.1 Estimated annual average tuition fees charged by tertiary educational institutions (2015/16)
Table C5.2 Estimated change in the tuition fees charged by tertiary educational institutions (2005/06 to 2015/16)
and recent tuition-fee reforms
Table C5.3 Public loans to students, repayment and remission in tertiary education (2015/16)
WEB Table C5.4 Average tuition fees charged by tertiary public and private institutions by field of study (2015/16)
WEB Table C5.5 Distribution of financial support to students (2015/16)
Cut-off date for the data: 18 July 2018. Any updates on data can be found on line at http://dx.doi.org/10.1787/eag-data-en. Data can also be found
at http://stats.oecd.org/, Education at a Glance Database.

300 Education at a Glance 2018: OECD Indicators   © OECD 2018

chapter C

How much do tertiary students pay and what public support do they receive? – INDICATOR C5

Under embargo until 11/09/2018 at 11.00am CEST
Table C5.1. [1/2] Estimated annual average tuition fees charged by tertiary educational institutions

(2015/16)

In equivalent USD converted using PPPs, by type of institutions and degree structure, based on full-time students

OECD

Percentage of
full-time national
students (tertiary
education)
enrolled in:

C5

Annual average tuition fees for full-time national students
charged by institutions

Public
institutions

Government-dependent
private institutions

Independent private
institutions

Bachelor's or
equivalent

Master's or
equivalent

Doctoral or
equivalent

Bachelor's or
equivalent

Master's or
equivalent

Doctoral or
equivalent

Bachelor's or
equivalent

Master's or
equivalent

Doctoral or
equivalent

Private institutions

(1)

(2)

(3)

(5)

(6)

(7)

(9)

(10)

(11)

(13)

(14)

(15)

Government-dependent private
institutions

Public institutions

Independent private institutions

Countries

Australia1

94

2

4

4 785

7 933

319

5 526

6 222

3 394

10 289

7 800

993

Austria1

m

m

m

910

910

910

910

910

a

m

m

m

Canada

m

m

m

4 965

5 158

m

m

m

m

m

m

m

Chile

15

12

72

7 351

9 950

8 929

8 437

12 116

9 237

6 487

10 597

8 510

Denmark2

m

m

m

0

0

0

m

m

m

m

m

m

Estonia

m

m

m

0

0

0

0

0

0

m

m

m

Finland

53

47

a

0

0

0

0

0

a

a

a

a

Hungary

90

6

4

751

783

619

586

1 175

659

1 896

541

1 237

Israel3

15

65

20

3 043

m

m

3 041

m

m

6 675

m

m

Italy1

90

a

10

1 647

1 817

1 234

a

a

a

5 771

6 368

2 268

Japan

26

a

74

5 218

5 216

5 216

a

a

a

8 411

6 943

5 762

Korea4

m

m

m

4 712

6 215

6 970

a

a

a

8 419

11 426

12 175

Latvia

7

70

24

a

a

a

1 906
to 24 912d

1961
to 29 894

3 388
to 18 136

1 435
to 15 346d

2 152
to 16 940

3 786
to 7 971

Luxembourg

m

m

m

449 to 896 449 to 3 586

448

a

a

a

m

m

a

Mexico1

70

a

30

m

a

a

a

4 711d

x(13)

x(13)

Netherlands

m

m

New Zealand5

m

m

Norway

84

Poland6

m

m

m

2 395

2 395

a

a

a

a

m

m

a

m

4 236d

m

4 598

m

m

a

m

m

a

6

10

0

0

a

2 928d

x(9)

a

6 288d

x(13)

a

93

a

7

0

0

0

a

a

a

2 175

658

m

Portugal

m

m

m

1 116
to 1 808

1 116
to 10 587

m

a

a

a

m

m

m

Slovak Republic

95

0

5

0

0

0

a

a

a

2 827

3 503

9 175

Slovenia

94

5

1

0

0

6 553d

0

0

x(7)

0

0

x(7)

Spain

82

x(3)

18d

1 832

2 860

m

m

m

m

m

m

m

Sweden2

87

13

a

0

0

0

0

0

0

a

a

a

Switzerland1

83

7

10

1 170d

1 170

437

1 170d

1 170

437

m

m

m

Turkey

m

a

m

0

0

0

a

a

a

m

m

m

United States7

67

a

33

8 202

11 064

13 264

a

a

a

21 189

17 084

22 929

a

Economies

Flemish Comm. (Belgium)

m

m

m 132 to 1 112 132 to 1 112

556 132 to 1 112 132 to 1 112

556

m

m

French Comm. (Belgium)1

40

60

a

419d

x(5)

x(5)

557d

x(9)

x(9)

a

a

a

England (UK)

m

m

m

a

a

a

11 797

m

m

m

m

m

Note: Tuition fees should be interpreted with caution as they do not cover all educational institutions. However, the data reported can be considered as good proxies
and show the difference among countries in tuition fees charged by main educational institutions and for the majority of students.
Data on short-cycle tertiary programmes are available on line (see StatLink below).
1. Year of reference 2014/15.
2. Tuition fees for foreign students refer to students from outside the European Economic Area.
3. Year of reference 2013/14.
4. Year of reference 2016.
5. Estimates include universities only and exclude ISCED 6, such as postgraduate certificates and diplomas.
6. Tuition fees for foreign students refer to students from countries outside the European Union.
7. Year of reference 2011/12.
Source: OECD (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933804660

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301

chapter C Financial Resources Invested In Education
Under embargo until 11/09/2018 at 11.00am CEST
Table C5.1. [2/2] Estimated annual average tuition fees charged by tertiary educational institutions

(2015/16)

In equivalent USD converted using PPPs, by type of institutions and degree structure, based on full-time students
Annual average tuition fees for full-time foreign students
charged by institutions
Private institutions

15 750

14 492

14 841

Austria1

1 819

1 819

1 819

Canada

17 588

12 875

m

Doctoral or
equivalent

Australia1

Master's or
equivalent

(19)

Bachelor's or
equivalent

Doctoral or
equivalent

(18)

Doctoral or
equivalent

Master's or
equivalent

(17)

Independent private institutions

Master's or
equivalent

Bachelor's or
equivalent
OECD

Public institutions

Government-dependent private
institutions
Bachelor's or
equivalent

C5

(21)

(22)

(23)

(25)

(26)

(27)

12 094

8 277

15 334

9 945

10 987

13 369

1 819

1 819

1 819

m

m

m

m

m

m

m

m

m

3 658

2 731

1 200

Countries

Chile

No differentiation for foreign students.

Denmark2

1092 to 2047

Estonia

Differentiation of tuition fees based on the language of the programmes: tuition fees may be charged
in programmes taught in languages other than Estonian.

Finland
Hungary

No differentiation for foreign students.
1 304

5 352

1 347

465

641

639

Israel3

No differentiation for foreign students.

Italy1

No differentiation for foreign students.

Japan

No differentiation for foreign students.

Korea4

No differentiation for foreign students.

Latvia

No differentiation for foreign students.

Luxembourg

No differentiation for foreign students.

Mexico1

No differentiation for foreign students.

Netherlands

m

m

a

a

a

a

m

m

a

New Zealand5

18 269d

m

4 598

m

m

a

m

m

a

3 082

2 583

m

0

0

x(19)

a

a

a

Norway
Poland6

No differentiation for foreign students.
4 545

2 419

0

Portugal
Slovak Republic
Slovenia

0

6 553d

United States7

a

0

0

x(19)

No differentiation for foreign students.
13 968

14 415

0

Switzerland1
Turkey

a

No differentiation for foreign students.
0

Spain
Sweden2

a

No differentiation for foreign students.

13 968

14 415

0

No differentiation for foreign students.
m

m

m

a

a

a

m

m

m

16 066

16 489

20 168

a

a

a

29 234

24 095

30 205

Economies

Flemish Comm. (Belgium)
French Comm. (Belgium)1
England (UK)

For students from outside the European Economic Area, institutions have the autonomy to fix the amount of the tuition fee,
except for some categories of students (e.g. refugees, asylum seekers).
1 483

1 979

m

x(17)

x(18)

m

a

a

a

a

a

a

m

m

m

m

m

m

Note: Tuition fees should be interpreted with caution as they do not cover all educational institutions. However, the data reported can be considered as good proxies
and show the difference among countries in tuition fees charged by main educational institutions and for the majority of students.
Data on short-cycle tertiary programmes are available on line (see StatLink below).
1. Year of reference 2014/15.
2. Tuition fees for foreign students refer to students from outside the European Economic Area.
3. Year of reference 2013/14.
4. Year of reference 2016.
5. Estimates include universities only and exclude ISCED 6, such as postgraduate certificates and diplomas.
6. Tuition fees for foreign students refer to students from countries outside the European Union.
7. Year of reference 2011/12.
Source: OECD (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933804660

302 Education at a Glance 2018: OECD Indicators   © OECD 2018

chapter C

How much do tertiary students pay and what public support do they receive? – INDICATOR C5

Under embargo until 11/09/2018 at 11.00am CEST
Table C5.2. [1/2] Estimated change in the tuition fees charged by tertiary educational institutions

(2005/06 to 2015/16) and recent tuition-fee reforms
Index of change (2005/06 = 100)

OECD

Index of change in the amount of tuition fees for students in tertiary programmes between 2005/06
and 2015/16 (public and private institutions, constant prices, 2005/06 = 100)
Short-cycle tertiary

Bachelor's or equivalent

Master's or equivalent

Doctoral or equivalent

(1)

(2)

(3)

(4)

Australia1, 2

m

117

116

127

Austria1

m

83

83

83

Canada

m

123

88

m

Estonia

m

m

m

m

Countries

Finland

a

a

a

a

Hungary

m

m

m

m

Italy

m

113

m

122

Japan

107

108

105

103

Korea

m

m

m

m

Latvia

65

65

65

65

Luxembourg

75

75

m

75

Netherlands

115

115

115

a

New Zealand

x(2)

121

m

m

Sweden

a

a

a

a

Turkey

a

a

a

a

103

120

98

112

Flemish Comm. (Belgium)

m

m

m

m

French Comm. (Belgium)

m

m

m

m

x(2)

415

m

m

United States3
Economies

England (UK)

Note: This table lists countries for which the calculation of the index of change in tuition fees was possible and/or those countries with information on tertiary
education policy reforms since 2010. The data in Columns 1-5 can be considered as good proxies of the tuition fees trends, although they are based on the weighted
average of the main tertiary programmes and do not cover all educational institutions.						
1. Year of reference 2014/15.						
2. Index of change calculated for public institutions only.						
3. Year of reference 2003/04 instead of 2005/06 and year of reference 2011/12 instead of 2015/16.						
Source: OECD (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933804679

Education at a Glance 2018: OECD Indicators   © OECD 2018

303

C5

chapter C Financial Resources Invested In Education
Under embargo until 11/09/2018 at 11.00am CEST
Table C5.2. [2/2] Estimated change in the tuition fees charged by tertiary educational institutions

(2005/06 to 2015/16) and recent tuition-fee reforms
Index of change (2005/06 = 100)

Reforms implemented since 2010 on tertiary education
Of which, at least some
were combined with
On levels a change in the level
of public subsidies
of tuition
available to students
fees
OECD

C5

Comments

(5)

(6)

(7)

Australia1, 2

yes

yes

Since the introduction of the demand-driven funding system, which came into full effect in 2012, the
Australian Government has provided a subsidy for every eligible domestic student enrolled in a bachelor’s
level course (excluding medicine) at a public university. This policy has significantly increased the number
of students accessing a Commonwealth subsidised place.

Austria1
Canada

no

no

yes

yes

Each jurisdiction sets its own tuition cap for colleges and universities with the exception of a few that do
not have an imposed cap.

Estonia

yes

yes

A new needs-based student support system was introduced in 2013/14. Students from less privileged
families can apply for study allowance (~ EUR 75-220 per month) when studying full-time and if the
period of study has not exceeded the standard period of the curriculum. In addition and starting from
2015, a needs-based special allowance was introduced if the application for the allowance had been
declined and the economic situation of the family changed since. Students are still able to apply for special
study loans from banks. The doctoral allowance for PhD students has not been changed.

Finland

no

no

In 2010-14, there was a tuition fee trial period when it was possible for higher education institutions to
charge fees to foreign students coming from outside EU or the European Economic Area and studying in
university and polytechnic programmes at master's level taught in a foreign language. Of the students
charged tuition fees, almost all received grants covering tuition fees either in full or partially. Some grants
also included a portion to cover some of the cost of living. Higher education institutions awarded grants
primarily based on academic achievement. From academic year 2017/18, tuition fees have been introduced
for students coming from outside the European Union and European Economic Area to study in Finland.

Hungary

yes

yes

Students are either fully financed through a state scholarship, partially financed through a state
scholarship (50% of the cost of the studies) or pay the full cost of studies. In the academic year 2012/13,
the government reduced the number of fully financed places by 27% and increased, more moderately, the
number of places partially financed by the state. This reduction has mainly affected fields of study such
as law and economics.
In the academic year 2012/13, a new student loan programme was launched for students who pay the full
cost of their studies.

Italy

yes

yes

An increase of fees has been possible since 2011/12 for students who have been in the tertiary system
for longer than the regular number of years and since 2013 for doctoral students receiving a scholarship.

Japan
Korea

no

no

yes

yes

no

no

no

no

Countries

National scholarships have been offered since 2012 by combining and expanding the existing scholarships
for low-income students. The annual budget for government-funded scholarships such as the national
scholarships has increased every year and reached almost eight times the 2011 value in 2016.

Latvia
Luxembourg
Netherlands
New Zealand

no

no

yes

no

The 2011 policy reform limits how much an institution may increase their fees and course costs. The level
is set by the government each year and from 2011-15 it has been 4%. It was set at 3% for 2016 and 2% for
2017.
In 2012, there were policy changes aimed at controlling how institutions set compulsory student levies for
non-tuition related services.
From 2018 fee-free tertiary education is progressively being introduced to national students entering
tertiary study for the first-time. By 2024, three years of tertiary education will be free to all national firsttime students.

Sweden

yes

yes

In 2011, tuition fees for non EEA-students were introduced as well as two different scholarship programmes
for paying students.

Turkey

yes

no

As of the academic year 2012/13, students in first education (regular morning programmes) and open
education programmes are not charged tuition fees over the course of the theoretical duration of the
programmes. Tuition fees are paid only by students in public institutions who are enrolled in evening
programmes and those who have not graduated from a programme within the theoretical duration.

United States3

no

no

Flemish Comm. (Belgium)

yes

no

Since 1/1/2015, adult education tuition fees at short-cycle tertiary level increased to EUR 1.50 per teaching
period and the maximum per year increased to EUR 600. From bachelor's to doctorate and equivalent
programmes the annual tuition fees for a full-time student increased from EUR 620 to EUR 890.

French Comm. (Belgium)

yes

no

28 972 students (17% of students eligible for financial support) no longer pay tuition fees (2014/15) and
3 892 students with a low-income background (2.3% of those eligible) benefit from reduced tuition fees.

England (UK)

yes

yes

Economies

Note: This table lists countries for which the calculation of the index of change in tuition fees was possible and/or those countries with information on tertiary
education policy reforms since 2010. The data in Columns 1-5 can be considered as good proxies of the tuition fees trends, although they are based on the weighted
average of the main tertiary programmes and do not cover all educational institutions.						
1. Year of reference 2014/15.						
2. Index of change calculated for public institutions only.						
3. Year of reference 2003/04 instead of 2005/06 and year of reference 2011/12 instead of 2015/16.						
Source: OECD (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933804679

304 Education at a Glance 2018: OECD Indicators   © OECD 2018

chapter C

How much do tertiary students pay and what public support do they receive? – INDICATOR C5

Under embargo until 11/09/2018 at 11.00am CEST
Table C5.3. [1/2] Public loans to students, repayment and remission in tertiary education (2015/16)

OECD

Public loans
Interest rate subsidies

Share of tertiary students who
benefit from a student loan

Average annual gross amount
of loan (in USD) available to
each student

Interest rate during studies

Interest rate after studies

(1)

(2)

(3)

(4)

Australia1, 2

84%

ISCED 5: 4 771; ISCED 6: 4 181;
ISCED 7: 5 385; ISCED 8: 6 171

2.6%

2.6%

Canada3, 4

60%

ISCED 5: 4 399; ISCED 6: 4 458;
ISCED 7: 6 094; ISCED 8: 6 685

No nominal interest rate

5.2%

Chile

4%

ISCED 5: 3 760; ISCED 6: 6 143;
ISCED 7: 9 416; ISCED 8: 9 268

No nominal interest rate

0.02%

Denmark

38%

4 946 (ISCED 5-7 only)

0.04%

0.01%

Estonia

m

3 561 (ISCED 6-8 only)

5.0%

5.0%

Finland5

29%

3 718 (ISCED 6-8 only)

No nominal interest rate

Interest rate agreed with private
bank

Germany6, 7

21%

m

No nominal interest rate

m

Japan8

45%

ISCED 5: 5 937; ISCED 6: 6 074;
ISCED 7: 8 527; ISCED 8: 12 580

No nominal interest rate

0% to 3%

Korea7, 9, 10

m

4 882

2.5% to 2.7%

2.5% to 2.7%

Latvia

9%

2 531

EURIBOR +2.5%

0% to 5%

Luxembourg

a

a

m

EURIBOR +0.5%
(-2% paid by the student)

C5

Countries

Mexico1

2%

19 826

m

m

Netherlands

33%

7 115 (ISCED 5-7 only)

0.1%

0.9%

New Zealand

m

ISCED 5: 5 314; ISCED 6: 6 424;
ISCED 7: 6 663; ISCED 8: 5 702

No nominal interest rate

No nominal interest rate if
New Zealand-based, 5.3% otherwise

Norway

100%

ISCED 5: 8 849; ISCED 6: 8 952;
ISCED 7: 8 519

No nominal interest rate

1.9%

Poland

15%

3 972

No nominal interest rate

0.9%

Slovak Republic

1%

4 795

No nominal interest rate

2.1%

Sweden11

100%

ISCED 5: 7 616; ISCED 6-7: 6 665;
ISCED 8: 4 697

0.6%

0.6%

Switzerland

1%

ISCED 5-6: 4 849; ISCED 7: 7 360;
ISCED 8: 5 216

m

m

Turkey

44%

ISCED 5-6: 3 991; ISCED 7: 7 982;
ISCED 8: 11 974

m

m

United States12, 13

55%

ISCED 5: 2 106; ISCED 6: 4 330;
ISCED 7: 16 363; ISCED 8: 5 984

4.3% to 6.8%

4.3% to 6.8%

Economies
French Comm. (Belgium)

0%

1 549

No nominal interest rate

4.0%

England (UK)14

m

14 997 (ISCED 5 and 6 only)

3.9%

0.9% to 3.9%

Note: Additional data on loan repayments, remission and forgiveness are available on line only (see StatLink below).
1. Reference year 2014/15.
2. Excluding short-cycle tertiary programmes.
3. Only includes information on the federal portion of student financial assistance, which represents 60% of student loans provided in the provinces participating in
the Canada Student Loans Program (CSLP). Figures also exclude the province of Quebec.
4. Reference year 2013/14.
5. Information refers to government-guaranteed private loans.
6. The percentage of students who benefit from a student loan refers to the share of students who are eligible.
7. Reference year 2016.
8. Includes interest-free loan amounts only.
9. The data only include government-funded student loans provided by the Korea Student Aid Foundation such as Income Contingent Student Loans, General
Installment Student Loans, Student Loans for Undergraduates from Rural Areas. Student loans provided by other government ministries have been excluded.
Overlapped beneficiaries have been excluded in each semester.
10. Eligibility rule: Income Contingent Student Loans, if 35 years old or younger, 8th income decile or below, took 12 credits or more and gained 70 points or higher
(maximum 100 points). General Installment Student Loans, if 55 years old or younger, regardless of his or her income level, undergraduate and graduate students,
took 12 credits or more, and gained 70 points or higher (maximum 100 points).
11. Includes loans granted only to citizens from countries in the EU / EEA / Switzerland.
12. Column 3 refers to the 2009 average debt for bachelor’s graduates of 2007/08. Column 8 refers to the average annualised salary in 2009 for 2007/08 graduates.
13. Reference year 2011/12.
14. Includes national and EU domiciled students.
Source: OECD (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933804698

Education at a Glance 2018: OECD Indicators   © OECD 2018

305

chapter C Financial Resources Invested In Education
Under embargo until 11/09/2018 at 11.00am CEST
Table C5.3. [2/2] Public loans to students, repayment and remission in tertiary education (2015/16)
Public loans

C5

OECD

Share of graduates with debt

Average amount of debt at graduation
(in USD)

Annual growth rate (%) of number
of nationals benefiting from a student loan
(2005/06-2015/16)

(5)

(6)

(7)

Countries

(5)

(6)

(7)

Australia1, 2

m

m

ISCED 5: 12.4%; ISCED 6: 5.3%;
ISCED 7: 10.9%; ISCED 8: 0.6%

Canada3, 4

m

ISCED 5: 7 762; ISCED 6-8: 12 856

m

Chile

m

m

m

Denmark

m

m

m

Estonia

a

a

ISCED 6: -19.4%; ISCED 7: -14.8%;
ISCED 8: -16.8%

Finland5

ISCED 6: 50.3%; ISCED 7: 47.0%

ISCED 6: 9 033 ISCED 7: 10 520

3.5% (ISCED 6-8 only)

Germany6, 7

m

m

1.9% (ISCED 5-7 only)

Japan8

m

ISCED 5: 20 868; ISCED 6: 32 172;
ISCED 7: 18 408; ISCED 8: 41 305

ISCED 5: 4.7%; ISCED 6: 4.2%;
ISCED 7: -1.1%; ISCED 8: -7.3%

Korea7, 9, 10

m

m

m

Latvia

0,0

m

-0.1

Luxembourg
Mexico1

a

a

a

100% (ISCED 7-8 only)

ISCED 7: 39 653; ISCED 8: 49 566

ISCED 7: 13.9%; ISCED 8: 10.0%

Netherlands

66.7% (ISCED 5-7 only)

18 413 (ISCED 5-7 only)

6.0% (ISCED 5-7 only)

New Zealand

ISCED 5: 64%; ISCED 6: 78%;
ISCED 7: 62%; ISCED 8: 54%

ISCED 5: 12 342; ISCED 6: 22 671;
ISCED 7: 28 208; ISCED 8: 24 043

ISCED 5: -1.9%; ISCED 6: 3.9%;
ISCED 7: 5.6%; ISCED 8: 4.7%

Norway

m

ISCED 6: 26 257; ISCED 7: 36 638

ISCED 6: 1.5%; ISCED 7: 2.1%

Poland

5%

10 105

-4.5% (ISCED 6-8 only)

1%(ISCED 6-8 only)

5 944

-7.3% (ISCED 6-8 only)

Sweden11

ISCED 5: 30%; ISCED 6: 77%;
ISCED 7: 64%; ISCED 8: 38%

ISCED 5: 12 646; ISCED 6: 21 432;
ISCED 7: 24 374; ISCED 8: 19 042

ISCED 5: 2.5%; ISCED 6-7: 0.1%;
ISCED 8: -18.2%

Switzerland

m

m

-0.1

Turkey

m

m

ISCED 6: 7.0%; ISCED 7: 11.8%;
ISCED 8: 6.3%

United States12, 13

m

24 900

m

French Comm. (Belgium)

m

m

-30.5%

England (UK)14

m

m

4.6% (ISCED 5-6 only)

Slovak Republic

Economies

Note: Additional data on loan repayments, remission and forgiveness are available on line only (see StatLink below).
1. Reference year 2014/15.
2. Excluding short-cycle tertiary programmes.
3. Only includes information on the federal portion of student financial assistance, which represents 60% of student loans provided in the provinces participating in
the Canada Student Loans Program (CSLP). Figures also exclude the province of Quebec.
4. Reference year 2013/14.
5. Information refers to government-guaranteed private loans.
6. The percentage of students who benefit from a student loan refers to the share of students who are eligible.
7. Reference year 2016.
8. Includes interest-free loan amounts only.
9. The data only include government-funded student loans provided by the Korea Student Aid Foundation such as Income Contingent Student Loans, General
Installment Student Loans, Student Loans for Undergraduates from Rural Areas. Student loans provided by other government ministries have been excluded.
Overlapped beneficiaries have been excluded in each semester.
10. Eligibility rule: Income Contingent Student Loans, if 35 years old or younger, 8th income decile or below, took 12 credits or more and gained 70 points or higher
(maximum 100 points). General Installment Student Loans, if 55 years old or younger, regardless of his or her income level, undergraduate and graduate students,
took 12 credits or more, and gained 70 points or higher (maximum 100 points).
11. Includes loans granted only to citizens from countries in the EU / EEA / Switzerland.
12. Column 3 refers to the 2009 average debt for bachelor’s graduates of 2007/08. Column 8 refers to the average annualised salary in 2009 for 2007/08 graduates.
13. Reference year 2011/12.
14. Includes national and EU domiciled students.
Source: OECD (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933804698

306 Education at a Glance 2018: OECD Indicators   © OECD 2018

Under embargo until 11/09/2018 at 11.00am CEST

Under embargo until 11/09/2018 at 11.00am CEST

ON WHAT RESOURCES AND SERVICES IS EDUCATION
FUNDING SPENT?
• From primary to tertiary education, 92% of the spending of educational institutions is devoted to
current expenditure (goods and services consumed within the current year).

INDICATOR C6

• On average across OECD countries, staff compensation comprises the largest share of current
expenditure in non-tertiary education (78%) and tertiary education (68%).

• OECD countries allocate on average 8% of their total education spending to capital expenditure.
The share is higher in tertiary education (12%) than in non-tertiary education (7%). Shares vary
considerably across countries, as well as between public and private educational institutions within
the same country.

Figure C6.1. Share of capital expenditure as a percentage of total expenditure
in public and private institutions (2015)
Primary to tertiary education

United Kingdom

Belgium

Hungary

Portugal

Italy

Austria

Iceland

Sweden

Spain

Ireland

Germany

Canada2

EU22 average

Australia

France

Private institutions

Poland

United States

OECD average

Estonia

Finland

Israel

Luxembourg

Korea

Turkey

Netherlands

Japan

Greece

Lithuania

Latvia

Colombia1

30
25
20
15
10
5
0

Russian Federation

Public institutions

%

1. Year of reference 2016.
2. Primary education includes pre-primary programmes and post-secondary non-tertiary figures are treated as negligible.
Countries are ranked in descending order of the share of capital expenditure in public institutions.
Source: OECD / UIS / Eurostat (2018), Education at a Glance Database, http://stats.oecd.org/. See Source section for more information
and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933804850

Context
How spending is allocated between current and capital expenses can affect the quality of instruction
(through teachers’ salaries, for example), the material conditions under which instruction takes place
(such as expenditure on school maintenance) and the ability of the education system to adjust to
changing demographic and enrolment trends. Decisions on resource allocation can thus influence the
nature of instruction and, by extension, student learning outcomes. Striking a proper balance, given a
country’s educational priorities, is a challenge facing all governments. Comparing the distribution of
educational expenditure across resource categories can shed light on the various organisational and
operational structures that different countries have developed.
This indicator describes the resources and services on which money for education from all funding
sources (governments, international sources and the private sector) is spent. It shows the difference
between current and capital expenditure. Capital expenditure can be driven by rising enrolment,
which often requires construction of new buildings. The indicator also presents details on how current
expenditure is allocated, looking particularly at staff salaries and other related aspects. Current
expenditure is mainly affected by teachers’ salaries (see Indicator D3), but also by the age distribution
of teachers and the size of the non-teaching staff employed in education. Educational institutions do
not only offer instruction. They also provide other services, such as meals, transport, housing and/or
research activities. All these expenditures are captured in this indicator.

308 Education at a Glance 2018: OECD Indicators   © OECD 2018

Under embargo until 11/09/2018 at 11.00am CEST
Other findings

• Staff compensation comprises the largest share of current expenditure at all levels of education.
Four-fifths of staff compensation goes to teachers in non-tertiary education with the remainder
going to other staff. In tertiary education, about one-third of staff compensation goes to other
staff, almost doubling its share in non-tertiary education.

• In non-tertiary education, the share of total expenditure allocated to current expenditures by
public institutions (93%) is larger than that of private institutions (91%). Conversely, at tertiary
levels, private institutions (92%) spend a larger share of total expenditure on current expenditures
than public institutions (87%).

INDICATOR C6

• The share of other staff expenditure varies in non-tertiary institutions, from a high of around 20%
or more in Belgium, the Czech Republic, Estonia, France, Iceland, Lithuania and the United States
to less than 10% in Austria, Colombia, Greece and Luxembourg.

Education at a Glance 2018: OECD Indicators   © OECD 2018

309

chapter C Financial Resources Invested In Education
Under embargo until 11/09/2018 at 11.00am CEST

Analysis

C6

Distribution of educational institutions’ current and capital expenditure by level
Expenditure by educational institutions is composed of current and capital expenditure. Current expenditure
includes spending on school resources used each year for operation of schools, while capital expenditure refers
to spending on the acquisition or maintenance of assets which last longer than one year (see Definitions section
at the end of this indicator). Given the labour-intensive nature of education, current expenditure, particularly
staff compensation, makes up the largest proportion of total education expenditure in OECD countries. In 2015,
an average of 92% of total expenditure by educational institutions in OECD countries was on current expenditure,
across all education levels from primary to tertiary. Across countries, the share of current expenditure for all levels
varies from 79% in Latvia to 97% in Belgium and the United Kingdom (Table C6.1).
The OECD average share of current expenditure is higher in non-tertiary education (93%) than at the tertiary
level (88%). At primary and secondary levels, shares vary from 83% in Latvia to 99% in Greece. At the post-secondary
non-tertiary level, shares vary from 83% in Latvia to 100% in Luxembourg. At the tertiary level, allocations vary
from 52% in Greece to 96% in Finland and Sweden. The share of current expenditure does not differ by more than
5 percentage points, on average, across all education levels. In most countries, the share of current expenditure in
non-tertiary education is greater than at tertiary level. The only countries where the share of current expenditure is
greater at tertiary level than in non-tertiary education are Finland, Ireland, Israel, Norway and Sweden.
Differences in expenditure allocation across countries reflect how various levels of education are organised and
the degree to which countries have invested in the construction of new buildings, which often becomes necessary
when enrolments increase (this has been particularly pronounced at the tertiary level). As presented in Table C6.1,
the share of capital expenditure is generally higher in tertiary institutions, where the OECD average is 12%, than
in non-tertiary institutions, where the OECD average is 7%. Capital expenditure on tertiary education reaches highs
of 39% in Colombia, 48% in Greece and 31% in Latvia. In non-tertiary education, Japan, Latvia and Norway allocate
the highest shares of education budgets to capital expenditure across countries with available data.
Differences in the relative shares of current and capital expenditure at the tertiary level can be explained in part
by the ownership arrangement of university buildings. For instance, in various cases, the buildings and land used
for education may be owned by the institution, used free of charge or rented. Therefore the amount of current
and capital expenditure reported by countries partially depends on the physical infrastructure arrangement that
prevails in a given country (see Box B6.1 in [OECD, 2012[1]]).
How current expenditure is allocated
Current expenditure by educational institutions can be further subdivided into three broad functional categories:
1) compensation of teachers; 2) compensation of other staff; and 3) other current expenditure (for example, teaching
materials and supplies, maintenance of school buildings, providing students’ meals and renting school facilities).
The relative shares of these categories typically do not change much from year to year. Current and projected changes
in enrolments, changes to salaries of education personnel and the costs of maintenance of education facilities can
affect not only the amounts allocated, but also the shares allotted to each category.
The salaries of teachers and other staff employed in education comprise the largest share of current expenditure in
non-tertiary and tertiary education. However, salaries represent a larger share in non-tertiary education (78%) than
at the tertiary level (68%), a difference of 10 percentage points. OECD countries spend on average 63% of the total
amount of current expenditure on teacher compensation and 15% on paying other staff in non-tertiary education,
leaving 22% for other current expenditure For tertiary education, 42% of current expenditures go to pay teachers,
26% to other staff, devoting 32% to other expenditures (Table C6.2 and Figure C6.2).
There is significant variation within countries in how current expenditure is allocated across levels of education.
Colombia and Iceland are the only countries to report a greater share of current expenditure allocated to staff
compensation at the tertiary level than at any other level (Table C6.2). Finland, France and Poland allocate equal
shares to staff compensation at the tertiary level and in non-tertiary education. For all other countries, tertiary
education receives the lowest share of total current spending allocated to staff compensation. In Italy and Japan,
the differences between tertiary and non-tertiary categories exceed 20 percentage points. When looking at all
education levels together, common patterns are observed in Belgium, Colombia, Greece, Luxembourg and Portugal.

310 Education at a Glance 2018: OECD Indicators   © OECD 2018

chapter C

On what resources and services is education funding spent? – INDICATOR C6

Under embargo until 11/09/2018 at 11.00am CEST
They tend to devote a larger share of current educational expenditure to staff compensation (above 82%) and
less to other contracted and purchased services, such as support services (e.g. building maintenance), ancillary
services (e.g. meal programmes) and rent paid for school buildings and other facilities.

C6

Figure C6.2. Composition of current expenditure in public and private
educational institutions (2015)
Primary to tertiary institutions
Compensation of teachers
Compensation of all staff (if breakdown not available)

Czech Republic
Italy

Sweden

Finland

Japan

Estonia

Slovak Republic

Latvia

Korea

Finland

Iceland

Poland

Sweden

United States

Austria

Australia

Austria

United Kingdom

EU22 average

Germany

2

Slovenia

OECD average

Russian Federation

Hungary
Lithuania

France

Canada2

Korea

Hungary

Australia

United Kingdom

Estonia

Canada

Latvia

Norway

Turkey

Slovenia

EU22 average

Netherlands

Israel

Portugal

Luxembourg

Iceland

Spain

Poland

Belgium

France

Greece

Colombia1

OECD average

Tertiary

%

100
90
80
70
60
50
40
30
20
10
0

Netherlands

Spain

United States

Germany

Israel

Turkey

Norway

Japan

Russian Federation

Italy

Portugal

Luxembourg

Colombia1

Greece

Belgium

Lithuania

Primary, secondary and post-secondary non-tertiary

%

100
90
80
70
60
50
40
30
20
10
0

Compensation of non-teaching staff
Other current expenditure

1. Year of reference 2016.
2. Primary education includes pre-primary programmes.
Countries are ranked in descending order of the share of all staff compensation.
Source: OECD / UIS / Eurostat (2018), Table C6.2. See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag2018-36-en).
1 2 https://doi.org/10.1787/888933804869

The variation between levels of education in the share of current expenditure allocated under “other current
expenditure” reflects to some extent the differences in the size of administrative systems (for instance, the number
of employees or the equipment available to the administrative staff across these levels). The cost of facilities and
equipment is generally higher in tertiary education than at other levels. In addition, in some countries, tertiary
institutions may be more likely to rent premises, which can account for a substantial share of current expenditure.
Education at a Glance 2018: OECD Indicators   © OECD 2018

311

chapter C Financial Resources Invested In Education
Under embargo until 11/09/2018 at 11.00am CEST

C6

The differences among countries in the shares allocated to paying non-teaching staff likely reflect the degree to which
non-teaching education personnel (such as principals, guidance counsellors, bus drivers, school nurses, janitors and
maintenance workers) are included in the category “non-teaching staff”. Compensation of staff involved in research
and development at the tertiary level may also explain some of the differences between countries and across levels
of education in this category (as in Finland and Sweden, see Indicator C1).
Distribution of current and capital expenditure by public versus private educational institutions
Public and private institutions allocate their spending to either current or capital expenditure in a similar way,
although differences are more marked in tertiary education than in non-tertiary education. Across OECD countries
in non-tertiary education, the average share of current expenditure in private institutions is (91%), 2 percentage
points lower than that of public institutions (93%). However, at the tertiary level, the share of current expenditure
in private institutions (92%) is 5 percentage points higher than that of public institutions (87%). This difference at
the tertiary level is more marked in Colombia, Greece and Lithuania. In Austria, Estonia, Hungary, Ireland, Italy and
Japan, the share of current expenditure is higher in public institutions.
Public and private institutions also differ in how current expenditure is distributed (Table C6.3). On average, across
OECD countries in non-tertiary education, the share of current expenditure devoted to staff compensation in
public institutions (80%) is 8 percentage points higher than that of private institutions (72%). This gap is most
pronounced in Greece, Italy, Portugal, the Russian Federation and Turkey, with differences of 20 percentage points
or more between the two sectors. The pattern is reversed in the Czech Republic, Finland, the Netherlands, Poland
and the Slovak Republic, where private institutions allocate a greater share of their current expenditure to staff
compensation than public institutions. At the tertiary level, public institutions also allocate a higher share of their
current spending to staff compensation (68% on average across OECD countries) than do private institutions (65%).
The fact that private institutions typically devote a lower share of current expenditure to paying staff can be
explained by factors inherent to each country’s educational system. It may be the case that private institutions
are more likely to contract services from external providers. They may more often rent school buildings and other
facilities (as opposed to functioning in state-owned properties), and they may be at a disadvantage when purchasing
teaching materials, as they cannot benefit from the same economies of scale in procurement as the public sector.
Public and private institutions allocate a very similar share of their total expenditure to capital investment (8%).
However, the share varies to a large extent by country and between public and private institutions (Figure C6.1).
Public institutions in Colombia, Latvia and Lithuania allocate the highest shares of spending to capital, reaching
more than 14% of total expenditure from primary to tertiary education. Public institutions spend the lowest share
on capital in Austria, Belgium, Hungary, Italy, Portugal, Sweden and the United Kingdom (below 6%). The variation
across countries is even higher for private institutions, with private institutions in Colombia, Latvia, and Turkey
spending more than 19% of their total expenditure on capital, and Greece and Iceland spending below 2%. The
difference between public and private institutions in the share of their allocations to capital expenditure is below
4 percentage points for two-thirds of the countries with data available. Latvia has the largest differences in the share
of capital expenditure, and its private institutions spend proportionally more than its public institutions.

Definitions
Capital expenditure refers to spending on assets that last longer than one year, including construction, renovation
or major repair of buildings, and new or replacement equipment. The capital expenditure reported here represents
the value of educational capital acquired or created during the year in question (i.e. the amount of capital formation),
regardless of whether the capital expenditure was financed from current revenue or through borrowing. Neither
current nor capital expenditure includes debt servicing.
Current expenditure refers to spending on goods and services consumed within the current year and requiring
recurrent production in order to sustain educational services. Other current expenditure (i.e. not on paying staff) by
educational institutions includes expenditure on subcontracted services, such as support services (e.g. maintenance
of school buildings), ancillary services (e.g. preparation of meals for students) and rental of school buildings and
other facilities. These services are obtained from outside providers, unlike the services provided by education
authorities or by educational institutions using their own personnel.
Staff compensation (including teachers and non-teaching staff, see below) includes: 1) salaries (i.e. gross salaries
of educational personnel, before deduction of taxes, contributions for retirement or healthcare plans, and other
contributions or premiums for social insurance or other purposes); 2) expenditure on retirement (actual or imputed

312 Education at a Glance 2018: OECD Indicators   © OECD 2018

On what resources and services is education funding spent? – INDICATOR C6

chapter C

Under embargo until 11/09/2018 at 11.00am CEST
expenditure by employers or third parties to finance retirement benefits for current educational personnel);
and 3) expenditure on other non-salary compensation (healthcare or health insurance, disability insurance,
unemployment compensation, maternity and childcare benefits and other forms of social insurance). The “teachers”
category includes only personnel who participate directly in the instruction of students. The “non‑teaching staff”
category includes other pedagogical, administrative and professional personnel as well as support personnel
(e.g. head teachers, other administrators of schools, supervisors, counsellors, school psychologists and health
personnel, librarians, building operations and maintenance staff).

Methodology
Calculations cover expenditure by public institutions or, where available, by both public and private institutions.
Please see the OECD Handbook for Internationally Comparative Education Statistics 2018: Concepts, Standards, Definitions
and Classification (OECD, 2018[2]) and Annex 3 for country-specific notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Lithuania was not an OECD member at the time of preparation of this publication. Accordingly, Lithuania does not
appear in the list of OECD members and is not included in the zone aggregates.

Sources
Data refer to the financial year 2015 (unless otherwise specified) and are based on the UNESCO, the OECD and
Eurostat (UOE) data collection on education statistics administered by the OECD in 2017 (for details see Annex 3 at
http://dx.doi.org/10.1787/eag-2018-36-en). Data from Argentina, China, Colombia, India, Indonesia, Saudi Arabia
and South Africa are from the UNESCO Institute of Statistics (UIS).

Note regarding data from Israel
The statistical data for Israel are supplied by and are under the responsibility of the relevant Israeli authorities. The use
of such data by the OECD is without prejudice to the status of the Golan Heights, East Jerusalem and Israeli settlements
in the West Bank under the terms of international law.

References
OECD (2018), OECD Handbook for Internationally Comparative Education Statistics 2018: Concepts, Standards, Definitions [2]
and Classifications, OECD Publishing, Paris, https://doi.org/10.1787/9789264304444-en.
OECD (2012), Education at a Glance 2012: OECD Indicators, OECD Publishing, Paris, http://dx.doi.org/10.1787/eag-2012-en. [1]

Indicator C6 Tables
1 2 https://doi.org/10.1787/888933804774

Table C6.1 Share of current and capital expenditure, by education level (2015)
Table C6.2 Current expenditure, by resource category (2015)
Table C6.3 Share of current expenditure, by resource category and type of institution (2015)
Cut-off date for the data: 18 July 2018. Any updates on data can be found on line at http://dx.doi.org/10.1787/eag-data-en. More breakdowns can
also be found at http://stats.oecd.org/, Education at a Glance Database.

Education at a Glance 2018: OECD Indicators   © OECD 2018

313

C6

chapter C Financial Resources Invested In Education
Under embargo until 11/09/2018 at 11.00am CEST
Table C6.1. Share of current and capital expenditure, by education level (2015)
Distribution of current and capital expenditure by educational institutions from public and private sources, by level of education
Secondary
Lower secondary

Primary

C6

Upper secondary

Post-secondary
non‑tertiary

Primary,
secondary and
post-secondary
non-tertiary

Primary
to tertiary

Tertiary

Partners

OECD

Current Capital Current Capital Current Capital Current Capital Current Capital Current Capital Current Capital
(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

(13)

(14)

Australia
Austria
Belgium
Canada1
Chile
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United Kingdom
United States

93
94
96
93d
m
88
m
94
88
93
94
99
96
94
93
89
96
86
89
83
94
m
89
m
86
94
97
96
92
97
94
m
91
97
92

7
6
4
7d
m
12
m
6
12
7
6
1
4
6
7
11
4
14
11
17
6
m
11
m
14
6
3
4
8
3
6
m
9
3
8

91
97
98
x(1)
m
88
m
93
88
92
95
99
96
95
93
x(5)
96
85
91
83
93
m
89
m
86
97
97
97
92
97
94
m
91
98
92

9
3
2
x(2)
m
12
m
7
12
8
5
1
4
5
7
x(6)
4
15
9
17
7
m
11
m
14
3
3
3
8
3
6
m
9
2
8

91
98
98d
93
m
92
m
86
92d
92
90
99
97
97
94
93d
97
89d
91
83
93
m
91
m
89
96
89d
95
94
97d
93
m
89
98
92

9
2
2d
7
m
8
m
14
8d
8
10
1
3
3
6
7d
3
11d
9
17
7
m
9
m
11
4
11d
5
6
3d
7
m
11
2
8

96
99
x(5)
m
m
m
m
89
x(5)
91
93
m
98
96
m
96
85
x(5, 11)
a
83
100
a
94
m
89
95
x(5, 11)
97
a
x(5)
94
m
a
a
90

4
1
x(6)
m
m
m
m
11
x(6)
9
7
m
2
4
m
4
15
x(6, 12)
a
17
0
a
6
m
11
5
x(6, 12)
3
a
x(6)
6
m
a
a
10

92
97
97
93d
m
m
m
92
89
92
93
m
96
95
93
91
96
87
90
83
93
m
90
m
87
95
95
96
93
97
94
m
90
98
92

8
3
3
7d
m
m
m
8
11
8
7
m
4
5
7
9
4
13
10
17
7
m
10
m
13
5
5
4
7
3
6
m
10
2
8

89
92
95
93
m
m
m
88
96
91
91
52
89
95
94
95
90
87d
88
69
75
m
89
m
91
84
93d
m
90
88
96
m
78
94
90

11
8
5
7
m
m
m
12
4
9
9
48
11
5
6
5
10
13d
12
31
25
m
11
m
9
16
7d
m
10
12
4
m
22
6
10

91
95
97
93d
m
m
m
90
91
92
92
m
95
95
93
92
95
87
89
79
90
m
89
m
88
92
94
m
92
94
95
m
86
97
91

9
5
3
7d
m
m
m
10
9
8
8
m
5
5
7
8
5
13
11
21
10
m
11
m
12
8
6
m
8
6
5
m
14
3
9

OECD average
EU22 average

93
94

7
6

93
94

7
6

93
93

7
7

m
m

m
m

93
94

7
6

88
87

12
13

92
92

8
8

Argentina
Brazil
China
Colombia2
Costa Rica
India
Indonesia
Lithuania

m
m
m
91
m
m
m

m
m
m
9
m
m
m

m
m
m
94
m
m
m

m
m
m
6
m
m
m

m
m
m
94d
m
m
m

m
m
m
6d
m
m
m

m
m
m
x(5)
m
m
m

m
m
m
x(6)
m
m
m

m
m
m
93
m
m
m

m
m
m
7
m
m
m

m
m
m
61
m
m
m

m
m
m
39
m
m
m

m
m
m
83
m
m
m

m
m
m
17
m
m
m

94

6

94

6

93d

7

92

8

94

6

73

27

86

14

Russian Federation

x(5)

x(6)

x(5)

x(6)

93d

7d

x(5)

x(6)

93

7

88

12

91

9

Saudi Arabia

m

m

m

m

m

m

m

m

m

m

m

m

m

m

South Africa

m

m

m

m

m

m

m

m

m

m

m

m

m

m

G20 average

m

m

m

m

m

m

m

m

m

m

m

m

m

m

Note: Some levels of education are included with others. Refer to “x” code for details.
1. Primary education includes pre-primary programmes. And post-secondary non-tertiary figures are treated as negligible.
2. Year of reference 2016.
Source: OECD / UIS / Eurostat (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933804793

314 Education at a Glance 2018: OECD Indicators   © OECD 2018

chapter C

On what resources and services is education funding spent? – INDICATOR C6

Under embargo until 11/09/2018 at 11.00am CEST
Table C6.2. Current expenditure, by resource category (2015)
Distribution of current expenditure by educational institutions from public and private sources as a percentage
of total current expenditure
Primary to tertiary

Other
staff

Total

Other current
expenditure

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

34
61
47
38
m
m
m
56
34
42
x(7)
67
x(7)
45
m
x(7)
36
x(7)
37

28
5
29
29
m
m
m
7
29
38
x(7)
22
x(7)
29
m
x(7)
22
x(7)
22

38
33
24
34
m
m
m
37
36
20
33
11
38
26
m
30
42
41d
40

52
64
64
53d
m
m
m
50
46
54
x(11)
87
x(11)
51
m
x(11)
59
x(11)
51

20
7
22
21d
m
m
m
18
18
26
x(11)
6
x(11)
22
m
x(11)
19
x(11)
19

x(3)

72

28

x(7)

x(7)

33

x(11)

x(11)

81
m
x(3)
m
x(3)
x(3)
76
54
x(3)
71
x(3)
m
x(3)
64
54

5
m
x(3)
m
x(3)
x(3)
11
14
x(3)
10
x(3)
m
x(3)
11
27

86
m
80
m
83
75
87
68
78
81
67
m
82
75
81

14
m
20
m
17
25
13
32
22
19
33
m
18
25
19

19
m
x(7)
m
x(7)
x(7)
x(7)
m
x(7)
53
x(7)
m
x(7)
36
30

53
m
x(7)
m
x(7)
x(7)
x(7)
m
x(7)
21
x(7)
m
x(7)
28
35

28
m
30
m
32
25
28d
m
31
26
35
m
31
37
36

73
m
x(11)
m
x(11)
x(11)
x(11)
m
x(11)
66
x(11)
m
x(11)
56
44

11
m
x(11)
m
x(11)
x(11)
x(11)
m
x(11)
13
x(11)
m
x(11)
16
30

72
71
86
74d
m
m
m
68
64
80
77
92
75
73
m
79
78
76
70
70
84
m
77
m
79
75
83
m
76
79
67
m
78
72
74

28
29
14
26d
m
m
m
32
36
20
23
8
25
27
m
21
22
24
30

x(3)

62
67
76
66
m
m
m
63
64
80
67
89
62
74
m
70
58
59d
60
67
72
m
70
m
68
75
72d
m
69
74
65
m
69
63
64

OECD average
EU22 average

63
64

15
14

78
77

22
23

42
m

26
m

68
70

32
30

58
m

18
m

76
76

24
24

Argentina
Brazil
China
Colombia2
Costa Rica
India
Indonesia
Lithuania

m
m
m
82
m
m
m

m
m
m
7
m
m
m

m
m
m
89
m
m
m

m
m
m
11
m
m
m

m
m
m
x(7)
m
m
m

m
m
m
x(7)
m
m
m

m
m
m
3
m
m
m

m
m
m
x(11)
m
m
m

m
m
m
x(11)
m
m
m

19

82

18

34

33

33

53

24

m
m
m
91
m
m
m
77

m
m
m
9
m
m
m

63

m
m
m
97
m
m
m
67

23

Russian Federation

x(3)

x(3)

83

17

x(7)

x(7)

67

33

x(11)

x(11)

77

23

Saudi Arabia

m

m

m

m

m

m

m

m

m

m

m

m

South Africa

m

m

m

m

m

m

m

m

m

m

m

m

G20 average

m

m

m

m

m

m

m

m

m

m

m

m

Total

(4)

23
26
11
21d
m
38
m
30
36
20
18
7
21
27
m
18
16
16
25

Other
staff

(3)

77
74
89
79d
m
62
m
70
64
80
82
93
79
73
m
82
84
84
75

Teachers

(2)

16
8
19
15d
m
19
m
23
12
22
x(3)
3
x(3)
20
m
x(3)
18
x(3)
17

Total

(1)

61
66
69
64d
m
43
m
47
52
58
x(3)
90
x(3)
53
m
x(3)
66
x(3)
58

Other
staff

Teachers

Staff compensation

Australia
Austria
Belgium
Canada1
Chile
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United Kingdom
United States

Teachers
OECD
Partners

Tertiary
Staff compensation

Other current
expenditure

Staff compensation

Other current
expenditure

Primary, secondary and post-secondary
non-tertiary

30
16
m
23
m
21
25
17
m
24
21
33
m
22
28
26

Note: Some levels of education are included with others. Refer to “x” code in Table C6.1 for details.
1. Primary education includes pre-primary programmes.
2. Year of reference 2016.
Source: OECD / UIS / Eurostat (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933804812

Education at a Glance 2018: OECD Indicators   © OECD 2018

315

C6

chapter C Financial Resources Invested In Education
Under embargo until 11/09/2018 at 11.00am CEST
Table C6.3. Share of current expenditure, by resource category and type of institution (2015)
Distribution of current expenditure by educational institutions
Primary, secondary and post-secondary non-tertiary

Tertiary
Compensation of staff as a percentage
of current expenditure

Compensation of staff as a percentage
of current expenditure

Share of current
expenditure
Compensation Compensation
in total
of teachers
of other staff
expenditure

C6

Share of current
expenditure
Total
Compensation Compensation
in total
compensation
of teachers
of other staff
expenditure

Total
compensation

Partners

OECD

Public Private Public Private Public Private Public Private Public Private Public Private Public Private Public Private
(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

(13)

(14)

(15)

(16)

95
97
95
93d
m
89
m
91
89
92
95
99
98
95
93
90
96
87
89

86
98
98
94d
m
25
m
96
95
93
88
99
92
100
100
97
93
86
94

62
66
68
65d
m
43
m
47
52
59
x(7)
92
x(7)
53
74
x(7)
67
x(7)
58

58
67
71
52d
m
50
m
51
48
53
x(8)
50
x(8)
53
m
x(8)
42
x(8)
59

15
8
21
15d
m
16
m
24
12
22
x(7)
2
x(7)
20
10
x(7)
18
x(7)
18

19
4
18
20d
m
27
m
14
18
20
x(8)
23
x(8)
17
m
x(8)
7
x(8)
13

77
74
89
80d
m
59
m
71
64
81
83
94
79
73
84
85d
86
85
76

77
71
89
71d
m
77
m
65
66
73
76
73
77
70
m
73d
49
73
72

89
92
95
92
m
90
m
89
96
91
91
52
90
94
94
86
90
89d
87

90
91
95
100
m
m
m
88
97
91
92
100
87
100
92
95
88
86d
89

34
61
49
37
m
32
m
45
32
40
x(15)
67
x(15)
45
60
x(15)
37
x(15)
29

42
60
46
38
m
m
m
59
43
53
x(16)
a
x(16)
45
m
x(16)
32
x(16)
41

28
6
28
29
m
21
m
8
31
41
x(15)
22
x(15)
29
25
x(15)
22
x(15)
26

39
3
29
24
m
m
m
7
26
22
x(16)
a
x(16)
29
m
x(16)
18
x(16)
20

62
67
77
67
m
53
m
53
62
81
67
89
61
74
85
64
59
55d
55

81
63
75
62
m
m
m
66
69
75
62
a
69
74
m
71
51
62d
62

83

84

x(7)

x(8)

x(7)

x(8)

72

72

67

69

x(15)

x(16)

x(15)

x(16)

68

67

92
98
89
m
86
96
96
95
93
98
94
90
92
98
92

98
m
97
m
m
80
89
100
m
95
94
m
83
98
92

82
80
x(7)
m
x(7)
x(7)
82
53
x(7)
73
39
72
x(7)
67
54

69
m
x(8)
m
x(8)
x(8)
46
63
x(8)
64
33
m
x(8)
62
52

4
12
x(7)
m
x(7)
x(7)
11
14
x(7)
9
12
14
x(7)
10
27

14
m
x(8)
m
x(8)
x(8)
12
14
x(8)
11
8
m
x(8)
12
26

86
92
80
m
81
75
93
67
78
83
68
86
86
76
81

83
m
86
m
m
76
58
77
61
75
66
m
58
74
78

75
93
89
m
90
83
92d
65
90
87
96
90
77
a
90

a
m
93
m
98
93
96d
m
m
95
97
m
79
94
90

19
57
x(15)
m
x(15)
x(15)
x(15)
28
x(15)
57
x(15)
50
x(15)
a
31

a
m
x(16)
m
x(16)
x(16)
x(16)
m
x(16)
35
x(16)
m
x(16)
36
28

53
14
x(15)
m
x(15)
x(15)
x(15)
20
x(15)
21
x(15)
26
x(15)
a
35

a
m
x(16)
m
x(16)
x(16)
x(16)
m
x(16)
20
x(16)
m
x(16)
28
34

72
72
69
m
68
75
75
49
71
78
65
76
75
a
66

a
m
77
m
66
71
62
m
42
55
62
m
53
63
62

93
94

91
91

64
64

m
55

14
13

m
14

80
78

72
72

87
86

92
92

m
m

m
m

m
m

m
m

68
69

65
64

Argentina
Brazil
China
Colombia2
Costa Rica
India
Indonesia
Lithuania

87
97
m
96
100
m
m

m
m
m
88
m
m
m

51
x(7)
m
85
75
m
m

m
m
m
78
m
m
m

17
x(7)
m
8
4
m
m

m
m
m
4
m
m
m

67
78
m
93
78
m
m

m
m
m
81
m
m
m

96
96
m
51
100
m
m

m
m
m
70
m
m
m

58
x(15)
m
x(15)
x(15)
m
m

m
m
m
x(16)
m
m
m

29
x(15)
m
x(15)
x(15)
m
m

m
m
m
x(16)
m
m
m

88
81
m
93
100
m
m

m
m
m
100
m
m
m

94

86

63

60

19

17

83

77

72

92

34

28

34

28

68

56

Russian Federation

93

96

x(7)

x(8)

x(7)

x(8)

84d

62

88

96

x(15)

x(16)

x(15)

x(16)

67

59

Australia
Austria
Belgium
Canada1
Chile
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United Kingdom
United States
OECD average
EU22 average

Saudi Arabia

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

South Africa

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

G20 average

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

Note: Some levels of education are included with others. Refer to “x” code in Table C6.1 for details.
1. Primary education includes pre-primary programmes.
2. Year of reference 2016.
Source: OECD / UIS / Eurostat (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933804831

316 Education at a Glance 2018: OECD Indicators   © OECD 2018

Under embargo until 11/09/2018 at 11.00am CEST

Under embargo until 11/09/2018 at 11.00am CEST

WHICH FACTORS INFLUENCE TEACHERS’ SALARY COST?
• The salary cost of teachers per student is calculated using four factors in this analysis: teachers’

INDICATOR C7

salaries, instruction time of students, teaching time of teachers and estimated class size (see
Definitions section at the end of this indicator). Different levels of salary cost of teachers per student
result from various different combinations of these four factors.

• On average across OECD countries, the salary cost of teachers per student increases from USD 2 936
in primary education to USD 3 604 in lower secondary education.

• The two main factors influencing the level of teachers’ salary cost are teachers’ salaries and
estimated class size. The relationship between these two factors is positive, meaning that countries
with higher teacher salaries tend to have larger estimated class sizes. This reflects the choice some
countries have to make between increasing teachers’ salaries and hiring more teachers.

Figure C7.1. Annual salary cost of teachers per student in public institutions,
by level of education (2016)
USD converted using PPPs for private consumption
Primary

Lower secondary

Upper secondary

Luxembourg
Switzerland
Slovenia
Austria
Germany
Flemish Comm. (Belgium)
French Comm. (Belgium)
Norway
Finland
Spain
Denmark
Australia
Portugal
Netherlands
Ireland
United States
Canada
Japan
OECD average
Italy
Iceland
Greece
Israel
Poland
France
Hungary
Estonia
Czech Republic
Chile
Slovak Republic
Turkey
Latvia
Mexico

USD

12 000
10 000
8 000
6 000
4 000
2 000
0

Countries and economies are ranked in descending order of the annual salary cost of teachers per student in lower secondary education.
Source: OECD (2018), Table C7.1. See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/
eag-2018-36-en).
1 2 https://doi.org/10.1787/888933804964

Context
Governments have become increasingly interested in the relationship between the amount of resources
devoted to education and student learning outcomes. They seek to provide more and better education
for their population, while ensuring that public funding is used efficiently, particularly when public
budgets are tight. Teachers’ compensation usually accounts for the largest share of expenditure on
education and thus of expenditure per student (Box C7.1). The salary cost of teachers, as calculated
in this indicator, is a function of students’ instruction time, teachers’ teaching time, teachers’ salaries
and estimated class size (see Methodology section at the end of this indicator).
Differences among countries in these four factors may explain differences in the level of expenditure
per student. Similarly, a given level of expenditure may be associated with different combinations
of these factors. This indicator examines the choices countries make when investing their resources
in primary and secondary education and explores how different policy choices related to these four
factors affect the salary cost of teachers.
The salary cost of teachers per student can be affected by other variables not directly assessed in
this indicator, such as demographic changes. For example, in countries where enrolments have been
declining in recent years, class size would also shrink (assuming all other factors remain constant),
unless there is a simultaneous drop in the number of teachers as well.

318 Education at a Glance 2018: OECD Indicators   © OECD 2018

Under embargo until 11/09/2018 at 11.00am CEST
Other findings

• Similar levels of expenditure among countries can mask a variety of contrasting policy choices.
For example, Australia and Portugal have very similar teachers’ salary costs in lower secondary
education, but teachers are better paid in Australia than in Portugal while estimated class size is
smaller in Portugal than in Australia. Theoretically, if Portugal increased its estimated class size by
five students, teachers’ salaries could be equivalent to those in Australia with no increase in public
spending.

INDICATOR C7

• The ranking by salary cost of teachers per student changes considerably for a few countries when
expressed as a percentage of GDP per capita rather than value in USD. For example, Luxembourg
has by far the highest salary cost of teachers per student in lower secondary education: USD 11 560,
over three times the OECD average of USD 3 604. However, this cost represents 11.2% of the
country’s GDP per capita, which is only the tenth highest across OECD countries.

• Given a fixed level of salary cost, a decrease in class size can be compensated by a decrease in
teachers’ salary, a decrease in instruction time or an increase in teaching time. For example, in
Australia, in order to decrease estimated class size by one student and keep the salary cost per
student constant, teacher salaries would have to decrease by USD 3 600, annual instruction time
would have to decrease by 63 hours, or annual teaching time would have to increase by 54 hours.
Note
The salary cost of teachers per student is estimated based on values for statutory salaries of
teachers after 15 years of experience and the most prevalent qualifications (see Indicator D3),
theoretical instruction time of students (see Indicator D1) and statutory teaching time of teachers
(see Indicator D4). This measure may differ from the actual salary cost of teachers, as a result of the
combination of actual average values for these four factors.
The use of statutory salaries means that the level of qualifications and the ageing of the teaching force
are not taken into account in this indicator. As teacher salaries tend to vary according to experience
and qualifications, an older or more qualified teaching force can lead to a higher salary cost without
changes to any of the four factors analysed in this indicator.

Education at a Glance 2018: OECD Indicators   © OECD 2018

319

chapter C Financial and Human Resources Invested In Education
Under embargo until 11/09/2018 at 11.00am CEST

Analysis
Variation in the salary cost of teachers per student by level of education

C7

On average across OECD countries and economies, the salary cost of teachers is USD 2 936 per primary student,
USD 3 604 per lower secondary student and USD 3 723 per general upper secondary student. Each of these averages
masks a wide range of salary costs across countries. For example, in primary education, the salary cost of teachers
per student in Luxembourg (USD 10 265) is over 14 times higher than in Latvia (USD 758). Higher salary costs are
a result of higher teachers’ salaries and/or of more teachers per student, which is itself pushed up by smaller classes,
more hours of required instruction time for students or fewer teaching hours for teachers.
The general increase in cost between primary and lower secondary education is the result of increases in teachers’
salaries and in instruction time of students, as well as a decrease in teaching time, all of which push up the cost.
In 2016, the OECD average statutory salary for teachers with 15 years of experience was USD 44 397 at lower
secondary level, around USD 2 200 higher than the salary of teachers at primary level. Moreover, the average
annual instruction time in lower secondary education was 118 hours higher than in primary education, while
the teaching time was 78 hours lower, implying that more teachers are needed to teach a given number of pupils.
Contrary to the other factors, estimated class size tends to increase between primary and lower secondary
education, which partially offsets the increase in cost between the two levels (the OECD average estimated class
size increases from 15 students at primary level to 16 students at lower secondary). However, in general, the
effect of the larger class size is not enough to offset the increase in cost caused by the other three factors. Chile
and Mexico are the only OECD countries where larger estimated class sizes in lower secondary education lead
to a lower salary cost of teachers per student at that level than at primary level (Tables C7.5a and b, available
on line).
In a few countries, the learning environment and the organisation of schools are relatively similar between primary
and lower secondary education. For example, in 2016, the difference between the salary cost of teachers per student
in primary and lower secondary was of less than USD 150 in Canada, Hungary, Iceland and the United States. The
greatest difference between primary and lower secondary education was over USD 3 700 in Slovenia (Table C7.1).
Variation in the salary cost of teachers per student after accounting for countries’ wealth
The level of the salary cost of teachers per student is positively correlated with countries’ GDP per capita, so it is
important to also take into account relative wealth when comparing across countries. On average across OECD
countries, the salary cost of teachers per student represents 6.9% of GDP per capita at primary level, 8.7% at lower
secondary level and 8.6% in general programmes at upper secondary level (Table C7.1).
The ranking of a few countries changes once GDP per capita is taken into account. For example, Poland’s salary
cost of teachers per student in primary education is below the OECD average, at USD 2 183. However, this amount
represents 8.0% of the country’s GDP per capita, above the OECD average of 6.9%. The opposite happens in
Luxembourg. Because of its high teachers’ salaries, Luxembourg has by far the highest salary cost of teachers per
student in lower secondary education: USD 11 560, over three times the OECD average of USD 3 604. However,
this cost represents 11.2% of the country’s GDP per capita, which is only the tenth highest across OECD countries.
Contribution of each factor to the level of the salary cost of teachers per student
The level of the salary cost of teachers per student is determined by four factors: teachers’ salaries, instruction time,
teaching time and estimated class size. The impact of the first factor, teachers’ salaries, is direct: higher salaries lead
to higher salary costs. The other three factors affect the salary cost by changing the number of teachers needed,
assuming that the number of students enrolled is constant. If instruction time increases or teaching time decreases,
more teachers must be hired to keep class size constant. Similarly, more teachers must be hired in order to decrease
class size while keeping everything else constant.
By comparing a country’s salary cost to the OECD average, it is possible to determine the contribution of each of
the four factors to the difference from the average. In other words, it is possible to assess whether a given salary
cost is above average because of higher salaries, higher instruction time, lower teaching time, smaller class sizes or a
combination of these four factors. Changes to one of these factors may require compensating trade-offs among the
other factors in order to keep the total salary cost constant (Box C7.2).

320 Education at a Glance 2018: OECD Indicators   © OECD 2018

Which factors influence teachers’ salary cost? – INDICATOR C7

chapter C

Under embargo until 11/09/2018 at 11.00am CEST

Figure C7.2. Contribution of various factors to salary cost of teachers per student in
public institutions, lower secondary education (2016)
USD converted using PPPs for private consumption
Contribution of estimated class size
Contribution of teaching time
Contribution of instruction time
USD

High salary cost

10 000

Contribution of teachers’ salaries
Difference of salary cost of teachers per student
from OECD average
Moderately low
salary cost

Moderately high salary cost

C7

Low salary cost

8 000
6 000
4 000
2 000
0
-2 000

Mexico

Latvia

Turkey

Chile

Slovak Republic

Estonia

Czech Republic

Hungary

France

Poland

Israel

Greece

Iceland

Italy

Japan

Canada

United States

Ireland

Portugal

Netherlands

Australia

Denmark

Spain

Finland

Norway

French Comm. (Belgium)

Flemish Comm. (Belgium)

Austria

Germany

Slovenia

Switzerland

-6 000

Luxembourg

-4 000

How to read this chart
This figure shows the contribution (in USD) of the factors influencing the difference between salary cost of teachers per student in the country
and the OECD average. For example, in Slovenia, the salary cost of teachers per student is USD 2 882 higher than the OECD average. Slovenia
has below-average teachers’ salaries (- USD 595) and below-average instruction time (- USD 975), both of which push the salary cost of teachers
down. However, this is more than compensated for by a lower estimated class size (+ USD 3 909) and lower teaching time (+ USD 543) than
the OECD average.
Countries and economies are ranked in descending order of the difference between the salary cost of teachers per student and the OECD average.
Source: OECD (2018), Table C7.3. See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933804983

Figure C7.2 shows the wide variety of combinations of the four factors across countries and their different effects on
the salary cost of teachers. The magnitude of the contribution of each factor to the difference between a country’s
salary cost and the OECD average depends on the difference between the factor itself and the respective OECD average.
The sum of each factor’s contribution equals the difference in salary cost between that country and the OECD
average. For example, the salary cost in lower secondary education in Denmark is USD 4 622, USD 1 018 higher
than the OECD average. This difference is the result of the contributing effects of the four factors: above-average
teachers’ salary adds USD 616 to the difference; above-average instruction time adds USD 1 078; above-average
teaching time subtracts USD 489; and above-average estimated class size subtracts USD 188.
Different policy choices made by countries with similar spending
Higher levels of expenditure on education cannot automatically be equated with better performance by education
systems (OECD, 2016[1]). In addition to the fact that structural changes cannot guarantee better learning outcomes,
countries spending similar amounts on education do not necessarily have similar education policies and practices.
The OECD countries and economies shown in Figure C7.2 can be divided into four groups with similar teachers’
salary cost per student, in order to better illustrate different policy choices that are possible and made by other
countries while spending similar amounts.
Education at a Glance 2018: OECD Indicators   © OECD 2018

321

chapter C Financial and Human Resources Invested In Education
Under embargo until 11/09/2018 at 11.00am CEST

C7

Group 1: High salary cost of teachers per student in lower secondary education
This group, which has the highest salary cost of teachers per student in lower secondary education, is composed
of Austria, the French and Flemish Communities of Belgium, Germany, Luxembourg, Slovenia and Switzerland.
The salary cost of teachers per student in this group ranges from USD 5 351 to USD 6 621. Luxembourg is not
included in this range because its salary cost per student of USD 11 560 makes it an outlier.
Although most of these countries (with the exception of Slovenia) have above-average GDP per capita, they
do not correspond to the five richest OECD countries. Moreover, although Austria, the French and Flemish
Communities of Belgium, Luxembourg and Switzerland have among the highest total education expenditure per
student, Germany and Slovenia fall close to the OECD average. This reinforces the finding that, although salary
cost of teachers is related to GDP per capita and total education expenditure, the relationship is not one to one.
Some countries allocate a much higher share of their budget to this type of expenditure than others.
Compared to countries from the other groups, it may seem as though these high-spending countries do not
face important trade-offs among the four factors analysed in this indicator. For example, with the exception
of Slovenia, all of the countries in this group can afford above-average teacher salaries and below-average class
size. However, the magnitude of the difference between these factors and the respective OECD averages vary
considerably across these countries.
Group 2: Moderately high salary cost of teachers per student in lower secondary education
This is the largest group, composed of 11 countries with above-average salary costs: Australia, Canada, Denmark,
Finland, Ireland, Japan, the Netherlands, Norway, Portugal, Spain and the United States. The salary cost of
teachers per student in this group ranges from USD 3 778 to USD 5 075. This group is highly heterogeneous
in terms of GDP per capita, education expenditure and even education systems, which sheds light on the many
different choices countries with similar spending can make.
One of the main salary cost trade-offs countries face is between teachers’ salaries and class size. With the
exception of Australia and Portugal, countries in this group have above-average teachers’ salaries which are at
least partially compensated by larger estimated class sizes. The two exceptions, Australia and Portugal, both
have below-average estimated class sizes, but teachers’ salaries are relatively high in Australia and relatively low
in Portugal. If Portugal increased its estimated class size by five students, teacher salaries could be equivalent to
those in Australia, with no increase in spending.
Another potential trade-off observed in some countries is between students’ required instruction time and
teachers’ teaching time. In the Netherlands, for example, instruction time is 77 hours longer per year than
the OECD average, but this is almost entirely offset by teaching time that is 53 hours longer than the average.
A requirement for more teaching hours, which limits the number of teachers that need to be hired, can also be
used to compensate for higher teachers’ salaries. This is the case in the United States, where the requirement for
270 teaching hours above the OECD average helps compensate for the additional USD 17 510 teachers receive
(teachers’ statutory salary in the United States is USD 61 907 compared to the OECD average of USD 44 397).
Group 3: Moderately low salary cost of teachers per student in lower secondary education
This group is composed of six countries with below-average salary cost of teachers per student: France, Greece,
Iceland, Israel, Italy and Poland. The salary cost of teachers per student in this group ranges from USD 2 615 to
USD 3 432. As was the case with Group 2, despite similar levels of salary cost of teachers per student, this group
is highly heterogeneous. Greece and Poland have two of the lowest expenditures per student and GDP per capita,
whereas the other countries fall around the OECD averages.
This group could be characterised by below-average teacher salaries that are partially offset by less teaching time.
But there are important variations across these countries. France and Poland have nearly the same salary cost
of teachers per student, but teachers’ salaries in France are 47% higher than in Poland, which is offset by having
about five more students per class. In Poland, the main factor pushing up the salary cost is the fact that teachers
have the lowest number of teaching hours of all OECD countries and economies (481 hours per year, compared
to 684 in France and 697 on average across OECD countries).
Group 4: Low salary cost of teachers per student in lower secondary education
This group is composed of the eight countries with the lowest salary cost of teachers per student in lower
secondary education: Chile, the Czech Republic, Estonia, Hungary, Latvia, Mexico, the Slovak Republic and Turkey.

322 Education at a Glance 2018: OECD Indicators   © OECD 2018

Which factors influence teachers’ salary cost? – INDICATOR C7

chapter C

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The salary cost of teachers per student in this group ranges from USD 1 039 to USD 1 971. These countries all have
below-average GDP per capita and below-average expenditure per student, but there are important differences
in their policy choices.
In an overall cross-country comparison, Latvia and the Slovak Republic might have been bundled together as
having low salary costs due to below-average salaries and below-average estimated class sizes. However, they
have made different policy choices: the Slovak Republic’s relatively larger estimated class size allows it to pay
teachers over twice as much as Latvia, which has the lowest teachers’ salaries and the second lowest estimated
class size of all OECD countries. Moreover, Chile spends about as much as the Slovak Republic on the salary cost
of teachers per student, but because teaching time in Chile is nearly double that of the Slovak Republic, it can
afford more instruction time and higher teachers’ salaries.
Main factors influencing the level of the salary cost: teachers’ salary and estimated class size
At each level of education, teachers’ salaries generally have the largest impact on the degree to which countries’
salary cost of teachers per student diverges from the OECD average. The second most influential factor is the
estimated class size. The trade-off between these two variables, which are often the aim of educational reforms and
policies, reflects the choice countries have to make between increasing teachers’ salaries and hiring more teachers.
Figure C7.3 plots teachers’ salaries against estimated class size, disaggregating between countries with above-average
and below-average teachers’ salary cost per student. It is important to control for the overall level of spending because,
compared to low-spending countries, high-spending countries are able to afford more of everything (i.e. higher salaries
and lower class sizes), which may give a misleading impression that they do not face trade-offs within their own budget
allocation. The figure shows that, within each group of countries, the relationship between estimated class size and
teachers’ salary is positive, meaning that countries with higher teacher salaries tend to have larger class sizes.

Figure C7.3. Relationship between teachers’ salaries and estimated class size, disaggregated
by level of salary cost of teachers per student (2016)
Lower secondary education, public institutions only
Below-average teachers’ salary cost per student
Above-average teachers’ salary cost per student

Estimated
class size

25
23

R2 = 0.56

Netherlands

21

France

19

Czech Republic

17

Slovak Republic

15

Poland

Israel

Italy

Denmark

Flemish Comm.
(Belgium)

Chile

Estonia1
Hungary

11

Ireland

Australia

R2 = 0.40

United
States
Germany

Portugal

Spain

Finland

French Comm. (Belgium)
Austria
Norway

Iceland

13

Canada

Japan

Switzerland2

Greece

9
Latvia

Slovenia

7
5

0

10 000

20 000

30 000

40 000

50 000

60 000

70 000

80 000

90 000

Annual statutory salary for teachers with 15 years
of experience and most prevalent qualification
in USD converted using PPPs for private consumption

Note: Luxembourg, Mexico and Turkey have been removed from the chart and the average because they are outliers for either teacher salaries or
estimated class size.
1. Teachers’ statutory salaries at the start of their career instead of after 15 years of experience.
2. Teachers’ statutory salary with 10 years of experience instead of 15 years.
Source: OECD (2018), Table C7.5b, available on line. See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag2018-36-en).
1 2 https://doi.org/10.1787/888933805002

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C7

Smaller class sizes are often seen as beneficial, but there are mixed evidence regarding their impact on student
learning. Results from the latest Programme for International Student Assessment (PISA) show that students in
larger classes score higher in science, on average across OECD countries. Other research has found that smaller class
sizes may be beneficial in some cases, such as for students from disadvantaged backgrounds that may need more
individualised attention (Dynarski, Hyman and Schanzenbach, 2013[2]). Given that reducing class size is a costly
measure (Box C7.2), it is important to compare its impact to other possible interventions (OECD, 2016[1]).
As highlighted in Figure C7.3, one alternative measure is to increase teacher salaries. Evidence from PISA point
to the importance of high-quality teaching in improving student outcomes (OECD, 2016[1]) and one way to help
school systems attract the best candidates to the teaching profession is by offering higher salaries. However, the
need to attract good candidates to the teaching profession and retain the effective ones is not only a matter of
raising salaries. It includes, among others, the quality of training before and after entering the profession and of the
relationship between teachers and society.

Box C7.1. Relationship between salary cost per student and expenditure per student
Expenditure per student reflects structural and institutional factors, such as the organisation of schools and
curricula. Current expenditure on educational institutions can be broken down into compensation of staff
and other expenditures (such as maintenance of school buildings, providing students’ meals and rental of
school buildings and other facilities). Teacher compensation usually constitutes the largest part of current
expenditure and therefore of expenditure on education (see Indicator C6). As a result, the level of teacher
compensation divided by the number of students – the salary cost of teachers per student – is the largest share
of expenditure per student.

Figure C7.a. Relationship between salary cost per student and expenditure per student
in lower secondary public institutions (2015, 2016)
Salary cost converted in USD using PPPs for private consumption and expenditure converted using PPPs for GDP
Salary cost per student
in public institutions (2016), in USD

8 000
R2 = 0.68

7 000
Slovenia

6 000

Germany
Australia
Spain

5 000
Portugal

4 000

Switzerland1

United States

Ireland

Greece

3 000

Austria
Flemish Comm.
(Belgium)
French Comm.
Norway
(Belgium)
Finland
Netherlands

Italy

Iceland

Poland
France

Hungary

2 000

Estonia

Turkey
Chile

1 000

Latvia

Mexico

Czech Republic

Slovak Republic

0
0

2 000

4 000

6 000

8 000

10 000

12 000

14 000

16 000

18 000

20 000

Expenditure per student
in public institutions (2015), in USD

Note: Luxembourg, an outlier, has been removed from the chart in order to improve the visibility. Its expenditure per student is USD 22 927
and teachers’ salary cost per student is USD 11 560.
1. Public expenditure only.
Source: OECD (2018), Table C7.1 and Education at a Glance Database, http://stats.oecd.org. See Source section for more information and
Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933805021

…

324 Education at a Glance 2018: OECD Indicators   © OECD 2018

Which factors influence teachers’ salary cost? – INDICATOR C7

chapter C

Under embargo until 11/09/2018 at 11.00am CEST

Figure C7.a plots the salary cost of teachers per student against expenditure per student in public
institutions in lower secondary education. The figure shows that, as expected, there is a strong positive
relationship between the two measures. However, the salary cost of teachers can vary considerably, even
among countries with a similar level of expenditure per student. Greece and Latvia, for example, both spend
around USD 7 000 per student in public institutions, but the salary cost per student in Greece is three times
that of Latvia.
These differences highlight the fact that countries not only have to decide how to best allocate salary cost
resources across the four factors (instruction time, teaching time, teachers’ salaries and estimated class
size), but also how much of the total education expenditure will be dedicated to the salary cost of teachers.
This decision in itself implies trade-offs with other potential types of expenditure not explored in this
indicator, such as non-salary compensation of teachers, salaries of non-teaching staff and infrastructure
improvements.

Box C7.2. What could be the trade-offs of decreasing class size by one student?
This indicator assesses the impact of four factors (teacher salaries, instruction time, teaching time and
estimated class size) on countries’ salary cost of teachers per student and the trade-offs that can exist
between them. This analysis can be used to answer the following question: Assuming that the number of
students and the salary cost remain constant, what could be potential trade-offs among the other factors
which would compensate for the smaller class size? More specifically, by how much would salaries or
instruction time have to decrease, or teaching time have to increase, in order to maintain the same salary
cost?
Table C7.a presents the results for this simulation. For each factor, the value is calculated keeping everything
else constant. For example, in Australia, in order to decrease estimated class size by one student and keep the
salary cost per student constant, teacher salaries would have to decrease by USD 3 600, annual instruction
time would have to decrease by 63 hours, or annual teaching time would have to increase by 54 hours. Any
one of these trade-offs would compensate for the additional cost of the decrease in class size, without any
change to the total salary cost of teachers per student.
These results emphasise the fact that decreasing class size, by as little as one student, comes with a price tag.
Indeed, class size has been decreasing in several OECD countries over recent years (OECD, 2016[3]), though
often as a result of demographic changes rather than of active policy choices. Class sizes tend to decrease
with student enrolment because of the political, economic and organisational challenges of simultaneously
decreasing the number of teachers. However, in the long term, a non‑reduction of the teaching force is in
itself a policy choice that will keep classes smaller. Table C7.a shows that the price of the smaller class sizes
can either be reflected in a higher salary cost, or it can be offset by changes to the other three factors.
It is important to assess the results presented in Table C7.a by taking into account the current values of
each factor in the country. For example, Chile already has the longest teaching time of all OECD countries,
so further increases to compensate for smaller class size may not be feasible or desirable.
This simulation is not meant to assess the real cost of reforms. The simple model only takes into account
four factors, and it only shows the trade-off of one factor at a time. In reality, trade-offs will often consist of
changes across several factors at the same time. Moreover, important regional variations, not captured in
this indicator, may require specific policies that would not necessarily be reflected on the national averages.
Instead, this analysis is only meant to highlight the importance of trade-offs in policy decisions, and to
provide some guidance as to the direction and magnitude of the potential trade-offs across the four factors
assessed in this indicator.

…
Education at a Glance 2018: OECD Indicators   © OECD 2018

325

C7

chapter C Financial and Human Resources Invested In Education
Under embargo until 11/09/2018 at 11.00am CEST
Table C7.a. Keeping salary cost constant, what could be the trade-offs of decreasing class size,
by one student? (2016)
Lower secondary education, public institutions only
Teacher salaries
Instruction time
Teaching time
(in equivalent USD
(in hours per year) (in hours per year)
per year)

C7
Australia
Austria
Canada
Chile
Czech Republic
Denmark
Estonia1
Finland
Flemish Comm. (Belgium)
France
French Comm. (Belgium)
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Latvia
Luxembourg
Mexico
Netherlands
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Switzerland2
Turkey
United States

(1)

(2)

-3 600
-4 100
-3 100
-1 600
-1 100
-3 000
-1 400
-3 500
-3 100
-1 800
-3 600
-4 700
-2 500
-1 700
-2 500
-3 300
-2 000
-2 200
-2 600
-1 000
-10 100
- 900
-3 300
-3 900
-1 600
-3 000
-1 200
-5 300
-3 200
-5 300
- 800
-3 700

-63
-71
-44
-67
-51
-70
-59
-66
-59
-48
-73
-57
-74
-64
-60
-53
-59
-57
-45
-91
-78
-28
-47
-72
-50
-65
-53
-103
-68
-65
-31
-61

(3)

54
52
37
78
37
49
47
51
36
35
53
50
61
60
48
44
44
38
32
93
75
26
37
60
31
47
45
97
50
55
19
62

Note: Teachers’ salaries used in the calculation of this indicator refer to the annual statutory teachers’ salaries in public institutions for
teachers with 15 years of experience and most prevalent qualification (Indicator D3). Instruction time refers to the average number of hours
per year of compulsory instruction time (Indicator D1) and teaching time refers to the statutory net teaching hours over the school year
(Indicator D4). The reference year for these factors may differ by one year for some countries. See Table C7.5b, available on line, for notes
on each factor.
1. Teachers’ statutory salaries at the start of their career instead of after 15 years of experience.
2. Teachers’ statutory salaries after 10 years of experience instead of 15 years.
Source: OECD (2018), Table C7.5b, available on line. See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/
eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933805040

Definitions
Instruction time refers to the time a public school is expected to provide instruction to students on all the subjects
integrated into the compulsory and non-compulsory curriculum, on school premises or in before or after-school
activities that are formal parts of the compulsory programme.
Teachers’ teaching time is the annual average number of hours that full-time teachers teach a group or class of
students including all extra hours, such as overtime.
Teachers’ salary refers to the annual statutory salary of teachers after 15 years of experience, converted to USD
using PPPs for private consumption.

326 Education at a Glance 2018: OECD Indicators   © OECD 2018

Which factors influence teachers’ salary cost? – INDICATOR C7

chapter C

Under embargo until 11/09/2018 at 11.00am CEST

Methodology
The salary cost of teachers per student (SCS) is calculated as:
SCS = Teacher salary * Instruction time *

1
1
Teaching time * Estimaed class size

C7

Where estimated class size is calculated as:
Estimated class size = Instruction time * Students
Teaching time
Teachers
The contribution of each factor to the level of the salary cost of teachers per student is analysed by comparing the
salary cost of teachers per student in each country to the OECD average and then calculating the contribution of
these different factors to the variation from the OECD average. This exercise is based on a mathematical relationship
between the various factors and follows the method presented in the Canadian publication Education Statistics
Bulletin (Quebec Ministry of Education, Recreation and Sports, 2003[4]). Using this mathematical relationship and
comparing a country’s values for the four factors to the OECD averages makes it possible to measure both the direct
and indirect contribution of each of these four factors to the variation in salary cost per student between that
country and the OECD average.
Please see the OECD Handbook for Internationally Comparative Education Statistics 2018 (OECD, 2018[5]) for more
information and Annex 3 for country-specific notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Lithuania was not an OECD member at the time of preparation of this publication. Accordingly, Lithuania does not
appear in the list of OECD members and is not included in the zone aggregates.

Source
Data referring to the 2016 school year are based on the UOE data collection on education statistics and on the
Survey on Teachers and the Curriculum, which were both administered by the OECD in 2016.
Note regarding data from Israel
The statistical data for Israel are supplied by and are under the responsibility of the relevant Israeli authorities. The use
of such data by the OECD is without prejudice to the status of the Golan Heights, East Jerusalem and Israeli settlements
in the West Bank under the terms of international law.

References
Dynarski, S., J. Hyman and D. Schanzenbach (2013), “Experimental evidence on the effect of childhood investments on
postsecondary attainment and degree completion”, Journal of Policy Analysis and Management, Vol. 32/4, pp. 692-717,
http://dx.doi.org/10.1002/pam.21715.

[2]

OECD (2018), OECD Handbook for Internationally Comparative Education Statistics 2018: Concepts, Standards, Definitions
and Classifications, OECD Publishing, Paris, https://doi.org/10.1787/9789264304444-en.

[5]

OECD (2016), Education at a Glance 2016 : OECD Indicators, OECD Publishing, Paris, http://dx.doi.org/10.1787/eag-2016-en
(accessed on 12 January 2018).

[3]

OECD (2016), PISA 2015 Results (Volume II): Policies and Practices for Successful Schools, PISA, OECD Publishing, Paris,
http://dx.doi.org/10.1787/9789264267510-en.

[1]

Quebec Ministry of Education, Recreation and Sports (2003), “Le coût salarial des enseignants par élève pour
l’enseignement primaire et secondaire en 2000-2001”, Education Statistics Bulletin, No. 29, www.education.gouv.qc.ca/
fileadmin/site_web/documents/PSG/statistiques_info_decisionnelle/bulletin_29.pdf.

[4]

Indicator C7 Tables
1 2 https://doi.org/10.1787/888933804888

Table C7.1 Salary cost of teachers per student, by level of education (2016)
Table C7.2 Contribution of various factors to salary cost of teachers per student in primary education (2016)
Table C7.3 Contribution of various factors to salary cost of teachers per student in lower secondary education (2016)

…

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chapter C Financial and Human Resources Invested In Education
Under embargo until 11/09/2018 at 11.00am CEST
WEB Table C7.4 Contribution of various factors to salary cost of teachers per student in general programmes
of upper secondary education (2016)

C7

WEB Table C7.5a Factors used to compute the salary cost of teachers per student in public institutions,
in primary education (2016)
Table
C7.5b
Factors used to compute the salary cost of teachers per student in public institutions,
WEB
in lower secondary education (2016)
WEB Table C7.5c Factors used to compute the salary cost of teachers per student in public institutions,
in general programmes of upper secondary education (2016)
Cut-off date for the data: 18 July 2018. Any updates on data can be found on line at http://dx.doi.org/10.1787/eag-data-en. Data can also be found
at http://stats.oecd.org/, Education at a Glance Database.

328 Education at a Glance 2018: OECD Indicators   © OECD 2018

Which factors influence teachers’ salary cost? – INDICATOR C7

chapter C

Under embargo until 11/09/2018 at 11.00am CEST
Table C7.1. Salary cost of teachers per student, by level of education (2016)
Annual salary cost of teachers per student in public institutions, in equivalent USD, converted using PPPs
for private consumption, and in percentage of GDP per capita

OECD

Salary cost of teachers per student
(in USD, 2016 constant prices)

Salary cost of teachers per student
(in percentage of GDP per capita)

Primary

Lower secondary

Upper secondary,
general
programmes

(1)

(2)

(3)

(4)

3 808

4 555

m

8.0

9.6

m

4 243

6 059

5 493

8.4

11.9

10.8

3 817

3 817

m

8.5

8.5

m

1 649

1 518

1 339

7.2

6.6

5.9

1 013

1 626

m

2.9

4.7

m

4 405

4 622

m

9.0

9.4

m

1 296

1 920

m

4.5

m

m

3 080

4 927

m

7.1

11.3

m

1 827

2 615

2 999

4.4

6.3

7.2

4 461

5 676

m

9.1

11.6

m

2 782

3 315

m

10.4

12.4

m

1 832

1 971

2 054

6.9

7.4

7.7

3 241

3 383

m

6.3

6.6

m

3 602

4 235

4 235

5.0

5.9

5.9

2 020

2 793

2 589

5.4

7.4

6.9

3 060

3 432

3 202

8.0

8.9

8.3

3 073

3 778

m

7.3

8.9

m

m

m

m

m

m

m

Primary

Lower secondary

Upper secondary,
general
programmes

(5)

(6)

Countries

Australia
Austria
Canada
Chile
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United States

758

1 115

m

3.0

4.4

m

10 265

11 560

11 535

9.9

11.2

11.2

1 115

1 039

2 709

6.0

5.5

14.5

3 424

4 459

4 459

6.8

8.8

8.8

m

m

m

m

m

m

4 516

5 075

m

8.8

9.9

m

2 183

2 623

m

8.0

9.6

m

3 268

4 466

4 470

10.7

14.6

14.6

1 089

1 504

1 304

3.6

4.9

4.3

2 775

6 487

m

8.5

19.8

m

3 580

4 724

4 624

9.9

13.0

12.7
m

m

m

m

m

m

4 407

6 621

m

6.9

10.3

m

1 258

1 412

1 546

4.9

5.5

6.1

3 808

3 911

3 847

6.6

6.8

6.6

Flemish Comm. (Belgium)
French Comm. (Belgium)
England (UK)
Scotland (UK)

4 186

5 479

6 761

9.0

11.8

14.5

3 863

5 351

6 004

8.3

11.5

12.9

m

m

m

m

m

m

m

m

m

m

m

m

OECD average1

2 936

3 604

3 723

6.9

8.7

8.6

Economies

Note: Teachers’ salaries used in the calculation of this indicator refer to the annual statutory teachers’ salaries in public institutions for teachers with 15 years
of experience and most prevalent qualification (Indicator D3). Instruction time refers to the average number of hours per year of compulsory instruction time
(Indicator D1) and teaching time refers to the statutory net teaching hours over the school year (Indicator D4). The reference year for these factors may differ by one
year for some countries. See Tables C7.5a, b and c, available on line, for notes on each factor.
1. The OECD average only includes countries and economies with data for all factors used to calculate salary cost.
Source: OECD (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933804907

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Table C7.2. Contribution of various factors to salary cost of teachers per student

in primary education (2016)

In equivalent USD, converted using PPPs for private consumption
Contribution of the underlying factors to the difference
from the OECD average

C7
Salary cost
of teachers
per student
(2016)
OECD

(1)

Effect (in USD)
Effect (in USD)
Effect (in USD)
Effect (in USD)
of instruction time of teaching time
of estimated class
of teachers’ salary
(for students)
(for teachers)
size below/above
Difference (in USD) below/above the
below/above the
below/above the
the 2016 OECD
from the 2016
2016 OECD average 2016 OECD average 2016 OECD average
average of
OECD average of
of
of
of
15 students
USD 2 936
USD 42 193
805 hours
775 hours
per class
(2) = (3)+(4)+(5)+(6)

(3)

(4)

(5)

3 808

872

4 243

1 307

(6)

1 031

734

- 365

- 528

551

- 480

- 21

1 257
- 930

Countries

Australia
Austria
Canada
Chile
Czech Republic
Denmark
Estonia1
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland2
Turkey
United States

3 817

881

1 456

454

- 100

1 649

-1 287

-1 084

596

- 914

114

1 013

-1 923

-1 387

- 283

447

- 700

4 405

1 469

681

966

- 43

- 135

1 296

-1 639

-1 814

- 422

618

- 22

3 080

144

- 88

- 734

394

572

1 827

-1 109

- 454

167

- 351

- 471

4 461

1 525

1 813

- 498

- 126

336

2 782

- 154

-1 406

- 72

472

852

1 832

-1 104

-1 804

- 470

433

738

3 241

305

- 562

- 312

674

504

3 602

666

1 024

421

- 550

- 229

2 020

- 916

- 852

443

- 224

- 283

3 060

124

- 612

305

36

395

3 073

137

582

- 164

130

- 412

m

m

m

m

m

m

758

-2 177

-2 652

- 569

151

891

10 265

7 329

5 102

852

- 276

1 652

1 115

-1 821

- 617

- 13

- 62

-1 129

3 424

488

989

497

- 589

- 409

m

m

m

m

m

m

4 516

1 580

365

- 276

166

1 325

2 183

- 753

-1 330

- 624

829

372

3 268

332

- 38

64

132

173

1 089

-1 847

-1 503

- 307

- 68

31

2 775

- 161

- 182

- 552

609

- 36

3 580

644

179

- 58

- 418

941

m

m

m

m

m

m

4 407

1 471

1 759

42

- 196

- 135

1 258

-1 678

-1 168

- 227

151

- 433

3 808

872

1 190

634

- 891

- 60

4 186

1 250

596

72

122

460

3 863

927

461

181

267

18

m

m

m

m

m

m

m

m

m

m

m

m

Economies

Flemish Comm. (Belgium)
French Comm. (Belgium)
England (UK)
Scotland (UK)

Note: Teachers’ salaries used in the calculation of this indicator refer to the annual statutory teachers’ salaries in public institutions for teachers with 15 years
of experience and most prevalent qualification (Indicator D3). Instruction time refers to the average number of hours per year of compulsory instruction time
(Indicator D1) and teaching time refers to the statutory net teaching hours over the school year (Indicator D4). The reference year for these factors may differ by one
year for some countries. See Table C7.5a, available on line, for notes on each factor.						
1. Teachers’ statutory salaries at the start of their career instead of after 15 years of experience.						
2. Teachers’ statutory salaries after 10 years of experience instead of 15 years.						
Source: OECD (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933804926

330 Education at a Glance 2018: OECD Indicators   © OECD 2018

Which factors influence teachers’ salary cost? – INDICATOR C7

chapter C

Under embargo until 11/09/2018 at 11.00am CEST
Table C7.3. Contribution of various factors to salary cost of teachers per student

in lower secondary education (2016)

In equivalent USD, converted using PPPs for private consumption
Contribution of the underlying factors to the difference from the OECD average

Salary cost
of teacher
per student
(2016)
OECD

(1)

Effect (in USD)
Effect (in USD)
Effect (in USD)
of instruction time of teaching time
of teachers’ salary
(for students)
(for teachers)
Difference (in USD) below/above the
below/above the
below/above the
from the 2016
2016 OECD average 2016 OECD average 2016 OECD average
OECD average of
of
of
of
USD 3 604
USD 44 397
923 hours
697 hours
(2) = (3) + (4) + (5) + (6)

(3)

4 555

951

6 059

2 455

Effect (in USD)
of estimated
class size
below/above
the 2016 OECD
average of
16 students
per class

(4)

(5)

(6)

1 039

328

- 544

127

726

- 124

656

1 198
- 963

Countries

Australia
Austria
Canada
Chile
Czech Republic
Denmark
Estonia1
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland2
Turkey
United States

3 817

213

1 421

6

- 251

1 518

-2 087

-1 288

381

-1 239

60

1 626

-1 979

-2 037

- 75

321

- 187
- 188

4 622

1 018

616

1 078

- 489

1 920

-1 685

-2 236

- 325

417

459

4 927

1 322

- 12

- 380

667

1 047
- 717

2 615

- 989

- 550

222

57

5 676

2 072

2 410

- 71

- 338

71

3 315

- 289

-1 908

- 582

633

1 568

1 971

-1 633

-2 216

- 537

193

927

3 383

- 221

- 813

- 337

389

540

4 235

630

1 065

52

- 187

- 301

2 793

- 812

- 955

255

-7

- 105

3 432

- 172

- 593

248

375

- 202

3 778

174

527

- 115

493

- 732

m

m

m

m

m

m

1 115

-2 489

-3 766

- 399

- 82

1 757

11 560

7 956

6 150

- 656

- 440

2 903

1 039

-2 566

- 281

540

- 882

-1 943

4 459

854

1 964

330

- 305

-1 135

m

m

m

m

m

m

5 075

1 470

206

- 236

213

1 287

2 623

- 982

-1 778

- 417

1 203

11

4 466

861

- 255

- 139

568

687

1 504

-2 100

-2 082

- 249

143

89

6 487

2 882

- 595

- 975

543

3 909

4 724

1 120

462

510

- 95

243

m

m

m

m

m

m

6 621

3 016

2 784

190

- 446

488

1 412

-2 192

-1 535

- 225

828

-1 260

3 911

306

1 270

379

-1 255

- 87

5 479

1 874

531

122

1 124

98

5 351

1 746

379

224

260

884

m

m

m

m

m

m

m

m

m

m

m

m

Economies

Flemish Comm. (Belgium)
French Comm. (Belgium)
England (UK)
Scotland (UK)

Note: Teachers’ salaries used in the calculation of this indicator refer to the annual statutory teachers’ salaries in public institutions for teachers with 15 years
of experience and most prevalent qualification (Indicator D3). Instruction time refers to the average number of hours per year of compulsory instruction time
(Indicator D1) and teaching time refers to the statutory net teaching hours over the school year (Indicator D4). The reference year for these factors may differ by one
year for some countries. See Table C7.5b, available on line, for notes on each factor.						
1. Teachers’ statutory salaries at the start of their career instead of after 15 years of experience.						
2. Teachers’ statutory salaries after 10 years of experience instead of 15 years.						
Source: OECD (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933804945

Education at a Glance 2018: OECD Indicators   © OECD 2018

331

C7

Under embargo until 11/09/2018 at 11.00am CEST

Under embargo until 11/09/2018 at 11.00am CEST

Chapter

D

Teachers, the Learning Environment
and the Organisation
of Schools

Indicator D1 How much time do students spend in the classroom?
1 2 https://doi.org/10.1787/888933805059

Indicator D2 What is the student-teacher ratio and how big are classes?
1 2 https://doi.org/10.1787/888933805230

Indicator D3 How much are teachers and school heads paid?
1 2 https://doi.org/10.1787/888933805363

Indicator D4 How much time do teachers spend teaching?
1 2 https://doi.org/10.1787/888933805553

Indicator D5 Who are the teachers?
1 2 https://doi.org/10.1787/888933805724

Indicator D6 Who makes key decisions in education systems?
1 2 https://doi.org/10.1787/888933805857

Education at a Glance 2018: OECD Indicators   © OECD 2018

333

Under embargo until 11/09/2018 at 11.00am CEST

HOW MUCH TIME DO STUDENTS SPEND IN
THE CLASSROOM?
• Students in OECD countries and economies receive an average of 7 533 hours of compulsory
instruction during their primary and lower secondary education, ranging from 5 940 hours in
Hungary to almost double that in Australia (11 000 hours) and Denmark (10 960 hours).

• Across OECD countries and economies, compulsory instruction time for primary students

INDICATOR D1

averages 799 hours per year, and lower secondary students receive an average of 114 more hours of
compulsory education per year than primary students (913 hours).

• On average across OECD countries and economies, instruction in reading, writing and literature,
mathematics, and the arts represents 51% of compulsory instruction time for primary school
students, and instruction in reading, writing and literature, second and other languages, and
mathematics represents 40% of compulsory instruction time for lower secondary school students.

Figure D1.1. Compulsory instruction time in general education (2018)
Primary and lower secondary education, in public institutions
Duration of primary
and lower secondary
education, in years

Primary

Lower secondary

Hungary 8
Latvia 9
Poland 9
Turkey 8
Finland1 9
Slovenia 9
Russian Federation 9
Austria 8
Estonia 9
Korea1 9
Slovak Republic 9
Flemish Comm. (Belgium) 8
Greece 9
Sweden1 9
French Comm. (Belgium) 8
Czech Republic 9
Lithuania 10
EU22 average 9
Japan 9
Germany2 9
Italy 8
OECD average 9
Switzerland 9
Iceland1 10
Portugal 9
Norway 10
Spain 9
Luxembourg 9
France 9
Ireland 9
Canada 9
Mexico2 9
Chile 8
Netherlands3 9
Israel 9
United States 9
Costa Rica 9
Denmark 10
Australia 11
0

2 000

4 000

6 000

8 000

10 000

12 000

Total number of compulsory instruction hours

1. Estimated number of hours by level of education based on the average number of hours per year, as the allocation of instruction
time across multiple grades is flexible.
2. Year of reference differs from 2018. See Table D1.1 for more information.
3. The number of grades in lower secondary education is three or four, depending on the track. The fourth year of pre-vocational
secondary education (VMBO) was excluded from the calculation.
Countries and economies are ranked in ascending order of the total number of compulsory instruction hours.
Source: OECD (2018), Table D1.1. See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/
eag-2018-36-en).
1 2 https://doi.org/10.1787/888933805154

334 Education at a Glance 2018: OECD Indicators   © OECD 2018

Under embargo until 11/09/2018 at 11.00am CEST
Context
Providing instruction in formal classroom settings accounts for a large portion of public investment
in education. Countries make various choices concerning the overall amount of time devoted to
instruction and which subjects are compulsory. These choices reflect national and/or regional priorities
and preferences concerning what material students should be taught and at what age. Almost all
countries have statutory or regulatory requirements regarding hours of instruction. These are most
often stipulated as the minimum number of hours of instruction a school must offer and are based
on the understanding that sufficient time is required for good learning outcomes. Matching resources
with students’ needs and making optimal use of time are central to education policy. Teachers’
salaries, institutional maintenance and provision of other educational resources constitute the main
costs of education. The length of time during which these resources are made available to students
(as partly shown in this indicator) is an important factor in determining how funds for education
are allocated (see Indicator C7, which shows the factors influencing the salary cost of teachers per
student). There is growing awareness of the importance of time spent outside the classroom during
the school day in activities other than instruction, including recesses and breaks. In addition to formal
instruction time, students may participate in extracurricular activities before and/or after the school
day or during school holidays, but these activities (as well as examination periods) are outside the
scope of this indicator.

INDICATOR D1

Other findings

• The proportion of the compulsory curriculum for primary students devoted to reading, writing
and literature ranges from 19% in Poland to 38% in France; for lower secondary students, it ranges
from 9% in Ireland (for English, one of the two national languages) to 25% in Greece (and more in
Italy, including social studies).

• The proportion of the compulsory curriculum devoted to mathematics at the primary level ranges
from 12% in Denmark to 27% in Mexico; at the lower secondary level, it ranges from 11% in
Hungary and Korea to 16% in Chile, Latvia and the Russian Federation (and 20% in Italy, including
natural science).

• Except for a few countries where the compulsory curriculum is mostly devoted to flexible subjects,
in OECD countries and economies, an average of 1% of compulsory instruction time for primary
students and lower secondary students is devoted to subjects with a flexible timetable. An average
of 5% of compulsory instruction time at the primary level and 7% at the lower secondary level is
devoted to flexible subjects chosen by schools.

• In one-third of countries with available data, the allocation of instruction time across grades is
flexible (i.e. instruction time for a specific subject is defined for a certain number of grades or even
the whole of compulsory education, without specifying the time to be allocated to each grade).

Education at a Glance 2018: OECD Indicators   © OECD 2018

335

chapter D Teachers, the Learning Environment and the Organisation of Schools
Under embargo until 11/09/2018 at 11.00am CEST

Analysis
Compulsory general education

D1

Both annual instruction time and the length of compulsory education have impacts on the total instruction time
during compulsory education. In some countries, the duration of compulsory education is shorter, and students
could bear a heavier workload based on statutory requirements. In other countries, the workload is distributed
evenly over more years. This indicator focuses on compulsory education at primary and lower secondary levels.
However, in some countries such as the Netherlands, pre-primary education is also compulsory, so the starting
age for compulsory education is younger than the age at which primary education starts (see Annex 3 for more
details on the length of compulsory education). Moreover, in around three out of five countries and economies
with available data, at least one year of upper secondary education is part of compulsory full-time education
(Table D1.1).
In around three out of four countries and economies with available data, students are required to start primary
education at age 6. In most other countries, students are not required to start until age 7, as in Estonia, Finland,
Latvia, Lithuania, Poland, the Russian Federation and Sweden. Only in Australia, England (United Kingdom),
New Zealand and Scotland (United Kingdom) does primary education start at age 5.
There is also substantial variation in the duration of primary education. On average across OECD countries and
economies, primary education lasts six years, but it ranges from four years in Austria, Germany, Hungary, Lithuania,
the Russian Federation, the Slovak Republic and Turkey to seven years in Australia, Denmark, Iceland, Norway
and Scotland (United Kingdom). Lower secondary education averages three years, but ranges from two years in
Chile and the Flemish and French Communities of Belgium to five years in Germany, the Russian Federation and
the Slovak Republic, and six years in Lithuania (Table D1.2).
Countries also allocate annual instruction time differently over the year. The number of instruction days and the
way they are distributed across the school year can vary significantly between countries, as countries organise
holidays differently (Box D1.1). Within instruction days, countries also vary in the way they organise recess and
breaks (Box D1.2).

Box D1.1. Organisation of breaks within the school year in primary education (2018)
The length of the school year varies greatly between countries, implying that there is also wide variation in the
number of weeks children are not at school across countries. Countries organise the school year in different
ways, in terms of the frequency and length of school breaks during the school year.
School breaks are usually defined for the whole country, but can differ between subnational entities, especially
in federal countries. Breaks are usually similar at primary and lower secondary levels, but in Ireland, Israel and
Lithuania, the number of weeks of instruction differs between these levels by one to four weeks (see Table D4.1).
The distribution of breaks during the school year can also be flexible according to regions. For example, dates
for school breaks are defined according to three areas in France, and similar flexibility occurs for several or all
breaks in federal countries, as well as in Australia, Austria, the Czech Republic, England (United Kingdom),
Italy, the Netherlands, Poland, Slovenia and the Slovak Republic (see Annex 3 for the organisation of the
school year at primary and lower secondary levels).
In all countries, the longest break is the one between two successive school years. Focusing on primary
education, this break varies from a minimum of 5 weeks in Mexico and in some subnational entities in
Australia and Switzerland to 12 weeks or more in Estonia, Greece, Italy (12 to 14 weeks), Latvia, Lithuania,
the Russian Federation and Turkey. In nearly all countries with available information, this break between two
school years represents at least half of the school holiday time (Figure D1.a).
In addition to this long break, children usually have three to four other shorter holiday periods during the
school year. Austria, England (United Kingdom), Luxembourg and Scotland (United Kingdom), as well as some
Länder in Germany offer a fifth break during the third term of the school year.

…

336 Education at a Glance 2018: OECD Indicators   © OECD 2018

How much time do students spend in the classroom? – INDICATOR D1

chapter D

Under embargo until 11/09/2018 at 11.00am CEST
Breaks during the school year differ in both length and timing, but the main common break period is at the
end of calendar year, corresponding to either a two-week break (in the northern hemisphere), or the end of
the school year in the southern hemisphere. These differences in the timing of breaks may result from flexible
calendar dates (e.g. for holidays such as Easter).
In most countries, the length of the different breaks within the school year varies significantly, from a few days
to two weeks. Exceptions to this pattern are Lithuania, the Russian Federation and Slovenia, with one-week
breaks (three to four during the school year), and Australia, France, Greece and New Zealand, with two-week
breaks (from two in Greece to four in France). Belgium, England (United Kingdom), Germany, Luxembourg
and Poland alternate one-week and two-week breaks during the school year.

Figure D1.a. School breaks in primary education (2018)
Number
of weeks

End of the school year break

Break 5

Break 4

Break 3

Break 2

Break 1

20
18
16
14
12
10
8
6
4
0

Russian Federation
Estonia
Latvia
Lithuania
France
Greece
Luxembourg
Portugal1
Spain
Iceland
Turkey
Sweden
Flemish Comm. (Belgium)
French Comm. (Belgium)
Italy1
Ireland
Hungary
Israel
Poland
Slovenia
Austria
Finland1
Slovak Republic
Norway
Chile
England (UK)
Scotland (UK)1
Germany1
New Zealand1
Czech Republic
Australia1
Netherlands
Denmark
Mexico
Costa Rica
Switzerland1

2

Note: Breaks exclude public/religious days, except if these days are included in longer breaks.
1. Minimum length of breaks as some may be longer for some regions within the country.
Countries are ranked in descending order of the number of weeks of breaks during the schol year.
Source: OECD (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933805211

Box D1.2. Recess and breaks during the school day
Learning in the classroom demands that students be focused and concentrate for long periods of time. Based
on annual instruction hours and the number of instruction days per year, primary students have less than
four hours of compulsory instruction per school day in about two-fifths of countries, but at least five hours
a day in a few countries (Australia, Canada, Chile, Costa Rica, Denmark, the Flemish Community of Belgium,
Ireland, Luxembourg and the United States). This is also the case in France, but the school week is organised in
4.5 rather than 5 days of school so that teaching time per day can be less than five hours. At lower secondary
level, the number of compulsory instruction hours per day is usually higher, with all countries having at least
four hours of compulsory instruction time per day. Three-quarters of countries have between four and less
than six hours per day, and Chile, Denmark and Spain have six hours or more per day (Tables D1.1 and D1.2).

…
Education at a Glance 2018: OECD Indicators   © OECD 2018

337

D1

chapter D Teachers, the Learning Environment and the Organisation of Schools
Under embargo until 11/09/2018 at 11.00am CEST
Research has found that spending some time outside the classroom during the school day in activities other
than instruction can help improve students’ performance in the classroom. In primary education, breaks in
instruction allow pupils to play, rest and freely interact with their peers to further develop cognitive, emotional
and social skills. Research suggests that students may then apply those skills in the classroom, thus improving
their learning (Pellegrini and Bohn, 2005[1]; Pellegrini et al., 2002[2]). OECD countries increasingly consider
recess and breaks as important components of the school day.

D1

How breaks during the school day are organised in OECD countries depends on how education systems are
governed and the degree of autonomy that individual schools enjoy (see Box D1.1 in [OECD, 2015[3]]). In most
countries, the school day is divided into lessons that last from 45 to 50 minutes, allowing for short breaks
between them to make up an entire hour. Across OECD countries, 10-15 minute breaks are generally long
enough to allow students to change classrooms and visit the bathroom. These short breaks are different in
length and purpose from longer breaks observed in the majority of countries. During longer breaks, students
can have breakfast or lunch and are commonly supervised by a teacher or group of teachers.
In primary education, long breaks are common and, in some cases, even compulsory. In Spain, for example,
breaks in primary school are considered part of compulsory instruction time. Primary students in Spain have
a half-hour break every day in the middle of the morning session that is considered part of the five daily
instruction hours. In several countries, a lunch break is set as part of the learning process, where students
learn about hygiene, healthy eating habits and/or recycling waste.
In several countries, long breaks can be found at all levels of education. In Australia, schools at all levels of
education tend to have one short morning recess and then a longer lunch break. In Canada, there is a midday
break for lunch in primary through upper secondary education. In both countries, long breaks can last around
40 to 60 minutes. Some countries have even longer lunch breaks, such as in France, where they last at least
90 minutes for primary education. Breaks can also occur throughout the day. In Switzerland, for example,
schools usually organise two breaks of between 15 and 30 minutes each and a long lunch break of about 60 to
90 minutes. In Chile, schools with a large number of pupils may divide students into two or more groups for
their breaks, by grade or age.
Schools can use recess and breaks for different purposes. They can use breaks as a way of helping students
who have to commute a long distance to school or to harmonise the end of classes when the duration of lesson
periods is different across grades, as in the Czech Republic, where ten-minute breaks can be shortened to five
minutes. In Denmark, municipalities often use breaks and recess as an integrated part of daily exercise and
physical activities for students at all grade levels. This is also the case in Slovenia, where schools sometimes
organise a long break intended for students to practice sports in the gym and on the school’s outdoor playing
fields.

Compulsory instruction time
Compulsory instruction time refers to the amount and allocation of instruction time that must be provided in
almost every public school and must be attended by almost all public sector students, as per public regulations.
Students in OECD countries and economies receive an average of 4 620 hours of instruction during primary school
and 2 913 hours during lower secondary education. While the total compulsory instruction time for primary and
lower secondary students averages 7 533 hours (in 9 years on average) across OECD countries and economies,
formal instruction-time requirements range from 5 940 in Hungary (in 8 years) to 11 000 in Australia (in 11 years)
(Figure D1.1). In England (United Kingdom), New Zealand and Scotland (United Kingdom), regulations do not
prescribe total compulsory instruction time in schools. However, schools are required to be open for instruction for
a minimum number of hours per day (New Zealand) or to allow sufficient instruction time to deliver a broad and
balanced curriculum that includes all statutory requirements (for variation of instruction time at the subnational
level, see Box D1.3).
Compulsory instruction time only captures the time spent by students in formal classroom settings. This is only a
part of the total time students spend receiving instruction. Instruction also occurs outside compulsory school hours
and outside the classroom or school. In some countries, secondary school students are encouraged to take after-

338 Education at a Glance 2018: OECD Indicators   © OECD 2018

How much time do students spend in the classroom? – INDICATOR D1

chapter D

Under embargo until 11/09/2018 at 11.00am CEST
school classes in subjects already taught in school to help them improve their performance. Students can participate
in after-school lessons in the form of remedial catch-up classes or enrichment courses, with individual tutors or in
group lessons provided by school teachers, or in other independent courses (see Box D1.3 in [OECD, 2017[4]]). These
lessons can be financed through public funds or by students and their families (see Box D1.1 in [OECD, 2011[5]]).
This indicator captures intended instruction time (as established in public regulations) as a measure of learning in
formal classroom settings. It does not show the actual number of hours of instruction that students receive and
does not cover learning outside the formal classroom setting.

Box D1.3. Compulsory instruction time at the subnational level at primary
and lower secondary levels
Instruction time varies largely between levels of education and also between countries for each level of
education. However compulsory education can also vary significantly within countries, especially in federal
countries where requirements are defined at the subnational level.
Among the four countries that reported at least some subnational data on instruction time (Belgium, Canada,
the United Kingdom and the United States), the difference in compulsory instruction time in primary education
between the subnational regions with the lowest and highest number of hours of instruction varies largely
between the two countries with available data. It varies from 4 931 hours to 5 012 hours (by 2%) between
the French and Flemish Communities of Belgium, and from 4 320 hours to 7 560 hours (by 75%) between
the 51 subnational regions (50 states and Washington DC) of the United States. At the lower secondary
level, the variations are similar to primary level: instruction time varies from 1 896 hours to 1 909 hours
(by less than 1%) in Belgium and from 2 160 hours to 3 780 hours (by 75%) in the United States. In both
these countries, these variations result from differences in annual instruction hours between subnational
entities, as the number of years of compulsory primary and lower secondary education does not vary between
subnational entities (OECD/NCES, 2018[6]).
Differences in the annual number of hours of compulsory instruction between subnational regions may be
explained by differences in the number of annual days of instruction at the subnational level at both primary
and lower secondary levels. Within countries with available data, the number of annual days of compulsory
instruction at these levels varies between subnational regions by about 6% in Canada (between 180 to 190 days),
less than 13% in Belgium (between 159 or 160 days to 179 days) and 16% in the United States (from 160 to
186 days), but does not vary between subnational entities with available information in the United Kingdom
(190 days) (OECD/NCES, 2018[6]).

Intended instruction time
Total intended instruction time is the estimated number of hours during which schools are obliged to offer
instruction in compulsory and, if applicable, non-compulsory subjects.
Intended and compulsory instruction time are of the same length (i.e. intended instruction time is fully compulsory)
for primary and lower secondary students in about three out of four countries with available data. In Finland, France
(lower secondary), Greece, Lithuania, Poland, Portugal (primary) and Slovenia, the intended instruction time is at
least 5% longer than the compulsory instruction time. However intended instruction time could be different from
actual instruction time of students (Box D1.3).
Instruction time per subject
On average across OECD countries, primary students spend 51% of the compulsory instruction time on three
subjects: reading, writing and literature (25%), mathematics (17%) and the arts (10%). Together with physical
education and health (9%), natural sciences (7%) and social studies (6%), these six study areas form the major part
of the curriculum in all OECD countries where instruction time per subject is specified. Second and other languages,
religion, ethics and moral education, information and communication technologies (ICT), technology, practical
and vocational skills, and other subjects make up the remainder of the non-flexible compulsory curriculum at the
primary level, representing 19% of the compulsory instruction time on average across OECD countries (Table D1.3a
and Figure D1.2a).
Education at a Glance 2018: OECD Indicators   © OECD 2018

339

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Figure D1.2a. Instruction time per subject in primary education (2018)
As a percentage of total compulsory instruction time, in public institutions

Netherlands

England (UK)

Italy

Flemish Comm. (Belgium)

French Comm. (Belgium)

Ireland

Poland3

Chile

Iceland

Latvia

Denmark

Israel

Korea

Natural sciences
Compulsory flexible curriculum

Slovenia

Spain

Estonia

Finland

Costa Rica

Japan

Australia

OECD average2

Hungary

EU22 average2

Norway

Mathematics
Other compulsory curriculum

Germany1

Greece

Portugal

Luxembourg

Czech Republic

Turkey

Austria

Canada

Slovak Republic

Mexico1

France

Russian Federation

D1

100
90
80
70
60
50
40
30
20
10
0

Lithuania

Reading, writing and literature
Second and other languages

%

1. Year of reference 2017.
2. Excludes England (United Kingdom), Flemish Comm. (Belgium), French Comm. (Belgium), Italy and the Netherlands.
3. Excludes the first three years of primary education for which a large proportion of the time allocated to compulsory subjects is flexible.
Countries and economies are ranked in descending order of the proportion of instruction hours devoted to reading, writing and literature.
Source: OECD (2018), Table D1.3a. See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933805173

At the lower secondary level, on average across OECD countries and economies, 40% of the compulsory curriculum
is composed of three subjects: reading, writing and literature (14%), second and other languages (13%) and
mathematics (12%). On average, an additional 12% of the compulsory curriculum is devoted to natural sciences,
10% to social studies, 8% to physical education and health and 7% to the arts. These seven study areas form the
major part of the curriculum for this level of education in all OECD countries where instruction time per subject is
specified. Religion, ethics and moral education, ICT, technology, practical and vocational skills, and other subjects
make up the remainder (12%) of the non-flexible compulsory curriculum for students at this level of education
(Table D1.3b and Figure D1.2b).
This is a significant shift in the allocation of time from primary schooling. On average across OECD countries and
economies, instruction in reading, writing and literature drops from 25% of compulsory instruction time to 14%,
and instruction in mathematics drops from 17% of compulsory instruction time to 12%. Conversely, instruction in
natural science climbs from 7% of the compulsory curriculum to 12%, and in social studies from 6% to 10%, while
instruction in other languages (second and others) climbs from 6% to 13%. At the national level, instruction in
second and other languages accounts for the largest share of the compulsory core curriculum at the lower secondary
level in Costa Rica, France, Germany, Iceland, Israel, Japan and Luxembourg (Tables D1.3a and b).
At the lower secondary level, there is substantial variation in how countries allocate time among the different
subjects within the compulsory curriculum. For example, reading, writing and literature account for 12% or less
of compulsory instruction time in Australia, Costa Rica, the Czech Republic, Finland, Ireland and Japan, but
more than 25% of compulsory instruction time in Greece and Italy (in Italy, it also includes time devoted to
social studies). In Ireland, reading, writing and literature are taught in two national languages, and therefore
the actual estimation of the combined percentage can reach about 21% of the total compulsory instruction
time. Compulsory instruction time devoted to second and other languages also varies largely between countries.
Second-language instruction accounts for less than 7% of compulsory instruction time in Greece, Ireland and
Poland and 13% or more in the French Community of Belgium, Iceland and Japan. In addition, in just over half
of countries with available data, studying another language in addition to a second language is compulsory for
lower secondary students.

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Figure D1.2b. Instruction time per subject in general lower secondary education (2018)
As a percentage of total compulsory instruction time, in public institutions
Reading, writing and literature
Second and other languages

%

Mathematics
Other compulsory curriculum

Natural sciences
Compulsory flexible curriculum

100
90
80

D1

70
60
50
40
30
20

Netherlands

England (UK)

Ireland

Flemish Comm. (Belgium)

Finland

Japan

Costa Rica

Australia

Hungary

Czech Republic

Estonia

Germany3

Korea

Slovenia

Portugal

Israel

Austria

Iceland

OECD average2

Mexico3

Latvia

Poland

Norway

EU22 average2

Chile

Turkey

Spain

Slovak Republic

France

French Comm. (Belgium)

Canada

Denmark

Luxembourg

Greece

Russian Federation

0

Italy1

10

1. Natural sciences included in mathematics. Social studies included with reading, writing and literature.
2. Excludes England (United Kingdom), Flemish Comm. (Belgium) and the Netherlands.
3. Year of reference 2017.
Countries and economies are ranked in descending order of the proportion of instruction hours devoted to reading, writing and literature.
Source: OECD (2018), Table D1.3b. See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933805192

As seen at primary and lower secondary levels, there are significant differences in how time is allocated to school
subjects as students grow older. On average across OECD countries, 28% of instruction time for 7-year-olds is
devoted to reading, writing and literature, 18% for 11-year-olds and 11% for 15-year-olds. By contrast, while an
average of 3% of instruction time for 7-year-olds is devoted to teaching of a second language, 10% of instruction
time for 11-year-olds is spent studying a second language and 2% studying other languages, and for 15-year-olds,
9% of instruction time is devoted to the second language and 5% to other languages. The share of instruction time
dedicated to natural sciences increases from 7% for 7-year-olds to 9% for 11-year-olds and 11% for 15-year-olds,
while instruction time in social studies increases from 5% for 7-year-olds to 9% for 11-year-olds and 15-year-olds.
The portion of instruction time dedicated to the arts slips from 11% for 7-year olds and 9% for 11-year-olds to
4% for 15-year-olds, while the time dedicated to physical education remains fairly constant, at 9% for 7-year-olds
and 8% for 11-year-olds, before dropping to 6% for 15-year-olds (Tables D1.5b, f and j, available on line).
Flexibility in the curriculum
In most countries, central and state authorities establish regulations or recommendations regarding instruction
time and the curriculum. However, local authorities, schools, teachers and/or students also have varying degrees of
freedom in organising instruction time or in choosing subjects.
In about one-third of countries with available data, the allocation of instruction time across grades is flexible
(i.e. instruction time for a specific subject is defined for a certain number of grades or even the whole of compulsory
education, without specifying the time to be allocated to each grade). In such cases, schools/local authorities are free
to decide how much time should be allocated for each grade (Tables D1.2 and D1.4).
Setting compulsory subjects within a flexible timetable is the practice for most subjects in a few countries. In
the Flemish and French Communities of Belgium and in Italy, 83% or more of the compulsory curriculum at the
primary level is organised within a flexible timetable. In England (United Kingdom) and the Netherlands, the whole
curriculum at the primary level is organised in a flexible timetable. At the lower secondary level, similar patterns
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D1

occur in the Flemish Community of Belgium, England (United Kingdom) and the Netherlands. In these countries
and economies, compulsory subjects and total instruction time are specified, but not the time to be allocated
to each subject. Local authorities, schools and/or teachers are free to decide how much time should be allocated
to each compulsory subject. In Scotland (United Kingdom), at both primary and lower secondary levels, some
compulsory subjects are specified, but there is no regulation on total instruction time, which is the responsibility of
local authorities and schools themselves. Excluding these countries, compulsory subjects with flexible timetables
account for less than 2% of the compulsory instruction time at both primary and lower secondary levels, even if they
could be a significant part of the curriculum in some countries. Flexible timetables account for more than 10% of the
compulsory subjects only in Canada at the primary level.
Flexibility in the choice of subjects is less common across OECD countries. On average, 5% of compulsory instruction
time is allocated to subjects chosen by schools at the primary level. At the lower secondary level, 7% of compulsory
instruction time is allocated to subjects chosen by schools and another 4% to subjects chosen by students. However,
some countries allocate a substantial part of the compulsory instruction time to flexible subjects. For example,
10% or more of compulsory instruction time is allocated to subjects chosen by schools in Canada (lower secondary),
Chile, the Czech Republic, Estonia (primary), the French Community of Belgium (lower secondary), Hungary,
the Slovak Republic (lower secondary) and Spain (primary). At least 20% of compulsory instruction time is allocated
in this way in Australia (29% at the primary level and 22% at lower secondary level), the Flemish Community of
Belgium (20% at lower secondary level), Ireland (50% at lower secondary level) and Spain (23% at lower secondary
level). In Australia, Iceland, Norway and Turkey, 15% to 20% of compulsory instruction time is allocated to subjects
chosen by lower secondary students (Tables D1.3a and b).
Non-compulsory instruction time
Non-compulsory instruction time is rare across OECD countries. Only six countries at primary level and eight countries
at lower secondary level devote a known amount of time to non-compulsory instruction. Across OECD countries,
non‑compulsory instruction time is equivalent to an average of 5% of the total compulsory instruction time for
primary students and 4% for lower secondary students. However, a considerable amount of additional non‑compulsory
instruction time is provided in some countries. At the primary level, additional non-compulsory time accounts for
53% of the total compulsory instruction time in Greece, 25% in Portugal and 21% in Slovenia. At the lower secondary
level, non-compulsory instruction time accounts for 11% of the total compulsory instruction time in Finland, 20% in
France, 32% in Greece, 15% in Lithuania and 23% in Slovenia (Tables D1.3a and b).

Definitions
Compulsory instruction time / curriculum refers to the amount and allocation of instruction time that has to be
provided in almost every public school and must be attended by almost all public sector students. The compulsory
curriculum may be flexible, as local authorities, schools, teachers and/or pupils may have varying degrees of freedom
to choose the subjects and/or the allocation of compulsory instruction time.
Compulsory flexible subjects chosen by schools refers to the total amount of compulsory instruction time
indicated by the central authorities, which regional authorities, local authorities, schools or teachers allocate to
subjects of their choice (or subjects they chose from a list defined by central education authorities). It is compulsory
for the school to offer one of these subjects, and students must attend.
Compulsory options chosen by the students refers to the total amount of instruction time in one or more subjects
that pupils have to select (from a set of subjects that are compulsory for schools to offer) in order to cover part of
their compulsory instruction time.
Compulsory subjects with a flexible timetable refers to the total amount of instruction time indicated by the
central authorities for a given group of subjects, which regional authorities, local authorities, schools or teachers
allocate to individual subjects. There is flexibility in the time spent on a subject, but not in the subjects to be taught.
Flexible allocation of instruction time across multiple grades refers to the case where the curriculum only indicates
the total instruction time for a specific subject for a certain number of grades, or even the whole of compulsory
education, without specifying the time to be allocated to each grade. In such cases, schools/local authorities are free
to decide how much time should be assigned for each grade.
Instruction time refers to the time a public school is expected to provide instruction to students on all the subjects
integrated into the compulsory and non-compulsory curriculum, on school premises or in before-school/after‑school
activities that are formal parts of the compulsory programme. Instruction time excludes breaks between classes or

342 Education at a Glance 2018: OECD Indicators   © OECD 2018

How much time do students spend in the classroom? – INDICATOR D1

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other types of interruptions, non-compulsory time outside the school day, time dedicated to homework activities,
individual tutoring or private study and examination periods (days for non-school-based examinations, e.g. national
examinations).
Intended instruction time refers to the number of hours per year of the compulsory and non-compulsory part
of the curriculum that students are entitled to receive in public schools. The intended curriculum can be based
on regulations or standards of the central (or top-level) education authorities or may be established as a set of
recommendations at the regional level.
The non-compulsory part of the curriculum refers to the total amount of instruction time to which students are
entitled beyond the compulsory hours of instruction and that almost every public school is expected to provide.
Subjects can vary from school to school or from region to region and take the form of elective subjects. Students
are not required to choose one of the elective subjects, but all public schools are expected to offer this possibility.

Methodology
This indicator captures intended instruction time (as established in public regulations) as a measure of learning in
formal classroom settings. It does not show the actual number of hours of instruction that students receive and
does not cover learning outside of the formal classroom setting. Differences may exist across countries between
the regulatory minimum hours of instruction and the actual hours of instruction received by students. Given such
factors as school timetables, lesson cancellations and teacher absenteeism, schools may not consistently attain the
regulatory minimum instruction time (see Box D1.1 in [OECD, 2007[7]]).
The indicator also illustrates how minimum instruction hours are allocated across different curricular areas.
It shows the intended net hours of instruction for those grades that are part of compulsory full-time general
education. Although the data are difficult to compare among countries because of different curricular policies, they
nevertheless provide an indication of how much formal instruction time is considered necessary for students to
achieve the desired educational goals.
When the allocation of instruction time across grades is flexible (i.e. instruction time for a specific subject is defined
for a certain number of grades, or even the whole of compulsory education, without specifying the time to be
allocated to each grade) instruction time per age or level of education was estimated by dividing the total number of
instruction hours per the number of grades.
For more information please see the OECD Handbook for Internationally Comparable Education Statistics 2018 (OECD,
2018[8]) and Annex 3 for country-specific notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Lithuania was not an OECD member at the time of preparation of this publication. Accordingly, Lithuania does not
appear in the list of OECD members and is not included in the zone aggregates.

Source
Data on instruction time are from the 2017 Joint Eurydice-OECD Instruction time data collection and refer to
instruction time during compulsory primary and full-time (lower and upper) secondary general education for the
school year 2017/18.
Note regarding data from Israel
The statistical data for Israel are supplied by and are under the responsibility of the relevant Israeli authorities. The use
of such data by the OECD is without prejudice to the status of the Golan Heights, East Jerusalem and Israeli settlements
in the West Bank under the terms of international law.

References
OECD (2018), OECD Handbook for Internationally Comparative Education Statistics 2018: Concepts, Standards, Definitions
and Classifications, OECD Publishing, Paris, https://doi.org/10.1787/9789264304444-en.

[8]

OECD (2017), Education at a Glance 2017: OECD Indicators, OECD Publishing, Paris, http://dx.doi.org/10.1787/eag-2017-en.

[4]

OECD (2015), Education at a Glance 2015: OECD Indicators, OECD Publishing, Paris, http://dx.doi.org/10.1787/eag-2015-en.

[3]

OECD (2011), Education at a Glance 2011: OECD Indicators, OECD Publishing, Paris, http://dx.doi.org/10.1787/eag-2011-en.

[5]

OECD (2007), Education at a Glance 2007: OECD Indicators, OECD Publishing, Paris, http://dx.doi.org/10.1787/eag-2007-en.

[7]

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343

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Under embargo until 11/09/2018 at 11.00am CEST

D1

OECD/NCES (2018), Education at a Glance Subnational Supplement, OECD/National Center for Education Statistics, Paris
and Washington, DC, https://nces.ed.gov/surveys/annualreports/oecd/index.asp.

[6]

Pellegrini, A. and C. Bohn (2005), “The role of recess in children’s cognitive performance and school adjustment”,
Educational Researcher, Vol. 34/1, pp. 13-19, http://dx.doi.org/10.3102/0013189x034001013.

[1]

Pellegrini, A. et al. (2002), “A short-term longitudinal study of children’s playground games across the first year of
school: Implications for social competence and adjustment to school”, American Educational Research Journal, Vol. 39/4,
pp. 991‑1015, http://dx.doi.org/10.3102/00028312039004991.

[2]

Indicator D1 Tables
1 2 https://doi.org/10.1787/888933805059

Table D1.1

Instruction time in compulsory general education (2018)

Table D1.2

Organisation of compulsory general education (2018)

Table D1.3a Instruction time per subject in primary education (2018)
Table D1.3b Instruction time per subject in general lower secondary education (2018)
WEB Table D1.4

Instruction time in compulsory general education, by age (2018)

WEB Table D1.5a Instruction time per subject for 6-year-olds (2018)
WEB Table D1.5b Instruction time per subject for 7-year-olds (2018)
WEB Table D1.5c Instruction time per subject for 8-year-olds (2018)
WEB Table D1.5d Instruction time per subject for 9-year-olds (2018)
WEB Table D1.5e Instruction time per subject for 10-year-olds (2018)
WEB Table D1.5f Instruction time per subject for 11-year-olds (2018)
WEB Table D1.5g Instruction time per subject for 12-year-olds (2018)
WEB Table D1.5h Instruction time per subject for 13-year-olds (2018)
WEB Table D1.5i Instruction time per subject for 14-year-olds (2018)
WEB Table D1.5j Instruction time per subject for 15-year-olds (2018)
WEB Table D1.5k Instruction time per subject for 16-year-olds (2018)
WEB Table D1.5l Instruction time per subject for 17-year-olds (2018)
Cut-off date for the data: 18 July 2018. Any updates on data can be found on line at http://dx.doi.org/10.1787/eag-data-en. Data can also be found
at http://stats.oecd.org/, Education at a Glance Database.

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Table D1.1. [1/2] Instruction time in compulsory general education1 (2018)
By level of education, in public institutions
Primary

Number
of grades
that are part
of compulsory
education

Noncompulsory
instruction
time

Intended
instruction
time

Compulsory
instruction
time

Noncompulsory
instruction
time

Intended
instruction
time

Total number of hours

Compulsory
instruction
time

OECD

Average hours per year

(1)

(2)

(3)

(4)=(2)+(3)

(5)

(6)

(7)=(5)+(6)

7
4
6
6
5
7
6
6
5
4
6
4
7
6
6
5
6
6
6
6
6
6
6
7
6
6
4
6
6
6
6
4
6

1 000
705
920
1 039
694
1 051
661
651
864
701
752
689
729
910
959
891
763
655
599
924
800
940
m
753
619
834
677
682
792
766
796
720
971

m
m
a
a
m
a
a
33
a
a
398
a
a
a
a
a
a
a
m
a
a
m
m
a
59
205
a
140
a
m
m
a
m

m
m
920
1 039
m
1 051
661
683
864
701
1 151
689
729
910
959
891
763
655
m
924
800
m
m
753
677
1 039
677
822
792
m
m
720
m

7 000
2 820
5 518
6 233
3 469
7 360
3 964
3 905
4 320
2 804
4 514
2 754
5 100
5 460
5 755
4 455
4 576
3 928
3 595
5 544
4 800
5 640
m
5 272
3 713
5 004
2 707
4 091
4 750
4 593
4 773
2 880
5 824

m
m
a
a
m
a
a
195
a
a
2 390
a
a
a
a
a
a
a
m
a
a
m
m
a
352
1 231
a
840
a
m
m
a
m

m
m
5 518
6 233
m
7 360
3 964
4 100
4 320
2 804
6 903
2 754
5 100
5 460
5 755
4 455
4 576
3 928
m
5 544
4 800
m
m
5 272
4 065
6 235
2 707
4 931
4 750
m
m
2 880
m

Flemish Comm. (Belgium)
French Comm. (Belgium)
England (UK)
Scotland (UK)

6
6
6
7

822
835
m
m

a
a
a
a

822
835
m
m

4 931
5 012
m
m

a
a
a
a

4 931
5 012
m
m

OECD average
EU22 average

6
6

799
775

m
m

m
m

4 620
4 337

m
m

m
m

Argentina
Brazil
China
Colombia
Costa Rica
India
Indonesia
Lithuania
Russian Federation
Saudi Arabia
South Africa

m
5
m
5
6
m
m
4
4
m
m

m
m
m
m
1 147
m
m
589
598
m
m

m
m
m
m
a
m
m
36
m
m
m

m
m
m
m
1 147
m
m
626
m
m
m

m
m
m
m
6 880
m
m
2 357
2 393
m
m

m
m
m
m
a
m
m
146
m
m
m

m
m
m
m
6 880
m
m
2 503
m
m
m

G20 average

m

m

m

m

m

m

m

Countries

Australia
Austria
Canada
Chile
Czech Republic
Denmark
Estonia
Finland2
France
Germany3, 4
Greece
Hungary
Iceland2
Ireland
Israel
Italy
Japan5
Korea2
Latvia
Luxembourg
Mexico3
Netherlands6
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden2
Switzerland
Turkey
United States

Partners

Economies

Note: Columns showing instruction time in compulsory upper secondary education (i.e. Columns 19-25) are available for consultation on line. See Definitions and
Methodology sections for more information. Data available at http://stats.oecd.org/, Education at a Glance Database.
1. Refers to full-time compulsory education and excludes pre-primary education, even if compulsory.
2. Estimated number of hours by level of education based on the average number of hours per year, as the allocation of instruction time across multiple grades is flexible.
3. Year of reference 2017.
4. Excludes the last year of compulsory education, which can be classified at either the lower secondary or the upper secondary level.
5. Average planned instruction time in each school at the beginning of the school year.
6. The number of grades in lower secondary education is three or four, depending on the track. The fourth year of pre-vocational secondary education (VMBO) was
excluded from the calculation.
Source: Source: OECD (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933805078

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chapter D Teachers, the Learning Environment and the Organisation of Schools
Under embargo until 11/09/2018 at 11.00am CEST
Table D1.1. [2/2] Instruction time in compulsory general education1 (2018)
By level of education, in public institutions
Lower secondary

Total number of hours

Compulsory
instruction
time

Noncompulsory
instruction
time

Intended
instruction
time

(9)

(10)

(11)=(9)+(10)

(12)

(13)

(14)=(12)+(13)

(15)

4
4
3
2
4
3
3
3
4
5
3
4
3
3
3
3
3
3
3
3
3
3
4
3
3
3
5
3
3
3
3
4
3

1 000
900
924
1 077
897
1 200
823
808
946
916
791
797
839
924
984
990
893
842
794
845
1 167
1 000
m
874
827
892
823
766
1 054
766
936
843
1 020

m
m
3
a
m
a
a
87
189
a
253
a
a
a
a
a
a
a
m
a
a
m
m
a
64
27
a
179
a
m
m
a
m

m
m
927
1 077
m
1 200
823
894
1 135
916
1 044
797
839
924
984
990
893
842
m
845
1 167
m
m
874
891
919
823
944
1 054
m
m
843
m

4 000
3 600
2 771
2 155
3 587
3 600
2 468
2 423
3 784
4 582
2 374
3 186
2 516
2 772
2 951
2 970
2 680
2 525
2 381
2 535
3 500
3 000
m
2 622
2 482
2 675
4 117
2 298
3 161
2 297
2 807
3 371
3 059

m
m
9
a
m
a
a
261
756
a
758
a
a
a
a
a
a
a
m
a
a
m
m
a
192
80
a
536
a
m
m
a
m

m
m
2 781
2 155
m
3 600
2 468
2 683
4 540
4 582
3 132
3 186
2 516
2 772
2 951
2 970
2 680
2 525
m
2 535
3 500
m
m
2 622
2 674
2 756
4 117
2 833
3 161
m
m
3 371
m

11
8
9
8
9
10
9
9
9
9
9
8
10
9
9
8
9
9
9
9
9
9
10
10
9
9
9
9
9
9
9
8
9

11 000
6 420
8 289
8 388
7 056
10 960
6 431
6 327
8 104
7 386
6 888
5 940
7 616
8 232
8 706
7 425
7 256
6 453
5 977
8 079
8 300
8 640
m
7 894
6 195
7 679
6 824
6 389
7 911
6 890
7 580
6 251
8 884

m
m
9
a
m
a
a
456
756
a
3 147
a
a
a
a
a
a
a
m
a
a
m
m
a
544
1 311
a
1 376
a
m
m
a
m

m
m
8 299
8 388
m
10 960
6 431
6 783
8 860
7 386
10 035
5 940
7 616
8 232
8 706
7 425
7 256
6 453
m
8 079
8 300
m
m
7 894
6 738
8 991
6 824
7 764
7 911
m
m
6 251
m

Flemish Comm. (Belgium)
French Comm. (Belgium)
England (UK)
Scotland (UK)

2
2
3
3

948
955
m
m

a
a
a
a

948
955
m
m

1 896
1 909
m
m

a
a
a
a

1 896
1 909
m
m

8
8
9
10

6 827
6 921
m
m

a
a
a
a

6 827
6 921
m
m

OECD average
EU22 average

3
3

913
894

m
m

m
m

2 913
2 913

m
m

m
m

9
9

7 533
7 250

m
m

m
m

Argentina
Brazil
China
Colombia
Costa Rica
India
Indonesia
Lithuania
Russian Federation
Saudi Arabia
South Africa

m
4
m
4
3
m
m
6
5
m
m

m
m
m
m
1 120
m
m
787
803
m
m

m
m
m
m
a
m
m
116
m
m
m

m
m
m
m
1 120
m
m
903
m
m
m

m
m
m
m
3 360
m
m
4 723
4 016
m
m

m
m
m
m
a
m
m
697
m
m
m

m
m
m
m
3 360
m
m
5 420
m
m
m

m
9
m
9
9
m
m
10
9
m
m

m
m
m
m
10 240
m
m
7 080
6 410
m
m

m
m
m
m
a
m
m
843
m
m
m

m
m
m
m
10 240
m
m
7 922
m
m
m

G20 average

m

m

m

m

m

m

m

m

m

m

m

Intended
instruction
time

Intended
instruction
time

(8)

Noncompulsory
instruction
time

Noncompulsory
instruction
time

Theoretical
duration in
years

Compulsory
instruction
time

Number
of grades
that are
part of
compulsory
education

D1
OECD

Primary and lower secondary
Total number of hours

Compulsory
instruction
time

Average hours per year

(16)=(5)+(12) (17)=(6)+(13) (18)=(16)+(17)

Countries

Australia
Austria
Canada
Chile
Czech Republic
Denmark
Estonia
Finland2
France
Germany3, 4
Greece
Hungary
Iceland2
Ireland
Israel
Italy
Japan5
Korea2
Latvia
Luxembourg
Mexico3
Netherlands6
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden2
Switzerland
Turkey
United States

Partners

Economies

Note: Columns showing instruction time in compulsory upper secondary education (i.e. Columns 19-25) are available for consultation on line. See Definitions and
Methodology sections for more information. Data available at http://stats.oecd.org/, Education at a Glance Database.
1. Refers to full-time compulsory education and excludes pre-primary education, even if compulsory.
2. Estimated number of hours by level of education based on the average number of hours per year, as the allocation of instruction time across multiple grades is flexible.
3. Year of reference 2017.
4. Excludes the last year of compulsory education, which can be classified at either the lower secondary or the upper secondary level.
5. Average planned instruction time in each school at the beginning of the school year.
6. The number of grades in lower secondary education is three or four, depending on the track. The fourth year of pre-vocational secondary education (VMBO) was
excluded from the calculation.
Source: Source: OECD (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933805078

346 Education at a Glance 2018: OECD Indicators   © OECD 2018

How much time do students spend in the classroom? – INDICATOR D1

chapter D

Under embargo until 11/09/2018 at 11.00am CEST
Table D1.2. Organisation of compulsory general education1 (2018)
By level of education, in public institutions
Primary

Lower secondary

OECD

Flexible
Number
Flexible
Number
Number allocation of
Number allocation of of grades
of grades
instruction
of days
Average
that are
instruction
of days
Average
that are
number of students go time across
part of
number of students go time across
part of
multiple
multiple compulsory Theoretical instruction to school
compulsory Theoretical instruction to school
grades
education starting age days per year per week
grades
education starting age days per year per week
(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

7
4
6
6
5
7
6
6
5
4
6
4
7
6
6
5
6
6
6
6
6
6
6
7
6
6
4
6
6
6
6
4
6

5
6
6
6
6
6
7
7
6
6
6
6
6
6
6
6
6
6
7
6
6
6
5
6
7
6
6
6
6
7
6
6
6

200
180
183
180
196
200
175
188
162
188
177
180
170
182
219
200
201
190
169
180
200
m
194
190
178
180
188
190
175
178
188
180
180

5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
4.5
5.0
5.0
5.0
5.0
5.0
6.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0

No
No
No
No
Yes
No
Yes
Yes
No
No
No
No
Yes
No
No
No
No
Yes
No
No
No
Yes
m
Yes
Yes
Yes
No
No
No
Yes
No
No
m

4
4
3
2
4
3
3
3
4
5
3
4
3
3
3
3
3
3
3
3
3
3
4
3
3
3
5
3
3
3
3
4
3

12
10
12
12
11
13
13
13
11
10
12
10
13
12
12
11
12
12
13
12
12
12
11
13
13
12
10
12
12
13
12
10
12

200
180
183
178
196
200
175
188
162
188
166
180
170
165
209
200
201
190
173
169
200
m
192
190
178
178
188
185
175
178
188
180
180

5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
4.5
5.0
5.0
5.0
5.0
5.0
6.0
6.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0

No
No
No
No
Yes
No
Yes
Yes
No
No
No
No
Yes
No
Yes
No
No
Yes
No
No
No
Yes
m
Yes
Yes
Yes
No
No
No
Yes
No
No
m

Flemish Comm. (Belgium)
French Comm. (Belgium)
England (UK)
Scotland (UK)

6
6
6
7

6
6
5
5

159
179
190
190

4.5
5.0
5.0
5.0

No
No
Yes
Yes

2
2
3
3

12
12
11
12

160
179
190
190

4.5
5.0
5.0
5.0

No
No
Yes
Yes

OECD average
EU22 average

6
6

6
6

185
182

5.0
5.0

m
m

3
3

12
12

183
180

5.0
5.0

m
m

Argentina
Brazil
China
Colombia
Costa Rica
India
Indonesia
Lithuania
Russian Federation
Saudi Arabia
South Africa

m
5
m
5
6
m
m
4
4
m
m

m
6
m
6
6
m
m
7
7
m
m

m
200
m
200
200
m
m
170
169
m
m

m
5.0
m
5.0
5.0
m
m
5.0
5.0
m
m

m
m
m
m
No
m
m
Yes
No
m
m

m
4
m
4
3
m
m
6
5
m
m

m
11
m
11
12
m
m
11
11
m
m

m
200
m
200
200
m
m
181
175
m
m

m
5.0
m
5.0
5.0
m
m
5.0
5.0
m
m

m
m
m
m
No
m
m
Yes
No
m
m

G20 average

m

m

m

m

m

m

m

m

m

m

Countries

Australia
Austria
Canada
Chile
Czech Republic
Denmark
Estonia
Finland2
France
Germany3, 4
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Luxembourg
Mexico3
Netherlands5
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden2
Switzerland
Turkey
United States

Partners

Economies

Note: Columns showing the organisation of compulsory upper secondary education (i.e. Columns 11-15) are available for consultation on line. See Definitions and
Methodology sections for more information. Data available at http://stats.oecd.org/, Education at a Glance Database.
1. Refers to full-time compulsory education and excludes pre-primary education, even if compulsory.
2. Allocation of instruction time across multiple levels of education is flexible.
3. Year of reference 2017.
4. Excludes the last year of compulsory education, which can be classified at either the lower secondary or the upper secondary level.
5. The number of grades in lower secondary education is three or four, depending on the track. The fourth year of pre-vocational secondary education (VMBO) was
excluded from the calculation.
Source: OECD (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933805097

Education at a Glance 2018: OECD Indicators   © OECD 2018

347

D1

chapter D Teachers, the Learning Environment and the Organisation of Schools
Under embargo until 11/09/2018 at 11.00am CEST

Information
and communication
technologies (ICT)

Technology

Practical and
vocational skills

Other subjects

Compulsory subjects
with flexible timetable

Compulsory options
chosen by the students

Compulsory flexible
subjects chosen
by schools

Total compulsory
curriculum

Non-compulsory
curriculum

(17)

(18)

x(11)
x(17)
a
x(16)
1
x(14)
x(16)
x(17)
x(3)
1
3
a
3
x(17)
a
a
a
x(13)
1
a
a
x(14)
m
a
4
a
2
x(17)
a
m
m
a
m

4d
x(3)
0
3
4d
a
3
a
x(3)
1
a
4
a
x(3)
x(3)
x(14)
a
x(12)
a
a
a
x(14)
m
a
4
2
a
5
a
m
m
a
m

x(11)
6
0
x(16)
x(11)
4
a
a
a
0
a
a
x(8)
a
4
a
a
x(3)
4
a
a
x(14)
m
2
a
a
2
2
a
m
m
1
m

x(16)
4
1
2
x(16)
23
a
a
a
3
a
a
x(15)
11
a
a
13
25d
10
a
a
a
m
a
4
4
x(16)
1
0
m
m
7
m

x(16)
a
17
a
a
8d
a
4
a
a
a
a
a
a
a
84d
7
a
a
a
a
100d
m
a
a
2
a
a
a
m
a
a
m

m
a
a
0
x(16)
a
a
a
a
1
a
a
5d
a
a
a
a
a
a
a
a
a
m
a
a
a
x(16)
a
x(16)
m
a
a
m

29d
a
5
14d
14d
a
12d
4
a
a
6
10
x(15)
a
5
x(17)
a
a
6
a
a
a
m
1
9
3
8d
a
20d
m
a
a
m

100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
m
100
100
100
100
100
100
m
m
100
m

m
m
a
a
m
a
a
5
a
a
53
a
a
a
a
a
a
a
m
a
a
m
m
a
9
25
a
21
a
m
m
a
m

7 x(17)
7
a
x(14) x(14)
m
m

x(3)
x(14)
x(14)
m

a
a
a
m

x(17)
a
a
a

93d
83d
100d
a

a
a
a
a

x(14)
a
a
a

100
100
100
m

a
a
a
a

1
1

1
2

1
1

5
4

1
1

0
0

5
5

100
100

5
8

m
m
m
m
5
m
m
4
1
m
m

m
m
m
m
a
m
m
a
a
m
m

m
a
m
m
a
m
m
x(8)
4
m
m

m
a
m
m
a
m
m
a
a
m
m

m
m
m
m
9
m
m
a
a
m
m

m
m
m
m
a
m
m
a
a
m
m

m
m
m
m
a
m
m
a
a
m
m

m
m
m
m
a
m
m
a
9
m
m

m
m
m
m
100
m
m
100
100
m
m

m
m
m
m
a
m
m
6
m
m
m

m

m

m

m

m

m

m

m

m

m

Arts

(16)

Physical education
and health

(15)

Other languages

(14)

Second language

(13)

Social studies

(12)

Natural sciences

(11)

Mathematics

(10)

Reading, writing
and literature

(9)

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

24
30
31
20
28
21
23
23
38
26
27
25
20
20
22
x(14)
24
21
21
29
35
x(14)
m
26
19
26
32
22
23
m
m
30
m

17
17
19
16
17
12
15
15
21
21
14
16
16
17
18
x(14)
17
14
17
19
27
x(14)
m
17
15
26
17
17
18
m
m
17
m

6
13d
6
9
10d
5
7
10
7d
4
12
4
8
4d
8d
x(14)
7
9d
5
7
13
x(14)
m
7
10
7
6
8
7
m
m
5
m

8d
x(3)
5
9
x(3)
3
5
4
3
6
6
a
13d
8
8
x(14)
6
9d
6
2
10
x(14)
m
7
4
7
3
7d
7
m
m
13
m

x(16)
2
1
3
8
5
8
7
6
5
8
2
6d
14
6
9
1
6
8
15
m
x(14)
m
7
11
6
6
8
11
m
a
5
m

x(16)
a
a
x(16)
a
1
2
1
a
a
2
a
x(5)
a
3
a
a
a
1
a
a
a
m
a
a
a
x(16)
a
x(16)
m
a
a
m

8
11
9
9
8
6
11
9
13
11
9
20
9
4
6
x(14)
10
7
8
10
5
x(14)
m
11
15
8
8
14
8
m
m
14
m

5
x(4)
9
9
5
0
10
5
10
x(13)
8
3
15
x(16)
16
5
8
4
14
7
10
3
16
4
d
19
x(4)
12
10
6
14
x(14)
7
12
3
9 x(4, 13)
12
2
11
7
5
5
x(14)
x(14)
m
m
14
8
7
a
9
a
10
4
15
x(4)
x(16)
5
m
m
m
m
7
2
m
m

x(14)
x(14)
x(14)
m

x(14)
x(14)
x(14)
m

x(14)
x(14)
x(14)
m

x(14)
x(14)
x(14)
m

x(14)
2
x(14)
m

a
a
a
a

x(14)
7
x(14)
m

x(14)
x(14)
x(14)
m

OECD average4
EU22 average4

25
25

17
17

7
7

6
5

6
7

0
1

9
10

10
11

5
4

Argentina
Brazil
China
Colombia
Costa Rica
India
Indonesia
Lithuania
Russian Federation
Saudi Arabia
South Africa

m
m
m
m
23
m
m
31
36
m
m

m
m
m
m
19
m
m
19
16
m
m

m
m
m
m
14
m
m
4
8
m
m

m
m
m
m
9
m
m
4
a
m
m

m
m
m
m
12
m
m
8
6
m
m

m
a
m
m
a
m
m
a
a
m
m

m
m
m
m
5
m
m
12
12
m
m

m
m
m
m
5
m
m
17d
8
m
m

G20 average

m

m

m

m

m

m

m

m

D1
OECD

Religion/ ethics/
moral education

Table D1.3a. Instruction time per subject in primary education (2018)
As a percentage of total compulsory instruction time, in public institutions

Countries

Australia
Austria
Canada
Chile
Czech Republic
Denmark
Estonia
Finland1
France
Germany2
Greece
Hungary
Iceland
Ireland3
Israel
Italy4
Japan
Korea
Latvia
Luxembourg3
Mexico2
Netherlands4
New Zealand
Norway
Poland5
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United States
Economies

Partners

Flemish Comm. (Belgium)4
French Comm. (Belgium)4
England (UK)4
Scotland (UK)

Note: The averages were adjusted to add up to 100% and do not correspond exactly to the average of each column. Please refer to Tables D1.5a to D1.5l, available
on line, for instruction time per subject for each age (see StatLink at the end of the indicator). See Definitions and Methodology sections for more information. Data
available at http://stats.oecd.org/, Education at a Glance Database.
1. Allocation of instruction time across multiple levels of education is flexible.
2. Year of reference 2017.
3. The second language of instruction includes other national languages taught.
4. England (United Kingdom), Flemish Comm. (Belgium), French Comm. (Belgium), Italy and the Netherlands are not included in the averages.
5. Excludes the first three years of primary education for which a large proportion of the time allocated to compulsory subjects is flexible.
Source: OECD (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933805116

348 Education at a Glance 2018: OECD Indicators   © OECD 2018

chapter D

How much time do students spend in the classroom? – INDICATOR D1

Under embargo until 11/09/2018 at 11.00am CEST

Reading, writing
and literature

Mathematics

Natural sciences

Social studies

Second language

Other languages

Physical education
and health

Arts

Religion/ ethics/
moral education

Information
and communication
technologies (ICT)

Technology

Practical and
vocational skills

Other subjects

Compulsory subjects
with flexible timetable

Compulsory options
chosen by the students

Compulsory flexible
subjects chosen
by schools

Total compulsory
curriculum

Non-compulsory
curriculum

OECD

Table D1.3b. Instruction time per subject in general lower secondary education (2018)
As a percentage of total compulsory instruction time, in public institutions

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

(13)

(14)

(15)

(16)

(17)

(18)

12
13
19
16
12
18
13
12
17
13
25
13
14
9
14
33d
12
13
15
19
14
x(14)
m
15
14
13
16
13
17
m
m
16
m

12
13
15
16
12
13
14
13
14
12
12
11
14
12
14
20d
12
11
16
13
14
x(14)
m
12
12
13
14
13
13
m
m
14
m

11
12
9
11
17
13
21
16
12
11
13
11
8
x(16)
13d
x(2)
12
20d
10
8
17
x(14)
m
9
14
18
12
17
11
m
m
11
m

10d
11
13
11
9
8
11
8
12d
10
8
9
8d
12
18
x(1)
11
15d
14
11
12
x(14)
m
9
12
14
11
15d
10
m
m
8
m

x(16)
12
7
8
10
8
10
8
12
12
6
10
19d
3
11
10
13
10
8
12
9
x(14)
m
8
3
8
10
11
11
m
m
10
m

x(16)
a
a
x(16)
5
8
10
5
7
6
6
a
x(5)
x(16)
10
7
a
a
6
13
a
x(14)
m
x(15)
2
8
x(16)
x(15)
x(16)
m
m
x(15)
m

8
12
10
5
8
5
6
12
12
8
6
17
8
6
6
7
10
8
6
8
6
x(14)
m
9
12
7
7
9
7
m
m
5
m

4
13
7
8
8
x(15)
6
7
8
9
6
7
8d
x(16)
4
13
7
8
6
9
6
x(14)
m
9
5
7
6
8
x(16)
m
m
6
m

x(4)
7
2
5
x(13)
2
x(16)
4
x(4)
5
6
3
x(4)
x(16)
9
3
3
x(4)
a
7
8
x(14)
m
6
a
a
3
x(4)
4
m
m
8
m

x(11)
x(17)
a
x(16)
1
x(15)
x(16)
x(17)
x(17)
1
3
3
2
x(16)
x(3)
a
a
x(3)
1
a
a
x(14)
m
a
2
2
3
x(17)
a
m
m
3
m

4d
a
3
3
2d
x(15)
5
a
4
2
3
3
a
x(16)
x(3)
7
3
x(12)
a
a
11
x(14)
m
a
1
a
x(16)
4
x(16)
m
m
3
m

x(11)
7
1
x(16)
x(11)
2
a
6
a
2
2
a
x(8)
x(16)
a
a
a
x(3)
4
a
a
x(14)
m
7
a
a
3
a
a
m
m
1
m

x(16)
a
1
3
x(16)
21
a
a
1
2
a
3
x(15)
2
a
a
12
9
7
a
3
a
m
x(15)
4
a
x(16)
2
3
m
m
a
m

x(16)
a
0
a
a
a
a
6
a
a
a
a
a
6d
a
a
5
a
a
a
a
100d
m
a
9
6
a
a
a
m
a
a
m

18
1
4
0
x(16)
5d
a
a
a
7
a
a
20d
a
a
a
a
x(16)
a
a
a
a
m
15d
a
a
x(16)
7d
x(16)
m
m
16d
m

22d
a
10
15d
15d
a
4d
4
a
a
3
10
x(15)
50d
0
x(17)
a
5d
9
a
a
a
m
x(15)
8
2
13d
a
23d
m
a
a
m

100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
m
100
100
100
100
100
100
m
m
100
m

m
m
0
a
m
a
a
11
20
a
32
a
a
a
a
a
a
a
m
a
a
m
m
a
8
3
a
23
a
m
m
a
m

x(14)
17
x(14)
m

x(14)
14
x(14)
m

x(14)
9
x(14)
m

x(14)
13
x(14)
m

x(14)
13
x(14)
m

x(14)
a
a
m

x(14)
9
x(14)
m

x(14)
3
x(14)
m

6
6
x(14)
m

a
x(16)
x(14)
m

x(14)
3
x(14)
m

a
x(16)
x(14)
m

a
a
x(14)
a

73d
a
100d
a

a
x(16)
a
a

20
13d
a
a

100
100
100
m

a
a
a
a

OECD average5
EU22 average5

14
15

12
12

12
12

10
10

9
9

4
5

8
8

7
7

4
3

1
1

2
2

1
2

3
2

1
1

4
1

7
8

100
100

4
6

Argentina
Brazil
China
Colombia
Costa Rica
India
Indonesia
Lithuania
Russian Federation
Saudi Arabia
South Africa

m
m
m
m
12
m
m
18
22
m
m

m
m
m
m
12
m
m
13
16
m
m

m
m
m
m
12
m
m
13
17
m
m

m
m
m
m
14
m
m
15
9
m
m

m
m
m
m
7
m
m
10
10
m
m

m
a
m
m
7
m
m
5
a
m
m

m
m
m
m
5
m
m
5
7
m
m

m
m
m
m
10
m
m
7
5
m
m

m
m
m
m
2
m
m
3
a
m
m

m
m
m
m
5
m
m
3
2
m
m

m
a
m
m
a
m
m
5
5
m
m

m
m
m
m
7
m
m
a
1
m
m

m
m
m
m
5
m
m
1
a
m
m

m
m
m
m
a
m
m
a
a
m
m

m
m
m
m
a
m
m
a
m
m
m

m
m
m
m
2
m
m
a
7
m
m

m
m
m
m
100
m
m
100
100
m
m

m
m
m
m
a
m
m
15
m
m
m

G20 average

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

Countries

Australia1
Austria
Canada
Chile
Czech Republic
Denmark
Estonia
Finland2
France
Germany3
Greece
Hungary
Iceland
Ireland4
Israel
Italy
Japan
Korea
Latvia
Luxembourg4
Mexico3
Netherlands5
New Zealand
Norway
Poland6
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United States
Economies

Partners

Flemish Comm. (Belgium)5
French Comm. (Belgium)
England (UK)5
Scotland (UK)

Note: The averages were adjusted to add up to 100% and do not correspond exactly to the average of each column. Please refer to Tables D1.5a to D1.5l, available
on line, for instruction time per subject for each age (see StatLink at the end of the indicator). See Definitions and Methodology sections for more information. Data
available at http://stats.oecd.org/, Education at a Glance Database.
1. The intended instruction time derived from the Australian Curriculum assumes that certain subjects, which may be considered compulsory in years 7 and 8, could be
delivered to students as electives in years 9 and 10.
2. Allocation of instruction time across multiple levels of education is flexible.
3. Year of reference 2017.
4. The second language of instruction includes other national languages taught.
5. England (United Kingdom), Flemish Comm. (Belgium) and the Netherlands are not included in the averages.
6. Second and other languages included in compulsory flexible curriculum for grades 8 and 9.
Source: OECD (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933805135

Education at a Glance 2018: OECD Indicators   © OECD 2018

349

D1

Under embargo until 11/09/2018 at 11.00am CEST

WHAT IS THE STUDENT-TEACHER RATIO AND HOW BIG
ARE CLASSES?
• The average primary school class in OECD countries in 2016 has 21 students in public institutions
and 20 students in private institutions. The difference between class sizes in public and private
primary school varies substantially across OECD countries, but it is considerably larger in partner
countries.

INDICATOR D2

• The student-teacher ratio is about the same in upper secondary general and vocational programmes
across OECD countries.

• On average across OECD countries, there are 15 students per teacher in primary education, 13 students
per teacher in secondary education and 15 students per teacher in tertiary education.

Figure D2.1. Average class size in primary education, by type of institutions (2016)
Number of students
per class

Public institutions

Private institutions

35
30
25
20
15
10
0

Chile
Israel
Japan
United Kingdom
Ireland
Colombia
Brazil
Mexico
Australia
Netherlands1
Korea
France
Denmark
OECD average
Hungary
Turkey
Portugal
United States
Czech Republic
Spain
Germany
EU22 average
Russian Federation
Slovenia
Finland
Poland
Sweden
Switzerland
Italy
Estonia
French Comm. (Belgium)
Iceland
Austria
Slovak Republic
Greece
Latvia
Lithuania
Costa Rica

5

1. Primary education includes pre-primary programmes.
Countries are ranked in descending order of the average class size in primary education public institutions.
Source: OECD / UIS / Eurostat (2018), Table D2.1. See Source for more information and Annex 3 for notes (http://dx.doi.org/10.1787/
eag-2018-36-en).
1 2 https://doi.org/10.1787/888933805306

Context
Class sizes and student-teacher ratios are much-discussed aspects of education and, along with
students’ instruction time (see Indicator D1), teachers’ working time and the division of teachers’
time between teaching and other duties (see Indicator D4), these ratios are among the determinants
of the demand for teachers. Together with teachers’ salaries (see Indicator D3) and age distribution
(see Indicator D5), class size and student-teacher ratios also have a considerable impact on the level of
current expenditure on education (see Indicators C6 and C7).
Smaller classes are often seen as beneficial, because they allow teachers to focus more on the needs of
individual students and reduce the amount of class time needed to deal with disruptions. Yet, while
there is some evidence that smaller classes may benefit specific groups of students, such as those from
disadvantaged backgrounds (Piketty and Valdenaire, 2006[1]), overall evidence of the effect of class
size on student performance is mixed (Fredriksson, Öckert and Oosterbeek, 2012[2]) (OECD, 2016[3]).
The ratio of students to teaching staff is an indicator of how resources for education are allocated.
Smaller student-teacher ratios often have to be weighed against higher salaries for teachers, investing
in their professional development, greater investment in teaching technology, or more widespread
use of assistant teachers and other paraprofessionals, whose salaries are often considerably lower
than those of teachers.

350 Education at a Glance 2018: OECD Indicators   © OECD 2018

Under embargo until 11/09/2018 at 11.00am CEST
Other findings

• In almost all countries with available data, the student-teacher ratio decreases or stays the same
between the primary and lower secondary levels, despite a general increase in class size between
these levels.

• On average across OECD countries, the student-teacher ratio in lower secondary education is
slightly lower in private institutions than in public institutions. This is most striking in Mexico,
where at the secondary level there are almost twice as many students per teacher in public
institutions as in private institutions.

• Class size in primary education varies significantly across countries, ranging from 15 students

INDICATOR D2

per class in Costa Rica to 31 students per class in Chile.

Education at a Glance 2018: OECD Indicators   © OECD 2018

351

chapter D Teachers, the Learning Environment and the Organisation of Schools
Under embargo until 11/09/2018 at 11.00am CEST

Analysis
Class size

Average class size in primary and lower secondary education
At the primary level, the average class in OECD countries has 21 pupils. There are fewer than 27 pupils per class in
nearly all of the countries with available data, with the exception of Chile, Israel and Japan (Table D2.1).

D2

At the lower secondary level, the average class in OECD countries has 23 students. Among all countries with
available data on lower secondary education, that number varies from fewer than 20 students per class in Estonia,
Latvia, Lithuania, the Slovak Republic and the Russian Federation to more than 30 students per class in Costa Rica
and Japan (Table D2.1).
The number of students per class tends to increase between primary and lower secondary education. In Costa Rica, this
increase is almost 18 students. On the other hand, in the United Kingdom and, to a lesser extent, Australia, Estonia,
Hungary and Latvia, student numbers per class decrease between these two levels of education (Table D2.1).
The indicator on class size is limited to primary and lower secondary education, because class size is difficult to
define and compare at higher levels, where students often split into several different classes, depending on the
subject area.

Class size in public and private institutions
Class size is one factor that parents may consider when deciding on a school for their children. Hence, the difference
in average class size between public and private schools (and between different types of private institutions) could
influence enrolment.
In most OECD countries, average class size does not differ between public and private institutions by more than two
students per class in both primary and lower secondary education. However, in some countries (including Brazil,
Colombia, the Czech Republic, Latvia, Poland and the Russian Federation), the average class in public primary
schools is larger than the average class in private schools by more than five students (Table D2.1). But with the
exception of Brazil and Colombia, the private sector is relatively small in all of these countries, representing at most
5% of students at the primary level (see Education at a Glance Database). In contrast, in Chile, Greece, Korea, and
Spain, the average class in private institutions is larger than in public institutions by four students.
At the lower secondary level, where private institutions are more prevalent, the comparison of class size between
public and private institutions shows a more mixed picture. The average class in lower secondary private institutions is
larger than in public institutions in 10 countries, smaller in 16 countries and the same in 5 countries. The differences,
however, tend to be smaller than in primary education.

Trends in average class size
On average across OECD countries, class size decreased between 2005 and 2016 at both primary and lower
secondary levels (Table D2.1). However, while 19 out of 26 countries with available data at the lower secondary level
experienced a decrease in average class size, this was the case for only 12 out of the 26 countries at the primary level.
The most significant decrease occurred at the lower secondary level, where the average class size fell by 7% over the
period. These averages mask considerably larger changes in individual countries. In Estonia and Korea, for example,
the average class size in lower secondary education has decreased by 20% over the past decade. Also in Korea, classes
at the primary level are, on average, 29% smaller than in 2005 – the largest decrease among OECD countries in the
past decade. Other countries, however, saw an increase in average class sizes in primary schools: by 14% in Portugal,
17% in Mexico, and 26% in the Russian Federation. At the lower secondary level, average class size has increased by
9% in Denmark, the largest increase among OECD countries.
Student-teacher ratios
The ratio of students to teaching staff compares the number of students (full-time equivalent) to the number of
teachers (full-time equivalent) at a given level of education and in similar types of institutions. However, this ratio
does not take into account the amount of instruction time for students compared to the length of a teacher’s working
day, or how much time teachers spend teaching. Therefore, it cannot be interpreted in terms of class size (Box D2.1).
At the primary level there are 15 students for every teacher on average across OECD countries. The student-teacher
ratio ranges from 10 to 1 in Lithuania and Norway to more than 25 to 1 in Mexico, India and South Africa (Table D2.2).

352 Education at a Glance 2018: OECD Indicators   © OECD 2018

What is the student-teacher ratio and how big are classes? – INDICATOR D2

chapter D

Under embargo until 11/09/2018 at 11.00am CEST
Student-teacher ratios vary even more at the lower secondary level, from fewer than 10 students per teacher
in Austria, Belgium, Finland, Latvia, Lithuania, Norway and Slovenia to more than 25 students per teacher in
Colombia, India and Mexico. The average across OECD countries is about 13 students per teacher at the secondary
level (Table D2.2).
On average, there are fewer students per teacher at the secondary level (13) than at the primary level (15).This
reduction in the student-teacher ratio from primary to secondary level may result from differences in annual
instruction time (as instruction hours tend to increase with the education level, so does the number of teachers) or
from differences in teaching hours (the teaching time decreases with the level of education as teacher specialisation
increases).
At the upper secondary level, the difference between general and vocational programmes in student-teacher
ratios varies across countries. On average, the ratio of students to teaching staff in upper secondary vocational
programmes and that in upper secondary general programmes are almost equal (13 to 1 in general programmes
and 14 to 1 in vocational programmes) (Figure D2.2). While the difference between the two is negligible in a few
countries, there are in fact as many countries where the ratio is greater in vocational programmes as countries
where it is lower. In Latvia, vocational programmes (16 to 1) have twice as many students per teacher as general
programmes (8 to 1). This may be due to the fact that in some countries, vocational programmes are significantly
work-based, thus vocational students spend considerable time outside the school. As a result, school need fewer
teachers, which may translate into higher student-teacher ratios (OECD, 2017[4]). In other countries such as
Brazil, which has the largest difference between programmes of all countries with available data, the difference
is inversed: there are 13 students per teacher in vocational programmes and 26 students per teacher in general
programmes. Students in vocational education typically need greater instructor attention, especially as they have
access to more sophisticated equipment. In fact, vocational students require more careful supervision as skill
specificity rises. This may have important implications in terms of the cost of vocational instruction, as advanced
vocational training requires both specialised machinery and a greater level of human resources (Klein, 2001[5]).
At the tertiary level, the student-teacher ratio ranges from 8 to 1 in Luxembourg and 10 to 1 in Norway and Sweden
to over 20 to 1 in Belgium, Colombia, Ireland, India, Indonesia and Turkey. In Colombia, the student-teacher ratio
in tertiary education reaches 31 to 1.

Figure D2.2. Ratio of students to teaching staff in upper secondary education,
by type of programmes (2016)
Vocational programmes

Number of students

General programmes

30
25
20
15
10

Lithuania

Spain

France2

Poland

Belgium

Italy

Luxembourg

Norway

Austria

Costa Rica

Czech Republic

OECD average

Korea

EU22 average

Hungary

Brazil

Slovak Republic

Slovenia

Turkey

Sweden

Germany

Latvia

New Zealand

Estonia

Finland

Netherlands1

United Kingdom

0

Chile

5

1. Public institutions only.
2. Public and government-dependent private institutions only.
Countries are ranked in descending order of the ratio of students to teaching staff in upper secondary vocational programmes.
Source: OECD / UIS / Eurostat (2018), Table D2.2. See Source for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933805325

Education at a Glance 2018: OECD Indicators   © OECD 2018

353

D2

chapter D Teachers, the Learning Environment and the Organisation of Schools
Under embargo until 11/09/2018 at 11.00am CEST

Student-teacher ratios in public and private institutions
Differences between public and private institutions in student-teacher ratios are similar to those observed for class
size. On average across countries for which data are available, the ratios of students to teaching staff are slightly
higher in public institutions than in private institutions at the lower and upper secondary level (Table D2.3).

At the upper secondary level, the student-teacher ratio is greater in public institutions than in private institutions
in 15 countries, smaller in public institutions in 14 countries, and similar for both sectors in 5 countries. Turkey
is the country with the highest difference in student-teacher ratios at this level, with 15 students per teacher in
public institutions and only 6 students per teacher in private institutions (Table D2.3). This mixed pattern in upper
secondary education may, in part, reflect differences in the types of programmes offered in public and private
institutions. For instance, in Norway, few private schools offer vocational programmes, in which the studentteacher ratio is typically lower than the ratio in general programmes (Education at a Glance Database).
Although tertiary education may involve more self-learning than primary and secondary education, the number of
students per teacher remains an important concern. The student-teacher ratio is considered to be a proxy of quality
in higher education (McDonald, 2013[6]). Students are more likely to receive more support and attention when the
student-teacher ratio is low. On average across OECD countries, there are 15 students per teacher at the tertiary level,
with very little difference between public and private institutions. In only a few OECD countries, such as Austria and
Italy, there are over five more students per teacher in public institutions than in private institutions. In these countries,
however, less than 20% of tertiary students are enrolled in private institutions (Education at a Glance Database).

Figure D2.3. Ratio of students to teaching staff in tertiary education,
by type of institution (2016)
Public institutions

Number of students

Private institutions

45
40
35
30
25
20
15
10

Brazil

Luxembourg4

Sweden

Norway

Germany

Russian Federation3

Spain

Slovak Republic

Poland

Finland

Hungary

Estonia

Switzerland

Netherlands

Portugal2

EU22 average

OECD average

United States2

Slovenia

Lithuania

Latvia

Austria

France2

New Zealand

Mexico

Czech Republic

Belgium

South Africa1

Saudi Arabia

Indonesia

Italy

Ireland

Turkey

0

India

5
Colombia

D2

At the lower secondary level, large differences between public and private institutions are found in Colombia,
Mexico and Turkey, where there are at least eight more students per teacher in public institutions than in private
institutions. In all these countries, however, less than 20% of lower secondary students are enrolled in private
institutions (Education at a Glance Database). In contrast, the student-teacher ratio is lower in public institutions
than in private institutions in some countries. This difference is most pronounced in Luxembourg, where although
over 80% of students are enrolled in public institutions (Education at a Glance Database), the student-teacher ratio
is 9 to 1 in public institutions, compared to 23 to 1 in private institutions (Table D2.3).

1. Year of reference is 2015.
2. Tertiary includes post-secondary non-tertiary education.
3. Tertiary includes part of vocational upper secondary education.
4. Short-cycle tertiary is not included.
Countries are ranked in descending order of the ratio of students to teaching staff in tertiary public institutions.
Source: OECD / UIS / Eurostat (2018), Education at a Glance Database, http://stats.oecd.org/. See Source for more information and Annex 3 for notes
(http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933805344

354 Education at a Glance 2018: OECD Indicators   © OECD 2018

What is the student-teacher ratio and how big are classes? – INDICATOR D2

chapter D

Under embargo until 11/09/2018 at 11.00am CEST
In contrast, the difference between public and private institutions in student-teacher ratios reaches 10 to 1 in Colombia
and 23 to 1 in India, where over 50% of tertiary students are enrolled in private institutions. The largest difference
across public and private institutions in terms of student-teacher ratio is in Brazil. Interestingly, the ratio is much
higher in private institutions, which enrol 73% of tertiary students, than in public institutions, which are the most
selective ones (Education at a Glance Database). In Brazil, students could either face a performance barrier in free but
highly-selective public institutions, or a financial barrier in private institutions, which could limit their opportunities
and raise significant equity concerns.

D2
Box D2.1. What is the relationship between class size and the student-teacher ratio?
Class size, as presented in Table D2.1, is defined as the number of students who are following a common course
of study, based on the highest number of common courses (usually compulsory studies), and excluding teaching
in subgroups. The calculation is done by dividing the number of students by the number of classes. The studentteacher ratio, as presented in Tables D2.2 and D2.3, is calculated by dividing the number of full-time equivalent
students by the number of full-time equivalent teachers at a given level of education and type of institution.
The two indicators, therefore, measure very different characteristics of the educational system. Studentteacher ratios provide information on the level of teaching resources available in a country, whereas class size
measures the average number of students that are grouped together in classrooms.
Given the difference between student-teacher ratio and average class size, it is possible for countries with similar
student-teacher ratios to have different class sizes. For example, at the primary level, Israel and the United States
have similar ratios of students to teaching staff (15 students per teacher) (Table D2.2), but the average class size
differs substantially (21 students per class in the United States and 27 in Israel). This can be explained by the fact
that teaching time in the United States is considerably higher than in Israel, meaning that American teachers can
teach more classes during the day and thus group students into smaller classes (see Indicator C7).

Definitions
The educational personnel include two categories:

• Teachers’ aides and teaching/research assistants include non-professional personnel or students who support
teachers in providing instruction to students.

• Teaching staff refers to professional personnel directly involved in teaching to students. The classification
includes classroom teachers, special-education teachers and other teachers who work with a whole class of
students in a classroom, in small groups in a resource room, or in one-to-one teaching situations inside or outside
a regular class. At the tertiary level, academic staff include personnel whose primary assignment is instruction or
research. Teaching staff also include department chairpersons whose duties include some teaching, but exclude
non-professional personnel who support teachers in providing instruction to students, such as teachers’ aides
and other paraprofessional personnel.

Methodology
Class size is calculated by dividing the number of students enrolled by the number of classes. In order to ensure
comparability among countries, special-needs programmes are excluded. Data include only regular programmes at
primary and lower secondary levels of education, and exclude teaching in subgroups outside the regular classroom
setting.
The ratio of students to teaching staff is obtained by dividing the number of full-time equivalent students at a given
level of education by the number of full-time equivalent teachers at that level and in similar types of institutions.
For more information, please see the OECD Handbook for Internationally Comparative Education Statistics 2018:
Concepts, Standards, Definitions and Classifications (OECD, 2018[7]) and Annex 3 for country-specific notes (http://
dx.doi.org/10.1787/eag-2018-36-en).
Lithuania was not an OECD member at the time of preparation of this publication. Accordingly, Lithuania does not
appear in the list of OECD members and is not included in the zone aggregates.
Education at a Glance 2018: OECD Indicators   © OECD 2018

355

chapter D Teachers, the Learning Environment and the Organisation of Schools
Under embargo until 11/09/2018 at 11.00am CEST

Source
Data refer to the academic year 2015/16 and are based on the UNESCO-UIS/OECD/EUROSTAT data collection on
education statistics administered by the OECD in 2017 (for details, see Annex 3 at http://dx.doi.org/10.1787/eag2018-36-en).

D2

Note regarding data from Israel
The statistical data for Israel are supplied by and are under the responsibility of the relevant Israeli authorities. The use
of such data by the OECD is without prejudice to the status of the Golan Heights, East Jerusalem and Israeli settlements
in the West Bank under the terms of international law.

References
Fredriksson, P., B. Öckert and H. Oosterbeek (2012), “Long-term effects of class size”, Working Paper Series, https://ideas.
repec.org/p/hhs/ifauwp/2012_005.html (accessed on 19 April 2018).

[2]

Klein, S. (2001), Financing Vocational Education: A State Policymaker’s Guide, RTI, www.rti.org/sites/default/files/resources/
financing_vocational_education.pdf.

[5]

McDonald, G. (2013), “Does size matter? The impact of student-staff ratios”, Journal of Higher Education Policy and
Management , Vol. 35/6, pp. 652-667, http://dx.doi.org/10.1080/1360080X.2013.844668.

[6]

OECD (2018), OECD Handbook for Internationally Comparative Education Statistics 2018: Concepts, Standards, Definitions
and Classifications, OECD Publishing, Paris, https://doi.org/10.1787/9789264304444-en.

[7]

OECD (2017), Education at a Glance 2017: OECD Indicators, OECD Publishing, Paris, http://dx.doi.org/10.1787/eag-2017-en.

[4]

OECD (2016), PISA 2015 Results (Volume II): Policies and Practices for Successful Schools, OECD Publishing, Paris, http://
dx.doi.org/10.1787/9789264267510-en.

[3]

Piketty, T. and M. Valdenaire (2006), “L’impact de la taille des classes sur la réussite scolaire dans les écoles, collèges et
lycées français”, Les Dossiers collection thème Enseignement scolaire, www.education.gouv.fr/cid3865/l-impact-de-la-tailledes-classes-sur-la-reussite-scolaire-dans-les-ecoles-colleges-et-lycees-francais.html (accessed on 19 April 2018).

[1]

Indicator A1 Tables
1 2 https://doi.org/10.1787/888933805230

Table D2.1 Average class size by type of institution (2016) and index of change (2005, 2016)
Table D2.2 Ratio of students to teaching staff in educational institutions, by level of education (2016)
Table D2.3 Ratio of students to teaching staff, by type of institution (2016)
Cut-off date for the data: 18 July 2018. Any updates on data can be found on line at http://dx.doi.org/10.1787/eag-data-en. More breakdowns can
also be found at http://stats.oecd.org/, Education at a Glance Database.

356 Education at a Glance 2018: OECD Indicators   © OECD 2018

What is the student-teacher ratio and how big are classes? – INDICATOR D2

chapter D

Under embargo until 11/09/2018 at 11.00am CEST

Public institutions

Total private
institutions

Total
public and private
institutions

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

(13)

(14)

(15)

(16)

23
18
19
m
28
21
22
19
20
23
21
17
21
19
25
27
19
27
23
16
m
24
23d
m
m
19
21
18
20
21
19
19
21
27
21

25
19
20
m
32
15
20
15
18
24
21
21
21
14
m
25
19
28
27
10
m
20
m
m
m
12
21
17
20
24
18
m
18
a
18

25
x(2)
20
m
33
15
20
a
18
x(2)
x(2)
a
21
14
a
25
a
a
a
a
m
a
m
m
m
11
24
17
20
25
18
m
a
27
a

a
x(2)
a
m
25
a
a
15
a
x(2)
x(2)
21
17
a
m
a
19
28
27
10
m
20
m
m
m
13
20
a
a
21
a
m
18
12
18

24
18
20
m
31
21
21
19
20
23
21
17
21
19
m
27
19
27
23
16
m
23
m
m
m
19
21
18
20
22
19
m
21
26
21

21
21
m
m
29
22
22
19
20
25
24
20
21
20
m
29
21
32
29
15
m
29
m
m
m
22
22
19
20
25
21
19
24
21
27

24
21
m
m
31
19
21
15
20
26
24
22
21
13
m
24
21
33
28
12
m
24
m
m
m
17
24
18
22
26
22
m
17
a
20

24
x(7)
m
m
33
19
21
a
20
26
x(7)
a
22
13
a
24
a
a
28
a
m
a
m
m
m
23
25
18
22
27
22
m
a
20
a

a
x(7)
a
m
25
a
a
15
a
12
x(7)
22
17
a
m
a
21
33
a
12
m
24
m
m
m
15
22
a
a
22
a
m
17
11
20

22
21
m
m
30
22
21
18
20
25
24
20
21
20
m
28
21
32
28
15
m
28
m
m
m
22
22
19
20
26
21
m
24
20
26

98
91
m
m
85
103
109
96
m
m
94
88
106
103
102
103
105
96
71
m
m
120
106d
m
m
95
116
91
108
107
m
m
77
105
102

m
m
m
m
101
m
m
m
m
m
90
m
108
m
m
m
m
84
85
m
m
89
m
m
m
101
96
m
m
101
m
m
m
m
99

99
91
m
m
95
102
110
96
m
m
94
88
106
102
m
100
105
96
71
m
m
117
m
m
m
93
114
91
108
105
m
m
78
107
102

88
87
m
m
82
93
109
81
m
106
98
83
96
102
m
92
101
96
79
m
m
96
m
m
m
92
98
84
97
106
m
m
m
85
101

m
m
m
m
96
m
m
m
m
105
92
m
97
m
m
m
m
92
80
m
m
91
m
m
m
101
101
m
m
99
m
m
m
m
95

89
87
m
m
90
93
109
80
m
106
97
83
96
102
m
89
101
96
80
m
m
95
m
m
m
91
98
83
97
104
m
m
m
89
100

OECD average
Average for countries
with available data for
both reference years
EU22 average

21

20

m

m

21

23

22

m

m

23

m

m

m

m

m

m

21

20

m

m

21

23

22

m

m

23

99

95

99

93

95

93

20

19

m

m

20

21

21

m

m

21

m

m

m

m

m

m

m
24
m
25
15
m
m
16

m
18
m
19
16
m
m
14

m
a
m
a
x(2)
m
m
a

m
18
m
19
x(2)
m
m
14

m
23
m
23
15
m
m
16

m
28
m
31
35
m
m
18

m
24
m
24
21
m
m
19

m
a
m
a
x(7)
m
m
a

m
24
m
24
x(7)
m
m
19

m
27
m
29
33
m
m
18

m
94
m
m
m
m
m
110

m
m
m
m
m
m
m
143

m
92
m
m
m
m
m
109

m
84
m
m
m
m
m
82

m
m
m
m
m
m
m
121

m
85
m
m
m
m
m
82

20

13

a

13

20

19

12

a

12

19

126

m

126

103

m

103

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

Argentina
Brazil
China
Colombia
Costa Rica
India
Indonesia
Lithuania
Russian Federation
Saudi Arabia
South Africa
G20 average

m

Governmentdependent private
institutions
Independent
private
institutions
Total
public and private
institutions

(1)

Australia
Austria
French Comm. (Belgium)
Canada
Chile
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Luxembourg
Mexico
Netherlands1
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United Kingdom
United States

Governmentdependent private
institutions
Independent
private
institutions
Total
public and private
institutions

Total
public and private
institutions

Lower secondary

Total private
institutions

Primary
Public institutions

Private institutions

Total private
institutions

Private institutions

Index of change between 2005 and 2016
(2005 = 100)

Public institutions

Lower secondary

Total private
institutions

Primary
Public institutions
Partners

OECD

Table D2.1. Average class size, by type of institution (2016) and index of change (2005, 2016)
By level of education, calculations based on number of students and number of classes

1. Primary education includes pre-primary programmes.
Source: OECD / UIS / Eurostat (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933805249

Education at a Glance 2018: OECD Indicators   © OECD 2018

357

D2

chapter D Teachers, the Learning Environment and the Organisation of Schools
Under embargo until 11/09/2018 at 11.00am CEST
Table D2.2. Ratio of students to teaching staff in educational institutions (2016)
By level of education, calculations based on full-time equivalents
Upper secondary

Partners

D2

OECD

Primary

PostGeneral
Vocational
All
secondary Short-cycle
Lower
All
secondary programmes programmes programmes secondary non-tertiary tertiary

Tertiary
Bachelor’s,
master’s,
doctoral or
equivalent
level

All tertiary

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

Australia
Austria
Belgium
Canada1
Chile
Czech Republic
Denmark
Estonia
Finland
France2
Germany
Greece
Hungary
Iceland
Ireland3
Israel3
Italy
Japan
Korea
Latvia
Luxembourg
Mexico
Netherlands4
New Zealand
Norway5
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland4
Turkey
United Kingdom
United States

15
12
13
17d
20
19
m
13
13
19
15
m
11
11
16
15
11
17
16
11
11
27
17
17
10
11
13
17
14
14
13
16
18
17
15

x(3)
9
9
x(1)
21
12
m
10
9
15
13
m
10
10
m
12
11
13
15
8
11
34
16
16
9
10
10
12
6
12
12
12
15
15
15

12d
10
11
x(5)
22
11
12
14
15
13
13
m
11
m
14
x(5)
12
x(5)
14
8
7d
x(5)
16
12
10
12
x(5)
14
15
12
x(5)
11
11
14
x(5)

m
10
9
x(5)
22
11
m
18
19
9
14
m
13
m
a
x(5)
9
x(5)
12
16
10d
x(5)
19
17
10
9
x(5)
13
14
9
x(5)
m
14
22
x(5)

12
10
10
12
22
11
m
15d
17
11
13
m
11
m
14
11
10
12d
14
10
9d
20
18
13
10
10
10d
14
14
11
14
m
13
16
15

m
9
10
12
22
11
m
13
13
13
13
m
11
m
14
11
11
13d
14
9
10
27
17
14
10
10
10d
13
9
11
13
12
14
16
15

m
12
16
m
a
18
a
x(4)
18
m
13
16
14
m
m
m
m
x(5, 10)
a
22
m
a
a
21
12
14
x(5, 10)
14
a
a
10
m
a
a
x(10)

m
8
x(10)
m
m
11
m
a
a
10
12
a
13
m
m
m
a
m
m
19
x(3, 4)
21
15
19
11
9
x(10)
8
18
10
9
a
55
x(10)
x(10)

15
17
x(10)
m
m
19
m
14
15
m
12
m
14
m
m
m
20
m
m
20
8
17
15
18
10
15
x(10)
13
15
13
10
15
19
x(10)
x(10)

m
14
21
m
m
19
m
14
15
m
12
m
14
m
21
m
20
m
m
18
8
17
15
18
10
15
14d
12
15
12
10
15
23
16
14d

OECD average
EU22 average

15

13

13

14

13

13

m

m

m

15

14

11

12

13

12

12

m

m

m

15

Argentina6
Brazil
China
Colombia
Costa Rica
India
Indonesia
Lithuania
Russian Federation
Saudi Arabia
South Africa6, 7

m
24
17
24
12
35
14
10
21
12
30

m
25
12
26
13
27
14
7
11d
m
x(5)

m
26
x(5)
x(5)
14
x(5)
x(5)
7
x(2)
m
x(5)

m
13
x(5)
x(5)
10
x(5)
x(5)
9
x(8)
m
x(5)

m
24
15
26
13
30
14
8
x(2, 8)
m
17d

m
25
13
26
13
28
14
7
11
m
28

a
26
m
31
a
8
a
15
41
a
m

m
10
m
32
m
a
15
a
11
x(10)
m

m
20
m
30
m
24
24
16
11
x(10)
m

m
20
m
31
m
24
22
16
11
20
m

G20 average

19

16

m

m

15

16

22

m

18

18

1. Primary education includes pre-primary programmes.
2. Public and government-dependent private institutions only.
3. For Ireland, public institutions only for all levels. For Israel, public institutions only for upper secondary education and all secondary.
4. Public institutions only.
5. Public and government-dependent institutions only for primary, lower secondary and tertiary institutions.
6. Year of reference 2015.
7. Upper secondary education includes lower secondary.
Source: OECD/UIS/Eurostat (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933805268

358 Education at a Glance 2018: OECD Indicators   © OECD 2018

chapter D

What is the student-teacher ratio and how big are classes? – INDICATOR D2

Under embargo until 11/09/2018 at 11.00am CEST
Table D2.3. Ratio of students to teaching staff, by type of institution (2016)
By level of education,calculations based on full-time equivalents
Upper secondary

All secondary programmes

Independent
private
institutions

Public institutions

Total private
institutions

Governmentdependent
private
institutions

Independent
private
institutions

Public institutions

Total private
institutions

Governmentdependent
private
institutions

Independent
private
institutions

Private institutions

Governmentdependent
private
institutions

Private institutions

Total private
institutions

Private institutions

Public institutions
Partners

OECD

Lower secondary

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

Australia1
Austria
Belgium
Canada
Chile
Czech Republic
Denmark
Estonia2
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan3
Korea
Latvia
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal3
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United Kingdom
United States

x(5)
9
9
m
17
12
m
10
9
14
13
m
10
10
x(5)
12
11
14
14
8
9
38
16
17
9
10
9
12
6
11
12
12
16
16
16

x(6)
10
9
m
25
11
m
8
9
m
13
m
11
3
m
8
11
12
16
5
23
18
m
13
m
9
15
11
4
15
17
m
7
14
11

x(7)
x(2)
9
m
26
11
m
a
9
17
x(2)
a
12
3
a
8
a
a
16
a
x(2)
a
a
0
8
11
14
11
4
15
17
m
a
16
a

a
x(2)
m
m
20
a
a
8
a
m
x(2)
m
9
a
m
0
11
12
a
5
x(2)
18
m
13
m
8
15
a
a
14
a
m
7
8
11

13d
10
10
12
20
11
m
15
17
11
13
m
11
m
14d
11
11
11d
13
10
9
22
18
13
10
10
9d
14
14
10
14
m
15
16
16

12d
10
10
13
24
12
m
12
17
m
12
m
12
m
m
m
7
14d
15
8
8
15
m
10
11
11
10d
12
16
14
14
m
6
17
11

12d
x(6)
10
x(6)
26
12
m
a
17
13
x(6)
a
11
m
a
m
a
a
15
a
11
a
a
10
11
12
12d
12
26
15
14
m
a
19
a

m
x(6)
m
x(6)
16
a
a
12
a
m
x(6)
m
12
m
m
a
7
14d
a
8
6
15
m
10
a
11
10d
a
12
13
a
m
6
8
11

m
9
10
12
19
11
m
13
13
13
13
m
11
m
14
11
11
12d
14
9
9
30
17
15
10
10
9d
13
9
10
13
m
16
16
16

m
10
9
13
24
12
m
10
16
m
12
m
12
m
m
m
8
13d
15
7
11
16
m
11
m
10
12d
12
13
15
15
m
6
16
11

m
x(10)
9
x(10)
26
12
m
a
16
15
x(10)
a
12
m
a
m
a
a
15
a
23
a
a
10
10
11
13d
12
15
15
15
m
a
18
a

m
x(10)
m
x(10)
17
a
a
10
a
m
x(10)
m
12
m
m
0
8
13d
a
7
12
16
m
12
m
10
11d
a
12
14
a
m
6
8
11

OECD average
EU22 average

13
11

12
11

m
m

m
m

13
12

12
12

m
m

m
m

13
12

12
12

m
m

m
m

Argentina
Brazil
China
Colombia
Costa Rica
India
Indonesia
Lithuania
Russian Federation
Saudi Arabia
South Africa

m
26
12
28
13
27
15

m
20
17
20
9
27
13

m
a
x(2)
a
x(2)
x(2)
x(2)

m
20
x(2)
20
x(2)
x(2)
x(2)

m
25
15
27
13
28
15

m
19
18
22
9
32
14

m
a
x(6)
a
x(6)
x(6)
x(6)

m
19
x(6)
22
x(6)
x(6)
x(6)

m
26
13
28
13
27
15

m
20
17
21
9
30
13

m
a
x(10)
a
x(10)
x(10)
x(10)

m
20
x(10)
21
x(10)
x(10)
x(10)

G20 average

7

9

a

9

8

5

a

5

7

8

a

8

11d

5d

a

5d

x(1)

x(2)

a

x(4)

11

5

a

5

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

17

14

m

m

15

14

m

m

16

14

m

m

1. Includes only general programmes in lower and upper secondary education.
2. Upper secondary education includes lower secondary and post-secondary non-tertiary vocational programmes.
3. Upper secondary education includes programmes from post-secondary non-tertiary education.
Source: OECD/UIS/Eurostat (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933805287

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HOW MUCH ARE TEACHERS AND SCHOOL HEADS PAID?
• Statutory and actual salaries of school heads are higher than those of teachers at pre-primary,
primary and general secondary levels of education. On average across OECD countries and
economies, actual salaries of school heads are more than 35% higher than those of teachers across
all levels of education.

INDICATOR D3

• Teachers’ actual salaries at pre-primary, primary and general secondary levels of education are 81%
to 96% of earnings of tertiary-educated workers on average across OECD countries.

• On average across OECD countries and economies, school heads’ salaries are at least 20% higher
than earnings of tertiary-educated workers at all levels of education.

Figure D3.1. Lower secondary teachers’ salaries relative to earnings
for tertiary-educated workers (2017)
Actual salaries (annual average salaries including bonuses and allowances) of lower secondary teachers
teaching general programmes in public institutions

Czech Republic

Slovak Republic

Italy

United States

Norway

Hungary

Poland

Turkey

Chile

French Comm. (Belgium)2

Denmark

Scotland (UK)1

Flemish Comm. (Belgium)2

France

New Zealand

Sweden

Austria

Slovenia

England (UK)1

Estonia

OECD average

Netherlands

EU22 average

Israel

Australia

Latvia

Lithuania

Greece

Germany

Portugal

Luxembourg

2.2
2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0

Finland

Teachers’ actual salaries relative to earnings for tertiary-educated workers
Teachers’ actual salaries relative to earnings for similarly educated workers (weighted averages)

Ratio

1. Data on earnings for full-time, full-year workers with tertiary education refer to the United Kingdom.
2. Data on earnings for full-time, full-year workers with tertiary education refer to Belgium.
Countries and economies are ranked in descending order of the ratio of teachers’ salaries to earnings for full-time, full-year tertiary-educated
workers aged 25-64.
Source: OECD (2018), Table D3.2a. See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/
eag-2018-36-en).
1 2 https://doi.org/10.1787/888933805458

Context
Salaries of school staff, and in particular teachers and school heads, represent the largest single
cost in formal education. Teachers’ salaries have also a direct impact on the attractiveness of the
teaching profession. They influence decisions to enrol in teacher education, to become a teacher after
graduation, to return to the teaching profession after a career interruption and/or to remain a teacher
(in general, the higher the salaries, the fewer the people who choose to leave the profession) (OECD,
2005[1]). The level of salaries can also have an impact on the decision to become school heads.
Burgeoning national debt, spurred by governments’ responses to the financial crisis of late 2008,
has put pressure on policy makers to reduce government expenditure, particularly on public payrolls.
Since compensation and working conditions are important for attracting, developing and retaining

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skilled and high-quality teachers and school heads, it is important for policy makers to carefully
consider their salaries and career prospects as they try to ensure both quality teaching and sustainable
education budgets (see Indicators C6 and C7).
However, statutory salaries are just one component of teachers’ and school heads’ total compensation.
Other benefits, such as regional allowances for teaching in remote areas, family allowances, reduced
rates on public transport and tax allowances on the purchase of instructional materials, may also form
part of teachers’ total remuneration. In addition, there are large differences in taxation and socialbenefits systems across OECD countries. This, as well as potential comparability issues related to data
collected (see Box D3.1 in (OECD, 2017[2]) and Annex 3), should be borne in mind when analysing
teachers’ salaries and comparing them across countries.

INDICATOR D3

Other findings

• In most OECD countries, the salaries of teachers and school heads increase with the level of
education they teach.

• In at least three-quarters of countries and economies with available data, the minimum qualifications
to enter the teaching profession are also the most prevalent qualifications of teachers.

• Statutory salaries of teachers with maximum qualifications at the top of their salary scales are,
on average, between 77% and 81% higher than those of teachers with minimum salaries and
minimum qualifications at the start of their career.

• Between 2005 and 2017, on average across OECD countries and economies with available data,
statutory salaries of teachers with 15 years of experience and most prevalent qualifications
increased by 8% at primary level, 7% at lower secondary level (general programmes) and 5% at
upper secondary level (general programmes).

• While statutory salaries of upper secondary teachers with 15 years of experience and minimum
qualifications have now reached pre-crisis levels, statutory salaries of primary and lower secondary
teachers have now exceeded pre-crisis levels.

• School heads are less likely than teachers to receive additional compensation for performing
responsibilities over and above their regular tasks. School heads and teachers working in
a disadvantaged or remote area are rewarded with additional compensation in half of the
OECD countries and economies with available data.

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Analysis
Statutory salaries of teachers
Statutory salaries of teachers can vary according to a number of factors, including the level of education taught, the
qualification level of teachers, and the level of experience or the stage of the career of teachers.

By level of education

D3

Teachers’ salaries vary widely across countries. The salaries of lower secondary school teachers with 15 years
of experience and most prevalent qualifications (proxy for mid-career salaries of teachers) range from less than
USD 25 000 in the Czech Republic, Hungary, Lithuania and the Slovak Republic to more than USD 60 000 in Canada,
Germany, Ireland, the Netherlands and the United States, and they exceed USD 100 000 in Luxembourg (Table D3.1a).
In most countries with available information, teachers’ salaries increase with the level of education they teach. In the
Flemish and French Communities of Belgium, the Netherlands and Norway, upper secondary teachers with 15 years
of experience and most prevalent qualifications earn between 25% and 30% more than pre-primary teachers with
the same experience, while in Lithuania and the Slovak Republic they earn 37% to 42% more, in Finland 50% more,
and in Mexico, 92% more. In Finland and the Slovak Republic, the difference is mainly explained by the gap between
pre-primary and primary teachers’ salaries. In the Flemish and French Communities of Belgium, teachers’ salaries
at upper secondary level are significantly higher than at other levels of education (Table D3.1a).
The increase in salaries between teachers (with 15 years of experience and most prevalent qualifications) at preprimary and upper secondary levels is less than 5% in Chile, Costa Rica, France and Slovenia, and teachers have the
same salary irrespective of the level of education taught in Australia, England (United Kingdom), Greece, Poland,
Portugal, Scotland (United Kingdom) and Turkey (Table D3.1a).
However, in Iceland and Israel the salary of a pre-primary teacher is at least 10% higher than the salary of an upper
secondary teacher. In Iceland, this may result from different collective agreements on teachers’ salaries, depending
of the level of education. In Israel, the difference results from the “New Horizon” reform, begun in 2008 and almost
fully implemented by 2014, which increased salaries for pre-primary, primary and lower secondary teachers. Another
reform, launched in 2012 with implementation ongoing, aims to raise salaries for upper secondary teachers.

By level of qualification
The minimum qualifications required to teach at a given level of education in the public school system refers to the
minimum duration and type of training required (based on official documents) to enter the profession. The “most
prevalent” level of qualifications refers to the level of qualifications and training held by the largest proportion of
teachers. It can be defined either for a level of education or at a specific stage of the teaching career (see Annex 3 for
the description of qualification levels).
Countries may require different minimum levels of qualifications to teach at various levels of education. Austria,
Hungary, Luxembourg, the Netherlands, Poland, Spain, and Switzerland require a higher degree (master’s or
equivalent) to teach at general lower and/or upper secondary level than at primary level. This helps explain the
higher salaries observed at these levels in those countries.
Differences in salaries of teachers between those with minimum and most prevalent qualifications are by no means
the general rule: in countries with a large proportion of teachers with the minimum qualification, they may also
represent the most prevalent qualification. In about three-quarters of countries and economies with available
information (or more, depending on the level of education taught), the minimum qualification to enter the teaching
profession is also the most prevalent qualification at that level (as a consequence, there is no difference in statutory
salaries between teachers with minimum and most prevalent qualifications throughout a teacher’s career).
In the remaining countries, the most prevalent qualification at a level of education is higher than the minimum
qualification required, and this is recognised by the compensation system. Among the 13 countries with available
data, salaries of teachers with the most prevalent qualifications are at least 10% higher than those of teachers with
the minimum qualifications in Canada, the Flemish Community of Belgium (upper secondary level), Norway (upper
secondary level), Poland (pre-primary, primary and lower secondary levels) and the United States (primary, lower
and upper secondary levels), and at some stages of the teaching career only in the French Community of Belgium,
Greece, Hungary, New Zealand and Norway (primary and lower secondary levels). The difference in teachers’
salaries between those with most prevalent and minimum qualifications exceeds 35% in England (United Kingdom)
and 75% in Costa Rica. However, in Costa Rica, salaries of teachers with the most prevalent qualifications are still at

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How much are teachers and school heads paid? – INDICATOR D3

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least 20% lower than the OECD average (at all stages of the teachers’ careers and at all levels of education). Caution
is necessary when interpreting these differences in salaries, as in some countries a very small proportion of teachers
have the minimum qualification required (Tables D3.1b and D3.1c, available on line).
The most prevalent qualifications of teachers may also vary according to the number of years of experience of
teachers. This is the case in a small number of countries (Canada, Hungary, Iceland, Ireland, Israel and Norway),
and the difference can refer to one or several of the four career stages taken into account (starting point, 10 years
of experience, 15 years of experience, and top of the range). This is usually linked to recent reforms related to
compensation system and/or qualification requirements of teachers. In Ireland, for example, the salary arrangements
have changed for teachers who entered the teaching profession from 2012. The salaries related to most prevalent
qualifications for teachers with ten or more years of experience refer to the salary arrangement in place for teachers
appointed prior to 2012 (the difference in salary varies from 8% to 17% according to levels of education and stage
of the career). In Norway, the most prevalent qualification when entering the teaching profession at the primary
and lower secondary level is the minimum qualification, and then differs from the most prevalent qualification of
all teachers at these levels of education (Table D3.1a and Table D3.1b, available on line).

By level of experience
Salary structures usually define the salaries paid to teachers at different points in their careers. Deferred
compensation, which rewards employees for staying in organisations or professions and for meeting established
performance criteria, is also used in teachers’ salary structures. OECD data on teachers’ salaries are limited to
information on statutory salaries at four points of the salary scale: starting salaries, salaries after ten years of
experience, salaries after 15 years of experience and salaries at the top of the scale. Further qualifications also
influence differences in starting and maximum salaries and lead to wage increases in some countries.
In OECD countries, teachers’ salaries rise during the course of their career (for a given qualification level), although
the rate of change differs across countries. With the most prevalent qualifications, the average statutory salaries
for lower secondary school teachers with 10 years of experience are 30% higher than the average starting salaries,
and 38% higher with 15 years of experience. In addition, salaries at the top of the scale (reached after an average of
27 years of experience) are 67% higher, on average, than starting salaries. In Greece, Hungary, Israel, Italy, Korea
and Spain, lower secondary school teachers reach the top of the salary scale only after at least 35 years of service.
By contrast, lower secondary teachers in Australia, New Zealand and Scotland (United Kingdom) reach the highest
step on the salary scale after 6 to 7 years (Table D3.1b and Table D3.3a, available on line).
In addition to pay scales, the number of years required to reach the top of scale is an indication of the speed of
career progression and perspectives. In general, the larger the range between minimum and maximum salaries, the
more years it takes for teachers to achieve maximum status. For example, while on average across OECD countries,
a lower secondary teacher with most prevalent qualifications can expect to reach the top of the salary scale after
27 years, it would take only 6-7 years to reach this level in Australia, New Zealand and Scotland (United Kingdom),
but maximum salary in these countries is only about 33% to 53% higher than starting salaries, compared to 66% on
average across OECD countries. However, this is not true of all countries. For example, while teachers with the most
prevalent qualifications in both the Czech Republic and Israel will reach the top of their scale within approximately
32-36 years, maximum statutory salaries in the Czech Republic are only 31% higher than starting statutory salaries,
compared to 108% higher in Israel (Table D3.3a, available on line).

Statutory salaries per hour of net teaching time
As the number of hours of teaching varies considerably between countries and also between levels of education,
differences in statutory salaries of teachers may also translate into different levels of salary per teaching hour. The
average statutory salary per teaching hour after 15 years of experience and with most prevalent qualifications is
USD 55 for primary teachers, USD 65 for lower secondary teachers and USD 74 for upper secondary teachers in
general education (Table D3.3a, available on line).
Because secondary teachers are required to teach fewer hours than primary teachers, their salaries per teaching
hour are usually higher than those of teachers at lower levels of education, even in countries where statutory salaries
are similar (see Indicator D4). On average across OECD countries, upper secondary teachers’ salaries per teaching
hour exceed those of primary teachers by about 31%. In Scotland (United Kingdom), there is no difference, while in
the Flemish Community of Belgium and Mexico, the salary per teaching hour for an upper secondary teacher is at
least 83% higher than that for a primary teacher. In Costa Rica and Lithuania, the salary per teaching hour is higher
at the primary level (Table D3.3a, available on line).
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However, for countries with similar statutory salaries at primary and secondary levels, these difference in salaries per
teaching hour between primary and secondary teachers may disappear when comparing salaries per hour of working
time, as statutory working time of teachers is usually similar at primary and secondary level (see Indicator D4).

By level of experience and qualification: minimum and maximum teachers’ salaries

At the lower secondary level, the average statutory salary of a teacher with the most prevalent qualification level
with 15 years of experience is 41% higher than that of a starting teacher with minimum qualifications. At the top of
the salary range with maximum qualifications, the average statutory salary is 78% higher than the average starting
salary with the minimum qualification (Figure D3.2).

Figure D3.2. Lower secondary teachers’ statutory salaries at different points
in teachers’ careers (2017)
Annual statutory salaries of teachers in public institutions, in equivalent USD converted using PPPs
Equivalent USD
converted using PPPs

Salary at top of scale/maximum qualifications
Salary after 15 years of experience/most prevalent qualifications
Starting salary/minimum qualifications

160 000
140 000
120 000
100 000
80 000
60 000
40 000
20 000
0

Luxembourg
Germany
Switzerland
Denmark
Spain
Australia
Netherlands
Austria
United States1
Norway
Sweden1, 2
Canada
Flemish Comm. (Belgium)3
Finland
Iceland
French Comm. (Belgium)
Ireland
Scotland (UK)
OECD average
Portugal
EU22 average
France4
Italy
Japan
New Zealand
Korea3
Slovenia
Turkey
Mexico
Chile
England (UK)
Israel
Estonia
Lithuania
Greece
Czech Republic
Hungary
Slovak Republic
Latvia
Brazil
Poland
Costa Rica

D3

Countries that are looking to increase the supply of teachers, especially those with an ageing teacher workforce and/or
a growing school-age population, might consider offering more attractive starting wages and career prospects.
However, to ensure a well-qualified teaching workforce, efforts must be made not only to recruit and select, but also
to retain the most competent and qualified teachers.

1. Actual base salaries.	
2. Salaries at top of scale and minimum qualifications, instead of maximum qualifications.
3. Salaries at top of scale and most prevalent qualifications, instead of maximum qualifications.
4. Includes the average of fixed bonuses for overtime hours.
Countries and economies are ranked in descending order of starting salaries for lower secondary teachers with minimum qualifications.
Source: OECD (2018), Table D3.1a, Tables D3.1c and D3.6, available on line. See Source section for more information and Annex 3 for notes
(http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933805477

In terms of the maximum statutory salary range, from starting salaries (with minimum qualifications) to maximum
salaries (with maximum qualifications), most countries and economies with starting salaries below the OECD average
also have maximum salaries that are below the OECD average. At the lower secondary level, exceptions are Chile,
France, England (United Kingdom) and Japan, where starting salaries are at least 5% lower than the OECD average,
but maximum salaries are 5% to 25% higher. The opposite is true in Denmark, Finland, Iceland and Sweden, where
starting salaries are between 7% and 36% higher than the OECD average, while maximum salaries are at least 5%
lower than the OECD average (12% to 30% lower). This results from relatively flat/compressed salary scales in a
number of these countries (Tables D3.1c and D3.6, available on line).

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Weak financial incentives may make it more difficult to retain teachers as they approach the peak of their earnings.
However, there may be some benefits to compressed pay scales. For example, organisations in which there are
smaller differences in salaries among employees may enjoy more trust, freer flows of information and more
collegiality among co-workers.
By contrast, for lower secondary teachers, maximum salaries (at top of scale, with maximum qualifications) are
at least double the starting salaries (with minimum qualifications) in the French Community of Belgium, Chile,
Costa Rica, France, Hungary, Ireland, Israel, Japan, Mexico, the Netherlands, and more than three times higher in
England (United Kingdom) (Figure D3.2).
The salary premium for maximum qualifications at the top of teachers’ pay scales, compared to most prevalent
qualifications after 15 years of experience also varies across countries. At lower secondary level, the pay gap is less
than 10% in a quarter of OECD countries and economies, while it exceeds 60% in Chile, France, Hungary and Israel
(Table D3.6, available on line and Figure D3.2).
When analysing starting salaries (with minimum qualifications) and maximum salaries (i.e. those at the top of
the salary scale with maximum qualification), it is important to bear in mind that minimum qualifications are
the most prevalent across the majority of countries, though not all as for example in England (United Kingdom)
(see Table X2.5 for the proportion of teachers with minimum or most prevalent qualification levels), that not all
teachers may aim for or reach the top of the salary scale and that few of them may hold the minimum or maximum
qualifications (Box D3.1).
Box D3.1. Salary range of teachers with maximum qualifications (2017)
Teachers are required to have specific minimum qualifications to enter the teaching profession. In some countries,
the most prevalent level of qualifications of teachers is higher than the minimum, and this qualification level is
recognised in the compensation system through different salary levels. Some teachers may hold qualifications
even higher than the most prevalent one and be paid according to a different salary scale.
About one-quarter of countries and economies with available data offer higher statutory salaries to the
teachers with highest qualifications, compared to the most prevalent, as is the case in Canada, England
(United Kingdom), France, the French Community of Belgium, Israel, Lithuania, Norway, the Slovak Republic
and the United States. In most of these countries, this highest qualification level differs from the most prevalent
one at all levels of education. However, in France, it is only available at secondary level (corresponding to salaries
associated with Professeurs agrégés). In Norway, the masters’ degree is the most prevalent qualification (at each
stage of the career) and also the highest qualification (recognised by the compensation system) for upper
secondary teachers. At primary and lower secondary levels, master’s is not the most prevalent qualification,
but is still considered as the highest qualification (recognised by the compensation system). As a consequence,
the associated salaries of primary and lower secondary teachers with the highest qualification are similar to
those of upper secondary teachers with most prevalent qualifications. In the French Community of Belgium,
Israel, Lithuania and the Slovak Republic, the minimum qualification is also the most prevalent one (for all
levels of education). In this case, a higher qualification level recognised by the compensation system is also
available, but held by a smaller proportion of teachers than the minimum qualifications. In Canada, England
(United Kingdom) and Norway, the maximum qualification is a third level, compared to the minimum and most
prevalent level. This maximum qualification is usually a masters’ degree, but it could be a higher qualification.
In Israel and the Slovak Republic, this qualification refers to doctoral level.
The proportion of teachers with these qualifications levels and associated salaries varies largely between
countries. Among countries with available data, more than 10% of teachers are paid according to this range in
England (United Kingdom) and France (upper secondary level).
More detailed information on qualification levels for all participating countries and economies is available in
Annex 3.

Salary trends since 2000
Among the half of the OECD countries with available data on statutory salaries of teachers with most prevalent
qualifications (with 15 years of experience) for 2000 and 2017 (and no break in the time series), teachers’ salaries increased
overall in real terms in most of these countries during this period. Notable exceptions are England (United Kingdom)
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and France, where there was a decline of 4% to 10% respectively, and Greece where salaries decreased by 16%. There
were also slight declines in teachers’ salaries in real terms (less than 3%) in Italy (primary and secondary education).
Salaries increased by more than 20% across primary and secondary education levels in Ireland and Israel. However, in
some countries, the overall increase in teachers’ salaries between 2000 and 2017 includes periods of decrease in salary
(in real terms), particularly from 2010 (Table D3.5a, available on line).

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Over the period 2005 to 2017, where three-quarters of OECD countries and economies have comparable data
for at least one level of education, more than half of these countries showed an increase in real terms in the
statutory salaries of teachers with 15 years of experience and most prevalent qualifications. On average across
OECD countries and economies with available data for 2005 and 2017 reference years, statutory salaries increased
by 8% at primary level, 7% at lower secondary level and 5% at upper secondary level. The increase exceeded
20% in Poland at pre-primary, primary and secondary levels (the result of a 2007 government programme that
aimed to increase teachers’ salaries successively between 2008 and 2013 and to improve the quality of education
by providing financial incentives to attract high-quality teachers) and also in Hungary (pre-primary), Israel,
Luxembourg (pre-primary and primary), Norway (primary and lower secondary) and Sweden (pre-primary,
primary and lower secondary).
In most countries, similar increases in salary occurred for teachers across primary, lower secondary and upper
secondary levels between 2005 and 2017. However, this is not the case in Israel for example where salaries increased
by more than 47% at pre-primary level, by 32% at primary level, by 43% at lower secondary level and by 35% at upper
secondary level. This is largely the result of the gradual implementation of the “New Horizon” reform in primary
and lower secondary schools, which began in 2008 following an agreement between the education authorities and
the Israeli Teachers Union (for primary and lower secondary education). This reform includes higher teacher pay in
exchange for more working hours (see Indicator D4).
By contrast, salaries have decreased slightly since 2005 in few countries, including Denmark, France, Italy, Japan,
Portugal, Scotland (United Kingdom) and Spain, and they decreased by 10% in England (United Kingdom) and by
more than 25% in Greece (as a result of a salary freeze since 2011) (Table D3.5a).
However, these overall changes in teachers’ salaries in OECD countries between 2005 and 2017 mask different
periods of change in teachers’ salaries, as a result of the impact of the economic downturn in 2008. On average
across OECD countries and economies with available data for all years over the period, salaries were either frozen
or cut between 2009 and 2013, before starting to increase again (Figure D3.3). While statutory salaries of primary
and lower secondary teachers with minimum qualifications have now exceeded pre-crisis levels, on average across
OECD countries with data for all reference years, those of upper secondary teachers are still lagging.

Figure D3.3. Change in teachers’ salaries in OECD countries (2005 to 2017)
Average index of change, among OECD countries with data on statutory salaries for all reference years,
for teachers with 15 years of experience and minimum qualifications (2005 = 100, constant prices)
Primary
Lower secondary, general programmes
Upper secondary, general programmes

Index of change
2005 = 100

110
108
106
104
102
100
98
96
94
92
90
2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

Source: OECD (2018), Table D3.5b, available on line. See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/
eag-2018-36-en).
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Statutory salaries of school heads
Responsibilities of school heads may vary between countries and also within countries, depending on the schools
they are responsible for. School heads may exercise educational responsibilities (which may include teaching tasks
but also responsibility for the general functioning of the institution in areas such as timetable, implementation of
the curriculum, decisions about what is to be taught and the materials and methods used). They may also have other
administrative, staff management and financial responsibilities.
Differences in the nature of the work carried out by school heads are reflected in the systems of compensation used
within countries. School heads may be paid according to a specific salary range and may or may not receive a schoolhead allowance on top of the statutory salary. However, they can also be paid in accordance with the salary scale(s)
of teachers and receive an additional school-head allowance. The use of the salary ranges of teachers may reflect
the fact that school heads are initially teachers with additional responsibilities. At the lower secondary level, among
the 32 countries with available information, school heads are paid according to the teacher salary range, with a
school-head allowance in 12 countries and according to a specific salary range in the other countries (in 12 countries
with no specific school-head allowance and in 8 countries with a school-head allowance). The amounts payable to
school heads, through statutory salary and/or school-head allowances, may vary according to criteria related to
the school(s) where the school head is based (for example the size of the school based on the number of students
enrolled, number of teachers supervised, etc.) and to the individual characteristics of school heads (e.g. the duties
he/she has to perform, number of year of experience, etc.) (Table D3.9, available on line).
Considering that the amount of teachers’ statutory salaries varies according to a large number of criteria, the
statutory salary data for school heads focuses on those minimum qualification requirements to become a school
head, and only minimum and maximum values are shown in Table D3.10. At lower secondary level, the minimum
salary is USD 48 316 on average across OECD countries, varying from USD 18 863 in Latvia to USD 109 968 in
Luxembourg, and the maximum salary is USD 81 872 on average across OECD countries, varying from USD 29 617
in Poland to USD 152 083 in Luxembourg. Caution is necessary when interpreting these values, as minimum and
maximum statutory salaries refer to school heads in different types of schools. About half of OECD countries have
similar pay ranges for primary and lower secondary school heads, while upper secondary school heads benefit, on
average, from higher statutory salaries.

Figure D3.4. Minimum and maximum statutory salaries for lower secondary teachers
and school heads (2017)
Based on teachers with most prevalent qualifications at a given level of education and school heads
with minimum qualifications

Poland

Turkey

Slovak Republic

Greece

Lithuania

Slovenia

Hungary

Denmark

Sweden1

Japan

Finland

France

Costa Rica

French Comm. (Belgium)

Italy

Israel

Portugal

Mexico

Spain

Flemish Comm. (Belgium)

EU22 average

Iceland

Austria

Chile

Korea

United States1

Scotland (UK)

Ireland

Australia

Netherlands

Luxembourg

England (UK)

160 000
140 000
120 000
100 000
80 000
60 000
40 000
20 000
0

OECD average

Salary range of teachers (most prevalent qualification)
School head - Minimum
School head - Maximum

Equivalent USD
converted using PPPs

1. Actual base salaries.	
Countries and economies are ranked in descending order of maximum salaries of school heads.
Source: OECD (2018), Table D3.1b available on line and Table D3.10. See Source section for more information and Annex 3 for notes (http://dx.doi.
org/10.1787/eag-2018-36-en).
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On average across OECD countries and economies, the maximum statutory salary of a school head with minimum
qualifications is 73% higher than the minimum statutory salary in primary education, 68% higher than in lower
secondary and 69% higher than in upper secondary. Only in ten countries can school heads at the top of their scale
expect to earn twice the statutory salary they started out with in at least one of these levels of education, and in
Costa Rica, they can expect to earn more than three times their starting salary.

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The minimum statutory salaries for school heads with minimum qualifications are higher than starting salaries of
teachers, except in Costa Rica (and Lithuania where they are equal). The difference between minimum salaries for
school heads (with minimum qualifications) and starting salaries for teachers (with most prevalent qualifications)
increases with levels of education: 24% on average across OECD countries and economies at pre-primary level, 32%
at primary level, 43% at lower secondary level and 44% at upper secondary level. In a few countries, the minimum
statutory salary of school heads is even higher than the maximum salary of teachers. This is the case at lower
secondary level in Australia, Denmark, England (United Kingdom), Finland, Iceland, Israel, Italy, Japan, Mexico,
Scotland (United Kingdom), Sweden and the United States (Figure D3.4).
Similarly, maximum statutory salaries of school heads are higher than those of teachers for all OECD countries and
economies with available data. At the top of their scale, at lower secondary level, the maximum statutory salary of
a school head is 45% higher than the salary of teachers at the top of the range (with most prevalent qualifications),
on average across OECD countries and economies. However, maximum statutory salaries of school heads in Chile,
England (United Kingdom), Iceland and Scotland (United Kingdom) are more than twice the statutory salaries at
top of the range for teachers (Figure D3.4).
Actual average salaries of teachers and school heads
Unlike statutory salaries, teachers’ and school heads’ actual salaries may include work-related payments, such
as annual bonuses, results-related bonuses, extra pay for holidays, sick-leave pay and other additional payments
(see Definitions section). These bonuses and allowances can represent a significant addition to base salaries.
In this case, actual average salaries are influenced by the prevalence of bonuses and allowances in the compensation
system, on top of factors such as the level of experience or the qualifications level of the teaching force (Box D3.3).
Differences between statutory and actual average salaries are also linked to the distribution of teachers by years
of experience and qualifications, as these two factors have an impact on the salary level of teachers.
Across OECD countries and economies, average actual salaries of teachers aged 25-64 are USD 37 440 at pre-primary
level, USD 41 244 at primary level, USD 43 546 at lower secondary level and USD 46 713 at upper secondary level.
Average actual salaries of school heads aged 25-64 vary from USD 57 141 at primary level, USD 64 423 at lower
secondary level and USD 68 932 at upper secondary level (Table D3.4) (see Box D3.2 for variation at subnational level).
Among the 29 OECD countries and economies with available data on both statutory salaries of teachers with
15 years of experience and most prevalent qualifications and actual salaries of 25-64 year-old teachers for at least
one level of education, actual annual salaries are 10% higher than statutory salaries in one-sixth (at pre-primary
level) to one-third (at upper secondary level) of countries.

Box D3.2. Subnational variation of teachers’ salaries at pre-primary, primary and secondary levels
Within the five countries that reported subnational data on statutory salaries of teachers (Belgium, Canada,
Sweden, the United Kingdom and the United States), statutory salaries vary largely between subnational entities,
with different patterns across countries according to level of education and stage of the career of teachers.
In Belgium, statutory salaries are 3% higher in the Flemish Community than in the French Community,
whatever the level of education or the stage of the career of teachers (salaries vary between levels of education
and stages of the career). In Canada and the United Kingdom, subnational differences vary according to the
stage of the career of teachers only (as the lowest salaries – respectively the highest salaries – are similar
at the different levels of education). In both countries, the differences between subnational entities are the
largest for starting salaries and decrease with the level of experience. For example in Canada, statutory salaries
vary by 80% between subnational entities at the starting point (from USD 31 912 to USD 57 425), by 76%
after 10 years of experience (from USD 46 418 to USD 81 741) and by 43% after 15 years of experience or
at the top of the scale (from USD 57 158 to USD 81 741). In Sweden and the United States, the differences
between subnational entities vary according to the stages of the career of teacher and the level of education.

…

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In Sweden the variations are the largest for starting salaries, varying by 18% to 21% according to levels of
education, and vary by 10% to 17% at other stages of the career (whatever the level of education). In the
United States, there is no clear pattern in the variation (between subnational entities) of statutory salaries at
different levels of education and stages of the career. The variations are the smallest for starting salaries at
lower secondary level (varying by 71% from USD 33 355 to USD 57 030) and the largest for top of the range
salaries at lower secondary level (varying by 200% from USD 51 957 to USD 104 045) (OECD/NCES, 2018[3]).
There are also large subnational variations in actual salaries among the six countries with available
data (Belgium, Brazil, Slovenia, Sweden, the United Kingdom and the United States). In Belgium and
Slovenia, actual salaries of 25-64 year-old teachers vary by less than 7% between subnational entities at
pre‑primary, primary, lower secondary and upper secondary levels. Subnational variations of actual salaries
for 25‑64 year‑old teachers are larger in Sweden and the United Kingdom, varying from 10% for upper
secondary teachers in Sweden (from USD 43 593 to USD 48 203) to 17% for lower and upper secondary
teachers in the United Kingdom (from USD 41 670 to USD 48 817). Subnational differences are much larger
in Brazil and the United States. The highest salaries are about twice the lowest salaries in the United States
at primary, lower and upper secondary levels (varying from USD 42 060 to USD 84 064 at primary, from
USD 41 641 to USD 81 567 at lower secondary and from USD 42 393 to USD 82 540 at upper secondary).
In Brazil, salaries in the subnational region with the highest actual salaries are more than three times those
in the subnational region with the smallest actual salaries at pre-primary, primary and lower secondary
levels, and 5.6 times higher than the lowest actual salaries at the subnational level at upper secondary level
(OECD/NCES, 2018[3]).
Within each country, differences in actual salaries at the subnational level are similar for the different age
groups for which data are collected (25-34 year-olds, 35-44 year-olds, 45-54 year-olds and 55-64 year-olds),
but are slightly larger for the younger age group in Brazil or Sweden. The differences in actual salaries at the
subnational level are also similar for women and men in the different countries with available information
(OECD/NCES, 2018[3]).

Figure D3.5. Actual salaries of lower secondary teachers and school heads (2016)
Annual actual salaries of teachers and school heads in public institutions, in equivalent USD converted using PPPs
Actual salaries of school heads

Equivalent USD
converted using PPPs

Actual salaries of teachers

140 000
120 000
100 000
80 000
60 000
40 000

Latvia

Slovak Republic

Turkey

Estonia

Greece

Czech Republic

Chile

Poland

Iceland

Slovenia

Sweden

Norway

Portugal

Average

Scotland (UK)

Israel

New Zealand

France1

Finland

Italy

Denmark

Flemish Comm. (Belgium)

Austria

French Comm. (Belgium)1

Netherlands

United States

Australia

England (UK)

0

Luxembourg

20 000

1. Year of reference differs from 2016. See Table D3.4 for more information.	
Countries and economies are ranked in descending order of actual salaries of school heads.
Source: OECD (2018), Table D3.4. See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933805534

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Actual salaries of school heads are higher than those of teachers, and the premium increases with levels of education.
On average across OECD countries and economies, actual salaries of school heads are 35% higher than those of
teachers at pre-primary level, and the premium is 39% at primary level, and 48% at lower and upper secondary
levels. The difference between actual salaries of school heads and teachers varies largely between countries and
between levels of education. Countries with the highest premium for school heads compared to teachers are
England (United Kingdom) (secondary levels) and Italy (primary and secondary levels), where actual salaries of
school heads are twice that of teachers. The premium is the lowest and less than 25% in Denmark (pre-primary
level), Finland (pre-primary level), France (pre-primary and primary levels), Luxembourg (secondary levels) and
Norway (pre‑primary level). Other countries show a steep rise in salaries of school heads compared to teachers at
the secondary level, while there is a more moderate difference at primary level. For example, in France actual salaries
of school heads and teachers are approximately similar at pre-primary and primary levels, but, the difference is 55%
at lower secondary and 37% at upper secondary level. In Latvia, the difference is much larger at pre-primary and
primary levels than at lower and upper secondary level (Table D3.4).
Teachers’ and school heads’ actual salaries relative to earnings for tertiary-educated workers
Education systems compete with other sectors of the economy to attract high-quality graduates as teachers.
Research shows that salaries and alternative employment opportunities are important factors in the attractiveness
of teaching (Johnes and Johnes, 2004[4]). Salaries of teachers relative to those of other occupations (with similar
education) and the likely growth in earnings may have a huge influence on a graduate’s decision to become a teacher
and stay in the profession. The career prospects of school heads and their relative salaries are also a signal of career
progression pathways available to teachers and the compensation they can expect in the longer term.
In most OECD countries, a tertiary degree is required to become a teacher and then a school head, at all levels of
education, meaning the likely alternative to teacher education is a similar tertiary education programme. Thus, to
interpret salary levels in different countries and reflect comparative labour-market conditions, actual salaries are
compared to earnings of other tertiary-educated professionals: 25-64 year-old full-time, full-year workers with a
similar tertiary education (ISCED 5 to 8) (see Box D3.3 for data by age group or gender). Moreover, to ensure that
the comparison between countries is not biased by differences between the distribution of teachers by tertiary
attainment and the distribution of tertiary-educated workers by attainment level, actual salaries of teachers are
compared to a weighted average of earnings of similarly educated workers (earnings of similarly educated workers
weighted by the proportion of teachers with similar tertiary attainment) (see Table X2.6 in Annex 2 for the
proportion of teachers by attainment level).
Among the 19 countries and economies with available data (for at least one level), actual salaries of teachers amount
to 60% or less of earnings of similarly educated workers in the Czech Republic (primary and lower secondary) and
the United States. Very few countries and economies have actual salaries of teachers that reach or exceed those of
similarly educated workers. However, in the Flemish Community of Belgium, actual salaries of teachers equal those
of similarly educated workers, and in Latvia they are 5% higher at the lower secondary level and 22% higher at upper
secondary level (Table D3.2a).
Considering the few countries with available data for this relative measure of teachers’ salaries, a second benchmark
is based on the actual salaries of all teachers, relative to earnings for full-time, full-year workers with tertiary
education (ISCED 5 to 8) (see Methodology section). Against this benchmark, actual teacher salaries relative to other
tertiary workers increase with higher education levels. Pre-primary teachers’ salaries amount to 81% of full-time,
full-year earnings, on average, among 25-64 year-olds with tertiary education. Primary teachers earn 86% of the
benchmark salary, lower secondary teachers 91%, and upper secondary teachers 96% (Table D3.2a).
In almost all countries and economies with available information, and at almost all levels of education, teachers’ actual
salaries are lower than those of tertiary-educated workers. The relative salary of teachers is lowest in the Slovak Republic
at the pre-primary level, where teachers’ salaries are 48% those of tertiary-educated workers, and in the Czech Republic
at primary and secondary levels where they reach 61% to 63% of those of tertiary-educated workers. However in some
countries, teachers earn more than tertiary-educated adults at all levels of education (in Greece, Luxembourg and
Portugal), or at upper secondary level only (in Finland, the Flemish and French Communities of Belgium, Germany
and Latvia). In Luxembourg and Portugal, teachers earn at least 30% more than tertiary-educated workers, and in
Luxembourg, secondary teachers earn twice as much. However caution is necessary when interpreting the ratio.
For example, in Greece the proportion of overqualified people in their job may lead to lower average earnings compared
to workers with similar proficiency but who are well-matched with their jobs. This may explain that teachers’ salaries
are higher than those of similarly educated workers (Table D3.2a and Figure D3.1).

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Box D3.3. Actual average salaries of teachers, by age group and gender (2016)
At primary and secondary levels, actual salaries of older teachers (age 55-64) are, on average, 37% to 39%
higher than those of younger teachers (age 25-34), but this difference between age groups varies considerably
between countries and economies. The difference is less than 20% at all levels of education in Australia, Norway
and Sweden, while it is 60% or more in Austria, Chile, Greece, Israel, and Portugal (Table D3.4).
Despite the increase in teachers’ salaries for older age groups, the comparison of teachers’ salaries with earnings
of tertiary-educated workers seems to show that teachers’ salaries may evolve at a slower rate than earnings
of other workers and that the teaching profession is less attractive as the workforce ages. On average across
OECD countries and economies, teachers’ actual salaries relative to earnings of tertiary-educated workers are
about 14 percentage points higher among the youngest adults (age 25-34) than among the older age groups
(age 55-64) at lower secondary level. However, there are large differences between countries, and in Chile,
Greece, Hungary, Israel and Latvia, teachers’ actual salaries relative to earnings of tertiary-educated workers
are higher for older age groups at pre-primary, primary and secondary levels.
Differences between actual salaries for male and female teachers are small, 2% or less, on average, at primary
and secondary levels, in favour of men.
There are larger gender differences in the ratio of teachers’ salaries to earnings for tertiary-educated workers
aged 25-64. On average across OECD countries and economies, actual salaries of male teachers (age 25-64) are
77% (at primary level) to 88% (at upper secondary level) of the earnings of a tertiary-educated 25-64 year-old
full-time, full-year male worker. Teachers’ actual salaries relative to earnings of tertiary-educated workers are
about 31 to 33 percentage points higher among women than among the men at pre-primary, primary and
secondary levels of education. This higher ratio among female teachers shows that the teaching profession may
be more attractive to women than to men, compared to other professions, but it also reflects the persistent
gender gap in earnings (in favour of men) in the labour market (Tables D3.2 and D3.4).

As actual salaries of school heads are higher than those of teachers, they are also higher on average than those of other
tertiary-educated adults, and the difference increases with the level of education. On average across OECD countries
and economies, school heads earn 21% more than tertiary-educated adults at primary level, 34% more at lower
secondary level and 42% more at upper secondary level. School heads earn less than tertiary‑educated adults only in
the Czech Republic (pre-primary, primary and lower secondary levels), Denmark (pre-primary level), Estonia (preprimary level), Finland (pre-primary level), France (pre-primary and primary levels), Norway (pre‑primary, primary
and lower secondary levels) and the Slovak Republic.
Formation of base salary and additional payments: Incentives and allowances
Statutory salaries, based on pay scales, are only one component of the total compensation of teachers and school
heads. School systems also offer additional payments to teachers and school heads, such as allowances, bonuses
or other rewards. These may take the form of financial remuneration and/or reduction in the number of teaching
hours, and decisions on the criteria used for the formation of the base salary are taken at different decision-making
levels (Tables D3.8 and D3.12, available on line).
Criteria for additional payments vary across countries. In the large majority of countries, teachers’ core tasks
(teaching, planning or preparing lessons, marking students’ work, general administrative work, communicating
with parents, supervising students and working with colleagues) are rarely considered as meriting bonuses or
additional payments (Table D3.7, available on line). Teachers may also be required to have some responsibilities or
perform some tasks without additional compensations (see Indicator D4 for tasks and responsibilities of teachers).
Taking on other responsibilities, however, often entails having some sort of extra compensation.
At lower secondary level, teachers who participate in school management activities in addition to their teaching duties
received extra compensation in three-quarters of countries and economies with available information. This may be
either reduced teaching time, as in Finland, Portugal and the Slovak Republic, or an occasional or annual additional
payment, as in Austria, Costa Rica, England (United Kingdom), France, Germany, Ireland, Italy, Japan, Korea, Norway,
Spain and Turkey. In Denmark, teachers may benefit from both reduced teaching time and an annual payment.
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It is also common to see additional payments, either annual or occasional, when teachers teach more classes or hours
than required by their full-time contract, have responsibility as a class or form teacher or perform special tasks, such as
training student teachers (Table D3.7, available on line).

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Additional compensation, either in the form of occasional additional or annual payments or through increases in basic
salary, is also awarded for outstanding performance by lower secondary teachers in about half of OECD countries
and economies with available data. Additional payments can also include bonuses for special teaching conditions,
such as teaching students with special needs in regular schools or teaching in disadvantaged, remote or high-cost
areas (Table D3.7, available on line).
There are also criteria for additional payments for school heads, but fewer tasks or responsibilities lead to additional
payments compared to teachers. At lower secondary level, only a few countries do not offer any type of additional
compensation to their school heads: Austria, England (United Kingdom), the French Community of Belgium and
Portugal.
Among the 29 countries with available data, about one-third provide additional compensation to school heads for
participation in management tasks over and above their usual school head responsibilities or for working overtime.
About half of the countries (Australia, Austria, the French Community of Belgium, Chile, England [United Kingdom],
Finland, Greece, Ireland, Japan, Korea, Mexico, Portugal, Slovenia, and Spain) provide additional compensation for
teachers when they take on extra responsibilities, but do not provide any additional payments to school heads
(Table D3.11, available on line). As for teachers (see above), in some countries, such as Greece, a number of these
responsibilities and tasks are considered part of teachers’ and school heads’ duties and are thus not compensated
with any extra allowances.
At lower secondary level, additional compensation is also awarded to school heads for outstanding performance
in one-third of the countries and economies with available data, as it is to teachers. However Austria, Chile,
England (United Kingdom), Israel and Turkey provide additional compensation for outstanding performance to
teachers, but not to school heads. The opposite is observed in France and Spain, where school heads are rewarded
for high performance, but not teachers (Tables D3.11 and D3.7, available on line).
Teachers and school heads are also likely to receive additional payments for working in disadvantaged, remote, or
high cost areas in half of the countries, with the exception of England (United Kingdom), where such incentives
are provided only to teachers, and Australia, where they are only provided to school heads (Tables D3.11 and D3.7,
available on line).

Definitions
Teachers refer to professional personnel directly involved in teaching to students. The classification includes
classroom teachers, special-education teachers and other teachers who work with a whole class of students in a
classroom, in small groups in a resource room, or in one-to-one teaching situations inside or outside a regular class.
School head refers to any person whose primary or major function is heading a school or a group of schools, alone
or within an administrative body such as a board or council. The school head is the primary leader responsible for
the leadership, management and administration of a school.
Actual salaries for teachers/school heads aged 25-64 refer to the annual average earnings received by full-time
teachers/school heads aged 25 to 64, before taxes. It is the gross salary from the employee’s point of view, since it
includes the part of social security contributions and pension scheme contributions that are paid by the employees
(even if deducted automatically from the employees’ gross salary by the employer). However, the employers’ premium
for social security and pension is excluded. Actual salaries also include work-related payments, such as school-head
allowance, annual bonuses, results-related bonuses, extra pay for holidays and sick-leave pay. Income from other
sources, such as government social transfers, investment income and any other income that is not directly related
to their profession are not included.
Earnings for workers with tertiary education are average earnings for full-time, full-year workers aged 25-64 with
an education at ISCED level 5, 6, 7 or 8.
Salary at the top of the scale refers to the maximum scheduled annual salary (top of the salary range) for a full-time
classroom teacher (for a given level of qualification of teachers recognised by the compensation system).
Salary after 15 years of experience refers to the scheduled annual salary of a full-time classroom teacher. Statutory
salaries may refer to the salaries of teachers with a given level of qualification recognised by the compensation

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system (the minimum training necessary to be fully qualified, the most prevalent qualifications, or the maximum
qualification), plus 15 years of experience.
Starting salary refers to the average scheduled gross salary per year for a full-time classroom teacher with a given
level of qualification recognised by the compensation system (the minimum training necessary to be fully qualified
or the most prevalent qualifications) at the beginning of the teaching career.
Statutory salaries refer to scheduled salaries according to official pay scales. The salaries reported are gross (total
sum paid by the employer) less the employer’s contribution to social security and pension, according to existing
salary scales. Salaries are “before tax” (i.e. before deductions for income tax).

Methodology
Data on teachers’ salary at lower and upper secondary level refer only to general programmes.
Salaries were converted using purchasing power parities (PPPs) for private consumption from the OECD National
Accounts database. The period of reference for teachers’ salaries is from 1 July 2016 to 30 June 2017 for statutory
data and from 1 July 2015 to 30 June 2016 for actual data. The reference date for PPPs is 2016/17 for statutory
data and 2015/16 for actual data, except for some Southern Hemisphere countries (e.g. Australia and New Zealand),
where the academic year runs from January to December. In these countries, the reference year is the calendar year
(i.e. 2017 and 2016). Tables with salaries in national currency are included in Annex 2. For calculation of changes in
teachers’ salaries (Table D3.5a and Table D3.5b, available on line), the deflator for private consumption is used to
convert salaries to 2005 prices.
In most countries, the criteria to determine the most prevalent qualifications of teachers are based on a principle of
relative majority (i.e. the level of qualifications of the largest proportion of teachers).
In Table D3.2a, the ratios of salaries to earnings for full-time, full-year workers with tertiary education aged 25‑64
are calculated based on weighted averages of earnings of tertiary-educated workers (first four columns). The
weights, collected for every country individually, are based on the percentage of teachers by ISCED level of tertiary
attainment (see Table X2.6 in Annex 2). The ratios have been calculated for countries for which these data are
available. When data on earnings of workers referred to a different reference year than the 2016 reference year used
for salaries of teachers or school heads, a deflator has been used to adjust earnings data to 2016 reference year).
For all other ratios in Table D3.2a and those in Table D3.2c (available on line), information on all tertiary-educated
workers was used instead of weighted averages. Data on earnings of workers take account of earnings from work
for all individuals during the reference period, including salaries of teachers. In most countries, the population of
teachers is large and may impact on the average earnings of workers. The same procedure was used in Table D3.2b
(available on line), but the ratios are calculated using the statutory salaries of teachers with 15 years of experience
instead of their actual salaries.
For more information please see the OECD Handbook for Internationally Comparative Education Statistics 2018 (OECD,
2018[5]) and Annex 3 for country-specific notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Lithuania was not an OECD member at the time of preparation of this publication. Accordingly, Lithuania does not
appear in the list of OECD members and is not included in the zone aggregates.

Source
Data on salaries and bonuses for teachers and school heads are derived from the 2017 joint OECD/Eurydice data
collection on salaries of teachers and school heads. Data refer to the school year 2016/17 (for statutory salaries)
or 2015/16 (for actual salaries) and are reported in accordance with formal policies for public institutions. Data on
earnings of workers are based on the regular data collection by the OECD LSO (Labour Market and Social Outcomes
of Learning) Network.

Note regarding data from Israel
The statistical data for Israel are supplied by and are under the responsibility of the relevant Israeli authorities. The use
of such data by the OECD is without prejudice to the status of the Golan Heights, East Jerusalem and Israeli settlements
in the West Bank under the terms of international law.

Education at a Glance 2018: OECD Indicators   © OECD 2018

373

D3

chapter D Teachers, the Learning Environment and the Organisation of Schools
Under embargo until 11/09/2018 at 11.00am CEST
References
Johnes, G. and J. Johnes (2004), International Handbook on the Economics of Education, Edward Elgar Publishing.

[4]

OECD (2018), OECD Handbook for Internationally Comparative Education Statistics 2018: Concepts, Standards, Definitions [5]
and Classifications, OECD Publishing, Paris, https://doi.org/10.1787/9789264304444-en.
OECD (2017), Education at a Glance 2017: OECD Indicators, OECD Publishing, Paris, http://dx.doi.org/10.1787/eag-2017-en. [2]

D3

OECD (2005), Teachers Matter: Attracting, Developing and Retaining Effective Teachers, Education and Training Policy, [1]
OECD Publishing, Paris, http://dx.doi.org/10.1787/9789264018044-en.
OECD/NCES (2018), Education at a Glance Subnational Supplement, OECD/National Center for Education Statistics, Paris [3]
and Washington, DC, https://nces.ed.gov/surveys/annualreports/oecd/index.asp.

Indicator D3 Tables
1 2 https://doi.org/10.1787/888933805363

Table D3.1a Teachers’ statutory salaries, based on the most prevalent qualifications at different points in
teachers’ careers (2017)
WEB Table D3.1b Teachers’ statutory salaries, based on the most prevalent qualifications at a given level of education
(2017)
WEB Table D3.1c Teachers’ statutory salaries, based on the minimum qualifications to enter the teaching profession
(2017)
Table D3.2a Actual salaries of teachers and school heads relative to earnings of tertiary-educated workers (2017)
WEB Table D3.2b Teachers’ statutory salaries relative to earnings of tertiary-educated workers (2017)
WEB Table D3.2c Teachers’ actual salaries relative to earnings of tertiary-educated workers, by age group and by
gender (2016)
WEB Table D3.2d School heads’ statutory salaries relative to earnings of tertiary-educated workers (2017)
WEB Table D3.3a Comparison of teachers’ statutory salaries, based on the most prevalent qualifications of teachers
by level of education (2017)
WEB Table D3.3b Comparison of teachers’ statutory salaries, based on the minimum qualifications required to enter
the teaching profession in the reference year (2017)
Table D3.4

Average actual salaries of teachers and school heads, by age group and by gender (2016)

WEB Table D3.5a Trends in teachers’ salaries, based on most prevalent qualifications at different points in teachers’
careers, between 2000 and 2017
WEB Table D3.5b Trends in teachers’ salaries, based on minimum qualifications on entry to the profession, between
2000 and 2017
WEB Table D3.6

Starting/maximum teachers’ statutory salaries, based on minimum/maximum qualifications (2017)

WEB Table D3.7

Criteria used for base salaries and additional payments awarded to teachers in public institutions, all
level of education (2017)

WEB Table D3.8

Decision-making level for criteria used for determining teachers’ base salaries and additional
payments, by level of education (2017)

WEB Table D3.9

Structure of compensation system for school heads (2017)

Table D3.10 Minimum / maximum school heads’ statutory salaries, based on minimum qualifications (2017)
WEB Table D3.11 Criteria used for base salaries and additional payments awarded to school heads in public
institutions, by level of education (2017)
WEB Table D3.12 Decision-making level for criteria used for determining schools heads’ base salaries and additional
payments, by level of education (2017)
Cut-off date for the data: 18 July 2018. Any updates on data can be found on line at http://dx.doi.org/10.1787/eag-data-en. Data can also be found
at http://stats.oecd.org/, Education at a Glance Database.

374 Education at a Glance 2018: OECD Indicators   © OECD 2018

How much are teachers and school heads paid? – INDICATOR D3

chapter D

Under embargo until 11/09/2018 at 11.00am CEST
Table D3.1a. Teachers’ statutory salaries, based on the most prevalent qualifications at different points

in teachers’ careers (2017)

Annual teachers’ salaries, in public institutions, in equivalent USD converted using PPPs for private consumption

OECD

Lower secondary,
general programmes

Salary after
15 years of
experience

Salary at
top of scale

Starting
salary

Salary after
10 years of
experience

Salary after
15 years of
experience

Salary at
top of scale

Starting
salary

Salary after
10 years of
experience

Salary after
15 years of
experience

Salary at
top of scale

Starting
salary

Salary after
10 years of
experience

Salary after
15 years of
experience

Salary at
top of scale

Upper secondary,
general programmes

Salary after
10 years of
experience

Primary

Starting
salary

Pre-primary

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

(13)

(14)

(15)

(16)

Countries

Australia
Austria
Canada
Chile
Czech Republic
Denmark
Estonia
Finland1
France2
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Luxembourg3
Mexico
Netherlands
New Zealand4
Norway
Poland
Portugal
Slovak Republic5
Slovenia5
Spain
Sweden4, 5, 6
Switzerland
Turkey
United States5, 6

41 798 59 043 59 568 59 568 41 798 59 043 59 568 59 568 41 800 59 043 59 568 59 568 41 798 59 043 59 568 59 568
m
m
m
m 40 548 44 633 49 961 73 501 40 411 46 965 52 538 78 495 40 460 50 880 57 533 83 660
m
m
m
m 39 222 62 860 65 474 65 474 39 222 62 860 65 474 65 474 39 222 62 860 65 474 65 474
23 429 29 004 34 231 43 760 23 429 29 004 34 231 43 760 23 429 29 004 34 231 43 760 24 028 29 804 35 111 44 959
17 920 18 338 18 805 20 964 18 944 20 110 21 007 24 785 18 953 20 147 21 049 24 901 18 971 20 165 21 044 24 862
41 274 46 552 46 552 46 552 44 919 49 863 51 506 51 506 45 134 50 466 52 183 52 183 42 841 55 675 55 675 55 675
a
a
a
a 19 529
a
a
a 19 529
a
a
a 19 529
a
a
a
29 578 31 945 31 945 31 945 33 408 38 671 40 991 43 451 36 081 41 765 44 271 46 927 38 261 45 951 47 789 50 656
29 516 33 618 35 963 52 374 29 516 33 618 35 963 52 374 31 003 35 106 37 450 54 010 31 003 35 106 37 450 54 010
m
m
m
m 56 535 66 950 70 693 75 002 63 555 73 357 76 838 83 451 63 866 77 619 81 260 92 386
19 374 22 754 25 998 37 699 19 374 22 754 25 998 37 699 19 374 22 754 25 998 37 699 19 374 22 754 25 998 37 699
14 227 19 206 20 629 27 031 14 227 19 206 20 629 27 031 15 752 19 206 20 629 27 031 15 752 21 265 22 840 29 928
34 394 35 716 38 105 38 105 35 756 37 179 39 477 39 477 35 756 37 179 39 477 39 477 30 347 31 805 32 706 41 414
m
m
m
m 33 962 53 805 59 459 68 712 33 962 55 761 60 053 69 306 33 962 55 761 60 053 69 306
23 001 29 855 33 647 61 436 20 051 27 056 30 321 51 495 20 159 28 891 33 442 53 650 20 666 27 221 30 580 49 298
28 514 31 368 34 444 41 914 28 514 31 368 34 444 41 914 30 739 34 051 37 530 46 030 30 739 34 879 38 581 48 121
m
m
m
m 30 631 43 847 51 593 63 969 30 631 43 847 51 593 63 969 30 631 43 847 51 593 65 658
30 395 45 746 53 405 84 842 30 395 45 746 53 405 84 842 30 455 45 806 53 465 84 902 29 738 45 088 52 747 84 185
12 994
a
a
a 14 252
a
a
a 14 252
a
a
a 14 252
a
a
a
70 192 90 782 102 505 124 036 70 192 90 782 102 505 124 036 79 551 99 439 109 734 138 279 79 551 99 439 109 734 138 279
19 893 25 261 31 686 39 996 19 893 25 261 31 686 39 996 25 401 32 237 40 595 51 139 49 286 57 031 60 886 65 843
38 922 48 775 58 036 61 279 38 922 48 775 58 036 61 279 41 309 63 345 72 778 84 469 41 309 63 345 72 778 84 469
m
m
m
m 30 254 46 337 46 337 46 337 30 746 46 963 46 963 46 963 31 238 47 589 47 589 47 589
35 577 41 489 41 489 41 908 39 585 47 687 47 687 51 209 39 585 47 687 47 687 51 209 47 211 52 171 52 171 57 740
15 600 20 926 25 553 26 636 15 600 20 926 25 553 26 636 15 600 20 926 25 553 26 636 15 600 20 926 25 553 26 636
32 887 40 041 42 489 65 417 32 887 40 041 42 489 65 417 32 887 40 041 42 489 65 417 32 887 40 041 42 489 65 417
12 754 14 037 14 673 15 824 14 267 17 129 20 057 21 625 14 267 17 129 20 057 21 625 14 267 17 129 20 057 21 625
26 823 31 917 38 890 44 691 26 823 33 099 40 351 48 166 26 823 33 099 40 351 48 166 26 823 33 099 40 351 48 166
38 987 42 217 45 069 55 384 38 987 42 217 45 069 55 384 43 565 47 241 50 257 61 543 43 565 47 241 50 257 61 543
36 192 38 433 39 444 42 737 36 689 41 322 43 201 49 587 37 566 42 321 43 827 50 964 37 566 43 771 44 891 52 217
52 743 66 002
m 80 416 56 351 70 049
m 85 753 63 308 80 029
m 96 997 71 249 91 416
m 109 240
26 219 27 223 28 835 33 288 26 219 27 223 28 835 33 288 26 219 27 223 28 835 33 288 26 219 27 223 28 835 33 288
38 635 52 853 64 279 71 280 39 183 53 826 61 028 67 197 39 707 54 566 63 046 68 052 40 517 54 609 63 006 70 900

Partners

Economies

Flemish Comm. (Belgium)5
French Comm. (Belgium)
England (UK)
Scotland (UK)

36 099
35 041
28 011
33 531

OECD average
EU22 average

30 817 38 456 41 386 50 486 32 258 41 884 45 004 54 156 33 498 43 886 46 780 56 874 34 943 46 244 48 697 59 639
29 922 36 921 40 714 47 867 31 699 40 426 44 568 52 868 33 041 42 704 46 644 56 006 33 781 44 886 48 884 58 736

Argentina
Brazil
China
Colombia
Costa Rica
India
Indonesia
Lithuania
Russian Federation
Saudi Arabia
South Africa

m
13 971
m
m
23 888
m
m
12 573
m
m
m

m
m
m
m
28 165
m
m
13 532
m
m
m

m
m
m
m
30 304
m
m
13 842
m
m
m

m
m
m
m
36 720
m
m
14 432
m
m
m

m
13 971
m
m
23 888
m
m
19 385
m
m
m

m
m
m
m
28 165
m
m
19 571
m
m
m

m
m
m
m
30 304
m
m
19 696
m
m
m

m
m
m
m
36 720
m
m
19 882
m
m
m

m
13 971
m
m
24 893
m
m
19 385
m
m
m

m
m
m
m
29 351
m
m
19 571
m
m
m

m
m
m
m
31 580
m
m
19 696
m
m
m

m
m
m
m
38 266
m
m
19 882
m
m
m

m
13 971
m
m
24 893
m
m
19 385
m
m
m

m
m
m
m
29 351
m
m
19 571
m
m
m

m
m
m
m
31 580
m
m
19 696
m
m
m

m
m
m
m
38 266
m
m
19 882
m
m
m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

G20 average

45 269
43 817
a
44 588

50 966
49 332
47 688
44 588

62 359
60 364
47 688
44 588

36 099
35 041
28 011
33 531

45 269
43 817
a
44 588

50 966
49 332
47 688
44 588

62 359
60 364
47 688
44 588

36 099
35 041
28 011
33 531

45 269
43 817
a
44 588

50 966
49 332
47 688
44 588

62 359
60 364
47 688
44 588

45 038
43 593
28 011
33 531

57 404
55 566
a
44 588

65 463
63 369
47 688
44 588

78 894
76 373
47 688
44 588

Note: The definition of teachers’ most prevalent qualifications is based on a broad concept, including the typical ISCED level of attainment and other criteria. The
most prevalent qualificaiton is defined for each of the four stage of the career included in this table. Please see Box D3.2, Annex 2 and Definitions and Methodology
sections for more information. Data available at http://stats.oecd.org/, Education at a Glance Database.
1. Data on pre-primary teachers includes the salary of kindergarten teachers who are the majority.
2. Includes the average of fixed bonuses for overtime hours for lower and upper secondary teachers.
3. Includes the social security contributions and pension-scheme contributions paid by the employers.
4. Excludes the social security contributions and pension-scheme contributions paid by the employees.
5. At the upper secondary level includes teachers working in vocational programmes. In Slovenia, includes only those teachers teaching general subjects within vocational
programmes.
6. Actual base salaries.
Source: OECD (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933805382

Education at a Glance 2018: OECD Indicators   © OECD 2018

375

D3

chapter D Teachers, the Learning Environment and the Organisation of Schools
Under embargo until 11/09/2018 at 11.00am CEST
Table D3.2a. Actual salaries of teachers and school heads relative to earnings

of tertiary‑educated workers (2016)

Ratio of salary, using annual average salaries (including bonuses and allowances) of teachers and school heads in public
institutions relative to the wages of workers with similar educational attainment (weighted average) and to the earnings
of full‑time, full-year workers with tertiary education.
All teachers

D3

All school heads

Primary

Lower secondary,
general programmes

Upper secondary,
general programmes

Pre-primary

Primary

Lower secondary,
general programmes

Upper secondary,
general programmes

Pre-primary

Primary

Lower secondary,
general programmes

Upper secondary,
general programmes

Actual salaries,
Actual salaries,
relative to earnings for full-time,
relative to earnings for full-time,
full‑year workers with tertiary education full‑year workers with tertiary education
(ISCED 5 to 8, 25-64 year-olds)
(ISCED 5 to 8, 25-64 year-olds)

Pre-primary

OECD

Year of
reference
of latest
available
data on
earnings
of
tertiaryeducated
workers

Actual salaries,
relative to earnings for full-time,
full‑year similarly educated workers
(weighted averages, 25-64 year-olds)

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

(13)

2016
2016
2015
2015
2015
2016
2016
2015
2014
2016
2016
2016
m
m
2016
2014
m
m
2016
2016
m
2014
2016
2016
2016
2016
2016
2016
m
2016
m
2016
2016

m
m
m
0.73
0.75
m
0.67
0.73
0.82
m
m
0.76
m
m
0.84
m
m
m
0.87
m
m
0.78
m
0.74
0.69
m
m
0.78
m
0.84
m
m
0.55

m
m
m
0.69
0.60
m
0.88
0.77
0.80
0.83
m
0.75
m
m
0.84
m
m
m
0.88
m
m
0.78
0.87
0.82
0.77
m
m
0.83
m
0.88
m
m
0.55

m
m
m
0.71
0.60
m
0.86
0.84
0.88
0.92
m
0.75
m
m
0.86
m
m
m
1.05
m
m
0.92
0.89
0.82
0.80
m
m
0.86
m
0.83
m
m
0.56

m
m
m
0.76
0.61
0.79
0.85
0.94
0.99
0.97
m
0.67
m
m
0.82
m
m
m
1.22
m
m
0.92
0.93
0.80
0.77
m
m
0.84
m
0.83
m
m
0.58

0.92
m
m
0.84
0.52
0.68
0.62
0.66
0.78
m
1.06
0.66
m
m
0.84
0.68
m
m
0.79
1.80
m
0.73
m
0.67
0.68
1.50
0.48
0.69
m
0.76
m
0.80
0.62

0.93
0.76
m
0.80
0.61
0.82
0.91
0.89
0.76
0.90
1.06
0.70
m
m
0.88
0.68
m
m
0.80
1.80
m
0.73
0.85
0.75
0.79
1.38
0.64
0.87
m
0.86
m
0.80
0.63

0.93
0.90
m
0.82
0.61
0.83
0.91
0.99
0.88
0.99
1.15
0.70
m
m
0.95
0.69
m
m
0.97
2.02
m
0.92
0.87
0.75
0.82
1.35
0.64
0.89
m
0.89
m
0.80
0.65

0.93
0.97
m
0.89
0.63
0.95
0.91
1.11
1.00
1.05
1.15
0.75
m
m
0.90
0.72
m
m
1.13
2.02
m
0.92
0.93
0.82
0.80
1.47
0.64
0.94
m
0.91
m
0.80
0.68

1.36
m
m
1.17
0.74
0.76
0.94
0.82
0.81
m
1.44
m
m
m
m
m
m
m
1.23
m
m
1.03
m
0.81
1.01
1.99
0.48
1.18
m
1.11
m
1.01
1.09

1.42
1.06
m
1.16
0.97
1.15
1.14
1.24
0.81
m
1.44
m
m
m
1.60
1.44
m
m
1.32
m
m
1.03
1.27
0.97
1.08
1.99
0.64
1.21
m
1.21
m
1.01
1.11

1.68
1.18
m
1.18
0.97
1.15
1.14
1.42
1.37
m
1.57
m
m
m
1.59
1.44
m
m
1.21
2.43
m
1.28
1.35
0.97
1.10
1.99
0.64
1.21
m
1.21
m
1.01
1.15

1.59
1.42
m
1.30
1.05
1.51
1.14
1.50
1.37
m
1.57
m
m
m
1.62
1.44
m
m
1.48
2.43
m
1.28
1.47
1.12
1.10
1.99
0.64
1.24
m
1.25
m
1.01
1.17

2015
2015
2016
2016

0.99
0.95
m
m

1.00
0.94
m
m

0.96
0.89
m
m

0.97
0.94
m
m

0.88
0.85
0.80
0.83

0.88
0.84
0.80
0.83

0.86
0.82
0.90
0.83

1.11
1.04
0.90
0.83

1.25
1.19
1.48
1.28

1.25
1.21
1.48
1.28

1.28
1.29
2.19
1.28

1.53
1.54
2.19
1.28

m
0.80

m
0.82

m
0.86

m
0.88

0.81
0.82

0.86
0.88

0.91
0.93

0.96
1.00

m
1.10

1.21
1.21

1.34
1.37

1.42
1.45

m
m
m
m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
0.95
m
m
m

m
m
m
m
m
m
m
0.95
m
m
m

m
m
m
m
m
m
m
0.95
m
m
m

m
m
m
m
m
m
m
0.95
m
m
m

m
m
m
m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m
m
m
m

m

m

m

m

m

m

m

m

m

m

m

m

Countries

Australia
Austria
Canada
Chile
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United States
Economies

Flemish Comm. (Belgium)
French Comm. (Belgium)
England (UK)
Scotland (UK)

Partners

OECD average
EU22 average
Argentina
Brazil
China
Colombia
Costa Rica
India
Indonesia
Lithuania
Russian Federation
Saudi Arabia
South Africa
G20 average

m
m
m
m
m
m
m
2014
m
m
m

Note: See Definitions and Methodology sections for more information. Data available at http://stats.oecd.org/, Education at a Glance Database.
Source: OECD (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933805401

376 Education at a Glance 2018: OECD Indicators   © OECD 2018

How much are teachers and school heads paid? – INDICATOR D3

chapter D

Under embargo until 11/09/2018 at 11.00am CEST
Table D3.4. Average actual salaries of teachers and school heads, by age group and by gender (2016)
Annual average salaries (including bonuses and allowances) of teachers in public institutions, in equivalent USD converted using
PPPs for private consumption, by age group and gender

OECD

25-64 year-old teachers

25-64 year-old school heads

Pre-primary

Primary

Lower
secondary,
general
programmes

Upper
secondary,
general
programmes

Pre-primary

Primary

Lower
secondary,
general
programmes

Upper
secondary,
general
programmes

(1)

(2)

(3)

(4)

(29)

(30)

(31)

(32)

54 654
m
m
29 659
20 233
44 441
15 861
33 450
38 941
m
24 770
22 824
36 140
m
35 210
34 167
m
m
12 267
96 884
m
53 149
m
44 120
26 303
47 336
17 449
28 621
m
37 696
m
22 143
51 295

54 914
56 684
m
28 400
24 060
53 121
23 584
45 244
37 968
65 716
24 770
24 122
39 572
m
36 950
34 167
m
m
12 465
96 884
m
53 149
42 536
49 753
30 508
43 498
23 316
36 120
m
42 657
m
22 143
52 197

55 313
66 329
m
28 901
23 966
53 703
23 584
49 860
44 294
72 593
26 697
24 122
39 572
m
39 897
34 568
m
m
15 096
108 673
m
66 617
43 397
49 753
31 567
42 770
23 316
36 864
m
44 016
m
22 143
54 000

55 313
71 920
m
31 290
24 888
61 437
23 584
56 220
49 883
76 823
26 697
25 909
54 021
m
37 536
36 383
m
m
17 590
108 673
m
66 617
46 714
54 126
30 779
46 587
23 367
38 950
m
45 349
m
22 143
55 992

80 743
a
m
41 282
28 980
49 457
24 157
41 462
40 455
m
33 399
m
50 464
m
m
a
m
m
19 146
m
m
74 911
m
53 748
39 184
63 006
17 449
49 114
m
54 965
m
27 757
90 208

84 312
78 503
m
40 956
37 888
74 628
29 421
62 917
40 455
m
33 399
m
56 885
m
67 167
72 478
m
m
20 670
m
m
74 911
63 537
64 421
41 586
63 006
23 316
50 269
m
60 097
m
27 757
91 888

99 364
87 432
m
41 666
37 888
74 628
29 421
71 567
68 517
m
36 484
m
56 885
m
66 413
72 478
m
m
18 882
131 144
m
92 837
67 435
64 421
42 417
63 006
23 316
50 269
m
60 097
m
27 757
94 775

94 123
104 942
m
45 873
41 110
98 402
29 421
75 819
68 517
m
36 484
m
79 496
m
67 885
72 478
m
m
23 142
131 144
m
92 837
73 319
73 979
42 529
63 006
23 367
51 636
m
62 271
m
27 757
96 262

Flemish Comm. (Belgium)
French Comm. (Belgium)5
England (UK)1
Scotland (UK)6

51 325
49 718
40 553
41 670

51 737
48 856
40 553
41 670

50 090
47 664
45 343
41 670

64 977
60 615
45 343
41 670

73 000
69 593
74 399
64 539

73 019
70 374
74 399
64 539

74 846
74 927
110 442
64 539

89 715
89 599
110 442
64 539

OECD average
EU22 average

37 440
36 883

41 244
41 402

43 546
44 246

46 713
47 466

50 496
48 072

57 141
55 046

64 423
64 257

68 932
68 570

Argentina
Brazil7
China
Colombia
Costa Rica
India
Indonesia
Lithuania8
Russian Federation
Saudi Arabia
South Africa

m
22 003
m
m
m
m
m
21 085
m
m
m

m
22 740
m
m
m
m
m
21 085
m
m
m

m
23 252
m
m
m
m
m
21 085
m
m
m

m
24 116
m
m
m
m
m
21 085
m
m
m

m
m
m
m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m
m
m
m

m

m

m

m

m

m

m

m

Countries

Australia
Austria1
Canada
Chile
Czech Republic
Denmark
Estonia
Finland2
France3
Germany
Greece1
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic1, 4
Slovenia
Spain
Sweden1
Switzerland
Turkey
United States1

Partners

Economies

G20 average

Note: Columns showing average actual teachers’ salaries, broken down by age groups (i.e. Columns 5-28), are available on line. See Annex 2 and Definitions and
Methodology sections for more information. Data available at http://stats.oecd.org/, Education at a Glance Database.
1. At the upper secondary level includes teachers working in vocational programmes.
2. Includes data on the majority, i.e. kindergarten teachers only for pre-primary education.
3. Year of reference 2015.
4. Includes salaries of school heads and teachers.
5. Year of reference 2017.
6. Includes all teachers, irrespective of their age.
7. Year of reference 2014.
8. Includes unqualified teachers.
Source: OECD (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933805420

Education at a Glance 2018: OECD Indicators   © OECD 2018

377

D3

chapter D Teachers, the Learning Environment and the Organisation of Schools
Under embargo until 11/09/2018 at 11.00am CEST
Table D3.10. Minimum/maximum school heads’ statutory salaries,

based on minimum qualifications (2017)

Annual school heads’ salaries, in public institutions, in equivalent USD converted using PPPs for private consumption
(by level of education)
Pre-primary

OECD

Ratio
(max/
min)

Minimum Maximum
salary
salary

Ratio
(max/
min)

Minimum Maximum
salary
salary

Upper secondary,
general programmes

Ratio
(max/
min)

Minimum Maximum
salary
salary

Ratio
(max/
min)

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

66 763
m
m
32 156
18 123
44 506
a
33 426
37 246
m
24 528
22 763
39 171
m
a
a
m
a
18 863
m
24 500
47 857
m
a
21 199
36 438
16 416
41 139
44 742
m
m
26 760
81 588

108 091
m
m
94 205
a
52 136
a
36 100
58 025
m
39 473
49 083
62 899
m
a
a
m
95 211
a
m
72 180
79 670
m
a
25 689
78 735
26 823
62 893
68 029
m
m
33 288
101 812

1.62
m
m
2.93
a
1.17
a
1.08
1.56
m
1.61
2.16
1.61
m
a
a
m
a
a
m
2.95
1.66
m
a
1.21
2.16
1.63
1.53
1.52
m
m
1.24
1.25

66 763
46 025
m
32 156
19 005
55 296
a
47 021
37 246
m
24 528
22 763
43 025
43 315
48 485
72 175
64 958
a
18 863
m
24 500
47 857
49 756
a
21 963
36 438
20 913
42 693
44 742
58 540
m
26 760
83 907

108 091
92 484
m
94 205
a
65 410
a
61 242
58 025
m
39 473
49 083
86 750
99 206
78 408
78 234
71 808
95 211
a
m
72 180
79 670
93 728
a
26 454
78 735
33 436
62 893
68 029
68 871
m
33 288
103 095

1.62
2.01
m
2.93
a
1.18
a
1.30
1.56
m
1.61
2.16
2.02
2.29
1.62
1.08
1.11
a
a
m
2.95
1.66
1.88
a
1.20
2.16
1.60
1.47
1.52
1.18
m
1.24
1.23

75 534
46 025
m
32 156
19 005
55 296
a
48 572
43 400
m
27 190
22 763
43 025
57 519
48 547
72 175
64 958
a
18 863
109 968
55 664
52 697
m
a
24 410
36 438
20 913
42 693
53 493
58 540
m
26 760
89 371

108 091
92 484
m
94 205
a
65 410
a
69 307
74 480
m
42 134
54 343
86 750
112 551
78 623
78 234
71 808
95 031
a
152 083
78 874
128 905
m
a
29 617
78 735
33 436
62 893
80 564
68 871
m
33 288
104 865

1.43
2.01
m
2.93
a
1.18
a
1.43
1.72
m
1.55
2.39
2.02
1.96
1.62
1.08
1.11
a
a
1.38
1.42
2.45
m
a
1.21
2.16
1.60
1.47
1.51
1.18
m
1.24
1.17

75 534
60 684
m
32 986
19 005
68 345
a
55 564
47 626
m
28 077
25 202
59 146
57 519
39 024
72 175
66 563
a
18 863
109 968
49 995
52 697
48 354
a
27 515
36 438
20 913
42 693
53 493
59 980
m
26 760
86 530

108 091
116 155
m
96 604
a
77 764
a
67 385
80 084
m
43 021
54 343
88 780
112 551
95 859
78 234
75 626
94 314
a
152 083
79 169
128 905
93 746
a
33 508
78 735
33 919
73 041
80 564
70 123
m
33 493
114 980

1.43
1.91
m
2.93
a
1.14
a
1.21
1.68
m
1.503
2.16
1.50
1.96
2.46
1.08
1.14
a
a
1.38
1.58
2.45
1.94
a
1.22
2.16
1.62
1.71
1.51
1.17
m
1.25
1.33

Flemish Comm. (Belgium)
French Comm. (Belgium)
England (UK)
Scotland (UK)

47 241
39 934
54 984
55 135

79 710
74 571
135 002
107 619

1.69
1.87
2.46
1.95

47 241
39 934
54 984
55 135

79 710
74 571
135 002
107 619

1.69
1.87
2.46
1.95

48 465
44 907
54 984
55 135

79 710
76 373
135 002
107 619

1.64
1.70
2.46
1.95

58 979
57 091
54 984
55 135

96 245
91 128
135 002
107 619

1.63
1.60
2.46
1.95

OECD average
EU22 average

38 064
35 561

70 056
64 904

m
1.68

43 233
40 794

75 687
71 481

1.73
1.68

48 316
46 066

81 872
81 137

1.68
1.70

50 575
49 225

86 369
85 520

1.69
1.68

Argentina
Brazil
China
Colombia
Costa Rica
India
Indonesia
Lithuania
Russian Federation
Saudi Arabia
South Africa

m
m
m
m
20 621
m
m
15 422
m
m
m

m
m
m
m
62 896
m
m
33 754
m
m
m

m
m
m
m
3.05
m
m
2.19
m
m
m

m
m
m
m
20 137
m
m
19 385
m
m
m

m
m
m
m
36 373
m
m
36 571
m
m
m

m
m
m
m
1.81
m
m
1.89
m
m
m

m
m
m
m
21 174
m
m
19 385
m
m
m

m
m
m
m
72 298
m
m
36 571
m
m
m

m
m
m
m
3.41
m
m
1.89
m
m
m

m
m
m
m
21 174
m
m
19 385
m
m
m

m
m
m
m
72 298
m
m
36 571
m
m
m

m
m
m
m
3.41
m
m
1.89
m
m
m

m

m

m

m

m

m

m

m

m

m

m

m

Countries

Australia
Austria
Canada
Chile
Czech Republic
Denmark
Estonia
Finland1
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan2
Korea
Latvia
Luxembourg3
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United States4, 5
Economies

Partners

D3

Minimum Maximum
salary
salary

Lower secondary,
general programmes

Primary

G20 average

Note: The definition of school heads’ minimum qualifications is based on a broad concept, including the typical ISCED level of attainment and other criteria. Please
see Definitions and Methodology sections for more information. Data available at http://stats.oecd.org/, Education at a Glance Database.
1. Includes data on the majority, i.e. kindergarten school heads only for pre-primary education.
2. Excludes the social security contributions and pension-scheme contributions paid by the employees.
3. Includes the social security contributions and pension-scheme contributions paid by the employers.
4. Actual base salaries.
5. Minimum salary refers to the most prevalent qualification (master’s degree) and maximum salary refers to the highest qualification (education specialist or
doctoral degree).
Source: OECD (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933805439

378 Education at a Glance 2018: OECD Indicators   © OECD 2018

Under embargo until 11/09/2018 at 11.00am CEST

Under embargo until 11/09/2018 at 11.00am CEST

HOW MUCH TIME DO TEACHERS SPEND TEACHING?
• Based on official regulations, public school teachers in OECD countries and economies are required
to teach on average 1 044 hours per year at pre-primary level, 784 hours at primary level, 703 hours
at lower secondary level (general programmes) and 657 hours at upper secondary level (general
programmes).

INDICATOR D4

• In the majority of countries with available data, the amount of statutory teaching time in primary,
lower secondary and upper secondary public institutions remained largely unchanged between
2000 and 2017.

Figure D4.1. Number of teaching hours per year in general lower secondary education
(2000, 2005 and 2017)
Net statutory contact time in public institutions
2017

2005

2000

Costa Rica
Colombia
Chile
Mexico
Latvia
United States1, 2
Scotland (UK)
New Zealand
Australia
Switzerland
Netherlands
Germany
Canada
Ireland
Spain
Israel
OECD average
France
Norway
French Comm. (Belgium)
Hungary
Slovak Republic
Slovenia
Italy
Iceland
Czech Republic
Portugal
Lithuania
Japan3
Greece
Austria
Estonia
Finland
Flemish Comm. (Belgium)
Korea
Turkey
Poland

Hours per year

1 300
1 200
1 100
1 000
900
800
700
600
500
400
300
200
100
0

Note: The OECD average refers to OECD countries and economies with available data for 2005, 2010, 2015 and 2017.
1. Actual teaching time.
2. Year of reference 2016 instead of 2017.
3. Average planned teaching time in each school at the beginning of the school year.
Countries and economies are ranked in descending order of the number of teaching hours per year in general lower secondary education in 2017.
Source: OECD (2018), Table D4.2. See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/
eag-2018-36-en).
1 2 https://doi.org/10.1787/888933805629

Context
Although statutory working hours and teaching hours only partly determine teachers’ actual workload,
they do offer valuable insights into the demands placed on teachers in different countries. Teaching
hours and the extent of non-teaching duties may also affect the attractiveness of the teaching
profession. Together with teachers’ salaries (see Indicator D3) and average class size (see Indicator D2),
this indicator presents some key measures of the working lives of teachers.
The proportion of statutory working time spent teaching provides information on the amount of time
available for non-teaching activities, such as lesson preparation, correction, in-service training and
staff meetings. A larger proportion of statutory working time spent teaching may indicate that a lower
proportion of working time is devoted to tasks such as assessing students and preparing lessons, as
stated in regulations. It also could indicate that teachers have to perform these tasks on their own
time and hence to work more hours than required by statutory working time.

380 Education at a Glance 2018: OECD Indicators   © OECD 2018

Under embargo until 11/09/2018 at 11.00am CEST
In addition to class size and the ratio of students to teaching staff (see Indicator D2), students’
hours of instruction (see Indicator D1) and teachers’ salaries (see Indicator D3), the amount of time
teachers spend teaching also affects the financial resources countries need to allocate to education
(see Indicator C7).
Other findings

• Most countries regulate the number of hours per year that teachers are formally required to work,
including teaching and non-teaching activities. Some of these countries regulate the specific
number of hours required at school, while others set the overall working time, including hours at
school and elsewhere.

INDICATOR D4

• The number of teaching hours per year required of the average OECD public school teacher in
pre-primary, primary and secondary education varies considerably across countries and tends to
decrease as the level of education increases.

• On average across OECD countries and economies, in public institutions pre-primary teachers are
required to teach about 39% more hours than primary school teachers. Statutory requirements
for working time at school and/or total working time also differ between pre-primary and primary
levels, but generally to a lesser extent.

• Required teaching time in public schools varies more across countries at the pre-primary level than
at any other level. The number of teaching hours required in public pre-primary schools averages
1 044 hours per year across OECD countries and economies, ranging from 532 hours per year in
Mexico to 1 755 in Germany.

• Public primary school teachers are required to teach on average 784 hours per year across
OECD countries and economies, but this ranges from less than 590 in Estonia, Lithuania and
Poland to more than 1 050 in Chile and Costa Rica.

• The number of teaching hours required in public lower secondary schools (general programmes)
averages 703 hours per year across OECD countries and economies, ranging from 478 hours in
Poland to over 1 050 hours in Chile, Colombia and Costa Rica.

• Teachers in public upper secondary schools (general programmes) are required to teach on average
657 hours per year across OECD countries and economies, but teaching time ranges from 405 hours
in Denmark to over 1 050 hours in Chile, Colombia and Costa Rica.

• There has been little change in statutory teaching hours between 2000 and 2017 on average across
countries with available data for 2000, 2005, 2010, 2015 and 2017, but in a few countries, teaching
time increased or decreased by 10% or more between 2000 and 2017.

Education at a Glance 2018: OECD Indicators   © OECD 2018

381

chapter D Teachers, the Learning Environment and the Organisation of Schools
Under embargo until 11/09/2018 at 11.00am CEST

Analysis
Teaching time
At pre-primary, primary and secondary levels of education, countries vary considerably in their annual statutory
teaching time, the number of teaching hours per year required of a full-time public school teacher (for variation of
teaching time at the subnational level, see Box D4.1).

D4

Across countries and economies with available data, statutory teaching time in public schools varies more at the
pre-primary level than at any other level. The number of teaching days ranges from 157 per year in the Flemish
Community of Belgium to 225 in Germany, Iceland and Norway. Annual teaching time ranges from 532 hours per
year in Mexico to 1 755 hours in Germany. On average across OECD countries and economies, teachers at this level
of education are required to teach 1 044 hours per year, spread over 41 weeks or 196 days of teaching (Table D4.1
and Figure D4.2).
Primary school teachers are required to teach an average of 784 hours per year in public institutions. In most
countries with available data, daily teaching time ranges from three to six hours a day. There is no set rule on
how teaching time is distributed throughout the year. In Spain, for example, primary school teachers must teach
880 hours per year, nearly 100 hours more than the OECD average. However, these teaching hours are spread over
fewer days of instruction than the OECD average, because primary school teachers in Spain teach an average of
5 hours per day, compared to the OECD average of 4.3 hours (Table D4.1).

Box D4.1. Teaching and working time at the subnational level
Differences are observed across regions in teachers’ statutory teaching and working time among the three
countries (Belgium, Canada and the United Kingdom) reporting subnational data. The number of weeks of
teaching (at pre-primary, primary, lower and upper secondary levels) varies between regions, by one week within
Belgium (from 36 to 37 weeks) and two weeks within Canada (from 36 to 38 weeks). In the United Kingdom,
there are 38 weeks of teaching in the different subnational regions. However these differences mask larger
differences in teaching time of teachers (number of days or hours of teaching) at the subnational level (OECD/
NCES, 2018[1]).
Patterns of variation at the subnational level are different between these countries. In Belgium, the number of
days of teaching varies much more between the French and Flemish Communities than the number of hours of
teaching. At upper secondary level (general programmes), the number of days of teaching is 40% higher in the
French Community than in the Flemish Community (179 days compared to 128 days), whereas the teaching
hours varies by 20% between the two communities (498 hours in the Flemish Community compared to 596 hours
in the French Community). However, these differences are mainly due to the fact that it is not possible to exclude
the number of examination days in the French Community of Belgium, whereas these days are excluded in the
Flemish Community of Belgium. By contrast, the number of teaching days at primary and secondary levels varies
by 6% between the different provinces/territories in Canada (190 days compared to 180 days), but teaching
hours vary much more between subnational regions. The largest number of teaching hours is 29% higher than
the smallest number at primary level (905 hours compared to 700 hours), and the difference exceeds 50% at
lower and upper secondary levels (934 hours compared to 612 hours) (OECD/NCES, 2018[1]).
However, caution is necessary when comparing information at the subnational level, considering potential
differences in the regulations between countries and between subnational regions within countries, and in the
way data are reported for the different subnational regions. For example minimum or typical teaching time
is reported in the subnational regions of Belgium, but maximum or estimated teaching time is reported in
the different subnational regions in Canada (for more information on potential differences in data reported,
see Box D4.2).
Lower secondary school teachers in general programmes in public institutions are required to teach an average of
703 hours per year, ranging from fewer than 600 hours in Finland, the Flemish Community of Belgium, Korea,
Poland and Turkey to more than 1 000 hours in Chile, Colombia, Costa Rica, Latvia and Mexico. However, teachers
in Poland can be obliged to teach as much as 25% of the statutory time as additional overtime, at the discretion of
the school head (at the lower secondary level).

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Figure D4.2. Number of teaching hours per year, by level of education (2017)
Net statutory contact time in public institutions
Hours per year

Lower secondary, general programmes
Upper secondary, general programmes

D4

Costa Rica
Colombia
Chile
Latvia
United States1, 2
Scotland (UK)
Mexico
Australia
New Zealand
Netherlands
Canada
Ireland
Germany
Spain
France
OECD average
Hungary
Switzerland
EU22 average
Italy
Portugal
Israel
Lithuania
French Comm. (Belgium)
Greece
Czech Republic
Austria
Slovenia
Estonia
Slovak Republic
Korea
Finland
Norway
Japan3
Turkey
Flemish Comm. (Belgium)
Iceland
Poland
Denmark

1 800
1 600
1 400
1 200
1 000
800
600
400
200
0

Pre-primary
Primary

1. Actual teaching time.
2. Year of reference 2016.				
3. Average planned teaching time in each school at the beginning of the school year.
Countries and economies are ranked in descending order of the number of teaching hours per year in general upper secondary education.
Source: OECD (2018), Table D4.1. See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933805648

A teacher of general subjects in upper secondary education in public institutions has an average teaching load of
657 hours per year. Teaching time exceeds 800 hours in only seven countries and economies: Chile, Colombia,
Costa Rica, Latvia, Mexico, Scotland (United Kingdom) and the United States. However, in Chile and Scotland
(United Kingdom), the reported hours refer to the maximum time teachers can be required to teach, not to their
typical teaching load (Box D4.2). In contrast, teachers are required to teach fewer than 500 hours per year in
Denmark, the Flemish Community of Belgium, Iceland and Poland. Teachers in Finland, Iceland, Japan, Korea,
Norway, Poland, the Slovak Republic, Slovenia and Turkey teach for three hours or less per day, on average, compared
to six hours or more in Colombia, Costa Rica and Latvia (Table D4.1).
Variations in how teaching time is regulated and/or reported across countries may explain some of the differences
in statutory teaching time between countries (Box D4.2).

Box D4.2. Comparability of statutory teaching time data (2017)
Data on teaching time in this indicator refer to net contact time as stated in the regulations of each country.
The international data collection gathering this information ensures that similar definitions and methodologies
are used in compilation of data in all countries. The impact on the comparability of data of differences in the
way teaching time is reported in regulations is also minimised as much as possible. For example, teaching time
is converted into hours (of 60 minutes) to avoid differences resulting from the varying duration of teaching
periods between countries.
Statutory teaching time in this international comparison excludes preparation time and periods of time
formally allowed for breaks between lessons or groups of lessons. However, at the pre-primary and primary
levels, short breaks (of ten minutes or less) are included in the teaching time if the classroom teacher is
responsible for the class during these breaks (see the Definitions section).

…

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Other activities for teachers, such as professional development days, student examination days and conference
attendance, are also excluded from the teaching time reported in this indicator. However, days devoted to these
activities are not always specified in the regulations, and it may be difficult to estimate and exclude them from
teaching time. At the pre-primary level, about one-quarter of the countries and economies reporting statutory
teaching time could not specify whether these activities were included or excluded from these data. At other
levels of education, most countries can exclude all or most of these activities from teaching time. However,
excluding examination days may be more challenging for countries. At the upper secondary level about 30%
of countries do not exclude them, and in 30% of countries, the information on whether they are excluded or
included is not available. This may result in overestimating teaching time by a few days in these countries.
Moreover, data based on regulations that are reported in this indicator may refer to minimum, typical or
maximum teaching time, which may explain some of the differences between countries. While most data refer
to typical teaching time, about one-quarter of countries report maximum or minimum values for teaching
time.
More detailed information on the reporting practices on teaching time for all participating countries and
economies is available in Annex 3.

Differences in teaching time between levels of education
In most countries, statutory teaching time at the upper secondary level (general programmes) is less than at the
pre-primary level. The exceptions are Chile and Scotland (United Kingdom), where the time teachers are required
to teach is the same at all levels of education, and Colombia, Costa Rica, Korea and Mexico, where upper secondary
school teachers are required to teach more hours than pre-primary school teachers (Table D4.1 and Figure D4.2).
Teaching time requirements vary the most between the pre-primary and primary levels of education. On average,
pre-primary school teachers are required to spend almost 39% more time in the classroom than primary school
teachers. In the Czech Republic, Estonia, Germany, Hungary, Iceland and Slovenia, pre-primary school teachers are
required to teach at least twice the number of hours per year as primary school teachers (Table D4.1).
In the Flemish Community of Belgium, France and Turkey, primary school teachers have at least 30% more annual
teaching time than lower secondary school teachers, while there is no difference in Chile, the Czech Republic,
Hungary, Iceland, Latvia, Scotland (United Kingdom) and Slovenia. The teaching load for primary school teachers is
slightly lighter than for lower secondary school teachers in Costa Rica, Estonia and Lithuania, and much lighter in
Colombia and Mexico (Table D4.1).
Teaching time at lower and upper secondary levels is similar across most countries. However, in Iceland, Mexico and
Norway, annual required teaching time at the lower secondary level is at least 20% more than at the upper secondary
level (Table D4.1).
Differences in teaching time between types of programmes
In most countries, statutory teaching time does not vary between general and vocational programmes. Focusing
on upper secondary level, for which most countries have both general and vocational programmes, teaching time is
similar in both general and vocational programmes in nearly two-thirds of the countries with available information.
However, teaching time is at least 15% higher in vocational than in general programmes in Finland, Latvia, Lithuania
and Switzerland, and at least 40% higher in the Flemish Community of Belgium (for practical courses in vocational
programmes) and Denmark. In both these countries, annual teaching time in general upper secondary programmes
is significantly lower than the OECD average (fewer than 500 hours, compared to 657 hours on average across OECD
countries). Canada and Mexico are the only countries where teaching time is significantly lower (at least 15% lower)
in vocational programmes than in general programmes (Figure D4.3).
Actual teaching time
Statutory teaching time, as reported by most of the countries in this indicator, refers to the time as defined in
regulations. However, teaching time of individual teachers may differ from the regulation, because of overtime, for
example. Actual teaching time is the annual average number of hours that full-time teachers teach a group or a class
of students, including overtime, and it thus provides a full picture of teachers’ actual teaching load.

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Figure D4.3. Number of teaching hours per year in general and vocational programmes
at upper secondary level (2017)
Net statutory contact time in public institutions
Upper secondary, vocational programmes
Upper secondary, general programmes

Hours per year

1 400
1 200

D4

1 000
800
600
400

Denmark

Poland

Iceland

Turkey

Flemish Comm. (Belgium)

Japan1

Norway

Korea

Finland

Slovenia

Slovak Republic

Greece

Czech Republic

French Comm. (Belgium)

Israel

Lithuania

Italy

Portugal

EU22 average

Hungary

Switzerland

OECD average

Spain

France

Germany

Mexico

Canada

Chile

Latvia

Colombia

0

Costa Rica

200

1. Average planned teaching time in each school at the beginning of the school year.
Countries and economies are ranked in descending order of the number of teaching hours per year in general upper secondary education.
Source: OECD (2018), Table D4.1. See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933805667

While only a few countries were able to report both statutory and actual teaching time, these data suggest that
actual teaching time can sometimes differ significantly from statutory requirements. In Latvia, for example,
lower secondary teachers actually teach 46% more than the statutory teaching time. This reflects the low value of
statutory salaries, meaning teachers often perform additional teaching time or other tasks for which they can be
compensated. In Slovenia, lower secondary teachers teach around 7% more hours than the statutory benchmark
time, while in Poland, actual teaching time is up to 14% more than statutory requirements. By contrast, in France
and Lithuania, actual teaching time is about 2% to 5% less than statutory teaching time at the lower secondary level
(Figure D4.5, available on line).
Differences between statutory and actual teaching time can be the result of overtime due to teacher absenteeism
or shortages, or may be explained by the nature of the data, as figures on statutory teaching time refer to official
requirements and agreements, whereas actual teaching time is based on administrative registers, statistical
databases, representative sample surveys or other representative sources.
Trends in teaching time
While there has been little change in average teaching hours over the last 17 years, some countries with available
data (and no break in time series) reported an increase or decrease of 10% or more in teaching time in one or several
levels between 2000 and 2017 (Table D4.2 and Figure D4.1).
At the primary level, teaching time increased by at least 15% (more than 100 hours) between 2000 and 2017 in
Israel, Japan and Latvia (Table D4.2). In Israel, this increase in teaching (and working) time is part of the “New
Horizon” reform that has been gradually implemented since 2008. One of the key measures of this reform was
to lengthen teachers’ working week to accommodate small-group teaching in exchange for more generous
compensation. Teachers’ working time was increased from 30 to 36 hours per week and now includes 5 hours of
small-group teaching in primary schools. To compensate, salaries have been raised substantially (see Indicator D3).
Teaching time for lower secondary school teachers also increased in Israel, by more than 20% (120 hours) during
this period. The increase at the lower secondary level is also significant in Japan, albeit to a lesser extent (about
9% or 53 hours). At the upper secondary level, the largest increase in teaching time also occurred in Israel, where
teachers had to teach at least 16% more hours (86 additional hours) in 2017 than in 2000 (Table D4.2).
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By contrast, net teaching time dropped between 2000 and 2017 in some countries and economies. At the
pre‑primary level, among the few countries and economies with available data for 2000 and 2017, teaching time
decreased by 9% or more (corresponding to 95 hours or more) in Portugal and Scotland (United Kingdom). At other
levels of education, teaching time decreased by 10% or more in Mexico at lower secondary level (by 135 hours), in
the Netherlands at both lower and upper secondary levels (by 117 hours), in Scotland (United Kingdom) at primary
level (by 95 hours) and in Turkey at upper secondary level (by 63 hours). The decrease exceeded 22% in Korea at
the primary level (194 hours). In Scotland (United Kingdom), the decrease in teaching time for primary teachers
was part of the teachers’ agreement, “A Teaching Profession for the 21st Century”, which introduced a 35-hour
working week for all teachers and a phased reduction of maximum teaching time to 22.5 hours per week for primary,
secondary and special-school teachers in 2001. However, even with this decrease of net contact time, the maximum
time teachers at these levels in Scotland (United Kingdom) can be required to teach is longer than the OECD average
teaching time (Table D4.2).
Teachers’ working time
In the majority of countries, teachers’ working time is partly determined by the statutory teaching time specified
in working regulations. In addition, in most countries, teachers are formally required to work a specific number
of hours per year, as stipulated in collective agreements or other contractual arrangements. This may be specified
either as the number of hours teachers must be available at school for teaching and non-teaching activities, or as the
number of total working hours. Both correspond to official working hours as specified in contractual agreements,
and countries differ in how they allocate time for each activity. In Israel, for example, recent reforms take into
account working hours at school beyond teaching time. Regulations now specify the working time required at school,
including teaching and non-teaching time. Following the reform, non-teaching hours at school have been extended,
to allow more time for non-teaching tasks, such as meetings with students or parents, preparation of lessons’ plans
and checking of students’ work.
More than half of OECD countries and economies specify the length of time teachers are required to be available
at school, for both teaching and non-teaching activities, for at least one level of education. In over half of these
countries, the difference between the time upper secondary school teachers and pre-primary school teachers are
required to be available at school is less than 10%. However, in Hungary, Latvia, Sweden and Turkey pre-primary
teachers are required to be available at school at least 30% more hours than upper secondary school teachers
(although statutory total working time is the same for both levels in Hungary, Latvia and Turkey) (Table D4.1).
In some other countries, teachers’ total annual statutory working time (at school and elsewhere) is specified, but the
allocation of time spent at school and time spent elsewhere is not. This is the case in Austria (in primary and lower
secondary education), the Czech Republic, Denmark, England (United Kingdom), Estonia (in primary and secondary
education), France (in lower and upper secondary education), the French Community of Belgium (in pre-primary
and primary education), Germany, Japan, Korea, Lithuania (in primary and secondary education), the Netherlands,
Norway (in pre-primary education), Poland, the Slovak Republic and Switzerland. This may result from the fact that,
in some countries, such as France for example, total annual statutory working time is valid for all civil servants, not
specifically for teachers (Table D4.1).
In Sweden, although the total working time per year is decided through collective agreements, school leaders decide
on the number of working hours per week and (to some extent) on the use of teachers’ time (teaching or non‑teaching
activities).
In addition, workload and teaching load requirements may evolve throughout a teacher’s career. In a number of
countries, some new teachers have a reduced teaching load as part of their induction programmes. Some countries
also encourage older teachers to stay in the teaching profession by diversifying their duties and reducing their teaching
hours. For example, in Portugal, teachers may have a reduced teaching workload, due to their age, years in the profession
or for doing extracurricular activities at school. Iceland reduces working time of upper secondary teachers according
to their age: 30-37 year-old teachers benefit from a 24-hour extra holiday a year and 38-year-old and older teachers
have a 48-hour extra holiday per year. In addition, 55-year-old or older upper secondary teachers receive a reduction of
teaching time (from 58 hours for 55-59 year-olds to 290 hours for 60-year-old and older teachers).
Non-teaching time
Although teaching time is a substantial component of teachers’ workloads, other activities such as assessing
students, preparing lessons, correcting students’ work, in-service training and staff meetings should also be taken
into account when analysing the demands placed on them in different countries (see Box D4.3 for details on these

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tasks at lower secondary level). The amount of time available for these non-teaching activities varies across countries;
a larger proportion of statutory working time spent teaching may indicate that a lower proportion of working time
is devoted to these activities.
Even if teaching is a core activity of teachers, in a large number of countries, most of their working time is spent on
activities other than teaching. In the 24 countries and economies with data for both teaching and total working time
for lower secondary teachers, 44% of teachers’ working time is spent on teaching on average, with the proportion
ranging from 32% or less in Japan, Poland and Turkey to 75% in Colombia. While the proportion of working time spent
teaching increases with the annual number of teaching hours, there are significant variations between countries.
For example, Japan and Portugal have a similar number of teaching hours (610 hours in Japan and 616 hours in
Portugal), but 32% of working time is spent on teaching in Japan, compared to 42% in Portugal. Moreover, in some
countries, teachers devote similar proportions of their working time to teaching, even if the number of teaching
hours differs considerably. For example, in Spain and the United States, lower secondary teachers spend about half
of their working time teaching, but teachers teach 713 hours in Spain, compared to 966 hours in the United States.
Only teachers in Chile, Colombia, Israel, Latvia, Scotland (United Kingdom) and Spain spend at least 50% of their
statutory working time teaching (Figure D4.4).
In some countries, such as Austria (upper secondary level), Costa Rica, the Flemish and French Communities of
Belgium (secondary levels) and Italy, there are no formal requirements for time spent on non-teaching activities.
However, this does not mean that teachers are given total freedom to carry out other tasks. In the Flemish Community
of Belgium, although there are no regulations regarding the time devoted to preparing lessons, correcting tests,
marking students’ papers and other non-teaching tasks, additional non-teaching hours at school are set at the
school level. In Italy, there is a requirement of up to 80 hours of scheduled non-teaching collegial work at school
per year. Of these 80 hours, up to 40 hours of compulsory working time per year are dedicated to meetings of the
teachers’ assembly, staff planning meetings and meetings with parents, with the remaining compulsory 40 hours
dedicated to class councils (Table D4.1).

Figure D4.4. Percentage of lower secondary teachers’ working time spent teaching (2017)
Net teaching time (typical annual number of hours) as a percentage of total statutory working time
in general programmes in public institutions
Percentage of total statutory
working time spent teaching
Country average

80

70

Scotland (UK)

Israel

60

Latvia

Slovak Republic

50

Portugal

Korea
Poland

30

400

Iceland
Austria

Turkey

Japan1

500

600

Chile

Spain
Hungary

Czech Republic
Estonia

40

20

Colombia

France
Norway
Lithuania

700

United States2, 3

Netherlands

Country average

Germany
Switzerland

800

900

1000

1100

1200

1300

Number of teaching hours per year

1. Average planned teaching time in each school at the beginning of the school year.
2. Actual teaching time.
3. Year of reference 2016 instead of 2017.
Source: OECD (2018), Table D4.1. See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933805686

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Box D4.3. Non-teaching tasks required of teachers in lower secondary education (2017)
Non-teaching tasks are a part of teachers’ workload and working conditions. The non-teaching activities
required by legislation, regulations or agreements between stakeholders (e.g. teachers’ unions, local authorities
and school boards) do not necessarily reflect the actual participation of teachers in non-teaching activities, but
they provide an insight into the breadth and complexity of teachers’ roles.

D4

According to regulations, individual planning or preparing lessons, marking/correcting student work, general
administrative communication and paperwork, and communicating and co-operating with parents are the
most common non-teaching tasks required of lower secondary teachers (general programmes) during their
statutory working time at school or statutory total working time (Table D4.3). These tasks are required in
at least 26 of the 37 countries and economies with available data. Teamwork and dialogue with colleagues
and supervising students during breaks are also required in around half of the countries with available data.
In a quarter of countries, lower secondary teachers are required to take on various additional responsibilities,
such as counselling students, teaching more classes or hours than required in the full-time contract, or being
class/form teacher (Table D4.3 and Figure D4.a).

Figure D4.a. Tasks and responsibilities lower secondary teachers are required
to perform (2017)
For lower secondary teachers teaching general programmes in public institutions
Mandatory
Required, at the discretion of individual schools
Mandatory, or required at the discretion of individual schools
Voluntary at the discretion of individual teachers

Mandatory, or voluntary at the discretion of individual teachers
Not required
Not applicable

Tasks
Teaching
Individual planning or preparation of lessons
either at school or elsewhere
Marking/correcting of student work
Communication and co-operation with parents or guardians
General administrative work (including communication, paperwork
and other clerical duties a teacher undertakes)
Team work and dialogue with colleagues at school or elsewhere
Supervision of students during breaks

Other responsibilities
Students counselling (including student supervising,
virtual counselling, career guidance and delinquency prevention)
Class teacher/form teacher
Teaching more classes or hours than required by full-time contract
(e.g. overtime compensation)
Participation in school or other management
in addition to teaching duties
Engaging in extracurricular activities
(e.g. sports and drama clubs, homework clubs, summer school, etc.)
Special tasks (e.g. training student teachers, guidance counselling)
Participation in mentoring programmes and/or supporting
new teachers in induction programmes

0

5

10

15

20

25

30

35

40

Number of countries

Source: OECD (2018), Table D4.3. See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933805705

…

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Teachers do not only perform tasks that are required by regulations; they often perform voluntarily tasks
such as engaging in extracurricular activities, training student teachers, offering guidance counselling and
participating in school or other management activities. In almost half of the countries, individual teachers
decided whether or not to perform these tasks. Responsibilities such as class/form teacher or participating in
school or other management in addition to teaching duties are largely distributed at the school level.

D4

Definitions
Actual teaching time is the annual average number of hours that full-time teachers teach a group or class of
students. It includes all extra hours, such as overtime. Data on these hours can be sourced from administrative
registers, statistical databases, representative sample surveys or other representative sources.
The number of teaching days is the number of teaching weeks multiplied by the number of days per week a teacher
teaches, less the number of days on which the school is closed for holidays.
The number of teaching weeks refers to the number of weeks of instruction excluding holiday weeks.
Statutory teaching time is defined as the scheduled number of 60-minute hours per year that a full-time teacher
teaches a group or class of students, as set by policy, teachers’ contracts of employment or other official documents.
Teaching time can be defined on a weekly or annual basis. Annual teaching time is normally calculated as the number
of teaching days per year multiplied by the number of hours a teacher teaches per day (excluding preparation time).
It is a net contact time for instruction, as it excludes periods of time formally allowed for breaks between lessons or
groups of lessons and the days that the school is closed for holidays. At pre-primary and primary levels, short breaks
between lessons are included if the classroom teacher is responsible for the class during these breaks.
Total statutory working time refers to the number of hours that a full-time teacher is expected to work as set by
policy. It can be defined on a weekly or annual basis. It does not include paid overtime. According to a country’s
formal policy, working time can refer to:
• the time directly associated with teaching and other curricular activities for students, such as assignments and
tests;
• the time directly associated with teaching and other activities related to teaching, such as preparing lessons,
counselling students, correcting assignments and tests, professional development, meetings with parents, staff
meetings and general school tasks.
Working time required at school refers to the time teachers are required to spend working at school, including
teaching and non-teaching time.

Methodology
In interpreting differences in teaching hours among countries, net contact time, as used here, does not necessarily
correspond to the teaching load. Although contact time is a substantial component of teachers’ workloads, preparing
for classes and necessary follow-up, including correcting students’ work, also need to be included when making
comparisons. Other relevant elements, such as the number of subjects taught, the number of students taught and
the number of years a teacher teaches the same students, should also be taken into account.
For more information please see the OECD Handbook for Internationally Comparable Education Statistics 2018 (OECD,
2018[2]) and Annex 3 for country specific notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Lithuania was not an OECD member at the time of preparation of this publication. Accordingly, Lithuania does not
appear in the list of OECD members and is not included in the zone aggregates.

Source
Data are from the 2017 OECD-INES Survey on Teachers and the Curriculum and refer to the school year 2016/17
(statutory information) or school year 2015/16 (actual data).
Note regarding data from Israel
The statistical data for Israel are supplied by and are under the responsibility of the relevant Israeli authorities. The use
of such data by the OECD is without prejudice to the status of the Golan Heights, East Jerusalem and Israeli settlements
in the West Bank under the terms of international law.

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References
OECD (2018), OECD Handbook for Internationally Comparative Education Statistics 2018: Concepts, Standards, Definitions
and Classifications, OECD Publishing, Paris, https://doi.org/10.1787/9789264304444-en.

[2]

OECD/NCES (2018), Education at a Glance Subnational Supplement, OECD/National Center for Education Statistics, Paris [1]
and Washington, DC, https://nces.ed.gov/surveys/annualreports/oecd/index.asp.

D4

Indicator D4 Tables
1 2 https://doi.org/10.1787/888933805553

Table D4.1 Organisation of teachers’ working time (2017)
Table D4.2 Number of teaching hours per year (2000, 2005 to 2017)
Table D4.3 Tasks and responsibilities of teachers, by level of education (2017)
WEB Figure D4.5 Actual and statutory teaching time in general lower secondary education (2016)
Cut-off date for the data: 18 July 2018. Any updates on data can be found on line at http://dx.doi.org/10.1787/eag-data-en. Data can also be found
at http://stats.oecd.org/, Education at a Glance Database.

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Table D4.1. [1/2] Organisation of teachers’ working time (2017)
Number of statutory teaching weeks, teaching days, net teaching hours and teachers’ working time
in public institutions over the school year
Lower secondary,
general programmes

Upper secondary,
general programmes

Upper secondary,
vocational
programmes

Pre-primary

Primary

Lower secondary,
general programmes

Upper secondary,
general programmes

Upper secondary,
vocational
programmes

Pre-primary

Primary

Lower secondary,
general programmes

Upper secondary,
general programmes

Upper secondary,
vocational
programmes

Net teaching time, in hours

Primary

Number of days of teaching

Pre-primary
OECD

Number of weeks of teaching

(1)

(2)

(3)

(5)

(6)

(7)

(8)

(9)

(11)

(12)

(13)

(14)

(15)

(17)

(18)

40
m
m
38
45
a
46
m
36
46
36
43
46
m
37
42
m
36
39
m
42
40
m
45
45
41
44
46
37
47
39
38
36

40
38
37
38
39
a
35
38
36
40
36
38
37
37
37
39
40
38
35
m
42
40
38
38
37
39
39
38
37
a
39
38
36

40
38
37
38
39
a
35
38
36
40
36
38
37
33
36
39
40
38
35
m
42
m
38
38
37
38
39
38
37
a
39
38
36

40
38
37
38
39
a
35
38
36
40
35
38
36
33
36
39
39
38
35
m
36
m
38
38
37
38
39
38
36
a
39
38
36d

m
m
40
38
39
a
40
38
36
40
35
38
36
m
36
39
39
38
44
m
36
m
m
38
37
38
39
38
36
a
39
38
x(5)

198
m
m
178
215
a
220
m
162
225
176
210
225
m
182
189
m
180
190
m
200
200
m
225
217
187
209
219
176
224
190
180
180

195
180
183
178
187
a
172
187
162
193
176
182
180
182
182
174
201
190
170
m
200
200
192
190
179
173
189
190
176
a
190
180
180

195
180
183
178
187
a
172
187
a
193
177
182
180
164
175
174
201
190
170
m
200
m
191
190
177
168
189
190
176
a
190
180
180

195
180
183
178
187
a
172
187
a
193
172
181
175
164
173
174
196
190
170
m
171
m
190
190
175
168
189
190
171
a
190
180
180d

m
m
200
178
187
a
195
187
a
193
172
181
175
m
173
174
196
190
215
m
171
m
m
190
175
168
189
190
171
a
190
180
x(11)

903
m
m
1 064
1 333
a
1 320
m
900
1 755
822
1 344
1 620
m
1 031
945
m
543
1 520
m
532
930
m
a
1 085
935
1 150
1 314
880
m
779
1080
1 011

865
779
798
1 064
617
a
585
673
900
801
660
655
624
910
843
766
742
671
1 020
m
800
930
922
741
564
779
794
627
880
a
817
720
1 004

797
607
745
1 064
617
a
602
589
684
747
609
655
624
722
699
626
610
533
1 020
m
1 047
750
840
663
478
616
652
627
713
a
760
504
966

797
589
746
1 064
589
405
568
547
684
719
594
652
485
722
610
626
511
551
1 020
m
838
750
760
523
473
616
567
570
693
a
646
504
966d

m
m
635
1 064
589
615
a
688
684
726
594
652
508
m
610
626
511
557
1 290
m
684
m
m
523
473
616
605
570
693
a
741
504
x(17)

Flemish Comm. (Belgium)1, 3
French Comm. (Belgium)1
England (UK)
Scotland (UK)2

37
36
38
38

37
36
38
38

37
36
38
38

37
36
38
38

37
36
a
a

157
179
190
190

157
179
190
190

128
179
190
190

128
179
190
190

128
179
a
a

725
775
a
855

739
716
a
855

533
657
a
855

498
596
a
855

699
596
a
a

OECD average
EU22 average

41
41

38
38

38
37

37
37

38
38

196
197

183
180

181
177

180
177

182
180

1044
1093

784
762

703
668

657
635

656
670

Argentina
Brazil
China
Colombia1
Costa Rica1
India
Indonesia
Lithuania1
Russian Federation
Saudi Arabia
South Africa

m
42
m
40
41
m
m
a
m
m
m

m
42
m
40
41
m
m
32
m
m
m

m
42
m
40
41
m
m
34
m
m
m

m
42
m
40
41
m
m
34
m
m
m

m
42
m
40
41
m
m
a
m
m
m

m
200
m
200
198
m
m
a
m
m
m

m
200
m
200
198
m
m
160
m
m
m

m
200
m
200
198
m
m
170
m
m
m

m
200
m
200
198
m
m
168
m
m
m

m
200
m
200
198
m
m
a
m
m
m

m
m
m
800
812
m
m
640
m
m
m

m
m
m
1 000
1 188
m
m
576
m
m
m

m
m
m
1 200
1 267
m
m
612
m
m
m

m
m
m
1 200
1 267
m
m
603
m
m
m

m
m
m
1 200
1 267
m
m
740
m
m
m

G20 average

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

Countries

Australia1
Austria1
Canada1
Chile2
Czech Republic1
Denmark
Estonia1
Finland3
France1
Germany1
Greece2
Hungary3
Iceland
Ireland1
Israel1
Italy1
Japan4
Korea3
Latvia1
Luxembourg1
Mexico1
Netherlands2
New Zealand1
Norway2
Poland1
Portugal2
Slovak Republic1
Slovenia1
Spain1
Sweden1
Switzerland1
Turkey1
United States5, 6

Partners

Economies

Note: See Definitions and Methodology sections for more information. Data on vocational programmes at lower secondary level (i.e. Columns 4, 10, 16, 22 and 28) are
available for consultation on line. Data available at http://stats.oecd.org/, Education at a Glance Database.
1. Typical teaching time (teaching time required from most teachers when no specific circumstances apply to teachers) (in the Flemish Community of Belgium, for
pre‑primary and primary levels).
2. Maximum teaching time.
3. Minimum teaching time (in the Flemish Community of Belgium, for lower and upper secondary levels).
4. Average planned teaching time in each school at the beginning of the school year.
5. Actual teaching time.
6. Year of reference 2016.
Source: OECD (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933805572

Education at a Glance 2018: OECD Indicators   © OECD 2018

391

D4

chapter D Teachers, the Learning Environment and the Organisation of Schools
Under embargo until 11/09/2018 at 11.00am CEST
Table D4.1. [2/2] Organisation of teachers’ working time (2017)
Number of statutory teaching weeks, teaching days, net teaching hours and teachers’ working time
in public institutions over the school year

Primary

Lower secondary,
general programmes

Upper secondary,
general programmes

Upper secondary,
vocational
programmes

Pre-primary

Primary

Lower secondary,
general programmes

Upper secondary,
general programmes

Upper secondary,
vocational
programmes

(19)

(20)

(21)

(23)

(24)

(25)

(26)

(27)

(29)

(30)

1 243
m
m
1 830
a
a
1 610
m
954
a
1 134
1 512
1 760
m
1 067
a
a
a
1 560
m
772
a
m
a
m
1 086
m
a
1 140
1 792
a
1 160
1 441

1 242
a
1 228
1 830
a
a
a
787
954
a
1 134
1 165
1 610
1 073
1 236
a
a
a
1 050
m
800
a
1 536
1 300
m
1 038
m
a
1 140
1 360
a
980
1 443

1 239
a
1 233
1 830
a
a
a
703
a
a
1 176
1 165
1 610
811
1 181
a
a
a
1 050
m
1 167
a
1 243
1 225
m
920
m
a
1 140
1 360
a
836
1 449

1 239
a
1 236
1 830
a
a
a
642
a
a
1 176
1 158
1 440
811
1 166
a
a
a
1 050
m
971
a
950
1 150
m
920
m
a
1 140
1 360
a
836
1 446d

m
a
1 280
1 830
a
a
a
769
a
a
1 176
1 158
1 440
m
1 166
a
a
a
1 320
m
692
a
m
1 150
m
920
m
a
1 140
1 360
a
836
x(23)

a
a
m
1 962
1 800
1 680
1 610
a
1 607
1 782
a
1 664
1 760
a
1 067
a
1 883
1 520
1 760
m
a
1 659
a
1 688
1 808
1 572
1 568
m
1 425
a
2 142
1 592
1 980

a
1 776
a
1 962
1 560
1 680
1 540
a
1 607
1 782
a
1 664
1 760
a
1 236
a
1 883
1 520
1 760
m
a
1 659
a
1 688
1 496
1 488
1 568
m
1 425
1 767
2 142
1 592
2 016

a
1 776
a
1 962
1 560
1 680
1 540
a
1 607
1 782
a
1 664
1 760
a
1 181
a
1 883
1 520
1 760
m
a
1 659
a
1 688
1 480
1 458
1 568
m
1 425
1 767
2 142
1 592
2 032

a
a
a
1 962
1 560
1 680
1 540
a
1 607
1 782
a
1 664
1 800
a
1 166
a
1 883
1 520
1 760
m
a
1 659
a
1 688
1 464
1 458
1 568
m
1 425
1 767
2 142
1 592
2 047d

a
a
1 280
1 962
1 560
1 680
1 540
a
1 607
1 782
a
1 664
1 800
a
1 166
a
1 883
1 520
1 760
m
a
1 659
a
1 688
1 464
1 458
1 568
m
1 425
1 767
2 142
1 592
x(29)

Flemish Comm. (Belgium)1, 3
French Comm. (Belgium)1
England (UK)
Scotland (UK)2

904
a
a
1 045

904
a
a
1 045

a
a
a
1 045

a
a
a
1 045

a
a
a
a

a
962
1 265
1 365

a
962
1 265
1 365

a
a
1 265
1 365

a
a
1 265
1 365

a
a
a
a

OECD average
EU22 average

1 295
1 274

1 184
1 059

1 178
1 041

1 135
1 034

1 160
1 121

1 630
1 568

1 622
1 551

1 645
1 585

1 640
1 571

1 635
1 610

Argentina
Brazil
China
Colombia1
Costa Rica1
India
Indonesia
Lithuania1
Russian Federation
Saudi Arabia
South Africa

m
a
m
1 350
a
m
m
1 452
m
m
m

m
a
m
1 350
a
m
m
a
m
m
m

m
a
m
1 350
a
m
m
a
m
m
m

m
a
m
1 350
a
m
m
a
m
m
m

m
a
m
1 350
a
m
m
a
m
m
m

m
a
m
1 600
a
m
m
1 584
m
m
m

m
a
m
1 600
a
m
m
1 584
m
m
m

m
a
m
1 600
a
m
m
1 584
m
m
m

m
a
m
1 600
a
m
m
1 584
m
m
m

m
a
m
1 600
a
m
m
1 584
m
m
m

m

m

m

m

m

m

m

m

m

m

D4
OECD

Total statutory working time, in hours

Pre-primary

Working time required at school, in hours

Countries

Australia1
Austria1
Canada1
Chile2
Czech Republic1
Denmark
Estonia1
Finland3
France1
Germany1
Greece2
Hungary3
Iceland
Ireland1
Israel1
Italy1
Japan4
Korea3
Latvia1
Luxembourg1
Mexico1
Netherlands2
New Zealand1
Norway2
Poland1
Portugal2
Slovak Republic1
Slovenia1
Spain1
Sweden1
Switzerland1
Turkey1
United States5, 6

Partners

Economies

G20 average

Note: See Definitions and Methodology sections for more information. Data on vocational programmes at lower secondary level (i.e. Columns 4, 10, 16, 22 and 28) are
available for consultation on line. Data available at http://stats.oecd.org/, Education at a Glance Database.
1. Typical teaching time (teaching time required from most teachers when no specific circumstances apply to teachers) (in the Flemish Community of Belgium, for
pre‑primary and primary levels).
2. Maximum teaching time.
3. Minimum teaching time (in the Flemish Community of Belgium, for lower and upper secondary levels).
4. Average planned teaching time in each school at the beginning of the school year.
5. Actual teaching time.
6. Year of reference 2016.
Source: OECD (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933805572

392 Education at a Glance 2018: OECD Indicators   © OECD 2018

How much time do teachers spend teaching? – INDICATOR D4

chapter D

Under embargo until 11/09/2018 at 11.00am CEST
Table D4.2. Number of teaching hours per year (2000, 2005 to 2017)
Net statutory contact time in public institutions, by level of education
Primary

OECD

Lower secondary, general programmes

Upper secondary, general programmes

2000

2005

2010

2015

2017

2000

2005

2010

2015

2017

2000

2005

2010

2015

2017

(15)

(16)

(21)

(26)

(28)

(29)

(30)

(35)

(40)

(42)

(43)

(44)

(49)

(54)

(56)

882
m
m
m
m
640
630
656
924
783
609
583
629
915
731
744
635
865
882
m
800
930
m
713
m
779
m
m
880
m
884
720
m

888
774
m
1 128
813
640
630
677
924
808
604
583
671
915
731
739
578
883
882
774
800
930
m
741
m
765
m
627
880
m
m
720
m

868
779
799
1 105
862
650
630
680
924
805
589
604
624
915
820
770
707
807
882
739
800
930
m
741
586
779
841
627
880
m
m
720
m

866
779
797
1 157
823
784b
619
677
900
799
630b
652
m
915
864
752
742
658
685b
810
800
930
922
741
573
743
832
627
880
a
810
720
1 004

865
779
798
1 064
617
a
585
673
900
801
660
655
624
910
843
766
742
671
1 020
m
800
930
922
741
564
779
794
627
880
a
817
720
m

811
m
m
m
650
640
630
570
648
732
426
555
629
735
579
608
557
570
882
m
1 182
867
m
633
m
634
m
m
713
m
m
504
m

810
607
m
1 128
647
640
630
592
648
758
434
555
671
735
579
605
505
621
882
642
1 047
750
m
656
m
623
m
627
713
m
m
504
m

819
607
740
1 105
647
650
630
595
648
756
415
604
624
735
598
630
602
627
882
634
1 047
750
m
654
497
634
652
627
713
m
m
504
m

806
607
742
1 157
617
784b
619
592
648
750
592b
652
m
735
704
616
610
548
685b
739
1 047
750
840
663
486
605
645
627
713
a
765
504
966

797
607
745
1 064
617
a
602
589
684
747
609
655
624
722
699
626
610
533
1 020
m
1 047
750
840
663
478
616
652
627
713
a
760
504
m

803
m
m
m
621
m
578
527
648
690
429
555
464
735
524
608
478
530
882
m
m
867
m
505
m
577
m
m
693
m
674
567
m

810
589
m
1 128
617
m
578
550
648
714
430
555
560
735
524
605
429
605
882
642
848
750
m
524
m
567
m
570
693
m
m
567
m

803
589
744
1 105
617
377
578
553
648
713
415
604
544
735
521
630
500
616
882
634
843
750
m
523
494
634
624
570
693
m
m
567
m

804
589
743
1 157
589
386
568
550
648
714
600b
648
m
735
587
616
511
551
685b
739
848
750
760
523
481
605
617
570
693
a
656
504
966

797
589
746
1 064
589
405
568
547
684
719
594
652
485
722
610
626
511
551
1 020
m
838
750
760
523
473
616
567
570
693
a
646
504
m

Flemish Comm. (Belgium)
French Comm. (Belgium)
England (UK)2
Scotland (UK)

754
722
m
950

748
722
m
893

748
732
684
855

744
728
942
855

739
716
a
855

m
662
m
893

554b
662
m
893

542
671
703
855

538
668
817
855

533
657
a
855

m
603
m
893

518b
603
m
893

505
610
703
855

502
606
817
855

498
596
a
855

OECD average

770

775

772

793

777

680

680

679

705

695

628

648

642

662

647

Average for OECD
countries with 2000, 2005,
2010, 2015 and 2017 data

777

775

781

767

784

682

673

681

685

696

634

632

640

635

654

Average for EU22 countries
with 2000, 2005, 2010,
2015 and 2017 data

783

780

782

766

791

678

673

676

680

697

660

655

661

657

682

Argentina
Brazil
China
Colombia
Costa Rica
India
Indonesia
Lithuania
Russian Federation2
Saudi Arabia
South Africa

m
m
m
m
m
m
m
m
m
m
m

m
m
m
1 000
m
m
m
m
615
m
m

m
m
m
1 000
m
m
m
m
615
m
m

m
m
m
1 000
1 188
m
m
565
561
m
m

m
m
m
1 000
1 188
m
m
576
m
m
m

m
m
m
m
m
m
m
m
m
m
m

m
m
m
1 200
m
m
m
m
507
m
m

m
m
m
1 200
m
m
m
m
507
m
m

m
m
m
1 200
1 267
m
m
610
483
m
m

m
m
m
1 200
1 267
m
m
612
m
m
m

m
m
m
m
m
m
m
m
m
m
m

m
m
m
1 200
m
m
m
m
507
m
m

m
m
m
1 200
m
m
m
m
507
m
m

m
m
m
1 200
1 267
m
m
610
483
m
m

m
m
m
1 200
1 267
m
m
603
m
m
m

G20 average

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

Countries

Australia
Austria1
Canada
Chile
Czech Republic
Denmark2, 3
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan4
Korea
Latvia
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United States2

Partners

Economies

Note: See Definitions and Methodology sections for more information. Data on years 2000 to 2017 for pre-primary education (i.e. Columns 1-14) are available for
consultation on line. Data on years 2006, 2007, 2008, 2009, 2011, 2012, 2013, 2014 and 2016 for primary education, lower secondary education and upper secondary
education (i.e. Columns 17-20; 22-25; 27; 31-34; 36-39; 41; 45-48; 50-53; 55) are available at http://stats.oecd.org/, Education at a Glance Database or via StatLink below.
1. Figures for the pre-primary level refer to primary teachers (in primary schools only) teaching pre-primary classes.
2. Actual teaching time (in Denmark except for pre-primary level, in England [UK] data for 2015 refer to 2016).
3. Year of reference 2011 instead of 2012 and 2013, and year of reference 2015 instead of 2014 for upper secondary education.
4. Average planned teaching time in each school at the beginning of the school year.
Source: OECD (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933805591

Education at a Glance 2018: OECD Indicators   © OECD 2018

393

D4

chapter D Teachers, the Learning Environment and the Organisation of Schools
Under embargo until 11/09/2018 at 11.00am CEST
Table D4.3. [1/2] Tasks and responsibilities of teachers, by level of education (2017)
Teachers’ tasks and responsibilities in public institutions as defined explicitly in regulations and/or steering documents
Lower secondary, general programmes
Tasks

Teaching

Individual
planning
or preparation
of lessons
either at school
or elsewhere

(1)

(2)

(3)

(4)

(5)

(6)

(7)

Mand.
Mand.
m
Mand.
Mand.
Mand.
Mand.
Mand.
Mand.
Mand.
Mand.
Mand.
Mand.
Mand.
Mand.
Mand.
Mand.
Mand.
Mand.
m
Mand.
School req.
Mand.
Mand.
Mand.
Mand.
Mand.
Mand.
Mand.
Mand.
Mand.
Mand.
Mand.

Mand.
Mand.
m
Mand.
Voluntary
Mand.
Mand.
Mand.
Mand.
Mand.
Mand.
Mand.
Mand.
Mand.
Mand.
Mand.
Mand.
Mand.
Mand.
m
Mand.
School req.
Mand.
Mand.
Mand.
Mand.
Mand.
Mand.
Mand.
Mand.
Mand.
Mand.
School req.

Mand.
Mand.
m
Mand.
Voluntary
Mand.
Mand.
Mand.
Mand.
Mand.
Mand.
Mand.
Mand.
Mand.
Mand.
Mand.
Mand.
Mand.
Mand.
m
Mand.
School req.
Mand.
Mand.
Mand.
Mand.
Mand.
Mand.
Mand.
Mand.
Mand.
Mand.
School req.

Mand.
Mand.
m
School req.
School req.
Mand.
Mand.
Mand.
Mand.
School req.
Mand.
Mand.
School req.
Mand.
Mand.
Mand.
Mand.
Mand.
Mand.
m
School req.
School req.
Mand.
Mand.
Mand.
Mand.
Mand.
Mand.
Mand.
Mand.
Mand.
Not req.
School req.

Mand.
Mand.
m
School req.
Voluntary
Mand.
Mand.
Mand.
Mand.
Mand.
Mand.
Mand.
School req.
Mand.
Mand.
Mand.
Mand.
Mand.
Mand.
m
School req.
School req.
Mand.
Mand.
Mand.
Mand.
Mand.
Mand.
Mand.
Mand.
Mand.
Mand.
School req.

Mand.
Mand.
m
School req.
School req.
School req.
School req.
School req.
Not req.
School req.
Mand.
Mand.
Voluntary
Mand.
Mand.
Mand.
Mand./School req.
Mand.
Mand.
m
Not req.
School req.
School req.
School req.
Mand.
Voluntary
Mand.
School req.
Mand.
School req.
Mand.
Voluntary
School req.

Mand.
Mand.
m
School req.
School req.
Mand.
Mand.
Mand.
Voluntary
Voluntary
Mand.
Mand.
Voluntary
Mand.
Mand.
Mand.
Mand.
Mand.
School req.
m
Voluntary
School req.
Mand.
Mand.
Mand.
Mand.
Mand.
Mand.
Mand.
Mand.
Mand.
Mand.
School req.

Flemish Comm. (Belgium)
French Comm. (Belgium)
England (UK)
Scotland (UK)

Mand.
Mand.
Mand.
Mand.

Mand.
Mand.
Mand.
Mand.

School req.
Mand.
Mand.
Mand.

School req.
Mand.
Voluntary
Voluntary

School req.
Mand.
Mand.
Mand.

School req.
Voluntary
Voluntary
Voluntary

School req.
Voluntary
Mand.
Mand./School req.

Argentina
Brazil
China
Colombia
Costa Rica
India
Indonesia
Lithuania
Russian Federation
Saudi Arabia
South Africa

m
Mand.
m
Mand.
Mand.
m
m
Mand.
m
m
m

m
Mand.
m
Mand.
Mand.
m
m
Mand.
m
m
m

m
m
m
Mand.
Mand.
m
m
Mand.
m
m
m

m
m
m
Mand.
Voluntary
m
m
Mand.
m
m
m

m
Mand.
m
Mand.
Mand.
m
m
Mand.
m
m
m

m
m
m
Mand.
Mand.
m
m
School req.
m
m
m

m
m
m
Mand.
Mand.
m
m
School req.
m
m
m

D4
OECD

General
administrative
work (including
communication,
Communication
paperwork and
and co-operation
other clerical
Marking/
with parents
duties undertaken
correcting
or guardians
of student work as part of the job)

Supervision
of students
during breaks

Team work
and dialogue
with colleagues
at school
or elsewhere

Countries

Australia
Austria
Canada
Chile
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Luxembourg
Mexico
Netherlands
New Zealand1
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United States

Partners

Economies

Are tasks/responsibilities required of teachers?
Mand.
= Yes, mandatory		
School req. = Yes, at the discretion of individual schools		
Voluntary = No, voluntary at the discretion of individual teachers		
Not req. = No, not required
Note: Pre-primary, primary, lower secondary (vocational programmes) and upper secondary levels (added in separate rows) are available for consultation on line
(see StatLink below). See Definitions and Methodology sections for more information.
1. Citeria for the first two years of lower secondary education (general programmes) follow those for primary education and those for the last two years of lower secondary
education (general programmes) follow those of upper secondary education (general programmes).
Source: OECD (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933805610

394 Education at a Glance 2018: OECD Indicators   © OECD 2018

How much time do teachers spend teaching? – INDICATOR D4

chapter D

Under embargo until 11/09/2018 at 11.00am CEST
Table D4.3. [2/2] Tasks and responsibilities of teachers, by level of education (2017)
Teachers’ tasks and responsibilities in public institutions as defined explicitly in regulations and/or steering documents
Lower secondary, general programmes
Other responsibilities

OECD

Students
Participation in
counselling
school or other
Engaging in
(including
management
extracurricular
student
in addition to Teaching more
Special tasks
activities
teaching duties classes or hours supervising,
(e.g. homework (e.g. training
virtual
than required
(e.g. serving
student
clubs, sports
counselling,
by full-time
as head of
teachers,
and drama
career guidance,
contract
department or
guidance
Class teacher/
clubs,
co-ordinator of (e.g. overtime and delinquency
summer school) counselling) form teacher
prevention)
compensation)
teachers)

Participation
in mentoring
programmes
and/or
supporting Participation
new teachers in professional
in induction development
activities
programmes

(8)

(9)

(10)

(11)

(12)

(13)

(14)

(15)

School req.
School req.
m
Voluntary
Voluntary
School req.
School req.
Voluntary
Voluntary
Voluntary
Not req.
Voluntary
Voluntary
School req.
Voluntary
School req.

Not req.
Mand.
m
School req.
School req.
School req.
Voluntary
Voluntary
Mand/Vol.
Voluntary
Voluntary
Voluntary
Not req.
Voluntary
Voluntary
Voluntary

Voluntary
School req.
m
School req.
Voluntary
School req.
Mand.
Mand.
Mand.
Voluntary
Mand.
Mand.
Voluntary
Not req.
School req.
Voluntary

Voluntary
Voluntary
m
Voluntary
Voluntary
School req.
School req.
Voluntary
Voluntary
Voluntary
Voluntary
Mand.
Voluntary
Voluntary
Not req.
Voluntary

School req.
Voluntary
m
Voluntary
Voluntary
School req.
School req.
Voluntary
Voluntary
Voluntary
Voluntary
Not req.
Voluntary
Voluntary
Voluntary
Voluntary

Voluntary
Voluntary
m
Voluntary
School req.
School req.
Voluntary
Voluntary
Voluntary
Voluntary
Mand.
Voluntary
Voluntary
Voluntary
Voluntary
Voluntary

School req.
Mand.
m
Mand.
Mand.
School req.
Mand.
Mand.
Mand/Vol.
School req.
Mand.
Mand.
Mand.
Mand.
Voluntary
Mand.

School req.

Mand.

School req.
School req.
m
School req.
School req.
School req.
Voluntary
Voluntary
School req.
Voluntary
Mand.
School req.
a
Voluntary
School req.
School req.

Mand.
Mand.
m
Mand.
School req.
School req.
Voluntary
Mand.
Voluntary
Voluntary
Mand.
Voluntary
School req.
Mand.
Voluntary
School req.

Countries

Australia
Austria
Canada
Chile
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy

Mand.

Mand./School req.

School req.

School req.
Mand.
m
School req.
School req.
School req.
School req.
School req.
Mand.
Voluntary
School req.
Mand.
Voluntary
Voluntary
Mand.
School req.

Voluntary
School req.
m
Not req.
School req.
School req.
School req.
Voluntary
Mand.
School req.
Mand.
Not req.
Voluntary
Not req.
Voluntary
School req.

Mand.
Mand.
m
Not req.
School req.
Mand./School req.
School req.
Not req.
Mand.
Voluntary
Mand.
Mand.
School req.
Mand.
Not req.
School req.

School req.
School req.
m
Not req.
School req.
Voluntary
Not req.
Voluntary
Mand.
Voluntary
Mand.
Voluntary
Voluntary
Not req.
Voluntary
School req.

School req.
School req.
m
School req.
School req.
School req.
Voluntary
Voluntary
School req.
Voluntary
Mand.
Voluntary
Voluntary
Voluntary
School req.
School req.

School req.
School req.
m
School req.
School req.
School req.
School req.
Voluntary
Voluntary
Voluntary
Mand.
Not req.
School req.
School req.
School req.
Not req.
Mand./School
req.
School req.
School req.
m
Not req.
School req.
School req.
School req.
School req.
Mand.
Mand.
a
Not req.
School req.
Voluntary
School req.
School req.

Flemish Comm. (Belgium)
French Comm. (Belgium)
England (UK)
Scotland (UK)

Voluntary
Voluntary
School req.
a

Voluntary
Voluntary
School req.
Voluntary

Not req.
Voluntary
School req.
Mand.

Voluntary
Voluntary
School req.
Voluntary

Voluntary
Voluntary
School req.
School req.

Voluntary
Voluntary
School req.
School req.

Voluntary
School req.
School req.
Mand.

Mand.
Mand.
School req.
Mand.

Argentina
Brazil
China
Colombia
Costa Rica
India
Indonesia
Lithuania
Russian Federation
Saudi Arabia
South Africa

m
m
m
Mand.
School req.
m
m
School req.
m
m
m

m
m
m
Not req.
Voluntary
m
m
School req.
m
m
m

m
m
m
Mand.
Mand.
m
m
School req.
m
m
m

m
m
m
Not req.
Voluntary
m
m
Voluntary
m
m
m

m
m
m
Not req.
Mand.
m
m
Voluntary
m
m
m

m
m
m
Not req.
Mand.
m
m
School req.
m
m
m

m
m
m
Not req.
Mand.
m
m
Voluntary
m
m
m

m
Mand.
m
School req.
School req.
m
m
Mand.
m
m
m

Japan
Korea
Latvia
Luxembourg
Mexico
Netherlands
New Zealand1
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United States

Mand./School req. Mand./School req.

Partners

Economies

Are tasks/responsibilities required of teachers?
Mand.
= Yes, mandatory		
School req. = Yes, at the discretion of individual schools		
Voluntary = No, voluntary at the discretion of individual teachers		
Not req. = No, not required
Note: Pre-primary, primary, lower secondary (vocational programmes) and upper secondary levels (added in separate rows) are available for consultation on line
(see StatLink below). See Definitions and Methodology sections for more information.
1. Citeria for the first two years of lower secondary education (general programmes) follow those for primary education and those for the last two years of lower secondary
education (general programmes) follow those of upper secondary education (general programmes).
Source: OECD (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933805610

Education at a Glance 2018: OECD Indicators   © OECD 2018

395

D4

Under embargo until 11/09/2018 at 11.00am CEST

WHO ARE THE TEACHERS?
• Women constitute almost all of the teaching workforce at the pre-primary level, while they represent
less than half of it at the tertiary level. Over the past decade, there has been a gradual increase in
this gender gap from primary level to upper secondary level, but a decrease at the tertiary level.

• On average across OECD countries, the share of teachers over 50 years old at primary and secondary

INDICATOR D5

levels combined has increased by 3 percentage points over the decade. However, teachers are getting
younger in a third of OECD countries.

• In most countries, teachers above 50 years old constitute a large share of the teaching force. Among
men, the share of younger teachers (below 30) at the upper secondary level is below 15% in most
OECD countries with available data.

Figure D5.1. Gender distribution of teachers (2016)
Percentage of women among teaching staff in public and private institutions, by level of education
All tertiary

Pre-primary

Primary

All secondary

Russian Federation1
Lithuania
Latvia
Finland
United States2
Estonia1
Canada
New Zealand
Belgium
Norway
Slovak Republic
Netherlands
Brazil
United Kingdom
Poland
Sweden
Portugal
France3
Ireland
Costa Rica
EU22 average
Turkey
Hungary
OECD average
Indonesia
Spain
Austria
Slovenia
Saudi Arabia
India
Germany
Czech Republic
Colombia
Italy
Luxembourg
Korea
Switzerland
Greece
Japan

%

100
90
80
70
60
50
40
30
20
10
0

1. Pre-primary includes early childhood education.
2. All tertiary includes post-secondary non-tertiary education.
3. Public and government-dependent private institutions only for all levels except for tertiary. For tertiary education, public
institutions only.
Countries are ranked in descending order of the share of female teachers in tertiary education.
Source: OECD / UIS / Eurostat (2018), Table D5.2 and Education at a Glance Database, http://stats.oecd.org/. See Source section for
more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933805800

Context
The demand for teachers depends on a range of factors, including average class size, required instruction
time for students, use of teaching assistants and other non-classroom staff in schools, enrolment rates
at the different levels of education, and starting and ending age for compulsory education. With large
proportions of teachers in several OECD countries set to reach retirement age in the next decade,
and/‑or the projected increase in the size of the school-age population, governments will be under
pressure to recruit and train new teachers. Given compelling evidence that the calibre of teachers is
the most significant in-school determinant of student achievement, concerted efforts must be made
to attract top talent to the teaching profession and provide high-quality training (OECD, 2015[1])
(Stigler and Hiebert, 1999[2]).
Teacher-retention policies need to promote work environments that encourage effective teachers to
continue teaching. In addition, as teaching at the pre-primary, primary and lower secondary levels
remains largely dominated by women, the gender imbalance in the teaching profession and its impact
on student learning warrant detailed study (OECD, 2017[3]).

396 Education at a Glance 2018: OECD Indicators   © OECD 2018

Under embargo until 11/09/2018 at 11.00am CEST
Other findings

• On average across OECD countries, 12% of primary teachers are under the age of 30.
The United Kingdom has the largest proportion of primary teachers (31%) under the age of 30 of
all countries with available data. By contrast, in Italy and Portugal, only 1% of primary teachers
are in that age group.

• At the primary level, the median of the average ages of teachers across OECD countries is about the
same for men and women (44 years old). Men tend to be slightly older in higher levels of education
(starting from lower secondary). The difference is the largest in tertiary education where the
median of the average ages across countries is 48 for male teachers and 46 for female teachers.

INDICATOR D5

Education at a Glance 2018: OECD Indicators   © OECD 2018

397

chapter D Teachers, the Learning Environment and the Organisation of Schools
Under embargo until 11/09/2018 at 11.00am CEST

Analysis

D5

Teachers’ age distribution
Teachers’ age distribution varies considerably across countries and can be affected by a variety of factors, such as the
size and age distribution of the population and the duration of tertiary education, as well as by teachers’ salaries and
working conditions. Declining birth rates, for example, may drive down the demand for new teachers, and longer
tertiary education can delay the entrance of teachers into the labour market. Competitive salaries, good working
conditions and career development opportunities may attract young people to teaching in some countries and, in
others, may help to retain effective teachers.
On average across the OECD, more than half of primary, lower secondary and upper secondary teachers are between
the ages of 30 and 49.
Young teachers (below the age of 30) – make up only a small proportion of the teaching population: 12% in primary
education, 10% in lower secondary and 8% in upper secondary, on average across the OECD. This pattern is
particularly striking at the upper secondary level: in nearly two-thirds of the countries with available data, teachers
below age 30 make up less than 10% of the teaching population. They account for less than 5% of teachers in
the Czech Republic, Finland, Greece, Hungary, Italy, Lithuania, Portugal, Slovenia and Spain (Table D5.1).
In contrast, a high share of teachers are 50 or older. This share increases with education levels, from 31% in primary
education to 35% in lower secondary and 38% in upper secondary education. This pattern is again quite striking at
the upper secondary level, where older teachers account for more than 30% of all teachers in 28 out of 35 countries
with available data. There is, however, a high level of cross-country variation, with figures ranging from 12% in
Turkey to 63% in Italy for upper secondary education.
Across OECD countries with available data, the average age of teachers tends to be slightly greater in higher
education levels compared to lower ones for both men and women. In half of the countries with available data,
female secondary teachers are, on average, over age 45 and male secondary teachers are over age 46. In comparison,
at the pre-primary level, female teachers are under age 42 and male teachers are under age 39 in half of the countries
with available data. However, this last result should be interpreted with caution as, on average across the OECD,
men make up only 3% of the teaching workforce at the pre-primary level.

Figure D5.2. Distribution of the average ages of teachers, by gender and education level (2016)
Median, minimum and maximum of the average ages of teachers
Maximum
Median
Minimum
Age

55

Pre-primary

Primary

All secondary

All tertiary

50
45
40
35
30
25

Women

Men

Women

Men

Women

Men

Women

Men

Source: OECD / UIS / Eurostat (2018), Education at a Glance Database, http://stats.oecd.org/. See Source section for more information and Annex 3
for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933805819

Overall, the distribution of the average ages of female teachers only varies slightly between primary and tertiary
education levels. The difference in teachers’ average age across education levels is greater among men than women.
Among countries with available data, the median average age of male teachers at the primary level is four years
less than the median average age of male teachers at the tertiary level. For female teachers, this difference drops
to only one year. These results mask stronger variations across countries. For example, in Canada, the difference

398 Education at a Glance 2018: OECD Indicators   © OECD 2018

Who are the teachers? – INDICATOR D5

chapter D

Under embargo until 11/09/2018 at 11.00am CEST
between the average age of primary teachers and the average age of tertiary teachers is the same for men and women
(4 years). In contrast, larger differences between the average age of primary and tertiary teachers are observed
for men and women in countries such as Korea and the United Kingdom: primary female teachers in Korea and
the United Kingdom are respectively 6 and 8 years younger than their peers teaching at tertiary level. Among men,
this difference rises to 13 years in Korea and 12 years in the United Kingdom (Figure D5.2).
The ageing of the teaching force has a number of implications for education systems across countries. In addition
to prompting recruitment and training efforts to replace retiring teachers, it may also affect budgetary decisions.
In most school systems, teachers’ salaries increase with years of teaching experience. Thus, the ageing of teachers
increases school costs, which can in turn limit the resources available for other initiatives (see Indicator D3).
Trends in teachers’ ages between 2005 and 2016
On average across OECD countries with available data for both years, the share of teachers age 50 and older has
increased by 3 percentage points over the decade, for primary to upper secondary education combined. Hungary,
Lithuania, Poland, Portugal and Slovenia saw an increase of over 10 percentage points (Education at a Glance
Database), although in Poland the share of teachers of age 50 and older remains lower than the OECD average.
Around one-third of the countries with available data (Chile, France, Germany, Ireland, Luxembourg, the United Kingdom
and the United States) exhibit a negative change in the percentage of teachers of age 50 or older, which indicates
that the teaching population is getting younger. This may be explained, in part, by efforts to implement teacher
recruitment policies. For instance, the United Kingdom, which has seen the largest decrease in the share of older
teachers, launched an ambitious recruitment campaign in the early 2000s.
In countries where the school-age population has increased over this period (see Indicator B1), new teachers will
be needed to replace the staff who will reach retirement over the next decade. Governments may have to develop
teacher-training programmes and increase incentives for students to join the teaching profession (see Indicator D6
in [OECD, 2014[4]]). In addition, fiscal constraints (particularly driven by pension obligations and healthcare costs
for retirees) may put pressure on governments to reduce academic offerings, increase class size or integrate more
self‑paced online learning (Peterson, 2011[5]).
Gender profile of teachers
On average across OECD countries, more than two-thirds of teachers are women, in all levels of education combined.
The highest proportions of female teachers, however, are concentrated in the earlier years of schooling, and the
share shrinks at each successive level of education. Indeed, while women represent 97% of the teaching staff in
pre‑primary education on average across OECD countries, they represent 43% at the tertiary level (Table D5.2).
At the pre-primary level, women make up at least 90% of the teaching population in all countries with available data,
except France (89%) and the Netherlands (88%). In primary education, the share of female teachers averages 83% in
OECD countries, and it is above 60% in all OECD and partner countries except India (51%), Saudi Arabia (53%) and
Turkey (59%).
In lower and upper secondary education, although female teachers continue to dominate, the proportion of male
teachers is larger than at earlier levels. In lower secondary education, 69% of teachers on average across OECD countries
are women. In fact, they represent at least 50% of the teaching staff at this level in all countries with available data
except India (45%), Indonesia (49%) and Japan (42%).
At the upper secondary level, the share of female teachers’ drops to 59% on average across OECD countries though
this can vary from 30% in Japan to 80% in Latvia. It also varies considerably between programmes. On average
across OECD countries, women represent 62% of teachers in general programmes and 56% of teachers in vocational
programmes. In some countries such as Estonia, Finland and Hungary, the share of female teachers in general
programmes is 15 percentage points higher than in vocational programmes, even though women still make up the
majority of vocational teachers in these countries.
At the tertiary level, the gender profile of teachers is reversed, with men making up the majority across OECD countries
and female teachers representing 43% of the teaching staff on average. In fact, among countries with available data,
only Finland, Latvia, Lithuania and the Russian Federation have more than 50% of female teachers in tertiary
education. The smallest share of female tertiary teachers in the OECD is found in Japan (27%). Among partner
countries, the smallest share of tertiary teachers is in Colombia (37%).
Education at a Glance 2018: OECD Indicators   © OECD 2018

399

D5

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Under embargo until 11/09/2018 at 11.00am CEST

D5

Why do so few men decide to teach at the lower levels of education? One explanation may be cultural: social perceptions
of links between gender and vocations may influence men and women’s career choices. This gender bias often arises
very early, at home, when parents have aspirations for their children’s professions based on gender stereotypes
(Croft et al., 2014[6]) (Kane and Mertz, 2012[7]) (OECD, 2015[1]). Even among teaching positions themselves, there
are gender imbalances across the different fields of education. At the lower secondary level, women make up a lower
share of teachers in science, mathematics and technology than in the overall teaching population (OECD, 2014[8])
(OECD, 2017[3]). This also may result from the social perception of science as being a masculine domain, which may
discourage women from pursuing tertiary studies in that field (OECD, 2014[8]).
From an economic point of view, the choice of future jobs is also influenced by young people’s expectations for
future earning potential. In every country with available data, male teachers earn less than their male tertiaryeducated counterparts in other professions, while female teachers in primary and lower secondary education earn
virtually the same as women with a tertiary degree in other fields (see Indicator D3 and [OECD, 2017[3]]). These
differences in relative salaries for men and women are likely to make the teaching profession more appealing to
women, especially at the lower levels of education.
The potential impact of this gender imbalance in the teaching profession on student achievement, student
motivation and teacher retention is worthy of study, especially in countries where few men are attracted to the
profession (Drudy, 2008[9]) (OECD, 2005[10]) (OECD, 2009[11]). While there is little evidence that a teacher’s gender
has an impact on student performance (e.g. [Antecol, Eren and Ozbeklik, 2012[12]] [Holmlund and Sund, 2008[13]]),
aiming for better balance across genders can nevertheless have positive effects on all students. In particular, there
is evidence that female teachers’ attitudes towards some school subjects, such as mathematics, can influence their
female students’ achievement (Beilock et al., 2010[14]) (OECD, 2014[15]). Furthermore, male teachers can serve as
role models and contribute to students developing positive gender identities, particularly for those students who do
not have many positive male role models in their lives.
The gender distribution of school leadership staff does not reflect the gender mix among teachers (OECD, 2014[15]).
While the proportion of male teachers in primary schools is relatively small in many countries, there is an
over‑representation of male principals. This suggests that male teachers tend to be promoted to principal positions
more often than female teachers, although most of them are recruited from the ranks of teachers who are mostly
women (see Indicator D6 in [OECD, 2016[16]]).
Share of male and female teachers by age group and level of education
The higher proportion of women among young teachers, together with the predominance of female tertiary
graduates in the field of education (see Education at a Glance Database), may raise concerns about future gender
imbalances at the primary to upper secondary levels, where women already dominate the profession.
Gender and age imbalances in the teaching profession can be analysed through at least two lenses: the age distribution
among both female and male teachers, and the gender distribution of teachers in each age group. In most countries,
the share of women is higher among young teachers (below age 30) than among older teachers (age 50 or older).
At the primary level, the difference between the two age groups is rather small, with 84% of women in the younger
group, compared to 82% in the older group, on average across OECD countries (Table D5.3). At lower secondary
level, the difference is also small on average: women make up 70% of teachers under the age of 30, and 66% of those
of age 50 or older. The difference grows larger at the upper secondary level: on average across OECD countries,
62% of teachers under age 30 are women, compared to 56% in the older group.
However, at the tertiary level, where female teachers are a minority on average, the higher share of women among
the younger generation of teachers suggests an increase in gender parity. On average across OECD countries, the
share of female tertiary teachers is closer to 50% (i.e. an equal gender distribution) among the younger group, with
52% of female teachers under age 30, and 38% age 50 or older.
These indicators are consistent with the gender distribution dynamics observed over the decade, which point to
a gradual increase in the gender gap in the teaching profession at the primary and secondary level, but a decrease
at the tertiary level. On average, for all OECD countries with data for both years, the rise in the share of female
teachers between 2005 and 2016 has widened the gender gap by 3 percentage points for the primary and secondary
levels combined, while it has narrowed the gap by 4 percentage points at the tertiary level. At the primary and
secondary levels combined, this difference reaches over 5 percentage points in countries such as the Czech Republic,
Germany, Greece, Ireland and Korea. At the tertiary level, the gender gap has decreased considerably in many
countries, with a change of at least 7 percentage points in Belgium, Germany, Japan, the Netherlands and Slovenia.

400 Education at a Glance 2018: OECD Indicators   © OECD 2018

Who are the teachers? – INDICATOR D5

chapter D

Under embargo until 11/09/2018 at 11.00am CEST
The gender gap at tertiary level has widened by 8 percentage points in the Russian Federation, where women
represent almost 60% of tertiary teachers in 2016.
These persistent gender imbalances in the teaching profession have raised a number of concerns, and countries
such as the United Kingdom have implemented policies encouraging the recruitment and retention of a diverse and
inclusive teacher workforce, including in terms of gender (OECD, 2017[3]) (OECD, 2014[8]).
These findings suggest that it is more likely to have male teachers of older age groups with increasing levels of
education. In most countries with available data, teachers over age 50 represent a large share of the male teaching
force at secondary level. The share of younger teachers (under age 30) is below 15% in almost all of OECD countries
with available data, except in Chile (19%) and Turkey (20%). Even in countries where men represent most of the
teaching workforce, as in Japan and Switzerland, they are more likely to belong to older age groups. In fact, in
some countries, the majority of male teachers in upper secondary education are above age 50. In Italy, 63% of male
teachers in upper secondary are above age 50, the largest share across OECD and partner countries.

Figure D5.3. Age distribution of male teachers in secondary education (2016)
< 30 years
50-59 years

%

30-39 years
>60 years

40-49 years

100
90
80
70
60
50
40
30
20

Greece

Portugal2

Italy

Spain

Finland

Germany

Hungary

Switzerland

Israel4

Austria

Poland

Czech Republic

Sweden

Colombia

Slovenia

Lithuania

EU22 average

Slovak Republic

Korea

France

Costa Rica

OECD average

Luxembourg3

Netherlands

New Zealand

Estonia2

Norway

Japan

Latvia

Belgium

United States

Ireland1

Chile

Brazil

Turkey

0

United Kingdom

10

1. Public institutions only.
2. Upper secondary includes programmes from post-secondary non-tertiary education.
3. Upper secondary includes short-cycle tertiary.
4. Private institutions are not included for upper secondary education.
Countries are ranked in descending order of the share of male secondary teachers below the age of 30.
Source: OECD / UIS / Eurostat (2018), Education at a Glance Database, http://stats.oecd.org/. See Source section for more information and Annex 3
for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933805838

Definitions
Instructional personnel (teachers) include two categories:

• Teachers’ aides and teaching/research assistants include non-professional personnel or students who support
teachers in providing instruction to students.

• Teaching staff refers to professional personnel directly involved in teaching to students. The classification
includes classroom teachers, special-education teachers and other teachers who work with a whole class of
students in a classroom, in small groups in a resource room, or in one-to-one teaching situations inside or outside
a regular class. At the tertiary level, academic staff include personnel whose primary assignment is instruction or
research. Teaching staff also include department chairpersons whose duties include some teaching, but exclude
non-professional personnel who support teachers in providing instruction to students, such as teachers’ aides
and other paraprofessional personnel.
Education at a Glance 2018: OECD Indicators   © OECD 2018

401

D5

chapter D Teachers, the Learning Environment and the Organisation of Schools
Under embargo until 11/09/2018 at 11.00am CEST

Methodology
For more information, please see the OECD Handbook for Internationally Comparative Education Statistics 2018:
Concepts, Standards, Definitions and Classifications (OECD, 2018[17]) and Annex 3 for country-specific notes (http://
dx.doi.org/10.1787/eag-2018-36-en).
Lithuania was not an OECD member at the time of preparation of this publication. Accordingly, Lithuania does not
appear in the list of OECD members and is not included in the zone aggregates.

D5

Source
Data refer to the academic year 2015/16 and are based on the UNESCO-UIS/OECD/EUROSTAT data collection on
education statistics administered by the OECD in 2017 (for details, see Annex 3 at http://dx.doi.org/10.1787/eag2018-36-en).
Note regarding data from Israel
The statistical data for Israel are supplied by and are under the responsibility of the relevant Israeli authorities. The use
of such data by the OECD is without prejudice to the status of the Golan Heights, East Jerusalem and Israeli settlements
in the West Bank under the terms of international law.

References
Antecol, H., O. Eren and S. Ozbeklik (2012), “The Effect of teacher gender on student achievement in primary school: [12]
Evidence from a randomized experiment”, IZA Discusssion Papers, No.6453, http://ftp.iza.org/dp6453.pdf (accessed on
20 April 2018).
Beilock, S. et al. (2010), “Female teachers’ math anxiety affects girls’ math achievement.”, Proceedings of the National [14]
Academy of Sciences of the United States of America, Vol. 107/5, pp. 1860-3, http://dx.doi.org/10.1073/pnas.0910967107.
Croft, A. et al. (2014), “The second shift reflected in the second generation”, Psychological Science, Vol. 25/7, pp. 1418‑1428, [6]
http://dx.doi.org/10.1177/0956797614533968.
Drudy, S. (2008), “Gender balance/gender bias: the teaching profession and the impact of feminisation”, Gender and [9]
Education, Vol. 20/4, pp. 309-323, http://dx.doi.org/10.1080/09540250802190156.
Holmlund, H. and K. Sund (2008), “Is the gender gap in school performance affected by the sex of the teacher?”, Labour [13]
Economics, Vol. 15/1, pp. 37-53, https://doi.org/10.1016/j.labeco.2006.12.002.
Kane, J. and J. Mertz (2012), “Debunking myths about gender and mathematics performance”, Notices of the AMS, [7]
Vol. 59/1, http://dx.doi.org/10.1090/noti790.
OECD (2018), OECD Handbook for Internationally Comparative Education Statistics 2018: Concepts, Standards, Definitions [17]
and Classifications, OECD Publishing, Paris, https://doi.org/10.1787/9789264304444-en.
OECD (2017), “Gender imbalances in the teaching profession”, Education Indicators in Focus, No. 49, OECD Publishing, [3]
Paris, http://dx.doi.org/10.1787/54f0ef95-en.
OECD (2016), Education at a Glance 2016 : OECD Indicators, OECD Publishing, Paris, http://dx.doi.org/10.1787/eag-2016-en [16]
(accessed on 12 January 2018).
OECD (2015), “What lies behind gender inequality in education?”, PISA in Focus, No. 49, OECD Publishing, Paris, http:// [1]
dx.doi.org/10.1787/5js4xffhhc30-en.
OECD (2014), Education at a Glance 2014 : OECD Indicators, OECD Publishing, Paris, http://dx.doi.org/10.1787/eag-2014-en. [4]
OECD (2014), PISA 2012 Results: What Students Know and Can Do (Volume I, Revised edition, February 2014): Student Performance [8]
in Mathematics, Reading and Science, PISA, OECD Publishing, Paris, http://dx.doi.org/10.1787/9789264208780-en.
OECD (2014), TALIS 2013 Results: An International Perspective on Teaching and Learning, OECD Publishing, Paris, http:// [15]
dx.doi.org/10.1787/9789264196261-en.
OECD (2009), Creating Effective Teaching and Learning Environments: First Results from TALIS, OECD Publishing, Paris, [11]
http://dx.doi.org/10.1787/9789264068780-en.
OECD (2005), Teachers Matter: Attracting, Developing and Retaining Effective Teachers, OECD Publishing, Paris, http:// [10]
dx.doi.org/10.1787/9789264018044-en.
Peterson, P. (2011), Saving Schools : From Horace Mann to Virtual Learning, Belknap Press of Harvard University Press, [5]
Cambridge, MA.
Stigler, J. and J. Hiebert (1999), The Teaching Gap: Best Ideas from the World’s Teachers for Improving Education in the Classroom, [2]
Free Press, New York, NY, https://eric.ed.gov/?id=ED434102 (accessed on 20 April 2018).

402 Education at a Glance 2018: OECD Indicators   © OECD 2018

Who are the teachers? – INDICATOR D5

chapter D

Under embargo until 11/09/2018 at 11.00am CEST
Indicator D5 Tables
1 2 https://doi.org/10.1787/888933805724

Table D5.1 Age distribution of teachers (2016)
Table D5.2 Gender distribution of teachers (2016)
Table D5.3 Gender distribution of teachers by age group (2016) and percentage of female teachers for all ages
(2005, 2016)
Cut-off date for the data: 18 July 2018. Any updates on data can be found on line at http://dx.doi.org/10.1787/eag-data-en. More breakdowns can
also be found at http://stats.oecd.org/, Education at a Glance Database.

Education at a Glance 2018: OECD Indicators   © OECD 2018

403

D5

chapter D Teachers, the Learning Environment and the Organisation of Schools
Under embargo until 11/09/2018 at 11.00am CEST
Table D5.1. Age distribution of teachers (2016)
Percentage of teachers in public and private institutions, by level of education and age group, based on head counts

Partners

D5

OECD

Primary

Lower secondary

Total: primary
to upper secondary

Upper secondary

< 30
years

30-49
years

>= 50
years

< 30
years

30-49
years

>= 50
years

< 30
years

30-49
years

>= 50
years

< 30
years

30-49
years

>= 50
years

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

Australia
Austria
Belgium
Canada1
Chile
Czech Republic
Denmark
Estonia2
Finland
France
Germany
Greece
Hungary
Iceland
Ireland3
Israel3
Italy
Japan4
Korea
Latvia
Luxembourg5
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal4
Slovak Republic
Slovenia
Spain
Sweden
Switzerland4
Turkey
United Kingdom
United States

m
15
20
11d
22
8
m
10
8
12
8
9
7
5
15
13
1
17
19
9
21
m
15
12
16
9
1
7
5
9
8
17
21
31
16

m
47
56
63d
53
51
m
47
61
67
53
54
54
56
67
65
45
52
66
52
59
m
49
49
54
59
61
63
58
58
55
49
63
54
55

m
39
25
26d
25
41
m
43
31
21
39
36
39
39
19
22
55
31
15
39
20
m
36
38
30
31
38
30
36
33
37
33
15
15
29

m
10
17
x(1)
21
9
m
8
8
9
7
1
5
5
x(7)
10
2
16
12
6
12
m
15
12
16
6
1
9
5
3
8
10
31
24
16

m
41
54
x(2)
51
56
m
39
60
60
46
52
53
56
x(8)
62
44
54
60
43
64
m
45
47
54
66
59
53
58
60
55
55
63
58
56

m
49
28
x(3)
28
36
m
53
32
31
47
47
42
39
x(9)
28
55
31
28
51
24
m
40
41
30
28
40
38
36
37
37
36
5
18
29

m
6
14
11
21
4
m
8d
3
9
5
0
4
m
11d
10
2
11d
11
6
12d
m
11
10
8
5
2d
8
3
3
5
5d
20
20
12

m
49
54
63
50
45
m
41d
49
60
54
50
60
m
63d
56
35
52d
59
42
64d
m
41
46
49
63
62d
50
53
60
51
53d
68
56
54

m
45
31
26
29
51
m
51d
47
31
41
50
36
m
26d
34
63
37d
31
52
24d
m
49
43
43
32
36d
43
44
37
44
42d
12
25
33

m
10
17
11
21
7
m
9d
7
10
7
5
5
m
13
12
1
15d
14
7
16d
m
14
12
14
7
1d
8
5
5
7
12d
24
26
15

m
45
55
63
52
50
m
43d
57
62
50
53
56
m
65
62
41
52d
62
47
62d
m
46
48
53
62
61d
55
57
59
54
52d
65
56
55

m
45
28
26
27
43
m
48d
36
27
43
43
39
m
22
26
58
33d
23
46
22d
m
40
40
33
31
38d
37
38
35
39
36d
11
19
30

OECD average
EU22 average

12

56

31

10

54

35

8

53

38

11

55

34

11

56

33

8

53

38

7

52

41

9

54

37

Argentina
Brazil
China
Colombia
Costa Rica
India
Indonesia
Lithuania
Russian Federation
Saudi Arabia
South Africa

m
13
m
7
5
m
m
4
m
m
m

m
68
m
54
63
m
m
52
m
m
m

m
18
m
39
31
m
m
44
m
m
m

m
15
m
7
8
m
m
5
m
m
m

m
65
m
56
67
m
m
47
m
m
m

m
20
m
38
24
m
m
48
m
m
m

m
14
m
7
9
m
m
4
m
m
m

m
64
m
56
67
m
m
43
m
m
m

m
22
m
38
23
m
m
53
m
m
m

m
14
m
7
7
m
m
4
m
m
m

m
66
m
55
65
m
m
47
m
m
m

m
20
m
38
28
m
m
48
m
m
m

G20 average

m

m

m

m

m

m

m

m

m

m

m

m

1. Primary education includes pre-primary programmes.
2. Upper secondary includes programmes from lower secondary vocational and post-secondary non-tertiary education.
3. For Ireland, public institutions only. For Israel, private institutions are included for all levels except for pre-primary and upper secondary levels.
4. Upper secondary includes post-secondary non-tertiary education.
5. Upper secondary includes short-cycle tertiary.
Source: OECD/UIS/Eurostat (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933805743

404 Education at a Glance 2018: OECD Indicators   © OECD 2018

Who are the teachers? – INDICATOR D5

chapter D

Under embargo until 11/09/2018 at 11.00am CEST
Table D5.2. Gender distribution of teachers (2016)
Percentage of female teachers in public and private institutions by level of education, based on head counts
Tertiary

(2)

(3)

(4)

(5)

(6)

(7)

m
99
97
x(2)
99
100
m
99
97
89
96
99
100
94
99
99
99
97
99
100
96
96
88
m
92
98
99
99
97
93
95
97
95
98
94

m
92
82
75d
81
94
m
91
79
83
87
71
97
83
86
85
96
65
78
93
76
68
87
84
75
86
81
90
97
76
77
83
59
85
87

m
72
64
x(2)
68
78
m
83
74
60
67
66
77
83
x(4)
79
77
42
70
85
54
53
53
66
75
73
72
77
79
60
77
54
59
64
67

m
63
63
x(6)
58
63
54
77
70
59
56
56
67
m
70d
x(6)
71
x(6)
53
84
56
x(6)
53
61
53
70
x(6)
73
66
57
x(6)
47
50
64
x(6)

m
50
63
x(6)
51
63
m
62d
55
58
49
50
51
m
a
x(6)
58
x(6)
45
71
53
x(6)
53
54
53
62
x(6)
71
66
51
x(6)
43d
52
56
x(6)

OECD average
EU22 average

97

83

69

62

56

59

m

m

41

43

70

97

86

71

64

58

62

m

m

43

44

73

Argentina
Brazil
China
Colombia
Costa Rica
India
Indonesia
Lithuania
Russian Federation1
Saudi Arabia
South Africa6

m
95
98
97
93
m
96
99
99
100
m

m
89
64
77
79
51
62
97
99
53
79

m
68
54
53
57
45
49
82
83d
m
x(6)

m
61
x(6)
x(6)
56
x(6)
x(6)
82
x(3)
m
x(6)

m
51
x(6)
x(6)
60
x(6)
x(6)
71
x(7, 8)
m
x(6)

m
59
51
46
57
41
50
79
x(3, 7, 8)
m
58d

a
47
m
66
a
61
a
64
57d
a
m

m
45
m
37
58
a
52
a
73d
x(10)
m

m
46
m
37
44
39
41
56
51
x(10)
m

m
46
m
37
44
39
43
56
59d
41
m

m
71
m
60
68
m
60
81
83
m
m

G20 average

96

75

61

m

m

54

56

m

40

43

m

Primary

Lower
secondary

m
55
63
75
56
63
m
70d
60
59
54
54
64
m
70d
70
63
30d
51
80
54d
48
53
60
53
66
69d
72
66
55
53
44d
51
61
58

All tertiary

All programmes

(1)

Australia
Austria
Belgium
Canada
Chile
Czech Republic
Denmark
Estonia1, 2
Finland
France3
Germany
Greece
Hungary
Iceland
Ireland4
Israel4
Italy
Japan
Korea
Latvia
Luxembourg
Mexico
Netherlands
New Zealand
Norway5
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United Kingdom
United States

Preprimary

Bachelor’s,
master’s,
doctoral or
equivalent level

Vocational
programmes

Postsecondary
nontertiary

Short-cycle
tertiary

General
programmes

Partners

OECD

Upper secondary

All levels of
education

(8)

(9)

(10)

(11)

m
68
46
m
a
39
a
x(5)
54
x(9)
59
53
52
m
m
m
m
x(6, 8, 9)
a
65
m
a
a
54
53
68
x(6, 10)
68
a
a
44
x(5)
a
a
x(10)

m
52
x(10)
54
m
63
m
a
a
59
39
a
39
m
x(10)
m
a
48d
45
64
x(6)
m
45
47
53
68
x(10)
58
48
49
43
a
40
x(10)
x(10)

45
40
x(10)
42
m
38
m
49
52
41d
39
34
43
m
x(10)
m
37
21d
32
54
35
m
45
49
46
45
x(10)
45
40
41
45
35
44
x(10)
x(10)

m
42
48
49
m
38
m
49
52
44d
39
34
43
m
44
m
37
27d
35
55
35
m
45
48
46
45
44d
46
42
43
45
35
43
45
49d

m
67
70
m
m
76
m
82
73
67
66
65
76
m
m
m
77
48
62
84
m
m
66
m
65
75
71
77
77
64
75
61
57
68
70

Note: The data in “All levels of education” do not include early childhood educational development (ISCED 01).
1. Pre-primary includes early childhood education.
2. Upper secondary vocational includes lower secondary and post-secondary non-tertiary vocational programmes.
3. Public and government-dependent private institutions only for all levels except for tertiary. For tertiary education, public institutions only.
4. For Ireland, public institutions only for all levels except pre-primary, where data include independent private institutions only. For Israel, private institutions are
included for all levels except for pre-primary and upper secondary levels.
5. Public and government-dependent private institutions only for primary, lower secondary and tertiary education.
6. Year of reference 2015.
Source: OECD/UIS/Eurostat (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933805762

Education at a Glance 2018: OECD Indicators   © OECD 2018

405

D5

chapter D Teachers, the Learning Environment and the Organisation of Schools
Under embargo until 11/09/2018 at 11.00am CEST
Table D5.3. Gender distribution of teachers by age group (2016) and percentage of female teachers

for all ages (2005, 2016)

Partners

D5

OECD

Percentage of female teachers, by age group and level of education
Primary

Lower secondary

Upper secondary

All tertiary

2016

2016

2016

2016

< 30 years

>= 50
years

< 30 years

>= 50
years

(1)

(2)

(3)

(4)

Australia
Austria
Belgium1
Canada
Chile
Czech Republic1
Denmark
Estonia2
Finland
France1, 3
Germany
Greece
Hungary
Iceland
Ireland4
Israel4
Italy
Japan5
Korea
Latvia
Luxembourg6
Mexico
Netherlands
New Zealand
Norway7
Poland
Portugal5
Slovak Republic
Slovenia
Spain
Sweden
Switzerland1
Turkey
United Kingdom
United States8

m
94
85
83d
80
93
m
84
81
89
93
87
94
70
84
91
96
65
73
84
79
m
89
87
69
83
86
89
100
79
71
89
73
82
88

m
91
78
70d
80
94
m
91
76
75
84
58
97
82
86
83
96
68
88
94
77
m
83
86
77
87
79
91
97
75
77
78
45
88
88

m
76
71
x(1)
70
74
m
76
77
64
79
74
70
70
x(5)
86
59
46
73
70
67
m
62
74
69
66
62
76
80
66
71
68
65
67
69

OECD average
Average for countries
with available data for
both reference years
EU22 average

84

82

70

87

85

70

69

61

61

52

Argentina
Brazil
China
Colombia
Costa Rica
India
Indonesia
Lithuania
Russian Federation9
Saudi Arabia
South Africa

m
83
m
72
68
m
m
90
m
m
m

m
92
m
77
80
m
m
97
m
m
m

m
62
m
55
58
m
m
74
m
m
m

m
71
m
54
60
m
m
81
m
m
m

m
55
m
49
59
m
m
67
m
m
m

m
60
m
47
58
m
m
79
m
m
m

G20 average

m

m

m

m

m

m

Total primary
to upper secondary

All tertiary

2005

2016

2005

2016

< 30 years

>= 50
years

< 30 years

>= 50
years

All ages

All ages

All ages

All ages

(5)

(6)

(7)

(8)

(10)

(9)

(12)

(11)

m
72
59
x(2)
65
82
m
84
72
56
67
61
76
82
x(6)
76
77
38
56
85
45
m
44
66
77
75
71
78
79
57
77
48
38
60
68

m
71
69
83
61
58
m
59d
68
63
73
67
61
m
64d
82
57
40d
70
63
66d
m
64
65
58
62
54d
79
9
62
53
56d
66
65
62

m
53
58
70
49
61
m
72d
56
55
50
46
59
m
69d
66
62
22d
29
82
48d
m
46
59
47
62
69d
72
99
52
51
40d
34
56
56

m
53
65
58
m
m
m
48
44
57d
46
48
51
m
m
m
52
47d
68
57
41
m
50
49
44
m
45d
57
67
51
46
54
53
50
m

m
37
44
44
m
m
m
46
52
39d
29
31
38
m
m
m
32
23d
22
53
27
m
36
47
42
m
39d
41
38
37
43
29
30
41
m

m
m
65d
73
70
71d
m
m
69
65
65
59
79
m
72
79
78
46
61
m
m
56
66
69
m
76
74
77
78
62
m
62
m
68
74

m
73
70
75
71
77
m
83d
72
67
70
66
78
m
80
80
78
49d
67
87
64d
57
69
72
69
77
74d
79
82
66
71
64d
56
72
75

m
m
41
48
m
40
m
48
47
38
32
36
39
m
39
m
34
18
31
m
m
m
35
50
m
41
42d
42
33
39
m
32
38
40
44d

m
42
48
49
m
38
m
49
52
44d
39
34
43
m
44
m
37
27d
35
55
35
m
45
48
46
45
44d
46
42
43
45
35
43
45
49d

66

62

56

52

38

68

72

39

43

68

71

39

43

39

70

74

39

44

m
50
m
m
47
m
m
54
64d
m
m

m
42
m
m
39
m
m
51
53d
m
m

m
m
m
m
m
m
m
84d
86
m
m

m
73
58
64
69
47
56
85
87
m
70

m
m
m
m
m
m
m
53
51d
m
m

m
45
m
37
44
39
43
56
59d
41
m

m

m

m

67

m

41

1. Upper secondary includes post-secondary non-tertiary education (only for 2005 for Belgium, the Czech Republic and France).
2. Upper secondary includes programmes from lower secondary and post-secondary non-tertiary vocational education.
3. Public and government-dependent private institutions only for all levels except for tertiary. For tertiary education, public institutions only.
4. For Ireland, public institutions only. For Israel, private institutions are included for all levels except for pre-primary and upper secondary levels.
5. Post-secondary non-tertiary education included in upper secondary and in all tertiary.
6. Upper secondary includes short-cycle tertiary education.
7. Public and government-dependent institutions only for primary, lower secondary and tertiary education.
8. All tertiary includes post-secondary non-tertiary education.
9. All tertiary includes part of upper secondary vocational education.
Source: OECD/UIS/Eurostat (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933805781

406 Education at a Glance 2018: OECD Indicators   © OECD 2018

Under embargo until 11/09/2018 at 11.00am CEST

Under embargo until 11/09/2018 at 11.00am CEST

WHO MAKES KEY DECISIONS IN EDUCATION SYSTEMS?
• Decisions about diverse aspects of public lower secondary education are most commonly made
either at the school level or at the central or state level.

• In most countries decisions on the organisation of instruction are predominantly taken at the
school level, decisions on resources are more often made at school or local level and decisions
related to planning and structures, personnel management are more likely to be made at higher
levels of authority, although countries vary widely in this regard.

INDICATOR D6

Figure D6.1. Percentage of decisions taken at each level of government
in public lower secondary education (2017)
School

Local

Regional or sub-regional

Central or state

Multiple levels

Netherlands
Czech Republic
England (UK)
Latvia
Flemish Comm. (Belgium)
Iceland
Estonia
Australia
New Zealand
Slovenia
Scotland (UK)
Chile
Austria
Ireland
Slovak Republic
Lithuania
Sweden
OECD average
Italy
Hungary
Denmark
French Comm. (Belgium)
Russian Federation
Japan
Israel
Germany
Luxembourg
Mexico
United States
Canada
Korea
Portugal
Norway
France
Spain
Switzerland
Greece
Turkey
Finland

%

100
90
80
70
60
50
40
30
20
10
0

Countries are ranked in descending order of the percentage of decisions taken at the school level.
Source: OECD (2018), Table D6.1. See Source for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag2018-36-en).
1 2 https://doi.org/10.1787/888933805933

Context
The division of responsibility among national, regional and local authorities, and schools is a muchdebated topic in education policy. Since the early 1980s, a key aim of education reform has been
to place more decision-making authority at lower levels of education systems. At the same time,
many countries have strengthened the influence of central authorities in setting standards, curricula
and assessments. For example, a loosening of “process” and financial regulations has often been
accompanied by an increase in the central-level control of outputs.
There are many reasons for changes in patterns of decision making and responsibility, and they vary
from country to country. The most common reasons to decentralise decision making are increased
efficiency and improved financial control; reduced bureaucracy; increased responsiveness to local
communities; more creative management of human resources; improved potential for innovation;
and creating conditions that provide better incentives to improve the quality of schooling (Burns and
Köster, 2016[1]).
This indicator shows where key decisions are made in public institutions at the lower secondary level
of education. It does not capture the totality of decisions made within a school system. Instead, a set
of 23 key decisions, organised across four domains, are considered. These decisions are based on a
streamlined version of earlier rounds of data collection in 2003, 2007 and 2011 on levels of decision
making in education (see Methodology section).

408 Education at a Glance 2018: OECD Indicators   © OECD 2018

Under embargo until 11/09/2018 at 11.00am CEST
Other findings

• In 16 of 38 countries, decisions are most often taken at the school level. In 10 of these countries, half
or more of the decisions are taken at the school level. In the Czech Republic and the Netherlands,
two-thirds or more of decisions taken at the school level.

• In 11 of 38 countries, decisions made at the state or central level were the most prevalent.
Luxembourg, Mexico and Portugal are the OECD countries and economies with the most centralised
decision making, as more than three-quarters of decisions are taken at the central or state level.

• Decisions on the organisation of instruction are predominantly taken by schools or the local level
in most countries. However, in Germany, two out of three of these decisions are taken at the
central or state level. Most decisions on personnel management and the use of resources are taken
at the local or school level in around one-half of countries. Decisions on planning and structures
are mostly taken at one of the more centralised tiers of government.

INDICATOR D6

• There are substantial differences between countries in the ways in which decisions are taken. On
average across OECD countries, nearly one-third of the decisions taken at the school or local levels
are taken in full autonomy, and two-thirds are within a framework set by a higher authority.

Education at a Glance 2018: OECD Indicators   © OECD 2018

409

chapter D Teachers, the Learning Environment and the Organisation of Schools
Under embargo until 11/09/2018 at 11.00am CEST

Analysis
Levels of decision making in public lower secondary schools
In this indicator, six distinct levels of government or education authority at which decisions can be taken are
distinguished: central, state, provincial/regional, sub-regional, local and school levels (see Definitions section). As
decisions in some countries are not made at one specific level, but rather taken at multiple levels, the category
“multiple level” has been included (Box D6.1).

D6

However, the figures group decisions across five different levels of government: school level; local level, regional or
sub-regional level; state or central level; and multiple level. This grouping makes it possible to more readily compare
federal countries and non-federal countries. For example, the state and national levels are grouped together, since the
most central level at which decisions about education are taken in a federal country is typically the state level, and the
most central level in a non-federal country is the national level. Similarly, the regional and sub-regional levels refer to
the second-most central level in federal and non-federal countries, so it was logical to group these together as well.
The results reveal that the largest share of decisions is taken at the school level among the 38 countries and
economies with available data. Across the 36 OECD countries and economies with available data, an average of 34%
of all decisions covered in the survey are taken at the school level, about 34% were made centrally (i.e. at the central
or state level), some 13% were made at the local level, which is the level just above the school level, and about 5%
of the decisions were made at the regional or sub-regional levels. However, in some countries, decisions are taken
by a combination of levels, and on average across OECD countries, 14% of the decisions are taken by multiple levels
(Table D6.1 and Figure D6.1).
Half of the countries (19 out of 38) reported that the largest proportion of decisions that affect lower secondary
education are taken at the school level (16 countries) or local level (3 countries). In the set of decisions taken into
account, most are taken at the school level (only) in Australia, the Czech Republic, England (United Kingdom),
Estonia, the Flemish Community of Belgium, Iceland, Latvia, the Netherlands and New Zealand. Among the three
countries that reported that the largest share of decisions is taken at the local level (i.e. by local school districts
or local or municipal education authorities), the local level is the level of authority taking most of the decisions in
Canada and the United States (Table D6.1).
The largest proportion of decisions is taken either at the state or central level in more than one-third of the countries
(14 countries). Most of the decisions are taken at the state or central level in eight of these countries: France,
Germany, Greece, Israel, Italy, Luxembourg, Portugal and Turkey. When central and state levels are combined, most
of the decisions are also taken at these levels in Austria, Mexico and Spain (Table D6.1).
In Denmark, Korea, Norway and Sweden, decision making is more evenly distributed among the central,
intermediate, and local or school level, and none of these levels makes more than 35% of the decisions taken into
account (Table D6.1).

Box D6.1. Multiple levels of decision and influence of non-government entities
Multiple levels of government or an education authority (rather than a single level) can be involved in decision
making on specific subjects in the four domains taken into account in the survey (see Methodology section).
In a few countries (Denmark, Hungary and Korea), multiple levels are involved in decisions on some or all
subjects covered in the four domains. The levels of decisions involved may vary according to the type of decision,
but in general some flexibility in the decisions is left to be determined at the lower levels of government.
In Finland, all decisions are taken by multiple levels, as local and school levels are involved in all decisions,
even when a more general framework is set at a higher level of government for some subjects. For example,
in Korea, the central government stipulates a minimum instruction time per group of grades, but schools
make decisions on allocation of the instruction time in each grade and can also decide to increase or decrease
instruction time within a certain extent (set at the central level).
In other countries, multiple levels of decisions take place in fewer subjects, but usually result from the fact that
there is some flexibility given to the school or local level to adapt or adjust the decisions. For example, duties of
teachers in Norway are stated in the collective agreement between the employer (local authorities) and teachers,

…

410 Education at a Glance 2018: OECD Indicators   © OECD 2018

Who makes key decisions in education systems? – INDICATOR D6

chapter D

Under embargo until 11/09/2018 at 11.00am CEST
but additional duties might be decided at school level. In some other cases, different levels of government jointly
take decisions. For example, in Lithuania, the hiring of school principals results from a competition process
between applicants. The committee in charge of the final decision is composed of representatives from the central
government, local authorities and the school board.
In addition to recognising the influence of different levels of government on decision making, many countries
have noted that non-government entities may also be consulted or involved in establishing a framework for
decisions taken at lower levels. The most common non-government participants are teachers’ unions. For
example, when teachers’ unions negotiate with education authorities to set pay scales, they are helping to
establish a framework for decisions related to teachers’ salaries for specific teachers. In many countries,
teachers’ unions are involved in decisions relating to duties and conditions of work, salary scales and
instruction time. The participation of teachers’ unions in decision making on these issues is notable in the
Flemish Community of Belgium, Denmark, Finland, Iceland, Israel, Norway and Sweden and also in some
Canadian provinces/territories.
In the Flemish Community of Belgium, for example, decisions on minimum and maximum instruction time
are taken by the state governments, but in consultation with non-government entities, such as teachers’
unions and education networks. This is also the case in the French Community of Belgium, but within this
framework, schools can decide about the instruction time and the programmes of study offered in the school.
Teachers’ unions can influence decisions on professional development of teaching staff and their careers, as
happens in Italy. In Norway, employers’ associations are involved in decisions about personnel management,
including salaries. In the Netherlands, employers’ associations and a variety of civil society organisations are
involved in decisions regarding education policies in general and those on how schools are run.
Parents and parents’ organisations also have an influence on decision making (see Indicator D6, “How can
parents influence the education of their children?” in Education at a Glance 2010 [OECD, 2010[2]]). In Scotland
(United Kingdom), for example, parent councils often participate in the selection of principals and education
authorities are required by law to involve parents in matters of education. In Turkey, some decisions, including
those on allocation of resources, are taken by the central government with the involvement of parent-teacher
associations. Portugal involves teachers’ associations, experts and scientific societies in establishing a
framework for instruction time and designing programmes of study.
More detailed information on the multiple levels of decision and non-government entities for all participating
countries and economies is available in Annex 3.
In a few countries, decisions are taken by a combination of different levels of government. Most of the decisions
are taken by multiple levels in Hungary and Finland. In Finland, all decisions covered in the survey are taken by a
combination of different levels. Although the local authorities, as education providers, are responsible for most
decisions in practice, many decisions in large urban districts are delegated to schools, particularly those related to
staffing (Table D6.1).
Domains of decision making
Decisions about education systems are organised across four general domains of decision making: organisation of
instruction, personnel management, planning and structures, and resource management (Table D6.2).
There are large differences in the levels of government responsible for decisions across these four domains. On
average across OECD countries and economies, decisions related to the organisation of instruction are predominantly
made at the school level (50%), decisions on resource management are more often made at the local or school level
(48%), while decisions about planning and structures are most likely to be made at the central or state level (48%).
Decisions on personnel management are more evenly distributed across the levels of decisions (Figure D6.2).
Because a general assessment of the roles played in the decision-making process includes decisions made about different
domains, an aggregate measure can mask differences in the degree of centralisation within those areas. For example, a
country may centralise almost all decisions about the curriculum, while schools may have nearly complete control over
decisions about the programmes of study offered in the school (Figure D6.3b, available on line). The distribution of
decisions taken by each administrative level across the four domains of decision making is an indicator of “functional
decentralisation”, which takes into account the fact that decision making may be decentralised in certain activities and
centralised in others (see Definitions and Methodology sections at the end of this indicator).
Education at a Glance 2018: OECD Indicators   © OECD 2018

411

D6

chapter D Teachers, the Learning Environment and the Organisation of Schools
Under embargo until 11/09/2018 at 11.00am CEST

Figure D6.2. Percentage of decisions taken at each level of government
in public lower secondary education in OECD countries, by domain of decisions (2017)
%

D6

100
90
80
70
60
50
40
30
20
10
0

School

All
decisions

Local

Regional or sub-regional

Organisation
of instruction

Personnel
management

Central or state

Planning
and structures

Multiple levels

Resource
management

Source: OECD (2018), Tables D6.1 and D6.2. See Source for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933805952

Organisation of instruction
Three decisions on the organisation of instruction have been considered in the survey: the school that a child should
attend; how children are grouped within the school; and the instruction time for children. Combining these decisions
as a whole, about half are taken at the school level, but with large variation in the level of authority in charge of the
decisions, both between countries and within countries (Table D6.2).
Decisions on these three matters are taken exclusively at the school level in Chile, the Czech Republic and
the Netherlands. In other countries, decisions are split between central/state, local and school levels (Figure D6.3b,
available on line).
Decisions on the school that children should attend are mostly made at the local or school level. In nearly all countries,
parents have also some choice in the school of their children. Only in Brazil, France, Greece, Israel, Norway and
Switzerland are these decisions taken by others than parents (when children are enrolled in public institutions)
(Table D6.5, available on line).
While decisions about grouping of pupils are taken by schools in nearly nine out of ten countries and economies
with available data, decisions about instruction time are made at the state or central level in six out of ten countries
and economies, and at school or local levels in most of the remaining countries, but within a centrally established
framework. Only in England (United Kingdom) is instruction time decided autonomously by schools (Table D6.5
and Figure D6.3b, both available on line) (see Indicator D1 and Box D1.3 for more information).

Planning and structure
Decisions related to programmes of study and learning resources (designing programmes of study, selection of
programmes of study offered in a particular school, selection of subjects taught in a particular school and definition
of course content) are most often made at the state or central level, on average across OECD countries. Otherwise,
these decisions are taken at the school level, or at multiple levels when decisions are not made by a single level. Local
or regional levels are in charge of decisions in only a few countries (Table D6.2).
In 21 of the 38 countries and economies for which data are available on decision making by domain, at least 50% of
decisions related to programmes of study and the subjects taught were taken at the state or central level. In Israel,
Luxembourg, Mexico, Norway, Portugal, the Russian Federation, Switzerland and Turkey, all these decisions were
made at either state or central level (Table D6.2 and Figure D6.3a).
However, there are variations in the level of authority in charge of decisions according to the type of decision.
School and local levels are responsible for decisions on the design of the programme of study in about one-fifth of
countries, but they are responsible for decisions on the selection of programmes of study offered in a particular
school, of subjects taught in a particular school or, in a larger proportion of countries (up to one-third), for decisions
on the definition of course content (Table D6.7 available on line).

412 Education at a Glance 2018: OECD Indicators   © OECD 2018

Who makes key decisions in education systems? – INDICATOR D6

chapter D

Under embargo until 11/09/2018 at 11.00am CEST

Figure D6.3a. Decisions taken at each level of government and mode of decision making
in public lower secondary education, by type of decision (2017)
School
Local
Regional or sub-regional
Central or state

Multiple levels
Missing
Not applicable

In full autonomy
After consultation
Within framework

Level of decisions

Other
Missing
Not applicable

Mode of decisions

D6

Organisation of instruction
School attended
Grouping pupils
Instruction time

Management of teachers
Hiring
Dismissal
Duties
Conditions of service
Fixing salary levels

Management of principals
Hiring
Dismissal
Duties
Conditions of service
Fixing salary levels

Planning and structures

Designing programmes of study
Selection of programmes of study in a particular school
Selection of subjects taught in a particular school
Definition of course content

Resource management: Allocation to schools
For teaching staff
For teachers’ professional development
For principals’ professional development

Resource management: Use of resources in schools
For staff
For teachers’ professional development
For principals’ professional development

50 45 40 35 30 25 20 15 10 5
Number of countries and economies

0

0

5 10 15 20 25 30 35 40 45 50
Number of countries and economies

Source: OECD (2018), Tables D6.5, D6.6a, D6.6b, D6.7 and D6.8 available on line. See Source for more information and Annex 3 for notes
(http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933805971

Decisions at the school or local levels are not taken in full autonomy at these levels of authority, but within a defined
framework set at a higher level or after consultation with other levels. An exception is Sweden, where the local level
takes decisions in full autonomy on the selection of programmes of study offered in a particular school (Table D6.7,
available on line).

Personnel management
Decisions about personnel management include hiring and dismissal of staff, duties and conditions for staff, and fixing
salary levels. The survey distinguished between decisions related to teachers and those related to principals.
Focusing on decisions related to teachers, the responsible level of authority varies according to the type of decision.
Among the five different decisions covered in the survey, those most often taken at the school level are related to four
issues: hiring, dismissal, duties, and working conditions of teachers. Among the 38 countries and economies with available
information, 40% to 50% of countries report the school as the level of authority for these decisions. All four types of
decisions are taken at the school level in nearly one-quarter of the countries with available information: the Czech Republic,
Denmark, England (United Kingdom), Estonia, the Flemish Community of Belgium, Latvia, Lithuania, the Netherlands,
the Slovak Republic and Slovenia. The state level is responsible for these four types of decisions in Australia and Mexico
and the central level in Luxembourg and Turkey. In the remaining countries with available data, various levels of authority
are in charge of each of these four types of decisions on teachers (Table D6.6a, available on line).
Education at a Glance 2018: OECD Indicators   © OECD 2018

413

chapter D Teachers, the Learning Environment and the Organisation of Schools
Under embargo until 11/09/2018 at 11.00am CEST
Decisions on setting salaries for teachers follow a different pattern (see Indicator D3 on and Box D3.2 for variation
of salaries at subnational level). In more than half of the countries with available information, these decisions are
the responsibility of the central or state level, whereas in more than one-quarter of the countries multiple levels are
responsible for these decisions. In all but one of the remaining countries, local or school levels are the responsible
authorities for these decisions (Table D6.6a, available on line).

D6

In most countries, the level of authority responsible for decisions related to principals is the same as for decisions
related to teachers. However, in a few countries, different levels of authority are in charge of decisions for teachers and
school heads. This is the case for each of the five types of decisions on personal management in the Czech Republic,
Estonia and Latvia. In these countries, schools are responsible for decisions on teachers, while the local level is
responsible for similar decisions on principals. In other countries with different levels of authority responsible for
decisions on teachers and principals, only a few of the five types of decisions are taken at different levels of authority
for teachers and principals. In most of these cases, decisions related to principals are taken at a more central level
than those related to teachers (Tables D6.6a and D6.6b, available on line).

Allocation and use of resources
Compared to other types of decisions, those related to the allocation and use of resources are made less frequently
at the central level (30% of decisions made at the central or state level). A clear difference in the level of authority
responsible for decisions on the allocation of resources versus their use is also evident.
Central or state authorities take decisions on the allocation of resources for teaching staff and for teachers’ and
principal’s professional development in 14 to 19 countries (according to decisions considered) out of the 38 with
available information. Decisions are taken at the school or local level in a slightly lower number of countries (in
13 to 16 countries according to decisions considered). In most countries (20 out of 38 countries), the three types
of decisions on the allocation of resources are taken by the same level of authority, but in the remaining countries,
these decisions are taken by two levels of authority. These three types of decisions are the responsibility of three
different levels of authority only in the Slovak Republic (Table D6.8, available on line).
Although state and central authorities decide on how resources are allocated in nearly half of the countries, the
use of resources within schools for staff and for professional development of teachers and principals is more often
decided at the school or local level. In more than half of countries, schools decide on the use of resources for staff
and professional development of teachers. However, although schools decide on use of resources for professional
development of teachers in most of the 38 countries and economies with available information, schools are the
decision level for use of resources for professional development of principals in less than a third of countries, as local
levels decide in nearly a quarter of these countries (Table D6.8, available on line).
Mode of decisions taken at the school or local levels
Decisions on a specific subject are usually the responsibility of a single level of authority. However, this does not
imply that this level of authority decides with full autonomy. Decisions may also be made after consulting with other
bodies, or within a framework set by a higher level of authority. The different mode of decisions used could result
from the need to ensure consistency of decisions across different subnational entities and avoid disparities within
the country.
Combining both local and school levels to analyse decisions made at the lowest levels of decision making, nearly
half of all decisions taken into account in the survey are made at the school or local level, on average across OECD
countries and economies. Nearly one-third of these decisions (15% of all decisions) are made in full autonomy,
whereas most (29% of all decisions) are made within a framework set by a higher authority. Decisions at these levels
after consultation with other bodies in the educational system are relatively rare and represent less than 5% of all
decisions taken into account. However, in Mexico, all decisions at school or local level (17% of the decisions) are
made based on this consultation process. In addition to decisions taken directly by schools or local authorities, some
decisions are taken at other levels after consultation with schools or local levels. These represent about 2% of the
decisions taken into account (Table D6.3 and Figure D6.4a).
The mode of decision varies largely between the domains of decisions. Planning and structures is the domain
with the lowest proportion of decisions made at the school or local level (less than 39% of the decisions), and a
negligible proportion is taken in full autonomy (they are taken in full autonomy only in Sweden). Some 50% of all
decisions related to resource management are made at the school or local level, with the majority of these decisions
in full autonomy. In addition, another 5% of decisions related to resource management are made by higher levels

414 Education at a Glance 2018: OECD Indicators   © OECD 2018

chapter D

Who makes key decisions in education systems? – INDICATOR D6

Under embargo until 11/09/2018 at 11.00am CEST
of government, but they are made after consulting with schools or local levels. Organisation of instruction is the
domain with the largest proportion of decisions made at the school or local level (nearly two-thirds of decisions).
However, in this domain, only 19% of decisions are taken in full autonomy by schools or at the local level, and the
largest proportion of decisions made by the school or local level are made within a framework set at a higher level
(Table D6.4a and Figure D6.4a).
There are substantial differences among countries in the mode in which decisions are made (Tables D6.3 and D6.4a,
and Figure D6.4b, available on line). All domains of decision combined, among the 19 OECD and partner countries
and economies in which most decision making is in the hands of school or local levels (at least 50% of decisions
made by these levels), most of these decisions are taken within a framework set at a higher level in most of them:
in Australia, Canada, Chile, the Czech Republic, Denmark, Estonia, the Flemish Community of Belgium, Latvia,
Lithuania, New Zealand, Scotland (United Kingdom) and Slovenia. However, at least half of these decisions are taken
in full autonomy in England (United Kingdom), Finland, Iceland, the Slovak Republic and Sweden (Table D6.3).
Perhaps predictably, decisions taken by schools in countries that tend to have the largest proportions of decisions
taken more centrally are more likely to be subject to an overarching framework. This is the case in France and
Portugal, where 15% or less of decisions are taken at the school level, most or all of them within a framework set at
a higher level (Table D6.3).
Even when decisions are taken at other levels, a substantial proportion of these decisions can be taken after
consultation with the school or local level. In Australia and Luxembourg, at least 10% of all decisions are taken at
other levels, but after consultation with schools or local levels (Table D6.3).

Figure D6.4a. Percentage of decisions taken at the local or school
levels in public lower secondary education in OECD countries,
by mode of decision making and domain (2017)
In full autonomy
After consultation with other bodies in the educational system
Within framework set by a higher authority
Other
Decisions taken at other levels after consultation with schools
%

70

Decisions taken at the local or school levels

A All decisions
B Organisation of instruction
C Personnel management
D Planning and structures
E Resource management

Decisions taken at the school level

Decisions taken at the local level

60
50
40
30
20
10
0

A

B

C

D

E

A

B

C

D

E

A

B

C

D

E

Source: OECD (2018), Table D6.3 and Tables D6.4a, D6.4b and D6.4c available on line. See Source for more information and Annex 3 for notes
(http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933805990

Definitions
Central level: The central government consists of all bodies at the national level that make decisions or participate
in different aspects of decision making.
Local level: The municipality or community is the smallest territorial unit in the nation with a governing authority.
The local authority may be the education department within a general-purpose local government, or it may be a
special-purpose government whose sole area of authority is education.
Education at a Glance 2018: OECD Indicators   © OECD 2018

415

D6

chapter D Teachers, the Learning Environment and the Organisation of Schools
Under embargo until 11/09/2018 at 11.00am CEST
Multiple levels: Multiple decision-making levels refer to a combination of two or more of the above-mentioned
authorities (e.g. the central government and the local authorities).
Regional level: The province or region is the first territorial unit below the national level in countries that do not
have a “federal” or similar type of government structure, and the second territorial unit below the nation in countries
with “federal” or similar types of governmental structures. Provincial/regional authorities or governments are the
decision-making bodies at this level.

D6

School, school board or committee refers to the individual school level only and includes school administrators
and teachers or a school board or committee established exclusively for that individual school. The decision-making
body (or bodies) for this school may be: an external school board, which includes residents of the larger community;
an internal school board, which could include headmasters, teachers, other school staff, parents, and students;
and both an external and an internal school board. “School networks”, “networks of schools”, “didactic circles” and
“groups of schools” should be considered as schools.
State level: The state is the first territorial unit below the nation in “federal” countries or countries with similar
types of governmental structures. State governments are the governmental units that are the decision-making
bodies at this level. For countries other than federal or similar, where the extent of the state is identical with that of
the country, this level is non-existent.
Sub-regional level: The sub-region is the second territorial unit below the nation in countries that do not have a
“federal” or similar type of governmental structure. Sub-regional or inter-municipal authorities or governments
are the decision-making bodies at this level.

Methodology
This indicator shows decision-making levels in public lower secondary education. Decentralisation is concerned
with the division of power between levels of government. This concept has two dimensions: the locus of decision
making (i.e. the level of decision-making authority) and the mode of decision making (related to the degree of
autonomous or “shared” decision making).
Seven levels of decision making are distinguished: central governments; state governments; provincial/regional
authorities or governments; sub-regional or inter-municipal authorities or governments; local authorities or
governments; schools or school boards or committees; and multiple levels (see Definitions section above). For most
of the decisions, there is only one level of decision-making authority, but it is possible to report that there are
multiple decision-making levels for specific decisions.
The most important factor in determining the degree of autonomy to take decisions or the mode of decision is “who
decides”. The following categories were provided in the survey: full autonomy; after consultation with bodies located
at another level within the education system; independently but within a framework set by a higher authority;
and other.
Some 23 general decisions were included in the survey (compared to 46 in the previous edition). These were
separated into four domains:
1. Organisation of instruction: focusing on student admissions; instruction time; grouping students.
2. Personnel management: hiring and dismissal of teaching staff and principals; duties and conditions of service
of teaching staff and principals; salary scales of teaching staff and principals.
3. Planning and structures: design of programmes of study; selection of programmes of study taught in a
particular school; choice of subjects taught in a particular school; definition of course content.
4. Resources: allocation and use of resources for teaching staff and principals.
The number of decisions within each of these domains was not equal, and adjustments were made to give equal
weight to each of the four domains. Because there are different numbers of items (i.e. decisions) in each domain,
each item is weighted by the inverse of the number of items in its domain. Some items are split up into sub-items.
The sum of weights of sub-items is equal to the weight of an item (in the same domain) without sub-items. Missing
and not applicable items receive weight zero, causing other weights to change within a domain.
More detailed information on specific countries is provided in Annex 3 at http://dx.doi.org/10.1787/eag-2018-36-en.
Information on additional subjects covered in the previous rounds of the data collection is available in Education at a
Glance 2012 (OECD, 2012[3]).

416 Education at a Glance 2018: OECD Indicators   © OECD 2018

Who makes key decisions in education systems? – INDICATOR D6

chapter D

Under embargo until 11/09/2018 at 11.00am CEST
Lithuania was not an OECD member at the time of preparation of this publication. Accordingly, Lithuania does not
appear in the list of OECD members and is not included in the zone aggregates.

Source
Data are from the 2017 OECD-INES Survey on Locus of Decision Making and refer to the school year 2016-17.
This updates the results of previous survey with a broader coverage which took place in 2011 (results published in
Education at a Glance 2012 [OECD, 2012[3]]).

D6
Note regarding data from Israel
The statistical data for Israel are supplied by and are under the responsibility of the relevant Israeli authorities. The use
of such data by the OECD is without prejudice to the status of the Golan Heights, East Jerusalem and Israeli settlements
in the West Bank under the terms of international law.

References
Burns, T. and F. Köster (eds.) (2016), Governing Education in a Complex World, Educational Research and Innovation, OECD [1]
Publishing, Paris, http://dx.doi.org/10.1787/9789264255364-en.
OECD (2012), “Indicator D6 Who makes key decisions in education systems?”, in Education at a Glance 2012: OECD [3]
Indicators, OECD Publishing, Paris, http://dx.doi.org/10.1787/eag-2012-34-en.
OECD (2010), “How can parents influence the education of their children?”, in Education at a Glance 2010: OECD Indicators, [2]
OECD Publishing, Paris, http://dx.doi.org/10.1787/eag-2010-30-en.

Indicator D6 Tables
1 2 https://doi.org/10.1787/888933805857

Table D6.1

Percentage of decisions taken at each level of government in public lower secondary education (2017)

Table D6.2

Percentage of decisions taken at each level of government in public lower secondary education,
by domain (2017)

Table D6.3

Percentage of decisions taken at the school level in public lower secondary education,
by mode of decision making (2017)

WEB Table D6.4a Percentage of decisions taken at the local or school levels in public lower secondary education
in OECD countries, by mode of decision making and domain (2017)
WEB Table D6.4b Percentage of decisions taken at the school level in public lower secondary education,
by mode of decision making and domain (2017)
WEB Table D6.4c Percentage of decisions taken at the local level in public lower secondary education, by mode
of decision making and domain (2017)
WEB Table D6.5

Level of government at which different types of decisions about organisation of instruction
are taken in public lower secondary education (2017)

WEB Table D6.6a Level of government at which different types of decisions about personnel management
of teachers are taken in public lower secondary education (2017)
WEB Table D6.6b Level of government at which different types of decisions about personnel management
of principals are taken in public lower secondary education (2017)
WEB Table D6.7

Level of government at which different types of decisions about planning and structures
are taken in public lower secondary education (2017)

WEB Table D6.8

Level of government at which different types of decisions about resources are taken
in public lower secondary education (2017)

WEB Figure D6.3b Percentage of decisions taken at each level of government in public lower secondary education,
by domain (2017)
WEB Figure D6.4b Percentage of decisions taken at the local or school levels in public lower secondary education,
by mode of decision making and domain (2017)
Cut-off date for the data: 18 July 2018. Any updates on data can be found on line at http://dx.doi.org/10.1787/eag-data-en. Data can also be found
at http://stats.oecd.org/, Education at a Glance Database.

Education at a Glance 2018: OECD Indicators   © OECD 2018

417

chapter D Teachers, the Learning Environment and the Organisation of Schools
Under embargo until 11/09/2018 at 11.00am CEST
Table D6.1. Percentage of decisions taken at each level of government

OECD

in public lower secondary education (2017)

D6

Central

State

Provincial/
regional

Sub-regional

Local

School

Multiple levels

Total

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

0
32
0
8
2
21
0
x(7)
55
0
52
2
8
42
69
52
13
29
18
83
49
0
21
25
m
77
48
42
8
21
0
73
0

48
22
33
0
0
a
0
a
a
63
a
a
a
a
a
a
a
a
a
0
34
0
0
a
m
0
a
a
47
a
48
0
8

a
0
0
0
4
0
0
0
16
10
4
a
a
a
4
11
33
15
a
0
0
0
0
a
m
0
0
a
22
a
a
19
a

a
0
0
0
0
a
0
0
10
10
4
19
a
a
a
a
a
a
a
0
0
0
0
a
m
0
a
a
0
a
a
0
a

a
0
52
31
26
22
13
x(7)
0
0
8
0
31
0
8
0
21
8
19
0
0
0
0
29
m
0
8
0
0
35
29
0
72

52
46
15
48
68
29
58
x(7)
10
17
8
29
60
46
19
30
21
15
64
17
17
92
52
15
m
15
44
50
10
35
8
8
16

0
0
0
13
0
28
29
100
8
0
23
50
0
13
0
6
13
33
0
0
0
8
27
31
m
8
0
8
13
8
15
0
4

100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
m
100
100
100
100
100
100
100
100

Flemish Comm. (Belgium)
French Comm. (Belgium)
England (UK)
Scotland (UK)

0
0
0
0

38
42
a
a

0
0
a
a

0
a
a
a

0
0
6
44

63
27
65
48

0
31
29
8

100
100
100
100

OECD average
EU22 average

24
24

11
9

4
3

1
2

13
8

34
38

14
16

100
100

Argentina
Brazil
China
Colombia
Costa Rica
India
Indonesia
Lithuania
Russian Federation
Saudi Arabia
South Africa

m
m
m
m
m
m
m
29
42
m
m

m
m
m
m
m
m
m
a
a
m
m

m
m
m
m
m
m
m
a
21
m
m

m
m
m
m
m
m
m
0
a
m
m

m
m
m
m
m
m
m
27
10
m
m

m
m
m
m
m
m
m
42
23
m
m

m
m
m
m
m
m
m
2
4
m
m

m
m
m
m
m
m
m
100
100
m
m

G20 average

m

m

m

m

m

m

m

m

Countries

Australia
Austria
Canada
Chile
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United States

Partners

Economies

Note: See Definitions and Methodology sections for more information.
Source: OECD (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933805876

418 Education at a Glance 2018: OECD Indicators   © OECD 2018

Who makes key decisions in education systems? – INDICATOR D6

chapter D

Under embargo until 11/09/2018 at 11.00am CEST
Table D6.2. [1/2] Percentage of decisions taken at each level of government

in public lower secondary education, by domain (2017)

State

Provincial/
regional

Subregional

Local

School

Multiple
levels

Total

Central

State

Provincial/
regional

Subregional

Local

School

Multiple
levels

Total

Personnel management

Central
OECD

Organisation of instruction

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

(13)

(14)

(15)

(16)

0
33
0
0
0
33
0
x(7)
33
0
33
0
33
33
33
33
0
0
33
33
33
0
33
0
m
33
50
33
0
0
0
33
0

33
0
33
0
0
a
0
a
a
67
a
a
a
a
a
a
a
a
a
0
0
0
0
a
m
0
a
a
33
a
33
0
0

a
0
0
0
0
0
0
0
0
0
0
a
a
a
0
0
0
0
a
0
0
0
0
a
m
0
0
a
33
a
a
33
a

a
0
0
0
0
a
0
0
33
0
0
0
a
a
a
a
a
a
a
0
0
0
0
a
m
0
a
a
0
a
a
0
a

a
0
33
0
0
0
0
x(7)
0
0
33
0
33
0
33
0
67
33
0
0
0
0
0
0
m
0
0
0
0
33
33
0
67

67
67
33
100
100
33
67
x(7)
33
33
33
0
33
67
33
67
33
33
67
67
67
100
67
33
m
33
50
67
33
67
33
33
33

0
0
0
0
0
33
33
100d
0
0
0
100
0
0
0
0
0
33
0
0
0
0
0
67
m
33
0
0
0
0
0
0
0

100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
m
100
100
100
100
100
100
100
100

0
50
0
33
8
0
0
0
83
0
42
8
0
50
67
58
0
58
0
100
33
0
33
0
m
75
50
17
0
0
0
83
0

100
33
33
0
0
a
0
a
a
67
a
a
a
a
a
a
a
a
a
0
67
0
0
a
m
0
a
a
42
a
58
0
0

a
0
0
0
0
0
0
0
0
17
17
a
a
a
17
33
83
33
a
0
0
0
0
a
m
0
0
a
17
a
a
17
a

a
0
0
0
0
a
0
0
8
17
17
25
a
a
a
a
a
a
a
0
0
0
0
a
m
0
a
a
0
a
a
0
a

a
0
58
58
42
33
50
x(15)
0
0
0
0
67
0
0
0
17
0
50
0
0
0
0
42
m
0
8
0
0
42
33
0
67

0
17
8
8
50
33
50
x(15)
8
0
0
8
33
50
17
8
0
0
50
0
0
67
58
0
m
25
42
50
8
25
0
0
17

0
0
0
0
0
33
0
100d
0
0
25
58
0
0
0
0
0
8
0
0
0
33
8
58
m
0
0
33
33
33
8
0
17

100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
m
100
100
100
100
100
100
100
100

Flemish Comm. (Belgium)
French Comm. (Belgium)
England (UK)
Scotland (UK)

0
0
0
0

33
33
a
a

0
0
a
a

0
a
a
a

0
0
0
67

67
67
67
33

0
0
33
0

100
100
100
100

0
0
0
0

33
50
a
a

0
0
a
a

0
a
a
a

0
0
0
58

67
0
100
8

0
50
0
33

100
100
100
100

OECD average

15

7

2

1

12

50

12

100

24

13

6

2

17

22

15

100

EU22 average

17

7

1

1

6

53

14

100

24

10

4

3

12

29

19

100

Argentina
Brazil
China
Colombia
Costa Rica
India
Indonesia
Lithuania
Russian Federation
Saudi Arabia
South Africa

m
33
m
m
m
m
m
33
33
m
m

m
0
m
m
m
m
m
a
a
m
m

m
a
m
m
m
m
m
a
0
m
m

m
a
m
m
m
m
m
0
a
m
m

m
0
m
m
m
m
m
33
33
m
m

m
67
m
m
m
m
m
33
33
m
m

m
0
m
m
m
m
m
0
0
m
m

m
100
m
m
m
m
m
100
100
m
m

m
m
m
m
m
m
m
33
33
m
m

m
m
m
m
m
m
m
a
a
m
m

m
m
m
m
m
m
m
a
8
m
m

m
m
m
m
m
m
m
0
a
m
m

m
m
m
m
m
m
m
25
8
m
m

m
m
m
m
m
m
m
33
33
m
m

m
m
m
m
m
m
m
8
17
m
m

m
m
m
m
m
m
m
100
100
m
m

G20 average

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

Countries

Australia
Austria
Canada
Chile
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United States

Partners

Economies

Note: See Definitions and Methodology sections for more information.
Source: OECD (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933805895

Education at a Glance 2018: OECD Indicators   © OECD 2018

419

D6

chapter D Teachers, the Learning Environment and the Organisation of Schools
Under embargo until 11/09/2018 at 11.00am CEST
Table D6.2. [2/2] Percentage of decisions taken at each level of government

in public lower secondary education, by domain (2017)

Central

State

Provincial/
regional

Subregional

Local

School

Multiple
levels

Total

Central

State

Provincial/
regional

Subregional

Local

School

Multiple
levels

Total

Resource management

(17)

(18)

(19)

(20)

(21)

(22)

(23)

(24)

(25)

(26)

(27)

(28)

(29)

(30)

(31)

(32)

0
33
0
0
0
50
0
x(23)
67
0
83
0
0
33
100
67
50
33
0
100
67
0
17
100
m
100
67
67
33
83
0
100
0

33
17
67
0
0
a
0
a
a
67
a
a
a
a
a
a
a
a
a
0
33
0
0
a
m
0
a
a
50
a
100
0
33

a
0
0
0
17
0
0
0
0
0
0
a
a
a
0
0
0
0
a
0
0
0
0
a
m
0
0
a
0
a
a
0
a

a
0
0
0
0
a
0
0
0
0
0
0
a
a
a
a
a
a
a
0
0
0
0
a
m
0
a
a
0
a
a
0
a

a
0
17
17
0
17
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
m
0
0
0
0
17
0
0
67

67
50
17
83
83
0
67
x(23)
0
33
0
83
100
17
0
33
50
0
100
0
0
100
33
0
m
0
33
33
0
0
0
0
0

0
0
0
0
0
33
33
100d
33
0
17
17
0
50
0
0
0
67
0
0
0
0
50
0
m
0
0
0
17
0
0
0
0

100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
m
100
100
100
100
100
100
100
100

0
13
0
0
0
0
0
0
38
0
50
0
0
50
75
50
0
25
38
100
63
0
0
0
m
100
25
50
0
0
0
75
0

25
38
0
0
0
a
0
a
a
50
a
a
a
a
a
a
a
a
a
0
38
0
0
a
m
0
a
a
63
a
0
0
0

a
0
0
0
0
0
0
0
63
25
0
a
a
a
0
13
50
25
a
0
0
0
0
a
m
0
0
a
38
a
a
25
a

a
0
0
0
0
a
0
0
0
25
0
50
a
a
a
a
a
a
a
0
0
0
0
a
m
0
a
a
0
a
a
0
a

a
0
100
50
63
38
0
x(31)
0
0
0
0
25
0
0
0
0
0
25
0
0
0
0
75
m
0
25
0
0
50
50
0
88

75
50
0
0
38
50
50
x(31)
0
0
0
25
75
50
25
13
0
25
38
0
0
100
50
25
m
0
50
50
0
50
0
0
13

0
0
0
50
0
13
50
100d
0
0
50
25
0
0
0
25
50
25
0
0
0
0
50
0
m
0
0
0
0
0
50
0
0

100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
m
100
100
100
100
100
100
100
100

Flemish Comm. (Belgium)
French Comm. (Belgium)
England (UK)
Scotland (UK)

0
0
0
0

33
33
a
a

0
0
a
a

0
a
a
a

0
0
0
0

67
17
17
100

0
50
83
0

100
100
100
100

0
0
0
0

50
50
a
a

0
0
a
a

0
a
a
a

0
0
25
50

50
25
75
50

0
25
0
0

100
100
100
100

OECD average
EU22 average

35
34

13
9

0
1

0
0

4
1

33
36

15
19

100
100

21
22

9
11

7
6

2
3

18
12

29
33

14
13

100
100

Argentina
Brazil
China
Colombia
Costa Rica
India
Indonesia
Lithuania
Russian Federation
Saudi Arabia
South Africa

m
m
m
m
m
m
m
50
100
m
m

m
m
m
m
m
m
m
a
a
m
m

m
m
m
m
m
m
m
a
0
m
m

m
m
m
m
m
m
m
0
a
m
m

m
m
m
m
m
m
m
0
0
m
m

m
m
m
m
m
m
m
50
0
m
m

m
m
m
m
m
m
m
0
0
m
m

m
m
m
m
m
m
m
100
100
m
m

m
m
m
m
m
m
m
0
0
m
m

m
m
m
m
m
m
m
a
a
m
m

m
m
m
m
m
m
m
a
75
m
m

m
m
m
m
m
m
m
0
a
m
m

m
m
m
m
m
m
m
50
0
m
m

m
m
m
m
m
m
m
50
25
m
m

m
m
m
m
m
m
m
0
0
m
m

m
m
m
m
m
m
m
100
100
m
m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

Countries

Australia
Austria
Canada
Chile
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United States
Economies

Other G20

D6

OECD

Planning and structures

G20 average

Note: See Definitions and Methodology sections for more information.
Source: OECD (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933805895

420 Education at a Glance 2018: OECD Indicators   © OECD 2018

Who makes key decisions in education systems? – INDICATOR D6

chapter D

Under embargo until 11/09/2018 at 11.00am CEST
Table D6.3. Percentage of decisions taken at the local and school levels in public lower secondary

education, by mode of decision making (2017)

Other

Total decisions taken
at the local or school levels
Decisions taken at other levels after
consultation with local or school
levels1
Total decisions taken at the local
or school levels or after consultation
with the local or school levels

In full autonomy

After consultation with other bodies
in the educational system
Within framework set
by a higher authority

Other

Total decisions taken
at the school level

Decisions taken at other levels after
consultation with school level1

Total decisions taken at the local
or school levels or after consultation
with the school level

In full autonomy

After consultation with other bodies
in the educational system
Within framework set
by a higher authority

Other

Total decisions taken
at the local level

Decisions taken at other levels after
consultation with the local level1

Total decisions taken at the local
or school levels or after consultation
with the local level

Decisions taken at the local level

After consultation with other bodies
in the educational system
Within framework set
by a higher authority

Decisions taken at the school level

In full autonomy
OECD

Decisions taken at the local or school levels

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(11)

(12)

(13)

(14)

(15)

(16)

(18)

(19)

(20)

(21)

6
3
23
8
29
2
21
50
2
0
0
3
50
0
6
11
8
8
0
8
0
44
15
18
m
4
35
6
8
47
6
0
8

0
11
0
0
0
17
0
0
0
0
8
0
0
0
10
0
0
0
0
0
17
0
0
3
m
0
8
4
0
0
19
0
54

46
31
44
71
65
32
50
33
8
17
8
26
29
46
10
19
33
15
82
0
0
40
38
23
m
10
8
40
2
24
13
8
23

0
0
0
0
0
0
0
17
0
0
0
0
13
0
0
0
0
0
0
8
0
8
0
0
m
0
0
0
0
0
0
0
2

52
46
67
79
94
51
71
100
10
17
17
29
92
46
27
30
42
23
82
17
17
92
52
44
m
15
52
50
10
71
38
8
88

15
0
0
0
0
0
0
0
3
0
0
2
0
0
4
0
8
0
6
13
0
0
0
0
m
4
6
6
6
0
2
0
2

67
46
67
79
94
51
71
100
14
17
17
31
92
46
31
30
50
23
89
29
17
92
52
44
m
19
58
56
17
71
40
8
90

6
0
46
0 52
3
11
31
0 46
0
0
15
0 15
8
0
40
0 48
16
0
52
0 68
0
8
21
0 29
15
0
44
0 58
x(1) x(2) x(3) x(4) x(5)
2
0
8
0 10
0
0
17
0 17
0
0
8
0
8
3
0
26
0 29
31
0
29
0 60
0
0
46
0 46
6
2
10
0 19
11
0
19
0 30
0
0
21
0 21
8
0
6
0 15
0
0
64
0 64
8
0
0
8 17
0
17
0
0 17
44
0
40
8 92
15
0
38
0 52
0
0
15
0 15
m
m
m
m
m
4
0
10
0 15
29
6
8
0 44
6
4
40
0 50
8
0
2
0 10
25
0
10
0 35
0
0
8
0
8
0
0
8
0
8
0
7
8
0 16

15
0
0
0
0
8
0
x(6)
3
0
0
2
0
0
10
0
0
0
0
13
0
0
0
3
m
4
2
6
6
0
19
0
13

67
46
15
48
68
38
58
x(7)
14
17
8
31
60
46
29
30
21
15
64
29
17
92
52
18
m
19
46
56
17
35
27
8
28

0
0
0
0
0
0
0
0
0
0
23
0
29
0 52
0
0
31
0 31
14
0
13
0 26
2
8
11
0 22
6
0
6
0 13
x(1) x(2) x(3) x(4) x(5)
0
0
0
0
0
0
0
0
0
0
0
8
0
0
8
0
0
0
0
0
19
0
0
13 31
0
0
0
0
0
0
8
0
0
8
0
0
0
0
0
8
0
13
0 21
0
0
8
0
8
0
0
19
0 19
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
18
3
8
0 29
m
m
m
m
m
0
0
0
0
0
6
2
0
0
8
0
0
0
0
0
0
0
0
0
0
22
0
14
0 35
6
19
4
0 29
0
0
0
0
0
8
47
15
2 72

0
0
0
0
0
8
0
x(6)
0
0
0
0
0
0
2
0
8
0
6
0
17
0
0
0
m
0
13
0
0
0
2
0
9

0
0
52
31
26
30
13
x(7)
0
0
8
0
31
0
10
0
29
8
25
0
17
0
0
29
m
0
21
0
0
35
31
0
81

Flemish Comm. (Belgium)
French Comm. (Belgium)
England (UK)
Scotland (UK)

21
0
54
23

0
0
4
10

42
27
13
58

0
0
0
0

63
27
71
92

0
0
0
8

63
27
71
100

21
0
48
15

0
0
4
0

42
27
13
33

0
0
0
0

63
27
65
48

0
0
0
10

63
27
65
58

0
0
6
8

0
0
0
10

0
0
0
25

0
0
0
0

0
0
6
44

0
0
4
8

0
0
10
52

OECD average
EU22 average

15
16

5
3

29
30

1
1

49
50

2
2

52
52

10
11

2
1

23
24

0
1

35
38

3
2

38
40

4
3

3
1

6
4

0
0

13
8

2
2

15
9

Argentina
Brazil
China
Colombia
Costa Rica
India
Indonesia
Lithuania
Russian Federation
Saudi Arabia
South Africa

m
m
m
m
m
m
m
23
31
m
m

m
m
m
m
m
m
m
0
2
m
m

m
m
m
m
m
m
m
46
0
m
m

m
m
m
m
m
m
m
0
0
m
m

m
m
m
m
m
m
m
69
33
m
m

m
m
m
m
m
m
m
0
0
m
m

m
m
m
m
m
m
m
69
33
m
m

m
m
m
m
m
m
m
23
23
m
m

m
m
m
m
m
m
m
0
0
m
m

m
m
m
m
m
m
m
19
0
m
m

m
m
m
m
m
m
m
0
0
m
m

m
m
m
m
m
m
m
42
23
m
m

m
m
m
m
m
m
m
0
0
m
m

m
m
m
m
m
m
m
42
23
m
m

m
m
m
m
m
m
m
0
8
m
m

m
m
m
m
m
m
m
0
2
m
m

m
m
m
m
m
m
m
27
0
m
m

m
m
m
m
m
m
m
0
0
m
m

m
m
m
m
m
m
m
27
10
m
m

m
m
m
m
m
m
m
0
0
m
m

m
m
m
m
m
m
m
27
10
m
m

G20 average

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

(10)

(17)

Countries

Australia
Austria
Canada
Chile
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United States

Partners

Economies

Note: See Definitions and Methodology sections for more information.
1. Number of decisions taken at other levels but in consultation with local or schools levels as a percentage of all decisions.
Source: OECD (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933805914

Education at a Glance 2018: OECD Indicators   © OECD 2018

421

D6

Under embargo until 11/09/2018 at 11.00am CEST

Under embargo until 11/09/2018 at 11.00am CEST

Annex

1

Characteristics
of Education Systems
All tables in Annex 1 are available on line at:
1 2 https://doi.org/10.1787/888933806009

Note regarding data from Israel
The statistical data for Israel are supplied by and are under the responsibility of the relevant Israeli authorities. The use
of such data by the OECD is without prejudice to the status of the Golan Heights, East Jerusalem and Israeli settlements
in the West Bank under the terms of international law.

Education at a Glance 2018: OECD Indicators   © OECD 2018

423

Annex 1

Characteristics of education systems

Under embargo until 11/09/2018 at 11.00am CEST
Table X1.1a. [1/2] Typical graduation ages, by level of education (2016)
The typical age refers to the age of the students at the beginning of the school year;
students will generally be one year older than the age indicated when they graduate at the end of the school year.
The typical age is used for the gross graduation rate calculation.
Upper secondary level

Post-secondary non-tertiary level

Tertiary level
Short-cycle tertiary
(ISCED 5)

General
programmes

Vocational
programmes

General
programmes

Vocational
programmes

General
programmes

Vocational
programmes

(1)

(2)

(3)

(4)

(5)

(6)

OECD

1
Australia
Austria
Belgium
Canada
Chile
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United Kingdom
United States

17-18
17-18
18-18
17-18
17-17
19-20
18-19
18-18
19-19
17-18
18-19
18-18
17-19
18-19
18-19
17-17
18-19
17-17
18-18
18-18
18-18
17-18
17-18
17-18
18-18
19-19
17-17
18-19
18-18
17-17
18-19
19-20
17-17
15-15
17-17

18-32
16-18
18-19
19-33
17-17
19-20
19-25
18-19
19-23
16-19
19-21
19-19
17-19
17-24
18-24
17-17
18-19
17-17
18-18
20-21
18-20
17-18
18-21
16-29
18-22
19-20
17-18
18-19
18-20
17-21
18-19
19-21
17-17
16-19
17-17

a
a
a
m
a
20-22
a
a
a
m
20-23
a
a
20-30
a
m
a
18-18
a
a
a
a
a
17-26
a
a
a
a
a
a
a
20-23
a
a
19-22

18-37
19-32
20-22
m
a
19-20
23-35
19-25
32-46
m
21-24
20-22
19-21
21-33
20-26
m
20-20
18-18
a
20-23
24-29
a
22-32
17-27
19-29
21-25
20-23
19-23
a
23-38
19-31
a
22-20
a
19-22

19-24
a
a
a
a
a
a
a
a
m
a
a
a
27-28
20-35
m
a
19-19
a
a
a
a
a
18-24
22-29
a
a
a
a
a
21-28
a
a
19-25
20-21

18-30
18-19
21-24
20-24
21-26
21-23
20-25
a
a
m
22-26
a
20-22
20-35
20-35
m
20-22
19-19
20-22
21-25
21-23
20-24
21-27
18-24
21-26
22-25
20-27
20-22
21-27
20-23
22-29
25-41
19-22
18-29
20-21

Partners

Annex

Argentina1
Brazil
China
Colombia
Costa Rica
India
Indonesia
Lithuania
Russian Federation
Saudi Arabia
South Africa1

17-18
16-17
17-18
16-17
16-17
17-17
17-19
18-18
17-18
17-18
17-18

17-20
16-18
17-20
16-17
17-18
18-18
17-19
19-24
17-18
17-20
17-20

a
a
a
18-20
a
a
a
a
a
a
a

a
18-26
a
m
a
21-21
a
21-22
18-19
a
a

20-22
19-27
20-22
19-24
18-20
a
a
a
a
20-22
20-22

20-24
19-26
20-24
19-24
m
a
21-29
a
19-20
20-24
20-20

1. Year of reference 2015.
Source: OECD (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933806028

424 Education at a Glance 2018: OECD Indicators   © OECD 2018

Characteristics of education systems

Annex 1

Under embargo until 11/09/2018 at 11.00am CEST
Table X1.1a. [2/2] Typical graduation ages, by level of education (2016)
The typical age refers to the age of the students at the beginning of the school year;
students will generally be one year older than the age indicated when they graduate at the end of the school year.
The typical age is used for the gross graduation rate calculation.
Tertiary level
Bachelor’s or equivalent
(ISCED 6)

Long first degree
(at least 5 years)

Second or
further degree,
(following
a bachelor’s
or equivalent
programme)

Second or
further degree,
(following
a master’s
or equivalent
programme)

Annex
Doctoral
or equivalent
(ISCED 8)

(7)

(8)

(9)

(10)

(11)

(12)

(13)

OECD

Second or
further degree,
(following
a bachelor’s
or equivalent
programme)

Australia
Austria
Belgium
Canada
Chile
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United Kingdom
United States

20-23
21-24
21-23
22-24
22-27
22-24
22-25
21-23
23-26
m
22-25
m
21-24
22-25
21-23
24-28
22-24
21-21
23-25
22-24
22-24
20-24
21-23
20-23
21-24
22-24
21-23
21-22
21-24
21-23
22-26
23-26
21-24
20-22
21-23

22-25
a
a
23-25
23-29
a
a
a
a
m
a
m
a
a
23-25
27-29
m
m
x(7)
23-25
a
x(7)
a
22-24
a
a
a
a
a
a
a
a
a
22-24
a

22-32
a
22-24
23-28
23-26
24-26
32-45
a
a
m
24-30
m
27-41
27-40
23-31
24-32
m
m
a
24-33
a
a
a
21-27
26-30
25-34
33-39
a
a
a
a
31-41
a
x(8)
a

a
23-27
a
22-24
25-26
25-26
25-27
24-25
26-28
m
24-27
a
23-26
25-26
22-30
m
24-27
23-23
a
25-29
a
a
a
a
24-26
24-25
23-24
24-25
25-31
22-25
24-28
23-25
23-25
x(11)
a

22-30
24-28
22-24
24-29
26-35
24-26
25-28
23-26
25-30
m
24-27
m
23-26
a
22-30
27-34
24-27
23-23
25-31
24-27
24-27
23-26
23-26
23-30
24-28
24-25
23-26
23-25
24-27
22-26
24-30
24-29
26-27
23-28
24-31

29-44
a
23-32
26-29
a
26-28
a
a
30-41
m
24-27
m
a
24-32
22-30
m
m
m
a
a
25-30
a
24-27
a
24-27
a
a
24-28
a
29-32
a
25-32
a
x(11)
24-31

26-35
28-32
27-31
29-34
29-35
29-33
27-39
28-33
30-37
26-30
28-32
m
27-34
28-35
27-32
31-37
27-35
26-26
28-37
28-36
28-32
24-28
28-31
27-35
28-35
29-32
27-36
26-29
32-40
28-35
28-34
29-33
29-34
25-32
26-32

Partners

First degree
(3-4 years)

Long first degree
(more than
4 years)

Master’s or equivalent
(ISCED 7)

Argentina1
Brazil
China
Colombia
Costa Rica
India
Indonesia
Lithuania
Russian Federation
Saudi Arabia
South Africa1

20-23
20-27
20-23
a
18-21
21-22
23-32
21-22
21-23
20-23
20-23

21-24
a
21-24
22-27
22-23
23-23
23-32
a
a
21-24
21-24

a
m
a
22-27
a
22-22
a
23-29
a
a
a

22-25
a
22-25
a
24-26
22-23
a
23-24
22-25
22-25
22-25

22-25
25-31
22-25
26-36
a
22-23
26-36
24-25
22-25
22-25
22-25

a
a
a
26-36
a
23-24
a
27-29
a
a
a

25-29
29-37
25-29
30-41
27-30
24-28
32-45
28-31
25-27
25-29
25-29

1. Year of reference 2015.
Source: OECD (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933806028

Education at a Glance 2018: OECD Indicators   © OECD 2018

425

1

Annex 1

Characteristics of education systems

Under embargo until 11/09/2018 at 11.00am CEST
Table X1.1b. Typical age of entry, by level of education (2016)
The typical age refers to the age of the students at the beginning of the school year.
Master’s or equivalent
(ISCED 7)

Doctoral or equivalent
(ISCED 8)

(1)

(2)

(3)

(4)

OECD

Annex

Bachelor’s or equivalent
(ISCED 6)

Australia
Austria
Belgium
Canada
Chile
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United Kingdom
United States

m
17-18
18-20
m
18-21
19-21
19-26
a
a
18-19
22-26
m
19-21
20-31
18-29
18-24
19-21
18-18
18-18
19-23
19-21
18-19
20-24
17-25
20-24
19-30
18-20
19-20
19-21
18-20
19-26
18-25
18-20
17-29
18-22

18-20
19-21
18-19
m
18-19
19-20
20-22
19-22
19-21
18-19
19-21
18-18
19-20
20-22
18-19
21-25
19-19
18-18
18-18
19-22
19-21
18-19
18-20
18-20
19-20
19-20
18-19
19-20
19-19
18-18
19-21
19-23
18-20
18-21
18-20

21-26
19-24
21-22
m
18-30
22-24
23-25
22-27
22-30
20-23
19-24
22-28
19-23
23-31
21-26
25-34
20-24
22-23
22-27
22-25
22-27
21-34
22-24
21-28
19-24
19-23
18-23
22-23
22-24
18-23
19-24
22-25
23-27
21-30
22-28

22-30
25-29
24-27
m
25-31
24-28
25-29
24-28
26-32
23-26
25-29
24-32
24-27
25-33
22-27
26-34
25-28
24-28
23-32
24-30
25-28
25-39
23-27
22-30
25-31
24-26
23-33
24-25
24-28
23-30
24-30
25-28
25-29
22-28
22-27

Partners

Short-cycle tertiary
(ISCED 5)

Argentina1
Brazil
China
Colombia
Costa Rica
India
Indonesia
Lithuania
Russian Federation
Saudi Arabia
South Africa1

18-19
m
18-19
17-21
17-18
a
20-23
a
17-18
18-19
18-19

18-20
m
18-20
17-21
17-18
18-18
20-26
19-19
17-20
18-20
18-20

21-24
m
21-24
22-33
m
21-22
24-32
23-26
21-24
21-24
21-24

23-26
m
23-26
25-36
m
23-23
27-33
25-28
23-26
23-26
23-26

1

1. Year of reference 2015.
Source: OECD (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933806047

426 Education at a Glance 2018: OECD Indicators   © OECD 2018

Characteristics of education systems

Annex 1

Under embargo until 11/09/2018 at 11.00am CEST
Table X1.2a. School year and financial year used for the calculation of indicators, OECD countries
Financial year

School year

OECD

2014
2015
2016
2017
Month 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6
Australia
Austria
Belgium

Annex

Canada
Chile
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United Kingdom
United States
Month 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6
2014
2015
2016
2017
Source: OECD (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933806066

Education at a Glance 2018: OECD Indicators   © OECD 2018

427

1

Annex 1

Characteristics of education systems

Under embargo until 11/09/2018 at 11.00am CEST
Table X1.2b. School year and financial year used for the calculation of indicators, partner countries
Financial year

School year

Partners

2014
2015
2016
2017
Month 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6

Annex

1

Argentina
Brazil
China
Colombia
Costa Rica
India
Indonesia
Lithuania
Russian Federation
Saudi Arabia
South Africa
Month 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6
2014
2015
2016
2017
Source: OECD (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
1 2 https://doi.org/10.1787/888933806085

428 Education at a Glance 2018: OECD Indicators   © OECD 2018

Characteristics of education systems

Annex 1

Under embargo until 11/09/2018 at 11.00am CEST
Table X1.3. Starting and ending age for students in compulsory education and starting age for students

in primary education (2016)

The typical age refers to the age of the students at the beginning of the school year.
Primary
(ISCED 1)

Starting age

Ending age

Starting age

(1)

(2)

(3)

OECD

Australia
Austria
Belgium
Canada
Chile
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United Kingdom
United States

6
6
6
6
6
6
6
7
7
6
6
5
3
6
6
3
6
6
6
5
4
3
5
5
6
5
6
6
6
6
7
4-5
5-6
4-5
4-6

17
15
18
16-18
18
15
16
16
16
16
18
14-15
16
16
16
17
16
15
14
16
16
17
18
16
16
16
18
16
14
16
16
15
17
16
17

5
6
6
6
6
6
6
7
7
6
6
6
7
6
5
6
6
6
6
7
6
6
6
5
6
7
6
6
6
6
7
6
6
5
6

Partners

Compulsory education

Argentina1
Brazil
China
Colombia
Costa Rica
India
Indonesia
Lithuania
Russian Federation
Saudi Arabia
South Africa1

5
4
m
5
m
m
7
7
7
6
7

17
17
m
15
m
m
15
16
17
11
15

m
6
6
m
m
6
m
7
7
m
m

Annex

Notes: Age refers to the age at the beginning of the school year.
Ending age of compulsory education is the age at which compulsory schooling ends. For example, an ending age of 18 indicates that all students under 18 are legally
obliged to participate in education.
1. Year of reference 2015.
Source: OECD (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933806104

Education at a Glance 2018: OECD Indicators   © OECD 2018

429

1

Under embargo until 11/09/2018 at 11.00am CEST

Under embargo until 11/09/2018 at 11.00am CEST

Annex

2

Reference Statistics
All tables in Annex 2 are available on line at:
1 2 https://doi.org/10.1787/888933806123

Note regarding data from Israel
The statistical data for Israel are supplied by and are under the responsibility of the relevant Israeli authorities. The use
of such data by the OECD is without prejudice to the status of the Golan Heights, East Jerusalem and Israeli settlements
in the West Bank under the terms of international law.

Education at a Glance 2018: OECD Indicators   © OECD 2018

431

Annex 2

Reference statistics

Under embargo until 11/09/2018 at 11.00am CEST
Table X2.1. Basic reference statistics (reference period: calendar year 2015 and 2016)
2015

2016

Total
government Gross domestic
Gross domestic
product
Purchasing
expenditure
product
power parity
(in millions of (in millions of
Total population GDP deflator
(adjusted to in thousands on (2010 = 100,
for GDP (PPP)
local currency, local currency,
(USD = 1)
current prices) current prices) financial year)1 1st January constant prices)
OECD

(1)

2

Partners

Annex

Australia
Austria
Belgium
Canada
Chile3
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Luxembourg
Mexico
Netherlands
New Zealand
Norway4

(2)

(3)

592 151

1 659 604

1 640 504

175 632

344 493

220 858

410 435

724 310

(6)

Gross domestic Gross domestic
product per
product per
capita
capita
(in equivalent (in equivalent
USD converted USD converted
using PPPs)2
using PPPs)2

(4)

(5)

(7)

(8)

23 778

102

1.5

47 454

48 789

344 493

8 576

110

0.8

50 269

50 792

410 435

11 237

107

0.8

45 580

46 541

1 994 911

2 005 060

35 886

107

1.2

44 581

44 825

42 811 545

167 227 448

167 227 448

18 192

122

402.6

22 834

22 834

1 916 390

4 595 783

4 595 783

10 538

107

13.0

33 493

34 790

1 110 402

2 027 108

2 027 108

5 660

106

7.3

48 879

49 207

8 185

20 348

20 348

1 315

116

0.5

28 701

29 740

119 759

209 604

209 604

5 472

112

0.9

42 131

43 441

1 243 414

2 194 243

2 194 243

66 488

105

0.8

40 551

41 425

1 334 874

3 043 650

3 043 650

81 198

109

0.8

48 099

49 046

94 885

176 312

176 312

10 858

95

0.6

26 606

26 746

17 226 168

34 324 110

34 324 110

9 856

115

133.4

26 114

26 656

949 126

2 232 362

2 232 362

329

120

142.2

47 691

51 103

75 572

262 037

262 037

4 629

110

0.8

69 658

71 851

462 289

1 162 530

1 162 530

8 297

112

3.9

36 249

37 622

830 126

1 652 622

1 652 622

60 796

106

0.7

36 601

38 356

209 545 400

531 985 800

533 600 800

127 083

101

102.8

40 736

42 248

505 139 400

1 564 123 900

1 564 123 900

51 015

107

870.9

35 204

36 532

9 022

24 320

24 320

1 986

114

0.5

24 404

25 465
103 414

21 604

52 102

52 102

563

113

0.9

103 727

4 917 247

18 536 531

18 536 531

119 713

120

8.5

18 129

18 729

306 759

683 457

683 457

16 901

104

0.8

49 643

50 691
38 565

73 929

251 755

255 245

4 596

108

1.5

37 426

1 521 635

2 621 032

2 621 032

5 166

110

9.7

52 121

51 501

Poland

747 949

1 799 392

1 799 392

38 006

107

1.8

26 581

27 385

Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United Kingdom
United States

86 669

179 809

179 809

10 375

104

0.6

29 485

30 612

35 692

78 896

78 896

5 421

103

0.5

29 535

30 486

18 541

38 837

38 837

2 063

105

0.6

31 478

32 737

472 740

1 079 998

1 079 998

46 450

101

0.7

34 815

36 340

2 084 437

4 199 860

4 199 860

9 747

107

8.9

48 146

49 262

222 498

653 735

653 735

8 238

99

1.2

63 994

64 236

804 987

2 338 647

2 338 647

77 696

143

1.2

25 029

25 495

800 404

1 888 737

1 907 381

64 875

108

0.7

41 742

42 795

6 814 719

18 120 714

17 774 162

319 528

109

1.0

56 711

57 920

2 315 082

5 854 014

5 854 014

43 417

328

6.6

20 338

m

1 914 809

6 000 570

6 000 570

204 860

145

1.9

15 699

15 301

Argentina
Brazil
China
Colombia3
Costa Rica3
India
Indonesia
Lithuania
Russian Federation
Saudi Arabia
South Africa

21 896 915

68 550 575

68 550 575

1 376 049

114

3.5

14 323

m

262 484 880

799 312 000

799 312 000

48 203

117

1 198.7

13 833

13 833

9 619 594

29 281 362

29 281 362

4 832

125

384.0

15 781

15 781

37 557 086

135 760 859

135 760 859

1 311 051

130

17.1

6 070

m

2 002 221 328

11 526 332 800

11 526 332 800

257 564

128

4 046.5

11 059

m

13 058

37 427

37 427

2 921

111

0.4

28 622

29 652

28 690 533

83 232 618

83 232 618

146 267

155

23.0

24 715

24 811

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

1. For countries where GDP is not reported for the same reference period as data on educational finance, GDP is estimated as: wt-1 (GDPt - 1) + wt (GDPt), where wt
and wt-1 are the weights for the respective portions of the two reference periods for GDP which fall within the educational financial year. Adjustments were made in
Chapter C for Australia, Canada, Japan, New Zealand, the United Kingdom and the United States.
2. These data are used in Indicator C7 in order to calculate salary costs of teachers per student as a percentage of GDP per capita.
3. Year of reference 2016 instead of 2015.
4. The GDP Mainland market value is used for Norway.
Source: OECD (2018). See Source section for more information and Annex 3 for notes (http:/http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933806142

432 Education at a Glance 2018: OECD Indicators   © OECD 2018

Reference statistics

Annex 2

Under embargo until 11/09/2018 at 11.00am CEST
Table X2.2. [1/2] GDP and total public expenditure
(reference period: calendar year 2005, 2010 to 2015, current prices)

OECD

Gross domestic product (in millions of local currency, current prices)
2010

2011

2012

2013

2014

(1)

(2)

(3)

(4)

(5)

(6)

2015
(7)

Australia

958 536

1 356 649

1 455 510

1 515 341

1 564 829

1 608 590

1 640 504

Austria

254 075

295 897

310 129

318 653

323 910

333 063

344 493

Belgium

311 481

365 101

379 106

387 500

392 340

400 288

410 435

Canada

1 435 823

1 689 078

1 783 143

1 841 489

1 920 694

1 991 365

2 005 060

Chile1

68 831 705

111 508 611

122 006 090

129 947 342

137 876 216

148 855 347

158 636 806

Czech Republic

3 264 931

3 962 464

4 033 755

4 059 912

4 098 128

4 313 789

4 595 783

Denmark

1 585 984

1 810 926

1 846 854

1 895 002

1 929 677

1 981 165

2 027 108

Estonia

11 262

14 717

16 668

17 935

18 932

19 766

20 348

Finland

164 387

187 100

196 869

199 793

203 338

205 474

209 604

France

1 771 978

1 998 481

2 059 284

2 086 929

2 115 256

2 147 609

2 194 243

Germany

2 300 860

2 580 060

2 703 120

2 758 260

2 826 240

2 932 470

3 043 650

Greece

199 242

226 031

207 029

191 204

180 654

178 656

176 312

Hungary

22 559 880

27 224 599

28 304 938

28 781 064

30 247 077

32 591 713

34 324 110

Iceland

1 051 258

1 627 108

1 708 315

1 787 684

1 899 680

2 019 038

2 232 362

Ireland

170 188

167 583

171 939

175 561

180 298

194 537

262 037

Israel

639 333

873 466

936 134

992 110

1 056 119

1 103 485

1 162 530

Italy

1 489 726

1 604 515

1 637 463

1 613 265

1 604 599

1 621 827

1 652 622

Japan

524 819 525

498 117 550

492 295 675

497 011 800

505 850 700

518 403 450

533 600 800

Korea

919 797 300

1 265 308 000

1 332 681 000

1 377 456 700

1 429 445 400

1 486 079 300

1 564 123 900

Latvia

13 597

17 938

20 303

21 886

22 787

23 618

24 320

Luxembourg

30 031

40 178

43 165

44 112

46 500

49 993

52 102

9 562 648

13 366 377

14 665 576

15 817 755

16 277 187

17 471 467

18 536 531

Netherlands

545 609

631 512

642 929

645 164

652 748

663 008

683 457

New Zealand

165 230

205 885

214 299

221 185

234 725

244 385

255 245

Norway2

1 514 363

2 077 603

2 161 616

2 298 445

2 423 242

2 539 596

2 621 032

Poland

990 468

1 445 298

1 566 824

1 629 425

1 656 895

1 719 769

1 799 392

Portugal

158 653

179 930

176 167

168 398

170 269

173 079

179 809

Slovak Republic

50 415

67 577

70 627

72 704

74 170

76 088

78 896

Slovenia

29 227

36 252

36 896

36 076

36 239

37 615

38 837

Spain

930 566

1 080 935

1 070 449

1 039 815

1 025 693

1 037 820

1 079 998

Sweden

4 199 860

Mexico

Partners

2005

2 907 352

3 519 994

3 656 577

3 684 800

3 769 909

3 936 840

Switzerland

508 900

608 831

621 256

626 414

638 177

649 718

653 735

Turkey

673 703

1 160 014

1 394 477

1 569 672

1 809 713

2 044 466

2 338 647

United Kingdom

1 405 648

1 593 673

1 647 603

1 702 057

1 773 681

1 849 981

1 907 381

United States

12 684 327

14 691 556

15 241 149

15 836 590

16 423 386

17 059 563

17 774 162
5 854 014

Argentina

582 538

1 661 721

2 179 024

2 637 914

3 348 308

4 579 086

Brazil

2 170 585

3 885 847

4 376 382

4 814 760

5 331 619

5 778 953

6 000 570

China

18 731 890

41 303 031

48 930 057

54 036 743

59 524 441

64 397 405

68 550 575

Colombia1

340 156 000

544 924 000

619 894 000

664 240 000

710 497 000

757 065 000

799 312 000

Costa Rica1

9 532 875

19 596 937

21 370 733

23 371 406

24 860 944

27 226 883

29 281 362

India

36 924 856

75 476 617

87 360 392

99 513 443

112 727 645

124 882 048

135 760 859

Indonesia

3 035 611 121

6 864 133 100

7 831 726 000

8 615 704 500

9 546 134 000

10 569 705 300

11 526 332 800

Lithuania

21 002

28 028

31 275

33 348

34 960

36 568

37 427

23 275 971

49 879 129

60 282 540

68 163 883

73 133 895

79 199 659

83 232 618

Saudi Arabia

m

m

m

m

m

m

m

South Africa

m

m

m

m

m

m

m

Russian Federation

1. Year of reference 2016 instead of 2015.
2. The GDP Mainland market value is used for Norway.
Source: OECD (2018). See Source section for more information and Annex 3 for notes (http:/http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933806161

Education at a Glance 2018: OECD Indicators   © OECD 2018

433

Annex

2

Annex 2

Reference statistics

Under embargo until 11/09/2018 at 11.00am CEST
Table X2.2. [2/2] GDP and total public expenditure
(reference period: calendar year 2005, 2010 to 2015, current prices)

OECD

Total government expenditure (in millions of local currency, current prices)

2

2010

2011

2012

2013

2014

2015

(8)

(9)

(10)

(11)

(12)

(13)

(14)

Australia

324 216

473 572

505 042

531 994

552 731

574 014

592 151

Austria

129 973

156 351

157 846

163 192

167 292

174 305

175 632

Belgium

160 811

194 749

206 433

216 479

219 062

220 981

220 858

Canada

m

641 141

665 215

675 081

689 601

703 778

724 310

Chile1

15 312 072

26 053 547

27 837 793

30 050 204

31 845 155

35 343 504

39 747 891

Czech Republic

1 380 188

1 724 241

1 735 916

1 805 836

1 745 908

1 821 984

1 916 390

812 682

1 026 310

1 042 167

1 098 247

1 077 153

1 093 954

1 110 402

Denmark
Estonia

3 827

5 962

6 238

7 049

7 280

7 597

8 185

Finland

81 002

102 446

107 066

112 291

116 922

119 399

119 759

France

936 988

1 128 022

1 152 416

1 185 751

1 206 724

1 225 643

1 243 414

Germany

1 062 999

1 219 219

1 208 565

1 221 782

1 263 000

1 298 801

1 334 874

Greece

90 778

118 616

111 973

105 923

112 318

89 629

94 885

Hungary

11 132 600

13 404 755

13 996 199

13 950 163

14 902 529

16 132 659

17 226 168

Iceland

437 351

799 305

777 342

807 229

830 530

908 485

949 126

Ireland

56 746

109 088

79 623

73 603

72 533

73 042

75 572

Israel

294 161

361 871

380 492

412 854

436 214

451 097

462 289

Italy

702 315

800 494

808 562

818 874

819 381

825 565

830 126

Japan

186 135 200

198 184 200

201 021 000

201 405 100

205 447 200

207 024 900

209 545 400

Korea

271 192 000

392 264 100

431 075 500

450 811 900

453 991 400

475 250 100

505 139 400

Latvia

4 662

8 034

7 927

8 112

8 427

8 854

9 022

Luxembourg

13 087

17 729

18 287

19 440

20 145

20 895

21 604

Mexico

1 979 808

3 355 288

3 655 757

3 942 261

4 206 351

4 566 809

4 917 247

Netherlands

230 867

304 107

302 010

303 865

302 036

306 204

306 759

New Zealand

49 084

70 099

68 939

69 962

71 174

72 363

73 929

Norway2

836 626

1 165 722

1 223 268

1 273 053

1 352 217

1 440 795

1 521 635

Poland

439 719

662 055

687 518

698 362

705 750

726 797

747 949

Portugal

74 054

93 237

88 112

81 719

85 032

89 598

86 669

Slovak Republic

20 053

28 480

28 828

29 539

30 737

31 983

35 692

Slovenia

13 127

17 858

18 448

17 503

21 568

18 656

18 541

Spain

356 547

493 202

490 592

500 177

467 326

465 424

472 740

Sweden

1 522 630

1 788 594

1 839 764

1 892 405

1 960 578

2 012 799

2 084 437

171 949

200 808

204 384

208 135

218 434

219 440

222 498

m

442 178

490 770

550 332

623 671

689 007

804 987

Switzerland
Turkey

Partners

Annex

2005

United Kingdom

573 271

754 886

755 024

774 632

773 965

793 200

800 404

United States

4 772 092

6 425 237

6 492 089

6 466 040

6 465 937

6 633 256

6 814 719
2 315 082

Argentina

142 219

527 111

722 171

919 573

1 192 696

1 668 167

Brazil

605 877

1 211 373

1 308 035

1 453 358

1 772 570

1 886 133

1 914 809

China

3 427 928

10 251 183

13 128 594

15 178 679

17 034 245

18 745 463

21 896 915

Colombia1

87 471 638

164 741 238

188 068 418

205 412 910

224 872 398

243 490 503

262 484 880

Costa Rica1

m

m

m

7 302 493

8 148 822

8 910 394

9 619 594

9 761 839

21 365 301

24 147 724

27 210 645

29 881 105

32 810 323

37 557 086

Indonesia

526 114 278

1 159 098 284

1 387 241 117

1 622 837 246

1 821 515 839

1 966 625 285

2 002 221 328

Lithuania

7 157

11 855

13 284

12 040

12 408

12 667

13 058

6 820 645

17 616 656

21 283 675

23 824 124

26 179 360

30 546 927

28 690 533

Saudi Arabia

m

m

m

m

m

m

m

South Africa

m

m

m

m

m

m

m

India

Russian Federation

1. Year of reference 2016 instead of 2015.
2. The GDP Mainland market value is used for Norway.
Source: OECD (2018). See Source section for more information and Annex 3 for notes (http:/http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933806161

434 Education at a Glance 2018: OECD Indicators   © OECD 2018

Reference statistics

Annex 2

Under embargo until 11/09/2018 at 11.00am CEST
Table X2.3. [1/2] Basic reference statistics
(reference period: calendar year 2005, 2010 to 2015, in 2010 constant prices)

OECD

Gross domestic product (in millions of local currency, constant prices)
2005

2010

2011

2012

2013

2014

(1)

(2)

(3)

(4)

(5)

(6)

(7)

Australia

1 187 601

1 356 649

1 428 729

1 489 812

1 516 627

1 570 474

1 609 007

Austria

277 307

295 897

304 545

306 617

306 696

309 237

312 614

Belgium

340 164

365 101

371 666

372 539

373 286

378 331

383 645

Canada

1 591 344

1 689 078

1 727 148

1 762 140

1 809 254

1 839 571

1 866 327

Chile1

92 687 960

111 508 611

118 322 811

124 615 961

129 656 682

132 132 727

135 109 066

Czech Republic

3 512 515

3 962 464

4 032 910

4 000 653

3 981 303

4 089 400

4 306 516

Denmark

1 791 959

1 810 926

1 835 134

1 839 290

1 856 457

1 886 520

1 916 829

Estonia

15 018

14 717

15 835

16 517

16 836

17 323

17 613

Finland

179 646

187 100

191 910

189 173

187 739

186 553

186 805

France

1 923 243

1 998 481

2 040 034

2 043 761

2 055 538

2 075 016

2 097 166

Germany

2 426 546

2 580 060

2 674 490

2 687 649

2 700 807

2 752 924

2 800 913

Greece

229 784

226 031

205 389

190 395

184 223

185 586

185 046

Hungary

27 521 109

27 224 599

27 677 049

27 222 099

27 792 734

28 967 736

29 943 122

Iceland

1 545 404

1 627 108

1 659 049

1 680 935

1 753 353

1 790 562

1 866 912

Ireland

161 843

167 583

172 586

172 650

175 479

190 094

238 677

Israel

706 218

873 466

919 027

939 210

978 692

1 012 731

1 039 346

Italy

1 629 932

1 604 515

1 613 766

1 568 274

1 541 172

1 542 924

1 557 612

Japan

498 566 759

498 117 550

500 678 668

509 354 112

520 145 516

523 909 132

527 962 389

Korea

1 034 337 497

1 265 308 000

1 311 892 696

1 341 966 504

1 380 832 595

1 426 972 405

1 466 788 298

Latvia

18 380

17 938

19 083

19 852

20 335

20 713

21 328

Luxembourg

35 606

40 178

41 198

41 053

42 553

45 009

46 297

12 417 875

13 366 377

13 855 989

14 360 668

14 555 125

14 969 260

15 458 825

Netherlands

592 793

631 512

642 018

635 232

634 023

643 024

657 561

New Zealand

191 302

205 885

209 949

217 792

220 429

227 140

235 555

Norway2

1 882 830

2 077 603

2 024 913

2 083 154

2 141 763

2 237 224

2 376 009

Poland

1 145 116

1 445 298

1 517 813

1 542 218

1 563 684

1 615 022

1 677 113

Portugal

174 509

179 930

176 643

169 527

167 611

169 108

172 190

Slovak Republic

53 590

67 577

69 482

70 634

71 687

73 658

76 494

Slovenia

33 274

36 252

36 488

35 514

35 112

36 158

36 975

Spain

1 025 389

1 080 935

1 070 139

1 038 808

1 021 089

1 035 180

1 070 710

Sweden

3 912 435

Mexico

Partners

2015

3 253 794

3 519 994

3 613 781

3 603 434

3 648 160

3 743 170

Switzerland

546 591

608 831

619 137

625 366

636 948

652 548

660 551

Turkey

989 036

1 160 014

1 288 932

1 350 671

1 465 361

1 541 071

1 634 859

United Kingdom

1 575 072

1 593 673

1 615 120

1 642 816

1 679 964

1 722 682

1 768 065

United States

13 957 599

14 691 556

14 932 841

15 235 590

15 549 000

15 866 554

16 353 832

Argentina

1 308 651

1 661 721

1 761 490

1 743 410

1 785 344

1 740 485

1 786 561

Brazil

3 127 392

3 885 847

4 037 996

4 122 713

4 251 305

4 311 976

4 146 837

China

24 169 867

41 303 031

45 242 986

48 797 624

52 583 542

56 419 444

60 321 214

Colombia1

436 551 119

544 924 000

580 831 828

604 320 345

633 775 311

661 620 916

681 813 696

Costa Rica1

15 532 812

19 596 937

20 440 997

21 421 535

21 907 595

22 677 722

23 501 306

India

52 200 696

75 476 617

80 487 029

85 009 244

90 652 848

97 219 261

104 572 311

Indonesia

5 181 384 704

6 864 133 100

7 287 635 302

7 727 083 416

8 156 497 772

8 564 866 594

8 982 517 102

Lithuania

26 436

28 028

29 721

30 859

31 938

33 068

33 741

Russian Federation

41 911 235

49 879 129

52 006 063

53 907 353

54 869 791

55 275 060

53 711 748

Saudi Arabia

1 488 298

1 975 543

2 172 286

2 289 252

2 350 373

2 444 841

2 545 236

South Africa

2 359 095

2 748 004

2 838 252

2 901 073

2 973 288

3 023 820

3 063 096

1. Year of reference 2016 instead of 2015.
2. The GDP Mainland market value is used for Norway.
Source: OECD (2018). See Source section for more information and Annex 3 for notes (http:/http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933806180

Education at a Glance 2018: OECD Indicators   © OECD 2018

435

Annex

2

Annex 2

Reference statistics

Under embargo until 11/09/2018 at 11.00am CEST
Table X2.3. [2/2] Basic reference statistics
(reference period: calendar year 2005, 2010 to 2015, in 2010 constant prices)

OECD

Total government expenditure (in millions of local currency, constant prices)

2

2010

2011

2012

2013

2014

2015

(8)

(9)

(10)

(11)

(12)

(13)

(14)

Australia

401 695

473 572

495 749

523 031

535 705

560 412

580 781

Austria

141 858

156 351

155 004

157 028

158 401

161 837

159 379

Belgium

175 619

194 749

202 382

208 121

208 424

208 859

206 442

Canada

m

641 141

644 326

645 992

649 590

650 132

674 194

Chile1

20 619 055

26 053 547

26 997 389

28 817 327

29 946 696

31 372 965

33 852 802

Czech Republic

1 484 849

1 724 241

1 735 552

1 779 478

1 696 138

1 727 210

1 795 769

918 227

1 026 310

1 035 553

1 065 959

1 036 281

1 041 693

1 049 994

Denmark
Estonia

5 103

5 962

5 926

6 491

6 474

6 658

7 085

Finland

88 521

102 446

104 369

106 322

107 952

108 404

106 733

France

1 016 974

1 128 022

1 141 643

1 161 224

1 172 656

1 184 214

1 188 403

Germany

1 121 066

1 219 219

1 195 765

1 190 504

1 206 946

1 219 279

1 228 415

Greece

104 693

118 616

111 086

105 475

114 537

93 105

99 585

Hungary

13 580 812

13 404 755

13 685 721

13 194 534

13 693 291

14 338 817

15 027 491

Iceland

642 929

799 305

754 924

759 027

766 557

805 680

793 749

Ireland

53 964

109 088

79 922

72 383

70 595

71 374

68 835

Israel

324 935

361 871

373 539

390 841

404 234

413 998

413 304

Italy

768 414

800 494

796 861

796 037

786 992

785 400

782 401

Japan

176 824 259

198 184 200

204 444 060

206 406 600

211 252 925

209 223 599

207 331 192

Korea

304 962 903

392 264 100

424 351 214

439 196 723

438 551 989

456 347 638

473 704 520

Latvia

6 302

8 034

7 450

7 358

7 521

7 765

7 912

Luxembourg

15 517

17 729

17 454

18 092

18 435

18 812

19 197

Mexico

2 570 941

3 355 288

3 453 947

3 579 112

3 761 336

3 912 765

4 100 814

Netherlands

250 832

304 107

301 582

299 187

293 371

296 974

295 136

New Zealand

56 829

70 099

67 540

68 889

66 839

67 257

68 226

Norway2

1 040 190

1 165 722

1 145 907

1 153 808

1 195 146

1 269 249

1 379 388

Poland

508 375

662 055

666 012

660 986

666 047

682 529

697 121

Portugal

81 455

93 237

88 350

82 267

83 705

87 542

82 996

Slovak Republic

21 316

28 480

28 361

28 699

29 707

30 962

34 605

Slovenia

14 945

17 858

18 244

17 230

20 897

17 933

17 652

Spain

392 878

493 202

490 450

499 693

465 228

464 240

468 674

Sweden

1 704 068

1 788 594

1 818 232

1 850 618

1 897 261

1 913 781

1 941 785

184 684

200 808

203 687

207 786

218 013

220 395

224 817

m

442 178

453 625

473 550

504 999

519 358

562 736

Switzerland
Turkey

Partners

Annex

2005

United Kingdom

642 368

754 886

740 139

747 671

733 071

738 619

741 942

United States

5 251 122

6 425 237

6 360 763

6 220 653

6 121 688

6 169 379

6 270 156
706 530

Argentina

319 490

527 111

583 792

607 750

635 955

634 061

Brazil

872 952

1 211 373

1 206 897

1 244 460

1 413 405

1 407 341

m

China

4 423 075

10 251 183

12 139 303

13 707 034

15 047 952

16 423 156

19 268 234

Colombia1

112 259 791

164 741 238

176 217 423

186 883 055

200 589 973

212 793 366

223 899 786

Costa Rica1

m

m

m

6 693 248

7 180 786

7 421 614

7 720 714

India

13 800 319

21 365 301

22 247 823

23 244 662

24 029 663

25 542 465

28 929 040

Indonesia

898 007 144

1 159 098 284

1 290 865 811

1 455 458 317

1 556 356 728

1 593 600 080

1 560 339 063

Lithuania

9 009

11 855

12 624

11 141

11 336

11 454

11 772

12 281 406

17 616 656

18 361 538

18 841 289

19 641 454

21 319 325

18 514 600

Saudi Arabia

418 967

670 985

724 629

762 801

837 613

983 120

1 036 353

South Africa

664 631

864 157

876 365

909 994

939 433

961 656

1 007 104

Russian Federation

1. Year of reference 2016 instead of 2015.
2. The GDP Mainland market value is used for Norway.
Source: OECD (2018). See Source section for more information and Annex 3 for notes (http:/http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933806180

436 Education at a Glance 2018: OECD Indicators   © OECD 2018

Reference statistics

Annex 2

Under embargo until 11/09/2018 at 11.00am CEST
Table X2.4a. [1/2] Teachers’ statutory salaries at different points in their careers, for teachers with

the most prevalent qualifications defined at different points in the teachers’ career (2017)
Annual salaries in public institutions for teachers with the most prevalent qualifications, in national currency

OECD

Pre-primary

Primary

Starting salary

Salary after
10 years
of experience

Salary after
15 years
of experience

Salary at top
of scale

(4)

(5)

(6)

(7)

(8)

95 524
m
m
15 578 131
268 584
392 168
a
31 116
31 223
m
17 584
3 081 845
6 153 881
m
148 645
27 845
m
53 605 200
a
103 204
320 453
51 829
m
435 800
48 105
28 713
8 028
26 225
33 187
378 000
m
46 252
64 279

95 524
m
m
19 914 696
299 412
392 168
a
31 116
45 472
m
25 498
4 038 279
6 153 881
m
271 412
33 884
m
85 160 520
a
124 881
404 493
54 726
m
440 200
50 145
44 207
8 658
30 136
40 783
409 560
113 684
53 395
71 280

67 029
34 595
53 163
10 662 024
270 564
378 411
11 832
32 542
25 626
46 984
13 104
2 125 410
5 774 574
33 806
88 579
23 051
3 282 000
30 509 040
8 160
70 671
201 191
34 760
49 588
415 800
29 368
22 224
7 806
18 087
28 709
351 600
79 663
42 056
39 183

94 683
38 080
85 202
13 199 333
287 220
420 063
a
37 668
29 188
55 640
15 390
2 869 304
6 004 410
53 558
119 526
25 358
4 698 000
45 917 280
a
91 401
255 471
43 558
75 949
500 900
39 395
27 059
9 372
22 320
31 087
396 000
99 029
43 667
53 826

95 524
42 626
88 746
15 578 131
300 024
433 903
a
39 928
31 223
58 750
17 584
3 081 845
6 375 566
59 186
133 954
27 845
5 528 000
53 605 200
a
103 204
320 453
51 829
75 949
500 900
48 105
28 713
10 974
27 210
33 187
414 000
m
46 252
61 028

95 524
62 710
88 746
19 914 696
353 988
433 903
a
42 324
45 472
62 331
25 498
4 038 279
6 375 566
68 397
227 496
33 884
6 854 000
85 160 520
a
124 881
404 493
54 726
75 949
537 900
50 145
44 207
11 832
32 480
40 783
475 200
121 229
53 395
67 197

39 719
38 444
a
35 763

44 717
43 283
38 250
35 763

54 713
52 962
38 250
35 763

31 673
30 744
22 467
26 895

39 719
38 444
a
35 763

44 717
43 283
38 250
35 763

54 713
52 962
38 250
35 763

m
m
m
m
10 512 285
m
m
6 843
m
m
m

m
m
m
m
11 310 565
m
m
7 000
m
m
m

m
m
m
m
13 705 405
m
m
7 298
m
m
m

m
30 651
m
m
8 915 725
m
m
9 803
m
m
m

m
m
m
m
10 512 285
m
m
9 897
m
m
m

m
m
m
m
11 310 565
m
m
9 960
m
m
m

m
m
m
m
13 705 405
m
m
10 054
m
m
m

Starting salary

Salary after
10 years
of experience

Salary after
15 years
of experience

Salary at top
of scale

(1)

(2)

(3)

67 029
m
m
10 662 024
255 936
347 704
a
28 811
25 626
m
13 104
2 125 410
5 554 658
m
101 611
23 051
m
30 509 040
7 440
70 671
201 191
34 760
m
373 700
29 368
22 224
6 978
18 087
28 709
346 830
74 563
42 056
38 635

94 683
m
m
13 199 333
261 912
392 168
a
31 116
29 188
m
15 390
2 869 304
5 768 185
m
131 894
25 358
m
45 917 280
a
91 401
255 471
43 558
m
435 800
39 395
27 059
7 680
21 523
31 087
368 310
93 308
43 667
52 853

31 673
30 744
22 467
26 895
m
30 651
m
m
8 915 725
m
m
6 358
m
m
m

Countries

Australia
Austria
Canada1
Chile
Czech Republic
Denmark
Estonia
Finland2
France3
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea1
Latvia
Luxembourg4
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic5
Slovenia5
Spain
Sweden1, 5, 6
Switzerland7
Turkey
United States5, 6
Economies

Partners

Flemish Comm. (Belgium)5
French Comm. (Belgium)
England (UK)
Scotland (UK)
Argentina
Brazil
China
Colombia
Costa Rica
India
Indonesia
Lithuania
Russian Federation
Saudi Arabia
South Africa

Note: The definition of teachers’ most prevalent qualification is based on a broad concept, including the typical ISCED level of attainment and other criteria. Please
see Box D3.2 and Annex 3 for more information. Data available at http://stats.oecd.org/, Education at a Glance Database.
1. Excludes the social security contributions and pension-scheme contributions paid by the employees.
2. Data on pre-primary teachers includes the salary of kindergarten teachers who are the majority.
3. Includes the average of fixed bonuses for overtime hours (for lower and upper secondary teachers) and accomodation allowance.
4. Includes the social security contributions and pension-scheme contributions paid by the employers.
5. At the upper secondary level includes teachers working in vocational programmes. In Slovenia, includes only those teachers teaching general subjects within
vocational programmes.
6. Actual base salaries.
7. Salaries after 11 years of experience for Columns 2, 6, 10 and 14.
Source: OECD (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933806199

Education at a Glance 2018: OECD Indicators   © OECD 2018

437

Annex

2

Annex 2

Reference statistics

Under embargo until 11/09/2018 at 11.00am CEST
Table X2.4a. [2/2] Teachers’ statutory salaries at different points in their careers, for teachers with

the most prevalent qualifications defined at different points in the teachers’ career (2017)
Annual salaries in public institutions for teachers with the most prevalent qualifications, in national currency

OECD

Lower secondary, general programmes

2

Starting salary

Salary after
10 years
of experience

Salary after
15 years
of experience

Salary at top
of scale

(12)

(13)

(14)

(15)

(16)

95 524
44 824
88 746
15 578 131
300 636
439 604
a
43 122
32 515
63 857
17 584
3 081 845
6 375 566
59 777
147 740
30 340
5 528 000
53 665 200
a
110 482
410 549
64 994
76 975
500 900
48 105
28 713
10 974
27 210
37 007
420 000
m
46 252
63 046

95 524
66 970
88 746
19 914 696
355 644
439 604
a
45 710
46 892
69 353
25 498
4 038 279
6 375 566
68 988
237 014
37 211
6 854 000
85 220 520
a
139 222
517 194
75 435
76 975
537 900
50 145
44 207
11 832
32 480
45 318
488 400
137 125
53 395
68 052

67 029
34 519
53 163
10 934 868
270 948
360 909
11 832
37 268
26 917
53 076
13 104
2 353 176
4 901 080
33 806
91 296
24 849
3 282 000
29 849 040
8 160
80 094
498 450
36 891
51 200
495 900
29 368
22 224
7 806
18 087
32 080
360 000
100 725
42 056
40 517

94 683
43 410
85 202
13 563 307
288 000
469 025
a
44 759
30 479
64 506
15 390
3 176 788
5 136 556
55 505
120 258
28 196
4 698 000
45 257 280
a
100 117
576 774
56 570
78 000
548 000
39 395
27 059
9 372
22 320
34 787
419 460
129 235
43 667
54 609

95 524
49 086
88 746
15 978 448
300 552
469 025
a
46 549
32 515
67 532
17 584
3 412 105
5 282 008
59 777
135 094
31 189
5 528 000
52 945 200
a
110 482
615 769
64 994
78 000
548 000
48 105
28 713
10 974
27 210
37 007
430 200
m
46 252
63 006

95 524
71 377
88 746
20 460 384
355 092
469 025
a
49 342
46 892
76 778
25 498
4 471 034
6 688 420
68 988
217 788
38 901
7 035 000
84 500 520
a
139 222
665 902
75 435
78 000
606 500
50 145
44 207
11 832
32 480
45 318
500 400
154 434
53 395
70 900

39 719
38 444
a
35 763

44 717
43 283
38 250
35 763

54 713
52 962
38 250
35 763

39 516
38 247
22 467
26 895

50 365
48 753
a
35 763

57 436
55 599
38 250
35 763

69 220
67 009
38 250
35 763

m
m
m
m
10 954 860
m
m
9 897
m
m
m

m
m
m
m
11 786 740
m
m
9 960
m
m
m

m
m
m
m
14 282 380
m
m
10 054
m
m
m

m
30 651
m
m
9 291 100
m
m
9 803
m
m
m

m
m
m
m
10 954 860
m
m
9 897
m
m
m

m
m
m
m
11 786 740
m
m
9 960
m
m
m

m
m
m
m
14 282 380
m
m
10 054
m
m
m

Starting salary

Salary after
15 years
of experience

Salary at top
of scale

(9)

(10)

(11)

67 032
34 478
53 163
10 662 024
270 696
380 228
11 832
35 145
26 917
52 818
13 104
2 353 176
5 774 574
33 806
89 057
24 849
3 282 000
30 569 040
8 160
80 094
256 889
36 891
50 394
415 800
29 368
22 224
7 806
18 087
32 080
360 000
89 499
42 056
39 707

94 683
40 070
85 202
13 199 333
287 748
425 144
a
40 682
30 479
60 964
15 390
2 869 304
6 004 410
55 505
127 633
27 527
4 698 000
45 977 280
a
100 117
326 021
56 570
76 975
500 900
39 395
27 059
9 372
22 320
34 787
405 570
113 137
43 667
54 566

31 673
30 744
22 467
26 895
m
30 651
m
m
9 291 100
m
m
9 803
m
m
m

Countries

Australia
Austria
Canada1
Chile
Czech Republic
Denmark
Estonia
Finland2
France3
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea1
Latvia
Luxembourg4
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic5
Slovenia5
Spain
Sweden1, 5, 6
Switzerland7
Turkey
United States5, 6
Economies

Flemish Comm. (Belgium)5
French Comm. (Belgium)
England (UK)
Scotland (UK)
Partners

Annex

Upper secondary, general programmes

Salary after
10 years
of experience

Argentina
Brazil
China
Colombia
Costa Rica
India
Indonesia
Lithuania
Russian Federation
Saudi Arabia
South Africa

Note: The definition of teachers’ most prevalent qualification is based on a broad concept, including the typical ISCED level of attainment and other criteria. Please
see Box D3.2 and Annex 3 for more information. Data available at http://stats.oecd.org/, Education at a Glance Database.
1. Excludes the social security contributions and pension-scheme contributions paid by the employees.
2. Data on pre-primary teachers includes the salary of kindergarten teachers who are the majority.
3. Includes the average of fixed bonuses for overtime hours (for lower and upper secondary teachers) and accomodation allowance.
4. Includes the social security contributions and pension-scheme contributions paid by the employers.
5. At the upper secondary level includes teachers working in vocational programmes. In Slovenia, includes only those teachers teaching general subjects within
vocational programmes.
6. Actual base salaries.
7. Salaries after 11 years of experience for Columns 2, 6, 10 and 14.
Source: OECD (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933806199

438 Education at a Glance 2018: OECD Indicators   © OECD 2018

Reference statistics

Annex 2

Under embargo until 11/09/2018 at 11.00am CEST
Table X2.4c. [1/2] Teachers’ statutory salaries at different points in their careers,

for teachers with minimum qualifications (2017)

Annual salaries in public institutions for teachers with minimum qualifications, in national currency

OECD

Pre-primary

Primary

Starting salary

Salary after
10 years
of experience

Salary after
15 years
of experience

Salary at top
of scale

(4)

(5)

(6)

(7)

(8)

95 524
m
m
15 578 131
268 584
392 168
a
31 116
31 223
m
17 584
3 081 845
6 153 881
m
148 645
27 845
m
50 572 080
a
103 204
320 453
51 829
m
435 800
36 897
28 713
8 028
26 225
33 187
378 000
m
46 252
48 855

95 524
m
m
19 914 696
299 412
392 168
a
31 116
45 472
m
25 498
4 038 279
6 153 881
m
221 968
33 884
m
85 160 520
a
124 881
404 493
54 726
m
440 200
38 450
44 207
8 658
30 136
40 783
409 560
113 684
53 395
59 588

67 029
34 595
50 300
10 662 024
270 564
378 411
11 832
32 542
25 626
46 984
13 104
2 125 410
5 774 574
33 806
88 579
23 051
3 282 000
30 509 040
8 160
70 671
201 191
34 760
47 980
415 800
23 076
22 224
7 806
18 087
28 709
351 600
79 663
42 056
39 183

94 683
38 080
74 878
13 199 333
287 220
420 063
a
37 668
29 188
55 640
14 424
2 869 304
6 004 410
50 482
119 526
25 358
4 698 000
45 917 280
a
91 401
255 471
43 558
59 621
469 400
30 402
27 059
9 372
22 320
31 087
396 000
99 029
43 667
44 796

95 524
42 626
78 322
15 578 131
300 024
433 903
a
39 928
31 223
58 750
15 744
3 081 845
6 375 566
56 110
133 954
27 845
5 528 000
53 605 200
a
103 204
320 453
51 829
59 621
469 400
36 897
28 713
10 974
27 210
33 187
414 000
m
46 252
48 893

95 524
62 710
78 322
19 914 696
353 988
433 903
a
42 324
45 472
62 331
24 324
4 038 279
6 375 566
65 321
186 236
33 884
6 854 000
85 160 520
a
124 881
404 493
54 726
59 621
487 000
38 450
44 207
11 832
32 480
40 783
475 200
121 229
53 395
59 020

39 719
38 444
a
35 763

44 717
43 283
a
35 763

54 713
52 962
26 034
35 763

31 673
30 744
16 461
26 895

39 719
38 444
a
35 763

44 717
43 283
a
35 763

54 713
52 962
26 034
35 763

m
m
m
m
5 880 035
m
m
6 843
m
m
m

m
m
m
m
6 352 815
m
m
7 000
m
m
m

m
m
m
m
7 771 155
m
m
7 298
m
m
m

m
30 651
m
m
4 934 475
m
m
9 803
m
m
m

m
m
m
m
5 880 035
m
m
9 897
m
m
m

m
m
m
m
6 352 815
m
m
9 960
m
m
m

m
m
m
m
7 771 155
m
m
10 054
m
m
m

Starting salary

Salary after
10 years
of experience

Salary after
15 years
of experience

Salary at top
of scale

(1)

(2)

(3)

67 029
m
m
10 662 024
255 936
347 704
a
28 811
25 626
m
13 104
2 125 410
5 554 658
m
101 611
23 051
m
29 273 520
7 440
70 671
201 191
34 760
m
373 700
23 076
22 224
6 978
18 087
28 709
346 830
74 563
42 056
38 635

94 683
m
m
13 199 333
261 912
392 168
a
31 116
29 188
m
15 390
2 869 304
5 768 185
m
131 894
25 358
m
43 166 760
a
91 401
255 471
43 558
m
435 800
30 402
27 059
7 680
21 523
31 087
368 310
93 308
43 667
47 256

31 673
30 744
16 461
26 895
m
30 651
m
m
4 934 475
m
m
6 358
m
m
m

Countries

Australia
Austria
Canada1
Chile
Czech Republic
Denmark
Estonia
Finland2
France3
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Luxembourg4
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic5
Slovenia5
Spain
Sweden1, 5, 6
Switzerland7
Turkey
United States5, 6
Economies

Partners

Flemish Comm. (Belgium)5
French Comm. (Belgium)
England (UK)
Scotland (UK)
Argentina
Brazil
China
Colombia
Costa Rica
India
Indonesia
Lithuania
Russian Federation
Saudi Arabia
South Africa

Note: See Definitions and Methodology sections for more information. Data available at http://stats.oecd.org/, Education at a Glance Database.
1. Excludes the social security contributions and pension-scheme contributions paid by the employees.
2. Data on pre-primary teachers includes the salary of kindergarten teachers who are the majority.
3. Includes the average of fixed bonuses for overtime hours for lower and upper secondary teachers.
4. Includes the social security contributions and pension-scheme contributions paid by the employers.
5. At the upper secondary level includes teachers working in vocational programmes. In Slovenia, includes only those teachers teaching general subjects within
vocational programmes.
6. Actual base salaries.
7. Salaries after 11 years of experience for Columns 2, 6, 10 and 14.
Source: OECD (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933806218

Education at a Glance 2018: OECD Indicators   © OECD 2018

439

Annex

2

Annex 2

Reference statistics

Under embargo until 11/09/2018 at 11.00am CEST
Table X2.4c. [2/2] Teachers’ statutory salaries at different points in their careers,

for teachers with minimum qualifications (2017)

Annual salaries in public institutions for teachers with minimum qualifications, in national currency

OECD

Lower secondary, general programmes

2

Starting salary

Salary after
10 years
of experience

Salary after
15 years
of experience

Salary at top
of scale

(12)

(13)

(14)

(15)

(16)

95 524
44 824
78 322
15 578 131
300 636
439 604
a
43 122
32 515
63 857
15 744
3 081 845
6 375 566
56 701
143 100
30 340
5 528 000
52 147 200
a
110 482
410 549
64 994
60 061
469 400
42 040
28 713
10 974
27 210
37 007
420 000
m
46 252
50 847

95 524
66 970
78 322
19 914 696
355 644
439 604
a
45 710
46 892
69 353
24 324
4 038 279
6 375 566
65 912
185 669
37 211
6 854 000
85 220 520
a
139 222
517 194
75 435
60 061
487 000
43 816
44 207
11 832
32 480
45 318
488 400
137 125
53 395
56 687

67 029
34 519
50 300
10 934 868
270 948
360 909
11 832
37 268
26 917
53 076
13 104
2 353 176
4 901 080
33 806
91 296
24 849
3 282 000
29 227 320
8 160
80 094
498 450
36 891
51 200
415 800
29 368
22 224
7 806
18 087
32 080
360 000
100 725
42 056
40 517

94 683
43 410
74 878
13 563 307
288 000
469 025
a
44 759
30 479
64 506
14 424
3 176 788
5 136 556
52 429
119 759
28 196
4 698 000
43 882 680
a
100 117
576 774
56 570
73 650
469 400
39 395
27 059
9 372
22 320
34 787
419 460
129 235
43 667
46 342

95 524
49 086
78 322
15 978 448
300 552
469 025
a
46 549
32 515
67 532
15 744
3 412 105
5 282 008
56 701
134 624
31 189
5 528 000
51 427 200
a
110 482
615 769
64 994
60 500
469 400
48 105
28 713
10 974
27 210
37 007
430 200
m
46 252
51 542

95 524
71 377
78 322
20 460 384
355 092
469 025
a
49 342
46 892
76 778
24 324
4 471 034
6 688 420
65 912
198 075
38 901
7 035 000
84 500 520
a
139 222
665 902
75 435
60 500
487 000
50 145
44 207
11 832
32 480
45 318
500 400
154 434
53 395
60 823

39 719
38 444
a
35 763

44 717
43 283
a
35 763

54 713
52 962
26 034
35 763

31 673
35 965
16 461
26 895

39 719
43 756
a
35 763

44 717
48 595
a
35 763

54 713
58 274
26 034
35 763

m
m
m
m
6 087 818
m
m
9 897
m
m
m

m
m
m
m
6 560 598
m
m
9 960
m
m
m

m
m
m
m
7 978 938
m
m
10 054
m
m
m

m
30 651
m
m
5 142 258
m
m
9 803
m
m
m

m
m
m
m
6 087 818
m
m
9 897
m
m
m

m
m
m
m
6 560 598
m
m
9 960
m
m
m

m
m
m
m
7 978 938
m
m
10 054
m
m
m

Starting salary

Salary after
15 years
of experience

Salary at top
of scale

(9)

(10)

(11)

67 032
34 478
50 300
10 662 024
270 696
380 228
11 832
35 145
26 917
52 818
13 104
2 353 176
5 774 574
33 806
89 057
24 849
3 282 000
29 947 320
8 160
80 094
256 889
36 891
49 590
415 800
25 987
22 224
7 806
18 087
32 080
360 000
89 499
42 056
39 707

94 683
40 070
74 878
13 199 333
287 748
425 144
a
40 682
30 479
60 964
14 424
2 869 304
6 004 410
52 429
127 633
27 527
4 698 000
44 602 680
a
100 117
326 021
56 570
66 636
469 400
34 476
27 059
9 372
22 320
34 787
405 570
113 137
43 667
46 751

31 673
30 744
16 461
26 895
m
30 651
m
m
5 142 258
m
m
9 803
m
m
m

Countries

Australia
Austria
Canada1
Chile
Czech Republic
Denmark
Estonia
Finland2
France3
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Luxembourg4
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic5
Slovenia5
Spain
Sweden1, 5, 6
Switzerland7
Turkey
United States5, 6
Economies

Flemish Comm. (Belgium)5
French Comm. (Belgium)
England (UK)
Scotland (UK)
Partners

Annex

Upper secondary, general programmes

Salary after
10 years
of experience

Argentina
Brazil
China
Colombia
Costa Rica
India
Indonesia
Lithuania
Russian Federation
Saudi Arabia
South Africa

Note: See Definitions and Methodology sections for more information. Data available at http://stats.oecd.org/, Education at a Glance Database.
1. Excludes the social security contributions and pension-scheme contributions paid by the employees.
2. Data on pre-primary teachers includes the salary of kindergarten teachers who are the majority.
3. Includes the average of fixed bonuses for overtime hours for lower and upper secondary teachers.
4. Includes the social security contributions and pension-scheme contributions paid by the employers.
5. At the upper secondary level includes teachers working in vocational programmes. In Slovenia, includes only those teachers teaching general subjects within
vocational programmes.
6. Actual base salaries.
7. Salaries after 11 years of experience for Columns 2, 6, 10 and 14.
Source: OECD (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933806218

440 Education at a Glance 2018: OECD Indicators   © OECD 2018

Reference statistics

Annex 2

Under embargo until 11/09/2018 at 11.00am CEST
Table X2.4f. [1/2] Reference statistics used in calculating teachers’ salaries (2000, 2005 to 2017)

OECD

Purchasing power parity for private consumption (PPP)1
2015

2016

2017

Jan 2016

Jan 2017

(1)

(2)

(3)

(4)

(5)

1.56
0.85
1.34
445.77
14.25
8.33
0.61
0.98
0.88
0.84
0.69
148.55
155.60
1.00
4.48
0.83
109.24
999.59
0.57
1.01
9.84
0.89
1.63
10.20
1.89
0.68
0.55
0.67
0.74
9.43
1.42
1.49
1.00

1.60
0.85
1.36
455.09
14.28
8.42
0.61
0.97
0.87
0.83
0.68
149.39
161.50
1.00
4.42
0.81
107.15
1 003.75
0.57
1.01
10.11
0.89
1.64
10.50
1.88
0.68
0.55
0.67
0.74
9.58
1.41
1.60
1.00

1.60
0.85
1.36
455.09
14.28
8.42
0.61
0.97
0.87
0.83
0.68
149.39
161.50
1.00
4.42
0.81
107.15
1 003.75
0.57
1.01
10.11
0.89
1.64
10.50
1.88
0.68
0.55
0.67
0.74
9.58
1.41
1.60
1.00

1.58
0.85
1.35
450.43
14.26
8.38
0.61
0.98
0.87
0.83
0.68
148.97
158.55
1.00
4.45
0.82
108.19
1 001.67
0.57
1.01
9.98
0.89
1.64
10.35
1.88
0.68
0.55
0.67
0.74
9.51
1.42
1.55
1.00

1.60
0.85
1.36
455.09
14.28
8.42
0.61
0.97
0.87
0.83
0.68
149.39
161.50
1.00
4.42
0.81
107.15
1 003.75
0.57
1.01
10.11
0.89
1.64
10.50
1.88
0.68
0.55
0.67
0.74
9.58
1.41
1.60
1.00

0.87
0.87
0.81
0.81

0.88
0.88
0.80
0.80

0.88
0.88
0.80
0.80

0.87
0.87
0.80
0.80

0.88
0.88
0.80
0.80

m
2.04
m
1 291.74
377.96
m
m
0.50
23.86
m
m

m
2.19
m
1 371.54
373.24
m
m
0.51
24.88
m
m

m
2.19
m
1 371.54
373.24
m
m
0.51
24.88
m
m

m
1.88
m
1 331.64
375.60
m
m
0.50
24.37
m
m

m
2.19
m
1 371.54
373.24
m
m
0.51
24.88
m
m

Countries

Australia
Austria
Canada
Chile
Czech Republic
Denmark
Estonia
Finland
France2
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United States

Annex

Economies

Partners

Flemish Comm. (Belgium)3
French Comm. (Belgium)3
England (UK)4
Scotland (UK)4
Argentina
Brazil
China
Colombia
Costa Rica
India
Indonesia
Lithuania
Russian Federation
Saudi Arabia
South Africa

Note: See Definitions and Methodology sections for more information. Data available at http://stats.oecd.org/, Education at a Glance Database.
1. Data on PPPs and GDP for countries now in the Euro area are shown in euros.
2. Data for PPP for January 2016 refers to January 2015.
3. Data on PPPs and deflators refer to Belgium.
4. Data on PPPs and deflators refer to the United Kingdom.
Source: OECD (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933806237

Education at a Glance 2018: OECD Indicators   © OECD 2018

441

2

Annex 2

Reference statistics

Under embargo until 11/09/2018 at 11.00am CEST
Table X2.4f. [2/2] Reference statistics used in calculating teachers’ salaries (2000, 2005 to 2017)
Private consumption deflators (2005 = 100)

Reference
year for
statutory
salary data

Reference
year for
actual
salary data

(20)

(21)

Jan
Jan
2000 2005

Jan
2006

Jan
Jan
Jan
Jan
Jan
Jan
Jan
Jan
Jan
Jan
Jan
2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017

(6)

(7)

(8)

(9)

(10)

(11)

(12)

(13)

(14)

(15)

(16)

(17)

(18)

(19)

88

100

103

106

110

113

116

118

121

124

127

130

131

132

2017

2016

91
91
86
90
92
82
93
92
93
87
73
82
83
93
87
105
84
77
90
80
88
92
91
84
85
76
76
85
93
97
28
90

100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100

102
101
104
101
102
105
101
102
101
103
103
104
102
102
102
100
102
110
103
104
102
102
101
102
104
104
102
104
101
101
109
103

105
103
107
104
104
112
103
104
103
107
108
110
105
104
105
99
104
122
105
109
105
105
103
104
107
108
106
107
102
102
118
105

107
105
113
108
106
121
106
107
104
111
115
121
107
107
108
99
107
137
108
115
107
108
106
107
111
111
111
111
105
104
128
108

108
105
118
111
109
126
108
107
105
114
121
139
105
111
109
98
111
143
109
121
107
111
109
111
111
114
114
112
108
105
138
110

110
106
121
112
111
128
110
107
106
116
125
150
100
114
110
96
114
139
110
127
107
113
111
113
111
115
116
113
110
105
147
111

112
108
125
113
113
134
113
109
108
120
130
154
100
118
112
94
117
141
112
132
109
116
113
118
113
117
117
115
111
105
160
113

115
110
129
115
116
141
116
111
110
121
136
161
101
121
115
94
121
148
115
137
111
118
114
122
115
122
119
118
113
105
174
116

118
111
133
117
118
145
119
112
111
121
142
169
102
123
117
93
123
150
117
142
113
119
116
125
116
125
121
120
113
104
186
117

121
113
138
117
119
148
121
112
112
118
144
174
104
124
118
94
124
152
118
147
115
119
118
125
117
125
121
121
114
103
199
119

123
115
146
118
120
148
122
112
113
115
144
177
105
124
118
95
125
153
118
153
115
120
121
124
118
125
121
121
115
103
212
120

124
116
153
118
120
149
123
112
114
114
144
179
106
123
118
95
126
152
118
159
116
121
125
123
119
125
120
121
117
102
227
121

125
117
157
118
120
149
123
112
114
114
144
180
107
123
118
94
127
153
118
161
116
121
127
123
119
125
120
120
117
102
235
122

2016/17
2016/17
2017
2016/17
2016/17
2016/17
2017
2016/17
2016/17
2016/17
2016/17
2016/17
2016/17
2016/17
2016/17
2016/17
2017
2016/17
2016/17
2016/17
2016/17
2017
2016/17
2016/17
2016/17
2016/17
2016/17
2016/17
2016
2017
2016/17
2016/17

2015/16
m
2016
2015/16
2015/16
2015/16
2015/16
2015
2015/16
2015/16
2016
2016
2015/16
2015/16
2015/16
2015
2017
2015/16
2015/16
2016/17
2015/16
2016
2015/16
2015/16
2015/16
2015/16
2015/16
2016/17
2016
2017
2015/16
2015/16

Flemish Comm. (Belgium)3
French Comm. (Belgium)3
England (UK)4
Scotland (UK)4

90
90
95
95

100
100
100
100

103
103
102
102

106
106
105
105

109
109
108
108

111
111
111
111

111
111
112
112

114
114
115
115

117
117
119
119

119
119
121
121

120
120
124
124

120
120
125
125

121
121
126
126

122
122
126
126

2016/17
2016/17
2016/17
2016/17

2015/16
2017
2015/16
2015/16

Argentina
Brazil
China
Colombia
Costa Rica
India
Indonesia
Lithuania
Russian Federation
Saudi Arabia
South Africa

m
65
m
72
56
m
m
99
48
m
m

m
100
m
100
100
m
m
100
100
m
m

m
106
m
104
115
m
m
104
110
m
m

m
112
m
109
129
m
m
109
120
m
m

m
118
m
115
144
m
m
118
132
m
m

m
126
m
120
154
m
m
127
148
m
m

m
135
m
124
159
m
m
131
160
m
m

m
144
m
128
167
m
m
134
172
m
m

m
156
m
133
173
m
m
139
185
m
m

m
168
m
136
178
m
m
142
196
m
m

m
179
m
140
185
m
m
142
210
m
m

m
194
m
147
189
m
m
142
235
m
m

m
213
m
156
188
m
m
142
264
m
m

m
223
m
162
188
m
m
143
276
m
m

m
2017
m
m
2017
m
m
2016/17
m
m
m

m
2014
m
m
2016
m
m
2016/17
m
m
m

OECD

Countries

2

Economies

Partners

Annex

Australia
Austria
Canada
Chile
Czech Republic
Denmark
Estonia
Finland
France2
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United States

Note: See Definitions and Methodology sections for more information. Data available at http://stats.oecd.org/, Education at a Glance Database.
1. Data on PPPs and GDP for countries now in the Euro area are shown in euros.
2. Data for PPP for January 2016 refers to January 2015.
3. Data on PPPs and deflators refer to Belgium.
4. Data on PPPs and deflators refer to the United Kingdom.
Source: OECD (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933806237

442 Education at a Glance 2018: OECD Indicators   © OECD 2018

Reference statistics

Annex 2

Under embargo until 11/09/2018 at 11.00am CEST
Table X2.4g. [1/2] Trends in average teachers’ actual salaries, in national currency

(2000, 2005, 2010 to 2016)

Average annual salary (including bonuses and allowances) of teachers aged 25-64

OECD

Pre-primary

Primary

2000

2005

2010

2016

2000

2005

2010

2016

(1)

(2)

(3)

(9)

(10)

(11)

(12)

(18)

m
m
m
m
m
m
m
m
m
m
m
m
m
m
m
m
m
m
m
m
m
m
m
m
m
m
m
m
m
204 516
m
m
38 028

m
m
m
m
m
m
m
m
m
m
m
m
m
m
m
m
m
m
m
m
m
m
m
289 548
m
m
m
m
m
252 268
m
m
40 268

77 641
m
m
m
228 603
372 336
m
29 759
31 448
m
m
2 217 300
m
m
110 959
25 774
m
m
m
88 315
m
43 374
m
368 580
40 626
m
m
m
m
296 997
m
m
48 103

86 445
m
m
13 359 310
288 610
372 319b
9 606
32 736
33 775
m
16 897
3 400 080
5 730 000
m
156 585
28 041
m
m
7 026
97 456
m
47 427
m
456 640
49 555
31 995
9 589
19 267b
m
358 334
m
34 242
51 295

m
m
m
m
m
m
m
28 723
m
m
m
m
m
m
m
m
m
m
m
m
m
m
m
m
m
m
m
m
m
239 887
m
m
38 746

m
m
m
m
m
m
m
35 654
m
m
m
m
m
m
m
m
m
m
m
m
m
m
m
348 877
m
m
m
m
m
288 154
m
m
41 059

78 352
m
m
m
290 682
452 337
m
40 458
30 876
m
m
2 473 800
m
m
123 151
25 774
m
m
m
88 315
m
43 374
m
422 930
46 862
m
m
m
m
323 621
m
m
49 133

86 856
48 335
m
12 792 300
343 200
445 044b
14 283
44 278
32 931
54 747
16 897
3 593 496
6 274 000
m
164 323
28 041
m
m
7 139
97 456
m
47 427
69 588
514 941
57 477
29 401
12 813
24 315b
m
405 490
m
34 242
52 197

m
m
22 968
m

m
m
29 418
m

41 046
m
33 680
31 884

44 833
43 622
32 635
33 534

m
m
22 968
m

m
m
29 418
m

41 543
m
33 680
31 884

45 192
42 865
32 635
33 534

m
m
m
m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m
m
m
m

m
41 278
m
m
m
m
m
10 617
m
m
m

m
m
m
m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m
m
m
m

m
42 661
m
m
m
m
m
10 617
m
m
m

Countries

Australia
Austria1
Canada
Chile
Czech Republic
Denmark2
Estonia
Finland3
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia4
Spain
Sweden5
Switzerland
Turkey
United States
Economies

Partners

Flemish Comm. (Belgium)
French Comm. (Belgium)
England (UK)
Scotland (UK)6
Argentina
Brazil
China
Colombia
Costa Rica
India
Indonesia
Lithuania
Russian Federation7
Saudi Arabia
South Africa

Note: Years 2011 to 2014 (i.e. Columns 4 to 8, 13 to 17, 22 to 26 and 31 to 35) are available for consultation on line. Data available at http://stats.oecd.org/, Education
at a Glance Database.
1. Before 2015, also includes data on actual salaries of headmasters, deputies and assistants.
2. Also includes data on actual salaries of teachers in early childhood educational development programmes for pre-primary education.
3. Also includes data on the majority, i.e. kindergarten teachers only for pre-primary education.
4. Also includes data on actual salaries of pre-school teacher assistants for pre-primary education for 2011-2015.
5. Average actual teachers’ salaries, not including bonuses and allowances.
6. Includes all teachers, irrespective of their age.
7. Average actual teachers’ salaries for all teachers, irrespective of the level of education they teach.
Source: OECD (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933806256

Education at a Glance 2018: OECD Indicators   © OECD 2018

443

Annex

2

Annex 2

Reference statistics

Under embargo until 11/09/2018 at 11.00am CEST
Table X2.4g. [2/2] Trends in average teachers’ actual salaries, in national currency

(2000, 2005, 2010 to 2016)

Average annual salary (including bonuses and allowances) of teachers aged 25-64

OECD

Lower secondary

2

2000

2005

2010

2016

2000

2005

2010

2016

(19)

(20)

(21)

(27)

(28)

(29)

(30)

(36)

m
m
m
m
m
m
m
32 919
m
m
m
m
m
m
m
m
m
m
m
m
m
m
m
m
m
m
m
m
m
247 793
m
m
39 500

m
m
m
m
m
m
m
39 519
m
m
m
m
m
m
m
m
m
m
m
m
m
m
m
348 877
m
m
m
m
m
290 058
m
m
41 873

78 221
m
m
m
289 771
457 728
m
44 421
37 198
m
m
2 473 800
m
m
126 309
27 170
m
m
m
101 471
m
52 831
m
422 930
47 410
m
m
m
m
324 639
m
m
50 158

87 487
56 559
m
13 017 993
341 870
449 917b
14 283
48 796
38 418
60 476
18 212
3 593 496
6 274 000
m
177 428
28 370
m
m
8 647
109 315
m
59 445
70 997
514 941
59 473
28 909
12 813
24 816b
m
418 415
m
34 242
54 000

m
m
m
m
m
m
m
37 728
m
m
m
m
m
m
m
m
m
m
m
m
m
m
m
m
m
m
m
m
m
265 488
m
m
41 124

m
m
m
m
m
m
m
44 051
m
m
m
m
m
m
m
m
m
m
m
m
m
m
m
372 694
m
m
m
m
m
315 592
m
m
43 588

78 225
m
m
m
313 534
m
m
49 808
41 789
m
m
2 814 100
5 172 300
m
133 790
28 986
m
m
m
101 471
m
52 831
m
449 704
46 147
m
m
m
m
347 967
m
m
52 188

87 487
61 326
m
14 093 804
355 020
514 715b
14 283
55 020
43 265
64 000
18 212
3 859 716
8 565 000
m
166 928
29 860
m
m
10 075
109 315
m
59 445
76 423
560 205
57 988
31 489
12 841
26 220b
m
431 081
m
34 242
55 992

m
m
25 347
m

m
m
32 355
m

41 277
m
36 173
31 884

43 754
41 820
36 490
33 534

m
m
25 347
m

m
m
32 355
m

54 381
m
36 173
31 884

56 758
53 183
36 490
33 534

m
m
m
m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m
m
m
m

m
43 621
m
m
m
m
m
10 617
m
m
m

m
m
m
m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m
m
m
m

m
45 242
m
m
m
m
m
10 617
m
m
m

Countries

Australia
Austria1
Canada
Chile
Czech Republic
Denmark2
Estonia
Finland3
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia4
Spain
Sweden5
Switzerland
Turkey
United States
Economies

Flemish Comm. (Belgium)
French Comm. (Belgium)
England (UK)
Scotland (UK)6
Partners

Annex

Upper secondary

Argentina
Brazil
China
Colombia
Costa Rica
India
Indonesia
Lithuania
Russian Federation7
Saudi Arabia
South Africa

Note: Years 2011 to 2014 (i.e. Columns 4 to 8, 13 to 17, 22 to 26 and 31 to 35) are available for consultation on line. Data available at http://stats.oecd.org/, Education
at a Glance Database.
1. Before 2015, also includes data on actual salaries of headmasters, deputies and assistants.
2. Also includes data on actual salaries of teachers in early childhood educational development programmes for pre-primary education.
3. Also includes data on the majority, i.e. kindergarten teachers only for pre-primary education.
4. Also includes data on actual salaries of pre-school teacher assistants for pre-primary education for 2011-2015.
5. Average actual teachers’ salaries, not including bonuses and allowances.
6. Includes all teachers, irrespective of their age.
7. Average actual teachers’ salaries for all teachers, irrespective of the level of education they teach.
Source: OECD (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933806256

444 Education at a Glance 2018: OECD Indicators   © OECD 2018

Annex 2

Reference statistics

Under embargo until 11/09/2018 at 11.00am CEST
Table X2.5. Proportion of teachers, by level of qualification (2017)
Teachers who have either minimum or a higher than minimum (and most prevalent) qualification

OECD

Percentage of teachers in salary range
based on minimum qualification of
teachers to enter the teaching profession
in 2017
Percentage of teachers in a salary
range based on a higher than minimum
qualification (and most prevalent) to
enter the teaching profession in 2017

Is there a difference between “minimum”
and “most prevalent” qualifications?

Upper secondary

Percentage of teachers in salary range
based on minimum qualification of
teachers to enter the teaching profession
in 2017
Percentage of teachers in a salary
range based on a higher than minimum
qualification (and most prevalent) to
enter the teaching profession in 2017

Is there a difference between “minimum”
and “most prevalent” qualifications?

Lower secondary

Percentage of teachers in salary range
based on minimum qualification of
teachers to enter the teaching profession
in 2017
Percentage of teachers in a salary
range based on a higher than minimum
qualification (and most prevalent) to
enter the teaching profession in 2017

Is there a difference between “minimum”
and “most prevalent” qualifications?

Primary

Percentage of teachers in salary range
based on minimum qualification of
teachers to enter the teaching profession
in 2017
Percentage of teachers in a salary
range based on a higher than minimum
qualification (and most prevalent) to
enter the teaching profession in 2017

Is there a difference between “minimum”
and “most prevalent” qualifications?

Pre-primary

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

m
m
a
No
No
No
a
No
No
No
No
No
No
No
No
No
m
Yes
No
No
No
No
Yes
No
Yes
No
No
No
No
No
No
No
No

m
m
m
m
92
100
a
90
98
m
100
m
46
m
72
100
m
2
100
76
m
100
m
m
m
100
m
100
100
100
m
m
49

m
m
m
a
a
a
a
a
a
m
a
m
a
m
a
a
m
33
a
a
a
a
m
m
m
a
a
a
a
a
m
a
a

m
No
Yes
No
No
No
a
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
Yes
Yes
Yes
No
No
No
No
No
No
No
Yes

m
100
m
m
100
100
a
99
98
100
100
m
96
16
63
100
m
55
100
83
m
100
m
39
m
100
m
100
100
100
m
m
44

m
a
m
m
a
a
a
a
a
a
a
m
a
a
a
a
m
a
a
a
a
a
m
37
m
a
a
a
a
a
m
a
46

m
No
Yes
No
No
No
a
No
No
No
No
No
No
No
No
No
No
Yes
No
No
No
No
Yes
Yes
Yes
No
No
No
No
No
No
No
Yes

m
100
m
m
100
100
a
96
87
100
100
m
96
17
50
100
m
11
100
69
m
100
a
39
m
100
m
100
100
100
m
m
40

m
a
m
m
a
a
a
a
a
a
a
m
a
a
a
a
m
37
a
a
a
a
m
37
m
a
a
a
a
a
m
a
48

m
No
Yes
No
No
No
a
No
No
No
No
No
No
No
No
No
No
Yes
No
No
No
No
Yes
Yes
Yes
No
No
No
No
No
No
No
Yes

m
100
m
m
100
100
a
91
67
100
100
m
86
17
49
100
m
9
100
84
m
100
m
9
m
100
m
100
100
100
m
m
35

m
a
m
m
a
a
a
a
a
a
a
m
a
a
a
a
m
33
a
a
a
a
0
53
a
a
a
a
a
a
m
a
50

Flemish Comm. (Belgium)
French Comm. (Belgium)
England (UK)
Scotland (UK)

No
No
Yes
No

100
99
0
100

a
a
99
a

No
No
Yes
No

100
95
0
100

a
a
99
a

No
No
Yes
No

96
88
0
100

a
a
100
a

Yes
Yes
Yes
No

38
9
0
100

62
82
100
a

Argentina
Brazil
China
Colombia
Costa Rica
India
Indonesia
Lithuania
Russian Federation
Saudi Arabia
South Africa

m
No
m
m
Yes
m
m
No
m
m
m

m
m
m
m
0
m
m
m
m
m
m

m
a
m
m
93
m
m
a
m
m
m

m
No
m
m
Yes
m
m
No
m
m
m

m
m
m
m
0
m
m
m
m
m
m

m
a
m
m
77
m
m
a
m
m
m

m
No
m
m
Yes
m
m
No
m
m
m

m
m
m
m
0
m
m
m
m
m
m

m
a
m
m
43
m
m
a
m
m
m

m
No
m
m
Yes
m
m
No
m
m
m

m
m
m
m
0
m
m
m
m
m
m

m
a
m
m
43
m
m
a
m
m
m

Countries

Australia
Austria
Canada
Chile
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United States

Partners

Economies

Note: See Definitions and Methodology sections for more information. Data available at http://stats.oecd.org/, Education at a Glance Database.
Source: OECD (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933806275

Education at a Glance 2018: OECD Indicators   © OECD 2018

445

Annex

2

Annex 2

Reference statistics

Under embargo until 11/09/2018 at 11.00am CEST
Table X2.6. Percentage of pre-primary, primary, lower secondary and upper secondary teachers,

by level of attainment (2017)
Attainment at ISCED
level 5 or lower

Attainment at ISCED
level 6

Attainment at ISCED
level 7 or 8

Attainment at ISCED
level 5 or lower

Attainment at ISCED
level 6

Attainment at ISCED
level 7 or 8

Attainment at ISCED
level 5 or lower

Attainment at ISCED
level 6

Attainment at ISCED
level 7 or 8

Upper secondary

Attainment at ISCED
level 7 or 8

Lower secondary

Attainment at ISCED
level 6

Primary

Attainment at ISCED
level 5 or lower

2

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

m

m

m

m

m

m

m

m

m

m

m

m

m
m
1
77
m
33
27
19
m
a
6
6
m
8
m
m
m
19
a
13
a
m
4
3
a
m
26
0
45
m
m
2

m
m
99d
15
m
43
67
67
m
m
93
92
m
73
m
m
m
81d
m
79
83
m
95
8
13
m
58
100
52
m
m
47

m
m
x(2)
8
m
24
6
14
m
m
1
2
m
19
m
m
m
x(2)
m
8
17
m
1
88
88
m
16
0
3
m
m
51

m
m
1
7
m
9
3
19
0
a
1
2
m
5
m
m
m
14
a
3
a
11
3
1
a
m
24
0
5
m
m
2

m
m
99d
4
m
20
7
67
0
m
84
87
m
64
m
m
m
86d
m
88
83
86
91
3
9
m
3
100
71
m
m
42

m
m
x(5)
89
m
71
90
14
100
m
16
11
m
31
m
m
m
x(5)
m
9
17
3
6
96
91
m
73
0
24
m
m
56

m
m
1
6
m
5
3
7
0
a
1
2
m
3
m
m
m
6
a
7
a
11
3
0
a
m
28
0
4
m
m
2

m
m
99d
5
m
16
5
67
0
m
84
87
m
51
m
m
m
94d
a
80
62
86
91
2
4
m
2
0
24
m
m
39

m
m
x(8)
89
m
79
92
26
100
m
16
11
m
46
m
m
m
x(8)
m
13
38
3
6
98
96
m
70
100
71
m
m
59

m
m
0
3
0
3
0
7
0
a
1
m
m
9
m
m
m
2
a
m
a
3
1
0
a
m
2
0
3
m
m
4

m
m
100d
3
0
13
1
67
0
m
24
m
m
48
m
m
m
98d
a
m
62
87
47
1
3
m
1
0
14
m
m
34

m
m
x(11)
94
100
84
99
26
100
m
75
m
m
43
m
m
m
x(11)
m
m
38
10
52
99
97
m
97
100
83
m
m
62

Flemish Comm. (Belgium)
French Comm. (Belgium)
England (UK)
Scotland (UK)

1
0
m
m

99
99
m
100d

0
1
m
x(2)

1
1
m
a

98
95
m
100d

1
3
m
x(5)

0
1
m
a

100
84
m
100d

0
15
m
x(8)

0
1
m
a

0
10
m
100d

100
89
m
x(11)

Argentina
Brazil
China
Colombia
Costa Rica
India
Indonesia
Lithuania
Russian Federation
Saudi Arabia
South Africa

m
28
m
m
m
m
m
m
m
m
m

m
72
m
m
m
m
m
m
m
m
m

m
0
m
m
m
m
m
m
m
m
m

m
23
m
m
m
m
m
m
m
m
m

m
77
m
m
m
m
m
m
m
m
m

m
1
m
m
m
m
m
m
m
m
m

m
11
m
m
m
m
m
m
m
m
m

m
87
m
m
m
m
m
m
m
m
m

m
2
m
m
m
m
m
m
m
m
m

m
5
m
m
m
m
m
m
m
m
m

m
92
m
m
m
m
m
m
m
m
m

m
2
m
m
m
m
m
m
m
m
m

Countries

Australia
Austria
Canada
Chile
Czech Republic
Denmark
Estonia
Finland
France1
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United States
Economies

Partners

Annex

OECD

Pre-primary

Note: See Definitions and Methodology sections for more information. Data available at http://stats.oecd.org/, Education at a Glance Database.
1. Data for pre-primary level refer to pre-primary and primary level teachers combined. Data for lower secondary level refer to lower secondary and upper secondary
combined.
Source: OECD (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933806370

446 Education at a Glance 2018: OECD Indicators   © OECD 2018

Under embargo until 11/09/2018 at 11.00am CEST

Annex

3

Sources, Methods
and Technical Notes
Annex 3 on sources and methods is available
in electronic form only. It can be found at:
http://dx.doi.org/10.1787/eag-2018-36-en

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447

Under embargo until 11/09/2018 at 11.00am CEST

Under embargo until 11/09/2018 at 11.00am CEST

Contributors to this publication
Many people have contributed to the development of this publication.
The following lists the names of the country representatives who have taken part to the INES meetings
and to the preparatory work leading to the publication Education at a Glance 2018: OECD Indicators.
The OECD wishes to thank them all for their valuable efforts.
INES Working Party
Ms Ana COPES (Argentina)
Ms Inés CRUZALEGUI (Argentina)
Mr Juan Manuel CORVALAN ESPINA (Argentina)
Mr Karl BAIGENT (Australia)
Mr Paul CMIEL (Australia)
Mr Patrick DONALDSON (Australia)
Mr Stuart FAUNT (Australia)
Ms Kee HIAUJOO (Australia)
Ms Rebecca SMEDLEY (Australia)
Mr Andreas GRIMM (Austria)
Ms Sabine MARTINSCHITZ (Austria)
Mr Mark NÉMET (Austria)
Mr Wolfgang PAULI (Austria)
Ms Helga POSSET (Austria)
Ms Natascha RIHA (Austria)
Mr Philippe DIEU (Belgium)
Ms Isabelle ERAUW (Belgium)
Ms Nathalie JAUNIAUX (Belgium)
Mr Guy STOFFELEN (Belgium)
Mr Raymond VAN DE SIJPE (Belgium)
Ms Ann VAN DRIESSCHE (Belgium)
Mr Pieter VOS (Belgium)
Mr Daniel Jaime CAPISTRANO DE OLIVEIRA (Brazil)
Ms Juliana MARQUES DA SILVA (Brazil)
Mr Patric BLOUIN (Canada)
Mr Richard FRANZ (Canada)
Ms Simone GREENBERG (Canada)
Ms Amanda HODGKINSON (Canada)
Ms Jolie LEMMON (Canada)
Mr David McBRIDE (Canada)
Mr Michael MARTIN (Canada)
Ms Klarka ZEMAN (Canada)
Mr Janusz ZIEMINSKI (Canada)
Mr Ignacio LARRAGUIBEL (Chile)
Ms Paola LEIVA (Chile)
Mr Fabián RAMÍREZ (Chile)
Mr Juan SALAMANCA (Chile)
Mr Roberto SCHURCH (Chile)
Ms Constanza VIELMA (Chile)
Ms Claudia DÍAZ (Colombia)
Ms Helga Milena HERNÁNDEZ (Colombia)
Mr Javier Andrés RUBIO (Colombia)
Ms Azucena Paola VALLEJO (Colombia)

Ms Elsa Nelly VELASCO (Colombia)
Mr Wilfer VALERO (Colombia)
Ms Erika VILLAMIL (Colombia)
Mr Andrés FERNÁNDEZ (Costa Rica)
Mr Miguel GUTIÉRREZ (Costa Rica)
Ms Eliecer RAMIREZ (Costa Rica)
Mr Vladimír HULÍK (Czech Republic)
Ms Michaela MARŠÍKOVÁ (Czech Republic)
Mr Lubomír MARTINEC (Czech Republic)
Mr Jens ANDERSEN (Denmark)
Mr Jens BJERRE (Denmark)
Ms Susanne Irvang NIELSEN (Denmark
Ms Signe Tychsen PHILIP (Denmark)
Ms Tiina ANNUS (Estonia)
Ms Katrin REIN (Estonia)
Ms Kadi SERBAK (Estonia)
Mr Jan PAKULSKI (European Commission)
Ms Christine COIN (Eurostat, European Commission)
Mr Arnaud DESURMONT (Eurostat, European Commission)
Mr Jacques LANNELUC (Eurostat, European Commission)
Ms Malgorzata STADNIK (Eurostat, European Commission)
Mr Mika TUONONEN (Finland)
Ms Kristiina VOLMARI (Finland)
Mr Cedric AFSA (France)
Ms Nathalie CARON (France)
Ms Marion DEFRESNE (France)
Ms Nadine ESQUIEU (France)
Ms Roselyne KERJOSSE (France)
Ms Florence LEFRESNE (France)
Ms Stéphanie LEMERLE (France)
Ms Valérie LIOGIER (France)
Ms Pascale POULET-COULIBANDO (France)
Mr Robert RAKOCEVIC (France)
Ms Marguerite RUDOLF (France)
Ms Julie SOLARD (France)
Mr Boubou TRAORE (France)
Ms Pia BRUGGER (Germany)
Mr Andreas SCHULZ (Germany)
Mr Hans-Werner FREITAG (Germany)
Mr Benny SCHNEIDER (Germany)
Mr Martin SCHULZE (Germany)
Ms Eveline VON GAESSLER (Germany)
Ms Susanne ZIEMEK (Germany)
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449

Contributors
Under embargo until 11/09/2018 at 11.00am CEST
Mr Michael LENZEN (Germany)
Ms Dimitra FARMAKIOTOU (Greece)
Ms Maria FASSARI (Greece)
Mr Antonios KRITIKOS (Greece)
Ms Vassiliki MAKRI (Greece)
Ms Evdokia OIKONOMOU (Greece)
Mr Athanasios STAVROPOULOS (Greece)
Ms Madga TRANTALLIDI (Greece)
Mr István BUCSI SZABÓ (Hungary)
Ms Dóra GÉCZI (Hungary)
Ms Tünde HAGYMÁSY (Hungary)
Ms Sára HATONY (Hungary)
Mr Tamás HAVADY (Hungary)
Mr Tibor KÖNYVESI (Hungary)
Mr László LIMBACHER (Hungary)
Mr Krisztián SZÉLL (Hungary)
Mr Gunnar J. ÁRNASON (Iceland)
Ms Ásta M. URBANCIC (Iceland)
Ms Swapna BHATTACHARYA (India)
Mr Tayyab MOHAMMAD (India)
Ms Deirdre CULLEN (Ireland)
Mr Pádraig MAC FHLANNCHADHA (Ireland)
Ms Violeta MOLONEY (Ireland)
Mr Diarmuid REIDY (Ireland)
Ms Sophie ARTSEV (Israel)
Mr Yoav AZULAY (Israel)
Ms Orit BARANY (Israel)
Mr Matan CHOCRON (Israel)
Mr Yosef GIDANIAN (Israel)
Ms Osnat LANDAU (Israel)
Mr Daniel LEVI-MAZLOUM (Israel)
Ms Silvia Liplewski (Israel)
Ms Iris Avigail MATATYAHU (Israel)
Mr Haim PORTNOY (Israel)
Ms Michal SALANSKI (Israel)
Ms Naama STEINBERG (Israel)
Ms Einat Weiss (Israel)
Mr Massimiliano CICCIA (Italy)
Ms Gemma DE SANCTIS (Italy)
Ms Daniela DI ASCENZO (Italy)
Ms Paola DI GIROLAMO (Italy)
Ms Maria Teresa MORANA (Italy)
Ms Claudia PIZZELLA (Italy)
Mr Paolo SESTITO (Italy)
Mr Paolo TURCHETTI (Italy)
Mr Takashi FURUDATE (Japan)
Ms Satoko IMAMURA (Japan)
Mr Yu KAMEOKA (Japan)
Mr Takashi KIRYU (Japan)
Ms Saki KISHIDA (Japan)
Mr Koji MAKINO (Japan)
Mr Shingo NAGAMI (Japan)
Mr Hiromi SASAI (Japan)
Mr Kenichiro TAKAHASHI (Japan)

450 Education at a Glance 2018: OECD Indicators   © OECD 2018

Ms Hiromi TANAKA (Japan)
Ms Kumiko TANSHO-HIRABAYASHI (Japan)
Mr Chang Woan YANG (Korea)
Mr Ho Hyeong LEE (Korea)
Ms Yeong Ok KIM (Korea)
Ms Hee Kyung KWON (Korea)
Ms Won Hee NA(Korea)
Ms Sun Ae YUN (Korea)
Ms Eun Ji LEE (Korea)
Mr Yeon Cheon KIM (Korea)
Ms Han Nah KIM (Korea)
Ms Yoon Hee IM (Korea)
Ms Sol Hwi KIM (Korea)
Mr Hyo Jung JU (Korea)
Ms Gui Ah KIM (Korea)
Ms Anita Švarckopfa (Latvia)
Mr Pēteris Veģis (Latvia)
Mr Aleksandrs Aleksandrovs (Latvia)
Mr Rolands Ņikitins (Latvia)
Mr Viktors Kravčenko (Latvia)
Mr Ričardas ALIŠAUSKAS (Lithuania)
Ms Salvinija CHOMIČIENĖ (Lithuania)
Ms Gailė DAPŠIENĖ (Lithuania)
Ms Rita DUKYNAITĖ (Lithuania)
Ms Daiva MARCINKEVIČIENĖ (Lithuania)
Ms Elisa MAZZUCATO (Luxembourg)
Mr Antonio ÁVILA DÍAZ (Mexico)
Ms Teresa BRACHO GONZÁLEZ (Mexico)
Mr Marco CALDERÓN ARGOMEDO (Mexico)
Mr Luis DEGANTE MÉNDEZ (Mexico)
Mr René GÓMORA CASTILLO (Mexico)
Mr Rolando Erick MAGAÑA RODRIGUEZ (Mexico)
Mr Tomás RAMÍREZ REYNOSO (Mexico)
Ms María del Carmen REYES GUERRERO (Mexico)
Mr Héctor Virgilio ROBLES VASQUEZ (Mexico)
Mr Gerardo H. TERRAZAS GONZÁLEZ (Mexico)
Mr Lorenzo VERGARA LÓPEZ (Mexico)
Ms Danielle ANDARABI (Netherlands)
Mr Maarten BALVERS (Netherlands)
Mr Joost SCHAACKE (Netherlands)
Ms Priscilla TEDJAWIRJA (Netherlands)
Ms Anouschka VAN DER MEULEN (Netherlands)
Ms Floor VAN OORT (Netherlands)
Ms Megan CHAMBERLAIN (New Zealand)
Ms Jessica FORKERT (New Zealand)
Mr David JAGGER (New Zealand)
Ms Nicola MARSHALL (New Zealand)
Mr Aaron NORGROVE (New Zealand)
Ms Beth RUST (New Zealand)
Mr David SCOTT (New Zealand)
Mr Zane VERRAN (New Zealand)
Ms Inga BILSTAD BRØYN (Norway)
Mr Sadiq Kwesi BOATENG (Norway)
Mr Øyvind KLUBBEN LEKNESSUND (Norway)

Contributors
Under embargo until 11/09/2018 at 11.00am CEST
Mr Christian Weisæth MONSBAKKEN (Norway)
Mr Geir NYGÅRD (Norway)
Mr Sverre RUSTAD (Norway)
Ms Anne Marie RUSTAD HOLSETER (Norway)
Ms Alette SCHREINER (Norway)
Ms Suzanne SKJØRBERG (Norway)
Ms Barbara ANTOSIEWICZ (Poland)
Ms Joanna DACIUK-DUBRAWSKA (Poland)
Ms Renata KORZENIOWSKA-PUCUŁEK (Poland)
Mr Andrzej KURKIEWICZ (Poland)
Ms Anna NOWOŻYŃSKA (Poland)
Ms Małgorzata ŻYRA (Poland)
Ms Mónica LUENGO (Portugal)
Mr Carlos Alberto MALACA (Portugal)
Ms Rute NUNES (Portugal)
Mr Marco PIMENTA (Portugal)
Ms Dora Pereira (Portugal)
Mr Joao PEREIRA DE MATOS (Portugal)
Mr José RAFAEL (Portugal)
Mr Nuno Miguel RODRIGUES (Portugal)
Mr Joaquim SANTOS (Portugal)
Mr Amaro Vieira (Portugal)
Mr Mark AGRANOVICH (Russian Federation)
Ms Julia ERMACHKOVA (Russian Federation)
Ms Irina SELIVERSTOVA (Russian Federation)
Mr Abdulrahman S. AL-ANGARI (Saudi Arabia)
Mr Saad ALBAIZ (Saudi Arabia)
Mr Peter BRODNIANSKY (Slovak Republic)
Ms Eva HLADIKOVA (Slovak Republic)
Ms Danica OMASTOVA (Slovak Republic)
Mr Roman SAJBIDOR (Slovak Republic)
Ms Gabriela SLODICKOVA (Slovak Republic)
Mr Dejan ARANĐELOVIĆ (Slovenia)
Ms Nina Češek Vozel (Slovenia)
Ms Andreja KOZMELJ (Slovenia)
Ms Barbara KRESAL STERNIŠA (Slovenia)
Ms Duša MARJETIČ (Slovenia)
Ms Karmen SVETLIK (Slovenia)
Ms Tatjana ŠKRBEC (Slovenia)
Ms Jadranka TUŠ (Slovenia)

Ms Darja VIDMAR (Slovenia)
Ms Rirhandzu BALOYI (South Africa)
Ms Mamphokhu KHULUVHE (South Africa)
Ms Letho MAPASEKA (South Africa)
Ms Bheki MPANZA (South Africa)
Ms Hersheela NARSEE (South Africa)
Ms Matome SEKGOTA (South Africa)
Ms Nthabiseng TEMA (South Africa)
Ms Cristina ABARCA del VILLAR (Spain)
Mr Miguel Ángel ÁLVAREZ ESPINOSA (Spain)
Ms Elena BANDA LÓPEZ (Spain)
Mr Leonardo CARUANA DE LAS CAGIGAS (Spain)
Mr Jesús IBAÑEZ MILLA (Spain)
Mr Joaquín MARTÍN MUÑOZ (Spain)
Ms Ana REVILLA TRUJILLO (Spain)
Ms Carmen TOVAR SÁNCHEZ (Spain)
Mr Jaime VAQUERO JIMÉNEZ (Spain)
MS Isabel YUN MORENO (Spain)
Ms Anna ERIKSSON (Sweden)
Ms Maria GÖTHERSTRÖM (Sweden)
Ms Marie KAHLROTH (Sweden)
Mr Alexander GERLINGS (Switzerland)
Ms Katrin HOLENSTEIN (Switzerland)
Ms Nicole SCHÖBI (Switzerland)
Mr Emanuel VON ERLACH (Switzerland)
Ms Hatice Nihan ERDAL (Turkey)
Ms Nuriye KABASAKAL (Turkey)
Mr Adolfo Gustavo IMHOF (UNESCO)
Ms Anuja SINGH (UNESCO)
Mr Said Ould Ahmedou VOFFAL (UNESCO)
Mr Bruce GOLDING (United Kingdom)
Ms Emily KNOWLES (United Kingdom)
Ms Aliki PAREAS (United Kingdom)
Ms Melissa DILIBERTI (United States)
Ms Rachel DINKES (United States)
Ms Jana KEMP (United States)
Ms Lauren MUSU-GILLETTE (United States)
Ms Ashley ROBERTS (United States)
Mr Thomas SNYDER (Chair INES Working Party, United States)

Network on Labour Market, Economic and Social Outcomes of Learning (LSO)
Mr Karl BAIGENT (Australia)
Mr Paul CMIEL (Australia)
Mr Patrick DONALDSON (Australia)
Mr Stuart FAUNT (Australia)
Ms Kee HIAUJOO (Australia)
Ms Rebecca SMEDLEY (Australia)
Mr Mark NÉMET (Austria)
Ms Isabelle ERAUW (Belgium)
Ms Geneviève HINDRYCKX (Belgium)
Mr Kasper OSSENBLOK (Belgium)

Ms Naomi WAUTERICKX (Belgium)
Ms Camila NEVES SOUTO (Brazil)
Ms Margarete da SILVA SOUZA (Brazil)
Mr Patric BLOUIN (Canada)
Ms Jolie LEMMON (Canada)
Ms Dallas MORROW (Canada)
Mr Marco SERAFINI (CEDEFOP)
Mr Daniel SCHEUREGGER (CEDEFOP)
Mr Ignacio LARRAGUIBEL (Chile)
Ms Paola LEIVA (Chile)
Education at a Glance 2018: OECD Indicators   © OECD 2018

451

Contributors
Under embargo until 11/09/2018 at 11.00am CEST
Mr Fabián RAMÍREZ (Chile)
Mr Roberto SCHURCH (Chile)
Ms Constanza VIELMA (Chile)
Mr Vladimír HULÍK (Czech Republic)
Ms Michaela MARŠÍKOVÁ (Czech Republic)
Ms Lidia GONZÁLEZ (Costa Rica)
Ms Dianny HERNÁNDEZ RUÍZ (Costa Rica)
Ms María Luz SANARRUSIA SOLANO (Costa Rica)
Mr Jens ANDERSEN (Denmark)
Ms Tiina ANNUS (Estonia)
Ms Kristel BANKIER (Estonia)
Ms Ingrid JAGGO (Estonia)
Mr Priit LAANOJA (Estonia)
Ms Marianne LEPPIK (Estonia)
Mr Marti Lillemägi (Estonia)
Ms Kaire Raasik (Estonia)
Ms Aune VALK (Estonia)
Mr Jens FISHER-KOTTENSTEDE (European Commission)
Mr Mantas SEKMOKAS (European Commission)
Ms Elodie CAYOTTE (Eurostat, European Commission)
Ms Sabine GAGEL (Eurostat, European Commission)
Ms Irja BLOMQVIST (Finland)
Mr Mika WITTING (Finland)
Ms Nathalie CARON (France)
Ms Pascale POULET-COULIBANDO (France)
Mr Hans-Werner FREITAG (Germany)
Ms Sylvia SCHILL (Germany)
Ms Susanne ZIEMEK (Germany)
Ms Maria FASSARI (Greece)
Mr Vasileios KARAVITIS (Greece)
Ms Athena PLESSA-PAPADAKI (Greece)
Ms Magda TRANTALLIDI (Greece)
Mr Georgios VAFIAS (Greece)
Mr László LIMBACHER (Hungary)
Mr István BUCSI SZABÓ (Hungary)
Ms Ásta M. URBANCIC (Iceland)
Ms Deirdre CULLEN (Ireland)
Ms Helen MAXWELL (Ireland)
Ms Helen MCGRATH (Ireland)
Ms Violeta MOLONEY (Ireland)
Mr Diarmuid REIDY (Ireland)
Ms Tracey SHANKS (Ireland)
Ms Sophie ARTSEV (Israel)
Mr Yonatan HAYUN (Israel)
Ms Rebecca KRIEGER (Israel)
Mr Haim PORTNOY (Israel)
Ms Raffaella CASCIOLI (Italy)
Mr Gaetano PROTO (Italy)
Ms Liana VERZICCO (Italy)
Mr Chang Woan YANG (Korea)
Mr Ho Hyeong LEE (Korea)
Ms Yeong Ok KIM (Korea)
Ms Hea Jun YOON (Korea)

452 Education at a Glance 2018: OECD Indicators   © OECD 2018

Ms Sook Weon MIN (Korea)
Ms Hee Kyung KWON (Korea)
Ms Sun Ae YUN (Korea)
Ms Zane Pallo-Mangale (Latvia)
Mr Viktors Kravčenko (Latvia)
Mr Eduardas DAUJOTIS (Lithuania)
Ms Jolita GALECKIENĖ (Lithuania)
Mr Gintautas JAKŠTAS (Lithuania)
Ms Julija UMBRASAITĖ (Lithuania)
Ms Karin MEYER (Luxembourg)
Mr Héctor Virgilio ROBLES VÁSQUEZ (Mexico)
Mr Gerardo H. TERRAZAS GONZÁLEZ (Mexico)
Mr Ted REININGA (Netherlands)
Ms Francis VAN DER MOOREN (Netherlands)
Ms Antoinette VAN WANROIJ (Netherlands)
Ms Megan CHAMBERLAIN (New Zealand)
Ms Jessica FORKERT (New Zealand)
Mr David JAGGER (New Zealand)
Ms Nicola MARSHALL (New Zealand)
Mr Aaron NORGROVE (New Zealand)
Ms Beth RUST (New Zealand)
Mr David SCOTT (New Zealand)
Mr Zane VERRAN (New Zealand)
Ms Hild Marte BJØRNSEN (Norway)
Mr Sadiq-Kwesi BOATENG (Norway)
Mr Piotr JAWORSKI (Poland)
Mr Jacek MAŚLANKOWSKI (Poland)
Ms Anna NOWOŻYŃSKA (Poland)
Ms Hanna ZIELIŃSKA (Poland)
Mr Carlos Alberto MALACA (Portugal)
Mr Joaquim SANTOS (Portugal)
Mr Mark AGRANOVICH (Russian Federation)
Ms Elena SABELNIKOVA (Russian Federation)
Mr Frantisek BLANAR (Slovak Republic)
Ms Nina Češek Vozel (Slovenia)
Mr Matej DIVJAK (Slovenia)
Ms Melita SELJAK (Slovenia)
Mr Miguel Ángel ÁLVAREZ ESPINOSA (Spain)
Mr Jesús IBAÑEZ MILLA (Spain)
Mr Raúl SAN SEGUNDO (Spain)
Ms Ann-Charlott LARSSON (Sweden)
Mr Mattias FRITZ (Sweden)
Ms Anna BENGTSSON (Sweden)
Ms Wayra CABALLERO LIARDET (Switzerland)
Mr Emanuel VON ERLACH (Chair LSO Network, Switzerland)
Mr Davut OLGUN (Turkey)
Mr Cengiz SARAÇOĞLU (Turkey)
Mr Bruce GOLDING (United Kingdom)
Ms Alicia HEPTINSTALL (United Kingdom)
Ms Rachel DINKES (United States)
Ms Ashley ROBERTS (United States)
Mr Thomas SNYDER (United States)

Contributors
Under embargo until 11/09/2018 at 11.00am CEST
Network for the Collection and Adjudication of System-level descriptive Information on Educational Structures,
Policies and Practices (NESLI)
Mr Karl BAIGENT (Australia)
Mr Stuart FAUNT (Australia)
Ms Kee HIAUJOO (Australia)
Ms Antonella SALPIETRO (Australia)
Ms Rebecca SMEDLEY (Australia)
Mr Andreas GRIMM (Austria)
Mr Stefan POLZER (Austria)
Mr Philippe DIEU (Belgium)
Ms Nathalie JAUNIAUX (Belgium)
Ms Bernadette SCHREUER (Belgium)
Mr Raymond VAN DE SIJPE (Belgium)
Ms Ann VAN DRIESSCHE (Belgium)
Mr Daniel Jaime CAPISTRANO DE OLIVEIRA (Brazil)
Ms Juliana MARQUES DA SILVA (Brazil)
Mr Richard FRANZ (Canada)
Ms Simone GREENBERG (Canada)
Ms Jolie LEMMON (Canada)
Mr Michael MARTIN (Canada)
Mr Brett WILMER (Canada)
Ms Klarka ZEMAN (Canada)
Mr Ignacio LARRAGUIBEL (Chile)
Ms Paola LEIVA (Chile)
Mr Fabián RAMÍREZ (Chile)
Mr Roberto SCHURCH (Chile)
Ms Constanza VIELMA (Chile)
Mr Vladimír HULÍK (Czech Republic)
Ms Michaela MARŠÍKOVÁ (Czech Republic)
Mr Lubomír MARTINEC (Czech Republic)
Mr Jorgen Balling RASMUSSEN (Denmark)
Ms Tiina ANNUS (Estonia)
Ms Hanna KANEP (Estonia)
Ms Kristel VAHER (Estonia)
Ms Hille Vares (Estonia)
Ms Lene MEJER (European Commission)
Ms Nathalie BAIDAK (Eurydice)
Ms Arlette DELHAXHE (Eurydice)
Ms Petra PACKALEN (Finland)
Ms Kristiina VOLMARI (Finland)
Ms Florence LEFRESNE (France)
Ms Valérie LIOGIER (France)
Mr Robert RAKOCEVIC (France)
Mr Thomas ECKHARDT (Germany)
Mr Benny SCHNEIDER (Germany)
Mr Marco MUNDELIUS (Germany)
Ms Dimitra FARMAKIOUTOU (Greece)
Ms Maria FASSARI (Greece)
Ms Eudokia KARDAMITSI (Greece)
Mr Georgios MALLIOS (Greece)
Mr Stylianos MERKOURIS (Greece)
Mr Konstantinos PAPACHRISTOS (Greece)
Ms Athena PLESSA-PAPADAKI (Greece)

Ms Magda TRANTALLIDI (Greece)
Ms Sára HATONY (Hungary)
Mr István BUCSI SZABÓ (Hungary)
Mr Gunnar J. ÁRNASON (Iceland)
Ms Asta URBANCIC (Iceland)
Ms Deirdre CULLEN (Ireland)
Mr Pádraig MAC FHLANNCHADHA (Ireland)
Ms Violeta MOLONEY (Ireland)
Mr Diarmuid REIDY (Ireland)
Mr Yoav AZULAY (Israel)
Mr Pinhas KLEIN (Israel)
Mr Aviel KRENTZLER (Israel)
Mr Daniel LEVI-MAZLOUM (Israel)
Mr David MAAGAN (Israel)
Mr Rakan MORAD SHANNAN (Israel)
Ms Gianna BARBIERI (Italy)
Ms Lucia DE FABRIZIO (Italy)
Ms Annarita Lina MARZULLO (Italy)
Mr Kota OSHIO (Japan)
Mr Takayuki SUGIMOTO (Japan)
Ms Kumiko TANSHO-HIRABAYASHI (Japan)
Mr Chang Woan YANG (Korea)
Mr Ho Hyeong LEE (Korea)
Ms Yeong Ok KIM (Korea)
Ms Hee Kyung KWON (Korea)
Ms Han Nah KIM (Korea)
Ms Modra Jansone (Latvia)
Mr Viktors Kravčenko (Latvia)
Mr Ričardas ALIŠAUSKAS (Lithuania)
Mr Evaldas BAKONIS (Lithuania)
Mr Ovidijus DAMSKIS (Lithuania)
Mr Eduardas DAUJOTIS (Lithuania)
Ms Rima ZABLACKĖ (Lithuania)
Mr Gilles HIRT (Luxembourg)
Ms Charlotte MAHON (Luxembourg)
Ms Elisa MAZZUCATO (Luxembourg)
Mr Antonio ÁVILA DÍAZ (Mexico)
Mr Marco CALDERÓN ARGOMEDO (Mexico)
Mr Juan Martín SOCA DE IÑIGO (Mexico)
Mr Thijs NOORDZIJ (Netherlands)
Mr Hans RUESINK (Chair of NESLI Network, Netherlands)
Mr Jerry STRATEN (Netherlands)
Mr Dick VAN VLIET (Netherlands)
Ms Megan CHAMBERLAIN (New Zealand)
Ms Jessica FORKERT (New Zealand)
Mr David JAGGER (New Zealand)
Ms Nicola MARSHALL (New Zealand)
Mr Aaron NORGROVE (New Zealand)
Ms Beth RUST (New Zealand)
Mr David SCOTT (New Zealand)
Mr Zane VERRAN (New Zealand)
Education at a Glance 2018: OECD Indicators   © OECD 2018

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Contributors
Under embargo until 11/09/2018 at 11.00am CEST
Mr Christian Weisæth MONSBAKKEN (Norway)
Ms Renata KARNAS (Poland)
Ms Renata KORZENIOWSKA-PUCUŁEK (Poland)
Ms Anna NOWOŻYŃSKA (Poland)
Mr Joaquim SANTOS (Portugal)
Mr Mark AGRANOVICH (Russian Federation)
Ms Julia ERMACHKOVA (Russian Federation)
Ms Eva HLADIKOVA (Slovak Republic)
Ms Gabriela SLODICKOVA (Slovak Republic)
Ms Barbara KRESAL-STERNIŠA (Slovenia)
Ms Duša MARJETIČ (Slovenia)
Ms Karmen SVETLIK (Slovenia)
Ms Tanja TAŠTANOSKA (Slovenia)
Mr Antonio ALAMILLO SÁNCHEZ (Spain)
Ms Inmaculada CABEZALÍ MONTERO (Spain)

Mr Joaquin MARTIN MUÑOZ (Spain)
Mr Jaime VAQUERO JIMÉNEZ (Spain)
Mr Joaquín VERA MOROS (Spain)
Mr Christian LOVERING (Sweden)
Mr Tomas GUSTAVSSON) (Sweden)
Ms Katrin MÜHLEMANN (Switzerland)
Mr Davut OLGUN (Turkey)
Mr Osman Yıldırım UĞUR (Turkey)
Mr Matthew BRIDGE (United Kingdom)
Mr Bruce GOLDING (United Kingdom)
Mr Adrian HIGGINBOTHAM (United Kingdom)
Mr Yousaf KANAN (United Kingdom)
Ms Jana KEMP (United States)
Ms Lauren MUSU-GILLETTE (United States)

Other contributors to this publication
BRANTRA SPRL (Translation)
Mr Jit CHEUNG (LSO consultant)
Ms Susan COPELAND (Edition)

454 Education at a Glance 2018: OECD Indicators   © OECD 2018

Mr Patrice DE BROUCKER (LSO consultant)
Ms Sally Caroline HINCHCLIFFE (Edition)
Ms Fung Kwan TAM (Layout)

Under embargo until 11/09/2018 at 11.00am CEST

Education Indicators in Focus
Education Indicators in Focus is a series of OECD briefs that highlight specific indicators in Education at a Glance that
are of particular interest to policy makers and practitioners. These briefs provide a detailed look into current issues
in pre-primary, primary and secondary education, higher education, and adult outcomes from a global perspective.
They contain an engaging mix of text, tables and charts that describe the international context of the most pressing
questions in education policy and practice.
The complete series is available at:
English: http://dx.doi.org/10.1787/22267077
French: http://dx.doi.org/10.1787/22267093

“How does the earnings advantage of tertiary-educated workers evolve across generations?”, Education
Indicators in Focus, No. 62 (2018)
https://doi.org/10.1787/3093362c-en
“How is the tertiary-educated population evolving?”, Education Indicators in Focus, No. 61 (2018)
https://doi.org/10.1787/a17e95dc-en
“How is depression related to education?”, Education Indicators in Focus, No. 60 (2018)
https://doi.org/10.1787/782fc82d-en
“How does access to early childhood education services affect the participation of women in the labour
market?”, Education Indicators in Focus, No. 59 (2018)
https://doi.org/10.1787/232211ca-en
“How do primary and secondary teachers compare?”, Education Indicators in Focus, No. 58 (2018)
https://doi.org/10.1787/535e7f54-en
“Is labour market demand keeping pace with the rising educational attainment of the population?”, Education
Indicators in Focus, No. 57 (2017)
https://doi.org/10.1787/1410f36e-en
“Who really bears the cost of education?”, Education Indicators in Focus, No. 56 (2017)
https://doi.org/10.1787/4c4f545b-en
“What are the gender differences and the labour market outcomes across the different fields of study?”,
Education Indicators in Focus, No. 55 (2017)
https://doi.org/10.1787/7913d157-en
“Transition from school to work: How hard is it across different age groups?”, Education Indicators in Focus,
No. 54 (2017)
https://doi.org/10.1787/1e604198-en
“How have teachers’ salaries evolved and how do they compare to those of tertiary-educated workers?”,
Education Indicators in Focus, No. 53 (2017)
http://dx.doi.org/10.1787/b5f69f4c-en
“Who bears the cost of early childhood education and how does it affect enrolment?”, Education Indicators in
Focus, No. 52 (2017)
http://dx.doi.org/10.1787/e1a6c198-en
“Tuition fee reforms and international mobility”, Education Indicators in Focus, No. 51 (2017)
http://dx.doi.org/10.1787/2dbe470a-en
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455

Education Indicators in Focus
Under embargo until 11/09/2018 at 11.00am CEST
“Educational attainment and investment in education in Ibero-American countries”, Education Indicators in
Focus, No. 50 (2017)
http://dx.doi.org/10.1787/48a205fb-en
“Gender imbalances in the teaching profession”, Education Indicators in Focus, No. 49 (2017)
http://dx.doi.org/10.1787/54f0ef95-en
“Educational attainment: A snapshot of 50 years of trends in expanding education”, Education Indicators in
Focus, No. 48 (2017)
http://dx.doi.org/10.1787/409ceb2b-en
“How are health and life satisfaction related to education?”, Education Indicators in Focus, No. 47 (2016)
http://dx.doi.org/10.1787/6b8ca4c5-en
“What influences spending on education?”, Education Indicators in Focus, No. 46 (2016)
http://dx.doi.org/10.1787/5jln041965kg-en
“Fields of education, gender and the labour market”, Education Indicators in Focus, No. 45 (2016)
http://dx.doi.org/10.1787/5jlpgh1ppm30-en
“Attainment and labour market outcomes among young tertiary graduates”, Education Indicators in Focus,
No. 44 (2016)
http://dx.doi.org/10.1787/5jlsmkvp0slq-en
“Subnational variations in educational attainment and labour market outcomes”, Education Indicators in Focus,
No. 43 (2016)
http://dx.doi.org/10.1787/5jlvc7mddlkl-en
“What are the benefits from early childhood education?”, Education Indicators in Focus, No. 42 (2016)
http://dx.doi.org/10.1787/5jlwqvr76dbq-en
“How much do tertiary students pay and what public support do they receive?”, Education Indicators in Focus,
No. 41 (2016)
http://dx.doi.org/10.1787/5jlz9zk830hf-en
“Teachers’ ICT and problem-solving skills”, Education Indicators in Focus, No. 40 (2016)
http://dx.doi.org/10.1787/5jm0q1mvzqmq-en
“The internationalisation of doctoral and master’s studies”, Education Indicators in Focus, No. 39 (2016)
http://dx.doi.org/10.1787/5jm2f77d5wkg-en
“How is learning time organised in primary and secondary education?”, Education Indicators in Focus, No. 38
(2015)
http://dx.doi.org/10.1787/5jm3tqsm1kq5-en
“Who are the bachelor’s and master’s graduates?”, Education Indicators in Focus, No. 37 (2016)
http://dx.doi.org/10.1787/5jm5hl10rbtj-en
“What are the benefits of ISCED 2011 classification for indicators on education?”, Education Indicators in Focus,
No. 36 (2015)
http://dx.doi.org/10.1787/5jrqgdw9k1lr-en
“How do differences in social and cultural background influence access to higher education and the completion
of studies?”, Education Indicators in Focus, No. 35 (2015)
http://dx.doi.org/10.1787/5jrs703c47s1-en
“What are the advantages today of having an upper secondary qualification?”, Education Indicators in Focus,
No. 34 (2015)
http://dx.doi.org/10.1787/5jrw5p4jn426-en

456 Education at a Glance 2018: OECD Indicators   © OECD 2018

Education Indicators in Focus
Under embargo until 11/09/2018 at 11.00am CEST
“Focus on vocational education and training (VET) programmes”, Education Indicators in Focus, No. 33 (2015)
http://dx.doi.org/10.1787/5jrxtk4cg7wg-en
“Are education and skills being distributed more inclusively?”, Education Indicators in Focus, No. 32 (2015)
http://dx.doi.org/10.1787/5js0bsgdtr28-en
“How is the global talent pool changing (2013, 2030)?”, Education Indicators in Focus, No. 31 (2015)
http://dx.doi.org/10.1787/5js33lf9jk41-en
“Education and employment - What are the gender differences?”, Education Indicators in Focus, No. 30 (2015)
http://dx.doi.org/10.1787/5js4q17gg540-en
“How much time do teachers spend on teaching and non-teaching activities?”, Education Indicators in Focus,
No. 29 (2015)
http://dx.doi.org/10.1787/5js64kndz1f3-en
“Are young people attaining higher levels of education than their parents?”, Education Indicators in Focus,
No. 28 (2015)
http://dx.doi.org/10.1787/5js7lx8zx90r-en
“What are the earnings advantages from education?”, Education Indicators in Focus, No. 27 (2014)
http://dx.doi.org/10.1787/5jxrcllj8pwl-en
“Learning Begets Learning: Adult Participation in Lifelong Education”, Education Indicators in Focus, No. 26 (2014)
http://dx.doi.org/10.1787/5jxsvvmr9z8n-en
“Who are the doctorate holders and where do their qualifications lead them?”, Education Indicators in Focus,
No. 25 (2014)
http://dx.doi.org/10.1787/5jxv8xsvp1g2-en
“How innovative is the education sector?”, Education Indicators in Focus, No. 24 (2014)
http://dx.doi.org/10.1787/5jz1157b915d-en
“At what age do university students earn their first degree?”, Education Indicators in Focus, No. 23 (2014)
http://dx.doi.org/10.1787/5jz3wl5rvjtk-en
“How much time do primary and lower secondary students spend in the classroom?”, Education Indicators in
Focus, No. 22 (2014)
http://dx.doi.org/10.1787/5jz44fnl1t6k-en
“How much are teachers paid and how much does it matter?”, Education Indicators in Focus, No. 21 (2014)
http://dx.doi.org/10.1787/5jz6wn8xjvvh-en
“How old are the teachers?”, Education Indicators in Focus, No. 20 (2014)
http://dx.doi.org/10.1787/5jz76b5dhsnx-en
“What are tertiary students choosing to study?”, Education Indicators in Focus, No. 19 (2014)
http://dx.doi.org/10.1787/5jz8ssmzg5q4-en
“What is the impact of the economic crisis on public education spending?”, Education Indicators in Focus, No. 18
(2013)
http://dx.doi.org/10.1787/5jzbb2sprz20-en
“Does upper secondary vocational education and training improve the prospects of young adults?”, Education
Indicators in Focus, No. 17 (2013)
http://dx.doi.org/10.1787/5jzbb2st885l-en
“How can countries best produce a highly-qualified young labour force?”, Education Indicators in Focus, No. 16
(2013)
http://dx.doi.org/10.1787/5k3wb8khp3zn-en
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457

Education Indicators in Focus
Under embargo until 11/09/2018 at 11.00am CEST
“How are university students changing?”, Education Indicators in Focus, No. 15 (2015)
http://dx.doi.org/10.1787/5k3z04ch3d5c-en
“How is international student mobility shaping up?”, Education Indicators in Focus, No. 14 (2013)
http://dx.doi.org/10.1787/5k43k8r4k821-en
“How difficult is it to move from school to work?”, Education Indicators in Focus, No. 13 (2013)
http://dx.doi.org/10.1787/5k44zcplv70q-en
“Which factors determine the level of expenditure on teaching staff?”, Education Indicators in Focus, No. 12 (2013)
http://dx.doi.org/10.1787/5k4818h3l242-en
“How do early childhood education and care (ECEC) policies, systems and quality vary across OECD countries?”,
Education Indicators in Focus, No. 11 (2013)
http://dx.doi.org/10.1787/5k49czkz4bq2-en
“What are the social benefits of education?”, Education Indicators in Focus, No. 10 (2013)
http://dx.doi.org/10.1787/5k4ddxnl39vk-en
“How does class size vary around the world?”, Education Indicators in Focus, No. 9 (2012)
http://dx.doi.org/10.1787/5k8x7gvpr9jc-en
“Is increasing private expenditure, especially in tertiary education, associated with less public funding and less
equitable access?”, Education Indicators in Focus, No. 8 (2012)
http://dx.doi.org/10.1787/5k8zs43nlm42-en
“How well are countries educating young people to the level needed for a job and a living wage?”, Education
Indicators in Focus, No. 7 (2012)
http://dx.doi.org/10.1787/5k91d4fsqj0w-en
“What are the returns on higher education for individuals and countries?”, Education Indicators in Focus, No. 6
(2012)
http://dx.doi.org/10.1787/5k961l69d8tg-en
“How is the global talent pool changing?”, Education Indicators in Focus, No. 5 (2012)
http://dx.doi.org/10.1787/5k97krns40d4-en
“How pronounced is income inequality around the world – and how can education help reduce it?”, Education
Indicators in Focus, No. 4 (2012)
http://dx.doi.org/10.1787/5k97krntvqtf-en
“How are girls doing in school – and women doing in employment – around the world?”, Education Indicators
in Focus, No. 3 (2012)
http://dx.doi.org/10.1787/5k9csf9bxzs7-en
“How are countries around the world supporting students in higher education?”, Education Indicators in Focus,
No. 2 (2012)
http://dx.doi.org/10.1787/5k9fd0kd59f4-en
“How has the global economic crisis affect people with different levels of education?”, Education Indicators in
Focus, No. 1 (2012)
http://dx.doi.org/10.1787/5k9fgpwlc6s0-en

458 Education at a Glance 2018: OECD Indicators   © OECD 2018

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The OECD member countries are: Australia, Austria, Belgium, Canada, Chile, the Czech Republic, Denmark,
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Education at a Glance 2018
OECD INDICATORS
Education at a Glance: OECD Indicators is the authoritative source for information on the state of education
around the world. It provides data on the structure, finances and performance of education systems
in the 35 OECD and a number of partner countries.
With more than 100 charts and tables included in the publication and links to much more available on the
educational database, Education at a Glance 2018 provides key information on the output of educational
institutions; the impact of learning across countries; access, participation and progression in education;
the financial resources invested in education; and teachers, the learning environment and the organisation
of schools.
New material in the 2018 edition includes:
• a focus on equity, investigating how progress through education and the associated learning and labour
market outcomes are impacted by dimensions such as gender, parents’ educational attainment, immigrant
background, and regional location
• a chapter dedicated to Target 4.5 of the Sustainable Development Goal 4 on equity in education, providing
an assessment of where OECD and partner countries stand in providing equal access to quality education
at all levels
• a new indicator on equity in entry to and graduation from tertiary education
• a new indicator on the levels of decision-making in education systems
• data on the statutory and actual salaries of school heads
• data on repeaters in lower and upper secondary general programmes
• trend data on expenditure on early childhood education and care, and data on the enrolment of children
in all registered early childhood education and care settings.
The Excel™ spreadsheets used to create the tables and charts in Education at a Glance are available via
the StatLinks provided throughout the publication. Tables and charts, as well as the complete OECD education
Database, are available via the OECD education website at www.oecd.org/education/education-at-aglance-19991487.htm. Updated data can be found online at http://dx.doi.org/10.1787/eag-data-en.

Consult this publication on line at: http://dx.doi.org/10.1787/eag-2018-en
This work is published on the OECD iLibrary, which gathers all OECD books, periodicals and statistical databases.
Visit www.oecd-ilibrary.org for more information.

ISBN 978-92-64-30338-6
96 2018 02 1P