Education at a Glance 2019
OECD INDICATORS

Education at a Glance
2019
OECD INDICATORS

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 OECD member countries.
This document, as well as any data and any map included herein, are without prejudice
to the status of or sovereignty over any territory, to the delimitation of international
frontiers and boundaries and to the name of any territory, city or area.

Please cite this publication as:
OECD (2019), Education at a Glance 2019: OECD Indicators, OECD Publishing, Paris,
https://doi.org/10.1787/f8d7880d-en.

ISBN 978-92-64-80398-5 (print)
ISBN 978-92-64-88811-1 (pdf)

Education at a Glance
ISSN 1563-051X (print)
ISSN 1999-1487 (online)

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.

Photo credits: Cover © Christopher Futcher/iStock; © Marc Romanelli/Gettyimages; © michaeljung/Shutterstock;
© Pressmaster/Shutterstock.

Corrigenda to OECD publications may be found on line at: www.oecd.org/about/publishing/corrigenda.htm.

© OECD 2019
You can copy, download or print OECD content for your own use, and you can include excerpts from OECD publications, databases and
multimedia products in your own documents, presentations, blogs, websites and teaching materials, provided that suitable
acknowledgement of OECD as source and copyright owner is given. All requests for public or commercial use and translation rights should
be submitted to rights@oecd.org. Requests for permission to photocopy portions of this material for public or commercial use shall be
addressed directly to the Copyright Clearance Center (CCC) at info@copyright.com or the Centre français d’exploitation du droit de copie
(CFC) at contact@cfcopies.com.

FOREWORD  3

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 their countries’
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, Majda Benzidia,
Andrea Borlizzi, Éric Charbonnier, Manon Costinot, Gillian Golden, Bruce Golding, Fatine Guedira, Corinne
Heckmann, Karinne Logez, Camila de Moraes, Simon Normandeau, Gara Rojas González, Daniel Sánchez
Serra, Markus Schwabe, Giovanni Maria Semeraro, and Choyi Whang. Administrative support was provided by
Valérie Forges, and additional advice and analytical support were provided by Vanessa Denis, Majda Eddaifi,
Yanjun Guo, Julia Himstedt and Hajar Sabrina Yassine. 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 made 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
EDUCATION AT A GLANCE 2019 © OECD 2019

4  FOREWORD
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 2019 © OECD 2019

TABLE OF CONTENTS  5

Table of contents

Foreword

3

Editorial

9

Introduction: The indicators and their framework

11

Reader’s guide

17

Executive summary

23

Youth in the Education Sustainable Development Goal

28

Chapter A. The output of educational institutions and the impact of learning

37

Indicator A1. To what level have adults studied?
Indicator A2. Transition from education to work: Where are today's youth?
Indicator A3. How does educational attainment affect participation in the labour market?
Indicator A4. What are the earnings advantages from education?
Indicator A5. What are the financial incentives to invest in education?
Indicator A6. How are social outcomes related to education?
Indicator A7. To what extent do adults participate equally in education and learning?

Chapter B. Access to education, participation and progress
Indicator B1. Who participates in education?
Indicator B2. How do early childhood education systems differ around the world?
Indicator B3. Who is expected to graduate from upper secondary education?
Indicator B4. Who is expected to enter tertiary education?
Indicator B5. How many students complete tertiary education?
Indicator B6. What is the profile of internationally mobile students?
Indicator B7. What are the characteristics and outcomes of doctoral graduates?

Chapter C. Financial resources invested in education
Indicator C1. How much is spent per student on educational institutions?
Indicator C2. What proportion of national wealth is spent on educational institutions?
Indicator C3. How much public and private investment in educational institutions is there?
Indicator C4. What is the total public spending on education?
Indicator C5. How much do tertiary students pay and what public support do they receive?
Indicator C6. On what resources and services is education funding spent?
Indicator C7. Which factors influence teachers' salary cost?

EDUCATION AT A GLANCE 2019 © OECD 2019

38
52
64
82
96
114
132

145
146
160
180
192
208
228
246

261
264
278
290
302
314
332
342

6  TABLE OF CONTENTS

Chapter D. Teachers, the learning environment and the organisation of schools
Indicator D1. How much time do students spend in the classroom?
Indicator D2. What is the student-teacher ratio and how big are classes?
Indicator D3. How much are teachers and school heads paid?
Indicator D4. How much time do teachers spend teaching?
Indicator D5. Who are the teachers?
Indicator D6. What are the admission systems for tertiary education?

357
358
376
390
414
434
446

Annex 1. Characteristics of education systems

463

Annex 2. Reference statistics

469

Annex 3. Sources, methods and technical notes

479

Contributors to this publication

481

Education Indicators in Focus

489

TABLES
Table A1.1. Educational attainment of 25-64 year-olds (2018)
Table A1.2. Trends in educational attainment of 25-34 year-olds, by gender (2008 and 2018)
Table A1.3. Fields of study among tertiary-educated 25-64 year-olds (2018)
Table A2.1. Percentage of 18-24 year-olds in education/not in education, by work status (2018)
Table A2.2. Trends in the percentage of young adults in education/not in education, employed or not, by age
group (2008 and 2018)
Table A2.3. Percentage of 18-24 year-olds in education/not in education, by work status and duration of
unemployment (2018)
Table A3.1. Employment rates of 25-64 year-olds, by educational attainment (2018)
Table A3.2. Trends in employment rates of 25-34 year-olds, by educational attainment and gender (2008
and 2018)
Table A3.3. Employment, unemployment and inactivity rates of 25-34 year-olds, by educational attainment
(2018)
Table A3.4. Employment rates of tertiary-educated adults, by field of study (2018)
Table A3.5. Unemployment rates of 25-64 year-olds, by duration of unemployment and educational
attainment (2018)
Table A4.1. Relative earnings of workers, by educational attainment (2017)
Table A4.2. Level of earnings relative to median earnings, by educational attainment (2017)
Table A4.3. Differences in earnings between female and male full-time workers, by educational attainment and
age group (2017)
Table A4.4. Relative earnings of tertiary-educated adults, by field of study (2017)
Table A5.1a. Private costs and benefits for a man attaining tertiary education (2016)
Table A5.1b. Private costs and benefits for a woman attaining tertiary education (2016)
Table A5.2a. Public costs and benefits for a man attaining tertiary education (2016)
Table A5.2b. Public costs and benefits for a woman attaining tertiary education (2016)
Table A5.3a. Private/public costs and benefits for a man attaining tertiary education, by level of tertiary
education (2016)
Table A5.3b. Private/public costs and benefits for a woman attaining tertiary education, by level of tertiary
education (2016)
Table A6.1. Social connections, by educational attainment (2015 or 2017)
Table A6.2a. Work-life balance, by educational attainment (2015 or 2016)
Table A6.2b. Job intensity and flexibility, by educational attainment (2012 or 2015)
Table A7.1. Participation in formal and/or non-formal education and training, by gender, age group and
educational attainment (2016)

49
50
51
61
62
63
77
78
79
80
81
91
92
93
94
108
109
110
111
112
113
129
130
131
141

EDUCATION AT A GLANCE 2019 © OECD 2019

TABLE OF CONTENTS  7
Table A7.2a. Distribution of non-formal education and training activities, by gender, age group and educational
attainment (2016)
Table A7.3. Enrolment in formal education, by age group, and distribution by level of education (2017)
Table B1.1. Enrolment rates by age group (2005, 2010 and 2017)
Table B1.2. Enrolment rates in tertiary education, by age group and level of education (2017)
Table B1.3. Profile of students enrolled in tertiary education (2017)
Table B2.1. Enrolment rates of children under the age of 3 in early childhood education and care, by type of
service and age (2005, 2010 and 2017)
Table B2.2. Enrolment rates in early childhood education and care (ECEC) and primary education, by age
(2005, 2010 and 2017)
Table B2.3. Enrolment of children in early childhood education and care (ISCED 0) in private institutions,
ratio of children to teaching staff and minimum qualification of ECEC staff (2017)
Table B2.4. Financing of early childhood education and care (ISCED 0) and change in expenditure as a percentage of
GDP (2012 and 2016)
Table B3.1. Profile of upper secondary graduates from vocational programmes (2017)
Table B3.2. Profile of post-secondary non-tertiary graduates from vocational programmes (2017)
Table B3.3. Trends in upper secondary and post-secondary non-tertiary first-time graduation rates (2005,
2010 and 2017)
Table B4.1. Profile of first-time entrants into tertiary education (2017)
Table B4.2. Distribution of new entrants by field of study, gender and tertiary level (2017)
Table B4.3. First-time entry rates, by tertiary level (2017)
Table B5.1. Completion rate of full-time tertiary students, by level of education and gender (2017)
Table B5.2. Completion rate of full-time tertiary students, by level of education and students' upper
secondary programme orientation (2017)
Table B5.3. Status of full-time bachelor's students at various timeframes after entry (2017)
Table B6.1. International and foreign student mobility in tertiary education (2010, 2013 and 2017)
Table B6.2. Distribution of international or foreign students by field of study and by region of origin (2017)
Table B6.3. Mobility patterns of foreign and international students (2017)
Table B7.1. Profile of doctoral graduates (2017)
Table B7.2. Distribution of graduates from doctoral programmes, by field of study (2017)
Table B7.3. Educational attainment and employment rates of 25-64 year-olds at master's and doctoral levels
(2018)
Table C1.1. Total expenditure on educational institutions per full-time equivalent student (2016)
Table C1.2. Total expenditure on educational institutions per full-time equivalent student for core educational
services, ancillary services and R&D (2016)
Table C1.3. Index of change in total expenditure on educational institutions per full-time equivalent student
(2005, 2011 and 2016)
Table C2.1. Total expenditure on educational institutions as a percentage of GDP (2016)
Table C2.2. Total expenditure on educational institutions as a percentage of GDP, by final source of funds
(2016)
Table C2.3. Index of change in total expenditure on educational institutions as a percentage of GDP (2005,
2011 and 2016)
Table C3.1. Relative share of public, private and international expenditure on educational institutions, final
source of funds (2016)
Table C3.2. Relative share of public, private and international expenditure on educational institutions, initial
source of funds (2016)
Table C3.3. Trends in the share of public, private and international expenditure on educational institutions
(2005, 2010 and 2016)
Table C4.1. Total public expenditure on education as a percentage of total government expenditure (2016)
Table C4.2. Share of sources of total public funds devoted to education (2016)
Table C4.3. Trends in total public expenditure on education as a percentage of total government expenditure
(2005, 2010 and 2016)
Table C5.1. Annual average (or most common) tuition fees charged by tertiary institutions to national and
foreign students (2017/18)
Table C5.2. Tuition fees charged by institutions for full-time students, in USD converted using PPPs, and
percentage of national students receiving financial support (2017/18)
Table C5.3. Public loans to students, repayment and remission in tertiary education (2017/18)
Table C5.4. Changes in tuition fee policies and public support to students (2007/08 to 2017/18)
Table C6.1. Share of current and capital expenditure, by education level (2016)
Table C6.2. Current expenditure, by resource category (2016)
EDUCATION AT A GLANCE 2019 © OECD 2019

142
143
157
158
159
175
176
177
178
189
190
191
204
205
206
225
226
227
242
243
244
257
258
259
274
275
276
286
287
288
299
300
301
311
312
313
327
329
330
331
339
340

8  TABLE OF CONTENTS
Table C6.3. Share of current expenditure, by resource category and type of institution (2016)
Table C7.1. Salary cost of teachers per student, by level of education (2017)
Table C7.2. Contribution of various factors to salary cost of teachers per student in primary education (2017)
Table C7.3. Contribution of various factors to salary cost of teachers per student in lower secondary
education (2017)
Table D1.1. Instruction time in compulsory general education1 (2019)
Table D1.2. Organisation of compulsory general education1 (2019)
Table D1.3a. Instruction time per subject in primary education (2019)
Table D1.3b. Instruction time per subject in general lower secondary education (2019)
Table D2.1. Average class size, by type of institution (2017) and index of change between 2005 and 2017
Table D2.2. Ratio of students to teaching staff in educational institutions, by level of education (2017)
Table D2.3. Ratio of students to teaching staff, by type of institution (2017)
Table D3.1a. Teachers' statutory salaries, based on the most prevalent qualifications at different points in
teachers' careers (2018)
Table D3.2a. Actual salaries of teachers and school heads relative to earnings of tertiary-educated workers
(2017)
Table D3.4. Average actual salaries of teachers and school heads, by age group and by gender (2017)
Table D3.10. Minimum/maximum school heads' statutory salaries, based on minimum qualifications (2018)
Table D4.1a. Organisation of teachers' teaching time (2018)
Table D4.1b. Organisation of teachers' working time (2018)
Table D4.2. Number of teaching hours per year (2000, 2005 to 2018)
Table D4.3a. Tasks of teachers, by level of education (2018)
Table D4.3b. Other responsibilities of teachers, by level of education (2018)
Table D5.1. Age distribution of teachers (2017)
Table D5.2. Gender distribution of teachers (2017)
Table D5.3. Gender distribution of teachers by age group (2017) and percentage of female teachers for all
ages (2005 and 2017)
Table D6.1a. Organisation of the admission system and application process to first-degree tertiary
programmes in public institutions (2017)
Table D6.2a. . Examinations and additional criteria used for admission to first-degree tertiary programmes in
public institutions (2017)
Table D6.3. Minimum qualification and academic performance requirements for entry into tertiary education
(government perspective) (2017)

341
354
355
356
371
372
373
374
387
388
389
410
411
412
413
427
428
429
430
431
443
444
445
459
460
462

Follow OECD Publications on:
http://twitter.com/OECD_Pubs
http://www.facebook.com/OECDPublications

http://www.linkedin.com/groups/OECD-Publications-4645871
http://www.youtube.com/oecdilibrary
OECD

Alerts

http://www.oecd.org/oecddirect/

This book has...

StatLinks2

A service that delivers Excel ® files from the printed page!

Look for the StatLinks2at the bottom of the tables or graphs in this book.
To download the matching Excel® spreadsheet, just type the link into your
Internet browser, starting with the http://dx.doi.org prefix, or click on the link from
the e-book edition.

EDUCATION AT A GLANCE 2019 © OECD 2019

EDITORIAL  9

Editorial
As countries struggle to respond to economic, environmental and social transformations – including technological
advances, climate change and migration – intellectual capital has become the most valuable asset of our time.
The core of intellectual capital is knowledge, and the development and transfer of knowledge is the primary
mission of higher education. Tertiary education thus plays a central role in helping people and societies confront
and cope with these profound changes.
The demand for higher-order skills and competencies is both economic and social. The employment rate of adults
with a tertiary degree is about 9 percentage points higher than for those with upper secondary education only,
and they earn on average 57% more. Tertiary-educated adults are also more likely to be in good health, take
care of the environment, or participate in public life.
Yet with these great strides comes greater uncertainty. Although the rise of artificial intelligence is expected to
result in increased productivity in a number of sectors, it is also fundamentally changing the way some jobs are
carried out. While widespread access to information has made it easier to learn than ever before, it has also
accelerated the pace of change, leaving many wondering how to adapt and struggling to keep up. Globalisation,
while providing many opportunities, has also triggered fierce competition for skills.
Countries have responded to these challenges by expanding access to education and learning. Financial support
mechanisms have alleviated some of the burden of pursuing additional studies, promising high returns and
flexible reimbursement options. The traditional linear progression through education, from primary through
tertiary, is being gradually replaced by a more holistic vision of lifelong learning. As market demand for skills
evolves quicker than some educational institutions may anticipate, many of these institutions are promoting
flexible pathways into tertiary education and seeking partnerships with other players, including employers,
industry and training institutions. While these policies help promote tertiary education to a growing share of adults,
educational institutions must balance larger enrolments with the need to contain costs, and maintain the
relevance and quality of their programmes.

Meeting the demand for higher-order skills
Recognising these challenges, this year’s edition of Education at a Glance focuses on tertiary education. It shows
that the demand for tertiary skills in the labour market remains strong in spite of the increasing supply of
graduates, and that the earnings advantage of tertiary-educated adults grows with age and professional
experience. Bachelor’s programmes remain the most common route of entry into tertiary education: the share of
young adults attaining a bachelor’s degree - 24% - is larger than it has ever been.
Ensuring the right supply of skills in a rapidly changing world is challenging. Adult participation in education and
training is on average 40 percentage points lower among low-educated adults – those that need it most- – than it is
for highly educated ones. Still less than 15% of new entrants to bachelor’s programmes study engineering,
manufacturing and construction and less than 5% study information and communication technologies – even though
these fields are most commonly associated with technological progress and yield the best labour-market outcomes.
The share of the population attaining a master’s or doctoral degree has remained constant across generations.
These degrees continue to be in high demand and offer attractive returns on the initial investment. While the
average annual cost is similar to that of a bachelor’s degree programme in more than half of OECD countries,
graduates of these programmes earn 32% more, on average.
EDUCATION AT A GLANCE 2019 © OECD 2019

10  EDITORIAL
Tertiary education admissions systems are pivotal in ensuring that upper secondary students make a smooth
transition to tertiary education. More than half of countries and economies have open admissions into public
tertiary education systems, whereas other countries use selective criteria, such as academic performance,
examinations and, in some cases, upper secondary programme orientation. Selective systems may seem more
effective in ensuring that students actually complete a degree by enabling only those students with the required
skills to enter. However, completion patterns can be similar across countries with very different admissions
systems. Only 39% of bachelor’s degree students graduate within the theoretical duration of their programme;
another 28% do so during the following three years, on average across countries with data.
This all comes at a cost. Between 2005 and 2016, spending on tertiary institutions increased at more than double
the rate of student enrolments to about USD 15 600 per student on average across OECD countries. Across the
majority of OECD countries, private sources have been called on to contribute more as countries introduce or
raise tuition fees. Most of this increase in spending has been devoted to core education services; the number of
academic staff at the tertiary level increased on average by about 1% over this period, almost on par with the
number of students enrolled.

Refining – and redefining – education pathways
While education helps individuals acquire the skills needed to contribute to society, the expansion of tertiary
education will only be sustainable if it balances the supply of graduates with labour market needs. Easy access
to funding and open admissions risks promoting tertiary education at the expense of other, much-needed
vocational and professional qualifications, which are often perceived as less attractive pathways.
The Sustainable Development Goal on education (SDG 4) reminds us of the importance of equal access to quality
education and lifelong learning opportunities, whatever those may be. The Goal recognises the many alternative
paths young people and adults can take to acquire the necessary skills to ease their transition into the labour
market and live better lives. In particular, SDG 4.3 aims to “by 2030, ensure equal access for all women and men
to affordable and quality technical, vocational and tertiary education, including university”. The SDG 4 agenda
provides a range of indicators to measure participation in education and the skills acquired throughout a lifetime,
encompassing levels in and outside of compulsory education, and considering a wide range of programmes that
include both formal and non-formal education.
This edition’s chapter on the Sustainable Development Goals describes the pathways that young people take
throughout their journey: the transition from secondary to higher levels of education and from education into the
labour market. It finds that, on average across OECD countries, about one in six 15-24 year-olds are enrolled in
vocational programmes. The attainment gap among young tertiary-educated adults and those with upper
secondary has narrowed. In 2018, the share of young adults with an upper secondary or post-secondary
non-tertiary qualification, 41%, is almost equal to the share attaining tertiary education, 44%.
Everyone hopes to be able to choose from among solid, well-paying career opportunities, enjoy a smooth
progression through that career, and find a sense of purpose in life. As education leaders, it is our responsibility
to help students sort through the breadth of opportunities and make informed decisions about their future. It is
also our responsibility to make a broad range of pathways attractive to students and equip them with the skills to
navigate through an unpredictable and changing world. To achieve this, we must expand opportunities, broaden
the options of programmes and qualifications, and build stronger bridges with the labour market. This also means
investing in student orientation and guidance so that each student finds his or her place in society and can
contribute to his or her full potential. Only then will students be able to acquire the knowledge that can carry them
forward, the kind of knowledge that can change their lives.

Angel Gurría
OECD Secretary-General

EDUCATION AT A GLANCE 2019 © OECD 2019

INTRODUCTION: THE INDICATORS AND THEIR FRAMEWORK  11

Introduction: The indicators and
their framework
The organising framework
Education at a Glance 2019: 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.

Figure A. Organising framework of indicators in Education at a Glance

Actors in education systems
The OECD Indicators of Education Systems (INES) 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
EDUCATION AT A GLANCE 2019 © OECD 2019

12  INTRODUCTION: THE INDICATORS AND THEIR FRAMEWORK
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.

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

EDUCATION AT A GLANCE 2019 © OECD 2019

INTRODUCTION: THE INDICATORS AND THEIR FRAMEWORK  13

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 2019 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.
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 the 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 the 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.
Chapters 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 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,
and on admission systems to tertiary education.

EDUCATION AT A GLANCE 2019 © OECD 2019

14  INTRODUCTION: THE INDICATORS AND THEIR FRAMEWORK
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 of a smaller number of countries that complement the findings presented.

The Sustainable Development Goal 4
In September 2015, world leaders gathered to set ambitious goals for the future of the global community. Goal 4
of the Sustainable Development Goals (SDGs) 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
continues to devote 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.

Tertiary education in Education at a Glance 2019
As the selected theme for this year’s publication, tertiary education is at the forefront of Education at a
Glance 2019. Tertiary education has seen unprecedented growth in the past decade and is presented as one of
the paths through which young people can succeed in life. There is increasing policy interest in providing
comparative analysis of the progression of students, the outcomes of graduates and the resources invested.
Therefore, a large number of indicators in this year’s edition analyse students’ participation and progression
through tertiary education, as well as the economic, labour market and social outcomes of tertiary-educated
adults. The analysis also includes indicators on the resources invested in tertiary education, both financial and
human. This year, three new indicators complement the set of indicators, offering additional analysis on tertiary
completion rates, doctoral graduates and their labour-market outcomes, and tertiary admission systems.
In line with this general focus of the publication, the SDG chapter in this year’s edition focuses on youth learning
pathways and helps inform the debate on youth prospects and youth employment in OECD and partner countries,
in the light of the Sustainable Development Agenda. Building not only on SDG 4 (quality education) but also on
SDG 8 (decent work and economic growth), the chapter describes the pathways that youth can take throughout
their journey: the transition from secondary to higher levels of education, and their progression through higher
levels of education, and from education into the labour market.

EDUCATION AT A GLANCE 2019 © OECD 2019

INTRODUCTION: THE INDICATORS AND THEIR FRAMEWORK  15

Table A below summarises the indicators and chapters that contribute to the analysis of tertiary education in this
year’s edition.

Table A. Indicators including an analysis of tertiary education in Education at a Glance 2019
Chapter

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

Indicator
number

A1
A2
A3
A4
A5
A6
A7
B1
B2
B3
B4
B5
B6
B7
C1
C2
C3
C4
C5
C6
C7
D1
D2
D3
D4
D5
D6

Indicator
Tertiary
education
content
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 complete tertiary education?
What is the profile of internationally mobile students?
What are the characteristics and outcomes of doctoral graduates?
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 in 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?
What are the admission systems for tertiary education?

EDUCATION AT A GLANCE 2019 © OECD 2019

X
X
X
X
X
X
X
X

X
X
X
X
X
X
X
X
X
X

X
X
X
X

READER’S GUIDE  17

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 work-based 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 all OECD countries;1 two 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, the People’s Republic of China,
Costa Rica, India, Indonesia, 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
regions.
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.

EDUCATION AT A GLANCE 2019 © OECD 2019

18  READER’S GUIDE

Note on subnational regions
When interpreting the results on subnational entities, readers should take into account their population as well
as their geographical size. For example, in Canada, the population of Nunavut was 37 996 in 2017 and the
territory covers 1.9 million square kilometres, while the population of the province of Ontario is 14.2 million and
the territory covers 909 000 square kilometres (OECD, 2019[2]). Also, regional disparities tend to be higher when
more subnational entities are used in the analysis, especially in big countries like Canada, the Russian Federation
or the United States.

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 Adults (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 overall values are given for countries 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 countries 2 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 countries 3 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, an additional 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 EU23 average is also presented. It is calculated as the unweighted mean of the data
values of the 23 countries that are members of both the European Union and the OECD for which data are
available or can be estimated. These 23 countries are Austria, Belgium, the Czech Republic, Denmark, Estonia,
Finland, France, Germany, Greece, Hungary, Ireland, Italy, Latvia, Lithuania, 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

EDUCATION AT A GLANCE 2019 © OECD 2019

READER’S GUIDE  19

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, EU23 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/EU23/G20 average” refers to the OECD, EU23 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.

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.

Table B. Education levels under the ISCED-2011 Classification
Terms used in this publication

ISCED classification

Early childhood education
Refers to early childhood programmes that have an intentional education component and aim to develop cognitive, physical and
socio-emotional skills necessary for participation in school and society. Programmes at this level are often differentiated by age.

ISCED 0 (sub-categories: 01
for early childhood educational
development and 02 for preprimary 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.

ISCED 1

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.

ISCED 2

Upper secondary education
Stronger specialisation than at lower secondary level. Programmes offered are differentiated by orientation: general or vocational.
Typical duration is 3 years.

ISCED 3

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.

ISCED 4

Short-cycle tertiary education
Often designed to provide participants with professional knowledge, skills and competencies. Typically, they are practically based,
occupation-specific and prepare students to enter the labour market directly. They may also provide a pathway to other tertiary
education programmes (ISCED levels 6 or 7). The minimum duration is 2 years.

ISCED 5

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.

ISCED 6

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.
Programmes of at least five years’ duration preparing for a long first degree/qualification are included at this level if they are
equivalent to a master’s level programmes in terms of their complexity and content.

ISCED 7

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 8

EDUCATION AT A GLANCE 2019 © OECD 2019

20  READER’S GUIDE
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.
Table B lists the ISCED 2011 levels used in the publication (OECD/Eurostat/UNESCO Institute for Statistics,
2015[3]). Tertiary education, the focus of this year’s publication, builds on secondary education and provides
learning activities in specialised fields of study. Tertiary education includes what is commonly understood as
academic education, but also includes advanced vocational or professional education. It comprises ISCED
levels 5 (short-cycle tertiary programmes), 6 (bachelor’s), 7 (master’s) and 8 (doctoral). Successful completion
of an upper secondary programme is a requirement to enter tertiary education, and students can enter through
short-cycle tertiary programmes, bachelor’s, or master’s long first degrees (Figure B). Access may also be
possible from ISCED level 4 (post-secondary non-tertiary).

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. The broad ISCED-F fields considered in this publication are education;
arts and humanities; social sciences, journalism and information; business, administration and law; natural
sciences, mathematics and statistics; information and communication technologies (ICT); engineering,
manufacturing and construction; and health and welfare. Throughout this publication, the term “field of study” is
used to refer to the different fields of this classification.

Figure B. Tertiary education pathways

Source: OECD/Eurostat/UNESCO Institute for Statistics (2015[3]), ISCED 2011 Operational Manual: Guidelines for Classifying National Education
Programmes and Related Qualifications, https://dx.doi.org/10.1787/9789264228368-en.

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

EDUCATION AT A GLANCE 2019 © OECD 2019

READER’S GUIDE  21

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 Glance
2019 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”.

EDUCATION AT A GLANCE 2019 © OECD 2019

22  READER’S GUIDE

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

References
OECD (2019), OECD Regional Statistics Database,
http://stats.oecd.org/Index.aspx?DataSetCode=REGION_DEMOGR.

[2]

OECD (2018), OECD Handbook for Internationally Comparative Education Statistics: Concepts,
Standards, Definitions and Classifications, OECD Publishing, Paris,
https://doi.org/10.1787/9789264304444-en.

[1]

OECD/Eurostat/UNESCO Institute for Statistics (2015), ISCED 2011 Operational Manual: Guidelines
for Classifying National Education Programmes and Related Qualifications, OECD Publishing,
Paris, http://dx.doi.org/10.1787/9789264228368-en.

[3]

UNESCO-UIS (2014), ISCED Fields of Education and Training 2013 (ISCED-F 2013): Manual to
Accompany the 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).

[4]

Notes

1 On 25 May 2018, the OECD Council invited Colombia to become a Member. While Colombia is included in the OECD

averages reported in this publication, at the time of its preparation, Colombia was in the process of completing its domestic
procedures for ratification and the deposit of Colombia’s instrument of accession to the OECD Convention was pending.
2 See Note 1.
3 See Note 1.

EDUCATION AT A GLANCE 2019 © OECD 2019

EXECUTIVE SUMMARY  23

Executive summary
Demand for tertiary education is still strong despite a larger supply of graduates
In 2018, 44% of 25-34 year-olds held a tertiary degree, compared to 35% in 2008, on average across OECD
countries. The expansion of the population of adults with a bachelor’s degree has contributed the most to this
growth. The employment advantage of young tertiary-educated adults over those with upper secondary education
has remained fairly constant over the past decade. Tertiary-educated adults are more resilient against long-term
unemployment and, in 2018, their employment rate was 9 percentage points higher than that of adults with upper
secondary education. Tertiary-educated adults also reap higher earnings, although this varies by field of study.
Their advantage increases with age too: 25-34 year-olds with tertiary education earn 38% more than their peers
with upper secondary education while 45-54 year-olds earn 70% more.

Education systems have facilitated access to tertiary education yet some gaps remain
Providing financial support mechanisms has helped make tertiary education more accessible to more people. In
countries with the highest tuition fees, more than 70% of students benefit from grants or loans. Progression to
master’s or doctoral level has remained constant across generations despite attractive returns on the initial
investment. The annual cost of these programmes is similar to that of a bachelor’s degree in more than half of
OECD countries with data, while earnings are 32% higher, on average.
Some sectors still struggle to find the skilled workers they need. While engineering, manufacturing and
construction, and information and communication technologies are two fields most commonly associated with
the best labour market outcomes, only 14% of graduates earned a degree in the former and 4% earned a degree
in the latter in 2017. Women are particularly under-represented: less than 25% of entrants into these fields are
women, on average across OECD countries.

Transitions from upper secondary education and tertiary admissions systems
influence progression through education
More than 40% of 19-20 year-olds in nearly half of OECD countries are enrolled in tertiary programmes and the
average age at entry into a bachelor’s programme ranges from 18 in Japan to 25 in Switzerland. Countries where
a larger share of students enrol in general upper secondary programmes are more likely to show larger enrolment
in tertiary education at younger ages. Entry into tertiary education is open in more than half of countries and
economies, whereas other countries use selective criteria, such as academic performance, examinations and, in
some cases, upper secondary programme orientation. On average across OECD countries, 17% of first-time
entrants into tertiary education enter a short-cycle programme compared to 76% who enter at the bachelor’s level
and 7% at the master’s level. However, by the beginning of the second year of study, an average of 12% of
bachelor’s degree students have left the tertiary education system. Only 39% of those who enter a bachelor’s
programme graduate within the theoretical duration of the programme; another 28% graduate during the following
three years. Male students and those from a vocational upper secondary programme are generally less likely to
enter and complete a tertiary degree. Tertiary education plays an important role in lifelong learning: more than
three in four 30-39 year-olds in education attend a tertiary programme, on average across OECD countries.

EDUCATION AT A GLANCE 2019 © OECD 2019

24  EXECUTIVE SUMMARY

EDUCATION AT A GLANCE 2019 © OECD 2019

EXECUTIVE SUMMARY  25

EDUCATION AT A GLANCE 2019 © OECD 2019

26  EXECUTIVE SUMMARY

Increased funding has sustained the expansion of tertiary education
Between 2005 and 2016, spending on tertiary institutions increased by 28%, on average across OECD countries,
more than double the rate of student enrolments (12%). However, both the number of students and total spending
have increased at a slower pace since 2010. In 2016, expenditure per tertiary student amounted to USD 15 556,
approximately one-third of which was devoted to research and development. While private sources financed
more than 30% of the expenditure, on average, tuition fees for bachelor programmes increased by more than
20% between 2007 and 2017 in half of the countries with data. Human resources in tertiary education have also
expanded in most countries. Between 2005 and 2017, the number of academic staff at the tertiary level across
OECD countries increased at an average rate of 1% per year, a rate similar to that of tertiary enrolments.

Graduation rates from upper secondary education have increased over the past
decade
Although graduation from upper secondary education increased by 6 percentage points between 2005 and 2017,
15% of 25-34 year-olds did not attain upper secondary education in 2018, on average across OECD countries.
In some countries, vocational programmes are prominent at the upper secondary level. On average across OECD
countries, 40% of first-time upper secondary graduates earned a vocational qualification in 2017; in Austria, the
Czech Republic, the Slovak Republic and Slovenia, more than 66% of this population did. OECD countries spent
an average of 3.5% of GDP on primary, secondary and post-secondary non-tertiary institutions in 2016, and
public expenditure at this level increased by 18% since 2005. Smaller classes and higher teachers’ salaries
contributed to this increase. At the lower secondary level, the average class shrank by 6% while teachers’ salaries
increased by 8% between 2005 and 2017, on average across OECD countries.

The teaching profession still struggles to attract new recruits
In most OECD countries, the share of primary and secondary teachers among 50-59 year-olds is larger than the
share among 25-34 year-olds, which raises concerns about future teacher shortages. About 10% of primary and
secondary teachers are under the age of 30, on average across OECD countries. Salaries tend to increase with
the level of education taught, but teachers’ earnings remain between 78% and 93% of the earnings of other
tertiary-educated adults. By contrast, school heads earn at least 25% more than their tertiary-educated peers.
The number of teaching hours per year decreases as the level of education increases, on average across OECD
countries, and this has remained largely unchanged between 2000 and 2018 in most countries with data.

Other findings
In 2017, more than one in three children under the age of three were enrolled in early childhood education and
care services, on average across OECD countries – an increase of 7 percentage points compared to 2010.
On average across OECD countries, 14% of 18-24 year-olds are neither employed nor in education or training
(NEET). In Brazil, Colombia, Costa Rica, Italy, South Africa and Turkey, over 25% of 18-24 year-olds are NEETs.
Adults with higher educational attainment tend to participate more in cultural or sporting activities: more than 90%
of tertiary-educated adults do compared to less than 60% of those who had not attained upper secondary
education.

EDUCATION AT A GLANCE 2019 © OECD 2019

28  YOUTH IN THE EDUCATION SUSTAINABLE DEVELOPMENT GOAL

Youth in the Education Sustainable
Development Goal
Highlights


The fourth Sustainable Development Goal on Education (SDG 4) adopts a lifelong learning approach to
education and introduces vocational and tertiary education into the global agenda. Combined with the
eighth Sustainable Development Goal on decent work and economic growth (SDG 8), the two goals
include sufficient indicators to track youth throughout their journey from education to employment.



Out-of-school youth (SDG 4.1.5) still represent more than 10% of the population in the official age
range for upper secondary education in over one-quarter of OECD and partner countries. Nonetheless,
some countries have succeeded in significantly reducing the proportion of out-of-school youth.
For instance, in Mexico and the Russian Federation, this proportion has decreased by at least
18 percentage points since 2005.



On average across OECD countries, 18% of 15-24 year-olds participate in vocational programmes
(ISCED levels 2 to 5; SDG Indicator 4.3.3). Most of them are enrolled at secondary level.

Figure 1. Upper secondary out-of-school rate (2005, 2017)
SDG Indicator 4.1.5

Note: The out-of-school rate is calculated as the number of students of the official age for upper secondary education enrolled in primary, secondary or
higher levels of education subtracted from the total population of the same age (numerator), over the total population of the same age (denominator).
1. The source for population data is the UOE data collection for demographic data (Eurostat/DEM) instead of the United Nations Population Division (UNPD).
2. Year of reference 2010 instead of 2005.
Countries are ranked in descending order of upper secondary out-of-school rate in 2017.
Source: OECD (2019). The official data sources for this indicator are the UOE data collection for enrolment data and the United Nations Population
Division (UNPD) for population data. Results may differ from national statistics. See Source section for more information
(https://doi.org/10.1787/f8d7880d-en).
Statlink2https://doi.org/10.1787/888933976289

EDUCATION AT A GLANCE 2019 © OECD 2019

YOUTH IN THE EDUCATION SUSTAINABLE DEVELOPMENT GOAL  29

Context
Unlike the previous Millennium Development Goals (MDGs 2000-2015) that were set for low- and middleincome countries, the 2030 Agenda for Sustainable Development is universal. Building on 17 ambitious and
far-reaching goals, it commits every single country in the world to eradicate poverty and foster prosperous and
sustainable development by 2030.
The fourth Sustainable Development Goal on Education (SDG 4) aims to “ensure inclusive and equitable
quality education and promote lifelong learning opportunities for all” by 2030. SDG 4 is to be achieved through
the accomplishment of ten targets, which represent the most comprehensive and ambitious global education
agenda ever attempted. Departing from the MDGs’ focus on universal primary education, SDG 4 defines
learning as a process that starts at birth and continues throughout all stages of life. In doing so, the SDG 4
agenda considers the various and flexible pathways to education throughout an individual’s journey. Tertiary
education, the theme of this year’s Education at a Glance publication, also plays a role in this framework, and
is presented as one of the paths through which young people can succeed in life (Box 1).
This chapter will focus on youth learning pathways and help inform the debate on youth prospects and
employment in OECD and partner countries, in the light of the Sustainable Development Agenda. Building not
only on SDG 4 (Quality education) but also on SDG 8 (Decent work and economic growth), this chapter will
describe the paths that youth can take throughout their journey: from secondary into higher levels of education
(including tertiary), throughout higher levels of education, and from education into the labour market.

Other findings


Young people are at greater risk of precarious employment than adults in older age groups. On
average across OECD countries, the unemployment rate is 2 percentage points higher among
25-34 year-olds (7%) than among 35-44 year-olds (5%) (see Indicator A3, used as a proxy for
SDG Indicator 8.5.2).



On average across OECD countries, 11% of 15-24 year-olds are neither employed, nor in education
or training (NEET) (see Indicator A2, used as a proxy for SDG Indicator 8.6.2).

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 figures in this chapter present some 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, reference is made
to the corresponding indicator.
Data presented in this chapter do not track a single cohort across time. Rather, the chapter describes and
analyses youth pathways through education and employment at a single point in time, across different age
groups.

EDUCATION AT A GLANCE 2019 © OECD 2019

30  YOUTH IN THE EDUCATION SUSTAINABLE DEVELOPMENT GOAL

Analysis

Box 1. Learning pathways in the SDG Framework
Several of the 17 Sustainable Development Goals and their targets explicitly mention young women and men.
SDG 4 on equal access to quality education and SDG 8 on decent work are the ones that are the most related
to youth. Other goals that are of particular relevance include SDG 10 (inequality) and SDG 16 (peace and
justice).
The Sustainable Development Goal on Education (SDG 4) insists on the importance of equal access to quality
education and lifelong learning opportunities for all. To track the continuous education process, the SDG 4
agenda provides a range of indicators to measure the participation and skills of individuals throughout their
lives, encompassing levels in and outside compulsory education and considering a wide range of programmes
(including formal and non-formal education).
Among SDG 4 targets, SDG 4.1 and SDG 4.2 emphasise the importance of both education participation and
education quality at pre-primary (SDG 4.2), and primary and secondary levels (SDG 4.1), while SDG 4.3
focuses on participation at higher levels. SDG 4.3 aims to “by 2030, ensure equal access for all women and
men to affordable and quality technical, vocational and tertiary education, including university”. This target is
closely linked to SDG 4.4 and 4.6, which both measure essential skills that youth and adults can acquire
through vocational, tertiary or adult education, including literacy and numeracy, digital literacy, and information
and communication technologies (ICT) skills. It is also closely linked to SDG 4.7, which aims to ensure that
learners acquire the knowledge and skills needed to promote sustainable development.
SDG 4.3 contains one global indicator on the participation rate of youth and adults in formal and non-formal
education and training, and two thematic indicators on the gross enrolment ratio for tertiary education and the
participation rate in vocational education. The phrasing of the target, as well as the indicators it contains,
recognises the many alternative paths through which young people and adults can acquire the necessary
skills to ease their transition to the labour market and live better lives.
Figure 2 describes how the SDG 4 and SDG 8 indicators track the progression of youth from secondary
education to employment, by evaluating their participation (blue arrows) and assessing the proportion of those
who leave education and/or the labour market (red rectangles).

Figure 2. Youth pathways from education to employment

EDUCATION AT A GLANCE 2019 © OECD 2019

YOUTH IN THE EDUCATION SUSTAINABLE DEVELOPMENT GOAL  31

SDG 4 and its associated targets set an ambitious agenda that encompasses quality learning and equity in
education alongside the more traditional indicators of access and participation, at all levels of education. 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 at primary level. The analysis below takes into
account this lifelong learning approach and reports on youth pathways throughout their journey from education
to the labour market.

Completing upper secondary education
Completing upper secondary education is an important step for youth to ensure a better entry into the labour
market. Individuals without upper secondary education are more likely to be unemployed (see Indicator A3) and
to have lower earnings (see Indicator A4) than those who complete this or a higher level of education.
As the SDG agenda confirms, education is also key in ensuring that youth become engaged citizens and
participate in society. In this context, SDG Target 4.7 aims at “ensuring that all learners acquire the knowledge
and skills needed to promote sustainable development, including, among others, through education for
sustainable development and sustainable lifestyles, human rights, gender equality, promotion of a culture of
peace and non-violence, global citizenship, and appreciation of cultural diversity and of culture’s contribution to
sustainable development”. While the data needed to properly monitor this target are still limited, SDG Target 4.7
acknowledges the many functions of education, including training better citizens.
Graduation from secondary education does not necessarily lead to further training as the pathways into education
after secondary level vary substantially across countries. For example, in some countries, young people who
want to pursue a tertiary degree may first need to pass a central entrance exam (see Indicator D6). In other
countries, young people with a secondary qualification might have fair chances if they join the labour market
directly. Therefore, the proportion of youth graduating from secondary education does not always reflect the
proportion going on to pursue further education after secondary school. However, across countries, the youth
who do not complete upper secondary education are less likely to pursue further education and more likely to be
unemployed or inactive.
SDG Indicator 4.1.5 measures the upper secondary out-of-school rate, which corresponds to the proportion of
young people in the official age range for upper secondary education who are not enrolled in primary, secondary
or higher levels of education. On average across OECD countries, almost 7% of youth of upper secondary school
age were out of school in 2017, but they represent 5% or less of that age group in over half of countries with
available data (Figure 1).In other words, while the majority of countries have managed to limit the proportion of
out-of-school youth (less than 5%), about one-quarter of OECD and partner countries still have a large proportion
of out-of-school youth (over 10%). Colombia and Mexico have the highest rate of out-of-school youth among all
OECD and partner countries, with over 25% of upper secondary school-aged youth not enrolled. They are
followed by Luxembourg (19%), Brazil (19%) and Switzerland (17%). In Luxembourg, the high rate of repeaters
in primary and secondary levels may contribute to a higher dropout rate (OECD, 2016[1]).
Some countries have made significant progress in reducing the numbers of out-of-school youth in the past
decade. Figure 1 highlights a decrease of 20 percentage points in the out-of-school rate in the Russian
Federation, 18 percentage points in Mexico, 16 percentage points in Portugal and 10 percentage points in
Australia and New Zealand between 2005 and 2017. Such large reductions reflect continuous policy efforts to
retain students of upper secondary education age in school.
Upper secondary out-of-school rates remain roughly similar between genders in most countries. The difference
between young women and men in out-of-school rates remain at or below 4 percentage points in almost all
countries, except in Luxembourg, where the out-of-school rate is 5 percentage points higher among young men,
and Sweden, where it is 11 percentage points higher among young women.

EDUCATION AT A GLANCE 2019 © OECD 2019

32  YOUTH IN THE EDUCATION SUSTAINABLE DEVELOPMENT GOAL
Advancing from secondary to higher levels of education
Education following upper secondary can take a variety of forms. Upon graduation from secondary level,
depending on the country, youth could opt for post-secondary non-tertiary education, short-cycle tertiary, or a
bachelor’s or long first degree.
SDG Target 4.3 is to “by 2030, ensure equal access for all women and men to affordable and quality technical,
vocational and tertiary education, including university”. It recognises the many alternative paths through which
young people and adults can acquire the necessary skills to ease their transition to the labour market, become
engaged citizens and live better lives. Although Target 4.3 focuses only on participation, it is closely linked to
Targets 4.4 and 4.6, which measure some of the skills that can be acquired through participation in vocational
and tertiary levels of education and training.
Target 4.3 also reveals a strong equity focus, by referring to “equal access for all women and men”. There may
be different paths available to young people, but what is most important is that everyone has equal opportunities
to access them. Moreover, tracking the different pathways sheds light on the education system’s permeability,
which is also related to equity: learners should be able to move easily between levels and types of programmes
(e.g. from vocational to general education). Finally, Target 4.3 highlights the importance of both the quality and
affordability of vocational and tertiary education, yet no indicator has been proposed to capture any of these two
concepts (UNESCO, 2016[2]).

Vocational education and training
Vocational education and training can play a crucial role in tackling youth unemployment. During economic
downturns, such as the 2008 recession, they have proved to be a powerful tool in addressing youth
unemployment in countries such as Austria, Germany and Switzerland. All three have efficiently used vocational
training programmes, particularly targeted at potential school dropouts (Dolado, 2015[3]).
The SDG Thematic Indicator 4.3.3 measures the participation rate in technical and vocational programmes
among 15-24 year-olds, either in formal education, work-based or other settings. The indicator focuses on this
broad age group and a wide range of education levels (secondary, post-secondary non-tertiary and short-cycle
tertiary), and seeks to measure participation in work-related training designed to lead to a job (UNESCO, 2017[4]).
On average across OECD countries, in 2017, 18% of 15-24 year-olds were enrolled in vocational education (at
the secondary, post-secondary non-tertiary and short-cycle tertiary levels combined), ranging from 3% in Brazil
to 35% in Slovenia (Figure 4). Levels of enrolment remain higher for young men than for young women in almost
all countries with available data (Figure 3). On average across OECD countries, while 16% of young women
(aged 15-24) are enrolled in vocational education and training, this proportion goes up to 19% for men.
Breaking down SDG 4.3.3 by level of education reveals that in almost all countries, most 15-24 year-olds in
vocational programmes are enrolled at secondary level (Figure 4). In other words, the large majority of students
who participate in vocational programmes will do so at the ages corresponding to upper secondary education,
i.e. 15-19 year-olds (see Indicator B1). Thus, the extended 15-24 age range in SDG 4.3.3 may underestimate
participation rates in these programmes in OECD countries.
Work experience remains a key feature of successful vocational education and training (OECD, 2014[5]). Yet
available data do not allow to report on the variety of vocational programmes that exist across countries. In
particular, monitoring existing “dual systems” (formal vocational schooling combined with on-the-job training)
would help to more thoroughly inform the role of vocational education and training in limiting school dropout rates
and offering alternative options to disengaged youth (see Box A5.1 in (OECD, 2017[6])).
Vocational education and training can also be a pathway to tertiary education. For example, countries such as
Finland and the Netherlands have developed education permeability and established “bridges” from vocational
training to tertiary education.

EDUCATION AT A GLANCE 2019 © OECD 2019

YOUTH IN THE EDUCATION SUSTAINABLE DEVELOPMENT GOAL  33

Figure 3. Enrolment rate of 15-24 year-olds in vocational education and training, by gender (2017)
SDG Indicator 4.3.3

1. The source for population data is the UOE data collection for demographic data (Eurostat/DEM) instead of the United Nations Population Division
(UNPD).
Countries are ranked in descending order of enrolment rate of 15-24 year-olds women in vocational education and training in 2017.
Source: OECD (2019). The official data sources for this indicator are the UOE data collection for enrolment data and the United Nations Population
Division (UNPD) for population data. See Source section for more information https://doi.org/10.1787/f8d7880d-en).
Statlink2https://doi.org/888933976308

Tertiary education
The number of students pursing tertiary education globally has grown continuously over the past two decades
and is expected to continue growing through to 2030 (OECD, 2018[7]). The share of tertiary-educated young
adults (aged 25-34) in OECD increased from 35% in 2008 to 44% in 2018 (see Indicator A1). This increase could
reflect a rise in demand for skilled labour, a greater demand for tertiary education, increasing wealth and the
growing number of financial support policies to promote access to tertiary education (OECD, 2018[7]; Owens,
2017[8]).
The SDG agenda acknowledges the increased importance of tertiary education globally and includes an indicator
dedicated to this level. SDG Indicator 4.3.2 measures the gross enrolment rate in tertiary education as the total
number of students enrolled in tertiary education regardless of age expressed as a percentage of the population
in the five-year age group immediately following upper secondary education (typically 18-22 year-olds). However,
this definition may underestimate enrolment rates in countries where students mainly enrol in programmes of
short duration compared to countries where students enrol in programmes of longer durations. Other confounding
factors occur in OECD countries where long periods of part-time enrolment are customary.
As mentioned above, SDG Target 4.3 is closely linked to SDG Targets 4.4, 4.6 and 4.7, which aim to increase
the number of youth and adults with the necessary skills to thrive in the labour market and engage in society
more generally. To this end, SDG Indicator 4.4.3 measures the “youth educational attainment rates by age group,
economic activity status and programme orientation”. On average across OECD countries, 41% of young adults
(aged 25-34) have an upper secondary or post-secondary non-tertiary qualification as their highest level of
education and 44% have attained tertiary education (see Indicator A1). SDG Indicator 4.4.3 also recognises the
importance of tracking the link between educational attainment and economic activity status, which will be the
focus of the next section.
EDUCATION AT A GLANCE 2019 © OECD 2019

34  YOUTH IN THE EDUCATION SUSTAINABLE DEVELOPMENT GOAL

Figure 4. Enrolment rate of 15-24 year-olds in vocational education and training, by level of
education (2017)
SDG Indicator 4.3.3

1. The source for population data is the UOE data collection for demographic data (Eurostat/DEM) instead of the United Nations Population Division
(UNPD).
Countries are ranked in descending order of enrolment rate of 15-24 year-olds in vocational education and training in 2017.
Source: OECD (2019). The official data sources for this indicator are the UOE data collection for enrolment data and the United Nations Population
Division (UNPD) for population data. See Source section for more information (https://doi.org/10.1787/f8d7880d-en).
Statlink2https://doi.org/888933976327

Entering the labour market
The transition from education to work can be a difficult period for many young people. The risk of unemployment,
job insecurity due to low-paid or temporary contracts, and the uncertainties associated with starting to live
independently can make this a challenging phase in young people’s lives (OECD, 2018[9]).
Across OECD countries, youth remain at higher risks of unemployment and precarious employment compared
to adults (see Indicator A3). Young people are usually less specialised and more likely to be dismissed when
firms are in distress; they may also find themselves in an “experience trap”, where employers favour experienced
workers and young people therefore cannot increase their own experience (Dolado, 2015[3]). On the labour supply
side, there is higher worker turnover among youth than among adults, as their initial jobs may not correspond to
their skills and preferences (Blanchflower and Bell, 2011[10]).
The eighth Sustainable Development Goal (SDG 8) aims to “promote sustained, inclusive and sustainable
economic growth, full and productive employment and decent work for all”. In this sense, it overlaps with
Target 4.4, which highlights the need for skills needed for “employment and decent work”. SDG 8 also recognises
the relative vulnerability of youth in the labour market and dedicates two targets specifically to them. Target 8.6
aims by 2020 to substantially reduce the proportion of youth not in employment, education or training and
Target 8.B to develop and operationalise a global strategy for youth employment and implement the Global Jobs
Pact of the International Labour Organization. Target 8.5 on productive employment and decent work for all
women and men also confirms the relative vulnerability of youth, and specifically mentions young people as a
likely disadvantaged group.
SDG Indicator 8.5.2 measures the unemployment rate by gender, age and disability status. Indicator A3 of this
publication allows unemployment rates for young people and adults in older age groups to be compared. On

EDUCATION AT A GLANCE 2019 © OECD 2019

YOUTH IN THE EDUCATION SUSTAINABLE DEVELOPMENT GOAL  35

average across OECD countries, the unemployment rate is 2 percentage points higher among 25-34 yearolds (7%) than among 35-44 year-olds (5%). Indicator A3 also highlights a clear link between educational
attainment and young people’s activity status. On average across OECD countries, the unemployment rate is
almost twice as high for young adults (aged 25-34) who have not completed upper secondary education (14%),
compared to those with upper secondary or post-secondary non-tertiary attainment (7%) and those with a tertiary
degree (6%) (see Indicator A3).
To monitor countries’ progress towards productive employment and decent work, Target 8.5 also includes a
measure of the average hourly earnings by occupation, gender, age and disability status (SDG Indicator 8.5.1).
Although Indicator A4 of this publication evaluates average relative yearly earnings, it could still shed light on
young people’s earnings across OECD countries. It shows that, just as with activity status, earnings are also
strongly associated with educational attainment: on average across OECD countries, 25-34 year-olds with a
tertiary degree earn 38% more than those with upper secondary attainment (see Indicator A4). The lack of data
by disability status means this dimension of Indicators 8.5.1 and 8.5.2 cannot be monitored yet.
The proportion of youth neither employed nor in education or training (NEET) remains a more relevant measure
of youth participation in the labour market than the unemployment rate, since a large proportion of individuals in
the age group considered will still be in education, and the indicator captures not just those who are unemployed
but also those who are inactive (Dolado, 2015[3]). It is a key indicator of youth labour market performance as this
is a group at high risk of marginalisation and social exclusion. SDG Indicator 8.6.1 measures the proportion of
youth (aged 15-24 years) who do not participate in any form of education, whether it is formal or non-formal, nor
any employment or training. Taking Indicator A2 of this publication as a proxy (as it only considers youth in formal
education), on average across OECD countries, 11% of 15-24 year-olds were NEET in 2017.

Definitions
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).
Technical and vocational education and training (TVET) 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.
SDG Indicator
4.1.5
4.3.2
4.3.3
4.4.3
8.5.1
8.5.2
8.6.1

Definition
Upper secondary out-of-school rate
Gross enrolment ratio for tertiary education, by sex
Participation rate in technical and vocational programmes (15- to 24-year-olds), by sex
Youth educational attainment rates by age group, economic activity status, level of education and programme
orientation
Average hourly earnings of female and male employees, by occupation, age and persons with disabilities
Unemployment rate, by sex, age and persons with disabilities
Proportion of youth (aged 15-24 years) not in education, employment or training

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 index is calculated as the indicator value for women
divided by the indicator value for men.
EDUCATION AT A GLANCE 2019 © OECD 2019

36  YOUTH IN THE EDUCATION SUSTAINABLE DEVELOPMENT GOAL
All indicators presented in this chapter follow the agreed SDG methodology, including for recommended data
sources, and may differ in some cases from other indicators presented in Education at a Glance.
Please see Annex 3 for country-specific notes (https://doi.org/10.1787/f8d7880d-en).

Source
Indicator

Source

4.1.5
4.3.3

UOE 2018 data collection and UNPD (unless otherwise specified)
UOE 2018 data collection and UNPD (unless otherwise specified)

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
Blanchflower, D. and D. Bell (2011), “Young people and the Great Recession”, Oxford Review of
Economic Policy, Vol. 27/2, pp. 241-267.

[10]

Dolado, J. (2015), No Country for Young People? Youth Labour Market Problems in Europe, Centre for
Economy Policy Research, http://www.cepr.org.

[3]

OECD (2018), Education at a Glance 2018: OECD Indicators, OECD Publishing, Paris,
https://dx.doi.org/10.1787/eag-2018-en.

[9]

OECD (2018), “How is the tertiary-educated population evolving?”, Education Indicators in Focus,
No. 61, OECD Publishing, Paris, https://doi.org/10.1787/a17e95dc-en.

[7]

OECD (2017), Education at a Glance 2017: OECD Indicators, OECD Publishing, Paris,
https://dx.doi.org/10.1787/eag-2017-en.

[6]

OECD (2016), Education Policy Outlook: Luxembourg, OECD, Paris,
https://www.oecd.org/luxembourg/Education-Policy-Outlook-Country-Profile-Luxembourg.pdf.

[1]

OECD (2014), Skills beyond School: Synthesis Report, OECD Reviews of Vocational Education and
Training, OECD Publishing, Paris, https://dx.doi.org/10.1787/9789264214682-en.

[5]

Owens, T. (2017), “Higher education in the sustainable development goals framework”, European
Journal of Education, http://dx.doi.org/10.1111/ejed.12237.

[8]

UNESCO (2017), Global Education Monitoring Report: Accountability in Education: Meeting our
commitments, UNESCO, Paris.

[4]

UNESCO (2016), Global Education Monitoring Report 2016: Education for People and Planet: Creating
Sustainable Futures for All, UNESCO, Paris.

[2]

EDUCATION AT A GLANCE 2019 © OECD 2019

 37

Chapter A. The output of educational
institutions and the impact of learning

Indicator A1 To what level have adults studied?
Statlink: https://doi.org/10.1787/888933980792
Indicator A2 Transition from education to work: Where are today’s youth?
Statlink: https://doi.org/10.1787/888933980811
Indicator A3 How does educational attainment affect participation in the labour
market?
Statlink: https://doi.org/10.1787/888933980830
Indicator A4 What are the earnings advantages from education?
Statlink: https://doi.org/10.1787/888933980849
Indicator A5 What are the financial incentives to invest in education?
Statlink: https://doi.org/10.1787/888933980868
Indicator A6 How are social outcomes related to education?
Statlink: https://doi.org/10.1787/888933980887
Indicator A7 To what extent do adults participate equally in education and
learning?
Statlink: https://doi.org/10.1787/888933980906

EDUCATION AT A GLANCE 2019 © OECD 2019

38  A1. TO WHAT LEVEL HAVE ADULTS STUDIED?

Indicator A1. To what level have adults studied?
Highlights


On average across OECD countries, about 25% of tertiary-educated 25-64 year-olds have
qualifications in business administration or law, while 5% or less had studied information and
communication technologies (ICT), natural sciences, mathematics or statistics.



The proportion of tertiary-educated 25-34 year-olds increased by 9 percentage points on average
across OECD countries between 2008 and 2018, while the share of adults with less than upper
secondary education fell from 19% to 15%.



Across all age groups, but particularly among young adults, the proportion of tertiary-educated women
is now higher than the proportion of tertiary-educated men in almost all OECD countries. In some
countries, the gender imbalance is reversed between the older and younger generations.

Figure A1.1. Fields of study among tertiary-educated 25-64 year-olds (2018)

1. Year of reference differs from 2018. Refer to the source table for more details.
2. Data refer to bachelor’s degree field, even for those with additional tertiary degrees.
Countries are ranked in descending order of the percentage of tertiary-educated 25-64 year-olds who studied in the field of education.
Source: OECD (2019), Table A1.3. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2https://doi.org/10.1787/888933976403

Context
Giving everyone a fair chance to obtain a high-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. A population that is highly qualified across diverse fields of study promotes inclusive
growth by broadening the pool of candidates for highly 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

EDUCATION AT A GLANCE 2019 © OECD 2019

A1. TO WHAT LEVEL HAVE ADULTS STUDIED?  39

capital and a signal of 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).
Higher levels of educational attainment are associated with several positive economic and social outcomes for
individuals (see Indicators A2, A3, A4, A5 and A6). Highly educated individuals tend to be more socially
engaged and have higher employment rates and larger relative earnings. Greater proficiency in literacy and
numeracy is also strongly associated with higher levels of formal education (OECD, 2016[1]).
Individuals thus have incentives to pursue more education, and governments have incentives to provide
appropriate infrastructure and policies to support higher levels of 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.
For employers, qualifications certify and offer information about the type of knowledge and skills that potential
employees have acquired in formal education. This helps them to make hiring decisions, or even to decide
where to locate their business in order to access the best-qualified talent. A qualification from a particular field
of study is also required to gain entry to some professions and industries. Analysing qualifications by fields of
study can therefore also provide an insight into supply and demand issues for different classes of occupation
in OECD countries.

Other findings


Between 2008 and 2018, the proportion of young adults with tertiary education increased in all OECD
and partner countries while the proportions of young adults with upper secondary education or
post-secondary non-tertiary education increased in Brazil, Costa Rica, Indonesia, Mexico, Portugal and
South Africa.



While tertiary attainment has risen for both younger men and younger women between 2008 and 2018
across OECD countries, the gender gap in favour of women has widened from 9 percentage points in
2008 to 12 percentage points in 2018.



There are marked differences in the share of adults with a tertiary qualification in the field of education,
ranging from about 20% in Costa Rica, Hungary and Iceland, to 5% or less in France, Italy and
the United Kingdom.



On average across the OECD, 14% of adults hold a master’s or doctoral level qualification. In Estonia,
Luxembourg, Poland, the Russian Federation, the Slovak Republic and Switzerland, the share is over
20%, while it is only around 2% in Argentina, Brazil, China, Chile, Costa Rica, Indonesia, Mexico, Saudi
Arabia, South Africa and Turkey.

EDUCATION AT A GLANCE 2019 © OECD 2019

40  A1. TO WHAT LEVEL HAVE ADULTS STUDIED?

Analysis
Below upper secondary education
The attainment of upper secondary education has become the minimum requirement for navigating the modern
economy and society. As a result, young people today who leave school before completing upper secondary
education not only face difficulties in the labour market, but are also twice as likely to have low numeracy skills
as those with an upper secondary education (OECD, 2015[2]). In most OECD countries, the large majority of
younger adults (25-34 year-olds) had at least an upper secondary qualification in 2018, while the average
proportion of young adults without an upper secondary qualification was 15% (Figure A1.2).

Figure A1.2. Educational attainment of 25-34 year-olds (2018)

1. Year of reference differs from 2018. Refer to Table A1.1 for more 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 (13% of adults aged 25-64 are in this group).
Countries are ranked in descending order of the percentage of tertiary-educated 25-34 year-olds.
Source: OECD (2019), Education at a Glance Database, http://stats.oecd.org. See Source section for more information and Annex 3 for notes
(https://doi.org/10.1787/f8d7880d-en).
Statlink2https://doi.org/10.1787/888933976422

Substantial variations remain in the share of young adults without upper secondary education across the OECD
and partner countries. While the share is below 10% among 25-34 year-olds in 13 countries (Canada,
the Czech Republic, Finland, Ireland, Israel, Korea, Lithuania, Poland, the Russian Federation,
the Slovak Republic, Slovenia, Switzerland and the United States), it is 50% or more in the People’s Republic of
China, Costa Rica, India and Indonesia. In Korea, only 2% of men and women aged 25-34 have not completed
upper secondary education, the lowest share across OECD and partner countries for both genders, while in
China and India the proportion of young adults with at most lower secondary education is 64% (Figure A1.2 and
Table A1.2).
On average across OECD countries, the share of younger adults with below upper secondary education fell from
19% in 2008 to 15% in 2018, indicating overall progress in increasing the levels of educational attainment in
the OECD. Some countries have reduced the share of young adults not completing upper secondary education

EDUCATION AT A GLANCE 2019 © OECD 2019

A1. TO WHAT LEVEL HAVE ADULTS STUDIED?  41

by a much larger amount. Across OECD countries with comparable data between 2008 and 2018, Portugal
experienced the largest decrease in young adults lacking an upper secondary or post-secondary non-tertiary
education, with a drop of 25 percentage points during this period. Mexico also reduced the share of young adults
without upper secondary education by at least 15 percentage points between 2008 and 2018. In both countries,
the decrease in the share of young adults without upper secondary education was combined with increased
attainment of both upper secondary or post-secondary non-tertiary education and tertiary education (Table A1.2).
On the other hand, in Austria, Finland and Hungary the share of adults without upper secondary education
changed by 1 percentage point or less between 2008 and 2018. Norway is the only country with comparable data
for 2008 and 2018 where the proportion of young adults with below upper secondary education increased
(Table A1.2).
In most countries, young men are more likely than young women to lack an upper secondary qualification, with
an OECD average of 17% for men and 14% for women. The gender gap is 5 percentage points or more in about
one-quarter of OECD and partner countries: Argentina, Brazil, Colombia, Costa Rica, Denmark, Estonia, Iceland,
India, Italy, Latvia, Norway, Portugal, South Africa, Spain and Turkey. In Iceland, India, Portugal and Spain, the
gap is 10 percentage points or more. In India and Turkey, the gender gap is in favour of young men whereas in
all other countries the gap is in favour of young women. Countries with similar shares of young men and women
without upper secondary education include Austria, the Czech Republic, Hungary, Korea, Luxembourg and
the Slovak Republic (Table A1.2).

Upper secondary and post-secondary non-tertiary education
On average in the OECD, 42% of 25-64 year-olds have upper secondary or post-secondary non-tertiary
education as the highest level of education: 37% having only an upper secondary education and 6% a
post-secondary non-tertiary qualification. The proportion of adults with a post-secondary non-tertiary qualification
is particularly high in Canada, Germany, Greece, Ireland, Latvia, Lithuania, New Zealand and
the Russian Federation, where 10% or more of the adult population hold qualifications at this level (Table A1.1).
Across OECD and partner countries, the share of young adults (aged 25-34) who have upper secondary or postsecondary non-tertiary education as the highest level achieved ranges from as low as 18% in China to as high
as 77% in South Africa (Figure A1.3).
The percentage of young adults with an upper secondary or post-secondary non-tertiary education as the highest
level of attainment has fallen from 46% in 2008 to 41% in 2018 on average across OECD countries. This change
has occurred in the context of a falling share of younger adults without an upper secondary education (from 19%
in 2008 to 15% in 2018), and a rising share of young adults with tertiary education (from 35% to 44%)
(Table A1.2).
Not all countries have followed a similar pattern. For example, among OECD countries, in Mexico the share of
young adults with an upper secondary or post-secondary non-tertiary education increased by 8 percentage points
and in Portugal it increased by 13 percentage points from 2008 to 2018. Most other OECD countries have
reduced the share of the young population with upper secondary or post-secondary non-tertiary education as the
highest level achieved, while increasing the share of young adults with tertiary education. For example, in Austria,
the share of young adults with tertiary education increased by 7 percentage points (from 33% to 40%) while the
share with upper secondary or post-secondary non-tertiary fell by the same extent from 55% to 48% (Table A1.2).

Tertiary education
On average across OECD countries, 39% of adults aged 25-64 had achieved a tertiary qualification in 2018.
Tertiary education has expanded significantly over recent decades across the OECD. On average, a larger
proportion of 25-34 year-olds in the OECD have attained tertiary education in 2018 than have upper secondary
education as the highest level of attainment. The share of younger adults with tertiary education is 44% on
average across OECD countries, much higher than the share among 55-64 year-olds (27%), reflecting increasing
EDUCATION AT A GLANCE 2019 © OECD 2019

42  A1. TO WHAT LEVEL HAVE ADULTS STUDIED?
access to tertiary education in the OECD in more recent decades. In all OECD countries, the share of younger
adults with tertiary education has increased between 2008 and 2018 (Table A1.2 and OECD (2019[3])).
The proportion of 25-34 year-olds with tertiary education is 60% or more in Canada, Japan, Korea and
the Russian Federation. In Canada, Korea and the Russian Federation this high share of tertiary-educated adults
comes with a correspondingly lower share (less than 7%) of adults with below upper secondary education. The
countries with the lowest share of tertiary-educated young adults in OECD and partner countries (16% or below)
are India, Indonesia and South Africa. In India and Indonesia, the commonest level of attainment among
25-34 year-olds is below upper secondary education, while in South Africa, the commonest level of attainment is
upper secondary or post-secondary non-tertiary education (Table 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, although some countries also have large numbers of adults with short-cycle
tertiary education. For example, in Canada, Korea and the Russian Federation, more than one-fifth of young
adults hold short-cycle tertiary qualifications, and in Austria and China, those with a short-cycle tertiary degree
represent the largest share of tertiary-educated 25-34 year-olds. Conversely, over 15 countries have almost no
young adults with short-cycle tertiary education (Figure A1.3).

Figure A1.3. Distribution of 25-34 year-olds with tertiary education, by level of tertiary education (2018)

1. Year of reference differs from 2018. Refer to Table A1.1 for more details.
Note: Some categories might be included in other categories. Please refer to Education at a Glance Database, http://stats.oecd.org for details.
Countries are ranked in descending order of the total percentage of tertiary-educated 25-34 year-olds.
Source: OECD (2019), Education at a Glance Database, http://stats.oecd.org. See Source section for more information and Annex 3 for notes
(https://doi.org/10.1787/f8d7880d-en).
Statlink2https://doi.org/10.1787888933976441

In the Czech Republic, France, Hungary, 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 of adults with tertiary education. This might reflect different patterns of organisation of tertiary education
across countries, with some countries having a stronger tradition of long first degree programmes that lead
directly to a master’s qualification. On average across OECD countries, about 1% of younger adults have a
doctoral or equivalent qualification, although in Luxembourg, Switzerland and the United States the proportion is
around 2%. Slovenia has the largest share of adults with a doctoral or equivalent qualification, where the share
of adults holding a qualification at this level is about 5% (Figure A1.3).
EDUCATION AT A GLANCE 2019 © OECD 2019

A1. TO WHAT LEVEL HAVE ADULTS STUDIED?  43

Gender differences in tertiary education
Across the OECD, the gender gap in tertiary attainment among young adults has increased from 9 percentage
points in 2008 to 12 percentage points in 2018. In almost all OECD countries, the proportion of tertiary-educated
women among 25-64 year-olds is higher than the proportion of tertiary-educated men. In Estonia, Iceland, Latvia
and Portugal the proportion of tertiary-educated women is at least 50% higher than the proportion of tertiaryeducated men, while just 9 countries have a higher proportion of tertiary-educated men. In India, the proportion
of tertiary-educated women is less than 60% of the proportion of tertiary-educated men (Figure A1.4 and
Table A1.2).

Figure A1.4. Share of tertiary-educated women as a percentage of the share of tertiary-educated men, by
age group (2018)
25-34 year-olds, 55-64 year-olds and 25-64 year-olds

1. Year of reference differs from 2018. Refer to Table A1.1 for more details.
Countries are ranked in descending order of the percentage point difference for the age group 25-64.
Source: OECD (2019), Education at a Glance Database, http://stats.oecd.org. See Source section for more information and Annex 3 for notes
(https://doi.org/10.1787/f8d7880d-en).
Statlink2https://doi.org/10.1787/888933976460

The gender gap in tertiary attainment is generally larger for younger adults than for older adults, except in Estonia,
Iceland, Lithuania, the Russian Federation and Sweden. Some countries have experienced a reversal of the
gender gap between younger and older adults. In Korea, for example, the share of 55-64 year-old women with
tertiary attainment is at 50% of the share of tertiary-educated men, but among 25-34 year-olds the proportion of
women with tertiary attainment is 18% higher (Figure A1.4).

Fields of study among tertiary-educated adults
Certain fields of study are more prevalent among tertiary-educated adults. On average across OECD countries
with available data, 24% of tertiary-educated 25-64 year-olds have a degree in business, administration and law,
which is the most common field of study. The share ranges from 12% in the Czech Republic to over 30% in
Costa Rica, France, Luxembourg, Mexico and Turkey. For most countries with disaggregated data on this field
of study, a larger share of adults obtained their degree in business and administration than in law (Figure A1.1
and Table A1.3).
EDUCATION AT A GLANCE 2019 © OECD 2019

44  A1. TO WHAT LEVEL HAVE ADULTS STUDIED?
In Belgium, the Czech Republic, Greece, Hungary, Iceland, Italy, Poland and the United States, the most popular
broad fields of study are arts and humanities, social sciences, journalism and information. In Austria, Germany,
the Russian Federation and the Slovak Republic, the largest share of tertiary-educated adults hold a degree in
engineering, manufacturing or construction, while the most widespread field of study in Denmark, Norway and
Sweden is health and welfare (Table A1.3).
Despite strong labour-market outcomes for graduates with qualifications in information and communication
technologies (ICT) (see Indicators A3 and A4), the share of adults electing to study these subjects is relatively
low across the OECD. On average, only 4% of tertiary-educated adults hold a qualification in this field, and the
proportion across countries varies much less than for many other fields of study. Among OECD and partner
countries, the share reaches about 6% in Finland, Hungary, Mexico and Spain, while Costa Rica and Luxembourg
has the highest proportion overall of adults with ICT qualification, at 7%. Conversely, just 1% or less of adults
with a tertiary qualification in the Russian Federation and Turkey studied ICT (Table A1.3).
The proportions of adults who have studied subjects related to the provision of social services (for example,
education, health and welfare) can indicate the potential supply of staff to carry out these vital services in the
population. For example, many countries have experienced shortages of teachers and health workers in recent
years, and have implemented active policies to increase staff to these areas and make these professions more
attractive.
On average across OECD countries, the field of education accounts for 12% of tertiary qualifications among
25-64 year-olds, but there is great variation across countries. In France, Italy and the United Kingdom, the share
of tertiary-educated adults whose field of study was education is 5% or below, whereas it is 18% or more in
Costa Rica, Hungary and Iceland. Patterns of qualification in health and welfare show a similar broad variation
in countries with available data. For example, in Denmark, 27% of tertiary-educated adults hold a qualification in
this field, while in Turkey it is only 6% (Table A1.3).

Box A1.1. Evolving preferences in fields of study over time
The concept of attainment measures the overall level of qualifications in the population, while graduates are
defined as the section of the population graduating in a given year (in this case, 2017). Nevertheless,
comparing the distribution of fields of study between the overall population and recent graduates can provide
insights into the evolution of preferences over time.
The broad fields of business, administration and law, and of arts and humanities, social sciences, journalism
and information are the most common fields of study both for recent graduates and for the tertiary-educated
population overall, although recent graduates appear to have a slightly stronger preference for business,
administration and law. This preference is particularly pronounced in the Czech Republic, Hungary,
Luxembourg and the Slovak Republic where the shares of recent graduates who studied in this field are all at
least 6 percentage points more than among tertiary-educated adults overall (Figure A1.a).
The difference is more pronounced in the field of health and welfare. In 2017, 16% of tertiary graduates
obtained a degree in this field, 3 percentage points more than the share of tertiary-educated adults in the
population overall. In Belgium, Latvia, Lithuania and the United States, the difference was more than
7 percentage points. These differences could be attributed to changing preferences, but could also be related
to increased requirements for qualifications in order to work in this field (Figure A1.a and Table A1.3).

EDUCATION AT A GLANCE 2019 © OECD 2019

A1. TO WHAT LEVEL HAVE ADULTS STUDIED?  45

Figure A1.a Distribution of recent tertiary graduates by field of study, compared with fields of study of
all tertiary-education 25-64 year-olds (2017 and 2018)
On average across OECD countries

Fields are ranked in descending order of the distribution of all tertiary-educated 25-64 year-olds (2018).
Source: OECD/UIS/Eurostat (2019) and OECD/ILO/UIS (2019). See Source section for more information and Annex 3 for notes
(https://doi.org/10.1787/f8d7880d-en).
Statlink2https://doi.org/10.1787/888933976479

In contrast, engineering, manufacturing and construction appears to have become a slightly less attractive
option for recent graduates. While 16% of all tertiary-educated 25-64 year-olds in 2017 had studied
engineering, manufacturing and construction, only 14% of that year’s tertiary graduates had done so
(Figure A1.a and Table A1.3).

Figure A1.b. Share of engineering, manufacturing and construction graduates among all tertiaryeducated 25-64 year-olds and recent graduates (2017 and 2018)

Countries are ranked in descending order of the share of engineering, manufacturing and construction graduates among all tertiary-educated 25-64
year-olds (2018).
Source: OECD/UIS/Eurostat (2019) and OECD/ILO/UIS (2019). See Source section for more information and Annex 3 for notes
(https://doi.org/10.1787/f8d7880d-en).
Statlink2https://doi.org/10.1787/888933976498

Labour-market demand for ICT and engineering qualifications is strong and is likely to remain strong into the
future as technology progresses. However, in most countries, preferences for these fields among students

EDUCATION AT A GLANCE 2019 © OECD 2019

46  A1. TO WHAT LEVEL HAVE ADULTS STUDIED?
appear to be either stable or decreasing. For example, across OECD countries, the percentage of the tertiaryeducated population aged 25-64 with engineering, manufacturing and construction qualifications ranges from
less than 10% in the United States to 20% and more in Austria, Estonia, Germany, Lithuania and the Russian
Federation. However, among recent graduates, the percentage achieving an engineering, manufacturing and
construction qualification is lower in almost all countries except Greece, Italy, Mexico, Norway, Poland,
Portugal and Slovenia (Figure A1.b).
In Austria, the Slovak Republic, the Russian Federation and the United Kingdom, there is an significant gap
(more than 6 percentage points) between the share of tertiary-educated 25-64 year-olds who studied
engineering, manufacturing and construction and the share of recent graduates in that field. In
the United Kingdom, the share of recent graduates getting a degree in this field is less than half the share
among the tertiary-educated population and the country is facing high skills shortages in this domain
(Figure A1.b).

Subnational variations in educational attainment
National level data often hide important regional inequalities. In general, regional inequalities in educational
attainment have narrowed in recent years, mainly due to improvements in the regions that had the lowest
educational attainment levels (OECD, 2018[4]). However, many countries still have substantial differences in
attainment between regions. In Brazil, the Czech Republic, Italy and Turkey, the most recent available data show
the regions with the highest percentage of tertiary-educated 25-64 year-olds have at least 3 times as high a rate
as the regions with the lowest. Many countries with relatively high tertiary attainment rates also have strong
regional inequalities. For example, in the Russian Federation (85 regions), the 2016 tertiary attainment rate at
the national level is 53% and ranges between 26% and 75% across regions. Similarly, in Canada, 57% of adults
have a tertiary education, but there is a 28 percentage-point gap between the provinces with the lowest and
highest rates (OECD (2019[5])).
Conversely, in many other countries, regional attainment levels vary far less. The narrowest gaps tend to occur
in countries with fewer defined subnational regions. The smallest ratios between the regions with the highest and
lowest tertiary attainment levels (less than 1.5) occur in Belgium, Finland, Hungary, Ireland, Poland, Slovenia
and Switzerland, countries that mostly have few large subnational regions. In Belgium, for example, the tertiary
attainment rates of all three regions are within10 percentage points of each other. In Hungary, which has eight
regions, the region with the largest share of tertiary-educated adults is has a rate that is less than 4 percentage
points higher than region with the lowest share (OECD, 2019[5]).

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.
Fields of study are categorised according to the ISCED Fields of Education and Training (ISCED-F 2013). See
the Reader’s Guide for a full listing of the ISCED fields used in this report.
Levels of education: See the Reader’s Guide at the beginning of this publication for a presentation of all
ISCED 2011 levels.
EDUCATION AT A GLANCE 2019 © OECD 2019

A1. TO WHAT LEVEL HAVE ADULTS STUDIED?  47

Methodology
Educational attainment profiles are based on annual data on the percentage of the adult population
(25-64 year-olds) in specific age groups who have 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 the “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[6]).
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.
Please see the OECD Handbook for Internationally Comparative Education Statistics (OECD, 2018[7]) for more
information and Annex 3 for country-specific notes (https://doi.org/10.1787/f8d7880d-en).

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 Labour Market, Economic and Social
Outcomes of Learning (LSO) 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 available in the OECD Regional Statistics Database
(OECD, 2019[5]).
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 (2019), Education at a Glance Database - Educational attainment and labour-force status,
http://stats.oecd.org/Index.aspx?datasetcode=EAG_NEAC.

[3]

OECD (2019), Regional Statistics Database - Educational attainment, by age group,
http://stats.oecd.org/Index.aspx?datasetcode= REGION_EDUCAT.

[5]

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 (2018), OECD Regions and Cities at a Glance 2018, OECD Publishing, Paris,
https://dx.doi.org/10.1787/reg_cit_glance-2018-en.

[4]

EDUCATION AT A GLANCE 2019 © OECD 2019

48  A1. TO WHAT LEVEL HAVE ADULTS STUDIED?
OECD (2016), Education at a Glance 2016: OECD Indicators, OECD Publishing, Paris,
http://dx.doi.org/10.1787/eag-2016-en.

[1]

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.

[2]

UNESCO Institute for Statistics (2012), International Standard Classification of Education (ISCED)
2011, UNESCO-UIS, Montreal, http://uis.unesco.org/sites/default/files/documents/internationalstandard-classification-of-education-isced-2011-en.pdf.

[6]

Indicator A1 Tables
Table A1.1

Educational attainment of 25-64 year-olds (2018)

Table A1.2

Trends in educational attainment of 25-34 year-olds, by gender (2008 and 2018)

Table A1.3

Fields of study among tertiary-educated 25-64 year-olds (2018)

Cut-off date for the data: 19 July 2019. 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.
StatLink: https://doi.org/10.1787/888933980792

EDUCATION AT A GLANCE 2019 © OECD 2019

A1. TO WHAT LEVEL HAVE ADULTS STUDIED?  49

Table A1.1. Educational attainment of 25-64 year-olds (2018)
Percentage of adults with a given level of education as the highest level attained

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 2017.
2. Year of reference 2010.
3. Year of reference 2011.
4. Year of reference 2016.
Source: OECD / ILO / UIS (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888933976346

EDUCATION AT A GLANCE 2019 © OECD 2019

50  A1. TO WHAT LEVEL HAVE ADULTS STUDIED?
Table A1.2. Trends in educational attainment of 25-34 year-olds, by gender (2008 and 2018)
Percentage of 25-34 year-olds with a given level of education as the highest level attained

Note: In most countries there is a break in the time series, represented by the code "b", as data for 2018 refer to ISCED 2011 while data for 2008 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 2017 instead of 2018.
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 (13% of adults aged 25-64 are in this group).
4. Year of reference 2010 instead of 2018.
5. Year of reference 2011 instead of 2018.
Source: OECD / ILO / UIS (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888933976365

EDUCATION AT A GLANCE 2019 © OECD 2019

A1. TO WHAT LEVEL HAVE ADULTS STUDIED?  51

Table A1.3. Fields of study among tertiary-educated 25-64 year-olds (2018)
Percentage of adults with tertiary education

Note: Data for aggregated fields may not be equivalent to the sum of the subcategories because of the category unknown.
1. Year of reference 2017.
2. Year of reference 2016.
3. Data refer to bachelor’s degree field, even for those with additional tertiary degrees.
Source: OECD / ILO / UIS (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888933976384

EDUCATION AT A GLANCE 2019 © OECD 2019

52  A2. TRANSITION FROM EDUCATION TO WORK: WHERE ARE TODAY'S YOUTH?

Indicator A2. Transition from education to work:
Where are today's youth?
Highlights


On average across OECD countries, 14.3% of 18-24 year-olds are neither employed nor in education
or training (NEET). In Brazil, Colombia, Costa Rica, Italy, South Africa and Turkey, over 25% of 1824 year-olds are NEET.



The duration of unemployment NEETs experience varies across countries. On average across OECD
countries, 1.5% of 18-24 year-olds are not in education and have been unemployed for more than a
year. In Argentina, Brazil, Greece, Italy, Portugal, the Slovak Republic and Spain, 3.0% or more of
18-24 year-olds are in this situation, with Greece having the highest share, at 7.9%.



The share of young adults who are no longer in education and are looking for work is on average
across OECD countries 1.9% for 15-19 year-olds; the share of unemployed NEETs rises considerably
among 20-24 year-olds (6.2%) and remains at this level among 25-29 year-olds.

Figure A2.1. Percentage of 18-24 year-olds not in education, by labour market status (2018)

1. Year of reference differs from 2018. Refer to the source table for more details.
Countries are ranked in descending order of the total percentage of 18-24 year-olds not in education.
Source: OECD (2019), Table A2.1. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933976574

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

EDUCATION AT A GLANCE 2019 © OECD 2019

A2. TRANSITION FROM EDUCATION TO WORK: WHERE ARE TODAY'S YOUTH?  53

women and young men experience the transition from education to work, while in other countries significant
proportions of young women go on to raise a family full time after leaving education 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 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 the labour market needs. Public investment in education
can be a sensible way to counterbalance unemployment and invest in future economic growth, by building the
necessary skills. In addition, public investment could be directed towards potential employers, through the
creation of incentives to hire young people.
Being left out of employment can have long-lasting consequences, especially when people experience long
spells of unemployment and become discouraged. Young people who are NEET are a current policy concern,
with significant future consequences for individuals and society if insufficient action is taken to address this
issue.

Other findings


Across all OECD countries, higher educational attainment is associated with lower NEET rates. On
average, 40.1% of 25-29 year-olds without upper secondary education are NEET, compared to 16.8%
of those with an upper secondary or post-secondary non-tertiary education and 10.8% for those who
completed a tertiary degree.



Between 2008 and 2018, access to higher education among young adults increased. In most countries,
this access to additional educational opportunities has been accompanied by a diminishing share of
young adults in employment. For example, in Spain the share of employed 20-24 year-olds not in
education is 21 percentage points lower than in 2008, while the share of the same age group in
education is about 18 percentage points higher.



The majority of female NEETs are inactive, while the unemployed account for a larger share of male
NEETs. On average across OECD countries, 10.8% of women aged 18-24 are inactive and NEET,
compared to only 6.5% of men, while 5.0% of women in this age group are unemployed and NEET,
compared to 6.4% for men.

Note
This indicator analyses the situation of young people in transition from education to work: those in education,
those who are employed, and those who are neither employed nor in education or training (NEET). 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 this
age group is no longer in compulsory education but a significant proportion of them will still be continuing their
studies.

EDUCATION AT A GLANCE 2019 © OECD 2019

54  A2. TRANSITION FROM EDUCATION TO WORK: WHERE ARE TODAY'S YOUTH?

Analysis
Labour-market outcomes of young adults once they leave education
Many young people leave education between the ages of 18 and 24. On average across OECD countries, almost
half (47%) of 18-24 year-olds have left the education system. In Colombia, Israel, Mexico and Turkey at least
60% of 18-24 year-olds are not in education, while in Belgium, Denmark, Germany, Greece, Lithuania,
Luxembourg, the Netherlands and Slovenia the share is below 40% (Figure A2.1).
Among 25-29 year-olds, on average across OECD countries, only 16% are still in education. However, in
Denmark, Finland, Iceland and Israel, over 25% of 25-29 year-olds remain in education (OECD, 2019[1]).
Young adults no longer in education may be employed, unemployed or inactive. On average across OECD
countries, 33% of 18-24 year-olds are employed and no longer in education, meaning that most 18-24 year-olds
who have left education are in employment. Among all 18-24 year-olds not in education, 80% or more are
employed in Iceland, the Netherlands, New Zealand, Norway, Sweden and Switzerland. In other countries, young
people have experienced more difficulty entering the labour market when they leave the education system. For
instance, in Greece and South Africa, over 30% of 18-24 year-olds who are not in education are unemployed
(Figure A2.1).
Young adults who have not found employment upon leaving education are often referred to as NEETs: young
people neither employed nor in education or training. On average across OECD countries, 14.3% of
18-24 year-olds are NEET. In Germany, Iceland, Luxembourg, the Netherlands, Norway, Slovenia, Sweden and
Switzerland the share of NEETs is below 10%, while it is 20% or more in Argentina, Brazil, Chile, Colombia,
Costa Rica, Greece, Italy, Mexico, South Africa, Spain and Turkey. In most countries, inactivity is more common
than unemployment: on average across OECD countries, 8.6% of 18-24 year-olds are inactive NEETs and
5.7% are unemployed NEETs. However, in France, Greece, Latvia, Portugal, the Slovak Republic and Spain the
share of unemployed NEETs exceeds that of inactive NEETs (Table A2.1).

Figure A2.2. Percentage of young adults not in education and unemployed, by age group (2018)

1. Year of reference differs from 2018. Refer to Table A2.1 for more details.
Countries are ranked in descending order of the percentage of 25-29 year-olds not in education and unemployed.
Source: OECD (2019), Education at a Glance Database, http://stats.oecd.org. See Source section for more information and Annex 3 for notes
(https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933976593

EDUCATION AT A GLANCE 2019 © OECD 2019

A2. TRANSITION FROM EDUCATION TO WORK: WHERE ARE TODAY'S YOUTH?  55

Unemployed NEETs by age group
The share of young adults who are no longer in education and looking for work increases with age. On average
across OECD countries, 1.9% of 15-19 year-olds are in this situation. This low share is partly explained by
compulsory education typically ending between the ages of 16 and 18 (see Table X1.3). The rate of unemployed
NEETs rises considerably among 20-24 year-olds (6.2%) and remains at this level among 25-29 year-olds
(6.1%). The share of unemployed NEETs is the lowest for the younger age group (15-19 year-olds) across all
OECD and partner countries with data. The pattern for 20-24 year-olds and 25-29 year-olds is more varied across
countries: in Argentina, Brazil, Colombia, Costa Rica, Lithuania, Portugal and the Russian Federation the share
of unemployed NEETs is at least 2 percentage points higher for 20-24 year-olds while in Denmark, Greece,
South Africa and Spain the share is at least 2 percentage points higher among 25-29 year-olds (Figure A2.2).

Duration of unemployment for young adults who are unemployed NEETs
Young people who experience unemployment following graduation are more likely to be affected by
unemployment later in their careers, and by lower earnings – the so-called “scarring effect” (Eurofound, 2017[2]).
The duration of unemployment has a significant impact on their later labour-market outcomes. While the scarring
effect is negligible for short-term unemployed youth – those who have been unemployed for under three months
– it is increasingly important for the medium-term unemployed (who have been unemployed for at least three
months and less than a year), and the long-term unemployed who have been unemployed for a year or more
(OECD, 2015[3]).
On average across OECD countries, 2.0% of 18-24 year-olds are NEET and have been unemployed for less
than 3 months, 2.8% have been unemployed for between 3 and 12 months, and 1.5% have been unemployed
and NEET for 12 months or more. In other words, an important share of unemployment among NEETs is not a
temporary situation where people are in the process of moving from one job to another, but a longer-lasting
situation (Table A2.3).

Figure A2.3. Percentage of unemployed 18-24 year-olds not in education, by duration of unemployment (2018)
As a percentage of all 18-24 year-olds

Note: The distribution of duration of unemployment may not sum up to the share of unemployed as these data were collected separately.
1. Year of reference differs from 2018. Refer to the source table for more details.
Countries are ranked in descending of the share of unemployed 18-24 year-olds.
Source: OECD (2019), Table A2.3. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933976612
EDUCATION AT A GLANCE 2019 © OECD 2019

56  A2. TRANSITION FROM EDUCATION TO WORK: WHERE ARE TODAY'S YOUTH?
Greece and Italy have the largest proportion of long-term unemployed NEETs among all unemployed NEETs
aged 18-24, where more than one in two unemployed NEETs have been unemployed for a year or more. In
contrast, the lowest relative proportion of long-term unemployed can be found in Canada, Chile, Colombia,
Costa Rica, Mexico, New Zealand and the United States where less than 10% of unemployed NEETs have been
in that situation for a year or more (Figure A2.3).

Gender gap among inactive NEETs
The majority of female NEETs are inactive, while a larger share of male NEETs are unemployed. On average
across OECD countries, 10.8% of women aged 18-24 are inactive and no longer in education, compared to only
6.5% of men, while 5.0% of women of this age are unemployed and not in education, compared to 6.4% of men
(OECD, 2019[1]).
Various factors contribute to people being inactive and not seeking employment. Among women, the main
reasons for inactivity are childcare responsibilities, while health and other factors are more prevalent among men
(OECD, 2016[4]). When interpreting the share of NEETs, it should be noted that a small share of inactive NEETs
are only temporarily inactive and may soon re-enter employment, education or training. A small share of young
adults may also have become discouraged and stopped looking for work because they believe that there are no
job opportunities for them (Eurofound, 2016[5]).
The share of inactive NEETs among women increases with age, while it is more or less stable among men. On
average across OECD countries, among 15-19 year-olds, 5.5% of women and 4.3% of men are inactive NEETs,
a gender gap of less than 2 percentage points. Among 20-24 year-olds the shares increase to 11.6% for women
and 6.5% for men, and among 25-29 year-olds to 16.5% for women and 5.6% for men, a gender gap of more
than 10 percentage points (OECD, 2019[1]).
In Colombia, Costa Rica, the Czech Republic, Mexico, the Slovak Republic and Turkey, the gender gap in
inactivity rates is at least 20 percentage points among 25-29 year-olds. Mexico and Turkey are the only two
OECD countries where the gender gap is over 35 percentage points. In these two countries, as in many others,
the overall high share of NEETs can mainly be attributed to the high share of inactive female NEETs (OECD,
2019[1]).

Educational attainment and the risk of becoming NEET
By the age of 25, most of young adults have either left education or are enrolled in education but have already
attained a first tertiary degree. The typical graduation age from a bachelor’s or equivalent degree ranges from
21 to 24 years (see Table X.1a). Young adults who have left education without a tertiary degree are more likely
to become NEET than those who completed one. On average across OECD countries, 10.8% of tertiary-educated
25-29 year-olds are NEET, while the share increases to 16.8% for those with an upper secondary or
post-secondary non-tertiary education and to about 40.1% for those without upper secondary education. The
situation is especially severe for 25-29 year-olds without an upper secondary education in Lithuania,
the Slovak Republic and South Africa, where the share of NEETs among 25-29 year-olds without upper
secondary education exceeds 60%. It is also very high in the Czech Republic, France, Greece, Ireland, Italy,
Poland and Slovenia where at least half of 25-29 year-olds are NEET (Figure A2.4).
Attaining at least upper secondary education considerably reduces the risk of becoming NEET. The positive
impact of further education on the risk of becoming NEET is especially great in Austria, the Czech Republic,
Denmark, Germany, Lithuania, Luxembourg, the Slovak Republic, Slovenia, Sweden and Switzerland. In all
these countries, the share of NEETs among 25-29 year-olds with an upper secondary or post-secondary nontertiary education is about one-third the share among those with below upper secondary education (Figure A2.4).
In Greece, Italy, South Africa and Turkey the share of NEETs exceeds one in five young adults aged 25-29
regardless of the level of educational attainment. Nevertheless, even in these countries, education pays off and
the risk of becoming NEETs falls significantly with higher educational attainment (Figure A2.4).
EDUCATION AT A GLANCE 2019 © OECD 2019

A2. TRANSITION FROM EDUCATION TO WORK: WHERE ARE TODAY'S YOUTH?  57

Figure A2.4. Percentage of NEETs among 25-29 year-olds, by educational attainment (2018)

Note: NEET refers to young people neither employed nor in education or training.
1. Year of reference differs from 2018. Refer to Table A2.1 for more details.
Countries are ranked in descending order of the percentage of NEETs among tertiary-educated 25-29 year-olds.
Source: OECD (2019), Education at a Glance Database, http://stats.oecd.org. See Source section for more information and Annex 3 for notes
(https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933976631

Trends in the transition from education to work
In 2008, the year of the outbreak of the financial and economic crisis in many countries, the share of young adults
neither in education nor employed was one of the lowest during the first decade of the 21 st century. In 2008, on
average across OECD countries, 15.3% of 20-24 year-olds were NEET, while in the years following the crisis the
share of NEETs was much higher, reaching its peak in 2010/11 in many countries. Between 2010 and 2018, the
share of 20-24 year-olds not in education nor employed fell by about 4 percentage points on average across the
OECD, from 19.0% in 2010 to 15.3% in 2018, about the same level as a decade earlier (Table A2.2 and OECD
(2019[1])).
In most OECD countries, the share of NEETs among 20-24 year-olds is higher in 2018 than in 2008, but several
countries have been able to reduce the number of NEETs considerably. Among countries with comparable data
for both 2008 and 2018, the relative decrease was the largest in Hungary where the share of NEETs fell from
18.4% to 15.4% (i.e. decrease of 16%). A large change is also observed in the United States where the share of
NEETs fell by 14% (Table A2.2).
Over the last decade, the general trend of increased access to higher education among young adults has
continued (see Indicator B1). In Spain the share of 20-24 year-olds in education increased by 18 percentage
points from 34% in 2008 to 52% in 2018, the largest increase over this period. In Austria, the percentage of young
adults still in education increased by almost 10 percentage points between 2008 and 2018 (Table A2.2).
In most of countries, increased access to education has been accompanied by a decreasing share of young
adults in employment. Among OECD countries with comparable data between 2008 and 2018, the decrease over
this period is at least 10 percentage points in Austria, Norway, Portugal and Spain for 20-24 year-olds. In Spain,
the share of employed 20-24 year-olds not in education in 2018 is about 20 percentage points lower than in 2008,

EDUCATION AT A GLANCE 2019 © OECD 2019

58  A2. TRANSITION FROM EDUCATION TO WORK: WHERE ARE TODAY'S YOUTH?
while the share of the same age group in education is 18 percentage points higher. Some countries show the
opposite trend: in Hungary and New Zealand, the share of employed adults aged 20-24 not in education has
increased between 2008 and 2018 while the share of young adults in education has fallen over the same period
(Table A2.2).

Subnational variations in the percentage of young people who are NEET
The proportion of young people who are neither employed nor in education or training shows significant
subnational variation as well as national variation across the OECD. Across the regions of the OECD, the share
of 18-24 year-old NEETs can range from as low as 2.1% in one region in Japan, to as high as 48.1% in one
region in Turkey. The national averages can also mask the regions which have much lower or higher NEET rates,
often making them outliers within the country (OECD, 2019[6]).
In 18 OECD and partner countries, the subnational regions with the highest share of 18-24 year-old NEETs have
at least twice as high a rate as the regions with the lowest shares. Within countries, the ratio of highest to the
lowest share between regions reaches 12 in the Russian Federation, while in Spain there are about three times
as many NEETs in the region with the highest share (30.7%) than in the region with the lowest share (9.9%)
(OECD, 2019[6]).
In contrast, across the OECD and partner countries, regional differences in NEET rates are smallest in Denmark,
Slovenia and Sweden, where the difference between the regions with the highest and lowest shares is below
3 percentage points. Each of these countries has eight or fewer subnational regions. Finland, the Netherlands
and Norway also have a relatively narrow range of NEET rates, the difference is less than 4 percentage points
in the three countries (OECD, 2019[6]).
Income and job opportunities tend to be more concentrated in cities across the OECD (OECD, 2018[7]). However,
distinct trends can be observed in the relative proportions of NEETS in capital cities across OECD countries. In
many countries, such as Chile, the Czech Republic, Denmark and Finland the region with the capital city has the
lowest share of NEETS, while in Austria, Belgium and Germany, the capital city region has the highest NEET
rate in the country (OECD, 2019[6]).

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 AT A GLANCE 2019 © OECD 2019

A2. TRANSITION FROM EDUCATION TO WORK: WHERE ARE TODAY'S YOUTH?  59

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[8]) for
more information and Annex 3 for country-specific notes (https://doi.org/10.1787/f8d7880d-en).

Source
For information on the sources, see Indicator A1.
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
Eurofound (2017), Long term unemployed youth - Characteristics and policy responses,
https://www.eurofound.europa.eu/publications/report/2017/long-term-unemployed-youth.

[2]

Eurofound (2016), Exploring the diversity of NEETs, Publications Office of the European Union,
Luxembourg, http://dx.doi.org/10.2806/62307.

[5]

OECD (2019), Education at a Glance Database - Transition from education to work,
http://stats.oecd.org/Index.aspx?datasetcode=EAG_TRANS.

[1]

OECD (2019), Regional Statistics Database - Early leavers from education and NEET,
http://stats.oecd.org/Index.aspx?datasetcode= REGION_EDUCAT.

[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.

[8]

OECD (2018), OECD Regions and Cities at a Glance 2018, OECD Publishing, Paris,
https://dx.doi.org/10.1787/reg_cit_glance-2018-en.

[7]

OECD (2016), Society at a Glance 2016: OECD Social Indicators, OECD Publishing, Paris,
https://dx.doi.org/10.1787/9789264261488-en.

[4]

OECD (2015), OECD Skills Outlook 2015: Youth, Skills and Employability, OECD Publishing, Paris,
https://dx.doi.org/10.1787/9789264234178-en.

[3]

EDUCATION AT A GLANCE 2019 © OECD 2019

60  A2. TRANSITION FROM EDUCATION TO WORK: WHERE ARE TODAY'S YOUTH?

Indicator A2 Tables
Table A2.1

Percentage of 18-24 year-olds in education/not in education, by work status (2018)

Table A2.2

Trends in the percentage of young adults in education/not in education, employed or not, by
age group (2008 and 2018)

Table A2.3

Percentage of 18-24 year-olds in education/not in education, by work status and duration of
unemployment (2018)

Cut-off date for the data: 19 July 2019. 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.
StatLink: https://doi.org/10.1787/888933980811

EDUCATION AT A GLANCE 2019 © OECD 2019

A2. TRANSITION FROM EDUCATION TO WORK: WHERE ARE TODAY'S YOUTH?  61

Table A2.1. Percentage of 18-24 year-olds in education/not in education, by work status (2018)

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 are available at http://stats.oecd.org/, Education at a Glance Database.
1. Year of reference 2017.
Source: OECD (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888933976517

EDUCATION AT A GLANCE 2019 © OECD 2019

62  A2. TRANSITION FROM EDUCATION TO WORK: WHERE ARE TODAY'S YOUTH?
Table A2.2. Trends in the percentage of young adults in education/not in education, employed or not, by age group (2008 and 2018)

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 are available at http://stats.oecd.org/, Education at a Glance Database.
1. Year of reference 2017 instead of 2018.
2. Year of reference 2005 instead of 2008.
Source: OECD (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888933976536

EDUCATION AT A GLANCE 2019 © OECD 2019

A2. TRANSITION FROM EDUCATION TO WORK: WHERE ARE TODAY'S YOUTH?  63

Table A2.3. Percentage of 18-24 year-olds in education/not in education, by work status and duration of unemployment (2018)

Note: The data on duration of unemployment may not equal total unemployed numbers because of the presence of missing data.
1. Year of reference 2017.
Source: OECD (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888933976555

EDUCATION AT A GLANCE 2019 © OECD 2019

64  A3. HOW DOES EDUCATIONAL ATTAINMENT AFFECT PARTICIPATION IN THE LABOUR MARKET?

Indicator A3. How does educational attainment
affect participation in the labour market?
Highlights


The average employment rates of tertiary-educated adults in OECD countries can vary by up to
7 percentage points depending on their fields of study, while within fields of study, large variations in
employment rates can also be observed across countries.



Levels of long-term unemployment decrease with higher educational attainment in most OECD
countries. In most countries, the proportion of unemployed adults who have been unemployed for
12 months or more is smaller for tertiary-educated adults than for adults with lower levels of
educational attainment.



In the majority of OECD and partner countries, older tertiary-educated adults have higher employment
rates than younger tertiary-educated adults. On average across the OECD, the employment rate for
45-54 year-olds is 4 percentage points higher than for 25-34 year-olds, while in some countries the
difference is more than 10 percentage points.

Figure A3.1. Employment rates of tertiary-educated adults, by field of study (2018)
Percentage of employed 25-64 year-olds among all 25-64 year-olds

1. Year of reference differs from 2018. Refer to the source table for more details.
Fields of study are ranked in descending order of the employment rates for the OECD average.
Source: OECD (2019), Table A3.4. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933976745

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 higher qualifications

EDUCATION AT A GLANCE 2019 © OECD 2019

A3. HOW DOES EDUCATIONAL ATTAINMENT AFFECT PARTICIPATION IN THE LABOUR MARKET?  65

are more likely to find employment. 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 lower 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 labour-market outcomes can exacerbate inequalities in
society.
Education systems face challenges in responding to changing demands for skills in the labour market. While
the general pattern is for those with lower levels of education to have poorer labour-market prospects, in
certain industries the high demand for skilled workers can result in narrower differences in employment rates
across levels of education, if individuals have acquired the relevant skills. For example, given the technological
advances that have been transforming the needs of the global labour market, those with qualifications in
information and communication technologies (ICT), and those who are comfortable using ICT for problem
solving often have the best employment prospects. In some cases, strong ICT skills can completely
compensate for lower levels of educational attainment in the labour market (Lane and Conlon, 2016[2]).
Comparing labour-market indicators across countries can help governments to better understand global trends
and anticipate how economies may evolve in the coming years. In turn, these insights can inform the design
of education policies, which aim to ensure that the students of today can be well prepared for the labour market
of tomorrow.

Other findings


Employment rates of tertiary-educated adults with master's or equivalent qualifications are higher than
those with bachelor's or equivalent qualifications across most countries. Adults with doctoral
qualifications generally have the highest employment rates, although there are some exceptions.



Inactivity rates vary greatly across countries, and below-average employment rates also tend to
correlate with above-average inactivity rates across countries.



Among tertiary-educated adults, those who studied information and communication technologies (ICT)
have the highest average employment rate across the OECD, while the lowest rates are found among
those who studied arts and humanities, social sciences, journalism and information.



In almost all OECD countries, the unemployment rate for adults with tertiary education is as low as or
lower than the unemployment rate for adults with upper secondary or post-secondary non-tertiary
education.

EDUCATION AT A GLANCE 2019 © OECD 2019

66  A3. HOW DOES EDUCATIONAL ATTAINMENT AFFECT PARTICIPATION IN THE LABOUR MARKET?

Analysis
Educational attainment and employment
Across the OECD, upper secondary education is generally considered the minimum educational attainment level
for successful labour-market integration. Adults of all age groups without at least this level of education are
penalised in the labour market. On average across OECD countries, the employment rate of adults (aged 25-64)
is 85% for those with a tertiary qualification, 76% for those with an upper secondary or post-secondary
non-tertiary qualification, and 59% for those who have not completed upper secondary education (Table A3.1).
In all OECD and partner countries, younger adults (those aged 25-34) are better educated than their older peers
(see Indicator A1). Employment rates for young adults are similar to those for 25-64 year-olds; on average across
OECD countries, 84% of tertiary-educated younger adults are employed, as are 78% of those with upper
secondary or post-secondary non-tertiary education, and 60% of those without upper secondary education
(Table A3.2).
Despite being on average more highly educated as a group than young men (see Indicator A1), young women
at all levels of educational attainment have lower employment rates. Women aged 25-34 with below upper
secondary education have employment rates of 45% on average across the OECD, compared with 72% for men
of the same educational attainment and age. Among tertiary-educated young adults, the gap in favour of men
narrows to 8 percentage points (Table A3.2).
Across countries, there are substantial variations in employment rates by level of education. The highest
employment premiums for tertiary-educated adults over those with upper secondary or post-secondary
non-tertiary education are in Lithuania and Poland, where the difference between employment rates is more than
16 percentage points. Conversely, in the Czech Republic, Denmark, Estonia, Iceland, New Zealand, Portugal,
Sweden and the United Kingdom, the average employment premium for tertiary-educated adults is 5 percentage
points or less over those with upper secondary or post-secondary non-tertiary education (Table A3.1).
Smaller differences in employment rates for different levels of educational attainment may occur in a number of
different national contexts, for example in countries with labour-market shortages, or countries with a strong
emphasis on vocational education at the upper secondary or post-secondary non-tertiary levels. For example, in
Germany and Switzerland, the majority of vocational graduates participate in combined school- and work-based
programmes, which can smooth the transition from education to work (OECD, 2019[3]).

Educational attainment and unemployment rates by duration of unemployment
In many OECD and partner countries, unemployment rates are especially high among 25-34 year-olds. On
average across OECD countries, the unemployment rate is twice as high for younger adults who have not
completed upper secondary education: 14% compared to 7% for those with upper secondary or post-secondary
non-tertiary education. The unemployment rate for tertiary-educated younger adults is only 6% (Table A3.3).
Unemployment rates for younger adults without an upper secondary education are especially high in
the Slovak Republic and South Africa, where the unemployment rate in both cases exceeds 35%. It is also very
high in France, Greece, Italy and Spain, where about one-quarter of these younger adults are unemployed
(Table A3.3).
The positive impact of upper secondary or post-secondary non-tertiary education on the unemployment rate is
especially high in Australia, Austria, the Czech Republic, Germany, Hungary, the Slovak Republic and Sweden.
In all these countries, the unemployment rate for younger adults with an upper secondary or post-secondary nontertiary education is one-third or less of the unemployment rate for those with below upper secondary education
(Table A3.3).

EDUCATION AT A GLANCE 2019 © OECD 2019

A3. HOW DOES EDUCATIONAL ATTAINMENT AFFECT PARTICIPATION IN THE LABOUR MARKET?  67

Duration of unemployment tends to decrease with higher educational attainment. On average across the OECD,
29% of unemployed adults with tertiary education have been unemployed for 12 months or longer, compared to
36% of those with upper secondary or post-secondary non-tertiary education and 41% of those with below upper
secondary education. Tertiary-educated adults have a lower incidence of long-term unemployment than adults
with lower levels of educational attainment in all OECD and partner countries with data except Brazil, Canada,
Chile, Colombia, Costa Rica, Denmark, Israel, Mexico and Turkey (Figure A3.2 and Table A3.5).

Figure A3.2. Percentage of long-term unemployed 25-64 year-olds, by educational attainment (2018)
Adults who have been unemployed for 12 months or more as a percentage of unemployed 25-64 year-olds

Note: The percentage in parentheses represents the overall unemployment rate of 25-64 year-olds.
1. Year of reference differs from 2018. Refer to the source table for more 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 (13% of adults aged 25-64 are in this group).
Countries are ranked in descending order of the percentage of 25-64 year-olds with tertiary education who have been unemployed for 12 months or
more.
Source: OECD (2019), Table A3.5. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933976764

The share of tertiary-educated unemployed adults who have been unemployed for 12 months or more is over
40% in only 9 countries, rising to 18 countries for adults with an upper secondary or post-secondary non-tertiary
education, and 22 countries for adults with below upper secondary education. The long-term unemployment rates
for adults with below upper secondary education are highest in Belgium, Greece, Ireland, Italy, Portugal and
the Slovak Republic, where the rate in each case is at least 60%. However, while in Ireland the long-term
unemployment rate among adults with below upper secondary education is more than double the rate for those
with tertiary education, in Greece the difference is 5 percentage points lower for tertiary-educated adults
(Figure A3.2).

EDUCATION AT A GLANCE 2019 © OECD 2019

68  A3. HOW DOES EDUCATIONAL ATTAINMENT AFFECT PARTICIPATION IN THE LABOUR MARKET?
Educational attainment and inactivity
Across OECD countries, the percentage of inactive people (individuals who are not employed and not looking for
a job) tends to be higher among those with lower educational attainment levels. On average, 30% of adults
aged 25-34 who had not completed upper secondary education were inactive in 2018, compared to 16% of those
with upper secondary or post-secondary non-tertiary education and 11% of those with a tertiary degree
(Table A3.3).
Inactivity rates for tertiary-educated young adults are particularly high in Italy, where more than one in five are
inactive. In contrast, some countries combine the highest employment rates for tertiary-educated adults with the
lowest inactivity rates. In Iceland, Lithuania and the Netherlands, employment rates of over 90% for tertiaryeducated 25-34 year-olds are combined with inactivity rates of 6% or less for the same group (Figure A3.3).

Figure A3.3. Employment and inactivity rates of tertiary-educated 25-34 year-olds (2018)

1. Year of reference differs from 2018. Refer to the source table for more details.
2. Data for tertiary education include upper secondary or post-secondary non-tertiary programmes (less than 5% of adults are in this group).
Countries are ranked in descending order of the employment rate of tertiary-educated 25-34 year-olds.
Source: OECD (2019), Table A3.3. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933976783

Women have consistently higher inactivity rates than men across all educational attainment levels, but rates are
especially high among women who have not completed upper secondary education. On average across OECD
countries, almost half (46%) of younger women with below upper secondary education are inactive, compared to
less than one-fifth of younger men (18%). The gender gap in inactivity rates is highest in Mexico (56% of younger
women compared to 5% of younger men) and Turkey (69% compared to 6%). Portugal is the only country where
the gender gap in inactivity rates has been almost completely closed: among less-educated younger adults, the
inactivity rates are 17% for women and 9% for men. Portugal’s gender gap at higher educational attainment
levels is one of the lowest among OECD countries (OECD, 2019[3]).

EDUCATION AT A GLANCE 2019 © OECD 2019

A3. HOW DOES EDUCATIONAL ATTAINMENT AFFECT PARTICIPATION IN THE LABOUR MARKET?  69

Employment rates by age group
On average across OECD countries, a tertiary education improves employment rates for younger adults by
roughly 25 percentage points compared to their peers with below upper secondary education. However, in the
majority of OECD countries, younger adults with tertiary education have lower employment rates than
45-54 year-olds. In some countries, this could indicate that there are fewer opportunities for younger graduates,
while in others it could be related to the likelihood of adults in the younger age cohort still being in education (see
Indicator A2). The average difference in employment rates in favour of the older age group (45-54 year-olds) is
6 percentage points across OECD countries. However, in the Czech Republic, Greece, Italy, the Slovak Republic
and Slovenia, the employment rate for younger adults is more than 10 percentage points lower than the rate for
older adults (Figure A3.4 and Table A3.2).

Figure A3.4. Employment rates of younger and older tertiary-educated adults (2018)
25-34 year-olds and 45-54 year-olds

1. Year of reference differs from 2018. Refer to the source table for more details.
2. Data for tertiary education include upper secondary or post-secondary non-tertiary programmes (less than 5% of adults are in this group).
Countries are ranked in descending order of the employment rate of tertiary-educated 25-34 year-olds.
Source: OECD (2019), Table A3.3 and Education at a Glance Database, http://stats.oecd.org. See Source section for more information and Annex 3 for
notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933976802

Employment rates for 25-34 year-olds and 45-54 year-olds are the same or similar (a difference of less than
1 percentage point) in eight countries: Brazil, Canada, Japan, Ireland, Lithuania, the Netherlands,
the United Kingdom and the United States. In every other country, the gap in employment rates between the
younger and older adults is in favour of the older age group (Figure A3.4).

Employment rates by levels of tertiary education
In general, employment rates continue to increase with further levels of tertiary education attainment. On average
across OECD countries, the employment rate is 82% for adults with a short-cycle tertiary qualification, rising to

EDUCATION AT A GLANCE 2019 © OECD 2019

70  A3. HOW DOES EDUCATIONAL ATTAINMENT AFFECT PARTICIPATION IN THE LABOUR MARKET?
84% for those with a bachelor’s or equivalent degree, 88% with a master's or equivalent degree and 92% with a
doctoral or equivalent degree (Table A3.1).
In most countries, employment rates for adults with short-cycle tertiary education are lower than those with a
bachelor’s or equivalent degree. However, there are exceptions, including those countries where short-cycle
education is especially prevalent. For example, employment rates are relatively high among short-cycle tertiary
degree holders in Austria (87%, compared to 79% for bachelor’s or equivalent degree holders), where 15% of
25-34 year-olds have a short-cycle tertiary qualification (see Indicator A1). On the other hand, in Poland, the
share of those with short-cycle tertiary education is negligible, and they appear to face difficulties in finding a job
compared to younger adults with higher levels of tertiary education and even adults with upper secondary or
post-secondary non-tertiary education (Table A3.1).

Figure A3.5. Employment rates of tertiary-educated younger adults, by levels of tertiary education (2018)
25-34 year-olds

1. Data for tertiary education include upper secondary or post-secondary non-tertiary programmes (less than 5% of adults are in this group).
2. Year of reference differs from 2018. Refer to Table A3.1 for details.
Countries are ranked in descending order of the employment rate of tertiary-educated younger adults with a bachelor's or equivalent qualification.
Source: OECD (2019), Education at a Glance Database, http://stats.oecd.org. See Source section for more information and Annex 3 for notes
(https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933976821

Young adults with the most advanced qualifications (master’s and doctoral or equivalent) generally have the best
employment prospects. In most countries with available data, 25-34 year-old adults with a master’s or equivalent
qualification have employment rates at least as high as those with bachelor’s or equivalent. In some countries,
the employment advantage for the additional step of earning a master’s or equivalent qualification is considerable,
reaching at least 10 percentage points in Argentina, Chile, Luxembourg, the Slovak Republic and Turkey. Young
doctorate holders also have strong employment outcomes, with employment rates at 90% or higher in 16 of the
26 countries with available data (Figure A3.5).
Doctoral training requires a substantial investment from both individuals and governments, as the key entry point
into a career in academic research. Doctoral candidates also tend to specialise more heavily in many of the

EDUCATION AT A GLANCE 2019 © OECD 2019

A3. HOW DOES EDUCATIONAL ATTAINMENT AFFECT PARTICIPATION IN THE LABOUR MARKET?  71

science and technology-related fields of study in high demand in the labour market (see Indicator B7). Therefore,
there is growing policy interest in following the outcomes of doctorate holders in the labour market. New sources
of data about adults with a doctorate are becoming available, which can provide more detailed insights than
employment rates alone (Box A3.1).

Box A3.1. Profile and labour-market activities of doctorate holders
Doctorate holders tend to have diverse labour-market outcomes. As well as pursuing careers in academia,
their advanced skills are in demand in industry and other sectors of the economy. The evidence suggests that
many recent doctoral graduates are not able to easily find a stable career pathway in academia, and the
increasing tendency towards casualisation of teaching and research jobs in higher education may be
prompting those with a doctoral degree to seek career opportunities outside of academic research (OECD
(2019[4]) and see Indicator B7).

Figure A3.a. Share of doctorate holders employed in the education sector (2016)
As a percentage of all doctorate holders

Source: OECD data collection on Careers of Doctorate Holders (2017), https://www.oecd.org/innovation/inno/careers-of-doctorate-holders.htm.
Statlink2 https://doi.org/10.1787/888933976859

It can be difficult to compile comparative information on graduates from doctoral level programmes due to the
small numbers surveyed; doctorate holders make up only about 1% of the population on average across the
OECD (see Indicator A1). However, as the number of doctorate holders in the population expands, it is
becoming increasingly possible to identify and analyse the profile and outcomes of doctorate holders as a
separate group. The OECD data collection on the Careers of Doctorate Holders (CDH) was initiated in 2011
in order to improve the information available about the profile and career patterns of doctorate holders in the
population. The survey is conducted every two years in OECD member and partner countries. Returns are
made based on a range of national data collections, including specific surveys of doctorate holders, labourforce surveys and population registers (OECD, 2017[5]).

EDUCATION AT A GLANCE 2019 © OECD 2019

72  A3. HOW DOES EDUCATIONAL ATTAINMENT AFFECT PARTICIPATION IN THE LABOUR MARKET?
The results of the 2017 CDH collection demonstrate some of the differences in the profile and labour-market
status of doctorate holders across the 15 OECD and partner countries for which comparable data are
available. Figure A3.a shows the extent to which doctorate holders are employed in the education sector
across OECD countries. In Germany and Switzerland, only around 15% of doctorate holders work in the
higher education sector. This could indicate a lack of available opportunities for those with doctorates in
academia, or more attractive working conditions outside academia. In contrast, in Brazil close to 70% work in
the higher education sector.
The share of self-employed doctorate holders also varies importantly across OECD and partner countries with
data. The proportion is low in countries such as Portugal and the Russian Federation, where less than 5% of
doctorate holders are self-employed. On the other hand, in Germany the proportion of self-employed doctorate
holders is more than 25% (Figure A3.b).

Figure A3.b. Share of self-employed doctorate holders in the population, by gender (2016)

Source: OECD data collection on Careers of Doctorate Holders (2017), https://www.oecd.org/innovation/inno/careers-of-doctorate-holders.htm.
Statlink2 https://doi.org/10.1787/888933976878

In most countries, male doctorate holders have higher rates of self-employment than female ones, although
the proportions are close to equal in Canada, Finland, Portugal, Spain and the United Kingdom, while in Chile
a greater proportion of women are self-employed (Figure A3.b).
Many countries also appear to be able to create conditions that attract doctorate holders from abroad, or
successfully retain foreign doctoral candidates in the country after they have completed their programme. This
means that doctorate holders as a group tend to be more mobile and willing to move across borders to take
up both study opportunities and opportunities in the labour market. In Norway and Switzerland, for example,
around 40% of doctorate holders in the population are foreign citizens, while in Argentina, the Czech Republic,
Finland, Latvia and Portugal, the share is 5% or less (Figure A3.c and see Indicator B7).

EDUCATION AT A GLANCE 2019 © OECD 2019

A3. HOW DOES EDUCATIONAL ATTAINMENT AFFECT PARTICIPATION IN THE LABOUR MARKET?  73

Figure A3.c. Share of foreign-born and foreign citizen doctorate holders in the population (2016)

1: Data refer to 2015.
2: Data refer to 2014.
3: Data refer to 2013.
Source: OECD data collection on Careers of Doctorate Holders (2017), https://www.oecd.org/innovation/inno/careers-of-doctorate-holders.htm.
Statlink2 https://doi.org/10.1787/888933976897

Employment rates at tertiary level by field of study
While employment rates are higher for tertiary-educated adults across OECD countries, they can vary
considerably by field of study. On average across OECD countries, the overall employment rate of tertiaryeducated adults (25-64 year-olds) ranges from 83% for those with a qualification in arts and humanities, social
sciences, journalism and information to 90% for those with an ICT qualification (Figure A3.1 and Table A3.4).
Within individual countries, the largest differences between employment rates across fields of study are in
Costa Rica, Estonia, Greece, Italy, the Russian Federation and the Slovak Republic, where employment rates
among tertiary-educated adults vary by at least 15 percentage points, depending on the fields they studied. Other
countries have much smaller differences between fields. For example in Australia, Iceland and the Netherlands,
which have relatively high employment rates in general, the differences in employment rates between different
fields of study do not exceed 5 percentage points (Table A3.4).
Employment rates for adults with tertiary qualifications in the education, health and welfare fields of study also
vary substantially across countries. Labour-market prospects, expected salaries and the general perception of
the role of teachers in society are a few of the factors that might influence young people’s choice of education as
field of study (see Indicator B4). In Denmark, Iceland, Latvia, Lithuania and Sweden, employment rates are 90%
or above for those with a tertiary qualification in the field of education. Employment prospects are also strong for
those with a medical or dental qualification in many countries. This field has the highest employment rates of all
fields in Chile, Denmark, and Lithuania (Table A3.4).

Subnational variations in labour-market outcomes by educational attainment level
On average, across OECD and partner countries with subnational data on labour-force status, there is more
regional variation in employment rates among those with lower levels of education. For example, in
the United States, the employment rates in different states for adults with below upper secondary education range

EDUCATION AT A GLANCE 2019 © OECD 2019

74  A3. HOW DOES EDUCATIONAL ATTAINMENT AFFECT PARTICIPATION IN THE LABOUR MARKET?
from 30% to 70%, while among adults with tertiary education they range from 77% to 90%. Similarly, in Italy,
employment rates for adults who have not completed upper secondary education can more than double across
regions, ranging from 35% to 74%, while the range across regions for adults with tertiary education is around
25 percentage points, from 64% to 89% (OECD, 2019[6]).

Figure A3.6. Employment rates of tertiary-educated adults, by subnational regions (2018)
Percentage of employed 25-64 year-olds among all 25-64 year-olds

1. Year of reference 2017.
2. Year of reference 2016.
3. Year of reference 2015.
Countries are ranked in descending order of the national employment rates for tertiary-educated adults (unweighted average of regions).
Source: OECD INES/CFE Subnational Data Collection. See Source section for more information and Annex 3 for notes
(https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933976840

In many countries, there is very little regional variation in employment rates among adults with tertiary education.
In Hungary, Ireland, Latvia, the Netherlands, Portugal, Slovenia and Sweden, there is less than a 5% difference
in employment rates between different regions of the country. Other countries have a broader range of
employment rates among regions. The widest disparity can be observed in Estonia, where employment rates for
tertiary-educated adults can vary by almost 35 percentage points (from 57% to 92%). The other countries with
large regional differences in employment rates for tertiary-educated adults are Canada, Chile, Colombia, Greece,
Israel, Italy, the Russian Federation, Spain, Turkey and the United States. In each of these countries the
difference between the regions with the highest and lowest employment rates is at least 10 percentage points
(Figure A3.6 and (OECD, 2019[6])).
Capital city regions tend to have employment rates for tertiary-educated adults that are above the country
average. In Colombia, for example, 86% of tertiary-educated adults in the capital region are employed, compared
to the country average of 83%. In some other countries, the employment rate for the region including the capital
is at a similar level to the national average. However, across OECD countries, the capital city region is often not
the region with the highest employment rates for tertiary-educated adults. In Chile, for example, the capital city

EDUCATION AT A GLANCE 2019 © OECD 2019

A3. HOW DOES EDUCATIONAL ATTAINMENT AFFECT PARTICIPATION IN THE LABOUR MARKET?  75

region has an employment rate above the national average, but only the third highest employment rate overall
(Figure A3.6 and OECD (2019[6])).

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.
Fields of study are categorised according to the ISCED Fields of Education and Training (ISCED-F 2013). See
the Reader’s Guide for a full listing of the ISCED fields used in this report.
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.
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.

Methodology
For information on methodology, see Indicator A1.
Please see the OECD Handbook for Internationally Comparative Education Statistics (OECD, 2018[7]) for more
information and Annex 3 for country-specific notes (https://doi.org/10.1787/f8d7880d-en).

Source
For information on sources, see Indicator A1.
Data on subnational regions for selected indicators are available in the OECD Regional Statistics Database
(OECD, 2019[8]).
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
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 2019 © OECD 2019

76  A3. HOW DOES EDUCATIONAL ATTAINMENT AFFECT PARTICIPATION IN THE LABOUR MARKET?

References

Arntz, M., T. Gregory and U. Zierahn (2016), “The risk of automation for jobs in OECD countries: A
comparative analysis”, OECD Social, Employment and Migration Working Papers, No. 189, OECD
Publishing, Paris, http://dx.doi.org/10.1787/5jlz9h56dvq7-en.

[1]

Lane, M. and G. Conlon (2016), “The impact of literacy, numeracy and computer skills on earnings and
employment outcomes”, OECD Education Working Papers, No. 129, OECD Publishing, Paris,
http://dx.doi.org/10.1787/5jm2cv4t4gzs-en.

[2]

OECD (2019), Benchmarking Higher Education System Performance, Higher Education, OECD
Publishing, Paris, https://dx.doi.org/10.1787/be5514d7-en.

[4]

OECD (2019), Education at a Glance Database - Educational attainment and labour-force status,
http://stats.oecd.org/Index.aspx?datasetcode=EAG_NEAC.

[3]

OECD (2019), Regional Statistics Database - Educational attainment, by age group,
http://stats.oecd.org/Index.aspx?datasetcode= REGION_EDUCAT.

[8]

OECD (2019), Regional Statistics Database - Employment rate, by level of educational attainment and
age group, http://stats.oecd.org/Index.aspx?datasetcode= REGION_EDUCAT.

[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), OECD Science, Technology and Industry Scoreboard 2017: The Digital Transformation,
OECD Publishing, Paris, https://dx.doi.org/10.1787/9789264268821-en.

[5]

Indicator A3 Tables
Table A3.1

Employment rates of 25-64 year-olds, by educational attainment (2018)

Table A3.2

Trends in employment rates of 25-34 year-olds, by educational attainment and gender (2008
and 2018)

Table A3.3

Employment, unemployment and inactivity rates of 25-34 year-olds, by educational
attainment (2018)

Table A3.4

Employment rates of tertiary-educated adults, by field of study (2018)

Table A3.5

Unemployment rates of 25-64 year-olds, by duration of unemployment and educational
attainment (2018)

Cut-off date for the data: 19 July 2019. 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.
StatLink: https://doi.org/10.1787/888933980830
EDUCATION AT A GLANCE 2019 © OECD 2019

A3. HOW DOES EDUCATIONAL ATTAINMENT AFFECT PARTICIPATION IN THE LABOUR MARKET?  77

Table A3.1. Employment rates of 25-64 year-olds, by educational attainment (2018)
Percentage of employed 25-64 year-olds among all 25-64 year-olds

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 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 (13% of adults aged 25-64 are in this group).
4. Year of reference 2016.
Source: OECD / ILO (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888933976650

EDUCATION AT A GLANCE 2019 © OECD 2019

78  A3. HOW DOES EDUCATIONAL ATTAINMENT AFFECT PARTICIPATION IN THE LABOUR MARKET?
Table A3.2. Trends in employment rates of 25-34 year-olds, by educational attainment and gender (2008 and 2018)
Percentage of employed 25-34 year-olds among all 25-34 year-olds

Note: In most countries, there is a break in the time series, represented by the code "b", as data for 2018 refer to ISCED 2011 while data for 2008 years 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 2017 instead of 2018.
2. Data for tertiary education include upper secondary or post-secondary non-tertiary programmes (less than 5% of the adults are under 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 (13% of adults aged 25-64 are in this group).
Source: OECD / ILO (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888933976669

EDUCATION AT A GLANCE 2019 © OECD 2019

A3. HOW DOES EDUCATIONAL ATTAINMENT AFFECT PARTICIPATION IN THE LABOUR MARKET?  79

Table A3.3. Employment, unemployment and inactivity rates of 25-34 year-olds, by educational attainment (2018)
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

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 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 (13% of adults aged 25-64 are in this group).
Source: OECD / ILO (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888933976688

EDUCATION AT A GLANCE 2019 © OECD 2019

80  A3. HOW DOES EDUCATIONAL ATTAINMENT AFFECT PARTICIPATION IN THE LABOUR MARKET?
Table A3.4. Employment rates of tertiary-educated adults, by field of study (2018)
Percentage of employed 25-64 year-olds among all 25-64 year-olds

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. Year of reference 2017.
2. Year of reference 2016.
3. Data for tertiary education include upper secondary or post-secondary non-tertiary programmes (less than 5% of adults are in this group).
4. Data refer to bachelor’s degree field, even for those with additional tertiary degrees.
Source: OECD (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888933976707

EDUCATION AT A GLANCE 2019 © OECD 2019

A3. HOW DOES EDUCATIONAL ATTAINMENT AFFECT PARTICIPATION IN THE LABOUR MARKET?  81

Table A3.5. Unemployment rates of 25-64 year-olds, by duration of unemployment and educational attainment (2018)
Percentage of unemployed 25-64 year-olds among 25-64 year-olds in the labour force

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. Year of reference 2017.
2. Data for tertiary education include upper secondary or post-secondary non-tertiary programmes (less than 5% of the adults are under 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 (13% of adults aged 25-64 are in this group).
4. Year of reference 2016.
Source: OECD (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787888933976726

EDUCATION AT A GLANCE 2019 © OECD 2019

82  A4. WHAT ARE THE EARNINGS ADVANTAGES FROM EDUCATION?

Indicator A4. What are the earnings advantages
from education?
Highlights


On average across OECD countries, adults with a short-cycle tertiary degree earn 20% more than
adults with upper secondary education. The earnings advantage increases to 44% for those with a
bachelor’s degree and to 91% for those with a master’s or doctoral degree.



The gender gap in earnings persists across all levels of educational attainment, and the gap is wider
among tertiary-educated adults. Women earn less than men do even with a tertiary degree in the same
broad field of study.



The tertiary broad fields of study most often associated with the highest earnings are engineering,
manufacturing and construction, and information and communication technologies (ICT).

Figure A4.1. Relative earnings of tertiary-educated adults, by educational attainment (2017)
25-64 year-old workers (full- and part-time workers), upper secondary education = 100

1. Year of reference differs from 2017. Refer to the source table for details.
2. Earnings net of income tax.
3. Bachelor's or equivalent includes master's, doctoral or equivalent.
4. Index 100 refers to the combined ISCED levels 3 and 4 of the educational attainment levels in the ISCED 2011 classification.
5. Bachelor's, master's, doctoral or equivalent include short-cycle tertiary.
Countries are ranked in descending order of the relative earnings of 25-64 year-olds with a bachelor's or equivalent qualification.
Source: OECD (2019), Table A4.1. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933976992

EDUCATION AT A GLANCE 2019 © OECD 2019

A4. WHAT ARE THE EARNINGS ADVANTAGES FROM EDUCATION?  83

Context
Higher levels of education usually translate into better employment opportunities (see Indicator A3) and higher
earnings. The potential to earn more and see those earnings increase over time, along with other social
benefits, is an important incentive for individuals to pursue education and training.
In particular, the attainment of a tertiary degree is associated with higher earnings in all OECD countries.
However, this advantage can vary according to age, gender, level of tertiary education and field of study.
Individuals with higher qualifications and more experience are more likely to earn higher wages. However, in
many countries, gender gaps in earnings persist regardless of age, level of education or field of study.
A number of factors other than education also play a role in individuals’ earnings, including the demand for
skills in the labour market, the supply of workers and their skills, the minimum wage and other labour-market
laws, and structures and practices (such as the strength of labour unions, the coverage of collective-bargaining
agreements and the quality of working environments). These factors also contribute to differences in the
distribution of earnings.

Other findings


Across countries, the likelihood of earning more than the median increases with educational
attainment. On average across OECD countries, about 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
about one out of four adults without upper secondary education do so.



The earnings advantage for tertiary-educated workers increases with age. While young adults
(25-34 year-olds) with tertiary education earn nearly 40% more than their peers with upper secondary
education, older adults (45-54 year-olds) earn 70% more.



In most countries with available data, the gender gap in earnings is smaller for those with a degree in
education or ICT, and larger for those with a degree in business, administration and law.

Note
This indicator presents two types of relative earnings. The first uses the earnings of adults whose highest level
of educational attainment is upper secondary education as a baseline. The results reflect the difference in
earnings between adults with upper secondary education and those with different levels of attainment. The
second type, used to indicate gender disparities in earnings, uses men’s earnings as a baseline. In both cases,
given the focus on relative earnings, any increase or decrease in the results could reflect a change in the
interest group (numerator) or in the baseline group (denominator). For example, higher relative earnings for
tertiary-educated individuals may reflect higher earnings among tertiary-educated individuals and/or lower
earnings among those with upper secondary education.

EDUCATION AT A GLANCE 2019 © OECD 2019

84  A4. WHAT ARE THE EARNINGS ADVANTAGES FROM EDUCATION?

Analysis
Relative earnings, by educational attainment
Earnings tend to increase with the level of educational attainment. On average across OECD countries, adults
(aged 25-64) without upper secondary education earn about 21% less for part-time or full-time employment than
those with upper secondary education, while those with a tertiary degree earn about 57% more (Table A4.1).
Indeed, 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 highest in Chile, Colombia and Costa Rica, where
adults with a tertiary education earn over twice as much as those with upper secondary education. 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 may partially explain the large earnings advantage of tertiary-educated workers (OECD,
2017[1]).
The earnings advantage of tertiary-educated workers, however, varies considerably by level of tertiary
attainment. In most OECD member and partner countries, workers with a master’s or doctoral degree earn more
than those with a bachelor’s degree, who in turn earn more than those with a short-cycle tertiary degree. On
average across OECD countries, those with a short-cycle degree earn about 20% more than those with only an
upper secondary education. The earnings advantage increases to 44% for those with a bachelor’s degree and to
nearly 91% for those with a master’s or doctoral degree (Figure A4.1).
There are some important exceptions to this general pattern. In Estonia and Portugal, adults with a short-cycle
degree earn less than those with an upper secondary education. In Austria, the same is true for those with a
bachelor’s degree. In all three cases, however, these groups represent relatively small shares of the tertiaryeducated population. Moreover, unlike in most countries, the earnings of workers with a short-cycle tertiary
degree are higher than those of workers with a bachelor’s degree in Austria, Denmark, Finland and Norway. With
the exception of Denmark, these countries have among the highest short-cycle tertiary attainment rates, with at
least 10% of adults having attained this level (see Indicator A1).

Relative earnings of tertiary-educated workers, by age and through time
Higher educational attainment is associated with higher earnings throughout a person’s working life, and the
advantage is particularly large for older workers. On average across OECD countries, young adults (25-34 yearolds) with tertiary education earn nearly 40% more than their peers with upper secondary education. Older adults
(45-54 year-olds) earn 70% more. The earnings advantage increases with age in all OECD and partner countries,
although the size of the difference varies considerably, from over 70 percentage points in Chile, Colombia and
Ireland to less than 10 percentage points in Estonia, New Zealand and the United States (Figure A4.2).
A greater earnings advantage for older age groups could mean either that the earnings advantage increases with
experience or that the earnings advantage has fallen for younger generations (or a combination of both effects).
In the first case, age acts as a proxy for work experience and in the second case, age acts as a proxy for changes
over time. Although it is not possible to determine the main driving force in each country for the results shown in
Figure A4.2, it is possible to shed some light on the issue by analysing the trends in earnings advantages over
the past decade.
In most OECD countries, the earnings advantage of tertiary-educated workers has not changed considerably
between 2007 and 2017. In at least 20 OECD and partner countries, the difference in the earnings advantage of
adults with tertiary education has changed by less than 10 percentage points during the last decade, and in many
cases the difference is less than 5 percentage points. Although these results only cover one decade, they suggest
that in many OECD countries, the higher earnings advantage of older workers is mostly the result of a positive
relationship between relative earnings and work experience.

EDUCATION AT A GLANCE 2019 © OECD 2019

A4. WHAT ARE THE EARNINGS ADVANTAGES FROM EDUCATION?  85

A possible explanation for the increase in the earnings advantage of tertiary workers as they progress in their
careers is that people with higher levels of education are more likely to be and remain employed, and may have
more opportunities to gain experience on the job.

Figure A4.2. Relative earnings of tertiary-educated adults, by age group (2017)
25-34 year-old and 45-54 year-old workers (full- and part-time workers); upper secondary education = 100

1. Year of reference differs from 2017. Refer to the source table for details.
2. Earnings net of income tax.
3. Index 100 refers to the combined ISCED levels 3 and 4 of the educational attainment levels in the ISCED 2011 classification.
Countries are ranked in descending order of the relative earnings of 45-54 year-olds with tertiary education.
Source: OECD (2019), Education at a Glance Database, http://stats.oecd.org/. See Source section for more information and Annex 3 for notes
(https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933977011

Distribution of earnings relative to the median
A strongly skewed earnings distribution signals income inequality, which may affect the social cohesion of
communities and have a significant impact on economic growth. 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 the 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. The difference is even more striking when considering the share of adults earning
more than twice the median. Across OECD countries, an average of 23% of tertiary-educated workers earn more
than twice median earnings, compared to only 7% of those with upper secondary or post-secondary non-tertiary
education and 3% for those without upper secondary education (Table A4.2).
In some countries, the earnings distribution is more skewed than in others. In Chile, Costa Rica, Colombia,
Hungary, Mexico and Portugal, over 80% of tertiary-educated workers earn more than the median. Moreover, in
Costa Rica and Mexico about half of tertiary-educated workers earn more than twice median earnings. Indeed,

EDUCATION AT A GLANCE 2019 © OECD 2019

86  A4. WHAT ARE THE EARNINGS ADVANTAGES FROM EDUCATION?
countries with relatively high levels of income inequality also tend to be those with the highest share of the
population without tertiary or even upper secondary education (OECD, 2018[2]).
Among tertiary-educated workers, the distribution of earnings can vary considerably depending on the level of
tertiary education attained. In nearly all OECD countries, the share of adults earning more than twice the median
increases at each level from short-cycle tertiary, to bachelor’s and master’s or doctoral degrees. On average
across OECD countries, 11% of workers with a short-cycle tertiary degree earn more than twice the median. The
share increases to 19% among those with a bachelor’s degree and to 32% among those with a master’s or
doctoral degree (Figure A4.3).

Figure A4.3. Percentage of tertiary-educated adults earning more than twice the median, by level of
tertiary education (2017)
25-64 year-old workers (full- and part-time workers)

1. Year of reference differs from 2017. Refer to the source table for details.
2. Earnings net of income tax.
3. Bachelor's or equivalent includes master's, doctoral or equivalent.
4. Data refer to full-time, full-year earners only.
5. Bachelor’s, master’s, doctoral or equivalent include short-cycle tertiary.
Countries are ranked in descending order of the share of 25-64 year-olds with a bachelor's or equivalent qualification earning more than twice the median.
Source: OECD (2019), Education at a Glance Database, http://stats.oecd.org/. See Source section for more information and Annex 3 for notes
(https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933977030

Relative earnings of tertiary-educated adults, by field of study
The earnings advantage for tertiary-educated adults also varies by their field of study. Among the 14 OECD
countries with data available, the broad fields of study most commonly associated with the highest earnings are
engineering, manufacturing and construction (six countries) and ICT (four countries). On average across OECD
countries, only 14% of tertiary graduates in 2017 obtained a degree in engineering, manufacturing and
construction and 4% obtained a degree in ICT. Using higher earnings as a proxy for market demand, these
figures suggest a potential imbalance in some countries between the fields most in demand by the labour market
and the current supply of graduates. Indeed, this imbalance may help explain the high earnings premium for
these fields in some countries (see Box A1.1 in Indicator A1).
EDUCATION AT A GLANCE 2019 © OECD 2019

A4. WHAT ARE THE EARNINGS ADVANTAGES FROM EDUCATION?  87

In some countries, the difference in earnings advantages across fields is relatively small. This is the case in
Australia and Finland, where those with the highest-paying degree earn 30-40% more than those with the lowestpaying degree. In other countries, such as the United Kingdom and the United States, those with a degree in the
highest-paying field of study earn nearly twice what those with a degree in the lowest-paying field of study earn
(Table A4.4). Some of the differences in earnings across fields may be explained by different patterns of full-time
versus part-time employment.
In some countries, there are tertiary fields of study that are actually associated with an earnings disadvantage
when compared to adults with only upper secondary education. In the United Kingdom, for example, individuals
with a tertiary degree in the broad fields of education or arts and humanities, social sciences, journalism and
information earn less on average than adults who attained an upper secondary qualification. In the same country,
adults with a tertiary degree in engineering manufacturing and construction and natural sciences, mathematics
and statistics earn over 60% more than adults with upper secondary education (Figure A4.4).
Data from the few countries able to disaggregate earnings across narrower fields of study highlight the wide
discrepancies that may exist within a broad field. For example, within the broad field of health, those with a
medical or dental degree earn about twice as much as those with a degree in nursing or associated health field
in nearly every country with available data (Table A4.4).

Figure A4.4. Relative earnings of tertiary-educated adults, by field of study (2017)
25-64 year-old tertiary-educated workers (full- and part-time workers); upper secondary education (all fields) = 100

1. Data refer to the field of study at the bachelor's level.
2. Earnings net of income tax.
3. Earnings refer to academic programmes only.
4. Arts and humanities, social sciences, journalism and information does not include the subfield of Languages.
5. Year of reference differs from 2017. Refer to the source table for details.
Countries are ranked in descending order of the relative earnings of 25-64 year-olds with a tertiary degree in information and communication technologies.
Source: OECD (2019), Table A4.4. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933977049

EDUCATION AT A GLANCE 2019 © OECD 2019

88  A4. WHAT ARE THE EARNINGS ADVANTAGES FROM EDUCATION?
Differences in earnings between women and men, by educational attainment
Women do not earn as much as men in any OECD or partner country. Across OECD countries, tertiary-educated
women working full time earn only 75% of the earnings of tertiary-educated men. This 25% gap in the earnings
of tertiary-educated women is slightly larger than the gap for women with below upper secondary education and
for those with upper secondary or post-secondary non-tertiary education (both 22%) (Table A4.3).
As women are more likely to work part time than men, the gender gap in the average earnings of all workers
(including full-time and part-time earners) is even larger. On average across OECD countries, tertiary-educated
women in full-time or part-time work earn only 69% of the earnings of tertiary-educated men (OECD, 2019[3]).
The reasons for the gender gap in earnings include gender stereotyping, social conventions and discrimination
against women (OECD, 2017[4]), but also differences between men and women in their 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 ICT, while a larger share of women enrol in fields associated with lower
earnings, including education, and arts and humanities (see Indicator B4).
Nevertheless, Figure A4.5 highlights the fact that women earn less than men even with a degree in the same
field of study. Indeed, women’s earnings do not surpass men’s in any field of study with available data – although
some fields seem to have been more successful than others in reducing the gender pay gap. In most countries
with available data, the gender gap is smaller for the fields of education and ICT and larger for the field of
business, administration and the law when compared to the average gap across all fields of study. Additional
factors which help explain the gender gap in earnings within the same field of study could include employment in
different sectors within the field, career progression, types of occupation and types of contracts.

Figure A4.5. Women's earnings as a percentage of men's earnings, by field of study (2017)
25-64 year-old full-time tertiary-educated workers

1. Year of reference differs from 2017. Refer to the source table for details.
2. Earnings net of income tax.
3. Earnings by field refer to academic programmes only.
4. Earnings by field refer to the field of study at the bachelor’s level.
Countries are ranked in descending order of women's earnings (all tertiary) as a percentage of men's earnings.
Source: OECD (2019), Education at a Glance Database, http://stats.oecd.org/. See Source section for more information and Annex 3 for notes
(https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933977068

EDUCATION AT A GLANCE 2019 © OECD 2019

A4. WHAT ARE THE EARNINGS ADVANTAGES FROM EDUCATION?  89

In recent years, awareness of the differences in pay between men and women has risen. 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[4]). In most of the countries with available data, the gender gap between the earnings of tertiaryeducated men and women has narrowed between 2010 and 2017. On average across OECD countries with data
available for both years, the gap fell by about 1.5 percentage points, reaching just over 5 percentage points in
Austria, Estonia and Korea (OECD, 2019[3]).

Definitions
Adults refer to 25-64 year-olds.
Educational attainment refers to the highest level of education attained by a person.
Fields of study are categorised according to the ISCED Fields of Education and Training (ISCED-F 2013). See
the Reader’s Guide for a full listing of the ISCED fields used in this report.
Levels of education: See the Reader’s Guide at the beginning of this publication for a presentation of all ISCED
2011 levels.

Methodology
The analysis of relative earnings of the population with specific educational attainment and 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. The analysis of differences
in earnings between men and women include full-time workers only. For the definition of full-time earnings,
countries were asked whether they had applied a self-designated full-time status or a threshold value for 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, for example.
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[5]) for
more information and Annex 3 for country-specific notes (https://doi.org/10.1787/f8d7880d-en).

Source
The indicator is based on the data collection on education and earnings by the OECD Labour Market and Social
Outcomes of Learning Network (LSO Network). The data collection takes account of earnings for individuals
working full time and 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
EDUCATION AT A GLANCE 2019 © OECD 2019

90  A4. WHAT ARE THE EARNINGS ADVANTAGES FROM EDUCATION?
source for most countries is national household surveys such as Labour Force Surveys (LFS), the European
Union Statistics on Income and Living Conditions (EU-SILC) or other dedicated surveys collecting data on
earnings. About one-quarter of countries use data from tax or other registers. Please see Annex 3 for countryspecific notes on the national sources (https://doi.org/10.1787/f8d7880d-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
OECD (2019), Education at a Glance Database - Education and earnings,
http://stats.oecd.org/Index.aspx?datasetcode=EAG_EARNINGS.

[3]

OECD (2018), Education at a Glance 2018: OECD Indicators, OECD Publishing, Paris,
https://dx.doi.org/10.1787/eag-2018-en.

[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 (2017), Education at a Glance 2017: OECD Indicators, OECD Publishing, Paris,
http://dx.doi.org/10.1787/eag-2017-en.

[1]

OECD (2017), The Pursuit of Gender Equality: An Uphill Battle, OECD Publishing, Paris,
http://dx.doi.org/10.1787/9789264281318-en.

[4]

Indicator A4 Tables
Table A4.1

Relative earnings of workers, by educational attainment (2017)

Table A4.2

Level of earnings relative to median earnings, by educational attainment (2017)

Table A4.3

Differences in earnings between female and male full-time workers, by educational attainment
and age group (2017)

Table A4.4

Relative earnings of tertiary-educated adults, by field of study (2017)

Cut-off date for the data: 19 July 2019. 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.
StatLink: https://doi.org/10.1787/888933980849
EDUCATION AT A GLANCE 2019 © OECD 2019

A4. WHAT ARE THE EARNINGS ADVANTAGES FROM EDUCATION?  91

Table A4.1. Relative earnings of workers, by educational attainment (2017)
25-64 year-olds with income from employment (full- and part-time workers); upper secondary education = 100

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 2016.
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 2015.
4. Earnings net of income tax.
5. Year of reference 2014.
Source: OECD (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888933976916

EDUCATION AT A GLANCE 2019 © OECD 2019

92  A4. WHAT ARE THE EARNINGS ADVANTAGES FROM EDUCATION?
Table A4.2. Level of earnings relative to median earnings, by educational attainment (2017)
Median earnings from work for 25-64 year-olds with earnings (full- and part-time workers) for all levels of education

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 2016.
2. Earnings net of income tax.
3. Year of reference 2015.
4. Year of reference 2014.
5. Data refer to full-time, full-year earners only.
Source: OECD (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787888933976935

EDUCATION AT A GLANCE 2019 © OECD 2019

A4. WHAT ARE THE EARNINGS ADVANTAGES FROM EDUCATION?  93

Table A4.3. Differences in earnings between female and male full-time workers, by educational attainment and age group (2017)
Adults with income from employment (full-time workers), average annual earnings of women as a percentage of men's earnings

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 2016.
2. Year of reference 2015.
3. Earnings net of income tax.
4. Year of reference 2014.
Source: OECD (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888933976954

EDUCATION AT A GLANCE 2019 © OECD 2019

94  A4. WHAT ARE THE EARNINGS ADVANTAGES FROM EDUCATION?
Table A4.4. Relative earnings of tertiary-educated adults, by field of study (2017)
25-64 year-olds with income from employment (full- and part-time workers); upper secondary education (all fields) = 100

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 2016.
2. Earnings refer to academic programmes only.
3. Earnings net of income tax.
4. Arts and humanities, social sciences, journalism and information does not include the subfield of Languages.
5. Data refer to the field of study at the bachelor's level.
Source: OECD (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888933976973

EDUCATION AT A GLANCE 2019 © OECD 2019

96  A5. WHAT ARE THE FINANCIAL INCENTIVES TO INVEST IN EDUCATION?

Indicator A5. What are the financial incentives to
invest in education?
Highlights


Adults who complete tertiary education benefit from high returns on investment because they are more
likely to be employed and to earn more than adults without tertiary 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, for example through greater tax revenues
and social contributions.



Across OECD countries on average, a man invests around USD 45 100 (direct costs plus foregone
earnings) to earn a tertiary degree, while a woman invests around USD 34 800. Because men tend to
have higher earnings and employment rates, they also have higher total benefits over their career:
USD 341 000 for men, compared to USD 262 400 for women.

Figure A5.1. Private net financial returns for a man or a woman attaining tertiary education (2016)
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%

1. Results are based on the net earnings of tertiary-educated adults (as compared with the net earnings of adults with upper secondary education).
2. Year of reference differs from 2016. Refer to the source table for details.
Countries are ranked in descending order of private net financial returns for a man.
Source: OECD (2019), Tables A5.1a and A5.1b. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933977201

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

EDUCATION AT A GLANCE 2019 © OECD 2019

A5. WHAT ARE THE FINANCIAL INCENTIVES TO INVEST IN EDUCATION?  97

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 higher revenues from taxes and social
contributions 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 access to and completion of higher education (see Indicator B5).
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, and social outcomes, such as greater
participation in cultural or sport activities (see Indicator A6).

Other findings


In most OECD countries, the main cost of tertiary education is not direct payments, such as tuition
fees and living expenses, but the earnings individuals forego while they are in education. This is true
even when taking students’ earnings into account.



The private benefits from investing in education depend on countries’ tax and social contributions
systems. For instance, in Chile, Estonia and Korea, income taxes and social contributions amount to
less than one-quarter of the gross earnings benefits for a man attaining tertiary education, while in
Belgium and the Netherlands they add up to more than half of the gross earnings benefits.



For nearly all countries with available data, the private and public net financial returns from obtaining
a bachelor’s, master’s or doctoral degree are greater 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 rates 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 qualification; and 2) investing in upper
secondary education versus entering the labour market without an upper secondary qualification (available on
line).
It considers two types of investors: 1) the individuals (referred to here as “private”) who choose to pursue
higher levels of education and the additional net earnings and costs they can expect; and 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. The direct costs of 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 2019 © OECD 2019

98  A5. WHAT ARE THE FINANCIAL INCENTIVES TO INVEST IN EDUCATION?

Analysis
Financial incentives for individuals to invest in tertiary education
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 return from tertiary education for a man is USD 295 900.
Although young women tend to be more likely to complete higher education than young men (see Indicator A1),
they tend to receive lower relative net financial returns on investing in tertiary education than men. For a woman,
on average, the net financial return from tertiary education is USD 227 600, representing about three-quarters of
the return for a man (Figure A5.1).
The private financial returns from tertiary education are higher for men than for women in most OECD countries
with available data. The only countries where women have higher private financial returns than men are Belgium,
Latvia, the Netherlands, Norway, Spain and Turkey (Tables A5.1a and b). Women in these countries still faced
lower earnings and employment rates than men in 2016 (Education at a Glance Database), but they gain more
from attaining a tertiary degree, compared to only upper secondary education, than men do. This means that, in
these countries, the gap between earnings and employment by level of educational attainment is larger 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 greater 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.
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 an 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 17% for men and 21% 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 correspond to earnings from employment. To show the impact of the tax system on
total benefits, the income tax effect and social contributions effect are also analysed (see Definitions section).
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 of attaining tertiary education is
about USD 8 400. However, in most countries, the main costs are foregone earnings, i.e. the earnings individuals
could expect to receive if they 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 reducing their foregone earnings and the total cost of education. Indicator A6 in
Education at a Glance 2017 (OECD, 2017[1]) shows the prevalence of student employment and the level of
student earnings across OECD and partner countries.

EDUCATION AT A GLANCE 2019 © OECD 2019

A5. WHAT ARE THE FINANCIAL INCENTIVES TO INVEST IN EDUCATION?  99

Figure A5.2. Private costs and benefits of education for a man or a woman attaining tertiary education
(2016)
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%

1. Year of reference differs from 2016. Refer to the source table for details.
2. Results are based on the net earnings of tertiary-educated adults (as compared with the net earnings of adults with upper secondary education).
Countries are ranked in ascending order of total private benefits for a man.
Source: OECD (2019), Tables A5.1a and A5.1b. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933977220

Men’s foregone earnings while attaining tertiary education range from less than USD 10 000 in Israel and Turkey
to nearly USD 70 000 in Switzerland. When direct costs and foregone earnings are combined, Turkey has the
lowest total cost and Switzerland the highest of all OECD countries with available data. Men or women attaining
tertiary education in Switzerland can expect their total costs to be more than seven times higher than those in
Turkey (Tables A5.1a and b).
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

EDUCATION AT A GLANCE 2019 © OECD 2019

100  A5. WHAT ARE THE FINANCIAL INCENTIVES TO INVEST IN EDUCATION?
benefit for a tertiary-educated man is USD 341 000, while the total benefit for a tertiary-educated woman is
USD 262 400. This means that, over a career of 40 years, a tertiary-educated man will gain about USD 2 000
more per year in total benefits (compared to a man with only upper secondary education) than a tertiary-educated
woman. 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 course of an individual’s career, private benefits from
investing in education also depend on countries’ tax and social contributions systems (Brys and Torres, 2013[2]).
For instance, in Chile, Estonia and Korea, income taxes and social contributions amount to less than one-quarter
of the gross earnings benefits for a man attaining tertiary education, while in Belgium and the Netherlands they
add up to more than half of the gross earnings benefits. As women tend to have lower earnings, they often fall
into lower income tax brackets. For example, in 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 whether 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), investment
in education generates higher public returns, because tertiary-educated adults pay higher income taxes and
social contributions. On average across OECD countries, the public net financial returns for each individual
completing tertiary education are about USD 148 200 for a man and USD 77 300 for a woman (Figure A5.3).

Figure A5.3. Public net financial returns for a man or a woman attaining tertiary education (2016)
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%

1. Results are based on the net earnings of tertiary-educated adults (as compared with the net earnings of adults with upper secondary education).
2. Year of reference differs from 2016. Refer to the source table for details.
Countries are ranked in descending order of total public returns for a man.
Source: OECD (2019). Tables A5.2a and A5.2b. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933977239

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

EDUCATION AT A GLANCE 2019 © OECD 2019

A5. WHAT ARE THE FINANCIAL INCENTIVES TO INVEST IN EDUCATION?  101

largest returns (Figure A5.1 and Figure A5.3). This is the case in Ireland, Luxembourg and the United States,
countries with very large net financial private and public returns.
However, different tax systems can considerably affect whether public returns will follow private returns. Chile,
for example, has one of the highest private returns for a man attaining tertiary education, but the second-lowest
public returns because it collects a smaller share of individuals’ additional earnings in the form of taxes and social
contributions (Tables A5.1a and A5.2a).

The costs and benefits of tertiary education for governments
Public net financial returns are based on the difference between the costs and the 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 and
social contributions.
For governments, direct costs (including student grants) 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). The countries with high direct costs are also
the countries with the largest total public costs, reaching over USD 100 000 for men in Denmark, Luxembourg,
Norway and Switzerland. In contrast, Chile has the lowest total public cost (around USD 10 000 for men and
women) of all OECD countries. On average across OECD countries, the total public cost for an individual to attain
tertiary education is USD 58 100 for a man and USD 54 100 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 206 300 for a man with tertiary education
and USD 131 400 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. On average, the total public benefits of education for a man attaining tertiary education are about 57%
larger than the total public benefits for a tertiary-educated woman. Across OECD countries, Ireland, Luxembourg
and the Netherlands have the largest total public benefits of tertiary education for a man (above USD 400 000)
and Belgium, Luxembourg and the Netherlands have the largest benefit for a woman (above USD 250 000)
(Tables A5.2a and b).
The internal rate of return to governments is higher for a man attaining tertiary education (9%) than for a woman
(7%). 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 greater 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 206 300) for a tertiary-educated man can be broken down into income
tax effects (USD 148 100) and social contribution effects (USD 58 200). For a tertiary-educated woman, the total
public benefits (USD 131 400) can be broken down into USD 87 300 in income tax effects and USD 44 100 in
social contribution effects (Tables A5.2a and b).

Private and public costs and benefits by level of tertiary education
The returns for tertiary education can be broken down by level 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 tertiary education overall (Figure A5.4).

EDUCATION AT A GLANCE 2019 © OECD 2019

102  A5. WHAT ARE THE FINANCIAL INCENTIVES TO INVEST IN EDUCATION?
For nearly all countries with available data, the private and public net financial returns from obtaining a bachelor's,
master's, doctoral or equivalent degree are greater than from obtaining a short-cycle tertiary degree. Although
the total costs of a bachelor's, master's, doctoral or equivalent degree tend to be higher than those of a shortcycle tertiary degree, the total benefits accrued during individuals’ working lives compensate for the higher initial
costs (Tables A5.3a and b).
Turkey is the only country where both the private and public returns to a short-cycle tertiary degree are higher
than for a bachelor’s, master’s and doctoral degree for a man. Turkey is also the OECD country with the highest
share of first-time entrants to tertiary education in short-cycle tertiary programmes (48%) (see Indicator B4). The
public returns for a woman attaining short-cycle tertiary education are higher than for a bachelor’s, master’s and
doctoral degree in Denmark and Korea.

Figure A5.4. Private financial returns for a woman attaining a short-cycle tertiary degree or a bachelor's,
master's and doctoral or equivalent degree (2016)
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%

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 2016. Refer to the source table for details.
Countries are ranked in descending order of total private returns for a woman with a bachelor's, master's, doctoral or equivalent degree.
Source: OECD (2019). Table A5.3b. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933977258

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
cost-benefit 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

EDUCATION AT A GLANCE 2019 © OECD 2019

A5. WHAT ARE THE FINANCIAL INCENTIVES TO INVEST IN EDUCATION?  103

that education is not a risk-free investment, and that the discount rate should therefore be higher. The OECD
countries that perform similar cost-benefit analysis use higher discount rates than 2%, but the rate used varies
across countries (OECD, 2018[3]).

Table A5.a. Net financial returns for a man attaining tertiary education, by discount rate (2016)
As compared with a man attaining upper secondary education, in equivalent USD converted using PPPs for GDP

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 to the nearest hundred.
1. Year of reference 2015.
2. The probability of students having earnings refers to the employment rate from the LSO TRANS questionnaire instead of the share of earners
from the LSO Earnings questionnaire.
3. Results are based on the net earnings of tertiary-educated adults (as compared with the net earnings of adults with upper secondary education).
4. Year of reference 2014.
Source: OECD (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888933977277

EDUCATION AT A GLANCE 2019 © OECD 2019

104  A5. WHAT ARE THE FINANCIAL INCENTIVES TO INVEST IN EDUCATION?
In order to assess the size of the impact of the discount rate it is helpful to perform a sensitivity analysis. Table
A5.a shows how the private financial returns 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 at least 70%
in all countries. These comparisons highlight the sensitivity of the NPV results to changes in the discount rate.

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 of
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 not in education (a non-student) can expect, minus the
net earnings an individual can expect to receive while studying.
Foregone taxes are the additional tax revenues the government would have received if the individual had chosen
to enter the labour force as a non-student instead of pursuing 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.
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.

Methodology
This indicator estimates the financial returns on investment in education from the age of 15 to a theoretical
retirement age of 64. Returns to education are studied from the perspective of financial investment.
Two periods are considered(Diagram 1):
1. time spent in education during which the private individual and the government pay the cost of education

EDUCATION AT A GLANCE 2019 © OECD 2019

A5. WHAT ARE THE FINANCIAL INCENTIVES TO INVEST IN EDUCATION?  105

2. time spent after leaving formal education (or "not studying") 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 lifetime for a representative individual

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
the 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).

Change in methodology between Education at a Glance 2019 and Education at a Glance 2018
The current model focuses on earnings from employment. The unemployment benefits and social transfers,
reported in the 2018 edition, are not included in the 2019 edition. Compared to previous editions, the main
changes have been the use of the employment rate (instead of a ratio based on the active population) as the
probability for an individual to receive earnings and the introduction of actual students' earnings in the calculation
of foregone earnings. Please see the OECD Handbook for Internationally Comparative Education Statistics 2018
(OECD, 2018[4]) for more information and Annex 3 for country-specific notes (https://doi.org/10.1787/f8d7880den).

Source
The source for the direct costs of education is the UOE data collection on finance (year of reference 2016 unless
otherwise specified in the tables).
The data on gross earnings are based on the OECD Network on Labour Market and Social Outcomes earnings
data collection, which compiles data from national Labour Force Surveys, EU Statistics on Incomes and Living
Conditions, Structure of Earnings Surveys, and other national registers and surveys. Earnings are age-, genderand attainment-level specific. For the calculation of this indicator, data on earnings have been pooled from three
different years (2014-16).

EDUCATION AT A GLANCE 2019 © OECD 2019

106  A5. WHAT ARE THE FINANCIAL INCENTIVES TO INVEST IN EDUCATION?
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 2018 (OECD, 2018[5]).
Employee social contributions are computed using the OECD Taxing Wages model’s scenario of a single worker
aged 40 with no children. For country-specific details on employee social contributions in this model, see Taxing
Wages 2018 (OECD, 2018[5]).
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
Brys, B. and C. Torres (2013), “Effective personal tax rates on marginal skills investments in OECD
countries: A new methodology”, OECD Taxation Working Papers, No. 16, OECD Publishing, Paris,
http://dx.doi.org/10.1787/5k425747xbr6-en.

[2]

OECD (2018), Education at a Glance 2018: OECD Indicators, OECD Publishing, Paris,
https://dx.doi.org/10.1787/eag-2018-en.

[3]

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.

[4]

OECD (2018), Taxing Wages 2018, OECD Publishing, Paris, https://dx.doi.org/10.1787/tax_wages2018-en.

[5]

OECD (2017), Education at a Glance 2017: OECD Indicators, OECD Publishing, Paris,
http://dx.doi.org/10.1787/eag-2017-en.

[1]

Indicator A5 Tables
Table A5.1a

Private costs and benefits for a man attaining tertiary education (2016)

Table A5.1b

Private costs and benefits for a woman attaining tertiary education (2016)

Table A5.2a

Public costs and benefits for a man attaining tertiary education (2016)

Table A5.2b

Public costs and benefits for a woman attaining tertiary education (2016)

Table A5.3a

Private/public costs and benefits for a man attaining tertiary education, by level of tertiary
education (2016)

Table A5.3b

Private/public costs and benefits for a woman attaining tertiary education, by level of tertiary
education (2016)
EDUCATION AT A GLANCE 2019 © OECD 2019

A5. WHAT ARE THE FINANCIAL INCENTIVES TO INVEST IN EDUCATION?  107

WEB Table A5.4a Private costs and benefits for a man attaining upper secondary education (2016)
WEB Table A5.4b Private costs and benefits for a woman attaining upper secondary education (2016)
WEB Table A5.5a Public costs and benefits for a man attaining upper secondary education (2016)
WEB Table A5.5b Public costs and benefits for a woman attaining upper secondary education (2016)
Cut-off date for the data: 19 July 2019. 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.
StatLink: https://doi.org/10.1787/888933980868

EDUCATION AT A GLANCE 2019 © OECD 2019

108  A5. WHAT ARE THE FINANCIAL INCENTIVES TO INVEST IN EDUCATION?
Table A5.1a. Private costs and benefits for a man attaining tertiary education (2016)
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%

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 2015.
2. The probability of students having earnings refers to the employment rate from the LSO TRANS questionnaire instead of the share of earners from the LSO Earnings
questionnaire.
3. Results are based on the net earnings of tertiary-educated adults (as compared with the net earnings of adults with upper secondary education).
4. Year of reference 2014.
Source: OECD (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
StatLink 2 https://doi.org/10.1787/888933977087

EDUCATION AT A GLANCE 2019 © OECD 2019

A5. WHAT ARE THE FINANCIAL INCENTIVES TO INVEST IN EDUCATION?  109

Table A5.1b. Private costs and benefits for a woman attaining tertiary education (2016)
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%

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 2015.
2. The probability of students having earnings refers to the employment rate from the LSO TRANS questionnaire instead of the share of earners from the LSO Earnings
questionnaire.
3. Results are based on the net earnings of tertiary-educated adults (as compared with the net earnings of adults with upper secondary education).
4. Year of reference 2014.
Source: OECD (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
StatLink 2 https://doi.org/10.1787/888933977106

EDUCATION AT A GLANCE 2019 © OECD 2019

110  A5. WHAT ARE THE FINANCIAL INCENTIVES TO INVEST IN EDUCATION?
Table A5.2a. Public costs and benefits for a man attaining tertiary education (2016)
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%

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 2015.
2. The probability of students having earnings refers to the employment rate from the LSO TRANS questionnaire instead of the share of earners from the LSO Earnings
questionnaire.
3. Results are based on the net earnings of tertiary-educated adults (as compared with the net earnings of adults with upper secondary education).
4. Year of reference 2014.
Source: OECD (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.

StatLink 2 https://doi.org/10.1787/888933977125

EDUCATION AT A GLANCE 2019 © OECD 2019

A5. WHAT ARE THE FINANCIAL INCENTIVES TO INVEST IN EDUCATION?  111

Table A5.2b. Public costs and benefits for a woman attaining tertiary education (2016)
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%

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 2015.
2. The probability of students having earnings refers to the employment rate from the LSO TRANS questionnaire instead of the share of earners from the LSO Earnings
questionnaire.
3. Results are based on the net earnings of tertiary-educated adults (as compared with the net earnings of adults with upper secondary education).
4. Year of reference 2014.
Source: OECD (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.

StatLink 2 https://doi.org/10.1787/888933977144

EDUCATION AT A GLANCE 2019 © OECD 2019

112  A5. WHAT ARE THE FINANCIAL INCENTIVES TO INVEST IN EDUCATION?
Table A5.3a. Private/public costs and benefits for a man attaining tertiary education, by level of tertiary education (2016)
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%

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 2015.
2. The probability of students having earnings refers to the employment rate from the LSO TRANS questionnaire instead of the share of earners from the LSO Earnings
questionnaire.
3. Year of reference 2014.
Source: OECD (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.

StatLink 2 https://doi.org/10.1787/888933977163

EDUCATION AT A GLANCE 2019 © OECD 2019

A5. WHAT ARE THE FINANCIAL INCENTIVES TO INVEST IN EDUCATION?  113

Table A5.3b. Private/public costs and benefits for a woman attaining tertiary education, by level of tertiary education (2016)
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%

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 2015.
2. The probability of students having earnings refers to the employment rate from the LSO TRANS questionnaire instead of the share of earners from the LSO Earnings
questionnaire.
3. Year of reference 2014.
Source: OECD (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.

StatLink 2 https://doi.org/10.1787/888933977182

EDUCATION AT A GLANCE 2019 © OECD 2019

114  A6. HOW ARE SOCIAL OUTCOMES RELATED TO EDUCATION?

Indicator A6. How are social outcomes related to
education?
Highlights


Higher educational attainment is associated with greater social connectedness. The association is
particularly striking for participation in cultural or sporting activities where, on average across OECD
countries participating in the European Union Statistics on Income and Living Conditions (EU-SILC),
participation for adults with tertiary education is above 90%, compared to less than 60% for those with
below upper secondary education.



Work-life balance is an important dimension of well-being. However, in contrast to social
connectedness, higher educational attainment does not seem to be associated with a better
equilibrium. In about half of countries with data, the difference in work-life balance by educational
attainment is not statistically significant.



Education may be a catalyst that enhances the motivation to read books and conversely frequent
reading may raise educational aspirations. On average across OECD countries and economies
participating in the Survey of Adult Skills (PIAAC), the percentage of frequent readers increases with
each additional educational level of education.

Figure A6.1. Measures of social connections, by educational attainment (2015)
European Union Statistics on Income and Living Conditions (EU-SILC-2015), 25-64 year-olds, average

Note: Refer to the source table and Annex 3 for more information on the questions asked.
Social connection measures are ranked in descending order of the percentage of tertiary-educated 25-64 year-olds who responded positively to the
question.
Source: OECD (2019), Table A6.1. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2https://doi.org/10.1787/888933977353

EDUCATION AT A GLANCE 2019 © OECD 2019

A6. HOW ARE SOCIAL OUTCOMES RELATED TO EDUCATION?  115

Context
Promoting social cohesion, often reflected in levels of civic and social engagement, is a policy priority in OECD
countries. Evidence indicates that in general, levels of civic participation are inadequate, posing a challenge
for the maintenance and improvement of our societies. Education may play an important role in ensuring social
cohesion by fostering the social and emotional skills that can contribute to enhancing social connections and
protecting people from isolation. Adults’ social networks comprise their family, friends, colleagues and, more
widely, the community they live in. Social interactions are shaped by our social context and our household’s
socio-economic status, but when they complete further education people expand their social networks,
increase their participation in the labour force (see Indicator A3) and ultimately benefit from the advantages of
positive social inclusion, such as better health (VicHealth, 2010[1]).
Online social networks have been growing significantly in our societies and an increasing share of our personal
interactions take place on line. In 2019, Facebook had 2.38 billion monthly active users representing over 30%
of the estimated world population (Statista, 2019[2]; Worldometers, 2019[3]). The term “friend” has a different
meaning in the virtual world where face-to-face interaction is not a prerequisite for friendship and the digital
divide may prevent a share of the population from building this social capital, namely older and less educated
adults.
Work-life balance is a highly topical and relevant aspect of social well-being and quality of life. As a contributor
to job and family stress, excessive working hours are increasingly recognised as one of the major issues facing
many societies today. Work-life balance is a core dimension of OECD’s framework for measuring quality of
life in the Better Life Index (OECD, 2013[4]), and is part of the framework adopted for measuring education
and social outcomes in Education at a Glance (OECD, 2017[5]). It is therefore important to assess how
educational attainment is associated with this social outcome which is a key determinant of well-being and life
satisfaction.

Other findings


Social connection measures related to personal ties, such as having someone to ask for help and
getting together with friends, show a smaller gap by educational attainment than participation in cultural
and sporting activities, social media, and formal volunteering.



In most countries participating in the Survey of Adult Skills (PIAAC), there is a positive association
between the level of educational attainment and the ability to work more flexible hours.



Reading books infrequently is not always associated with a low literacy level. For example, in Japan
the frequency of book reading is low while literacy proficiency is the highest among countries and
economies participating in the Survey of Adult Skills (PIAAC).



Data from the Survey of Adults Skills (PIAAC) show that educational attainment can affect job
satisfaction through indirect effects. Even if in some cases educational attainment seems to have no
direct effect on job satisfaction, mediating variables such as job complexity, income and autonomy at
work may capture these indirect effects.

Note
The differences by educational attainment displayed in this indicator do not account for socio-economic status
and other moderating or mediating factors. The educational attainment gradient should therefore not be
interpreted as the effect of education on the social outcome measured.

EDUCATION AT A GLANCE 2019 © OECD 2019

116  A6. HOW ARE SOCIAL OUTCOMES RELATED TO EDUCATION?

Analysis
Social connections, by educational attainment
Participation in various social activities across OECD countries is higher on average for 25-64 year-olds who
attained tertiary education than for their lower-educated peers. However, the advantage in social connectedness
for individuals with higher education depends heavily on the type of activity measured. On average across OECD
countries participating in EU-SILC, participation in cultural and sporting activities, in social media, and in formal
volunteering is highly related to educational attainment. Over 90% of tertiary-educated adults participated in
cultural and sporting activities in the 12 months prior to the survey while less than 60% of adults with below upper
secondary education did so. This is the largest gap by educational attainment across the different domains of
social connection measured (Figure A6.1).
On average across OECD countries taking part in EU-SILC, almost 80% of adults reported participation in
sporting or cultural activities in the previous 12 months, with participation increasing with educational attainment
in all countries. In contrast, less than one-third of adults reported daily active participation in social media, and
one-quarter reported participating in formal voluntary activities in the 12 months prior to the survey. While there
is still a clear tendency for more participation in formal volunteering and social media among those with higher
levels of educational attainment, the percentage-point differences between attainment levels are smaller, which
may be partly explained by the generally lower participation in these activities. In contrast, measures related to
personal ties show very little difference by educational attainment; adults of all education levels were almost
equally likely to get together with friends on a weekly basis. Similarly, the range across educational levels in the
proportion of adults who have someone to ask for help (moral, material or financial) is less than 10 percentage
points on average (Figure A6.1 and Table A6.1).

Participation in any sporting or cultural activities in the last 12 months, by educational attainment
The pattern emerging from OECD countries participating in EU-SILC is that tertiary-educated 25-64 year-olds
are more likely to engage in sporting or cultural activities than their peers with lower educational attainment. On
average, roughly 90% of those with a tertiary education participated in at least one sporting or cultural activity in
the previous 12 months prior to the survey; the highest shares (98% and over) can be found in Finland, Iceland,
Norway and Switzerland. In contrast, less than 80% of tertiary-educated adults in Greece and Italy participated
in such activities. The participation rates of tertiary-educated adults in Greece and Italy are the same as or lower
than participation rates for adults with below upper secondary education in Denmark, Iceland, Netherlands,
Norway and Sweden. The gap in sporting or cultural engagement between those with a tertiary education and
those with an upper secondary or post-secondary non-tertiary education tends to widen when fewer
tertiary-educated adults participated in such activities. The difference reaches 36 percentage points in Poland,
33 in Hungary and 29 in Lithuania. Those without an upper secondary qualification are even less likely to
participate, with rates ranging from 89% in Iceland to 21% in Hungary. Iceland has the least variation in
participation by educational attainment, where the difference in participation between those with below upper
secondary education and those with tertiary education is only 9 percentage points, compared to a gap of
36 percentage points on average (Figure A6.2).

Getting together with friends at least once a week, by educational attainment
On average across OECD countries participating in EU-SILC, 25-64 year-olds with a tertiary education are more
likely to meet friends on a weekly basis than adults with a lower educational attainment, but the average difference
compared with those with an upper secondary or post-secondary non-tertiary education is only around
1 percentage point. The gap between tertiary-educated adults and those who have not completed upper
secondary education is similar. The Netherlands and the Slovak Republic were the two countries where
tertiary-educated adults were more likely to get together with friends at least once a week than those with an
upper secondary or post-secondary non-tertiary education, both with a difference of about 7 percentage points.

EDUCATION AT A GLANCE 2019 © OECD 2019

A6. HOW ARE SOCIAL OUTCOMES RELATED TO EDUCATION?  117

Elsewhere, the gap was below 5 percentage points except in Finland where the situation is reversed: 65% of
adults with upper secondary or post-secondary non-tertiary education reported getting together with friends at
least once a week compared to only 55% of tertiary-educated adults (Table A6.1).

Figure A6.2. Participation in cultural or sporting activities in the last 12 months, by educational
attainment (2015 or 2017)
European Union Statistics on Income and Living Conditions (EU-SILC-2015) and International Social Survey Programme
(ISSP-2017), 25-64 year-olds

Note: Refer to the source table and Annex 3 for more information on the questions asked in the two surveys.
1. The distribution of educational attainment varies by 10-15 percentage points compared to data published in Indicator A1.
Countries are ranked in descending order of the percentage of tertiary-educated 25-64 year-olds who participated in any cultural or sporting activities at
least once in the last 12 months.
Source: OECD (2019), Table A6.1. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2https://doi.org/10.1787/888933977372

Participation in formal voluntary activities, by educational attainment
Greater educational attainment is generally associated with participation in volunteering activities. Across OECD
countries participating in EU-SILC, however, participation in formal voluntary activities varies widely even for
people with the same educational level. The shares of tertiary-educated adults who volunteer span from 13% in
Hungary and Latvia to 59% in Norway. Shares fall a little among adults with an upper secondary or
post-secondary non-tertiary education, ranging from 5% in Hungary to 53% in Norway, while among adults
without upper secondary education the shares range from 3% in Hungary to 33% in Denmark and the
Netherlands. Volunteering thus appears more widespread in some countries than in others, but the percentagepoint difference between the tertiary-educated and upper secondary-educated adults averaged 7 percentage
points across OECD countries, similar to the 9 percentage-point gap on average between 25-64 year-olds who
completed upper secondary education and those who did not (Table A6.1).
The countries showing the largest participation gap between tertiary-educated adults and adults with upper
secondary or post-secondary non-tertiary qualification are Lithuania and the United Kingdom (15 percentage
EDUCATION AT A GLANCE 2019 © OECD 2019

118  A6. HOW ARE SOCIAL OUTCOMES RELATED TO EDUCATION?
points). In comparison, the difference between adults with upper secondary or post-secondary non-tertiary and
those without upper secondary education is over 15 percentage points in Austria, Luxembourg, Norway and
Switzerland (Table A6.1).

Having someone to ask for help, by educational attainment
This measure shows the least variation across educational levels. Regardless of their attainment, the great
majority of people in the countries surveyed can rely on a social network of some kind, as they mostly have
someone to ask for help. On average among OECD countries participating in EU-SILC, 97% of tertiary-educated
adults reported having someone to ask for help, falling to 95% among adults with upper secondary or
post-secondary non-tertiary education and to 90% among those who did not complete upper secondary
education. Generally, countries with a large percentage of tertiary-educated adults who have someone to ask for
help are also those where the shares for less highly educated adults are also relatively high. In
the Czech Republic, Finland, Norway and the Slovak Republic almost all tertiary-educated adults have someone
to ask for help and the difference for adults with upper secondary or post-secondary non-tertiary education
amounts to just 1 percentage point (Table A6.1).
The largest variation in access to someone to ask for help is found between those who have an upper secondary
or post-secondary non-tertiary education and those who do not. The difference amounts to at least 8 percentage
points in Belgium, Luxembourg, the Netherlands and Switzerland (Table A6.1).

Participation in social media, by educational attainment
On average across OECD countries participating in EU-SILC, 23% of adults with below upper secondary
education reported actively using social media on a daily basis. The share rises to 31% among adults with upper
secondary or post-secondary non-tertiary education and to 36% among tertiary-educated adults. The greatest
gap between adults with below upper secondary education and adults with tertiary education is seen in
the Slovak Republic where 8% of adults with below upper secondary education reported daily active participation
in social media, rising to 47% among tertiary-educated adults. A similar pattern is observed in Greece where the
gap is also over 30 percentage points. In contrast, in Norway there is almost no difference by educational
attainment, with 48% of adults with below upper secondary education reporting they actively participate in social
media on a daily basis. This is the highest share for this level of educational attainment across OECD countries
participating in EU-SILC and it is almost the same as the share among tertiary-educated adults in Norway (49%)
(Table A6.1).

Work-life balance, by educational attainment
Existing data and research suggest a possible negative association between educational attainment and work-life
balance, one that is moderated to a significant extent by other work-related, family-related or individual
characteristics (Statistics Canada, 2016[6]; Konishi and Dufour, 2016[7]; Tausig and Fenwick, 2001[8]). Work-life
balance is not traditionally included in school curricula which could explain why higher educational attainment is
not positively associated with this important social outcome. Higher educational attainment leads to higher
employment rates and higher earnings and is often associated with better health. It is also associated with greater
social connections, but there does not seem to be a strong link between educational attainment and the ability to
find a better equilibrium between their working life and their family life.
This section uses data from the European Quality of Life Survey (EQLS) and the International Social Survey
Programme (ISSP) to assess the difference by educational attainment in the level to which people report that
their work negatively interferes with their family life, and vice versa. It uses data from the Survey of Adult Skills
(PIAAC) to assess job flexibility and the mean number of hours worked per week in relation to educational
attainment. These two elements are not direct measures of people’s satisfaction with their work-life balance, but
they are important indicators to measure work intensity and how much time people have available outside work.

EDUCATION AT A GLANCE 2019 © OECD 2019

A6. HOW ARE SOCIAL OUTCOMES RELATED TO EDUCATION?  119

Work interferes with family life, by educational attainment
The results from the EQLS and ISSP show that the relationship between educational attainment and the impact
of work on family life goes in different directions in different OECD member and partner countries. In Chile, Iceland
and the Netherlands, the percentage of adults who report that their job negatively affects their family life rises
with each level of educational attainment. In contrast, in Turkey higher educational attainment is associated with
a smaller share of adults reporting a negative impact of work on family life. Furthermore, in about half of the
countries with data, there is no statistically significant difference between any level of educational attainment
measured. On average across the OECD countries that participated in the EQLS, 50% of adults with upper
secondary or post-secondary non-tertiary education reported that over the 12 months preceding the survey it has
been difficult for them to fulfil their family responsibilities because of the amount of time they spend at work,
compared with 51% of those with tertiary education (Figure A6.3).

Figure A6.3. Job has a negative impact on family life, by educational attainment (2015 or 2016)
European Quality of Life Survey (EQLS-2016) and International Social Survey Programme (ISSP-2015), percentage of
employed 25-64 year-olds who reported that their job negatively impacted their family life in the last 12 months

Note: Refer to the source table and Annex 3 for more information on the questions asked in the two surveys. Blue zone denotes statistically significant
differences between some or all educational attainment levels.
1. The distribution of educational attainment varies by 10-15 percentage points compared to data published in Indicator A1.
2. Year of reference 2016.
Countries are ranked in descending order of the percentage of tertiary-educated 25-64 year-olds who reported that their job negatively impacted their
family life in the last 12 months.
Source: OECD (2019), Table A6.2a. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2https://doi.org/10.1787/888933977391

As Figure A6.3 shows, the variation between countries for the same level of educational attainment are generally
more significant than the variation between levels of attainment within countries. This shows that, regardless of
educational attainment, there is a wide variation across OECD member and partner countries in the share of
adults who report that their job negatively affects their family life. For example, in Turkey, 88% of adults with
below upper secondary education reported that it has been difficult for them to fulfil their family responsibilities

EDUCATION AT A GLANCE 2019 © OECD 2019

120  A6. HOW ARE SOCIAL OUTCOMES RELATED TO EDUCATION?
because of the amount of time they spend at work while the share for similarly educated adults in the Netherlands
is 27%. By comparison, the largest difference by educational attainment within one country is in Belgium where
the gap reaches 23 percentage points between adults with below upper secondary education and adults with
upper secondary or post-secondary non-tertiary education (Figure A6.3).

Family life interferes with work, by educational attainment
Adults were less likely to report that their family life negatively affected their job than the other way around. Less
than half of adults reported that their family life interfered with their job in all OECD member and partner countries,
with a few notable exceptions. For example, in Turkey, 82% of adults with below upper secondary education
reported that, during the 12 months preceding the survey, they had several times experienced difficulty in
concentrating at work because of their family responsibilities. The share is lower among those who had completed
tertiary education (63%) but still higher than the share in any other OECD member or partner countries that
participated in the EQLS or ISSP (Table A6.2a).
The relationship between educational attainment and the share of adults reporting that their family life negatively
affects their job also goes in different directions across both OECD member and partner countries. The gap by
educational attainment is generally low; in more than half of the OECD countries with available data, the gap
between any level of educational attainment is 8 percentage points or less (Table A6.2a).

Figure A6.4. Job flexibility, by educational attainment (2012 or 2015)
Survey of Adult Skills (PIAAC), percentage of 25-64 year-olds who reported having a high or very high degree of flexibility
over working hours in their main job

Note: Blue zone denotes statistically significant differences between some or all educational attainment levels.
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 and economies are ranked in descending order of the percentage of tertiary-educated 25-64 year-olds who reported having a high or very high
degree of flexibility over working hours in their main job.
Source: OECD (2019), Table A6.2b. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2https://doi.org/10.1787/888933977410

EDUCATION AT A GLANCE 2019 © OECD 2019

A6. HOW ARE SOCIAL OUTCOMES RELATED TO EDUCATION?  121

Job flexibility and intensity, by educational attainment
One area related to work-life balance where educational attainment seems to have a greater impact and in a
more consistent direction, is job flexibility. Data from the Survey of Adult Skills (PIAAC) show that on average
across OECD countries and economies, 23% of adults with below upper secondary education reported that they
have a high or very high degree of flexibility over working hours in their main job. The proportion rises to 27% for
those with upper secondary or post-secondary non-tertiary and 33% for those with tertiary education. The gap is
particularly large in Austria, the Czech Republic, Germany, the Netherlands, the Slovak Republic and Slovenia
where the difference across the different levels of educational attainment is over 15 percentage points
(Figure A6.4).
Job intensity is another area that is related to work-life balance. This variable is also covered by the Survey of
Adult Skills (PIAAC) which asks adults to report the number of hours per week they usually work in their main
job. The average across OECD countries and economies ranges from 38 hours among adults with below upper
secondary education to 39 hours among adults with upper secondary or post-secondary non-tertiary education
and among adults with tertiary education, but this again masks results going in opposite directions. For example,
in Greece those with a tertiary qualification reported working 40 hours per week while those who did not complete
upper secondary education reported working 44 hours per week. In contrast, in Austria and Germany, those with
a tertiary qualification reported working 40 hours per week and those who did not complete upper secondary
education reported working 35 hours per week or less (Table A6.2b).

Box A6.1. Frequency of reading books and educational attainment (2012 or 2015)
There is a robust body of evidence that activities requiring focused attention, such as reading books, are
declining, while activities that encourage on multitasking, such as instant messaging, are increasing (Levine,
Waite and Bowman, 2007[9]). Poor academic performance can be predicted by higher levels of smartphone
use (Beland and Murphy, 2016[10]), media multitasking (Junco, 2012[11]; Levine, Waite and Bowman, 2007[9]),
social media networking (Junco, 2012[12]) and general electronic media usage (Jacobsen and Forste, 2011[13];
Junco and Cotten, 2012[14]). On the other hand, the evidence indicates a strong relationship between regularly
reading books and higher literacy skills (OECD, 2010[15]).
Reading is an important gateway to personal development, and to social, economic and civic life (Holden,
2004[16]). The main outcomes of "reading for pleasure or empowerment" reported by adults are enjoyment,
relaxation, empathy, knowledge, relatedness, community cohesion and increasing social capital (The Reading
Agency, 2015[17]).
Although the association between levels of education and reading books in everyday life is less established,
especially in international comparisons, the data collected by the Survey of Adult Skills (PIAAC) show its
existence and the strength of this association.
On average across participating OECD countries and economies, the percentage of frequent readers
increases with each additional educational level of education. Chile, the Czech Republic, the Netherlands,
Sweden and the Russian Federation are the only countries where no statistically significant differences were
found in the percentage of frequent readers between adults with below upper secondary education and adults
with upper secondary or post-secondary non-tertiary education. The difference between adults with upper
secondary or post-secondary non-tertiary education and adults with tertiary education is generally larger and
it is statistically significant in all participating countries and economies (Figure A6.a).
In most countries and economies, the relationship between frequency of reading and educational attainment
also remains strong in the employed population. Gender, age and literacy proficiency are among the important
factors associated with frequency of reading. Women read more than men in all countries and economies and
across all attainment levels. The relationship between age and frequency of reading differs across countries

EDUCATION AT A GLANCE 2019 © OECD 2019

122  A6. HOW ARE SOCIAL OUTCOMES RELATED TO EDUCATION?
and economies but the general trend shows a higher share of frequent readers among 45-64 year-olds than
among 25-44 year-olds (Table A6.a, available on line).

Figure A6.a. Adults who read books at least once a week, by educational attainment (2012 or 2015)
Survey of Adult Skills (PIAAC), 25-64 year-old non-students

Note: The value in parentheses represents the total percentage of adults who read books at least once a week, regardless of educational attainment.
All countries and economies have statistically significant differences between some or all educational attainment levels.
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 and economies are ranked in descending order of the percentage of adults with tertiary education who read books in everyday life at least
once a week.
Source: OECD (2019), Table A6.a, available on line. See Source section for more information and Annex 3 for notes
(https://doi.org/10.1787/f8d7880d-en).
Statlink2https://doi.org/10.1787/888933977429

Figure A6.b shows that the largest difference in literacy proficiency is between those who do not read books
in everyday life and those who do (at any frequency). On average across OECD countries and economies,
adults who reported never reading books in everyday life have a mean literacy score of 243. This score rises
to 269 for those who reported a frequency of less than once a month, 273 for those who reported a frequency
of less than once a week but at least once a month, and 277 for those who reported reading books in everyday
life at least once a week (Figure A6.b).
The evidence shows different associations in different countries and economies between frequency of reading
books and literacy proficiency. For example, in Chile and Turkey both variables are low. However, in Japan,
the frequency of book reading is low while literacy proficiency is the highest among participating countries and
economies. In contrast, England (United Kingdom) and New Zealand have the highest frequency of book
reading but literacy proficiency scores below that of Japan (Figure A6.a and Figure A6.b). Some countries
have policies to promote reading, for example, England (United Kingdom) and New Zealand have active
organisations that promote reading. Because of both low frequency of reading and low literacy proficiency,
Chile recently implemented a national programme to promote reading from the start of primary education
(I Read First programme).

EDUCATION AT A GLANCE 2019 © OECD 2019

A6. HOW ARE SOCIAL OUTCOMES RELATED TO EDUCATION?  123

Figure A6.b. Mean literacy proficiency score, by frequency of reading books (2012 or 2015)
Survey of Adult Skills (PIAAC), 25-64 year-old non-students

Note: The difference between the mean literacy proficiency score for adults who report never reading books and those who report reading books
less than once a month is statistically significant in all countries and economies, except in the Russian Federation.
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 and economies are ranked in descending order of the mean literacy score of those who reported that the frequency of reading books in
everyday life is "Never".
Source: OECD (2019). Table A6.b, available on line. See Source section for more information and Annex 3 for notes
(https://doi.org/10.1787/f8d7880d-en).
Statlink2https://doi.org/10.1787/888933977448

To conclude, those who are more educated tend to read frequently but this does not imply a causal
relationship between educational attainment and frequent reading in everyday life. However, what can be
assumed is a mutually reinforcing relationship between reading performance and the frequency of reading
(OECD, 2010[15]) and consequently a mutually reinforcing relationship between frequency of reading and
education. Reading books in everyday life for pleasure or empowerment is a matter of choice, and education
may be a catalyst that enhances the motivation to read while, conversely, frequent reading may raise
educational aspirations.

EDUCATION AT A GLANCE 2019 © OECD 2019

124  A6. HOW ARE SOCIAL OUTCOMES RELATED TO EDUCATION?

Box A6.2. Job satisfaction and structural equation modelling, by educational attainment (2012 or 2015)
Analysing the indirect impact of education
The causal effect of education on social outcomes is often analysed using regression analyses where
education is a predictor and the coefficient represents its impact on an outcome. This approach may not take
into account that education can also affect outcomes through mediating factors. With regards to job
satisfaction for instance, where previous research on the direct effects of education has provided inconclusive
results, estimating indirect effects may provide additional insight (Fabra and Camisón, 2009[18]).
The possible relevance of indirect relations between education and job satisfaction can be illustrated through
the development of a structural equation model, using data from the Survey of Adult Skills (PIAAC). In this
model, it is assumed that there is no direct effect of educational attainment on job satisfaction, but education
may have an indirect effect by affecting working and employment conditions, which in turn are related to job
satisfaction. Variables representing these conditions are job complexity, income, the frequency of exchanges
between colleagues (relatedness) and work autonomy. It is also assumed that single predictors of job
satisfaction are inter-related. Figure A6.c shows the resulting path diagram of the indirect effects of education
on job satisfaction, using New Zealand as an example. Arrows represent the effects of each variable. The
arrow numbers specify the standardised coefficients of these effects (Figure A6.c).

Figure A6.c. Model with indirect effects of education on job satisfaction for New Zealand (2015)
Survey of Adult Skills (PIAAC)

Note: For work autonomy three indicators were available, thus it was measured as a latent variable indicated by the freedom to determine the
sequence of task (I1), of the way it can be done (I2) and the freedom to determine the speed (I3). Education was measured by ISCED levels, job
complexity by frequency of complex problems at work, relatedness by frequency of learning exchange between staff, and income by percentile ranks.
The effects are standardised. *** indicates p=0.001, ** indicates p=0.05.
Source: OECD calculations using data from the Survey of Adult Skills (PIAAC). See Source section for more information and Annex 3 for notes
(https://doi.org/10.1787/f8d7880d-en).
Statlink2https://doi.org/10.1787/888933977467

EDUCATION AT A GLANCE 2019 © OECD 2019

A6. HOW ARE SOCIAL OUTCOMES RELATED TO EDUCATION?  125

Although there is no arrow from education to job satisfaction (no direct effect), it can be seen that there are
various indirect paths from education to job satisfaction via different variables. Among these variables,
different paths from education to job satisfaction are possible, with effects of different magnitude (Figure A6.c).
The consideration of indirect effects helps to better understand the pathways through which a variety of
working and employment conditions can influence job satisfaction. For example, in the model for
New Zealand, education has a greater influence on job complexity than on work autonomy, but work autonomy
in turn has a positive direct effect on job satisfaction, while job complexity does not. However, the analysis of
indirect effects in the model shows that in fact job complexity does have an indirect effect on work satisfaction
through its effect on income, work autonomy and relatedness (Figure A6.c).
The structural equation model allows the total effects to be calculated by considering all the direct and indirect
effects. Education and job satisfaction can therefore be related by taking into account the indirect effects.
Table A6.c displays the resulting total effects of the model variables in Korea, New Zealand and
the Slovak Republic. For these countries, education indirectly affects job satisfaction. However, the interrelations of the variables can differ in different countries, highlighting the importance of taking country contexts
into account when producing or reviewing evidence for making policy (Table A6.c).

Table A6.c. Total effects of variables on job satisfaction (2012 or 2015)
Survey of Adult Skills (PIAAC)
Variables

Slovak
Republic

Korea

New
Zealand

Income
Job complexity

0.07***
0.09***

0.11***
0.07***

0.06**
0.04**

Relatedness

0.15***

0.11***

0.19***

Work autonomy
Education

0.21***
0.11***

0.15***
0.10***

0.15***
0.05***

Note: There is no variance homogeneity of variables over countries. Thus standardised effects are not directly comparable over countries.
*** indicates p=0.001, ** indicates p=0.05.
Source: OECD calculations using data from the Survey of Adult Skills (PIAAC). See Source section for more information and Annex 3 for notes
(https://doi.org/10.1787/f8d7880d-en).

The results in Table A6.c show that education has a positive total effect on job satisfaction overall in the
countries examined. Considering indirect effects allows more options for modelling the relationships between
variables and can lead to different results than when only direct effects are analysed. The results show it is
important to determine precisely the impact of variables and consider indirect effects when developing related
policy measures, to avoid drawing incorrect conclusions about causal inter-relations.

Definitions
Age groups: Adults refer to 25-64 year-olds.
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):
Below upper secondary corresponds to ISCED-97 levels 0, 1, 2 and 3C short programmes; upper secondary

EDUCATION AT A GLANCE 2019 © OECD 2019

126  A6. HOW ARE SOCIAL OUTCOMES RELATED TO EDUCATION?
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
For the 2016 European Quality of Life Survey (EQLS) and the 2015 and 2017 International Social Survey
Programme (ISSP), 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:


ISSP 2017: Israel and the Russian Federation.



ISSP 2015: Chile, France, Israel, the Russian Federation and the United States.

See Annex 3 (https://doi.org/10.1787/f8d7880d-en) for more information on the discrepancies in the survey
sample distribution.

Source
Data from the EU-SILC 2015 module on social and cultural participation and material deprivation provided
evidence on social connections for European OECD member countries.
Data from ISSP 2017 provided evidence on social connections for non-European OECD member and partner
countries (ISSP Research Group, 2019[19]).
Data from EQLS provided evidence on work-life balance for European OECD member countries (Eurofound,
2018[20]).
Data from ISSP 2015 provided evidence on work-life balance for European OECD member countries and
non-European OECD member and partner countries (ISSP Research Group, 2017[21]).
Data from the OECD Programme for the International Assessment of Adult Competencies (the Survey of Adult
Skills [PIAAC]) provided evidence on job intensity and flexibility, frequency of book reading by educational
attainment, and job satisfaction by educational attainment.

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[22]).

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 2019 © OECD 2019

A6. HOW ARE SOCIAL OUTCOMES RELATED TO EDUCATION?  127

References
Beland, L. and R. Murphy (2016), “Ill Communication: Technology, distraction & student performance”,
Labour Economics, Vol. 41, pp. 61-76, http://dx.doi.org/10.1016/j.labeco.2016.04.004.

[10]

Eurofound (2018), European Quality of Life Survey Integrated Data File, 2003-2016, [data collection],
UK Data Service. SN: 7348,
https://discover.ukdataservice.ac.uk/catalogue/?sn=7348&type=Data%20catalogue.

[20]

Fabra, E. and C. Camisón (2009), “Direct and indirect effects of education on job satisfaction: A
structural equation model for the Spanish case”, Economics of education review, Vol. 28/5, pp. 600610.

[18]

Holden, J. (2004), Creative Reading : Young People, Reading and Public Libraries, Demos, London,
https://www.demos.co.uk/files/creativereading.pdf (accessed on 10 May 2019).

[16]

ISSP Research Group (2019), International Social Survey Programme: Social Relations and Social
Networks III - ISSP 2017. GESIS Data Archive, Cologne. ZA6980 Data file Version 1.0.0,
http://dx.doi.org/10.4232/1.13251.

[19]

ISSP Research Group (2017), International Social Survey Programme: Work Orientations IV - ISSP
2015. GESIS Data Archive, Cologne. ZA6770 Data file Version 2.1.0,
http://dx.doi.org/10.4232/1.12848.

[21]

Jacobsen, W. and R. Forste (2011), “The wired generation: Academic and social outcomes of
electronic media use among university students”, Cyberpsychology, Behavior, and Social
Networking, Vol. 14/5, pp. 275-280, http://dx.doi.org/10.1089/cyber.2010.0135.

[13]

Junco, R. (2012), “In-class multitasking and academic performance”, Computers in Human Behavior,
Vol. 28/6, pp. 2236-2243, http://dx.doi.org/10.1016/J.CHB.2012.06.031.

[11]

Junco, R. (2012), “Too much face and not enough books: The relationship between multiple indices of
Facebook use and academic performance”, Computers in Human Behavior, Vol. 28/1,
http://dx.doi.org/10.1016/j.chb.2011.08.026.

[12]

Junco, R. and S. Cotten (2012), “No A 4 U: The relationship between multitasking and academic
performance”, Computers & Education, Vol. 59/2, pp. 505-514,
http://dx.doi.org/10.1016/j.compedu.2011.12.023.

[14]

Konishi, M. and F. Dufour (2016), Work-life balance: A typology of workers,
https://www.europeansocialsurvey.org/docs/about/conference/KONISHI-DUFOUR_Work-lifebalance-a-Typology.pdf (accessed on 8 February 2019).

[7]

Levine, L., B. Waite and L. Bowman (2007), “Electronic media use, reading, and academic distractibility
in college youth”, CyberPsychology & Behavior, Vol. 10/4, pp. 560-566,
http://dx.doi.org/10.1089/cpb.2007.9990.

[9]

OECD (2017), Education at a Glance 2017: OECD Indicators, OECD Publishing, Paris,
https://dx.doi.org/10.1787/eag-2017-en.

[5]

OECD (2016), Technical Report of the Survey of Adult Skills (PIAAC), 2nd Edition, OECD, Paris,
http://www.oecd.org/skills/piaac/PIAAC_Technical_Report_2nd_Edition_Full_Report.pdf.

[22]

EDUCATION AT A GLANCE 2019 © OECD 2019

128  A6. HOW ARE SOCIAL OUTCOMES RELATED TO EDUCATION?
OECD (2013), How’s Life? 2013: Measuring Well-being, OECD Publishing, Paris,
https://dx.doi.org/10.1787/9789264201392-en.

[4]

OECD (2010), PISA 2009 Results: Learning to Learn: Student Engagement, Strategies and Practices
(Volume III), PISA, OECD Publishing, Paris, https://dx.doi.org/10.1787/9789264083943-en.

[15]

Statista (2019), Number of monthly active Facebook users worldwide as of 1st quarter 2019,
https://www.statista.com/statistics/264810/number-of-monthly-active-facebook-users-worldwide/
(accessed on 10 May 2019).

[2]

Statistics Canada (2016), Satisfaction with work-life balance: Fact sheet, Statistics Canada,
https://www150.statcan.gc.ca/n1/en/pub/89-652-x/89-652-x2016003-eng.pdf?st=Ukrvj8pE
(accessed on 8 February 2019).

[6]

Tausig, M. and R. Fenwick (2001), “Unbinding time: Alternate work schedules and work-life balance”,
Journal of Family and Economic Issues, Vol. 22/2,
http://www3.uakron.edu/publications/tausig%20Unbinding%20Time.pdf (accessed on
8 February 2019).

[8]

The Reading Agency (2015), Literature Review: The impact of reading for pleasure and empowerment,
BOP Consulting,
https://readingagency.org.uk/news/The%20Impact%20of%20Reading%20for%20Pleasure%20and
%20Empowerment.pdf (accessed on 10 May 2019).

[17]

VicHealth (2010), Opportunities for social connection, VicHealth,
http://www.vichealth.vic.gov.au/~/media/ResourceCentre/PublicationsandResources/Social%20con
nection/opportunities_for_Social_Connection_Summary_Nov10.ashx (accessed on 7 May 2019).

[1]

Worldometers (2019), World Population Clock: 7.7 Billion People (2019),
https://www.worldometers.info/world-population/ (accessed on 7 May 2019).

[3]

Indicator A6 Tables
Table A6.1

Social connections, by educational attainment (2015 or 2017)

Table A6.2a

Work-life balance, by educational attainment (2015 or 2016)

Table A6.2b

Job intensity and flexibility, by educational attainment (2012 or 2015)

WEB Table A6.a Adults who read books at least once a week, by labour-force status, gender, age and
educational attainment (2012 or 2015)
WEB Table A6.b Mean literacy proficiency score, by educational attainment and frequency of reading books
(2012 or 2015)
Cut-off date for the data: 19 July 2019. 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.
StatLink: https://doi.org/10.1787/888933980887
EDUCATION AT A GLANCE 2019 © OECD 2019

A6. HOW ARE SOCIAL OUTCOMES RELATED TO EDUCATION?  129

Table A6.1. Social connections, by educational attainment (2015 or 2017)
European Union Statistics on Income and Living Conditions (EU-SILC-2015) and International Social Survey Programme (ISSP-2017),
25-64 year-olds

Note: Additional columns showing data not disaggregated by level of educational attainment are available for consultation on line along with standard errors for data from
the International Social Survey Programme (ISSP-2017) (see StatLink below).
1. The distribution of educational attainment varies by 10-15 percentage points compared to data published in Indicator A1.
Source: OECD (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2https://doi.org/10.1787888933977296

EDUCATION AT A GLANCE 2019 © OECD 2019

130  A6. HOW ARE SOCIAL OUTCOMES RELATED TO EDUCATION?
Table A6.2a. Work-life balance, by educational attainment (2015 or 2016)
European Quality of Life Survey (EQLS-2016) and International Social Survey Programme (ISSP-2015), employed 25-64 year-olds

1. The distribution of educational attainment varies by 10-15 percentage points compared to data published in Indicator A1.
2. Year of reference 2016.
Source: OECD (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2https://doi.org/10.1787/888933977315

EDUCATION AT A GLANCE 2019 © OECD 2019

A6. HOW ARE SOCIAL OUTCOMES RELATED TO EDUCATION?  131

Table A6.2b. Job intensity and flexibility, by educational attainment (2012 or 2015)
Survey of Adult Skills (PIAAC), employed 25-64 year-olds

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.
Source: OECD (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2https://doi.org/10.1787/888933977334

EDUCATION AT A GLANCE 2019 © OECD 2019

132  A7. TO WHAT EXTENT DO ADULTS PARTICIPATE EQUALLY IN EDUCATION AND LEARNING?

Indicator A7. To what extent do adults
participate equally in education and learning?
Highlights


Learning begets learning. On average across OECD countries, the participation of adults in formal
and/or non-formal education and training is about 20 percentage points higher for those who
completed tertiary education than for those who completed upper secondary or post-secondary
non-tertiary education.



Participation in non-formal education and training is much higher than participation in formal education
and training. This holds true even for 25-34 year-olds: on average across the OECD countries taking
part in the Adult Education Survey (AES), 50% of younger adults were participating in non-formal
education and training while only about 16% were participating in formal education and training.



Participation in adult education and training is largely driven by employment. On average across the
OECD countries participating in the AES, 70% of the education and training activities followed by
tertiary-educated 25-64 year-olds participating in non-formal education and training were job-related
and sponsored by their employer.

Figure A7.1. Participation in formal and/or non-formal education, by educational attainment (2016)
Adult Education Survey (AES), Survey of Adult Skills (PIAAC) or national surveys, 25-64 year-olds

1. Some categories might need to be interpreted with caution. Refer to the source table for more details.
2. Year of reference differs from 2016. Refer to the source table for more details.
* 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 participating in formal and/or non-formal education.
Source: OECD (2019), Table A7.1. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933977543

EDUCATION AT A GLANCE 2019 © OECD 2019

A7. TO WHAT EXTENT DO ADULTS PARTICIPATE EQUALLY IN EDUCATION AND LEARNING?  133

Context
Adult learning can play an important role in helping adults to develop and maintain key information-processing
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]).
Adult learning can also contribute to non-economic goals, such as personal fulfilment, improved health, civic
participation and social inclusion. However, the wide 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 adult education systems (Borkowsky,
2013[2]).

Other findings


Across all OECD countries taking part in the AES, participation in formal and/or non-formal education
and training increases with each additional level of formal educational attainment.



Distance learning is an increasingly common form of participation in adult learning. Across OECD
countries and economies participating in the Survey of Adult Skills (PIAAC), 20% of the adults who
reported participating in non-formal education and training were doing so through distance learning.



Across OECD countries, most adults enrolled in formal education are attending a tertiary programme.
However, in Australia, Belgium, Mexico and Sweden, less than half of adults participating in formal
education were enrolled in tertiary programmes.

EDUCATION AT A GLANCE 2019 © OECD 2019

134  A7. TO WHAT EXTENT DO ADULTS PARTICIPATE EQUALLY IN EDUCATION AND LEARNING?

Analysis
Participation in formal and/or non-formal education and training by gender, age group and
educational attainment
On average across OECD countries taking part in the Adult Education Survey (AES), 47% of 25-64 year-olds
had participated in formal and/or non-formal education and training in the 12 months preceding the survey. In
Greece and Turkey, less than 25% of adults were participating, while this rate reaches 60% and above in Austria,
the Netherlands, Norway, Sweden and Switzerland (Table A7.1).
Figure A7.1 shows that adults with higher educational attainment are more likely to participate in formal and/or
non-formal education and training activities. On average across OECD countries taking part in the AES, 26% of
25-64 year-olds with below upper secondary education had participated in formal and/or non-formal education
and training in the 12 months preceding the survey. This rate increases to 44% for those with upper secondary
or post-secondary non-tertiary education and reaches 66% for those with a tertiary education. Participation
across countries varies greatly even among tertiary-educated adults: the rates range from 31% in Greece to
86% in Switzerland. The difference in participation between those with a tertiary degree and those with below
upper secondary education is over 25 percentage points in all OECD countries participating in AES, and reaches
50 percentage points or more in the Czech Republic, Italy, Slovenia and Switzerland (Figure A7.1).
Completing upper secondary or post-secondary non-tertiary education is also associated with big differences in
participation rates: participation is at least 25 percentage points higher in Austria, the Czech Republic, Italy,
the Netherlands, Portugal, Slovenia and Switzerland among adults educated to this level compared to those who
did not complete upper secondary education. In contrast, Denmark, Estonia, Finland, Greece, Hungary, Latvia,
Norway, Poland and Sweden have the smallest gap, with 15 percentage points difference or less (Figure A7.1).
In most countries, the participation rates for women and men vary by less than 5 percentage points. The gender
gap exceeds 10 percentage points only in Estonia and Finland; in both countries women participate more than
men do. In Turkey, the gender gap is reversed and particularly large considering the country’s generally low
participation in adult learning: 17% of women and 25% of men had taken part in formal and/or non-formal
education and training (Table A7.1).
In all countries participating in AES, younger adults (25-34 year-olds) are more likely to participate in formal
and/or non-formal education and training than older age groups (35-44, 45-54 and 55-64 year-olds). On average
across OECD countries taking part in the AES, 57% of 25-34 year-olds were taking part in formal and/or nonformal education and training, 52% of 35-44 year-olds, 46% of 45-54 year-olds and 33% of 55-64 year-olds. The
participation gap between age groups is highest in Finland where the rates are 68% for 25-34 year-olds and 34%
for 55-64 year-olds. In contrast, the gap is the lowest in Germany where 57% of younger adults were taking part
in formal and/or non-formal education and training compared to 44% among older adults (Table A7.1).

Comparison of participation in formal and non-formal education and training
Participation in non-formal education and training surpasses participation in formal education and training among
all age groups. This is true in all countries, even among 25-34 year-olds, the age group with the highest
participation in formal education and training. On average across OECD countries taking part in the AES, 16% of
25-34 year-olds were taking part in formal education and training while 50% were taking part in non-formal
education and training. In Greece, Poland and Turkey, participation in both formal and non-formal education and
training is below 30%. In contrast, the rates are above 30% for both types of adult learning programmes in
Denmark and Finland. In Denmark, the data suggest that a significant share of younger adults who were taking
part in non-formal education and training were also taking part in formal education and training (Figure A7.2).

EDUCATION AT A GLANCE 2019 © OECD 2019

A7. TO WHAT EXTENT DO ADULTS PARTICIPATE EQUALLY IN EDUCATION AND LEARNING?  135

Figure A7.2. Participation of 25-34 year-olds in education and training, by formal/non-formal status (2016)
Adult Education Survey (AES), Survey of Adult Skills (PIAAC) or national surveys

1. Some categories might need to be interpreted with caution. Refer to the source table for more details.
2. Year of reference differs from 2016. Refer to the source table for more details.
* See note on data for the Russian Federation in the Source section.
Countries are ranked in descending order of the percentage of 25-34 year-olds participating in formal and/or non-formal education.
Source: OECD (2019), Table A7.1. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933977562

Participation in non-formal education (job-related and non-job related)
Figure A7.3 shows that education and training sponsored by the employer makes up the largest share of activities
among tertiary-educated adults participating in non-formal education. This is true for all countries except Greece,
where the commonest form of non-formal education was job-related education not sponsored by the employer.
Non-job-related education is less common than job-related education in all countries, but represents 20% or more
of the programmes undertaken by adults in Austria, France, Italy, Luxembourg, Slovenia and Switzerland. This
shows that participation in non-formal adult education is most commonly linked to a current job or to improve
skills for a future job and is rarely strictly for leisure (Table A7.2a).
The share of not job-related non-formal education and training activities increases for participants with below
upper secondary education. This can be partly explained by the lower employment rates for adults with lower
levels of education (see Indicator A3) and therefore their lower exposure to job-related training opportunities.
This is an important consideration as participation in adult learning among those who are not employed is key to
them increasing their human capital and reintegrating into the labour market (Table A7.2a).

Distance learning and non-formal education
Non-formal education activities can take place in many different settings, including seminars, private lessons,
on-the-job training and distance learning courses (OECD, 2014[3]). The growth in participation in education has
led to increased demand for more flexible learning options, and as a result distance learning (particularly online
EDUCATION AT A GLANCE 2019 © OECD 2019

136  A7. TO WHAT EXTENT DO ADULTS PARTICIPATE EQUALLY IN EDUCATION AND LEARNING?
learning) has become mainstream (Kentnor, 2015[4]). Distance learning is also a feature of non-formal education;
on average across OECD countries, 20% of all adults who reported participating in non-formal education and
training in the Survey of Adult Skills did so through distance learning. The largest shares of adults participating
in non-formal distance learning are in Lithuania and Poland, where more than 45% of adults participating in
non-formal education took part in distance learning. On the other hand, just 9% of adults in Norway and Slovenia
participating in non-formal learning did so by distance learning (Figure A7.4 and Table A7.2c, available on line).

Figure A7.3. Distribution of job-related and employer sponsorship education and training activities
among tertiary-educated adults participating in non-formal education (2016)
Adult Education Survey (AES), Survey of Adult Skills (PIAAC), 25-64 year-olds

1. Some categories might need to be interpreted with caution. Refer to the source table for more details.
2. Year of reference differs from 2016. Refer to the source table for more details.
* 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 participating in non-formal job-related education
sponsored by their employer.
Source: OECD (2019), Table A7.2a. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933977581

Differences are also evident in distance-learning patterns across attainment levels in OECD countries. In the
majority of countries, among adults who participate in non-formal education, those who have attained tertiary
education are more likely to participate through distance learning than adults with below upper secondary
education. This mirrors the greater tendency for adults with tertiary education to participate in non-formal
education (Figure A7.1). The differences are particularly large in Korea, where the share of adults with tertiary
education participating in non-formal distance learning is 40 percentage points higher than the share of adults
with below upper secondary education. Conversely, in Austria, Germany, Japan, the Netherlands, New Zealand,
Norway and Turkey, the difference is less than 5 percentage points across education levels (Figure A7.4 and
Table A7.2c, available on line).

EDUCATION AT A GLANCE 2019 © OECD 2019

A7. TO WHAT EXTENT DO ADULTS PARTICIPATE EQUALLY IN EDUCATION AND LEARNING?  137

Figure A7.4. Distance learning rates among adults participating in non-formal education and training
(2012 or 2015)
Survey of Adult Skills (PIAAC), 25-64 year-olds

Note: Grey zone denotes statistically significant differences between below upper secondary and tertiary education.
1. Reference year is 2015; for all other countries and economies the reference year is 2012.
Countries and economies are ranked in descending order of the distance learning participation rate among tertiary-educated adults participating in nonformal education.
Source: OECD (2019). Table A7.2c, available on line only. See Source section for more information and Annex 3 for notes
(https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933977600

On average across the OECD, there is little difference in participation in non-formal distance learning by gender
(19% for men and 21% for women). However, the gender differences are more substantial in a small number of
countries; in Poland, the share of men participating in non-formal distance learning was 57%, which was
21 percentage points higher than the share of participating women. The share of men participating in non-formal
distance education was also 10 percentage points higher than the share of women in Lithuania and Turkey
(Table A7.2c, available on line).

Enrolment in different levels of formal education by age group
The share of adults enrolled in formal education decreases with age, but the distribution of educational levels
they are enrolled in remains somewhat similar across the different age groups. On average across OECD
countries, 16% of 25-29 year-olds are participating in formal education, 7% of 30-39 year-olds and only 2% of
40-64 year-olds. Across all three age groups, tertiary education is the most common but its share decreases
slightly with age: from 79% among 25-29 year-olds, to 72% among 30-39 year-olds and 65% among 40-64 yearolds (Table A7.3).
Across OECD countries, enrolment in formal education among 30-39 year-olds ranges from 2% in France, Korea,
Luxembourg and the Slovak Republic to over 15% in Australia, Finland and Sweden. The level of education also
shows some substantial differences among countries for this age group. In most countries, tertiary education
remains the most important level, indicating the high demand for tertiary education in the labour market. However,
in Australia, Belgium, Mexico and Sweden, less than half of participants are enrolled in tertiary programmes. In
Australia, Belgium and Finland at least 40% of 30-39 year-olds who are enrolled in formal education are in upper
EDUCATION AT A GLANCE 2019 © OECD 2019

138  A7. TO WHAT EXTENT DO ADULTS PARTICIPATE EQUALLY IN EDUCATION AND LEARNING?
secondary or post-secondary non-tertiary programmes while in Mexico about half of participants are enrolled in
below upper secondary education (Figure A7.5 and Table A7.3).
The high enrolment rate of 30-39 year-olds in formal education in Sweden is in line with the national effort to
make adult education accessible. Formal adult education, organised at the municipal level, is deep-rooted in
Sweden. Its aim is to provide basic adult education for all Swedish residents who are at least 20 years old and
have not completed lower secondary education (Eurydice, 2018[5]). In the public education system, adult
education and training is free of charge for Swedish citizens (OECD, 2015[6]). Similarly, in Finland, adults are
entitled to acquire the same educational and vocational qualifications as the young, and in some cases, young
and older students learn together. This may partly explain the higher than average share of 30-39 year-olds
enrolled in formal upper secondary or post-secondary non-tertiary programmes in Finland. Finally, providing
information and guidance is key to increase participation and inclusiveness. For example, Denmark’s relatively
high enrolment rates could be associated with the country’s proactive dissemination of information about general
education, higher education and adult/continuing education through the website UddannelsesGuiden (OECD,
2019[7]).

Figure A7.5. Enrolment in different levels of formal education (2017)
OECD / UIS / Eurostat, 30-39 year-olds

1. Data for upper secondary and post-secondary non-tertiary education enrolment excludes upper secondary education.
Note: The enrolment rates for each level of education is calculated based on the distribution presented in Table A7.3.
Countries are ranked in descending order of the percentage of 30-39 year-olds enrolled in formal tertiary education.
Source: OECD/UIS/Eurostat (2019), Table A7.3. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933977619

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 AT A GLANCE 2019 © OECD 2019

A7. TO WHAT EXTENT DO ADULTS PARTICIPATE EQUALLY IN EDUCATION AND LEARNING?  139

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-ofschool children, life skills, work skills and general culture.
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):
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
Calculations for data based Adult Education Survey (AES) can be found at: https://circabc.europa.eu/ui/group/d
14c857a-601d-438a-b878-4b4cebd0e10f/library/c28a2e5b-ecdf-4b07-ac2f-f3811d032295/details.
For data from the Survey of Adult Skills (PIAAC), 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.

Source
Tables A7.1, A7.2a and A7.2b on adult education and training are based on:


Adult Education Survey (AES) for European OECD countries.



The OECD Programme for the International Assessment of Adult Competencies (the Survey of Adult
Skills [PIAAC]) for: Canada, Chile, Israel, Japan, Korea, New Zealand, the Russian Federation and
the United States.



The Survey of Work-Related Training and Adult Learning, Australian Bureau of Statistics, for Australia.



Encuesta Continua de Empleo (ECE), Instituto Nacional de Estadística y Censos (INEC), for Costa Rica.

Table A7.2c on participation in distance learning is based on data from the OECD Programme for the International
Assessment of Adult Competencies (the Survey of Adult Skills [PIAAC]) for all countries and economies.
Table A7.3 on enrolment in formal education is based on the UNESCO-UIS/OECD/EUROSTAT data collection
on education statistics administered by the OECD in 2018 for all countries; all data refer to the academic year
2016/17 (for details, see Annex 3 at https://doi.org/10.1787/f8d7880d-en).
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[8]).

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 2019 © OECD 2019

140  A7. TO WHAT EXTENT DO ADULTS PARTICIPATE EQUALLY IN EDUCATION AND LEARNING?

References

Borkowsky, A. (2013), “Monitoring adult learning policies: A theoretical framework and indicators”,
OECD Education Working Papers, No. 88, OECD Publishing, Paris,
http://dx.doi.org/10.1787/5k4c0vxjlkzt-en.

[2]

Eurydice (2018), Adult Education and Training - Sweden, https://eacea.ec.europa.eu/nationalpolicies/eurydice/content/adult-education-and-training-80_en (accessed on 19 July 2019).

[5]

Kentnor, H. (2015), “Distance education and the evolution of online learning in the United States”,
Curriculum and Teaching Dialogue, Vol. 17/1-2, pp. S21-S21.

[4]

OECD (2019), Getting Skills Right: Future-Ready Adult Learning Systems, Getting Skills Right, OECD
Publishing, Paris, https://dx.doi.org/10.1787/9789264311756-en.

[7]

OECD (2016), Technical Report of the Survey of Adult Skills (PIAAC), 2nd Edition, OECD, Paris,
http://www.oecd.org/skills/piaac/PIAAC_Technical_Report_2nd_Edition_Full_Report.pdf.

[8]

OECD (2015), Education Policy Outlook 2015: Making Reforms Happen, OECD Publishing, Paris,
https://dx.doi.org/10.1787/9789264225442-en.

[6]

OECD (2014), Education at a Glance 2014: OECD Indicators, OECD Publishing, Paris,
https://dx.doi.org/10.1787/eag-2014-en.

[3]

OECD (2013), OECD Skills Outlook 2013 : First results from the Survey of Adult Skills, OECD
Publishing, Paris, http://dx.doi.org/10.1787/9789264204256-en.

[1]

Indicator A7 Tables
Table A7.1

Participation in formal and/or non-formal education and training, by gender, age group and
educational attainment (2016)

Table A7.2a

Distribution of non-formal education and training activities, by gender, age group and
educational attainment (2016)

WEB Table A7.2b Participation in job-related and non-job-related non-formal education and training, by gender,
age group and educational attainment (2016)
WEB Table A7.2c Participation in distance learning among adults participating in non-formal education and
training, by gender and age group and educational attainment (2012 or 2015)
Table A7.3

Enrolment in formal education, by age group, and distribution by level of education (2017)

Cut-off date for the data: 19 July 2019. 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.
StatLink: https://doi.org/10.1787/888933980906
EDUCATION AT A GLANCE 2019 © OECD 2019

A7. TO WHAT EXTENT DO ADULTS PARTICIPATE EQUALLY IN EDUCATION AND LEARNING?  141

Table A7.1. Participation in formal and/or non-formal education and training, by gender, age group and educational attainment
(2016)
Adult Education Survey (AES), Survey of Adult Skills (PIAAC) or national surveys, 25-64 year-olds

Note: Participation in formal and/or non-formal education and training during previous 12 months. Additional columns showing data for participation in formal and nonformal education and training separately are available for consultation on line (see StatLink below). Note that the average differs from the one published by Eurostat as this
is an unweighted average and the country coverage is different.
1. Year of reference 2012.
2. Year of reference 2015.
* See note on data for the Russian Federation in the Source section.
Source: OECD (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations..

StatLink 2 https://doi.org/10.1787/888933977486

EDUCATION AT A GLANCE 2019 © OECD 2019

142  A7. TO WHAT EXTENT DO ADULTS PARTICIPATE EQUALLY IN EDUCATION AND LEARNING?
Table A7.2a. Distribution of non-formal education and training activities, by gender, age group and educational attainment (2016)
Adult Education Survey (AES), Survey of Adult Skills (PIAAC) or national surveys, 25-64 year-olds who participated in non-formal
education and training activities

Note: The distribution of non-formal education and training activities refers to the previous 12 months. Additional columns showing the "no response" category and showing
data by gender and age group are available for consultation on line (see StatLink below). Note that the average differs from the one published by Eurostat as this is an
unweighted average and the country coverage is different.
1. Year of reference 2012.
2. Year of reference 2015.
* See note on data for the Russian Federation in the Source section.
Source: OECD (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.

StatLink 2 https://doi.org/10.1787/888933977505
EDUCATION AT A GLANCE 2019 © OECD 2019

A7. TO WHAT EXTENT DO ADULTS PARTICIPATE EQUALLY IN EDUCATION AND LEARNING?  143

Table A7.3. Enrolment in formal education, by age group, and distribution by level of education (2017)
OECD/UIS/Eurostat

1. Data for upper secondary and post-secondary non-tertiary education enrolment excludes upper secondary education.
Source: OECD/UIS/Eurostat (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.

StatLink 2 https://doi.org/10.1787/888933977524

EDUCATION AT A GLANCE 2019 © OECD 2019

 145

Chapter B. Access to education,
participation and progress

Indicator B1 Who participates in education?
StatLink https://doi.org/10.1787/888933980925
Indicator B2 How do early childhood education systems differ around the world?
StatLink https://doi.org/10.1787/888933980944
Indicator B3 Who is expected to graduate from upper secondary education?
StatLink https://doi.org/10.1787/888933980963
Indicator B4 Who is expected to enter tertiary education?
StatLink https://doi.org/10.1787/888933980982
Indicator B5 How many students complete tertiary education?
StatLink https://doi.org/10.1787/888933981001
Indicator B6 What is the profile of internationally mobile students?
StatLink https://doi.org/10.1787/888933981020
Indicator B7 What are the characteristics and outcomes of doctoral graduates?
StatLink https://doi.org/10.1787/888933981039

EDUCATION AT A GLANCE 2019 © OECD 2019

146  B1. WHO PARTICIPATES IN EDUCATION?

Indicator B1. Who participates in education?
Highlights


On average across OECD countries, around 70% of 17-18 year-olds are enrolled in upper secondary
education (more than 40% in general programmes and around 30% in vocational programmes).
In most countries, students in this age group are not typically enrolled in post-secondary non-tertiary
and tertiary programs.



More than 40% of 19-20 year-olds are enrolled in tertiary programmes in almost half of OECD
countries. Enrolment in tertiary education peaks among those aged 21-22 in about one-third of
countries, while only in Denmark does enrolment reach its highest level at the age of 23-24.



Enrolment in bachelor's programmes is more prevalent than enrolment in other programmes at the
tertiary level. The average enrolment rate across OECD countries in bachelor’s programmes reaches
32% among 20-21 year-olds.

Figure B1.1. Tertiary enrolment rates from age 19 to age 28 (2017)
Students in full-time and part-time programmes in both public and private institutions

1. Year of reference 2016.
2. Underestimated due to many resident students enrolled in neighbouring countries.
Countries are ranked in descending order of enrolment rates at ages 19 to 20.
Source: OECD/UIS/Eurostat (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787888933977695

Context
Pathways through education can be diverse, both across countries and for different individuals within the same
country. Experiences in primary and secondary education are probably the most similar across countries.
Compulsory education is usually relatively homogeneous as pupils progress through primary and lower

EDUCATION AT A GLANCE 2019 © OECD 2019

B1. WHO PARTICIPATES IN EDUCATION?  147

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, including upper secondary and tertiary education.
Ensuring that people have suitable opportunities to attain adequate levels of education is a critical challenge
and depends on their ability to progress through the different levels of an educational system. Developing and
strengthening both general and vocational education at upper secondary level can make education more
inclusive and appealing to individuals with different preferences and aptitudes. Vocational education and
training (VET) programmes are an attractive option for youth who are more interested in practical occupations
and for those who want to enter the labour market earlier (OECD, 2019[1]). In many education systems, VET
enables some adults to reintegrate into a learning environment and develop skills that will increase their
employability.
To some extent, the type of upper secondary programme students attended conditions their educational
tracks. Successful completion of upper secondary programmes gives students access to post-secondary
non-tertiary education programmes, where available, or to tertiary education. Upper secondary vocational
education and post-secondary non-tertiary programmes, which are mostly vocational in nature, can allow
students to enter the labour market earlier, but higher levels of education often lead to higher earnings and
better employment opportunities (see Indicators A3 and A4). Tertiary education has become a key driver of
today’s economic and societal development. The deep changes that have occurred in the labour market over
the past decades suggest that better-educated individuals have (and will continue to have) an advantage as
the labour market becomes increasingly knowledge-based. As a result, ensuring that a large share of the
population has access to a high-quality tertiary education capable of adapting to a fast-changing labour market
are some of the main challenges tertiary educational institutions, and educational systems more generally,
face today.

Other findings


There are various types of bachelor’s and master’s programmes. Three-to-four-year bachelor’s
degrees account for 72% of students at bachelor’s and master’s level on average across the OECD.



Part-time enrolment in tertiary education varies across levels: on average across OECD countries in
2017, 16% of students in bachelor’s programmes were part time, compared to 21% in master’s and
doctoral programmes, and 26% in short-cycle tertiary programmes.



Across the 23 countries that are both members of the European Union and the OECD, enrolment of
tertiary students in public institutions (77%) is higher than the average across OECD countries (71%).
Among all OECD countries, only Belgium, Chile, Estonia, Israel, Japan, Korea, Latvia and
the United Kingdom had less than half of students enrolled in public institutions in 2017, compared to
95% or more in Canada, Denmark, Greece, Ireland, Luxembourg and Saudi Arabia.

EDUCATION AT A GLANCE 2019 © OECD 2019

148  B1. WHO PARTICIPATES IN EDUCATION?

Analysis
Compulsory education
In OECD countries, compulsory education typically begins with primary education, starting at the age of 6.
However, in about one-third of OECD and partner countries, compulsory education begins earlier while in Estonia,
Finland, Indonesia, Lithuania, the Russian Federation and South Africa, compulsory education does not begin
until the age of 7. Compulsory education ends with the completion or partial completion of upper secondary
education at 16 on average across OECD countries, ranging from 14 in Korea and Slovenia to 18 in Belgium,
Chile, Germany and Portugal. In the Netherlands, there is a partial compulsory education (i.e. pupils must attend
some form of education for at least two days a week) from age 16 to 18 or until when they complete a diploma.
However, high enrolment rates extend beyond the end of compulsory education in a number of countries. On
average across OECD countries, full enrolment (the age range when at least 90% of the population are enrolled
in education) lasts 14 years from the age of 4 to the age of 17. For most countries the period of full enrolment
lasts 11-16 years in most countries and reaches 17 years in Norway. Full enrolment is shorter in Costa Rica,
Indonesia and Turkey and can be as short as four years in Colombia.
In almost all OECD countries, the enrolment rate among 4-5 year-olds in education exceeded 90% in 2017.
Enrolment at an early age is relatively common in the OECD area, with about one-third of countries achieving full
enrolment for 3-year-olds. In Iceland and Norway, full enrolment is also achieved for 2-year-olds (see
Indicator B2). In other countries, full enrolment is achieved for children at the age of 5, except in Finland,
the Slovak Republic and Turkey where full enrolment is achieved at age 6, and in Colombia at age 9.
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 range 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 6-14 year-olds attained or exceeded
95% in all OECD and partner countries except Colombia (88%).

Upper secondary and post-secondary non-tertiary education pathways
Upper secondary education is typically designed to prepare students for tertiary education, to provide them with
the 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 14 and 16 years
of age, and these programmes usually end 12 or 13 years after the beginning of primary school. Therefore, this
educational level accounts for most of the enrolment of 15-19 year-olds. The duration of upper secondary
education varies from two years in Australia, Ireland, Lithuania and the Russian Federation to five years in Italy.
While general education is designed to develop learners’ general knowledge and competencies, often to prepare
them for more advanced education programmes, vocational education and training programmes are considered
effective at developing skills directly applicable to the labour market. Upper secondary vocational education
tracks prepare participants for direct entry into specific occupations and attract a diverse range of students,
including youths seeking technical skills to start work, adults wishing to increase their employability and students
who may pursue higher education at a later stage (OECD, 2019[1]). Countries with well-established VET and
apprenticeship programmes have been more effective in holding the line on youth unemployment (OECD,
2018[2]). However, 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[3]).

EDUCATION AT A GLANCE 2019 © OECD 2019

B1. WHO PARTICIPATES IN EDUCATION?  149

Figure B1.2. OECD average enrolment rates by level of study (2017)
Students in full-time and part-time programmes in both public and private institutions

Source: OECD/UIS/Eurostat (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933977714

On average across OECD countries, 42% of students in upper secondary education were enrolled in vocational
upper secondary programmes. The distribution of upper secondary students by programme orientation largely
depends on the education programmes available, as well as the labour-market outcomes of these programmes.
In about one-third of countries with available data, more upper secondary students are enrolled in vocational than
in general programmes, reaching at least 70% in the Czech Republic, Finland and Slovenia.
Participation in upper secondary vocational education is highest between the ages of 15 to 19, reaching its peak
among 17 year-olds (31% enrolment on average across OECD countries), but it is less concentrated than in
general programmes. Participation in general programmes is generally higher and covers a narrower age range,
between 15 and 18 years of age (Figure B1.2).
Enrolment in post-secondary non-tertiary programmes is much more spread out over a wider age range.
Post-secondary non-tertiary education provides knowledge, skills and competencies with less complexity than
those characteristic of tertiary education, but building on secondary education. Programmes at this level prepare
students for labour-market entry as well as tertiary education (UNESCO-UIS, 2012[4]). The majority of students
enrol in post-secondary non-tertiary programmes between the ages of 18 and 22, although enrolment typically
remains low (Figure B1.2).

EDUCATION AT A GLANCE 2019 © OECD 2019

150  B1. WHO PARTICIPATES IN EDUCATION?
Transition to tertiary education
Tertiary programmes account for most of the participation in education between the ages of 20 and 29, including
short-cycle, bachelor’s, master’s and doctoral programmes. Tertiary education builds on secondary education,
providing learning activities in specialised fields of education. It aims at learning with a high level of complexity
and specialisation. Tertiary education includes what is commonly understood as academic education but also
includes advanced vocational or professional education.
Programme orientation at the upper secondary level tends to influence enrolment patterns in tertiary education
(see Indicator B5). Countries with a greater participation of 15-19 year-olds in upper secondary general
programmes than in vocational tracks tend to have higher enrolment rates in tertiary education. This is the case
for example in France, Greece, Ireland, Korea and the United States where participation in tertiary education is
over 50% among 19-20 year-olds, and at least 40% of 15-19 year-olds (up to 100% in the United States) were
enrolled in general upper secondary programmes in 2017. There are notable exceptions, however: in Belgium,
the Netherlands and Slovenia more than half of all 15-19 year-old students were enrolled in vocational
programmes but tertiary enrolment rates for 19-22 year-olds were above the OECD average in the same period.
Countries can be divided into three groups based on the age when students typically transition into tertiary
education.


Transition to tertiary education occurs mostly at age 19-20: the OECD and partner countries with the
highest participation in tertiary education are also the ones in which students’ transition into tertiary
education tends to occur at a younger age. In about half of OECD and partner countries, participation in
tertiary education among 19-20 year-olds is 40% or more and in France, Ireland, Korea,
the Russian Federation, the United Kingdom and the United States, enrolment rates for this age group
are at least 10 percentage points higher than among 21-22 year-olds. Korea, with 71% of 19-20 year-olds
in tertiary education is well above the other countries (Figure B1.1).



Transition to tertiary education occurs mostly at age 19-22: on average across OECD countries,
37% of 19-20 year-olds and 21-22 year-olds were enrolled in tertiary education in 2017. Enrolment rates
in these two age groups are also very similar and close to the OECD average in a number of countries,
including Argentina, Austria, Italy, Estonia and the Netherlands.



Transition to tertiary education occurs mostly at age 21-22: transition into tertiary education begins
a bit later and tertiary enrolment rates peak among 21-22 year-olds in the Czech Republic, Hungary,
Iceland and the Slovak Republic, as well as in Norway, Poland and Turkey where enrolment exceeds
40%. In addition, in Finland, Germany, Sweden and Switzerland, participation in tertiary education among
21-22 year-olds is similar to the rate among 23-24 year-olds. Denmark is the only country where
enrolment in tertiary education peaks among 23-24 year-olds. Various factors can influence a later
entrance to tertiary education (see Indicator B4).

Tertiary education pathways
The share of students enrolled in each tertiary education level and at each age illustrates the different educational
systems and pathways in countries. As students get older, they enrol in bachelor’s programmes and can then
move on to higher educational levels, including master’s programmes from the age of 20 (or earlier in case of
long first degrees, see Box B1.1), and doctoral programmes from the age of 25. Depending on the structure of
the educational system, students across the OECD may also enrol in short-cycle tertiary programmes from the
age of 17.
Short-cycle tertiary programmes are often designed to provide participants with professional knowledge, skills
and competencies; these practically based programmes prepare students to enter the labour market, but may
also provide a pathway to other tertiary education programmes. The OECD average enrolment rate for these
programmes peaks at age 18-21, reaching between 4% and 5%. These programmes are not offered in some
countries such as Estonia, Finland, Greece and Lithuania. However, enrolment rates in short-cycle tertiary
EDUCATION AT A GLANCE 2019 © OECD 2019

B1. WHO PARTICIPATES IN EDUCATION?  151

programs are more similar to those in bachelor’s programmes in countries like Canada, Chile, France, Korea,
the Russian Federation, Spain, Turkey and the United States. In these countries, enrolment of 19-20 year-olds
in these programmes exceeds 10%. The typical enrolment period (for which at least 50% of students at this level
are enrolled) lasts between two years (France) and seven years (Turkey).
Enrolment in bachelor's programmes is more prevalent than enrolment in other programmes at the tertiary level.
They are designed to provide participants with intermediate academic and/or professional knowledge, skills and
competencies, leading to a first degree or equivalent qualification. In most OECD countries, the typical age range
over which students enrol in bachelor’s programmes lasts 4-5 years, starting from age 18 or 19, although
participation at this level may start later (at 21 or 22) in a number of countries like Denmark, Iceland and Israel.
Only in Belgium, France, Ireland, Lithuania, the Slovak Republic, Slovenia and the United Kingdom do the typical
enrolment ages exactly reflect the typical duration of bachelor’s programmes, which is usually three years. The
average enrolment rate across OECD countries in bachelor’s programmes peaks between the ages of 19 and 22,
reaching 32% among 20-21 year-olds. Overall enrolment patterns at this level strongly mirror those at tertiary
level more generally.(
Master’s programmes are designed to provide advanced academic or professional knowledge, skills and
competencies and may have a substantial research component. They are less prevalent than bachelor’s in OECD
countries, where the average enrolment rate remains below 10%: among 22-26 year-olds enrolment rates range
between 5% and 9%, peaking at the age of 23. In 2017, at least 10% of the population aged 21-22 were enrolled
in master’s programmes in Belgium, France, Italy, Poland Portugal, the Russian Federation and Sweden. The
enrolment rate for 23-24 year-olds is higher than for 21-22 year-olds on average across OECD countries and it
reached 15% in France and Italy and more in the Czech Republic (17%), Poland (20%), the Slovak Republic
(17%) and Slovenia (20%).

Box B1.1. Types of bachelor’s and master’s programmes
There are various types of bachelor’s and master’s programmes. First short degrees at bachelor’s level
(i.e. with a cumulative theoretical duration of three to four years) are the most popular type of programme in
OECD and partner countries and account for 72% of students at bachelor’s and master’s level on average
across the OECD and at least 90% of students at these levels in Brazil, Korea and Mexico (Figure B1.a).
Across OECD countries, only 13% of all students at bachelor’s and master’s level are enrolled in a first short
master’s programme following a bachelor’s degree. Enrolling in these programmes is particularly uncommon
in Brazil, Colombia, Japan, Mexico and New Zealand, accounting for less than 10% of all bachelor’s and
master’s students (Figure B1.a).
First degrees may take longer than four years and may award qualifications either at bachelor’s or, more often,
at master’s level, depending on the field of study and the setup of the tertiary education system in each
country. Their longer duration is due to the greater complexity of content. Long first degrees, especially at
master’s level, cover highly specialised professional studies of greater cumulative duration (e.g. medicine,
dentistry, architecture, law or engineering). All first degrees in Colombia are long and 91% of all bachelor’s
and master’s students were enrolled in this type of programme in 2017. Other than Colombia, these
programmes are popular in France, Italy, Portugal and Sweden where the share of students enrolled at these
levels equalled or exceeded 19% in the same year.
In addition to first bachelor’s and master’s programmes, students in tertiary education may enrol in second or
further degree programmes, which are typically 1-2 years long at bachelor’s level and 1-4 years of (often
professionally oriented) full-time study at master’s level (UNESCO-UIS, 2012[4]). Second or further degrees
are more uncommon in OECD countries, although they equal or exceed 10% of bachelor’s and master’s
students in New Zealand and Poland at bachelor’s level and in Luxembourg at master’s level. In New Zealand,

EDUCATION AT A GLANCE 2019 © OECD 2019

152  B1. WHO PARTICIPATES IN EDUCATION?
for example, these generally relate to professionally oriented one-year post-bachelor’s programmes in a
specific field.
Recognised intermediate qualifications from the successful completion of stages of programmes (prior to
completing a first degree) which are insufficient for full completion of a level may be classified at a lower
attainment level or simply classified as insufficient for level completion. An example of the latter are the classes
préparatoires aux grandes écoles (higher school preparatory classes) in France, which are not recognised as
degrees but rather prepare students for a degree programmes (e.g. in the fields of business or engineering).

Figure B1.a. Share of bachelor's and master's students by educational programme (2017)
Students in full-time and part-time programmes in both public and private institutions

Note: Long first degrees and programmes insufficient for level completion include programmes classified at both bachelor's and master's levels.
1. Excludes private institutions at short-cycle tertiary level.
2. Master's following a bachelor's programme include second or further bachelor's degrees.
Countries are ranked in descending order of the share of students enrolled in first bachelor's degrees or equivalent programmes.
Source: OECD/UIS/Eurostat (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933977752

Profile of tertiary students
Public institutions tend to dominate enrolments across tertiary education levels. In general across OECD
countries, while the relative share of enrolment in public institutions tends to fall with higher educational levels
from primary to tertiary education (OECD, 2018[2]), the opposite is true within tertiary education, where enrolment
in public institutions increases with each higher level.
On average across OECD countries in 2017, 71% of students in tertiary education were enrolled in public
institutions, compared to 77% on average across the EU23. Among all OECD and partner countries, only
Belgium, Estonia, Israel, Latvia and the United Kingdom have more than 50% of students enrolled in governmentdependent private institutions and only Brazil, Chile, Japan and Korea have more than 50% of students in
independent private institutions. In contrast, 95% of tertiary students or more were enrolled in public institutions
in 2017 in Canada, Denmark, Greece, Ireland, Luxembourg and Saudi Arabia (Figure B1.3).
EDUCATION AT A GLANCE 2019 © OECD 2019

B1. WHO PARTICIPATES IN EDUCATION?  153

The share of students enrolled in public institutions varies by level of education. On average across the OECD,
60% of students in short-cycle tertiary programmes are enrolled in public institutions compared to 69% for
bachelor’s programmes. In some countries, the share of students enrolled in public institutions is much larger in
short-cycle tertiary programmes than at bachelor’s level. This is the case in Brazil, Colombia, Costa Rica, Israel,
Latvia and Mexico, where the difference between these levels is equal to or exceeds 30 percentage points.

Figure B1.3. Share of tertiary students enrolled by type of institution (2017)
Students in full-time and part-time programmes

1. Excludes private institutions at short-cycle tertiary level.
2. Year of reference 2016.
Countries are ranked in descending order of share of tertiary students enrolled in public institutions.
Source: OECD/UIS/Eurostat (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933977733

The share of master’s students in public institutions is 1 percentage point higher than at bachelor’s level on
average across OECD countries. However, the difference equals or exceeds 25 percentage points or more in
Brazil, Finland and Japan. In contrast, in some countries a smaller share of students is enrolled in public
institutions in master’s programmes than at bachelor’s level: in Estonia, Mexico, the Netherlands, Saudi Arabia
and the United States, the share of students in public institutions at master’s programmes is at least
15 percentage points lower than at bachelor’s level. In doctoral programmes, the average share of enrolment in
public institutions increases by 8 percentage points compared to master’s programmes, reaching 78% in 2017
on average across OECD countries and 100% in 15 OECD and partner countries. Only in Costa Rica, Estonia,
Israel and Latvia are the majority of doctoral students enrolled in private institutions (in Estonia, Israel and Latvia
more than 9 out of 10 doctoral students enrolled in government-dependent private institutions).
The share of part-time enrolment increases with higher levels of education and with the average age of students
enrolled (OECD, 2018[2]). However, this varies across different tertiary education levels: on average across
OECD countries in 2017, 16% of students in bachelor’s programmes were part time, 21% in master’s and doctoral
programmes and 26% in short-cycle tertiary programmes (Table B1.3). However, there are stark disparities
between countries. The share of part-time students in bachelor programmes ranges from 2% or less in
the Czech Republic and Luxembourg as well as in countries where bachelor’s programmes do not allow part-time
EDUCATION AT A GLANCE 2019 © OECD 2019

154  B1. WHO PARTICIPATES IN EDUCATION?
study at this level (Austria, Chile, Colombia, Costa Rica, France, Greece, Italy, Mexico and Turkey), to 49% in
the Russian Federation and 53% in Sweden. The share of part-time students reaches its peak for master’s
programmes in New Zealand (63%) and for doctorates in Finland, Germany, Norway and Slovenia, where at
least 75% of doctoral students are enrolled part time.

Subnational variations in enrolment
Subnational variation in enrolment patterns reveal the equality of access to education across a country, as well
as labour-market opportunities and perceptions of lifelong learning for levels beyond compulsory education.
Between the ages of 6 and 14 (corresponding to compulsory education in many countries) and 15 to 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 from the age of 6, 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 relatively low in Estonia, Germany and Sweden, the coefficient of
variation shows considerable variation and exceeds 80% in the Czech Republic, Latvia, Lithuania and
the Slovak Republic. Latvia also has the highest ratio between the highest and lowest enrolment rates at
subnational level for this age group.
Subnational disparities in enrolment increase among 30-39 year-olds. The variation is especially high in Greece,
Latvia and the Slovak Republic, where the coefficient of regional variation exceeds 70%. The enrolment rate for
older adults (40-64 year-olds) are relatively low, reaching 2% on average across OECD countries. Regional
differences at this age are still observed across countries with available data, particularly in Greece and Latvia,
where the ratio between the highest and lowest enrolment rates across regions increases the most for this age
group compared to the one for 30-39 year-olds (OECD, 2019[5]).

Definitions
The data in this indicator cover formal education programmes that represent at least the equivalent of one
semester (or 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.
Private institutions are those controlled and managed by a non-governmental organisation (e.g. a church, a
trade union or a business enterprise, foreign or international agency), or their governing board consists mostly of
members not selected by a public agency. Private institutions are considered government-dependent if they
receive more than 50% of their core funding from government agencies or if their teaching personnel are paid by
a government agency. Independent private institutions receive less than 50% of their core funding from
government agencies and their teaching personnel are not paid by a government agency.
A full-time student is 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.
EDUCATION AT A GLANCE 2019 © OECD 2019

B1. WHO PARTICIPATES IN EDUCATION?  155

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%.
For more information, please see the OECD Handbook for Internationally Comparative Education Statistics 2018:
Concepts, Standards, Definitions and Classifications (OECD, 2018[6]) and Annex 3 for country-specific notes
(https://doi.org/10.1787/f8d7880d-en).

Source
Data refer to the academic year 2016/17 and are based on the UNESCO-UIS/OECD/EUROSTAT data collection
on education statistics administered by the OECD in 2018 (for details, see Annex 3 at
https://doi.org/10.1787/f8d7880d-en). Data from Argentina, the People’s Republic of China, India, Indonesia,
Saudi Arabia and South Africa are from the UNESCO Institute of Statistics (UIS).
Data on subnational regions for selected indicators are available in the OECD Regional database (OECD,
2019[5]).
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
Hanushek, E., L. Woessmann and L. Zhang (2011), “General education, vocational education, and
labor-market outcomes over the life-cycle”, IZA Discussion Paper No. 6083,
http://ftp.iza.org/dp6083.pdf (accessed on 27 April 2018).

[3]

OECD (2019), OECD Regional Statistics Database - Enrolment rate by age,
http://stats.oecd.org/Index.aspx?DataSetCode=REGION_EDUCAT.

[5]

OECD (2019), “What characterises upper secondary vocational education and training?”, Education
Indicators in Focus, No. 68, OECD Publishing, Paris, https://dx.doi.org/10.1787/a1a7e2f1-en.

[1]

OECD (2018), Education at a Glance 2018: OECD Indicators, OECD Publishing, Paris,
https://dx.doi.org/10.1787/eag-2018-en.

[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.

[6]

UNESCO-UIS (2012), International Standard Classification of Education ISCED 2011,
http://www.uis.unesco.org (accessed on 23 May 2019).

[4]

EDUCATION AT A GLANCE 2019 © OECD 2019

156  B1. WHO PARTICIPATES IN EDUCATION?

Indicator B1 Tables
Table B1.1

Enrolment rates by age group (2005, 2010 and 2017)

Table B1.2

Enrolment rates in tertiary education, by age group and level of education (2017)

Table B1.3

Profile of students enrolled in tertiary education (2017)

Cut-off date for the data: 19 July 2019. 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.
StatLink: https://doi.org/10.1787/888933980925

EDUCATION AT A GLANCE 2019 © OECD 2019

B1. WHO PARTICIPATES IN EDUCATION?  157

Table B1.1. Enrolment rates by age group (2005, 2010 and 2017)
Students in full-time and part-time programmes in both public and private institutions

1. Excludes post-secondary non-tertiary education.
2. Breakdown by age not available after 15 years old.
3. The 6 to 14 age group includes a number of students aged over 14 who are enrolled in primary education.
4. Year of reference 2016.
Source: OECD/UIS/Eurostat (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.

StatLink 2 https://doi.org/10.1787/888933977638

EDUCATION AT A GLANCE 2019 © OECD 2019

158  B1. WHO PARTICIPATES IN EDUCATION?
Table B1.2. Enrolment rates in tertiary education, by age group and level of education (2017)
Students enrolled in full-time and part-time programmes in both public and private institutions

1. Excludes private institutions at short-cycle tertiary level.
2. Underestimated due to many resident students enrolled in neighbouring countries.
3. Short-cycle tertiary programmes include a small number of bachelor's professional programmes.
3. Short-cycle tertiary programmes include part of upper secondary vocational programmes.
Source: OECD/UIS/Eurostat (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.

StatLink 2 https://doi.org/10.1787/888933977657

EDUCATION AT A GLANCE 2019 © OECD 2019

B1. WHO PARTICIPATES IN EDUCATION?  159

Table B1.3. Profile of students enrolled in tertiary education (2017)

1. Typical enrolment ages correspond to the shortest age interval which covers at least 50% of students at that level.
2. Private institutions at short-cycle tertiary level are excluded.
3. Year of reference 2016.
Source: OECD/UIS/Eurostat (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
StatLink 2 https://doi.org/10.1787/888933977676

EDUCATION AT A GLANCE 2019 © OECD 2019

160  B2. HOW DO EARLY CHILDHOOD EDUCATION SYSTEMS DIFFER AROUND THE WORLD?

Indicator B2. How do early childhood education
systems differ around the world?
Highlights


More than 70% of the OECD countries with available data have integrated early childhood education
and care (ECEC) services, where one or several authorities are responsible for administering the
whole ECEC system and setting adequate intentional education for children from the ages of 0 or 1
until entry into primary education.



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 2017, more than one-third of
children under 3 were enrolled in early childhood education (ISCED 0) and other registered ECEC
services outside the scope of ISCED 0, an increase of 8 percentage points compared to 2010. On
average, 40% of 1-year-olds and 62% of 2-year-olds were already enrolled in ECEC services.



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). Enrolment rates for 5 year-olds in pre-primary or
primary education is above 90% in 36 out of 43 countries with available data in 2017.

Figure B2.1. Enrolment rates of children under the age of 3 in early childhood education and care, by age (2017)
All ECEC services (Early childhood education [ISCED 0] and other registered ECEC services outside the scope of ISCED 0)

Note: Figures in parentheses refer to the age when ECEC systems start offering intentional education objectives.
1. Age 1 also includes children under the age of 1.
2. Data for other registered ECEC services come from the survey "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.
Countries are ranked in descending order of the enrolment rates in ISCED 0 of children under the age of 3.
Source: OECD (2019). Table B2.1. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933977847

EDUCATION AT A GLANCE 2019 © OECD 2019

B2. HOW DO EARLY CHILDHOOD EDUCATION SYSTEMS DIFFER AROUND THE WORLD?  161

Context
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 in children’s development, learning and well-being.
Children who start strong will be more likely to have better outcomes when they grow older. This is particularly
true for children from disadvantaged socio-economic backgrounds, because they often have fewer
opportunities to develop these abilities in their home-learning environments (OECD, 2017[1]).
Economic prosperity also depends on maintaining a 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. High-quality ECEC services and other provision aiming to improve people’s work-life balance
give parents greater opportunities to enter employment and make it possible for individuals to combine work
and family responsibilities (OECD, 2018[2]; OECD, 2011[3]; OECD, 2016[4]).
Such evidence has prompted policy makers to design early interventions, to take initiatives that aim to enhance
the quality of ECEC services and improve the equity of access to ECEC settings, lower the age of compulsory
education, and to rethink their education spending patterns to gain “value for money” (Duncan and Magnuson,
2013[5]). Despite these general trends, there are significant differences across OECD countries in the quality
of ECEC services provided to young children, the types of ECEC services available and the usual number of
hours per week each child attends.

Other findings


In early childhood educational development services (ISCED 01), public funding accounts for an
average of 69% of total expenditure, while in pre-primary education (ISCED 02), it amounts to 83%.
In total, expenditure on ECEC (ISCED 0) accounts for an average of 0.8% of gross domestic product
(GDP), of which around three-quarters goes to pre-primary education.



Variations across countries in the duration of ECEC programmes have a strong impact on the level of
expenditure allocated to ECEC. For instance, in Ireland, children typically enter primary education at
the age of 5 while in Finland they typically enter at age 7. To avoid this distortion, this indicator now
calculates expenditure by age and not by ISCED level. Expenditure on all children aged 3 to 5 enrolled
in ECEC and primary education amounts to an average of 0.6% of GDP. It exceeds 0.9% only in
Iceland, Norway and Sweden.



A bachelor’s degree (ISCED 6) has become the minimum qualification required to be a teacher in
ECEC (ISCED 0) in around three-quarters of OECD countries with available data.



The child-teacher ratio at the pre-primary level for OECD countries, excluding teachers’ aides, ranges
from more than 25 children per teacher in Colombia and Mexico to fewer than 10 in Finland and
Germany. However, some countries make extensive use of teachers’ aides in pre-primary education,
as shown by their smaller ratios of children to contact staff than of children to teaching staff. In the
majority of these countries, teachers’ aides need an upper secondary qualification.

EDUCATION AT A GLANCE 2019 © OECD 2019

162  B2. HOW DO EARLY CHILDHOOD EDUCATION SYSTEMS DIFFER AROUND THE WORLD?

Analysis
Types of early childhood education and care services
There is a growing consensus among OECD countries about the importance for good quality ECEC. However,
the types of early childhood education and care (ECEC) services available to children and parents in OECD
countries differ greatly. There are variations in the targeted age groups, governance of centres, funding of
services, type of delivery (full-day versus part-day attendance), and the location of provision, either in centres or
schools, or at home (OECD, 2017[1]).
Generally, formal ECEC services can be classified into two categories:


The ECEC services reported in the ISCED 2011 classification (OECD/Eurostat/UNESCO Institute for
Statistics, 2015[6]). To be classified as ISCED level 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. a curriculum)
5. have trained or accredited staff (e.g. educators are required to have pedagogical qualifications).



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 an educational programme (e.g. crèches in
France or amas in Portugal). The distinction between these two categories is explicitly shown in
Tables B2.1 and B2.5.

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 by this indicator
(see the Definitions section 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 a positive effect on children’s well-being, learning and development
in the first years of their lives (OECD, 2018[2]).
On average across OECD countries in 2017, around one-third of children under the age of 3 were enrolled in
ECEC, either full time or part time. This average masks great differences across countries. Less than 5% of
children under 3 are enrolled in ECEC services in Mexico and Turkey, while this proportion is 50% or over in
Denmark, Iceland, Israel, Luxembourg, Korea, the Netherlands, New Zealand and Norway (Table B2.1).
The length of parental leave and the age when ECEC services start becoming available also influence the age
at which children enrol in these services. For instance, only 7 of the 22 countries with available data have
enrolment rates of over 10% for children below the age of 1, namely Australia, Israel, Korea, Luxembourg,
New Zealand, Portugal and Spain. In contrast, once children reach the age of 1, around 40% will be enrolled in
ECEC, with enrolment rates at this age exceeding 50% in Iceland, Israel, Korea, Luxembourg, New Zealand and
Norway. By the age of 2, enrolment in ECEC services has become the norm in many countries, with 62% of
2-year-olds enrolled in ECEC. However, this average also hides wide variation. Enrolment rates for 2-year-olds
range from less than 20% in Costa Rica, Mexico and Poland to 89% or more in Luxembourg and in all Nordic
countries except Finland (Figure B2.1).

EDUCATION AT A GLANCE 2019 © OECD 2019

B2. HOW DO EARLY CHILDHOOD EDUCATION SYSTEMS DIFFER AROUND THE WORLD?  163

Despite significant differences across countries, a common pattern is emerging. The share of children under the
age of 3 enrolled in ECEC is rising in most countries with available data for years 2010 and 2017, and has
increased on average by 8 percentage points between 2010 and 2017 (from 26% to 34%). The rise has been
particularly marked in many European countries, as a result of further stimulus from the objectives set by the
European Union (EU) at its Barcelona 2002 meeting, to supply subsidised full-day places for one-third of children
under the age of 3 by 2010 (OECD, 2017[1]). Globally, the rise in ECEC provision over recent decades is strongly
correlated to the increase in women’s participation in the labour force, particularly for mothers with children
under 3. Countries with higher enrolment rates of children under 3 in 2017 tend to be those in which the
employment rates of mothers are highest ( (OECD, 2018[2]; OECD, 2018[7]); Table B2.1).
However, wider enrolment in ECEC services does not guarantee the quality of education provided to children. In
countries such as Norway, for instance, not only do more than half of children below the age of 3 attend ECEC
services, but they also attend programmes that have integrated ECEC curricula (including intentional educational
objectives) adapted to the age of children from 0 until the beginning of primary school. In these programmes,
children are often exposed to an ECEC setting with trained or accredited staff, even before they turn 3. In other
countries with high enrolment rates, such as France and the Netherlands, different standards are often set for
different ECEC settings or for different age groups of children (Table B2.1 and Box B2.1).

Enrolment of children from age 3 until entry to primary education
In many OECD countries, ECEC begins for most children long before they are 5 years old and there are universal
legal entitlements to a place in ECEC services for at least one or two years before the start of compulsory
schooling. On average, 87% of 3-5 year-olds are enrolled in ECEC (ISCED 0) and primary education, at that age
usually in pre-primary education (ISCED 02). In half of the 42 countries with available data, the enrolment of
children between the ages of 3 and 5 is near universal, exceeding 90% (Table B2.2).
The highest enrolment rates of 3-year-olds in ECEC are found in Belgium, Denmark, France, Hungary, Iceland,
Israel, Norway, Spain and the United Kingdom, where they exceed 95%. Almost nine out of ten 4-year-olds (88%)
are enrolled in pre-primary and primary education across OECD countries. In the EU23 countries (countries that
are members of both the EU and the OECD), 92% of 4-year-olds are enrolled. OECD enrolment rates at this age
vary from 98% or higher in Belgium, Denmark, France, Iceland, Ireland, Israel, Spain and the United Kingdom,
to less than 50% in Saudi Arabia, Switzerland and Turkey (Table B2.2).
This situation is the result of the expansion of ECEC services over recent decades in many countries. Between
2005 and 2017, the average enrolment of 3-5 year-olds in pre-primary or primary education in OECD countries
rose from 76% to 86%. A few countries have seen spectacular increases in ECEC over this period, as in Chile,
Lithuania, Israel, Poland, the Russian Federation and Turkey. In contrast, other countries have not shown much
change. For instance, Switzerland reported among the lowest enrolment rates in 2005 and this is still the case in
2017 (Figure B2.2 ).
Over this period, the increased focus on ECEC policy has resulted in the extension of compulsory education to
younger children, 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 the age
of 1 until entry into primary education. For instance, compulsory education coincided with the start of primary
school in most countries a decade ago. In contrast, compulsory education started at pre-primary level in around
one-third of countries with available data in 2017 (Table B2.2).

Enrolment in ECEC by subnational regions
If average enrolment of 3-5 year-olds in pre-primary or primary education now exceeds 80% in many countries,
some strong subnational differences remain in access to education at these ages. In 7 out of 23 countries with
available data, there is a difference of more than 20 percentage points between the regions with the highest and
the lowest rates of enrolment. For instance, there are striking differences in the United States, where up to 80% of

EDUCATION AT A GLANCE 2019 © OECD 2019

164  B2. HOW DO EARLY CHILDHOOD EDUCATION SYSTEMS DIFFER AROUND THE WORLD?
3-5 year-olds are enrolled in ECEC and primary education in the District of Columbia, compared to only 46% in
North Dakota (OECD, 2019[8]). Similar strong regional differences are observed in France (from 79% in Mayotte
to 100% in several regions), Greece (from 57% in Attica to 78% in Western Macedonia), Lithuania (from 65% in
Taurage to 94% in Vilnius), the Slovak Republic (from 63% in East area to 83% in West area) and Switzerland
(39 % in Central area to 86% in Ticino). In some of these countries, the organisation and governance of ECEC
sharply differ between regions. Each region has the autonomy to make the decision to what extent ECEC services
should be prioritised and funded, which can lead to wide variations in enrolment rates (see more details in
Box B2.1). By contrast, the difference between regions is less than 8 percentage points only in Estonia, Germany,
Hungary, Latvia, the Netherlands, Slovenia and Sweden. This emphasises the importance of granting equal
access to ECEC across territories and between urban and rural areas.

Figure B2.2. Change in enrolment rates of children aged 3 to 5 years (2005, 2010 and 2017)
Early childhood education (ISCED 0) and primary education

1. Year of reference 2012 instead of 2010.
Countries are ranked in descending order of the enrolment rates of 3-5 year-olds in 2017.
Source: OECD (2019). Table B2.2. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933977866

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, Jung and Park, 2009[9]).
In most countries, the share of children enrolled in private institutions is considerably larger in ECEC than in
primary and secondary education. Private institutions can be classified into two categories: independent 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

EDUCATION AT A GLANCE 2019 © OECD 2019

B2. HOW DO EARLY CHILDHOOD EDUCATION SYSTEMS DIFFER AROUND THE WORLD?  165

government agencies. Government-dependent private institutions have similar governance structures but they
rely on government agencies for more than 50% of their core funding.
On average across OECD countries, about half of the children in early childhood educational development
services (ISCED 01) are enrolled in private institutions. This average, however, hides huge discrepancies across
countries. In Chile, Denmark, Finland, Hungary, Iceland, Latvia, Lithuania, Slovenia, Sweden and
the Russian Federation, 20% or less of the children in early childhood educational development programmes
attend private ECEC institutions, while in Costa Rica, Indonesia, Israel, Korea, New Zealand and
the United Kingdom, more than three-quarters of all children attend private institutions (Table B2.3).
Private institutions usually are more common for children under the age of 3 than for older ones. About two-thirds
of children enrolled in pre-primary education (ISCED 02) attend public institutions across OECD countries, and
up to three-quarters of children across EU23 countries, reflecting the development of 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 Australia, India, Indonesia, Ireland, Japan,
Korea and New Zealand, at least 70% of children attending pre-primary programmes are in private institutions
(Table B2.3). In Ireland, the government provides a capitalisation fee to participating playschools and day-care
services.

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 greatly influence the participation to ECEC of children from disadvantaged socio-economic
backgrounds (OECD, 2017[1]).

Expenditure per child
In pre-primary education, annual expenditure per child for both public and private settings averages USD 8 349
in OECD countries, ranging from less than USD 5 000 in Colombia, Ireland, Mexico, and the Russian Federation
to more than USD 10 000 in Austria, Finland, Germany, Iceland, Luxembourg, Norway, Sweden and Switzerland.
Annual expenditure per child enrolled in early childhood educational development services (ISCED 01) is
significantly higher than in pre-primary education (ISCED 02) in 10 out of the 15 OECD countries with available
data for both programmes, averaging USD 12 080 for ISCED 01. The smaller child-to-staff ratio in early childhood
development services (ISCED 01) is one of the main drivers of this difference (Tables B2.3 and B2.4). The
average number of hours children spend in ECEC settings per year also influences different countries’ spending
(see Box B2.2 in (OECD, 2018[10])).

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. While 0.3% or less of GDP is spent on pre-primary education in Australia, Colombia, Greece and
Japan, countries such as Iceland, Norway and Sweden spend at least 1% of GDP (Table B2.4).
These differences are largely explained by enrolment rates, legal entitlements and the intensity of participation,
as well as the different starting ages for primary education. On the latter point, the shorter duration of pre-primary
education, as the result of children’s earlier transition from pre-primary to primary education in Australia, Ireland,
New Zealand and the United Kingdom, partly explains why the expenditure on ECEC as a percentage of GDP is
EDUCATION AT A GLANCE 2019 © OECD 2019

166  B2. HOW DO EARLY CHILDHOOD EDUCATION SYSTEMS DIFFER AROUND THE WORLD?
below the OECD average in these four countries. Similarly, late entry into primary education, as in Estonia,
Finland, Latvia, Poland and Sweden, means a longer duration of ECEC than in other countries and may explain
why they spend more as a percentage of GDP than the OECD average (see the starting age of primary education
in Tables B2.1 and B2.4).
To avoid this distortion, the indicator on the financing of ECEC is presented by age as well as by ISCED level.
As this is first time this indicator is presenting estimates expenditure on all children aged 3 to 5 enrolled in either
ECEC or primary education, data should be interpreted with caution. This new methodology avoids the distortion
arising from the differences in age groups attending ECEC, and compares expenditure on children of the same
ages, giving a more accurate picture of countries’ investment in young children. Across OECD countries, the
share of national resources devoted to 3-5 year-olds enrolled in ECEC and primary education is 0.6% of GDP. It
ranges from less than 0.4% of GDP in Colombia, the Czech Republic, Ireland, the Netherlands, Switzerland,
Turkey and the United States, to more than 0.8 % in Chile, Israel, Iceland, New Zealand, Norway and Sweden
(Figure B2.3).

Figure B2.3. Expenditure on all children aged 3 to 5 enrolled in early childhood education and care
(ISCED 0) and primary education, as a percentage of GDP (2016)
Public and private institutions

1. Expenditure on all children aged 3 to 5 are underestimated due to the estimation method used.
2. Public sources only.
Countries are ranked in descending order of expenditure as a percentage of GDP.
Source: OECD (2019). Table B2.4. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933977885

Public and private funding of ECEC
The source of funding for ECEC settings varies across countries. In many countries, the public sector provides
universal access from a certain age. Many governments may also delegate responsibility for the public funding
of ECEC to local authorities. In general, public funding of ECEC is more decentralised than at any other level of
education (OECD, 2018[11]).
Generally, there has been a substantial and increasing public investment in ECEC, although there are differences
between pre-primary (ISCED 02) and early childhood educational development (ISCED 01). On average, public
sources account for 69% of total expenditure on early childhood educational development, while for pre-primary
education, the share of public expenditure is 83%. Japan and the United Kingdom are the only countries where
private funds account for more than 40% of total expenditure on pre-primary education. In the United Kingdom,
EDUCATION AT A GLANCE 2019 © OECD 2019

B2. HOW DO EARLY CHILDHOOD EDUCATION SYSTEMS DIFFER AROUND THE WORLD?  167

most of the private funding comes from households. In Japan, the high cost is shared between households,
foundations and the business sector (Table B2.4).

Box B2.1. Who is responsible for early childhood education and care?
Countries present different profiles when the governance of ECEC is analysed (Figure B2.a).
Currently, about half of OECD countries have an integrated system, where responsibility for administering all
ECEC services lies with one lead authority at the national and/or regional level. In all the countries with an
integrated system except Hungary and Iceland, the education ministry is in charge of the entire ECEC age
group at the central level. The responsibilities of the leading authority in those countries may stretch from
curriculum development to standard setting, monitoring and financing. Countries with integrated systems also
have integrated ECEC curricula adapted to the age of children from under 1 until the beginning of primary
school. An increasing number of countries have recently moved towards these types of integrated systems.

Figure B2.a. Who is responsible for early childhood education and care (ECEC)?

1. The state Secretariat for Education is responsible for ISCED 0 while the state Secretariat for Family and Youth Affairs is responsible for ECEC
services outside ISCED 0. Both are under the auspices of the Ministry of Human Capacities.
2. The entire ECEC system (ISCED 01 and ISCED 02) is administered under the responsibility of the Ministry of Health and Welfare.
3. In England, Scotland and Northern Ireland the entire ECEC system is the responsibility of the education ministry, but for Wales ECEC services
for younger children is the responsibility of the health and welfare ministry.
4. In ISCED 02, the health and welfare authority has also an important role.
5. For 3-year-olds, the welfare authority is responsible for ECEC, except for targeted programmes where the education authority is responsible. For
ages 4 and 5, the education authority is responsible for ECEC.
6. Tageseltern, Kinderkrippe and Kindergarten are governed by regional legislation; regarding Vorschulstufe (ISCED 02) education authority is
responsible.
7. The entire ECEC system is under the authority of the Inter-sectoral Commission for Early Childhood, composed by different sectors
8. The Department of Children and Youth Affairs, in collaboration with the Department of Education and Skills, has overall responsibility for policy in
relation to ECEC.
Source: INES ad-hoc survey. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).

Ten out of the 36 countries with available data have what is called a “split system”. In many countries with a
split system, policies for care and early education have developed separately and fall under the responsibility
of different authorities. In these countries, ECEC services for children under the age of 3 are often under the

EDUCATION AT A GLANCE 2019 © OECD 2019

168  B2. HOW DO EARLY CHILDHOOD EDUCATION SYSTEMS DIFFER AROUND THE WORLD?
authority of the social affairs, family, or health and welfare ministries, while settings providing ECEC for older
children are under the authority of the education ministry. In countries with split systems, different quality
standards are often set for different ECEC settings or for different ages. ECEC services for children under the
age of 3 are also often outside the scope of ISCED 0 in these countries. In contrast, in all countries with an
integrated system, the same quality standards are applied to any ECEC setting.
Finally, in a third group of countries, multiple authorities (which may vary depending on regional arrangements)
administer the entire ECEC system (ISCED 01 and ISCED 02) and ECEC services are for most of them in
adherence with ISCED 0 criteria. Countries in this group are often federal countries. For instance, early
childhood development services (ISCED 01) are governed by regional legislations in Austria while
Vorschulstufe (ISCED 02) falls under the responsibility of the ministry of education. In Ireland, the Department
of Children and Youth Affairs, in collaboration with the Department of Education and Skills, has overall
responsibility for policy in relation to ECEC. Finally, Germany concentrates responsibility for the entire ECEC
age bracket on the welfare sector, under the auspices of the Federal Ministry of Family Affairs, Senior Citizens,
Women and Youth, as well as the federal states and municipalities. Most of the countries in this group have
an integrated curriculum including intentional education objectives starting from the ages of 0 or 1 until the
beginning of primary school (OECD, 2017[1]).
In principle, children should not have any difficulty making the transition from childcare to early education in
countries with integrated administration of early childhood services, where there is generally a common
curriculum for children aged 1 to 5 years, which applies to the majority of countries with available data. In
contrast, there can be fundamental differences in goals, means and quality between the childcare and early
education sectors in countries operating split or two-tier early childhood systems. The result can be a lack of
coherence for children and families, with confusing differences in objectives, funding streams, operational
procedures, regulatory frameworks, and staff training and qualifications.

Staffing of early childhood education and care
Minimum qualifications among ECEC teaching staff
Prospective teachers should be provided with high-quality initial training. The type of qualification, duration of
training and the programme content provided can influence how well initial teacher education prepares teachers
for their role. Evidence from the literature shows that the level and duration of initial staff training are positively
associated with overall ECEC quality (Manning, 2017[12]). Highly qualified staff result in a more stimulating
environment and high-quality pedagogical practices, which boost children’s well-being and learning outcomes
(Litjens, 2010[13]).
The qualification awarded at the completion of a teacher-training programme for almost all ECEC teaching staff
is a tertiary qualification. In 19 out of the 25 countries with available data, an individual can teach in ECEC
(ISCED 0) after earning at least a bachelor’s degree or equivalent (ISCED level 6) at the end of their initial teacher
education. However, there are some exceptions. In the Slovak Republic, pre-primary teachers can start teaching
with an upper secondary diploma, but an increasing number of teachers now have a bachelor’s or a master’s
degree. In Germany, they can begin teaching after graduating from a tertiary vocational programme (e.g.
Erzieherausbildung, ISCED 6); in Austria and Israel, they typically graduate at ISCED level 5 after a two-year
short-cycle tertiary programme. At the other end of spectrum, in France, Poland and Portugal pre-primary school
teachers are required to have a master’s degree or equivalent (ISCED level 7), For France, since school year
2010/2011, each student who wants to become an ECEC or primary teacher must obtain a master's degree or
equivalent (Table B2.3).
However, no matter how high the quality of pre-service training, it cannot be expected to prepare teachers for all
the challenges they will face throughout their careers. Given the changes in student demographics, the length of
most teachers’ careers, and the need to update knowledge and competencies, initial teacher education must only
EDUCATION AT A GLANCE 2019 © OECD 2019

B2. HOW DO EARLY CHILDHOOD EDUCATION SYSTEMS DIFFER AROUND THE WORLD?  169

be viewed as the starting point for teachers’ ongoing development. Recent research also shows that in preprimary education, the effects of specialised in-service training on process quality are greater than those of preservice training, particularly when it comes to collaborative work, support for play and support for early literacy,
mathematics and science (Assel, 2006[14]; de Haan, 2013[15]).

Child-staff ratios
Research demonstrates that enriched, stimulating environments and high-quality pedagogy are fostered by
better-qualified 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[16]).
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 16 children for every teacher working in pre-primary education but wide variations are
observed across countries. Thus, the child-teaching staff ratio, excluding teachers’ aides, ranges from more than
20 children per teacher in Brazil, Chile, Colombia, France, Israel, Mexico and the United Kingdom to less than 10
in Finland and Germany (Table B2.3).

Figure B2.4. Ratio of children to staff in pre-primary (ISCED 02) education (2017)
Public and private institutions, calculation based on full-time equivalents

Note: Figures in parentheses show the percentages of teachers' aides among ECEC contact staff (teachers and teachers' aides).
1. Excluding independent private institutions. Data on teachers are not comparable with previous years due to a new methodology introduced.
2. Data on staff do not cover all ECEC services.
3. ISCED 0 instead of pre-primary education (ISCED 02).
Countries are ranked in descending order of the ratio of children to teaching staff in pre-primary education.
Source: OECD (2019). Table B2.3. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933977904

EDUCATION AT A GLANCE 2019 © OECD 2019

170  B2. HOW DO EARLY CHILDHOOD EDUCATION SYSTEMS DIFFER AROUND THE WORLD?
Some countries – Austria, Chile, France, Israel, Lithuania, Norway, Sweden and the United Kingdom – also make
extensive use of teachers' aides, which can be seen from the smaller ratios of children to contact staff than of
children to teaching staff. Teachers' aides assist teachers in their daily tasks and deal with children with special
needs. In most countries, they have an upper secondary qualification, often vocationally oriented (Table B2.3
and Figure B2.4).
Child-to-staff ratio matters more for interactions with children under the age of 3 than for 3-5 year-olds (OECD,
2018[16]). In most countries, the ratios of children to contact staff (teachers and teachers’ aides) are smaller in
early childhood development programmes than in pre-primary education. On average across the 13 OECD
countries with available data for both programmes, there are 12 children for every contact staff working in preprimary education, while the ratio is only 5 children per teacher in early childhood development (Table B2.3).
However, the number of hours per week that represent typical full-time enrolment in an education programme at
ISCED level 0 varies widely between countries. Because of this, figures should be interpreted with caution
(see Methodology section).

Definitions
Adults refer to 25-64 year-olds.
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[1]) and
Table B2.5):


Regular centre-based ECEC: More formalised ECEC centres typically belong to one of these three subcategories:
o

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.

o

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.

o

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 childcare 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 childcare 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. Table B2.5 makes 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 01 refers to early childhood educational development services, typically aimed at children under the age
of 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
EDUCATION AT A GLANCE 2019 © OECD 2019

B2. HOW DO EARLY CHILDHOOD EDUCATION SYSTEMS DIFFER AROUND THE WORLD?  171

opportunities for active play so that children can exercise their co-ordination and motor skills under supervision
and in interaction with staff.
ISCED 02 refers to pre-primary education, aimed at children in the years immediately prior to starting compulsory
schooling, typically aged between the ages of 3 and 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.
For data-reporting purposes, data from age-integrated programmes designed to include children younger and
older than 3 are allocated to levels 01 and 02 according to the age of the children. This may involve the estimation
of expenditure and personnel at levels 01 and 02.
Teachers and comparable practitioners: Teachers have the most responsibility for a group of children at the
class or playroom level. They may also be called pedagogue, educator, childcare practitioner or pedagogical staff
in education, while the term teacher is almost universally used at the primary level.
Teachers’ aides: Aides support the teacher in a group of children or class. They usually have lower qualification
requirements than teachers, which may range from no formal requirements to, for instance, vocational education
and training. This category is only included in the Education at a Glance indicator on children-to-staff ratio.
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
Enrolment rates
Net enrolment rates are calculated by dividing the number of students of a particular age group enrolled in ECEC
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 and different sources used in some countries
resulting in enrolment rates exceeding 100%.

Full-time and part-time children
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 levels 01 and 02 according to the age of the children. This may involve the estimation of expenditure
and personnel at levels 01 and 02.
For more information please see the OECD Handbook for Internationally Comparative Education Statistics
(OECD, 2018[17]) and Annex 3 for country-specific notes (https://doi.org/10.1787/f8d7880d-en).

EDUCATION AT A GLANCE 2019 © OECD 2019

172  B2. HOW DO EARLY CHILDHOOD EDUCATION SYSTEMS DIFFER AROUND THE WORLD?
Estimated expenditure for all children aged 3 to 5 enrolled in ECEC and primary education
The calculation of this new measure is based on the distribution of children aged 3 to 5 enrolled in ISCED 01,
ISCED 02 and primary education (ISCED 1). For each country, the calculation was based on what proportion of
all children enrolled at each of these three ISCED levels were aged 3 to 5. For instance, in Australia, children
aged 3 to 5 accounted for 5% of all children enrolled in ISCED 01, 99% of all children enrolled in ISCED 02 and
12% of all children enrolled in ISCED 1. These percentages were used to estimate total expenditure for all
children aged 3 to 5 enrolled in ECEC and primary education. Total expenditure for all children aged 3 to 5 are
calculated by: 5% of all expenditure in ISCED 01 and 99% of all expenditure in ISCED 02 and 12% of all
expenditure in ISCED 1. A similar calculation was made for all countries.

Source
Data refer to the reference year 2017 (school year 2016/17) and financial year 2016.
Data from Argentina, the People’s Republic of China, India, Indonesia, Saudi Arabia and South Africa are from
the UNESCO Institute of Statistics (UIS).
Data are based on the UNESCO-UIS/OECD/EUROSTAT data collection on education statistics administered by
the OECD in 2018 (for details, see Annex 3 at https://doi.org/10.1787/f8d7880d-en) and on a special survey
administered by the OECD in 2018.
Data on subnational regions for selected indicators are available in the OECD Regional database (OECD,
2019[8]).
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
Assel, M. (2006), “An evaluation of curriculum, setting, and mentoring on the performance of children
enrolled in prekindergarten””, Reading and Writing, Vol. 20/5, pp. 463-494,
http://dx.doi.org/10.1007/s11145-006-9039-5.

[14]

de Haan, A. (2013), “Targeted versus mixed preschools and kindergartens: Effects of class
composition and teacher-managed activities on disadvantaged children’s emergent academic
skills”, School Effectiveness and School Improvement, Vol. 24/2,
https://doi.org/10.1080/09243453.2012.749792.

[15]

Duncan, G. and K. Magnuson (2013), “Investing in preschool programs”, Journal of Economic
Perspectives, Vol. 27/2, pp. 109-132, http://dx.doi.org/10.1257/jep.27.2.109.

[5]

Litjens, I. (2010), Literature overview for the 7th meeting of the OECD network on early childhood
education, OECD, Paris.

[13]

Manning, M. (2017), The relationship between teacher qualification and the quality of the early
childhood education and care environment”, Campbell Systematic Reviews,Vol. 1, pp. 1-82,
http://dx.doi.org/10.4073/csr.2017.1.

[12]

EDUCATION AT A GLANCE 2019 © OECD 2019

B2. HOW DO EARLY CHILDHOOD EDUCATION SYSTEMS DIFFER AROUND THE WORLD?  173

OECD (2019), OECD Regional Statistics Database - Enrolment rate by age,
http://stats.oecd.org/Index.aspx?DataSetCode=REGION_EDUCAT.

[8]

OECD (2018), Education at a Glance 2018: OECD Indicators, OECD Publishing, Paris,
https://dx.doi.org/10.1787/eag-2018-en.

[10]

OECD (2018), Engaging Young Children: Lessons from Research about Quality in Early Childhood
Education and Care, Starting Strong, OECD Publishing, Paris,
http://dx.doi.org/10.1787/9789264085145-en.

[16]

OECD (2018), “How does access to early childhood education services affect the participation of
women in the labour market?”, Education Indicators in Focus, No. 59, OECD Publishing, Paris,
http://dx.doi.org/10.1787/232211ca-en.

[2]

OECD (2018), OECD Family Database, http://www.oecd.org/els/family/database.htm.

[7]

OECD (2018), OECD Handbook for Internationally Comparative Education Statistics: Concepts,
Standards, Definitions and Classifications, OECD Publishing, Paris,
https://doi.org/10.1787/9789264304444-en.

[17]

OECD (2018), OECD Online education database, http://www.oecd.org/education/database.htm.

[11]

OECD (2017), Starting Strong 2017: Key OECD Indicators on Early Childhood Education and Care,
Starting Strong, OECD Publishing, Paris, http://dx.doi.org/10.1787/9789264276116-en.

[1]

OECD (2016), Walking the Tightrope: Background Brief on Parents’ Work-Life Balance across the
Stages of Childhood, OECD, Paris, http://www.oecd.org/social/family/Background-brief-parentswork-life-balance-stages-childhood.pdf.

[4]

OECD (2011), How’s Life?: Measuring Well-being, OECD Publishing, Paris,
https://dx.doi.org/10.1787/9789264121164-en.

[3]

OECD/Eurostat/UNESCO Institute for Statistics (2015), ISCED 2011 Operational Manual: Guidelines
for Classifying National Education Programmes and Related Qualifications, OECD Publishing,
Paris, http://dx.doi.org/10.1787/9789264228368-en.

[6]

OECD/NCES (2018), Education at a Glance Subnational Supplement, OECD/National Center for
Education Statistics, Paris and Washington, DC,, https://nces.ed.gov/suveys/annualreports/oecd/.

[18]

Shin, E., M. Jung and E. Park (2009), A Survey on the Development of the Pre-school Free Service
Model, Korean Educational Development Institute.

[9]

Indicator B2 Tables
Table B2.1

Enrolment rates of children under the age of 3 in early childhood education and care, by type
of service and age (2005, 2010 and 2017)

Table B2.2

Enrolment rates in early childhood education and care (ECEC) and primary education, by age
(2005, 2010 and 2017)

EDUCATION AT A GLANCE 2019 © OECD 2019

174  B2. HOW DO EARLY CHILDHOOD EDUCATION SYSTEMS DIFFER AROUND THE WORLD?
Table B2.3

Enrolment of children in early childhood education and care (ISCED 0) in private institutions,
ratio of children to teaching staff and minimum qualification of ECEC staff (2017)

Table B2.4

Financing of early childhood education and care (ISCED 0) and change in expenditure as a
percentage of GDP (2012 and 2016)

WEB Table B2.5 Coverage of early childhood education and care in OECD and partner countries
Cut-off date for the data: 19 July 2019. 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.
StatLink: https://doi.org/10.1787/888933980944

EDUCATION AT A GLANCE 2019 © OECD 2019

B2. HOW DO EARLY CHILDHOOD EDUCATION SYSTEMS DIFFER AROUND THE WORLD?  175

Table B2.1. Enrolment rates of children under the age of 3 in early childhood education and care, by type of service and age
(2005, 2010 and 2017)
Public and private institutions

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 the 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 "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 2016 instead of 2017.
3. Year of reference 2012 instead of 2010.
Source: OECD/UIS/Eurostat (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
StatLink 2 https://doi.org/10.1787/888933977771
EDUCATION AT A GLANCE 2019 © OECD 2019

176  B2. HOW DO EARLY CHILDHOOD EDUCATION SYSTEMS DIFFER AROUND THE WORLD?
Table B2.2. Enrolment rates in early childhood education and care (ECEC) and primary education, by age (2005, 2010 and 2017)
Public and private institutions, from age 3 to age 6

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 the relevant national authorities (e.g. curriculum); and 5) have trained or accredited staff (e.g. requirement of pedagogical qualifications for educators).
1. ECEC data include only part of the children enrolled in early childhood development programmes (ISCED 01).
2. Year of reference 2016 instead of 2017.
3. Year of reference 2012 instead of 2010.
Source: OECD/UIS/Eurostat (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
StatLink 2 https://doi.org/10.1787/888933977790

EDUCATION AT A GLANCE 2019 © OECD 2019

B2. HOW DO EARLY CHILDHOOD EDUCATION SYSTEMS DIFFER AROUND THE WORLD?  177

Table B2.3. Enrolment of children in early childhood education and care (ISCED 0) in private institutions, ratio of children to
teaching staff and minimum qualification of ECEC staff (2017)

Note: Early childhood educational development programmes = ISCED 01, pre-primary education = ISCED 02; ISCED 5 = Short tertiary cycle; ISCED 6 = Bachelor’s degree
or equivalent; ISCED 7 = Master’s degree or equivalent.
1. France: Data for Columns 7 to 12 represent public and government-dependent private institutions only. Data on teachers are not comparable with previous years due to
a new methodology introduced. Israel and Switzerland: Public institutions only.
2. Data on staff do not cover all ECEC services.
3. The minimum qualification of ECEC staff is ISCED 6 in England and ISCED 5 in Scotland.
4. Year of reference 2016 instead of 2017.
Source: OECD/UIS/Eurostat (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
StatLink 2 https://doi.org/10.1787/888933977809
EDUCATION AT A GLANCE 2019 © OECD 2019

178  B2. HOW DO EARLY CHILDHOOD EDUCATION SYSTEMS DIFFER AROUND THE WORLD?
Table B2.4. Financing of early childhood education and care (ISCED 0) and change in expenditure as a percentage of GDP (2012 and 2016)
Public and private institutions

1. Year of reference 2017 instead of 2016.

2. Expenditure on all children aged 3 to 5 are underestimated due to the estimation method used.
3. Data on financing do not cover all ECEC services.
4. Public sources only.
Source: OECD/UIS/Eurostat (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
StatLink 2 https://doi.org/10.1787/888933977828
EDUCATION AT A GLANCE 2019 © OECD 2019

180  B3. WHO IS EXPECTED TO GRADUATE FROM UPPER SECONDARY EDUCATION?

Indicator B3. Who is expected to graduate from
upper secondary education?
Highlights


In almost all countries with available data, women represent at least half of upper secondary graduates
from general programmes. In contrast, women are under-represented in vocational programmes in
about seven out of ten countries with available data.



Across OECD countries, the average age of first-time graduation at upper secondary level is higher
for vocational programmes (21 years old) than for general programmes (18 years old), and much
higher for post-secondary non-tertiary vocational programmes (31 years old).



Current estimates indicate that on average, 86% of people across OECD countries will graduate from
upper secondary education in their lifetime, and 81% of people will do so before the age of 25.

Figure B3.1 Average age of first-time upper secondary and post-secondary non-tertiary graduates, by
programme orientation (2017)

1. Year of reference 2016.
Countries are ranked in descending order of the average age of first time graduates from upper secondary vocational programmes.
Source: OECD/UIS/Eurostat (2019), data could slightly differ from Tables B3.1 and B3.2 as they refer to first-time graduates. See Source section
for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933977999

Context
Upper secondary education, defined as the second stage of learning after completing lower secondary
education, is essential for both pursuing further levels of education and successful labour market integration.
It can be either vocational or general and provided in both public and private schools, or in vocational and
technical institutes. In many countries, this level of education is not compulsory and can last from two to five

EDUCATION AT A GLANCE 2019 © OECD 2019

B3. WHO IS EXPECTED TO GRADUATE FROM UPPER SECONDARY EDUCATION?  181

years. Post-secondary non-tertiary programmes straddle upper secondary and post-secondary education and
may be considered either upper secondary or post-secondary programmes, depending on the country.
In most developed countries, almost all students in lower secondary school enrol in upper secondary education
and most of them study in programmes providing access to tertiary education. In general, demand for upper
secondary education is increasing worldwide, with the development of a variety of educational pathways. In
fact, 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.

Other findings
●

The average age of graduates from vocational programmes varies considerably across countries,
particularly at upper secondary level. In Canada, the average age of graduates from upper secondary
vocational programmes is 32 years old compared with 16 in Colombia.

●

On average across OECD countries, first-time graduation rates increased by 2 percentage points at
the upper secondary level and remained constant at the post-secondary non-tertiary level, between
2010 and 2017.

●

On average across OECD countries, women represent 54% of post-secondary non-tertiary graduates;
however, variations across countries are significant, ranging from 19% in Luxembourg to 75% in
Austria and Poland.

Note
Graduation rates, when calculated for all ages, represent the estimated percentage of people from a given
age cohort who are expected to graduate within the country at some point during their lifetime. This estimate
is based on the number of graduates in 2017 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.
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 when measuring average age, share of
female graduates and graduates by field of study (see Definitions section).

EDUCATION AT A GLANCE 2019 © OECD 2019

182  B3. WHO IS EXPECTED TO GRADUATE FROM UPPER SECONDARY EDUCATION?

Analysis
Profile of upper secondary graduates
Profile of upper secondary graduates, by programme orientation
Although many countries have developed extensive vocational programmes at the secondary level, in most
countries, fewer students pursue vocational programmes than general programmes. On average across OECD
countries, 40% 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, Hungary, Iceland, Japan, Korea and Lithuania (below 25%). In contrast, in Austria,
the Czech Republic, the Slovak Republic and Slovenia, more than 65% of 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). In some countries, VET has been neglected and
marginalised in policy discussions, often overshadowed by the increasing emphasis on general academic
education. However, participating in an initial VET programme has both, micro and macro beneficial outcomes:
the opportunity to acquire qualifications, integration into the labour market with a satisfactory wage, further career
development opportunities, professional status and economic competitiveness (CEDEFOP, 2011[1]).
It has been also found that VET has a positive effect on graduates' employability, because of their early entry
into the labour market. The transition to work is faster for upper secondary graduates from vocational programmes
than those enrolled in general programmes; they are more likely to get a permanent first job and are less likely
to find themselves in a first job with a qualification mismatch. At a time when professional experience is often a
requirement to enter the labour market, vocational upper secondary graduates have an advantage over those
with little or no professional experience. However, at tertiary level the opposite pattern is found: technical
graduates have to search significantly longer for a job than academic graduates in the European Union, mainly
because tertiary technical programmes develop more specific skills that lead to a relatively longer search for the
correct match (CEDEFOP, 2013[2]).
Vocational programmes can be offered in combined school- and work-based programmes, where 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, 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, Norway and Switzerland, this type of dual system attracts
at least 30% of the students enrolled in upper secondary VET programmes (see the Education at a Glance
Database). Through work-based learning, students acquire the skills that are valued in the workplace. Workbased learning is also a way to develop public-private 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. 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 from
general programmes, compared to 48% for vocational programmes.

EDUCATION AT A GLANCE 2019 © OECD 2019

B3. WHO IS EXPECTED TO GRADUATE FROM UPPER SECONDARY EDUCATION?  183

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 61% in the Czech Republic and the Slovak Republic, and
62% in Italy. In contrast, women are under-represented in vocational programmes in about seven out of ten
countries with available data (Figure B3.2).

Figure B3.2. Share of women among upper secondary graduates, by programme orientation (2017)

Countries are ranked in descending order of the share of women in general programmes.
Source: OECD/UIS/Eurostat (2019), Education at a Glance Database, http://stats.oecd.org/. See Source section for more information and Annex 3
for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933978018

There is, however, significant cross-country variation in vocational programmes. The share of women ranges
from less than 36% in Estonia and Lithuania to 63% in New Zealand. In fact, New Zealand is one of just five
countries (i.e. Brazil, Colombia, Ireland and the United Kingdom) where women make up a higher share of
graduates in vocational programmes than in general programmes. In these countries, the difference between the
share of women in vocational and general programmes ranges from less than 4 percentage points in Brazil,
Colombia and the United Kingdom to over 10 percentage points in Ireland and New Zealand (Figure B3.2).

Profile of upper secondary vocational graduates, by field of study
On average across OECD countries, 33% of graduates from upper secondary vocational programmes earn a
qualification in the field of engineering, manufacturing and construction. This falls to 18% for business,
administration and law, and 11% for health and welfare. However, this pattern does not hold for every country.
In Chile, Estonia, Hungary, Iceland and Lithuania nearly 50% of students graduate with a specialisation in
engineering, manufacturing and construction. In contrast, business, administration and law is the most popular
field in upper secondary vocational programmes for Brazil, Luxembourg and Switzerland. In Denmark, the
Netherlands, Spain and the United Kingdom, the field of health and welfare is the most popular (Figure B3.3).
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 82% of graduates on average. In fact,
in health and welfare, the share of female graduates exceeds 75% in all countries except Latvia (71%), Poland
(56%), Slovenia (73%) and Sweden (72%). Between these two extremes, there is more gender balance in the
field of services where, on average, 61% of graduates are women, and in business, administration and law, where
65% of graduates are women (Table B3.1).

EDUCATION AT A GLANCE 2019 © OECD 2019

184  B3. WHO IS EXPECTED TO GRADUATE FROM UPPER SECONDARY EDUCATION?

Figure B3.3 Distribution of upper secondary vocational graduates by selected field of study (2017)

1. Year of reference 2016.
Countries are ranked in descending order of the share of engineering, manufacturing and construction graduates.
Source: OECD/UIS/Eurostat (2019), Table B3.1. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933978037

Gender gaps in fields of study may be partly due 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[3]).

Profile of upper secondary vocational graduates, by age
The average age of upper secondary graduates tends to be older for vocational programmes than general
programmes. On average across OECD countries, first-time upper secondary graduates obtain their qualification
at the age of 21 in vocational programmes, compared to 18 in general programmes (Figure B3.1).
However, there is some variation across countries. In Canada, Denmark, Iceland and Norway, the average
graduation age is significantly higher for vocational programmes than general ones, with a difference of at least
seven years. In contrast, in Chile, Colombia and Poland, students graduate from general programmes at least
one year later than from vocational programmes. In the Czech Republic, Israel, Korea, Mexico, Portugal,
the Slovak Republic, Sweden and Turkey, the average graduation age is the same for both general and
vocational programmes (Figure B3.1).
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 could contribute to the higher graduation age for vocational programmes (OECD Education
GPS, 2018[4]).

EDUCATION AT A GLANCE 2019 © OECD 2019

B3. WHO IS EXPECTED TO GRADUATE FROM UPPER SECONDARY EDUCATION?  185

Profile of post-secondary non-tertiary graduates
Various kinds of post-secondary non-tertiary programmes (ISCED level 4) are offered in OECD countries. These
programmes straddle upper secondary and post-secondary education and may be considered either upper
secondary or post-secondary 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. However about 13 countries do not offer
programmes at post-secondary non-tertiary level of education.

Profile of post-secondary non-tertiary graduates, by programme orientation
On average across OECD countries, around 94% of post-secondary non-tertiary first-time graduates have
graduated from vocational programmes. Professionalisation is particularly high at this level of education as
post-secondary non-tertiary programmes are most often designed for direct labour market entry. There are some
national initiatives to provide general programmes at post-secondary non-tertiary level to target students who
have completed a vocational upper secondary level and want to increase their chances of entering tertiary
education. For instance, in Switzerland, a one-year general programme – Programme Passerelle DUBS –
prepares graduates from vocational upper secondary education to enter general programmes at the tertiary level
(OECD/Eurostat/UNESCO Institute for Statistics, 2015[5])

Profile of post-secondary non-tertiary graduates, by age
The average age of first-time graduates from vocational programmes tends to be higher for post-secondary
non-tertiary education than for upper secondary education. On average across OECD countries, first-time upper
secondary vocational graduates obtain their qualification at the age of 21, compared to 31 for vocational
post-secondary non-tertiary programmes. However, significant variation exists across countries: whereas for
some countries, such as Germany, Hungary and Belgium, there is a difference of only two years between the
average age of first-time graduation from upper secondary and post-secondary non-tertiary education, for others,
such as Finland, Spain and Sweden, the difference is more than 14 years (Figure B3.1).
This pattern could be partially explained by the fact that some countries have developed lifelong learning
strategies. In fact, some countries are progressively developing pathways for adults in their VET strategy. In
Denmark, Adult Vocational training (AMU) aims to provide adults with skills and competencies relevant to the
labour market. The programmes help learners either deepen their existing knowledge in a particular field or
develop new knowledge in related fields (CEDEFOP, 2019[6]).

Profile of post-secondary non-tertiary graduates, by field of study
On average across OECD countries, 21% of post-secondary non-tertiary graduates in vocational programmes
specialised in health and welfare, 21% in services followed by 20% for business, administration and law; and
19% for engineering, manufacturing and construction. However, this pattern is not always repeated across
countries. In Luxembourg, for instance, 80% of post-secondary non-tertiary graduates obtained a qualification in
engineering, manufacturing and construction whereas in Austria the share is only 1% (Table B3.2).

Profile of post-secondary non-tertiary graduates, by gender
On average across OECD countries, women make up 54% of post-secondary non-tertiary graduates but there
are significant variations across countries, with the share ranging from 19% in Luxembourg to 75% in Austria and
Poland.
In almost all countries with available data, women make up more than half of post-secondary non-tertiary
graduates from vocational programmes, except in Australia, Belgium, the Czech Republic, Denmark, Iceland,
Luxembourg, Portugal and the Russian Federation. The percentage of women pursuing a programme in

EDUCATION AT A GLANCE 2019 © OECD 2019

186  B3. WHO IS EXPECTED TO GRADUATE FROM UPPER SECONDARY EDUCATION?
engineering, manufacturing and construction is low at the post-secondary non-tertiary level: they make up only
18% of graduates in this field. In contrast, women are over-represented in health and welfare, where the share
of female graduates is 75% or more in all countries, except Australia (70%). There is more gender balance in the
field of services, where on average 57% of graduates are women, and business, administration and law, where
the figure is 66% (Table B3.2).

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 Indicator A5).
Graduation rates offer an indication of whether government initiatives have been successful in increasing the
share 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, 86% of people across OECD countries will graduate from upper
secondary education in their lifetime, and 81% of people will do so before the age of 25. First-time graduation
rates for those under 25 exceed 80% in more than half of OECD countries with available data, with values ranging
from 60% in Mexico to over 90% in Greece, Korea and Slovenia (Table B3.3).
The higher graduation rates for general programmes may reflect the lower share of students enrolled in upper
secondary vocational programmes than in general programmes (see Indicator B1), along with lower completion
rates for vocational education (Box B3.1 in (OECD, 2017[7])).
In countries with available data, the first-time upper secondary graduation rate for those below the age of 25
increased by 2 percentage points between 2010 and 2017. The increase was striking in three countries: Spain,
Turkey (both 18 percentage points) and Mexico (15 percentage points). In contrast, the first-time graduation rate
for those under 25 fell by 5 percentage points in Austria, Lithuania and Sweden and by 13 percentage points in
the Slovak Republic over the same period (Table B3.3).
However, improved upper secondary graduation rates alone will not guarantee 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 upper secondary 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
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 a post-secondary non-tertiary programme over their lifetime. The only countries where first-time
graduation rates (for all ages) 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 2017, the first-time graduation rate (for people younger than 30) has
remained constant over the past decade, at around 3% 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 B3.3).

EDUCATION AT A GLANCE 2019 © OECD 2019

B3. WHO IS EXPECTED TO GRADUATE FROM UPPER SECONDARY EDUCATION?  187

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 firsttime 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 agespecific 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.
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- 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.
When an 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 2017 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.
Please see Annex 3 for country-specific notes (https://doi.org/10.1787/f8d7880d-en).

Source
Data refer to the academic year 2016/17 and are based on the UNESCO-UIS/OECD/EUROSTAT data collection
on education statistics administered by the OECD in 2018 (for details, see Annex 3 at
https://doi.org/10.1787/f8d7880d-en).

EDUCATION AT A GLANCE 2019 © OECD 2019

188  B3. WHO IS EXPECTED TO GRADUATE FROM UPPER SECONDARY EDUCATION?
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
CEDEFOP (2019), Spotlight on VET - 2018 Compilation: Vocational Education and Training Systems in
Europe, Publication Office of the European Union, Luxembourg.

[6]

CEDEFOP (2013), Labour Market Outcomes of Vocational Education in Europe, Publication Office of
the European Union, Luxembourg.

[2]

CEDEFOP (2011), The Benefits of Vocational Education and Training, Publication Office of the
European Union, Luxembourg.

[1]

OECD (2017), Education at a Glance 2017: OECD Indicators, OECD Publishing, Paris,
https://dx.doi.org/10.1787/eag-2017-en.

[7]

OECD (2015), The ABC of Gender Equality in Education: Aptitude, Behaviour, Confidence, PISA,
OECD Publishing, Paris, https://dx.doi.org/10.1787/9789264229945-en.

[3]

OECD Education GPS (2018), Diagram of the education system: Norway.

[4]

OECD/Eurostat/UNESCO Institute for Statistics (2015), ISCED 2011 Operational Manual: Guidelines
for Classifying National Education Programmes and Related Qualifications, OECD Publishing,
Paris, https://dx.doi.org/10.1787/9789264228368-en.

[5]

Indicator B3 Tables
Table B3.1

Profile of upper secondary graduates from vocational programmes (2017)

Table B3.2

Profile of post-secondary non-tertiary graduates from vocational programmes (2017)

Table B3.3

Trends in upper secondary and post-secondary non-tertiary first-time graduation rates (2005,
2010 and 2017)

Cut-off date for the data: 19 July 2019. Any updates on data can be found on line at
http://dx.doi.org/10.1787/eag-data-en. More breakdowns can be found at http://stats.oecd.org/, Education at
a Glance Database.
StatLink: https://doi.org/10.1787/888933980963

EDUCATION AT A GLANCE 2019 © OECD 2019

B3. WHO IS EXPECTED TO GRADUATE FROM UPPER SECONDARY EDUCATION?  189

Table B3.1. Profile of upper secondary graduates from vocational programmes (2017)

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 2016.
2. Includes post-secondary non-tertiary level.
Source: OECD/UIS/Eurostat (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
StatLink 2 https://doi.org/10.1787/888933977942

EDUCATION AT A GLANCE 2019 © OECD 2019

190  B3. WHO IS EXPECTED TO GRADUATE FROM UPPER SECONDARY EDUCATION?
Table B3.2. Profile of post-secondary non-tertiary graduates from vocational programmes (2017)

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 2016.
Source: OECD/UIS/Eurostat (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
StatLink 2 https://doi.org/10.1787/888933977961

EDUCATION AT A GLANCE 2019 © OECD 2019

B3. WHO IS EXPECTED TO GRADUATE FROM UPPER SECONDARY EDUCATION?  191

Table B3.3. Trends in upper secondary and post-secondary non-tertiary first-time graduation rates (2005, 2010 and 2017)

1. Year of reference 2016 instead of 2017.
Source: OECD/UIS/Eurostat (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
StatLink 2 https://doi.org/10.1787/888933977980

EDUCATION AT A GLANCE 2019 © OECD 2019

192  B4. WHO IS EXPECTED TO ENTER TERTIARY EDUCATION?

Indicator B4. Who is expected to enter tertiary
education?
Highlights


Bachelor’s programmes are the most common entry route into tertiary education. In 2017, more than
seven out of every ten first-time entrants into tertiary education were enrolled at bachelor’s level, two
at short-cycle tertiary level and less than one at master’s level on average across OECD countries.



Across OECD countries, the average age of new entrants was 22 at bachelor’s level and 21 at master’s
long first degrees (LFDs) level, which is younger than new entrants to short-cycle tertiary programmes
(25 years).



Women outnumber men among new entrants to short-cycle tertiary, bachelor’s programmes and
master’s LFDs. However, there are stark differences across fields of study: women are underrepresented in science, technology, engineering and mathematics (STEM) but over-represented in
health and welfare.

Figure B4.1. Distribution of first-time entrants into tertiary education, by level of education (2017)

1. Short-cycle tertiary: data refers to the Flemish Community of Belgium only.
Countries are ranked in descending order of percentage of first-time entrants into short-cycle tertiary programmes in 2017.
Source: OECD / UIS / Eurostat (2019), Table B4.1. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933978113

Context
Access to tertiary education plays an essential role in developing young adults’ skills so they can contribute
fully to society. Yet students’ profiles and academic aptitudes can be very diverse. Some people find academic
learning unappealing, too long, too uncertain. Not all students develop skills at the same pace, and the

EDUCATION AT A GLANCE 2019 © OECD 2019

B4. WHO IS EXPECTED TO ENTER TERTIARY EDUCATION?  193

traditional route of only entering tertiary education following an upper secondary general programme is
increasingly being challenged. At the same time, the sequencing of higher education within educational life
cycles has also seen changes. Students are more likely to postpone entry to higher education, take a gap
year, or alternate periods of employment with periods of study. Stimulating employment opportunities and
burgeoning economies have prompted students in some countries to defer education in favour of learning in
the workplace, particularly when financial support for study is limited. Lifelong learning is slowly emerging as
the new vision for education, enabling individuals to continually update their skills to meet volatile and
constantly evolving market demand.
To address the growing needs of a diverse population, some countries have progressively adapted their
tertiary-level programmes to ensure more learning flexibility to suit a wide range of students’ skills and learning
aptitudes. This includes building more pathways between upper secondary and tertiary programmes, including
those with a vocational orientation, but also expanding the types of programmes available to first-time tertiary
students: short-cycle tertiary programmes, bachelor’s programmes or long first degrees at master’s level. Each
education level and programme requires different skills at entry and addresses specific labour-market
demands. Flexible entrance criteria can support lifelong learning and second-chance programmes can offer
new opportunities to older students who might have dropped out of the education system or for those who
wish to develop new skills. Providing a range of educational options adapted to the needs and ambitions of
young adults also ensures a smoother transition from education to work.
The profile of first-time entrants to tertiary education provides an indication of the learning trajectories across
various tertiary levels and programmes. It also provides information about equity in access to tertiary
programmes. Entry rates estimate the proportion of people who are expected to enter a specific type of tertiary
education programme 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.

Other findings


On average across OECD countries, the share of international new entrants to master’s LFDs is 15%, greater
than for bachelor’s programmes (8%) and much more than for short-cycle tertiary programmes (5%).



On average across OECD countries, the share of female new entrants to bachelor’s and short-cycle
tertiary programmes is 53-54%, well below their share of 61% for master’s LFDs.



Based on current patterns, 58% of young adults on average across OECD countries are expected to
enter a bachelor’s or equivalent programme in their lifetime and 17% will enter a short-cycle tertiary
programme.

Note
Short-cycle tertiary and master’s long first degree programmes may not exist or are not prevalent in a number
of educational systems. To ensure relevant cross-country comparisons, the analysis of the distribution of new
or first-time entrants by gender, field of study or mobility at these levels of education only includes those
countries where at least 10% of new or first-time tertiary entrants are enrolled in such programmes.
Entry rates are sensitive to changes in the education system, such as the introduction of new programmes.
The rates can be very high, even exceeding 100%, during a period when there are unexpectedly high numbers
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 return to education through secondchance programmes can also boost entry rates.

EDUCATION AT A GLANCE 2019 © OECD 2019

194  B4. WHO IS EXPECTED TO ENTER TERTIARY EDUCATION?

Analysis
Pathways of new and first-time entrants into tertiary education
Students may enter tertiary education at three levels: short-cycle tertiary (ISCED 5), bachelor’s (ISCED 6) or
master’s level (ISCED 7). Each programme has specific entry requirements and develops a specific set of skills
relevant to the labour market. Bachelor’s programmes are the most common route into tertiary education, and
exist in all OECD countries. Short-cycle tertiary programmes are often designed to provide participants with
professional knowledge, skills and competencies. Typically, they are practically based, occupation-specific and
prepare students to enter the labour market directly. Short-cycle tertiary programmes have the double advantage
of offering reasonably priced higher education (as two-year programmes, their direct and foregone costs are
lower than four-year programmes – see Indicator A5) and a readily employable qualification, but they do not exist
in all countries.
First-time entry into tertiary education at master’s level mainly comprises students entering master’s long first
degrees (LFDs) and students entering a master's programme without a bachelor’s degree from the host country.
Master’s long first degrees are programmes of at least 5 years that prepare students for a first degree or
qualification and have equivalent complexity of content to a master’s programme. They include highly specialised
fields such as medicine, dentistry or, in some cases, law and engineering (OECD/Eurostat/UNESCO Institute for
Statistics, 2015[1]). In the United Kingdom, where master’s LFDs are not available, first-time tertiary entrants at
master's level are students entering the level based on industry experience rather than academic qualifications.

Distribution of first-time tertiary entrants
The level at which students first enter tertiary education helps determine the length of their studies and the
employment or further learning opportunities they will have access to following their degree. The distribution
pattern of students across each tertiary entry-level programme depends on each programme’s availability,
capacity and entry requirements within the national education system.
On average across OECD countries, more than three-quarters of first-time tertiary entrants are enrolled in
bachelor’s programmes. However, the predominance of such programmes in the educational landscape varies
greatly from country to country. In Belgium, Finland, Greece, Iceland, India, Lithuania, Mexico, the Netherlands
and the Slovak Republic, more than 90% of first-time tertiary entrants enter bachelor’s programmes. In other
countries, first-time tertiary entrants are more evenly distributed across the various entry-level tertiary
programmes. For example, in Austria, Chile, the People’s Republic of China, the Russian Federation, Turkey and
the United States, 45% or more of first-time entrants into tertiary education entered short-cycle programmes,
more than twice the OECD average of 17%. Despite the benefits offered by these programmes, they do not exist
in all countries. Where they do, they are not always very attractive to students. In 11 OECD member and partner
countries where short-cycle tertiary programmes exist, less than 10% of first-time entrants into tertiary education
enrol in them (Figure B4.1).
Master's programmes are the least common entry point into tertiary level. On average across OECD member
and partner countries with available data, 7% of first-time entrants into tertiary education are in master's level
programmes, but this exceeds 20% in Sweden and Switzerland. In most countries, the majority of first-time
tertiary entrants at master's level enter through master’s LFDs. The share of first-time tertiary entrants at master's
level in countries where long first degrees are not available remains quite low: less than 2% in the United Kingdom
(Figure B4.1).

Age of new entrants to each tertiary level
Various factors can influence the age distribution of new entrants to each tertiary level. A wide age distribution
may reflect the existence of second chance and lifelong learning programmes characteristic of flexible pathways
allowing for re-entry into the education system. Delayed entry can indicate difficulties in access to tertiary
EDUCATION AT A GLANCE 2019 © OECD 2019

B4. WHO IS EXPECTED TO ENTER TERTIARY EDUCATION?  195

education, either through selective entry requirements (see Indicator D6), numerus clausus (a fixed maximum
number of entrants admissible to an academic institution), or financial challenges in affording the private costs
associated with higher education (see Indicator C5). From an economic point of view, delayed entry into tertiary
education can be costly to the public purse as adults postpone their entry into the labour market and hence the
time when they are typically able to start contributing financially to society (see Indicator A5).

Box B4.1. Transition between upper secondary and tertiary education
The growing flexibility of tertiary educational systems is reflected in the increasing availability of new learning
pathways and modalities. Part-time studies, online courses and allowing students to collect credits without
the intention of completing a degree are some examples of how tertiary programmes have been adapting to
a vision of education as lifelong learning. In this context, students in many countries may not be expected, or
even encouraged, to follow a direct path from upper secondary to tertiary education.
Figure B4.a shows the share of entrants to bachelor’s programmes who did not take at least one gap year
between upper secondary and tertiary education. In other words, it shows the share of entrants who moved
directly from upper secondary to tertiary education without any significant break. The share varies
considerably across countries, which highlights the diversity in the pool of tertiary entrants. While over 90%
of those who enter bachelor's programmes in the United States do so right after upper secondary education,
the same is true for only 20% of entrants in Finland and 3% of entrants in Israel.
This variation reflects important differences in institutional and social factors that are specific to each country.
In many countries, it is common for students to enter military or civil service after upper secondary education.
Students may also be led to take gap years because of highly selective tertiary entrance systems. In Finland,
for example, it is common for students to apply several times before being accepted by some tertiary
programmes (see Indicator D6), and the Finnish government has been actively trying to reduce the number
of years between graduation from upper secondary and entry to tertiary education. In other countries,
however, policies were put in place to actually encourage students to take gap years as a way to value
students’ experiences (e.g. work and civil or military service), before entering higher education. In Lithuania
and Norway, students who have taken a gap year gain some advantage in the tertiary admission systems
(e.g. bonus points are added to their competition score).
Entry into tertiary education can also be influenced by students’ upper secondary programme orientation. In
some countries, such as Estonia, Norway and Slovenia, entrants coming from vocational upper secondary
programmes are considerably more likely to have taken at least one gap year before entering tertiary
education than their peers with a general upper secondary degree. This could reflect the fact that students
who complete a vocational upper secondary programme may choose to enter the labour market before
pursuing a bachelor’s programme. It may also be because some vocational upper secondary qualifications
require students to take specific exams or supplementary courses before they can access tertiary education.
In other countries, however, bachelor’s students from general and vocational upper secondary education are
equally likely to have taken gap years before entering the programme. This is the case, for example, in the
Flemish and French communities of Belgium and in the Netherlands.
It is important, however, to look beyond averages when analysing students’ transition from upper secondary
to tertiary education. While flexibility and permeability may be important characteristics of education systems,
country averages could mask underlying problems faced by disadvantaged students or at-risk groups during
this transition period. It is also important to examine students’ pathways after entering tertiary education, and
how their educational and social background may influence their ability to succeed at this level (see
Indicator B5).

EDUCATION AT A GLANCE 2019 © OECD 2019

196  B4. WHO IS EXPECTED TO ENTER TERTIARY EDUCATION?

Figure B4.a. Share of entrants to bachelor's programmes who entered directly from upper secondary
education, by upper secondary programme orientation

How to read this figure: In Estonia, about 76% of entrants to bachelor's or equivalent programmes with a general upper secondary degree entered
directly from upper secondary education. The same is true for about 40% of entrants with a vocational upper secondary education and 70% of all
entrants (with general or vocational upper secondary degrees).
Note: Data in the figure come from an ad-hoc survey on tertiary completion rates, which followed a cohort of students from entry into bachelor's
programmes until three years after the end of the programme's theoretical duration. The reference year for the completion rate survey is 2017, but
the year of entry into bachelor's level depends on the theoretical duration of programmes available in each country. For nearly every country
presented in the figure, the data refer to students who entered bachelor's programmes in the period between 2010 and 2012. For the United States,
it refers to students who entered bachelor's programmes in 2003.
1. Data refer only to the Hautes Écoles (HE) and the Écoles des arts (ESA), representing about 60% of entrants to bachelor's or equivalent
programmes
2. Data disaggregated by programme orientation is based on an entry cohort that excludes students with unknown upper secondary qualification
and is therefore smaller than the total for "All programmes".
Countries are ranked in descending order of the share of students who entered tertiary education directly from upper secondary education, all
programmes
Source: Ad-hoc survey on tertiary completion rates OECD (2019). See Source section for more information and Annex 3 for notes
(https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933978170

The average age at entry to tertiary programmes also varies depending on the entry-level programme and the
student profile each programme tends to attract. Students tend to think about enrolling in bachelor’s or master’s
LFDs shortly after upper secondary school, while short-cycle tertiary programmes tend to attract older adults,
potentially with some employment experience. On average across OECD countries, the average age of new
entrants is 25 years for short-cycle tertiary programmes, 22 for bachelor’s programmes and 21 for master’s long
first degrees. However, there are large disparities among countries. The average age of new entrants to
bachelor’s programmes varies from 18-19 in Japan and Korea to 24 and over in Sweden and Switzerland. The
average age of new entrants to short-cycle tertiary programmes varies from 18 in Japan to 30 or older in Denmark,
Iceland, Ireland, Poland and Switzerland (Figure B4.2).

EDUCATION AT A GLANCE 2019 © OECD 2019

B4. WHO IS EXPECTED TO ENTER TERTIARY EDUCATION?  197

Structural factors, such as admission procedures, the typical age at which students graduate from upper
secondary education, or cultural perceptions of the value of professional or personal experiences outside of
education may explain the differences in the average age of entry to tertiary education across countries.
Traditionally, students entered tertiary programmes immediately after completing upper secondary education,
and this remains true in many cases. However, in a few countries, less than 25% of entrants to bachelor’s
programmes enrol straight after upper secondary (Box B4.1). This is the case in Israel, for example, where military
service is compulsory. In Finland and Sweden, admissions are also restricted for many programmes and fields
of study resulting in more than 60% of applicants being rejected (see Indicator D6). Countries with lower average
entry ages are also those where enrolment into tertiary programmes is more likely to follow directly after
graduation from upper secondary level. In some cases, this is facilitated by tertiary systems with open admissions,
such as in the Netherlands. In others, direct entry following upper secondary has also been fuelled by tertiary
expansion policies and a strong culture valuing academic achievement and educational attainment. For instance
in Japan, an increase in tertiary capacity since the 1970s, combined with specific policies to promote tertiary
attainment following the Japan Revitalisation Strategy, have led to higher enrolment rates in spite of selective
admission systems (OECD, 2009[2]).

Figure B4.2. Average age of new entrants by level of education (2017)

Note: Data for master's long first degree may rely on small sample sizes.
1. Short-cycle tertiary: data refers to the Flemish Community of Belgium only.
Countries are ranked in descending order of the average age for new entrants into bachelor's programmes in 2017.
Source: OECD/UIS/Eurostat (2019), Table B4.1. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933978132

Upper secondary programme orientation and the tertiary programme students enter also strongly influence the
average age of entry to tertiary level. In some countries, these programmes are specifically designed for adults
with work experience and may have specific entry requirements. For instance in Denmark, the
Akademiuddannelser, requires two years relevant work experience. Furthermore, these programmes tend to
appeal more to upper secondary vocational students who are more likely to delay entrance to tertiary education
because of their strong employment prospects from their upper secondary qualification.

EDUCATION AT A GLANCE 2019 © OECD 2019

198  B4. WHO IS EXPECTED TO ENTER TERTIARY EDUCATION?
Share of international students among new entrants at tertiary level
International students provide an additional income stream for educational institutions and contribute to the
economy of their host country (García, De and Villarreal, 2014[3]). Beyond the economic benefits, interaction
between domestic and international students promotes cultural understanding (culture, politics, religion, ethnicity
and worldview), and dialogue, all essential to navigating an increasingly globalised economy. On average across
OECD countries, international students make up 5% of new entrants to short-cycle tertiary programmes, rising
to 8% for bachelor’s programmes and 15% for master’s LFDs. The more limited share of international students
in short-cycle tertiary programmes could be due to the smaller number of countries providing such qualifications.
In contrast, bachelor’s and master’s programmes are recognised qualifications with good employment prospects
in all OECD countries.
Some countries are better than others at attracting international students. The share of international students
among new entrants to short-cycle tertiary programmes ranges from close to zero in Chile, Colombia, Sweden
and Turkey to 24% in New Zealand and 35% in Iceland. The share of international students among new entrants
to bachelor’s programme ranges from 2% or less in Chile, Colombia, Korea, Mexico and Spain to more than 30%
in New Zealand. The total share of international students entering a master’s LFD programme ranges from 3%
or less in Chile, Finland, Iceland, Norway and Sweden to 27% or more in the Czech Republic, Germany, Hungary,
Latvia and the Slovak Republic.

Distribution of new entrants by level of education and gender
Equal opportunities for both men and women to enter tertiary education can contribute to stronger, better and
fairer growth by raising the overall level of human capital and labour productivity (OECD, 2011[4]). However, the
expansion of tertiary education in OECD countries over the past decades has benefited women more than men:
51% of 25-34 year-old women now have a tertiary degree on average across OECD countries, up from 40% in
2008. In contrast, 38% of 25-34 year-old men were tertiary educated in 2018, an increase of 7 percentage points
since 2008 (see Indicator A1).
The gender divide is set to keep on growing as women also outnumber men among new entrants to each tertiary
level. On average across OECD countries, women represent 53% of new entrants at short-cycle tertiary level,
54% at bachelor’s level, and 61% at master’s level. At bachelor’s and master’s level in all countries, the share of
women is close to 50% or above. In some countries, men are particularly under-represented even at bachelor’s
level, which represents the most common entry route into tertiary education. In Iceland and Sweden, they make
up less than 40% of new entrants at this level. Short-cycle tertiary or master’s LFD levels are more influenced by
gender due to their specific focus on certain fields of study which tend to be associated with male or female
occupations. Master’s LFDs, which generally cover health or science programmes, tend to have a lower
enrolment rate among men, who make up 30% or less of the new entrants to the level in Slovenia, and
Switzerland. In contrast, men represent 60% or more of new entrants into short-cycle tertiary programmes in
Slovenia. These programmes are also strongly dominated by men in Italy, Mexico, Norway and Portugal although
they account for less than 10% of all first-time tertiary entrants (Table B4.1).
While many countries have promoted higher educational attainment for men and provided incentives to pursue
higher education, men have not responded. This may be partly due to the critical years before tertiary education,
when boys are more likely to struggle academically, repeat a grade, or drop out of school (OECD, 2017[5]; OECD,
2018[6]). This may also reflect differences in educational pathways at lower levels; for example, vocational training
tends to appeal to men more than women in some countries (see Indicator B3). Students from vocational upper
secondary programmes are indeed less likely to enter tertiary education, particularly at bachelor’s level: only 28%
of entrants to a bachelor’s programme graduated from an upper secondary vocational programme on average
across countries with available data (see Indicator B5). Short-cycle tertiary programmes provide more
educational opportunities at tertiary level for students from vocational tracks, but the availability of such
programmes is limited in a number of countries.

EDUCATION AT A GLANCE 2019 © OECD 2019

B4. WHO IS EXPECTED TO ENTER TERTIARY EDUCATION?  199

Fields of study of new entrants to each tertiary level
Students’ choice of field of study is guided by career opportunities and their aspirations after education. The
largest share of new entrants, one in four on average across OECD countries and across all tertiary levels,
entered the broad field of business, administration and law in 2017 (OECD, 2019[7]). In only six OECD countries
were different field of study more popular among new entrants: Belgium and Finland (health and welfare), Israel
(education), Italy (arts and humanities), and Korea and Sweden (engineering, manufacturing and construction).
Promoting the broad field of science, technology, engineering and mathematics (STEM) has become a priority in
many countries (OECD, 2017[8]). In addition to building the skills to drive innovation in technology and research,
science-related competencies such as problem solving and quantitative analysis are considered essential in
today’s unpredictable and data-driven economy and are in high demand in the labour market. On average across
OECD and partner countries, 27% of new entrants into bachelor’s programmes enrol in a STEM field, with the
largest shares in Germany (40%), the Russian Federation (35%), and Austria, Greece and Korea (34%) (Table
B4.2). Of those, adults who studied information and communication technologies (ICT) and engineering,
construction and manufacturing reap the greatest benefits in terms of employment (see Indicator A3) and
earnings (see Indicator A4). In spite of these strong labour-market outcomes, these fields still attract a smaller
share of students. On average across OECD countries and across all tertiary levels, 16% of new entrants enrol
in engineering, manufacturing and construction and 5% in ICT (OECD, 2019[7]).

Figure B4.3. Share of women first-time new entrants by level of education and field of study (2017)
OECD average

Source: OECD / UIS / Eurostat (2019), Table B4.2. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787//888933978151

Entry patterns by field of study reveal a strong gender bias. While the share of women new entrants has now
overtaken that of men, women are still under-represented in STEM fields of study and over-represented in health
and welfare across all tertiary levels. However, the gender difference varies across educational pathways and
tends towards greater gender equality among new entrants into master's LFDs in both these fields (Figure B4.3).
On average across OECD countries in 2017, 20% of new entrants to short-cycle tertiary programmes and 30%
of new entrants to bachelor’s programmes in STEM fields were women. Only master’s LFD programmes achieved
anything approaching gender parity in STEM fields, with 42% of women on average across OECD countries,
although this ranges from 33% in Sweden to 58% in Hungary and Italy (Table B4.2).
At the other end of the spectrum, women dominate in other fields of study such as health and welfare, although
their share tends to decrease with each additional educational level: women represent 79% of new entrants to
EDUCATION AT A GLANCE 2019 © OECD 2019

200  B4. WHO IS EXPECTED TO ENTER TERTIARY EDUCATION?
health and welfare short-cycle tertiary programmes, compared to 77% at bachelor's level and 64% for master's
long first degrees. Health and welfare mainly includes nursing and welfare in short-cycle tertiary or bachelor’s
programmes but mainly medical studies in master’s LFD programmes (Box B4.2).

Box B4.2. Graduates in health and welfare
The fields of study aggregated under health and welfare include a wide range of programmes: dental studies,
medicine, nursing and midwifery, medical diagnostic and treatment technology, therapy and rehabilitation,
pharmacy, etc. Some of these programmes require extensive studies, such as dental studies and medicine,
while others are more variable in length, such as nursing or welfare. Therefore, some of these programmes
are offered at short-cycle or bachelor’s level while others are exclusively offered through master’s long first
degrees. However, there are large differences among countries on the programmes offered to students at
various levels.

Figure B4.b Share of health and welfare graduates among all tertiary graduates, by field of study and
tertiary level (2017)
On average across OECD countries

Note: Other health and welfare includes: medical diagnostic and treatment technology, therapy and rehabilitation, traditional and complementary
medicine and therapy, health and welfare not further defined, and health and welfare not elsewhere classified.
Source: OECD/UIS/Eurostat (2019) and OECD/ILO/UIS (2019). See Source section for more information and Annex 3 for notes
(https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933978189

On average across OECD countries, health and welfare represents 19% of graduates from short-cycle tertiary
of which half come from nursing and midwifery programmes (Figure B4.b). Some countries offer programmes
at this level for only a few subjects. This is the case in Belgium and Poland where short-cycle programmes
are exclusively dedicated to nursing (in Belgium) and welfare (in Poland). Medicine and dental studies, which
are often considered longer studies, are offered as short-cycle tertiary programmes in some countries: the

EDUCATION AT A GLANCE 2019 © OECD 2019

B4. WHO IS EXPECTED TO ENTER TERTIARY EDUCATION?  201

field of medicine accounted for 10% of short-cycle tertiary graduates in Latvia and 2-3% in Colombia and
Spain, while 2-3% of short-cycle tertiary graduates specialised in dental studies in Korea and Sweden.
Medicine and dental studies make up the largest share of graduates from master’s long first degree
programmes: 34% for medicine and 7% for dental studies. Pharmacy, the third most prevalent field of study
contributes 6% of graduates (Figure B4.b). Again, there are large variations among countries. In Chile, Finland
and Iceland, all master’s long first degrees are in health but few students attend these programmes. In Japan,
Latvia, the Slovak Republic and Turkey, more than 80% of graduates from master’s long first degrees studied
health.
Health and welfare fields are less commonly pursued through bachelor’s programmes although this may differ
by country: 15% of bachelor’s graduates earned a degree in health and welfare on average across OECD
countries, rising to 30% or more Belgium and Denmark.

Entry rates into tertiary education
If current entry patterns continue, it is estimated that 65% of young adults will enter tertiary education for the first
time in their life on average across OECD countries. Chile (85%), New Zealand (89%), the Russian Federation
(88%), Saudi Arabia (87%) and Switzerland (82%) have the highest first-time tertiary entry rates among OECD
and partner countries with available data. The rates in these countries 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 the age of 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 for adults under 25 are similar in Austria and Switzerland (47%,
compared to the OECD average of 49%), but the total first-time entry rate in Switzerland is 14 percentage points
higher than in Austria, suggesting that the lower entry rate for those under 25 is more a question of deferred
entrance in Switzerland and of access in Austria. This is also corroborated by the average age of new entrants
to each tertiary level shown in Figure B4.2.
International students can significantly affect tertiary entry rates. For example in Australia, an attractive
destination country for international students, the entry rate for bachelor’s programmes falls from 94% to 77%
when international students are excluded, although it still has the highest entry rate in bachelor’s programmes
across OECD countries. Conversely, Luxembourg has the lowest entry rate across OECD countries (12% when
international students are removed), due to the large proportion of its citizens studying 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 first time.
First-time entrants into tertiary education are students who are enrolling in tertiary education for the first time,
without previous education at any other tertiary level. They may enter tertiary education at different levels through
short-cycle tertiary (ISCED 5), bachelor programmes (ISCED 6) or master’s programmes. First-time entrants
to a master’s programme can include entrants to a master’s long first degree (ISCED 7-LFD); entrants to a
stage of a programme at ISCED level 7 insufficient for level or partial level completion; foreign students entering
a master's programme (programme normally following a bachelor's) but without having completed a bachelor’s
EDUCATION AT A GLANCE 2019 © OECD 2019

202  B4. WHO IS EXPECTED TO ENTER TERTIARY EDUCATION?
degree in the host country; and students authorised to enter a master’s programme after validation of acquired
experience (VAE).
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 often considered first-time
entrants in that country.
Master's long first degree (LFD) is a master’s programme (ISCED 7-LFD) of 5 to 7 years that prepares for a
first degree or qualification that is equivalent to master’s level programme in terms of their complexity of content.
This includes highly specialised fields such as medicine, dentistry or, in some cases, law and engineering.
New entrants to a tertiary level of education are students who are enrolling for the first time at that tertiary
level but may have previously entered and completed a degree in another tertiary level of education.
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
Compared to enrolment, entry rates measure the inflow to education during a specific period and represent the
percentage of an age cohort who are expected to enter a tertiary programme during their lifetime. The net entry
rate for a specific age is obtained by dividing the number of new 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 or her lifetime if current age-specific entry rates continue.
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.
For more information, please see the OECD Handbook for Internationally Comparative Education Statistics 2018:
Concepts, Standards, Definitions and Classification (OECD, 2018[9]) and Annex 3 for country-specific notes
(https://doi.org/10.1787/f8d7880d-en).

Source
Data refer to the academic year 2016/17 and are based on the UNESCO-UIS/OECD/EUROSTAT data collection
on education statistics administered by the OECD in 2018. Data on the share of entrants to bachelor's
programmes who entered directly from upper secondary education, by upper secondary programme orientation
refer to the academic year 2016/17 and were collected through a special survey undertaken in 2018. Data for
some countries may have a different reference year. For details, see Annex 3 at
https://doi.org/10.1787/f8d7880d-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.

EDUCATION AT A GLANCE 2019 © OECD 2019

B4. WHO IS EXPECTED TO ENTER TERTIARY EDUCATION?  203

References
García, H., M. De and L. Villarreal (2014), “The redirecting of international students: American higher
education policy hindrances and implications”, Journal of International Students, Vol. 4/2, pp. 126136, https://doi.org/10.32674/jis.v4i2 (accessed on 16 May 2019).

[3]

OECD (2019), Education at a Glance Database, https://stats.oecd.org/ (accessed on 10 June 2019).

[7]

OECD (2018), Education at a Glance 2018: OECD Indicators, OECD Publishing, Paris,
https://dx.doi.org/10.1787/eag-2018-en.

[6]

OECD (2018), OECD Handbook for Internationally Comparative Education Statistics 2018: Concepts,
Standards, Definitions and Classifications, OECD Publishing, Paris,
https://dx.doi.org/10.1787/9789264304444-en.

[9]

OECD (2017), Education at a Glance 2017: OECD Indicators, OECD Publishing, Paris,
https://dx.doi.org/10.1787/eag-2017-en.

[5]

OECD (2017), The Pursuit of Gender Equality: An Uphill Battle, OECD Publishing, Paris,
https://dx.doi.org/10.1787/9789264281318-en.

[8]

OECD (2011), Report on the Gender Initiative: Gender Equality in Education, Employment and
Entrepreneurship, OECD, Paris, https://www.oecd.org/education/48111145.pdf (accessed on
16 May 2019).

[4]

OECD (2009), OECD Reviews of Tertiary Education: Japan 2009, OECD Reviews of Tertiary
Education, OECD Publishing, Paris, https://dx.doi.org/10.1787/9789264039322-en.

[2]

OECD/Eurostat/UNESCO Institute for Statistics (2015), ISCED 2011 Operational Manual: Guidelines
for Classifying National Education Programmes and Related Qualifications, OECD Publishing,
Paris, https://dx.doi.org/10.1787/9789264228368-en.

[1]

Indicator B4 Tables
Table B4.1

Profile of first-time entrants into tertiary education (2017)

Table B4.2

Distribution of new entrants by field of study, gender and tertiary level (2017)

Table B4.3

First-time entry rates, by tertiary level (2017)

Cut-off date for the data: 19 July 2019. 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.
StatLink: https://doi.org/10.1787/888933980982

EDUCATION AT A GLANCE 2019 © OECD 2019

204  B4. WHO IS EXPECTED TO ENTER TERTIARY EDUCATION?
Table B4.1. Profile of first-time entrants into tertiary education (2017)

Note: Columns 1 to 3 refer to first-time entrants into tertiary education by level attended. Columns 4 to 12 refer to new entrants in each ISCED level. See Definitions and
Methodology sections for more information. Data and more breakdowns available at http://stats.oecd.org/, Education at a Glance Database.
1. Short-cycle tertiary: data refers to the Flemish Community of Belgium only.
Source: OECD/UIS/Eurostat (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
StatLink 2 https://doi.org/10.1787/888933978056

EDUCATION AT A GLANCE 2019 © OECD 2019

B4. WHO IS EXPECTED TO ENTER TERTIARY EDUCATION?  205

Table B4.2. Distribution of new entrants by field of study, gender and tertiary level (2017)

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. Short-cycle tertiary: data refers to the Flemish Community of Belgium only.
2. All fields of study include the field Information and Communication Technologies (ICTs).
Source: OECD/UIS/Eurostat (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
StatLink 2 https://doi.org/10.1787/888933978075

EDUCATION AT A GLANCE 2019 © OECD 2019

206  B4. WHO IS EXPECTED TO ENTER TERTIARY EDUCATION?
Table B4.3. First-time entry rates, by tertiary level (2017)

1. Short-cycle tertiary: data refers to the Flemish Community of Belgium only.
Source: OECD/UIS/Eurostat (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
StatLink 2 https://doi.org/10.1787/888933978094

EDUCATION AT A GLANCE 2019 © OECD 2019

208  B5. HOW MANY STUDENTS COMPLETE TERTIARY EDUCATION?

Indicator B5. How many students complete
tertiary education?
Highlights


On average across countries with true cohort data (data on individual students), 39% of full-time
students who enter a bachelor’s programme graduate within the theoretical duration of the programme.
The average completion rate after three additional years increases to 67%.



The completion rate (within the theoretical duration of the programme plus three years) of students
with a general upper secondary degree (70%) is higher than that of students with a vocational upper
secondary degree (58%), on average across countries.



On average, 12% of students who enter a bachelor’s programme full time leave the tertiary system
before the beginning of their second year of study. This share increases to 20% by the end of the
programme’s theoretical duration and to 24% three years later.

Figure B5.1. Completion rate of full-time students who entered a bachelor's or equivalent programme (2017)

Note: For countries with true cohort data, the completion includes students who transferred and graduated from another tertiary level.
1. Year of reference differs from 2017. Refer to the source table for details.
2. Completion rate of students who entered a bachelor's programme does not include students who transferred to and graduated from short-cycle
programmes.
3. The theoretical duration plus 3 years refers to the theoretical duration plus 2 years.
4. Data do not include entrants to 6-year bachelor’s programmes, which correspond to about 2% of total entrants at this level.
5. Data refer only to the hautes écoles (HE) and the écoles des arts (ESA), representing about 60% of entrants to bachelor's or equivalent
programmes.
6. Data refer to estimated completion rates based on a modelled relationship between future graduates and students still enrolled.
Countries and economies are ranked in descending order of completion rate by theoretical duration (true cohort) or cross cohort.
Source: OECD (2019), Table B5.1. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933978284

EDUCATION AT A GLANCE 2019 © OECD 2019

B5. HOW MANY STUDENTS COMPLETE TERTIARY EDUCATION?  209

Context
Tertiary completion rates can indicate the efficiency of tertiary education systems, as they show what
proportion of the students who enter a tertiary programme ultimately graduate from it. However, low completion
rates do not necessarily imply an inadequate tertiary system, as students may leave a programme for a variety
of reasons. They may realise that they have chosen a subject or educational programme that is not a good fit
for them, or they may find attractive employment opportunities before completing the programme. In some
educational systems, it may also be common for students to enrol without intending to graduate from a specific
programme, but rather to pursue a few courses as part of lifelong learning or upskilling.
A variety of factors can influence completion rates, including students’ prior educational background and social
and economic characteristics. This indicator analyses the completion rate of tertiary students by gender and
by their upper secondary programme orientation (general or vocational). It also analyses the extent to which
students’ immigration background and their parents’ educational attainment can influence their likelihood of
succeeding in tertiary education (Box B5.2).
Completion of a programme may be defined differently across countries. This indicator focuses on full-time
students and just two specific timeframes for completion: 1) the share of students who graduate from any tertiary
programme within the theoretical duration of the programme they entered; and 2) the share of students who
graduate within three years after the end of the theoretical duration. The difference between these two
timeframes can shed light on the extent to which students graduate “on time” (within the amount of time expected
given the theoretical duration of the programme) or after some delay. This indicator also examines the share of
students who transfer between tertiary levels and who leave the education system without graduating.

Other findings


In all countries with available data, women have higher completion rates than men in bachelor’s
programmes. The gender gap in completion within the programme’s theoretical duration reaches over
27 percentage points in Finland.



On average across countries and economies with available data, 45% of students who entered a
short-cycle tertiary programme graduated from any tertiary programme by the end of the theoretical
duration of the programme in which they entered.



In some countries, students transfer to different tertiary levels during their studies. In France, 13% of
students who entered a bachelor’s programme had transferred to a short-cycle or a master’s long first
degree by the beginning of their second year of study.

Note
Completion, graduation and attainment rates are three different measures. Completion rates describe the
percentage of students who enter a tertiary programme and who graduate from it a given number of years
later. Graduation rates represent the estimated percentage of people from a certain age cohort who are
expected to graduate at some point during their lifetime. They measure the number of graduates from a level
of education relative to the country’s population (Education at a Glance Database). The third indicator,
attainment rates, measure the percentage of a population that has reached a certain level of education (see
Indicator A1). They represent the relationship between all graduates (of the given year and previous years)
and the total population.
This indicator only covers full-time students. On average across OECD countries, about 26% of short-cycle
tertiary students and 16% of bachelor’s students are enrolled part time. Please see Indicator B1 for more
information on the share of part-time students enrolled in each tertiary level of education.
The theoretical duration of tertiary programmes may vary across countries. Therefore, despite having the
same reference year for graduates (2017 unless specified otherwise), the year used for entry cohorts will differ
depending on the duration of the programmes.

EDUCATION AT A GLANCE 2019 © OECD 2019

210  B5. HOW MANY STUDENTS COMPLETE TERTIARY EDUCATION?

Analysis
Completion rate by level of educational attainment
Completion rates in this indicator are calculated using two different methods, depending on countries’ data
availability: true cohort and cross cohort. The results from these two methodologies are analysed separately as
they are not comparable (see Box B5.1).

True cohort completion
On average across countries and economies that submitted true cohort data, 39% of students who entered a
bachelor’s programme graduated within the theoretical duration of the programme. This includes all students who
graduated from a tertiary programme, even if at a different level. Three years after the end of the theoretical
duration, the average completion level increases to 67% (Table B5.1).
There is a wide variation among countries and economies in completion rates within the theoretical duration,
ranging from less than 30% in Austria, Chile, the French Community of Belgium, the Netherlands and Slovenia,
to 60% or more in Ireland, Israel, Lithuania and the United Kingdom (Figure B5.1). The completion rate after three
additional years increases for all countries and economies, but it tends to increase by more where the completion
rate by the theoretical duration is lower. As a result, the range of completion rates after three additional years is
narrower, ranging from 50% in Brazil to 85% in the United Kingdom. Notably, the completion rate within the three
additional years increases by over 40 percentage points in the Netherlands, New Zealand and Switzerland.
A variety of institutional factors and country-specific characteristics can help explain the different levels of
“delayed” graduation across countries. For example, in some countries it is common for students to take remedial
or prerequisite courses that may not be included in the official curriculum (Scrivener et al., 2018[1]). In some
countries, remedial courses are counted as years spent in tertiary education, as is the case in United States. In
other countries, such as Norway, students are only considered to have started the level of education after they
have completed any remedial courses, thus not affecting the completion rate.
Nevertheless, a large difference in completion rates between the shorter and longer periods is not necessarily a
negative outcome. In the Flemish Community of Belgium, for example, higher education programmes are very
flexible and are not divided into years of study. Students are required to take a certain number of credits to
graduate, but the years of study, even if full time, may not be consecutive. This type of flexible system tends to
increase the number of students who do not graduate “on time”, but could be beneficial to students in many other
ways. In countries that provide relatively broad access to tertiary education, as is the case in the Flemish
Community of Belgium, flexibility may be particularly important, giving students more time to meet the standards
set by their educational institution.
Only ten countries have data available for short-cycle tertiary programmes and, as with bachelor’s programmes,
completion rates at this level vary widely. In the United States, only about 9% of students who enter a short-cycle
programme full-time graduate from any tertiary programme within two years, the theoretical duration of their
programmes. In Austria, nearly 70% of students graduate within this time. Three years after the end of the
theoretical duration, the completion rates increase in all countries, but especially so in countries which saw lower
rates within the theoretical duration. The completion rate doubles in Chile (from 23% to 46%) and more than
triples in the United States (from 9% to 31%).
The completion rate of short-cycle tertiary programmes is higher than that of bachelor’s programmes in about
half of the countries with available data. The difference between the two levels is highest in Austria, where the
completion rate of short-cycle tertiary programmes is 43 percentage points higher than at the bachelor’s level
(both within their respective theoretical durations). In order to put these differences into context, it is important to
examine the share of students enrolled in each tertiary level. Austria, for example, is the only OECD country

EDUCATION AT A GLANCE 2019 © OECD 2019

B5. HOW MANY STUDENTS COMPLETE TERTIARY EDUCATION?  211

where more first-time entrants to tertiary education enrol in short-cycle programmes than in bachelor’s
programmes (see Indicator B4).
Only seven countries have data available for master’s long first degrees and, in every country, the completion
rate of these programmes is higher than that of bachelor’s programmes. Completion by the theoretical duration
of programmes varies from 32% in Chile to 53% in Norway and Switzerland. Completion within the theoretical
duration plus three years increases considerably in all countries, and ranges from 65% in Austria and Slovenia
to 89% in Norway.
In recent years, many countries have implemented a variety of policies aimed at increasing tertiary completion
rates. A common approach is to make the financing of institutions conditional to some extent on student
completion rate. This is the case in Austria, Brazil, Estonia, Finland and Israel. In other countries, completion
rates are taken into account in the financing provided directly to students. In Chile, the government only provides
tuition-free education for the theoretical duration of the programme. In Norway, student loans can be partly
converted into scholarships if students advance without delays. In some countries, such as Brazil, specific
financing is provided to institutions in order to help ensure that students from disadvantaged backgrounds
complete the degree without excessive delays. Other policies focus on helping students make better study
choices and ensuring that teachers have the necessary tools to help students succeed.

Cross cohort completion
Cross cohort completion rates take into account all graduates in a given academic year, regardless of the time it
took them to complete the programme. As a result, cross cohort completion rates tend to be considerably higher
than true cohort completion rates (see Box B5.1 for more information on the comparison between two
methodologies).
On average across the seven countries that submitted cross cohort data, 77% of students who enter a bachelor’s
programme complete it. This rate ranges from 48% in Latvia to over 90% in Japan and Korea. At short-cycle
tertiary level, completion rates range from 55% in the Slovak Republic to 89% in Japan. The difference in
completion rates between bachelor’s and short-cycle programmes varies across countries. In Mexico, completion
at short-cycle tertiary level is over 20 percentage points lower than at bachelor’s level. The opposite is true in
Latvia, where the completion rate of short-cycle tertiary programmes is 13 percentage points higher than that of
bachelor’s programmes.

Box B5.1. Difference between true cohort and cross cohort completion rates
This indicator presents completion rates calculated using two different methods: true cohort and cross cohort.
The true cohort method follows an entry cohort through a specific timeframe which in the case of this survey
corresponds to the theoretical duration of the programme and an additional three years. This method is the
preferred methodology for analysing completion rates, but only countries with longitudinal surveys or registers
are able to provide such information. Panel data can be available in the form of an individual student registry
(a system including unique personal identification numbers for students) or a cohort of students used for
conducting a longitudinal survey. Using the true cohort method, the completion rate corresponds to the share
of students from a specific cohort who graduate within each timeframe.
The cross cohort method is used to calculate completion rates in countries where true cohort data are not
available. This method only requires the number of new entrants to a given ISCED level and the number of
graduates from the level N years later, where N corresponds to the theoretical duration of the programme.
Under the assumption of constant student flows (constant increases or decreases in the number of students
entering a given education level over these years), cross cohort completion rates are closer to true cohort

EDUCATION AT A GLANCE 2019 © OECD 2019

212  B5. HOW MANY STUDENTS COMPLETE TERTIARY EDUCATION?
completion rates over longer timeframes. This is because cross cohort completion rates take into account all
graduates in a given academic year, regardless of the time it took them to graduate.
Any comparison between the two methodologies should be avoided. Table B5.a exemplifies the difference in
completion rate results between the two methodologies in a few countries that provided both true cohort and
cross cohort data. As expected, the cross cohort completion is considerably higher than the true cohort
completion, even when taking into account rates three years after the end of the theoretical duration.

Table B5.a. Difference in the completion rate of students who entered a bachelor's or equivalent
programme when calculated using the true cohort and cross cohort methodologies (2017)

1. Data refer only to the hautes écoles (HE) and the écoles des arts (ESA), representing about 60% of entrants to bachelor's or equivalent
programmes.
Source: OECD (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).

Completion rate by gender
In every country with available data (both true cohort and cross cohort), women have higher completion rates
than men in bachelor’s programmes (Table B5.1). On average across countries and economies with true cohort
data, 44% of female entrants and 33% of male entrants to bachelor’s programmes graduate within the theoretical
duration. The average gap remains similar when taking three additional years into account: the completion rate
among women increases to 72% and among men to 61%.
Some countries have a narrower gender gap than others. The difference in bachelor’s programme completion
rates between women and men within the theoretical duration is below 7 percentage points in Switzerland and
the United Kingdom and 27 percentage points in Finland. In most countries, the gender gap does not change
considerably three years after the end of the theoretical programme duration. Only in Finland does the gap
change by more than 10 percentage points, with the gender gap narrowing to 16 percentage points.

Completion rate by upper secondary programme orientation
Another factor that may influence students’ tertiary completion rate is their upper secondary programme
orientation. On average across countries and economies with available data, 38% of bachelor’s students with a
general upper secondary qualification graduate within the theoretical duration of the programme in which they
entered. The same is true for 35% of bachelor’s students with a vocational upper secondary degree. This
3 percentage-point gap increases to 12 percentage points within the three years following the end of the
theoretical duration of programmes.
The pattern of completion rates within the theoretical duration varies widely across countries: students from
general programmes have a higher completion rate than students from vocational programme in exactly half of
the countries with available data. However, the pattern becomes clearer when looking at completion rates after
three additional years. Within this longer timeframe, the completion rate of students with general upper secondary
EDUCATION AT A GLANCE 2019 © OECD 2019

B5. HOW MANY STUDENTS COMPLETE TERTIARY EDUCATION?  213

qualifications is either higher or very similar to students with vocational qualifications in nearly all countries. In
fact, only in one country – Austria – are bachelor’s students from vocational upper secondary programmes more
likely to graduate than their peers who attended general programmes (Figure B5.2).
To understand the context behind these results, it is important to assess the representativeness of these students
among entrants to bachelor’s programmes (Table B5.2). For example, in Lithuania, 53% of students from
vocational upper secondary programmes graduate within the theoretical duration of the programme in which they
entered. However, these students represent less than 1% of entrants into bachelor’s programmes. In nearly all
countries with available data, the share of bachelor’s entrants with a general upper secondary degree is higher
than the share of entrants with a vocational upper secondary degree. On average across countries and
economics with available data, students from vocational programmes make up 28% of entrants. The share ranges
from less than 15% in Estonia, Lithuania and Norway to 51% in Austria – the only country where they make up
the majority of entrants.

Figure B5.2. Completion rate of full-time students who entered a bachelor's or equivalent programme, by
students' upper secondary programme orientation (2017)
True cohort only

1. Completion rate of students who entered a bachelor's programme does not include students who transferred to and graduated from short-cycle
programmes.
2. If the student has completed both upper secondary general and vocational education or if the data on previous education is missing, the student is
reported under upper secondary vocational.
3. Year of reference differs from 2017. Refer to the source table for details. Data on students from vocational upper secondary programmes have been
withdrawn due to small sample size.
4. Data refer only to the hautes écoles (HE) and the écoles des arts (ESA), representing about 60% of entrants to bachelor's or equivalent programmes
Countries and economies are ranked in descending order of completion rate by the theoretical duration of students with general upper secondary
education.
Source: OECD (2019), Table B5.2. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933978303

EDUCATION AT A GLANCE 2019 © OECD 2019

214  B5. HOW MANY STUDENTS COMPLETE TERTIARY EDUCATION?
It is important to note that in many countries, such as Belgium and Estonia, some upper secondary vocational
programmes do not grant access to bachelor’s programmes. Depending on the share of students enrolled in
these programmes, this may help explain the lower share of bachelor’s entrants with vocational degrees.
Relative to bachelor’s level, students from vocational programmes make up a considerably larger share of
entrants to short-cycle tertiary programmes, but a considerably lower share of entrants to master’s long first
degree programmes in the few countries with data available at these levels (Table B5.2, Panels B and C). In
Chile and Norway, students from vocational programmes who enter short-cycle programmes have a higher
completion rate than those from general programmes. Indeed, in some countries it is common for short-cycle
tertiary programmes to be specifically geared towards students from an upper secondary vocational track.

Pathways through tertiary education
In addition to students’ completion rates, it is important to examine their different paths once they enter tertiary
education. This helps understand the flexibility and effectiveness of education systems. It can also shed light on
the other portion of students – those who have not graduated. Are they still in education? Have they transferred
to a different tertiary level? Or have they left the system without graduating?

Where are students after their first year of study?
Examining students’ status right after their first year of study can be very relevant to understanding what happens
during their first contact with tertiary education. This could reflect, among other things, the effectiveness of student
orientation or preparedness for tertiary education. On average across countries and economies with available
data some 12% of students who entered a bachelor’s programme were no longer enrolled in any tertiary
programme by their second year of study, more than 2% had transferred to another tertiary level and 85% were
still enrolled in the same or another bachelor’s programme (Table B5.3).
In some countries, students enter one tertiary level but transfer and graduate instead from a different level. In
fact, a large portion of the transfers between tertiary levels actually takes place very soon after students have
entered a programme. In France, 11% of students who entered a bachelor’s programme had transferred to a
short-cycle programme by the beginning of their second year of study. The same is true for over 3% of students
in Chile and Slovenia (Table B5.3).
The share of students who are no longer enrolled after their first year of studies ranges from 6% in the United Sates
to at least 20% in Slovenia and the French Community of Belgium. High levels after just one year could be
particularly concerning given that the share of students who leave the system without graduating tends to increase
considerably with time. Indeed, by three years after the end of theoretical duration the share has nearly doubled –
and even tripled in some cases – in most countries and economies with available data (Figure B5 3).

Where are students by the end of their programmes’ theoretical duration? And three years later?
The two timeframes this indicator uses to measure students’ status are: 1) by the end the theoretical duration of the
programme in which they entered; and 2) by three years after the end of the theoretical duration of the programme.
On average across countries and economies with available data, 39% of students who entered a bachelor’s
programme graduated from that or another bachelor’s programme by the end of the theoretical duration.
About 1% had transferred and graduated instead from a short -cycle tertiary programme, 41% were still in
tertiary education (even if at a different level) and 20% n o longer enrolled in any tertiary programme. The
picture evolves quite considerably within the three years after the end of the theoretical duration of the
programme, as many of those who were still in education either graduate or leave the system. At this point,
on average, 64% of students have graduated from a bachelor’s programme, 2% have graduated from a
short-cycle tertiary programme and 1% from a master’s long first degree programme. Some 9% are still in
education and 24% are no longer enrolled (Figure B5.4).

EDUCATION AT A GLANCE 2019 © OECD 2019

B5. HOW MANY STUDENTS COMPLETE TERTIARY EDUCATION?  215

Figure B5.3. Share of full-time bachelor's students who are no longer enrolled in tertiary education (and
have not graduated) at various timeframes after entry (2017)
True cohort only

Note: The share of students "not graduated and not enrolled in tertiary education" may include students who left the country before graduation.
1. Data refer only to the hautes écoles (HE) and the écoles des arts (ESA), representing about 60% of entrants to bachelor's or equivalent programmes.
2. Includes students who transferred to short-cycle tertiary programmes.
3. Year of reference differs from 2017. Refer to the source table for details.
4. Data do not include entrants to 6-year bachelor's programmes, which correspond to about 2% of total entrants at this level.
5. The theoretical duration plus 3 years refers to the theoretical duration plus 2 years.
Countries and economies are ranked in descending order of share of students not enrolled by the beginning of the second year of study.
Source: OECD (2019), Table B5.3. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933978322

A high transfer rate between tertiary levels can help explain some delays in students’ graduations. Delays are
expected to occur if there are difficulties in transferring credits, or if students transfer to a programme with a
longer theoretical duration (students’ status is always measured within the timeframe of their original
programme’s theoretical duration). Transfer rates among students who enter a bachelor’s programme are highest
in France, where about 8% graduate from a short-cycle tertiary programme, and in Slovenia, where about 2%
graduate from a short-cycle tertiary programme and 6% graduate from a master’s long first degree programme
(all within the theoretical duration of the original programmes plus three years).
The overall evolution in the status of students between the end of the theoretical duration of programmes and
three years later differs across countries. Whereas completion increases by over 40 percentage points in
the Netherlands, New Zealand and Switzerland, the increase is only 4 percentage points in Lithuania. There are
also important differences in what happens to students who are still in education by the end of the theoretical
duration of the programme. In some countries, like Israel and Slovenia, over 90% of these students will graduate
within the following three years. In other countries and economies, like the French Community of Belgium, Brazil
and Estonia, at least 20% of the students still in education by the end of the theoretical duration leave the system
without graduating over the following three years.

EDUCATION AT A GLANCE 2019 © OECD 2019

216  B5. HOW MANY STUDENTS COMPLETE TERTIARY EDUCATION?

Figure B5.4. Status of full-time bachelor's students by the theoretical duration and by the theoretical
duration plus three years (2017)
True cohort only

Note: The share of students "not graduated and not enrolled in tertiary education" may include students who left the country before graduation.
1. Year of reference differs from 2017. Refer to the source table for details.
2. Share of students who graduated does not include students who transferred to and graduated from short-cycle programmes.
3. The theoretical duration plus 3 years refers to the theoretical duration plus 2 years.
4. Data do not include entrants to 6-year bachelor's programmes, which correspond to about 2% of total entrants at this level.
5. Data refer only to the hautes écoles (HE) and the écoles des arts (ESA), representing about 60% of entrants to bachelor's or equivalent programmes.
Countries and economies are ranked in descending order of the share of students who graduated by the theoretical duration
Source: OECD (2019), Table B5.3. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933978341

EDUCATION AT A GLANCE 2019 © OECD 2019

B5. HOW MANY STUDENTS COMPLETE TERTIARY EDUCATION?  217

Delayed completion, or even non-completion, can be costly to both governments and individuals. The cost of
tertiary education is high, and students and governments may not reap the full benefits until the degree is
completed. Data show that individuals with a tertiary qualification tend to have higher earnings and higher
employment rates, which in turn translate into higher taxes and higher social contributions for the government
(see Indicator A5). Nevertheless, delaying graduation or dropping out are not necessarily symptoms of student
or institutional failure. In some countries, the labour market recognises the partial completion of tertiary degrees,
either formally or informally, which may encourage students to work part time (and potentially delay graduation)
or to drop out and join the labour market full time. In Sweden, for example, the strong labour market demand in
some fields such as engineering leads many students to start working before attaining their degree.

Box B5.2. Completion rate by parents’ educational attainment and by students’ immigration
background
Studies have shown that coming from a disadvantaged socio-economic background has a strong impact on
tertiary completion (Vossensteyn et al., 2015[2]; Thomas and Quinn, 2006[3]). Even among highly qualified
students, those from disadvantaged backgrounds tend to be more at risk of dropping out because of financial
constraints, family problems or peer pressure (Quinn, 2013[4]). This box examines the extent to which
completion rates differ for individuals from potentially disadvantaged backgrounds, identified through two
proxy measures: parents’ highest level of educational attainment and immigrant background.

Completion by parents’ educational attainment
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[5]). Figure B5.a shows the completion rate
of students who entered a bachelor’s programme full time disaggregated by the highest level of educational
attainment of at least one parent. There is no clear pattern across countries between parental education and
completion within the theoretical duration. However, in nearly every country with available data, the
completion rate within the theoretical duration plus three years is highest for students with at least one tertiaryeducated parent and lowest for students whose parents did not complete upper secondary education.
The gap between students is considerably wider in some countries than in others. The difference in
completion within the theoretical duration plus three years between a student with a tertiary-educated parent
and one whose parents did not complete upper secondary ranges from less than 5 percentage points in
Estonia, Finland, Portugal and Sweden to over 20 percentage points in the Flemish Community of Belgium
and the United States (Figure B5.a). In order to address some of the equity issues at this level of education,
the Flemish government has recently set a target to have at least 60% of upper secondary graduates whose
mother’s' educational attainment is below tertiary participate in a tertiary programme by 2020 (Cabinet of
Prime Minister of the Flemish Government and Flemish Minister for Economy, Foreign Policy, Agriculture and
Rural Policy, 2009[6]).
The gap in completion rates between these students indicates that entrants from disadvantaged backgrounds
may face particular challenges in completing tertiary education. However, this measure alone is not enough
to assess the equitability of education systems. At least two other factors must be taken into account: 1) the
share of students from each group in the entry cohort; and 2) the representativeness of the entry cohort in
the population as a whole. Table B5.b (available on line) shows the distribution of entrants to bachelor’s
programmes by parents’ education attainment. In Estonia, for example, students whose parents did not
complete upper secondary education are more likely to graduate within the theoretical duration than their
peers, but they only represent 2% of bachelor’s entrants. In Portugal, they represent 44% of entrants.

EDUCATION AT A GLANCE 2019 © OECD 2019

218  B5. HOW MANY STUDENTS COMPLETE TERTIARY EDUCATION?

Figure B5.a. Completion rate of full-time students who entered bachelor’s or equivalent level, by
parents’ educational attainment (2017)

1. Completion rate of students who entered a bachelor's programme does not include students who transferred to and graduated from short-cycle
programmes.
2. Upper secondary and post-secondary non-tertiary attainment includes short-cycle tertiary; and tertiary attainment includes only bachelors,
master's and doctoral or equivalent levels.
3. Year of reference 2018.
4. Year of reference for entrance cohort is 2008. Graduation years vary depending on the theoretical duration of programmes.
5. Year of reference for entrance cohort is 2003. Graduation years vary depending on the theoretical duration of programmes. The theoretical
duration plus 3 years for bachelor's or equivalent programmes refers to the theoretical duration plus 2 years.
Countries and economies are ranked in descending order of completion rate by the theoretical duration for students whose parents have not attained
upper secondary education.
Source: OECD (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933978360

It is also important to assess the representativeness of the entry cohort in the population. A system is not
equitable if most of a country’s youth do not have tertiary-educated parents, but they make up only a minority
of the entrants to bachelor’s programmes. Please see Indicator B7 in (OECD, 2018[7]) for further information
on the representativeness of potentially disadvantaged groups among tertiary students.
Finally, it must be noted that students from disadvantaged backgrounds may be more likely to enrol part time
in some countries, which is not captured by this indicator.

Completion by students’ immigration background
Immigrant background, although not always indicative of a disadvantage, is also correlated with lower student
performance (OECD, 2018[7]). Students with an immigrant background must often overcome adversities
associated with displacement, socio-economic disadvantage and language barriers.

EDUCATION AT A GLANCE 2019 © OECD 2019

B5. HOW MANY STUDENTS COMPLETE TERTIARY EDUCATION?  219

Figure B5.b. Completion rate of full-time students who entered bachelor’s or equivalent level, by
students' immigration background (2017)

1. Completion rate of students who entered a bachelor's programme does not include students who transferred to and graduated from short-cycle
programmes.
2. Year of reference for entrance cohort is 2003. Graduation years vary depending on the theoretical duration of programmes. The theoretical
duration plus 3 years for bachelor's or equivalent programmes refers to the theoretical duration plus 2 years
Countries are ranked in descending order of completion rate by the theoretical duration for first-generation immigrant students
Source: OECD (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933978379

Figure B5.b shows the completion rate of students who entered a bachelor’s programme full time
disaggregated by their immigration status. In nearly every country with available data, non-immigrant students
(i.e. students who were born in the country and who have at least one parent also born in the country) have
a higher completion rate than students with an immigration background, both within the theoretical duration
and three years later. The difference between first- and second-generation immigrants varies across
countries, but the difference between them tends to be smaller (in absolute terms) than the difference
between non-immigrants and either first- or second-generation immigrants.
As with parental education, it is important to take into account the share of each group in the entry cohort
(Table B5.c, available on line) and in the population (OECD, 2018[7]). Finland, for example, is the only country
where the completion rate of non-immigrant students is below that of both first- and second-generation
immigrants. However, Finland is also the country with the lowest share of students with an immigration
background among entrants to bachelor’s programmes: 4% are first-generation immigrants and 0.1% are
second-generation immigrants. Students with an immigration background make up a considerably higher
share of bachelor’s entrants in other countries such as Israel (25%) and Sweden (18%).

EDUCATION AT A GLANCE 2019 © OECD 2019

220  B5. HOW MANY STUDENTS COMPLETE TERTIARY EDUCATION?

Box B5.3. Using student surveys to measure quality in higher education
This box shows how surveys of student experiences can inform policies for quality improvements in
post-secondary education and provide international comparisons of higher education outcomes.
Measurement of the quality of higher education teaching and learning, either at the institutional or
national/systemic level, suffers from a lack of appropriate data. Direct measurement of student learning
outcomes is expensive and time consuming, and difficult to scale up to the national level.
An alternative approach to measuring teaching quality are surveys of students or graduates. These surveys
measure aspects of the student experience with the education they have received and provide valuable
information on a wide range of contextual and personal factors that impact learning. Examples of student
surveys include the National Survey of Student Engagement (NSSE) in the United States and Canada, the
National Student Survey (NSS) in the United Kingdom, the Student Experience Survey (SES) in Australia,
and the Eurostudent survey, conducted by 25 to 30 participating European countries.
Focusing on the quality of student experiences can assist institutions in raising retention rates, by identifying
factors such as teaching practices, support services and academic resources which encourage engagement
and success for each student. Areas of relative weakness can be isolated at institutional or discipline levels,
or conversely, models of best practice can be identified. The student experience can also be improved
through policy responses to specific survey items, such as those dealing with retention. For example, the
Australian SES asks respondents whether they have considered leaving their studies in the past year, and if
so why.

Figure B5.c. Overall assessment of study programme (% positive rating), all students (2016)

1. Year of reference 2017.
Source: National Survey of Student Engagement (NSSE) for the United States, the Student Experience Survey (SES) for Australia, the National
Student Survey (NSS) for the United Kingdom and the Eurostudent survey for the other European countries.

Another potential use for student survey data is for international comparisons of higher education systems.
Figure B5.c shows an example of international comparisons using publicly available survey data from
Eurostudent participant nations, Australia, the United States and the United Kingdom.
Student surveys have limitations as measures of teaching quality and learning outcomes. They do not provide
a direct, objective measure of learning outcomes, but instead aggregate individual students’ subjective
assessments of learning outcomes, or of proxies or factors believed to be important for achieving learning

EDUCATION AT A GLANCE 2019 © OECD 2019

B5. HOW MANY STUDENTS COMPLETE TERTIARY EDUCATION?  221

outcomes. As such, student survey results need to be analysed in the context of the educational and
demographic characteristics of the students themselves.
Absolute levels of performance recorded in surveys are of less importance than relationships between
population sub-groups (for instance institutions or student demographics) and changes in performance over
time. Such analyses are supported by the scalability and repeatability of survey instruments.
Results from student surveys should not be interpreted simplistically. Although measuring similar concepts,
it is important to acknowledge that differences in survey methodologies and the precise wording of survey
items can have a substantial impact on results. For example, Figure B5.c is based on a Eurostudent survey
item asking whether students would recommend their study programme to others, whereas survey items for
Australia, the United Kingdom and the United States relate to overall student experience/satisfaction. In
addition, survey results can be affected by differences in the demographic makeup of the student cohorts, or
differences in national cultures and expectations of education.
Given these limitations, changing relationships between national system measures over time are likely to be
more meaningful than absolute scores at any one point in time. An example of a time series comparison is
presented in Figure B5.d.
Further work in developing comparable items and in understanding cultural differences in responding to
survey items would assist in interpreting these results and serve to increase the value of international
comparisons.

Figure B5.d. Student/graduate overall rating of study experience (% rating positively), selected
countries, 2008 to 2018

Source: National Survey of Student Engagement (NSSE) for the United States, the National Student Survey (NSS) for the United Kingdom, the
Student Experience Survey (SES) for Australia.

Definitions
The true cohort method requires following an entry cohort through a specific time frame, which in the case of
this survey corresponds to the theoretical duration of the programme and the theoretical duration plus three years.
Only countries with longitudinal surveys or student registers are able to provide such information.
The cross cohort method only requires the number of new entrants to a given ISCED level and the number of
graduates N years later, where N corresponds to the theoretical duration of the programme.

EDUCATION AT A GLANCE 2019 © OECD 2019

222  B5. HOW MANY STUDENTS COMPLETE TERTIARY EDUCATION?
Full-time students in this indicator refer to students who entered the given tertiary programme with full-time
status. They may have switched status during their studies.
The theoretical duration of programmes is the regulatory or common-practice time it takes a full-time student
to complete a level of education.
Immigration status:


First-generation immigrants refer to those born outside the country and whose parents were also both
born in another country. This excludes international students.



Second-generation immigrants refer to those born in the country but whose parents were both born in
another country.



Non-immigrants refer to those with at least one parent born in the country.

Parents’ educational attainment:


Below upper secondary means that both parents have attained ISCED 2011 levels 0, 1 or 2 and
includes recognised qualifications from ISCED 2011 level 3 programmes (see Reader’s Guide), which
are not considered as sufficient for ISCED 2011 level 3 completion, and do not provide direct access to
post-secondary non-tertiary education or tertiary education.



Upper secondary or post-secondary non-tertiary means that at least one parent has attained
ISCED 2011 levels 3 and 4.



Tertiary means that at least one parent has attained ISCED 2011 levels 5, 6, 7 or 8.

Methodology
For countries that submitted data using the true cohort method, it is possible to calculate two different completion
rates (described below) which are computed for two different timeframes (theoretical duration N and three years
later, N+3):


completion rate of students who graduate at the same ISCED level which they entered: number of
graduates in a given calendar year and ISCED level divided by the number of entrants to that same
ISCED level N/N+3 calendar years before



completion rate of students who graduate at any tertiary ISCED level: the sum of graduates from all
tertiary ISCED levels in a given calendar year who entered a given ISCED level N/N+3 calendar years
before.

Countries that submitted true cohort data either used first-time entrants to tertiary education (which considers
only students who entered tertiary education for the first time) or new entrants to the tertiary level (which considers
all first-time entrants to each tertiary level, regardless of whether they have pursued a different tertiary level
before). Please see Annex 3 for the list of countries using each methodology (https://doi.org/10.1787/f8d7880den).
For cross cohort data, only one completion rate is calculated: the number of graduates in a given calendar year
and ISCED level divided by the number of entrants to that same ISCED level N calendar years before.
If countries offer programmes of different theoretical durations within the same ISCED level, the completion rate
of each programme is weighted by the number of new entrants to each programme.
Please see the OECD Handbook for Internationally Comparative Education Statistics 2018 (OECD, 2018[8]) for
more information and Annex 3 for country-specific notes (https://doi.org/10.1787/f8d7880d-en).

EDUCATION AT A GLANCE 2019 © OECD 2019

B5. HOW MANY STUDENTS COMPLETE TERTIARY EDUCATION?  223

Source
Data on completion rates refer to the academic year 2016/17 and were collected through a special survey
undertaken in 2018. Data for some countries may have a different reference year, please refer to Annex 3 for
country-specific notes (https://doi.org/10.1787/f8d7880d-en). Countries submitted data using either the true
cohort or cross cohort methodology.
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
Cabinet of Prime Minister of the Flemish Government and Flemish Minister for Economy, Foreign
Policy, Agriculture and Rural Policy (2009), Pact 2020. Een nieuw toekomstpact voor Vlaanderen 20 doelstellingen | Vlaanderen.be, https://www.vlaanderen.be/publicaties/pact-2020-een-nieuwtoekomstpact-voor-vlaanderen-20-doelstellingen (accessed on 19 June 2019).

[6]

OECD (2018), Education at a Glance 2018: OECD Indicators, OECD Publishing, Paris,
https://dx.doi.org/10.1787/eag-2018-en.

[7]

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 (2013), OECD Skills Outlook 2013: First Results from the Survey of Adult Skills, OECD
Publishing, Paris, https://dx.doi.org/10.1787/9789264204256-en.

[5]

Quinn, J. (2013), Drop-out and Completion in Higher Education in Europe among Students from Underrepresented Groups, European Union, http://nesetweb.eu/wp-content/uploads/2015/09/2013-Dropout-and-Completion-in-Higher-Education-in-Europe-among-students-from-under-representedgroups.pdf (accessed on 17 May 2019).

[4]

Scrivener, S. et al. (2018), Becoming College-Ready: Early Findings from a CUNY Start Evaluation,
MDRC, http://www.mdrc.org. (accessed on 14 May 2019).

[1]

Thomas, L. and J. Quinn (2006), First Generation Entry into Higher Education: An International Study,
Open University Press.

[3]

Vossensteyn, H. et al. (2015), Dropout and Completion in Higher education in Europe, Publications
Office of the European Union, Luxembourg, http://dx.doi.org/10.2766/826962.

[2]

EDUCATION AT A GLANCE 2019 © OECD 2019

224  B5. HOW MANY STUDENTS COMPLETE TERTIARY EDUCATION?

Indicator B5 Tables
Table B5.1

Completion rate of full-time tertiary students, by level of education and gender (2017)

Table B5.2

Completion rate of full-time tertiary students, by level of education and students' upper
secondary programme orientation (2017)

Table B5.3

Status of full-time bachelor's students at various timeframes after entry (2017)

Table B5.a

Difference in the completion rate of students who entered a bachelor's or equivalent
programme when calculated using the true cohort and cross cohort methodologies (2017)

WEB Table B5.b. Distribution of entrants to bachelor’s or equivalent programmes, by parents’ education
attainment (2017)
WEB Table B5.c Distribution of entrants to bachelor’s or equivalent programmes, by students' immigration
background (2017)
Cut-off date for the data: 19 July 2019. 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.
StatLink: https://doi.org/10.1787/888933981001

EDUCATION AT A GLANCE 2019 © OECD 2019

B5. HOW MANY STUDENTS COMPLETE TERTIARY EDUCATION?  225

Table B5.1. Completion rate of full-time tertiary students, by level of education and gender (2017)

Note: True cohort (individual-level data) and cross cohort (aggregate data) completion rates are not comparable with each other. Please refer to Methodology section for
an explanation of the true cohort and cross cohort methodologies. The year of reference for the data (2017) corresponds to the graduation year three years after the
theoretical duration of the programme. The reference year for the entrance cohort changes depending on the duration of programmes.
1. Completion rate of students who entered a bachelor's programme does not include students who transferred to and graduated from short-cycle programmes.
2. Data refer only to the hautes écoles (HE) and the écoles des arts (ESA), representing about 60% of entrants to bachelor's or equivalent programmes.
3. Data do not include entrants to 6-year bachelor's programmes, which correspond to about 2% of total entrants at this level.
4. Year of reference 2015.
5. Year of reference for entrance cohort is 2008. Graduation years vary depending on the theoretical duration of programmes.
6. Data for short-cycle tertiary refer only to the higher education provided in universities.
7. Year of reference for entrance cohort is 2003. Graduation years vary depending on the theoretical duration of programmes. The theoretical duration plus 3 years for
bachelor's or equivalent programmes refers to the theoretical duration plus 2 years.
8. Data refer to estimated completion rates based on a modelled relationship between future graduates and students still enrolled.
Source: OECD (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
StatLink 2 https://doi.org/10.1787/888933978208

EDUCATION AT A GLANCE 2019 © OECD 2019

226  B5. HOW MANY STUDENTS COMPLETE TERTIARY EDUCATION?
Table B5.2. Completion rate of full-time tertiary students, by level of education and students' upper secondary programme
orientation (2017)
True cohort only

Note: The year of reference for the data (2017) corresponds to the graduation year three years after the theoretical end of the programme. The reference year for the
entrance cohort changes depending on the duration of programmes.
1. Completion rate of students who entered a bachelor's programme does not include students who transferred to and graduated from short-cycle programmes.
2. Data refer only to the hautes écoles (HE) and the écoles des arts (ESA), representing about 60% of entrants to bachelor's or equivalent programmes
3. If the student has completed both upper secondary general and vocational education or if the data on previous education is missing, the student is reported under upper
secondary vocational.
4. Year of reference for entrance cohort is 2008. Graduation years vary depending on the theoretical duration of programmes.
Source: OECD (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
StatLink 2 https://doi.org/10.1787/888933978227

EDUCATION AT A GLANCE 2019 © OECD 2019

B5. HOW MANY STUDENTS COMPLETE TERTIARY EDUCATION?  227

Table B5.3. Status of full-time bachelor's students at various timeframes after entry (2017)
True cohort only

Note: The year of reference for the data (2017) corresponds to the graduation year three years after the theoretical end of the programme. The reference year for the
entrance cohort changes depending on the duration of programmes.
1. The columns for "not enrolled in tertiary education" or "not graduated and not enrolled in tertiary education" may include students who left the country before graduation.
2. Short-cycle tertiary includes students who transferred to/graduated from master's or doctoral programmes within the timeframe.
3. Data refer only to the hautes écoles (HE) and the écoles des arts (ESA), representing about 60% of entrants to bachelor's or equivalent programmes
4. Data do not include entrants to 6-year bachelor's programmes, which correspond to about 2% of total entrants at this level.
5. Year of reference is 2015.
6. Year of reference for entrance cohort is 2008. Graduation years vary depending on the theoretical duration of programmes.
7. Year of reference for entrance cohort is 2003. Graduation years vary depending on the theoretical duration of programmes. The theoretical duration plus 3 years refers
to the theoretical duration plus 2 years.
Source: OECD (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
StatLink 2 https://doi.org/10.1787/888933978246

EDUCATION AT A GLANCE 2019 © OECD 2019

228  B6. WHAT IS THE PROFILE OF INTERNATIONALLY MOBILE STUDENTS?

Indicator B6. What is the profile of
internationally mobile students?
Highlights


Overall, the share of internationally mobile students across the OECD increased by 2 percentage
points between 2010 and 2017. Over this time period, the share of incoming students increased in
nearly all the countries with data available and particularly in Estonia, Hungary, Latvia, the Netherlands
and New Zealand.



English-speaking countries are the most attractive to international students. Australia, Canada,
the United Kingdom and the United States together receive more than 40% of all mobile students in
OECD and partner countries. Other main destination areas include France, Germany and
the Russian Federation.



Students from Asia form the largest group of international students enrolled in tertiary education
programmes at all levels, representing 56% of all mobile students across the OECD in 2017.
Two-thirds of Asian students converge on only five countries: Australia, Canada, Japan,
the United Kingdom and the United States. European students prefer to stay in the European Union
(EU); they account for 24% of mobile students in all OECD destination countries but 42% in the OECD
countries within the EU.

Figure B6.1. Incoming student mobility in tertiary education in 2010 and 2017
International or foreign student enrolment as a percentage of total enrolment in tertiary education

1. Years of reference 2013 and 2017.
2. Years of reference 2012 and 2017.
3. Share of foreign rather than international students.
4. Years of reference 2013 and 2016.
5. Years of reference 2014 and 2017.
Countries are ranked in descending order of the percentage of international or foreign students in 2017.
Source: OECD/UIS/Eurostat (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933978474

EDUCATION AT A GLANCE 2019 © OECD 2019

B6. WHAT IS THE PROFILE OF INTERNATIONALLY MOBILE STUDENTS?  229

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 high-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. International students often pay higher tuition fees than domestic
students (see Indicator C5) and, in some countries, incur higher registration fees. 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 innovation and economic performance.
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[1]). 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.
For their countries of origin, mobile students might be viewed as lost talent (or “brain drain”). 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. Some research suggests that students overseas
are a good predictor of future scientist flows in the opposite direction, providing evidence of a significant
movement of skilled labour across nations, which can also be referred to as “brain circulation” effect (Appelt
et al., 2015[2]). In addition, student mobility appears to shape international scientific co-operation networks
more deeply than either a common language or geographical or scientific proximity.
Competition for talent has become more intense and global, prompting educational institutions to access a
wider pool of high-potential students, with a view to increasing their reputation and revenues (Hénard,
Diamond and Roseveare, 2012[3]). The popularity of university league tables and other institutional rankings
has reinforced a perception of quality differences across institutions (Perkins and Neumayer, 2014[4]). As part
of their internationalisation strategy, 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. As a consequence, the international
activities of 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 expanded
massively in past few decades, rising from 2 million in 1998 to 5.3 million in 2017. In the OECD area,
there were 3.7 million international or foreign students in 2017, 6% more than in 2016.



Students become more mobile as they reach more advanced levels of education. International
students account for only 3% of total enrolment in short-cycle tertiary programmes and 4% of total
enrolment in bachelor's programmes, but they represent 22% of enrolment in doctoral programmes.

EDUCATION AT A GLANCE 2019 © OECD 2019

230  B6. WHAT IS THE PROFILE OF INTERNATIONALLY MOBILE STUDENTS?

Analysis
Trends in the number of international students
Student migration into the OECD area remains dynamic, but international student mobility is also consolidating
in developing economies (Box B6.1). Mobile students refer to both international students (those who cross
borders for the sole purpose of study) and foreign students (students who do not hold the same nationality as the
host country), whose number is used in some countries as a proxy measure for the number of international (crossborder) students (see Definitions section).
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. Incoming student mobility in tertiary
education in a country is determined by the number of mobile students as a share of the overall number of
students in tertiary education. The level of incoming mobility is 6% on average across OECD countries but in
about one-third of the OECD countries, it equals or exceeds 10%. Incoming international students made up at
least 15% of tertiary students in Australia, Austria, Luxembourg, New Zealand, Switzerland and
the United Kingdom, peaking at 47% for Luxembourg and 21% for Australia. The Czech Republic (13%) and
the Slovak Republic (7%) have the largest shares of foreign students at tertiary level.
Overall, the total share of mobile students across the OECD increased by 0.4 percentage points between 2010 and
2013 and another 1.6 percentage points over the period 2013-17, but the growth in international student mobility
varies significantly across countries. Between 2010 and 2017, the share of incoming mobile students increased in
nearly all countries with data available. In Australia, the share fell slightly, by 1 percentage point, while still remaining
high. More than half of these countries observed an increase of at least 3 percentage points over the same period
(Figure B6.1), especially the Netherlands (7 percentage points), Estonia, Latvia (both with a 6-percentage-point
increase), Hungary and New Zealand (both with 5 percentage points). Among the countries for which data were
only available for a shorter time period, the share of international students increased the most in the Czech Republic,
Ireland and Luxembourg, by more than 2 percentage points over the period 2013-17.
Looking at longer-term trends, the number of mobile students enrolled in tertiary education programmes
worldwide has expanded massively over the last two decades. It rose from 2 million in 1998 to 5.3 million in 2017,
growing at an average annual rate of 5% among OECD countries and 6% among non-OECD countries. This
increase was constant with peaks in 2002-03 and 2014-16 and a slight levelling off in long-term trends in 1999,
2004 and 2012 (Figure B6.2). However, the number of international students began increasing strongly again in
2014 (an increase of 7% over 2013) and the years that followed, with annual increases of 8% in both 2015 and
2016. In the last year with available data, the growth was slightly more moderate, returning to 5% between 2016
and 2017.
The increase in foreign enrolment is being driven by a variety of domestic and external factors, both push
(encouraging outward mobility) and pull (encouraging inward mobility) (UNESCO, 2013[5]). 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 of the growing middle classes 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.
Most countries have implemented reforms aiming to lower the barriers to migration of highly skilled individuals,
beyond education purposes, and most countries operate funding programmes to support inward, outward or
return mobility. While the 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).

EDUCATION AT A GLANCE 2019 © OECD 2019

B6. WHAT IS THE PROFILE OF INTERNATIONALLY MOBILE STUDENTS?  231

Figure B6.2. Growth in international or foreign enrolment in tertiary education worldwide (1998 to 2017)
Number of international or foreign students enrolled in OECD and non-OECD countries

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 (2019). Other non-OECD countries and years prior to 2013: UNESCO Institute for Statistics. See Source section for more
information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933978493

Profiles of internationally mobile students
Students are more likely to travel abroad for more advanced education programmes. 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 22% of all enrolments at doctoral level.
International enrolment in bachelor’s programmes remains relatively low (below 5% in nearly half of the countries
for which data are available). However, a few countries have a more international profile at this level. In Austria,
Luxembourg and New Zealand, more than 15% of students at bachelor’s level are international (Figure B6.3).

Box B6.1. How is the international pool of graduates evolving?
The share of tertiary-educated young adults (aged 25-34) has been increasing in OECD-G20 countries over
the past decade, and it is expected to keep growing in the next 15 years. Countries that were lagging behind
should experience the fastest increases and catch up, while countries with initially larger shares of tertiaryeducated adults should face slower growth. If trends remain constant, the People’s Republic of China and
India could account for a particularly large share of the OECD-G20 pool of tertiary-educated young adults,
despite the projected drop in China’s young adult population.
As Figure B6.a shows, it is possible to project regional contributions to OECD-G20 pool of tertiary-educated
young adults in 2030 based on the expected educational attainment and population changes. China and India,
which together accounted for 40% of tertiary-educated young adults in 2015, should keep their overall rank.
While China’s contribution is likely to fall by 4 percentage points in the next decade, mainly due to its
decreasing population, India’s will significantly increase. Latin American countries, in which 20% of young
adults in 2015 had attained tertiary education, are likely to experience a particularly fast increase (more than

EDUCATION AT A GLANCE 2019 © OECD 2019

232  B6. WHAT IS THE PROFILE OF INTERNATIONALLY MOBILE STUDENTS?
2.5% growth per year). In contrast, the North American countries and the Russian Federation are expected
to witness the slowest increases.

Figure B6.a. Regions’ projected contributions to the global tertiary-educated population of
25-34 year-olds (2015 to 2030)

Countries and regions are ranked in descending order of their projected regions contribution to the OECD-G20 tertiary-educated population of
25-34 year-olds in 2030.
Source: OECD (2018[6]), "How is the tertiary-educated population evolving?", Education Indicators in Focus, No. 61
(https://doi.org/10.1787/a17e95dc-en).
Statlink2 https://doi.org/10.1787/888933978569

International enrolment increases significantly at master’s level. On average across the OECD, 13% of students
are international or foreign at this level. The proportion of incoming students at least doubles between bachelor’s
and master’s levels in nearly two-thirds of OECD countries. The share of international students in Chile, Spain
and Sweden is at least four times higher at master’s than at bachelor’s level. Greece, on the other hand, seems
relatively less attractive to master’s students, as its inflows of foreign students are slightly lower than at bachelor’s
level (Figure B6.3).

EDUCATION AT A GLANCE 2019 © OECD 2019

B6. WHAT IS THE PROFILE OF INTERNATIONALLY MOBILE STUDENTS?  233

Figure B6.3. Incoming student mobility in tertiary education, by level of study (2017)
International or foreign student enrolment as a percentage of total enrolment in tertiary education

Note: All tertiary education includes short-cycle tertiary programmes, which are not presented separately in the figure.
1. Share of foreign rather than international students.
2. Year of reference 2016.
Countries are ranked in descending order of the percentage of international or foreign students in tertiary education.
Source: OECD (2019), Table B6.1. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933978512

International enrolment is much higher at doctoral level in the OECD area, particularly in France, Luxembourg,
the Netherlands New Zealand, Switzerland and the United Kingdom, where 40% or more tertiary students come
from abroad. 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). While most countries have higher shares of international students at doctoral than at master’s level,
a number of countries show the opposite pattern. This is particularly striking in Australia (decreasing from 48% at
master’s level to 32% at doctoral level), Germany (from 14% to 10%), Hungary (from 17% to 15%), Latvia (from
17 to 10%), Lithuania (from 9% to 4%) and Poland (from 5% to 2%) (Figure B6.3).

International student flows in tertiary education
In 2017, there were 3.7 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.
Identifying the determinants of international student mobility is key to designing efficient policies to encourage
the movement of skilled labour. 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 better economic performance by the host country, exchange
rates, more affordable mobility (due to lower tuition fees or higher education subsidies, for instance) and higherquality education in the host country. In addition, the decision to study abroad may be determined by noneconomic factors, such as political stability or cultural and religious proximity between origin and destination
countries (Guha, 1977[7]; UNESCO, 2013[8]; Weisser, 2016[9]).

EDUCATION AT A GLANCE 2019 © OECD 2019

234  B6. WHAT IS THE PROFILE OF INTERNATIONALLY MOBILE STUDENTS?
Setting appropriate tuition fees remains one of the most debated topics in education policy, in a context where 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. These result from different funding models across tertiary
institutions, combined with different levels of public financial support allocated to tertiary 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[10]). 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 disseminated. 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.

Main destination countries of mobile students studying in OECD countries
English is the lingua franca of the globalised world, with one in four people using it worldwide (Sharifian, 2013[11]).
Not surprisingly, English-speaking countries are the most attractive student destinations overall, with four
countries receiving more than 40% of all mobile students in OECD and partner countries. The United States is
the top OECD destination country for mobile tertiary students. Of the 3.7 million international students in the
OECD area, 985 000 enrol in programmes in the United States. Among English-speaking countries, after
the United States, the United Kingdom accounts for 436 000 international students, Australia 381 000 and
Canada 210 000 (Figure B6.4). As a destination country, the United States alone accounts for 22% of the total
international education market share in OECD and partner countries (about 18% of the number of mobile students
globally). Australia and the United Kingdom each have between 9% and 10% of the market share for OECD and
partner countries, while Canada has 5%. The United States has an even higher share at doctoral level, hosting
26% of the internationally mobile doctoral students in OECD and partner countries.

Figure B6.4. International education market shares (2017)
International or foreign students enrolled in each destination country as a share of all mobile students in OECD and partner
countries

Note: All tertiary education includes short-cycle tertiary programmes, which are not presented separately in the figure. Year of reference 2016 for
Argentina and South Africa.
Countries are ranked in descending order of the incoming international or foreign students as a share of all mobile students in OECD and partner
countries.
Source: OECD (2019), Table B6.3. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933978531
EDUCATION AT A GLANCE 2019 © OECD 2019

B6. WHAT IS THE PROFILE OF INTERNATIONALLY MOBILE STUDENTS?  235

Box B6.2. Credit mobility in European OECD member countries
Initiatives at national, regional, local, supranational or institutional level have also contributed to cross-border
mobility. In 2011, the European Union (EU) set the ambitious goal of increasing the proportion of EU graduates
from higher education who completed a period of their studies or training abroad to 20% by 2020 (Council of
the European Union, 2011[12]).

Table B6.a. Credit mobility in European OECD member countries (2017)

Note: The ECTS (European Credit Transfer and Accumulation System) credits are based on the workload students need in order to achieve expected
learning outcomes. Sixty credits are the equivalent of a full year of study or work. In a standard academic year, 60 credits would be usually broken
down into several smaller components.
Source: OECD/UIS/Eurostat (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933978455

The EU had already started to make European higher education more homogeneous and comparable across
countries and more attractive to international students in 1999 with the Bologna process, which set in motion
a series of reforms. Its main objectives were the introduction and standardisation of a three-cycle degree
system (bachelor’s, master’s and doctoral degrees), and the recognition of qualifications from foreign
institutions and of periods of study. One of the underlying objectives of the process was to stimulate mobility
across Europe of students, teachers and researchers.
The Erasmus+ programme (and its predecessor Erasmus) gives students and teaching staff the opportunity
to develop their skills and boost their employment prospects. Students can study abroad for up to 12 months

EDUCATION AT A GLANCE 2019 © OECD 2019

236  B6. WHAT IS THE PROFILE OF INTERNATIONALLY MOBILE STUDENTS?
(during each cycle of tertiary education). Over the period 2014-20, around 2 million students are expected to
have benefited from Erasmus+ (EUROSTAT, 2018[13]).
Students who are temporarily studying abroad to gain academic credit within the framework of a tertiary
education programme at their home institutions are defined as credit mobile students (UNESCO-UIS / OECD
/ EUROSTAT, 2018[14]). Credit mobility is distinct from degree mobility as degree mobile students – the
subject of the rest of this indicator – are enrolled as regular students with the objective of graduating in the
country of destination. On average across the European countries that are members of the OECD, 12% of
2017 graduates had benefited from credit mobility, ranging from less than 5% in Greece and Slovenia to 36%
in Luxembourg. With the exception of the Slovak Republic, graduates from most countries spent at least three
months abroad (84% of all credit-mobile graduates on average) or a similar period in terms of study or
workload (Table B6.a). Of these, 38% had studied at master’s or doctoral levels.
Erasmus+ and other EU programmes account for the great majority (64%) of credit-mobile graduates who
studied abroad at least three months, ranging from 3% in Norway (which is not a member of the EU) and 21%
in Denmark to 95% or more in Greece, Hungary, Latvia and Slovenia. In addition, students may benefit from
credit mobility through other international or national programmes, including other bi- or multilateral
programmes such as partnerships between universities, or other programmes involving students organising
their own mobility, which is then credited by their home institution. The Nordic and Baltic countries, for
example, 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.
Credit mobility mostly involves participation in academic study, but it can also take other forms, such as work
placements, internships or traineeships. In all the countries with available data, most graduates who had
travelled abroad for at least three months did so to benefit from a study period abroad (with or without a work
placement), but in 10 countries students are also allowed to benefit from credit mobility for a standalone work
placement without a study component.
The European Union is another key geographical area for inward mobility, with 1.7 million mobile students
enrolled in the 23 OECD countries that are also members of the EU (EU23). After the United Kingdom, France
and Germany (both with nearly 260 000 students) are major host countries for international students, far ahead
of Italy (98 000), the Netherlands (96 000) and Austria (74 000). As destination countries, France and Germany
each account for 6% of the international students in OECD and partner countries (about 5% of the global share).
Their shares increase at master’s level where they hosted between 9% and 10% of mobile master’s students in
OECD and partner countries in 2017 (Table B1.3). The Russian Federation is also a major destination country,
with 278 000 students enrolled from abroad, accounting for 6% of mobile students in OECD and partner countries
in all tertiary programmes and 9% at bachelor’s level.
Japan is the preferred Asian destination among OECD and partner countries, with 164 000 international students,
just above China with 157 000 foreign students: they each have a share of 4% in the international education
market in OECD and partner countries and about 3% globally. Finally, Argentina is the most popular destination
for mobile students among Latin American countries with a 2% share of the number of mobile students in OECD
and partner countries (Figure B6.4).

Regions of origin
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 tertiary education programmes at
all levels, totalling 2.1 million and 56% of all mobile students across the OECD in 2017 (Figure B6.5). Of these,
EDUCATION AT A GLANCE 2019 © OECD 2019

B6. WHAT IS THE PROFILE OF INTERNATIONALLY MOBILE STUDENTS?  237

over 860 000 come from China. Two-thirds of Asian students converge on only five countries: Australia, Canada,
Japan, the United Kingdom and the United States.
The second major region of origin of international students is Europe, who make up 24% of all mobile students
enrolled in OECD countries. European students prefer to stay in Europe, as their share reaches 42% of mobile
students enrolled in the EU23 countries (Box B6.2). At least 8 out of 10 mobile students in Austria, Denmark,
Luxembourg, Poland, Portugal, the Slovak Republic and Slovenia come from European countries. Students from
Luxembourg are the most mobile in tertiary education as 3 out of 4 enrol in a tertiary programme abroad (this
leads to the underestimation of tertiary enrolment rates in Luxembourg, see Indicator B1). Students from Iceland
and the Slovak Republic are also more likely to study abroad than nationals from other OECD and partner
countries: 14%-18% of their national students are enrolled in a tertiary programme abroad (Table B1.3).
Demonstrating the importance of proximity, in Austria, the Czech Republic, Luxembourg, the Slovak Republic
and Switzerland more than 50% of international or mobile students in 2017 came from neighbouring countries.

Figure B6.5. Distribution of international and foreign students by region of origin (2017)

1. Share of foreign rather than international students.
2. Year of reference 2016.
Countries are ranked in descending order of the percentage of international or foreign students from Asia.
Source: OECD (2019), Table B6.2. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933978550

Students from African countries make up the majority of foreign students only in South Africa (81% of students
are mobile) among OECD and partner countries, although at least 3 out of 10 mobile students are from Africa in
France, Portugal and Saudi Arabia. International student flows from Latin America and the Caribbean highlight
proximity patterns, as they represent the majority of mobile students in Argentina, Brazil, Chile, Colombia,
Costa Rica and Mexico, but also the importance of the language of studies: between 4 and 5 in every 10 mobile
students in Portugal and Spain come from this region. Finally, North American students represent more than
10% of international enrolment only in Iceland, Ireland, Israel and Mexico, while students from Oceania are a
minority of international students in all OECD and partner countries, making up only 1% of mobile students in
OECD destination countries (Figure B6.5).

EDUCATION AT A GLANCE 2019 © OECD 2019

238  B6. WHAT IS THE PROFILE OF INTERNATIONALLY MOBILE STUDENTS?

Definitions
There are two types of mobility: degree mobility and credit mobility. Degree-mobile students are enrolled as
regular students in any semester/term of a programme taught in the country of destination with the intention of
graduating from it in the country of destination (distance learners are not considered as mobile). Credit mobility
is defined as temporary tertiary education or study-related traineeships abroad within the framework of enrolment
in a tertiary education programme at a home institution, usually for the purpose of gaining academic credit. Creditmobile students do not obtain their qualifications from the host institution abroad.
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 will be 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.
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
(https://doi.org/10.1787/f8d7880d-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[15]).
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.

EDUCATION AT A GLANCE 2019 © OECD 2019

B6. WHAT IS THE PROFILE OF INTERNATIONALLY MOBILE STUDENTS?  239

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 massively online open courses (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[15]) and Annex 3 for country-specific notes
(https://doi.org/10.1787/f8d7880d-en).

Source
Data refer to the academic year 2016/17 and are based on the UNESCO-UIS/OECD/EUROSTAT data collection
on education statistics administered by the OECD in 2018 (for details, see Annex 3 at
https://doi.org/10.1787/f8d7880d-en). Data on credit mobility, based on the UNESCO-UIS/OECD/EUROSTAT
data collection, were administered by Eurostat in 2018.
The UNESCO Institute of Statistics (UIS) provided data 1) for Argentina, China, India, Indonesia, Saudi Arabia
and South Africa; 2) for all countries beyond the OECD and partner countries; and 3) for OECD countries for the
period not covered by OECD statistics (2005 and 2010-17).
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, pp. 621-635, http://dx.doi.org/10.1111/twec.12319.

[10]

Appelt, S. et al. (2015), “Which factors influence the international mobility of research scientists?”,
OECD Science, Technology and Industry Working Papers, No. 2015/2, OECD Publishing, Paris,
https://dx.doi.org/10.1787/5js1tmrr2233-en.

[2]

Council of the European Union (2011), “Council conclusions on the modernisation of higher education”,
3128th Education, Youth, Culture and Sport Council Meeting, Brussels, 28 and 29 November 2011,
Council of the European Union, Brussels.

[12]

EDUCATION AT A GLANCE 2019 © OECD 2019

240  B6. WHAT IS THE PROFILE OF INTERNATIONALLY MOBILE STUDENTS?
EUROSTAT (2018), Learning mobility statistics - Statistics Explained,
https://ec.europa.eu/eurostat/statisticsexplained/index.php/Learning_mobility_statistics#Credit_mobile_students (accessed on
4 June 2019).

[13]

Guha, A. (1977), “Brain-drain issue and indicators on brain-drain”, International Migration, Vol. 15/1,
pp. 3-20, http://dx.doi.org/10.1111/j.1468-2435.1977.tb00953.x.

[7]

Hénard, F., L. Diamond and D. Roseveare (2012), Approaches to Internationalisation and Their
Implications for Strategic Management and Institutional Practice: A Guide for Higher Education
Institutions, OECD,
http://www.oecd.org/education/imhe/Approaches%20to%20internationalisation%20-%20final%20%20web.pdf (accessed on 29 April 2018).

[3]

OECD (2018), “How is the tertiary-educated population evolving?”, Education Indicators in Focus,
No. 61, OECD Publishing, Paris, https://dx.doi.org/10.1787/a17e95dc-en.

[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.

[15]

OECD (2016), OECD Science, Technology and Innovation Outlook 2016, OECD Publishing, Paris,
http://dx.doi.org/10.1787/sti_in_outlook-2016-en.

[1]

Perkins, R. and E. Neumayer (2014), “Geographies of educational mobilities: Exploring the uneven
flows of international students”, The Geographical Journal, Vol. 180/3, pp. 246-259,
http://dx.doi.org/10.1111/geoj.12045.

[4]

Sharifian, F. (2013), “Globalisation and developing metacultural competence in learning English as an
International Language”, Multilingual Education, Vol. 3/1, p. 7, http://dx.doi.org/10.1186/2191-50593-7.

[11]

UNESCO (2013), The International Mobility of Students in Asia and the Pacific, UNESCO,
http://unesdoc.unesco.org/images/0022/002262/226219E.pdf (accessed on 3 July 2018).

[8]

UNESCO (2013), The International Mobility of Students in Asia and the Pacific, UNESCO, Paris,
http://unesdoc.unesco.org/images/0022/002262/226219E.pdf (accessed on 7 May 2018).

[5]

UNESCO-UIS / OECD / EUROSTAT (2018), UOE data collection on formal education: Manual on
concepts, definitions and classifications, UNESCO-UIS / OECD / EUROSTAT, Montreal, Paris,
Brussels, http://uis.unesco.org/sites/default/files/documents/uoe2016manual_11072016_0.pdf
(accessed on 23 January 2019).

[14]

Weisser, R. (2016), “Internationally mobile students and their post-graduation migratory behaviour: An
analysis of 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.

[9]

EDUCATION AT A GLANCE 2019 © OECD 2019

B6. WHAT IS THE PROFILE OF INTERNATIONALLY MOBILE STUDENTS?  241

Indicator B6 Tables
Table B6.1

International and foreign student mobility in tertiary education (2010, 2013 and 2017)

Table B6.2

Distribution of international or foreign students by field of study and by region of origin (2017)

Table B6.3

Mobility patterns of foreign and international students (2017)

Cut-off date for the data: 19 July 2019. 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.
StatLink: https://doi.org/10.1787/888933981020

EDUCATION AT A GLANCE 2019 © OECD 2019

242  B6. WHAT IS THE PROFILE OF INTERNATIONALLY MOBILE STUDENTS?
Table B6.1. International and foreign student mobility in tertiary education (2010, 2013 and 2017)
International or foreign student enrolment as a percentage of total tertiary enrolment

1. Data on short-cycle tertiary programmes are based on nationality and refer to the Flemish community only.
2. Year of reference 2016.
Source: OECD/UIS/Eurostat (2019). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2019-36-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
StatLink 2 https://doi.org/10.1787/888933978398

EDUCATION AT A GLANCE 2019 © OECD 2019

B6. WHAT IS THE PROFILE OF INTERNATIONALLY MOBILE STUDENTS?  243

Table B6.2. Distribution of international or foreign students by field of study and by region of origin (2017)
All tertiary programmes

Note: This table does not present the shares of students enrolled in generic programmes and those whose region of origin is not known.
1 The share of students by country of origin is based on citizenship criteria.
2. Data on information and communication technologies are included in other fields.
3. Column 2 includes all interdisciplinary programmes, Column 9 includes public administration programmes.
4. Year of reference 2016.
Source: OECD/UIS/Eurostat (2019). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2019-36-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
StatLink 2 https://doi.org/10.1787/888933978417
EDUCATION AT A GLANCE 2019 © OECD 2019

244  B6. WHAT IS THE PROFILE OF INTERNATIONALLY MOBILE STUDENTS?
Table B6.3. Mobility patterns of foreign and international students (2017)

Note: Neighbouring countries are considered to be those with land or maritime borders with the host country. International education market shares refer to the number of
mobile students enrolled in each destination country as a share of all mobile students (Column 5) or of all mobile students in OECD and partner countries (Columns 6-10).
1. National tertiary students are calculated as total enrolment minus foreign students instead of total enrolment minus international students.
2. Excluding internationally mobile students enrolled in short-cycle tertiary programmes.
3. Year of reference 2016.
Source: OECD/UIS/Eurostat (2019). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2019-36-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
StatLink 2 https://doi.org/10.1787/888933978436

EDUCATION AT A GLANCE 2019 © OECD 2019

246  B7. WHAT ARE THE CHARACTERISTICS AND OUTCOMES OF DOCTORAL GRADUATES?

Indicator B7. What are the characteristics and
outcomes of doctoral graduates?
Highlights


Doctorate holders represent 1.1% of 25-64 year-olds on average across OECD countries, though this
varies from 0.1% or less in Indonesia and Mexico to more than 3% in Slovenia and Switzerland.



Women tend to be under-represented in certain fields at doctoral level even where they are
over-represented at master’s level. While 54% of graduates in natural science, mathematics and
statistics at master’s level were women, they represented only 46% of doctoral graduates on average
across OECD countries in 2017.



The relative employment advantage of adults with a doctoral degree compared to those with a master’s
varies across OECD countries from 10% in Finland, Hungary and Italy to 1% in Iceland and Sweden.

Figure B7.1. Share of 25-64 year-olds with a doctorate (2018)

1. Year of reference differs from 2018.
Countries are ranked in descending order of the share of 25-64 year-olds with a doctorate.
Source: OECD (2019), Table B7.3. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933978645

Context
A doctorate is the highest degree awarded in academia. Doctoral study plays an important role in developing
future innovations by training the researchers needed to advance knowledge and explore new research areas
relevant for the economy and society of tomorrow. Doctorate holders can develop a unique set of quantitative
and qualitative skills in both research methodology and statistical analysis, which are valuable in both an
academic and an industrial setting. Doctorate holders are attractive in the labour market and have on average
a high employment rate even during economic downturns. Doctorate holders also enjoy high relative earnings,
especially those who enter the private sector (European Commission, 2016[1]).

EDUCATION AT A GLANCE 2019 © OECD 2019

B7. WHAT ARE THE CHARACTERISTICS AND OUTCOMES OF DOCTORAL GRADUATES?  247

This has led many countries to implement reforms to develop and support doctoral studies and postdoctoral
research, stressing the crucial role of doctoral students and doctorate holders in terms of economic growth,
innovation and scientific research. Given the high investment in personal and financial resources and the
pivotal role of doctorate holders in pushing back the frontiers of knowledge, there has been growing policy
interest in attracting talented young people into careers in research, ensuring equitable access to doctoral
programmes for both men and women, and providing rewarding employment opportunities to its graduates
(OECD, 2019[2]).

Other findings


The median age at entry to doctoral programmes is 29 on average across OECD countries with 60%
of entrants aged between 26 and 37 years old.



On average across OECD countries, 25% of enrolled doctoral graduates are international students. In
some countries, international students make up the majority of graduates at doctoral level: more than
half are international students in Luxembourg and Switzerland.



On average across OECD countries, the employment rate of women with a doctorate is 5% higher
than that of women with a master’s, and is 15% or higher in Greece and Hungary. In contrast, men
with a doctorate have an employment rate that is 3% higher than men with a master’s, on average
across OECD countries, and this advantage does not exceed 8% in any OECD or partner country.

EDUCATION AT A GLANCE 2019 © OECD 2019

248  B7. WHAT ARE THE CHARACTERISTICS AND OUTCOMES OF DOCTORAL GRADUATES?

Analysis
Graduation and entry patterns at doctoral level
If current entry patterns continue, 2.3% of today’s young adults across OECD countries will enter a doctoral
programme in their lifetime. This varies from 4% and more in Switzerland and the United Kingdom – mostly due
to a large share of international students in these countries – to less than 0.5% in Chile, China, Colombia and
Saudi Arabia. Excluding international students, the countries with the highest entry rates at doctoral level are
Germany (3.2%), Spain (3.1%) and Korea (3.0%).
Doctorate holders account for a small proportion of the adult population. In 2018, just 1.1% of 25-64 year-olds
held a doctorate on average across OECD countries, though this varies from less than 0.1% in Indonesia and
Mexico to more than 3% in Slovenia and Switzerland (Figure B7.1). In spite of these low levels, the number of
doctorate holders has been increasing. Between 2013 and 2017, the number of students graduating with a
doctorate increased by approximately 8% across OECD countries, reaching 276 800 students in 2017. This
growth is primarily driven by the increase in doctoral graduates in Mexico, Spain and the United States over this
period. The United States remains the top supplier of doctoral graduates among OECD countries with about
71 000 graduates in 2017, followed by Germany and the United Kingdom (around 28 000 each).
Doctoral students are more likely than other tertiary students to study abroad. On average across OECD
countries, 22% of enrolled doctoral students are international or foreign students, compared to 13% at master’s
level and 4% at bachelor’s. In some countries, international students make up the majority of graduates at
doctoral level: more than half are international students in Luxembourg and Switzerland (Figure B7.2).

Figure B7.2. Share of international doctoral graduates (2017)
As a percentage of total doctoral graduates

Countries are ranked in descending order of the share of international doctoral graduates among total doctoral graduates.
Source: OECD (2019), Table B7.1. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933978664

Attracting the best doctoral students from around the world enables countries to build a leading role in research
and innovation, and some countries have implemented policies to nurture an attractive research environment for
potential students. Some countries, such as Australia, Italy, and Switzerland, charge lower fees for doctoral
programmes than at lower levels of education (see Indicator C5). Others recognise doctoral candidates as
EDUCATION AT A GLANCE 2019 © OECD 2019

B7. WHAT ARE THE CHARACTERISTICS AND OUTCOMES OF DOCTORAL GRADUATES?  249

employees rather than students, such as in Norway or Switzerland (European Commission/EACEA/Eurydice,
2017[3]). The language of instruction also plays an important role for doctoral students when they select their
institution and country of study. English-speaking countries tend to have a larger share of the international pool
of doctoral candidates: the share of international students among doctoral graduates is 40% or above in Australia,
New Zealand and the United Kingdom. Some non-English speaking countries, such as Denmark,
the Netherlands and Sweden, also offer a large share of programmes in English with the aim of attracting more
foreign talent (Wächter and Maiworm, 2014[4]). In all three countries, the share of international doctoral graduates
in 2017 was above the OECD average (Figure B7.2).
Career prospects and the availability of a strong funding stream for research and development (R&D) both play
an important role in supporting the progress of doctoral students both during and after study. Spending by higher
education institutions provides an indication of the emphasis placed on R&D within the national system and can
be indicative of future research opportunities. In 2015, spending on research and development in tertiary
institutions represented on average 0.5% of GDP across OECD countries, but exceeded 0.8% in Denmark,
Sweden and Switzerland (OECD, 2018[5]). While R&D within tertiary institutions is largely financed by the public
sector in most OECD countries, some systems are also able to raise funding from the business enterprise sector,
such as in Germany (14% of overall funding) or Korea (13% of overall funding). In both countries, funding by
business and enterprises represents more than 60% of gross domestic expenditure on total R&D (OECD, 2019[2]).
The strong financial input of enterprises into R&D demonstrates the engagement of the private sector in
advancing frontier research and indicates that doctoral graduates could benefit from a wider range of research
career opportunities beyond academia. This contributes to the attractiveness of doctoral programmes: both
Germany and Korea have comparatively high entry rates to doctoral programmes among OECD countries.

Age distribution of new entrants at doctoral level
Admission to doctoral studies is generally on the basis of a master’s degree or an equivalent qualification in most
countries. However, in some countries, such as Australia and the United States, students may enter a doctoral
degree following the completion of a bachelor’s programme, although in Australia an honours component is
additionally required (Class I or IIA) (OECD, 2019[2]). The median age at entry to doctoral programmes is 29 on
average across OECD countries with 60% of entrants between the ages of 26 and 37. However, the median age
varies markedly across countries, ranging from 26 in France and the Netherlands to 35 in Colombia (Figure B7.3).
The age of entry to a doctoral programme depends largely on the first-time entry and graduation ages to tertiary
education, and the extent to which students are likely to have started to work between tertiary degrees. Countries
where students typically first enter tertiary education at a young age are also likely to see students start their
doctoral degrees earlier. This is the case in Belgium, France, Hungary, Italy, Lithuania, the Netherlands, Poland
and the United Kingdom, where both the average age at entry to bachelor’s programmes and the median age at
entry to doctoral levels are below the OECD average. Similarly, countries where students first enter a bachelor’s
programme at an older age, such as Australia, Finland, Iceland, Israel, Latvia, New Zealand and Norway, also
have a higher median age at entry to doctoral programmes. However, there are some exceptions to this pattern:
while students in Greece, Korea, Mexico, Portugal and Spain enter a bachelor’s degree for the first time aged 21
or younger, those pursuing a doctorate tend not to enrol in their degree before the age of 30. Students in these
countries may value opportunities to work first to gain industry or sector experience, which they can leverage in
their doctoral research. In contrast, first-time tertiary entrants to bachelor programmes in Denmark, Estonia and
Switzerland are among the oldest across OECD countries, but the median age of entry to doctoral programmes
is below the OECD average of 29. This may be due to the higher prevalence of master’s long-first degrees in
some of these countries (Estonia and Sweden), or to the high share of international doctoral students, who are
often younger than national ones.
The age distribution of new entrants to doctoral programmes provides insights into the diversity of entrants’ ages,
compared to the median value. In some countries, the age distribution is closely centred on the median, implying
a relatively small age difference among doctoral students. This is the case in Germany and the Netherlands,
where less than 6 years separate the 80th and 20th percentile age groups. In other countries, the age distribution
EDUCATION AT A GLANCE 2019 © OECD 2019

250  B7. WHAT ARE THE CHARACTERISTICS AND OUTCOMES OF DOCTORAL GRADUATES?
is much wider. For example in Iceland, Korea and Portugal, new entrants in the 80th percentile are at least
17 years older than those in the 20th percentile. However in all OECD countries, the median age is closer to the
20th percentile, indicating the age distribution skews more towards the younger than the older age group
(Figure B7.3).

Figure B7.3. Age distribution of new entrants to doctoral level (2017)

Countries are ranked in descending order of the median age of new entrants to doctoral level.
Source: OECD (2019),Table B7.1. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933978683

Fields studied by doctoral graduates
Students entering a doctoral programme are expected to contribute to and expand the knowledge base in their
selected field of study. In contrast to lower levels of tertiary education, doctoral candidates tend to specialise
more heavily in the science and technology-related fields of study. The broad field of natural sciences,
mathematics and statistics attracts the largest share of doctoral graduates, 23% on average across OECD
countries, followed by engineering, manufacturing and construction, and health and welfare, both at 17% (Table
B7.2). In contrast, business, administration and law, which accounted for the largest share of graduates at
bachelor’s level, represents less than 10% at doctoral level.
There are marked differences among countries in the distribution of the fields studied by doctoral graduates.
Although most graduate from natural sciences, mathematics and statistics on average across OECD countries,
this varies from almost none in Colombia to 43% in France. Health and welfare is a common field of study in
Denmark, Japan, the Netherlands and Norway, representing more than 30% of graduates at doctoral level. In
Canada, 18% of doctoral students graduated from the broad field of social science, journalism and information,
although the share of doctoral graduates from this field does not exceed 13% in three-quarters of countries with
available data. Finally, more than 22% of doctoral students graduated from the field of information and
communication technologies (ICT) in Luxembourg, compared to an OECD average of 4% (Table B7.2).
Fields of study are a key part of students’ decisions to pursue a doctoral degree abroad. Some countries devote
more resources to research in certain fields and therefore benefit from strong international recognition. On
average across OECD countries, the distribution of fields among international doctoral graduates mirrors the
distribution among all doctoral students. However, there are also notable exceptions. The field of engineering,
EDUCATION AT A GLANCE 2019 © OECD 2019

B7. WHAT ARE THE CHARACTERISTICS AND OUTCOMES OF DOCTORAL GRADUATES?  251

manufacturing and construction attracts 22% of international doctoral students compared to 17% of all students
on average. There are also striking differences within countries, highlighting potential specialisations and the
attractiveness of research in some countries for a given field of study. For instance in Chile and the United States,
the share of international doctoral graduates having studied engineering, manufacturing or construction was
double that of national students. In Iceland, 65% of international doctoral graduates in 2017 had studied natural
sciences, mathematics and statistics, compared to 34% of all doctoral graduates (Table B7.2).

Gender distribution of doctoral graduates
While the share of women has overtaken that of men at bachelor’s and master’s level, women are still slightly
under-represented at doctoral level. Women represented 47% of doctoral graduates in 2017, a 4 percentagepoints increase on 2005 levels. Gender parity (where women represent between 48-52% of all graduates) is
observed in less than one-third of OECD member and partner countries with available data. Moreover, some
strong gender imbalances exist: more than 60% of those graduating from doctoral programmes in Iceland and
Latvia were women in 2017, compared to less than 40% in the People’s Republic of China, Indonesia, Japan,
Korea and Saudi Arabia.
Given the high share of international students in doctoral programmes, the gender distribution among graduates
can also be affected by the characteristics of incoming students at this level who are predominantly male. In
2017, only 40% of international doctoral graduates were women compared to 53% among nationals on average
across OECD countries. However, the difference between the share of women among international and national
doctoral graduates exceeds 30 percentage points in Iceland, Latvia, and Lithuania – a combination of a high
share of women among national graduates and a low share of women among international ones. In New Zealand,
Switzerland and the United Kingdom, where international students make up more than 45% of doctoral
graduates, the difference in the share of women between international and national students is much lower and
below 10 percentage points.
Gender imbalances are more evident when analysing graduation patterns across fields of study. Women tend to
be under-represented at doctoral level even in some fields where they are over-represented at master’s level.
While 54% of graduates in natural science, mathematics and statistics at master’s level were women, they made
up only 46% of doctoral graduates in this field on average across OECD countries in 2017 (Figure B7.4). A similar
pattern is observed for business, administration and law. In other fields like education, health and welfare, and
social sciences, arts, and humanities, the share of women decreases between master’s and doctoral levels, but
women still represent the majority of recent doctoral graduates. In contrast, although women are underrepresented in engineering, manufacturing, and construction at master’s level, their share remains very similar
at doctoral level (Table B7.1).
Beyond these general trends, there is strong variability across countries. The strongest declines in the share of
women in the field of natural sciences, mathematics and statistics are observed in the Czech Republic, Denmark,
India, Korea, Poland, Saudi Arabia and Slovenia where the share of women graduates falls by 15 percentage
points or more between master’s and doctoral level. While this creates greater gender parity in Poland and
Slovenia at the doctoral level (as women are strongly over-represented at master’s level), it creates a greater
gender imbalance, to the disadvantage of women, in Denmark and Korea (Figure B7.4).
The picture is slightly different for the fields of engineering, manufacturing and construction, even though on
average across OECD countries the share of women remains the same across master’s and doctoral graduates.
About half of OECD member and partner countries have improved their gender balance in this field of study at
doctoral level compared to master’s. This is most striking in Israel and in Latvia where the share of women
increased by 12 and 20 percentage points respectively between doctoral and master’s graduates. In contrast,
the share of women in engineering, manufacturing and construction declines by 10 or more percentage points in
Colombia, the Czech Republic, Iceland, India, New Zealand and South Africa (Table B7.1).

EDUCATION AT A GLANCE 2019 © OECD 2019

252  B7. WHAT ARE THE CHARACTERISTICS AND OUTCOMES OF DOCTORAL GRADUATES?

Figure B7.4. Share of women graduates in natural sciences, mathematics and statistics at master's and
doctoral levels (2017)

1. Year of reference 2016.
Countries are ranked in descending order of the share of women with master's degrees in natural sciences, mathematics and statistics.
Source: OECD (2019), Table B7.1. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933978702

The smaller share of women in science fields is reflected through their contribution to research outputs and
innovation. Only 22% of scientific authors are women, and the proportion of patents featuring women inventors
ranges between about 4% in Austria to over 15% in Portugal (OECD, 2017[6]). This has prompted some countries
to initiate policy action to promote women in science, technology, engineering and mathematics (STEM) fields
and in research more generally. Across the European Union (EU), the European Charter for Researchers and
Code of Conduct places an emphasis on gender balance in all staff categories (European Commission, 2016[7]).
In addition, the research programme Horizon 2020 includes gender equity in research and innovation among its
work programme and, among other goals, aims to reinforce women’s presence and progression in STEM fields
of study among EU members. Some countries have implemented financial incentives and support mechanisms
to encourage higher participation of women in science-related fields. For example, the National Science
Foundation in the United States awards grants to support the ADVANCE programme which aims at increasing
the participation and advancement of women in academic science and engineering careers. In Korea, a dedicated
fund supports female student research teams in architecture, materials and machinery, as well as computers
(Borgonovi et al., 2018[8])

Doctorate holders and labour-market outcomes
Rewarding work opportunities can act as an incentive for students to enter and complete a doctoral degree and
are essential for prospective candidates in evaluating the attractiveness of doctoral programmes. Doctorate
holders have a range of employment opportunities available to them, most of which are outside the higher
education system (see Indicator A3).
On average across OECD countries, 25-64 year-olds with a doctorate have the highest employment rate of all
attainment levels, at 92% compared to 88% for those with a master’s degree. However, the relative employment
advantage over a master’s degree varies across countries, ranging from 10% in Finland, Hungary and Italy to
1% in Iceland and Sweden (Table B7.3).

EDUCATION AT A GLANCE 2019 © OECD 2019

B7. WHAT ARE THE CHARACTERISTICS AND OUTCOMES OF DOCTORAL GRADUATES?  253

Young doctorate holders, those aged 25-34, have similarly strong prospects although their employment rates
tend to be lower than for 25-64 year-olds and their comparative advantage over their peers with a master’s degree
tends to be more variable (see Indicator A3).
Both women and men with a doctorate benefit from higher employment rates than those with a master’s degree,
and the gender gap narrows with higher educational attainment. On average across OECD countries, the
employment rate of 25-64 year-old men with a doctoral degree is 5 percentage points higher than that of similarly
educated women. Among those with a master’s degree, the employment difference is 6 percentage points in
favour of men (Table B7.3). However, some countries have small or non-significant differences between the
employment rate of adults with a master’s degree and those with a doctorate and these results should be
interpreted with caution.
This reduction in the employment gap between men and women with a doctorate is due to the stronger increase
in the employment rate among women compared to men at this level of educational attainment. Whereas the
employment rate of women with a master’s degree is lower than that of similarly educated men in every OECD
country, the picture tends to shift at doctoral level. Women with a doctoral degree have a higher employment rate
than their male counterparts in Australia, Belgium, Greece, Portugal and Sweden. In many other countries, the
increase in employment rates for those attaining a doctorate compared to a master’s is stronger for women than
for men. On average across OECD countries, the employment rate of women with a doctorate is 5% higher than
that of women with a master’s, and is 15% or higher in Greece and Hungary. In contrast, men with a doctorate
have an employment rate that is 3% higher than men with a master’s on average across OECD countries, and
this advantage does not exceed 8% in any OECD or partner country (Figure B7.5).

Figure B7.5. Relative employment rate of 25-64 year-old doctorate holders compared to master's holders (2018)

How to read this figure: A relative employment rate above 100% indicates that doctorate holders have a higher employment rate than adults with a
master’s degree. A relative employment rate below 100% indicates the opposite.
1. Year of reference differs from 2018.
Countries are ranked in descending order of the relative employment rate of doctorate holders compared to master's holders.
Source: OECD (2019), Table B7.3. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933978721

EDUCATION AT A GLANCE 2019 © OECD 2019

254  B7. WHAT ARE THE CHARACTERISTICS AND OUTCOMES OF DOCTORAL GRADUATES?
In some countries, adults with doctorates still have lower employment rates than those with a master’s: this is the
case for women in Estonia and Norway and for men in Australia, Norway and Sweden.
As well as the likelihood of finding employment, students also consider their career prospects and expected
earnings when deciding to enter a doctoral programme and pursue a career in research. Career options for
doctorate holders can be diverse, and range from academia to business and industry, public administration or
self-employment (see Box A3.1 in Indicator A3).
While the higher education sector has been the traditional career destination for doctorates, many doctoral
graduates are turning towards businesses and industry, where they are typically better paid. The business sector
represents the greatest share of researchers – over 70% – in Israel, Japan, Korea, and the United States (OECD,
2017[6]). However, the opportunities available for the different fields of study can be unequal, reflecting variable
labour-market demands for specialised skills and knowledge. For instance, earnings in agricultural sciences and
the humanities are below the overall median for doctorate holders in most countries, whereas earnings in medical
and health sciences tend to be above median levels (Auriol, Misu and Freeman, 2013[9])

Definitions
Doctoral level corresponds to ISCED-2011 level 8, which leads directly to the award of an advanced research
qualification, e.g. a PhD. In most countries, the theoretical duration of these programmes is three years full time
(leading to a cumulative total of at least seven years of full-time equivalent tertiary education), although the actual
enrolment time is typically longer. Programmes at this ISCED level are devoted to advanced studies and original
research and are typically offered by research-oriented tertiary educational institutions such as universities.
Doctoral programmes may exist in both academic and professional fields (OECD/Eurostat/UNESCO Institute for
Statistics, 2015[10]).
Doctoral students refers to all individuals pursuing a degree at doctoral level irrespective of their legal status in
their country (student or employee).
Doctorate holders refers to the adult population between 25-64 years of age with a doctorate degree.
Graduates refer to those graduating in the reference year. They 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,
whereas a repeat graduate may have already obtained an earlier degree at the same level.
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 often considered first-time
entrants in that country
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. Therefore, the average age of first-time graduates may be underestimated by up to six
months.

Methodology
See the Methodology section in indicators A1, A3 and B4.
Please see the OECD Handbook for Internationally Comparative Education Statistics (OECD, 2018[11]) for more
information and Annex 3 for country-specific notes (https://doi.org/10.1787/f8d7880d-en).

EDUCATION AT A GLANCE 2019 © OECD 2019

B7. WHAT ARE THE CHARACTERISTICS AND OUTCOMES OF DOCTORAL GRADUATES?  255

Source
For information on sources for attainment and employment data, see Indicator A1 and A3.
Data on entrants and graduates refer to the academic year 2016/17 and are based on the UNESCOUIS/OECD/EUROSTAT data collection on education statistics administered by the OECD in 2018 (for details,
see Annex 3 at https://doi.org/10.1787/f8d7880d-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
Auriol, L., M. Misu and R. Freeman (2013), “Careers of doctorate holders: Analysis of labour market
and mobility indicators”, OECD Science, Technology and Industry Working Papers, No. 2013/04,
OECD Publishing, Paris, http://dx.doi.org/10.1787/5kmh8phxvvf5-en.

[9]

Borgonovi, F. et al. (2018), Empowering Women in the Digital Age; Where Do We Stand?, OECD,
Paris, https://www.oecd.org/social/empowering-women-in-the-digital-age-brochure.pdf (accessed on
30 August 2018).

[8]

European Commission (2016), PEGASUS - Giving Wings to the Career of Experienced Researchers,
European Commission, Brussels, https://cordis.europa.eu/result/rcn/191992_en.html (accessed on
23 May 2018).

[7]

European Commission (2016), She Figures 2015, Publications Office of the European Union,
Luxembourg, http://dx.doi.org/10.2777/064694.

[1]

European Commission/EACEA/Eurydice (2017), Modernisation of Higher Education in Europe:
Academic Staff – 2017, Publications Office of the European Union, Luxembourg,
https://publications.europa.eu/en/publication-detail/-/publication/40f84414-683f-11e7-b2f201aa75ed71a1/language-en (accessed on 18 October 2018).

[3]

OECD (2019), Benchmarking Higher Education System Performance, Higher Education, OECD
Publishing, Paris, https://dx.doi.org/10.1787/be5514d7-en.

[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.

[11]

OECD (2018), OECD Science, Technology and R-D Statistics, http://dx.doi.org/10.1787/strd-data-en.

[5]

OECD (2017), OECD Science, Technology and Industry Scoreboard 2017: The Digital Transformation,
OECD Publishing, Paris, https://dx.doi.org/10.1787/9789264268821-en.

[6]

OECD/Eurostat/UNESCO Institute for Statistics (2015), ISCED 2011 Operational Manual: Guidelines
for Classifying National Education Programmes and Related Qualifications, OECD Publishing,
Paris, https://dx.doi.org/10.1787/9789264228368-en.

[10]

EDUCATION AT A GLANCE 2019 © OECD 2019

256  B7. WHAT ARE THE CHARACTERISTICS AND OUTCOMES OF DOCTORAL GRADUATES?
Wächter, B. and F. Maiworm (2014), “English-taught programmes in European higher education”, ACA
Papers on International Cooperation in Education, http://www.acasecretariat.be/fileadmin/aca_docs/images/members/ACA-2015_English_Taught_01.pdf (accessed
on 28 May 2019).

[4]

Indicator B7 Tables
Table B7.1

Profile of doctoral graduates (2017)

Table B7.2

Distribution of graduates from doctoral programmes, by field of study (2017)

Table B7.3

Educational attainment and employment rates of 25-64 year-olds at master's and doctoral
levels (2018)

Cut-off date for the data: 19 July 2019. 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.
StatLink: https://doi.org/10.1787/888933981039

EDUCATION AT A GLANCE 2019 © OECD 2019

B7. WHAT ARE THE CHARACTERISTICS AND OUTCOMES OF DOCTORAL GRADUATES?  257

Table B7.1. Profile of doctoral graduates (2017)
Age distribution, international graduates, share of women master's and doctoral graduates by field, and number of doctoral graduates

Note: Data reported in this table concern total graduates except for the share of international doctoral graduates which refers to first-time graduates.
1. All fields of study include the field Information and Communication Technologies (ICTs).
2. Columns 11,12 and 13 display the sum of all OECD, EU23 and G20 countries instead of an average.
3. Year of reference 2016.
Source: OECD/UIS/Eurostat (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888933978588

EDUCATION AT A GLANCE 2019 © OECD 2019

258  B7. WHAT ARE THE CHARACTERISTICS AND OUTCOMES OF DOCTORAL GRADUATES?
Table B7.2. Distribution of graduates from doctoral programmes, by field of study (2017)

Note: The distribution excludes the fields of Agriculture, forestry, fisheries and veterinary; Education; and Services, which tend to represent a lower share of graduates at
doctoral level.
1. All fields of study include the field Information and Communication Technologies (ICTs)..
2. Year of reference 2016.
Source: OECD/UIS/Eurostat (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787888933978607

EDUCATION AT A GLANCE 2019 © OECD 2019

B7. WHAT ARE THE CHARACTERISTICS AND OUTCOMES OF DOCTORAL GRADUATES?  259

Table B7.3. Educational attainment and employment rates of 25-64 year-olds at master's and doctoral levels (2018)

1. Year of reference differs from 2018; for more details, please refer to Table A1.1 for Columns 1 to 3, and Table A3.1. for Columns 4 to 9.
Source: OECD/ILO/UIS (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888933978626

EDUCATION AT A GLANCE 2019 © OECD 2019

 261

Chapter C. Financial resources invested
in education

Indicator C1 How much is spent per student on educational institutions?
StatLink https://doi.org/10.1787/888933981058
Indicator C2 What proportion of national wealth is spent on educational institutions?
StatLink https://doi.org/10.1787/888933981077
Indicator C3 How much public and private investment on educational institutions is
there?
StatLink https://doi.org/10.1787/888933981096
Indicator C4 What is the total public spending on education?
StatLink https://doi.org/10.1787/888933981115
Indicator C5 How much do tertiary students pay and what public support do they
receive?
StatLink https://doi.org/10.1787/888933981134
Indicator C6 On what resources and services is education funding spent?
StatLink https://doi.org/10.1787/888933981153
Indicator C7 Which factors influence teachers’ salary cost?
StatLink https://doi.org/10.1787/888933981172

EDUCATION AT A GLANCE 2019 © OECD 2019

262 

The framework for educational finance indicators
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.

EDUCATION AT A GLANCE 2019 © OECD 2019

 263

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).



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).



The contribution of various factors to the salary cost of teachers per student in public institutions
(Indicator C7).

EDUCATION AT A GLANCE 2019 © OECD 2019

264  C1. HOW MUCH IS SPENT PER STUDENT ON EDUCATIONAL INSTITUTIONS?

Indicator C1. How much is spent per student on
educational institutions?
Highlights


On average, OECD countries spend 1.7 times more per student at the tertiary level than in non-tertiary
education (primary, secondary and post-secondary non-tertiary levels). OECD countries spend on
average USD 10 500 per student on primary to tertiary educational institutions. This represents about
USD 9 400 per student at primary, secondary and post-secondary non-tertiary level, and USD 15 600
at tertiary level.



In non-tertiary education, spending on core educational services represents 93% of institutions’
expenditure per student. At the tertiary level, a much lower share of institutional expenditure goes to
core services (67%), while roughly 30% of total educational expenditure per student goes on research
and development (R&D).



The cumulative expenditure per student from the age of 6 to 15 amounts to about USD 93 000 on average
across OECD countries.

Figure C1.1. Total expenditure on educational institutions per full-time equivalent student, by level of
education (2016)
In equivalent USD converted using PPPs

1. Primary education includes pre-primary programmes. Post-secondary non-tertiary figures are treated as negligible.
2. Year of reference 2017.
Countries are ranked in descending order of the total expenditure per student on tertiary education.
Source: OECD/UIS/Eurostat (2019), Table C1.1. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880den).
Statlink2 https://doi.org/10.1787/888933978797

EDUCATION AT A GLANCE 2019 © OECD 2019

C1. HOW MUCH IS SPENT PER STUDENT ON EDUCATIONAL INSTITUTIONS?  265

Context
The willingness of policy makers to expand access to educational opportunities and to provide high-quality
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 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 influenced by teachers’ salaries (see Indicators C7 and D3), pension systems,
instructional and teaching hours (see Indicators C7, D1 and D4), 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, reduce average class sizes or
change staffing patterns (see Indicator D2) have also affected per-student expenditure. Ancillary services and
R&D activities 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.

Other findings


On average, total expenditure per student is higher in private institutions than in public ones. Total
expenditure in primary to tertiary public institutions amounts to over USD 10 300 per student,
compared to USD 10 800 in private ones (Table C1.5, available on line).



From 2010 to 2016, expenditure on non-tertiary educational institutions increased by 5% on average
across OECD countries, while the number of students remained stable over this period. This resulted in an
increase of 5% in expenditure per student over the same period.



Annual expenditure per student on educational institutions as a share of gross domestic product (GDP)
per capita amounts to 23% at primary, secondary and post-secondary non-tertiary levels 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 students.

EDUCATION AT A GLANCE 2019 © OECD 2019

266  C1. HOW MUCH IS SPENT PER STUDENT ON EDUCATIONAL INSTITUTIONS?

Analysis
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 2016, annual spending per student from primary to tertiary
education ranged from around USD 3 600 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 per student on primary to tertiary educational institutions.
The way resources are allocated across the different levels of education vary widely and largely reflect the mode
of educational provision. Education still essentially takes place in settings with generally similar organisation,
curricula, teaching style and management. These shared features have tended to result in similar patterns of
expenditure per student from primary to post-secondary non-tertiary levels. In recent decades, however, greater
use of private funds for tertiary education has modified the allocation of expenditure at this level compared to
lower ones (see Indicator C3, and Table C1.5, available on line). In 2016, OECD countries on average spent
around USD 9 400 per student at the primary, secondary and post-secondary non-tertiary levels and USD 15 600
at the tertiary level, although at this level, the average is affected by high expenditure in a few countries, most
notably Canada, Luxembourg, Norway, Sweden, the United Kingdom and the United States (Table C1.1 and
Figure C1.1). These differences lead to large differences in the cumulative expenditure per student over the
theoretical duration of studies (Table C1.6, available on line). Significant differences are also observed at the
subnational level (Box C1.1).

Box C1.1. Subnational variation in annual expenditure per student on educational institutions
Annual expenditure per student can be quite heterogeneous across countries with large differences across
regions. Among the three countries with available data at subnational level, Canada has the highest variation
in annual expenditure per student on educational institutions at primary and secondary levels combined: the
region with the highest value (USD 23 000) spends almost three times as much per student as the region with
the lowest value (USD 8 000). Regional differences were the smallest in Belgium and Germany (OECD,
2019[1]).
An examination of regional differences in spending on primary and secondary education presents contrasting
patterns. In Germany, 8 of the 12 Länder that spent less than the national average per student were located
in the western part of the country. This may be explained by the sharp demographic downturn in the eastern
Länder that led to a reduction in the number of students enrolled (OECD, 2019[1]).
To ensure comparability 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.
The distribution of expenditure at different levels of education reflects governments’ priorities and 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 18% more per secondary student than they do per primary student. This percentage is 50% or above in
Canada, the Czech Republic, France and the Netherlands, but countries invest more per primary student than
they do per secondary student in Chile, Colombia, Iceland, Israel, Lithuania, the Slovak Republic, Slovenia and
the United Kingdom, despite the fact that teacher’s salaries tend to increase with higher levels of education.
Similarly, educational institutions in OECD countries spend an average of 31% more on each tertiary student
(excluding R&D) than on each primary student. Turkey and the United States spend twice as much on a tertiary
student (excluding R&D) than on a primary student (Table C1.1).
EDUCATION AT A GLANCE 2019 © OECD 2019

C1. HOW MUCH IS SPENT PER STUDENT ON EDUCATIONAL INSTITUTIONS?  267

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 and other
expenditure related to education) represents 87% of total expenditure per student from primary to tertiary
educational institutions and it exceeds 90% in Chile, Latvia and Poland. In about a third of OECD and
partner countries with available data, annual expenditure on research and development (R&D) and ancillary
services per student accounts for around 15% or more of the total annual expenditure per student on primary to
tertiary institutions. In the Slovak Republic and Sweden, this reaches 20%.

Figure C1.2. Total expenditure on educational institutions per full-time equivalent student, by type of
service (2016)
In equivalent USD converted using PPPs

1. Primary education includes pre-primary programmes. Post-secondary non-tertiary figures are treated as negligible.
2. Year of reference 2017.
Countries are ranked in descending order of total expenditure on educational institutions per full-time equivalent student.
Source: OECD/UIS/Eurostat (2019), Table C1.2. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933978816

EDUCATION AT A GLANCE 2019 © OECD 2019

268  C1. HOW MUCH IS SPENT PER STUDENT ON EDUCATIONAL INSTITUTIONS?
However, this overall picture masks large variations across levels of education (Table C1.2 and Figure 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 spend 93% of their total per-student expenditure
(about USD 8 700) on core educational services at this level. However, in Finland, France, the Slovak Republic
and Sweden, ancillary services account for 10% or slightly more of the expenditure per student (Table C1.2).
The share of total expenditure on educational institutions per student devoted to core services differs more across
countries at tertiary level, as R&D expenditure can account for a significant proportion of educational spending
(Table C1.2). On average across OECD countries, 67% of total expenditure on educational institutions at tertiary
level goes to core services, while around 30% is spent on research and development. OECD countries in which
R&D is mostly conducted in tertiary education institutions tend to report higher levels of expenditure per student
than those where a large proportion of R&D is performed in other public institutions or in industry. Excluding R&D
activities, average expenditure per student on average across OECD countries amounts to over USD 11 000,
ranging from less than USD 6 000 in Lithuania and Mexico to more than USD 25 000 in Luxembourg and
the United States.
On average across OECD countries, expenditure on R&D and ancillary services at the tertiary level represents
33% of all tertiary expenditure on educational institutions per student. In five 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 Sweden (54%) the country with the highest share.
However, the share of expenditure on ancillary services tends to be lower in tertiary education than at lower
levels of education. On average, only 5% of expenditure on tertiary institutions goes towards ancillary services,
and the amount is negligible (below USD 100 per student) in Austria, Chile, the Czech Republic, Estonia, Finland,
Israel, Korea, Poland and Sweden. The United Kingdom and the United States spend the most in ancillary
services per student at tertiary level among OECD countries, over USD 2 000 per student.

Figure C1.3. Cumulative expenditure on educational institutions per full-time equivalent student between
the age of 6 and 15 (2016)
In equivalent USD converted using PPPs

1. Year of reference 2017.
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 (2019), Table C1.6, available on line. See Source section for more information and Annex 3 for notes
(https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933978835
EDUCATION AT A GLANCE 2019 © OECD 2019

C1. HOW MUCH IS SPENT PER STUDENT ON EDUCATIONAL INSTITUTIONS?  269

Policy makers are interested in the relationship between the resources devoted to education and the outcomes
of their education systems (Box B1.1 in Education at a Glance 2017 (OECD, 2017[2])). The cost of education
across countries depends not only on the annual expenditure per student, but also on the total duration of studies
at each level and the level of enrolment. High expenditure per student, for example, might be offset by short
programmes or limited access to education at certain levels. On the other hand, a seemingly inexpensive
education system in per student terms 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 cumulative expenditure per
student between the ages of 6 and 15 at these levels shows how much it costs to teach a student on average
during the course of current compulsory education (Figure C1.3 and Table C1.6, available on line). On average
across OECD countries, the total cumulative expenditure per student from the age of 6 to 15 amounts to around
USD 92 700 per student. Theoretical cumulative expenditure on educational institutions per student varies
considerably among countries. Austria, Iceland, Luxembourg, Norway, Sweden and the United States spend over
USD 120 000 per student over this period, while the figure is below USD 50 000 in Colombia and Turkey.

Expenditure per student on educational institutions relative to per capita GDP
Expenditure on educational institutions per student relative to gross domestic product (GDP) per capita is a
measure of spending that takes into account the relative wealth of OECD countries. Since access to education
in most OECD countries is universal (and usually compulsory) at lower levels of schooling, the amount spent per
student as a share of per capita GDP can indicate whether the resources spent per student are proportionate to
the country’s ability to pay. At higher levels of education, where student enrolment varies 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.
In OECD countries, overall expenditure per student on educational institutions from primary to tertiary levels
averages 26% of per capita GDP, which can be broken down into 23% at primary, secondary and post-secondary
non-tertiary levels and 38% at the tertiary level (Table C1.4, available on line). Countries with low levels of
expenditure per student may still be investing relatively large amounts as a share of per capita GDP. For example,
although Portugal’s expenditure per student for all educational levels and its per capita GDP are both below the
OECD average, it spends an above-average share of its per capita GDP per student at 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 between countries with similar levels of per capita
GDP, especially among countries where 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, secondary and post-secondary non-tertiary education. Austria
spends 28% of per capita GDP on non-tertiary institutions (above the OECD average of 23%) while
the Netherlands spends 22% (Table C1.4, available on line).
At tertiary level, there is more variation in spending and in the relationship between countries’ relative wealth and
their level of tertiary expenditure. Spending on tertiary institutions in Canada, the United Kingdom and
the United States represents more than 50% of per capita GDP for each student (Table C1.4, available on line).
The high share for the United Kingdom is mostly the result of its high expenditure on R&D, which accounts for
about one-fourth of total expenditure per student at this level (Table C1.2).

Changes in expenditure per student on educational institutions between 2010 and 2016
Changes in expenditure on educational institutions largely reflect changes in the size of the school-age population
and in teachers’ salaries. Teachers’ salaries, the main component of educational costs, have increased in the

EDUCATION AT A GLANCE 2019 © OECD 2019

270  C1. HOW MUCH IS SPENT PER STUDENT ON EDUCATIONAL INSTITUTIONS?
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.
At non-tertiary levels, the number of students has remained fairly stable on average across OECD countries
between 2010 and 2016. During the same period, expenditure by non-tertiary educational institutions increased
by an average of 5% (Table C1.3). As a result, expenditure per student at these levels increased by 5% in 2016
compared to its 2010 level. Most OECD countries spent more per student in 2016 than they did in 2010, with the
exception of some countries that were heavily hit by the economic crisis of 2008 such as Australia, Estonia,
Ireland, Italy, Slovenia and Spain. Expenditure per student increased by over 20% in Chile, Israel, and Latvia.
In Chile, Latvia, Poland and the Slovak Republic, decreases in enrolments of more than 5% coincided with
significant increases in spending on educational institutions per student between 2010 and 2016. In contrast, the
increase in number of students enrolled was accompanied by a reduction in spending on educational institutions
per student in Ireland, Slovenia and Spain.
Expenditure at tertiary level increased at a higher rate than at lower levels of education, rising on average by
9% between 2010 and 2016. It also increased more than the number of students enrolled over this period (3%).
As a result, OECD countries recorded an average increase of 8% in expenditure per student over this period.
However, there are stark differences across countries. Among OECD and partner countries with available data,
Australia, Finland, France, Germany, Italy, Lithuania, Mexico, Portugal 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 contrast, expenditure per tertiary student increased in Estonia,
Iceland and the Slovak Republic due to an increase in total expenditure and a reduction in the number of students
at tertiary level (Table C1.3). Changes in expenditure on tertiary educational institutions can affect the allocation
of resources across types of service, and in particular, the investment in core educational goods and services
(Box C1.2).

Box C1.2. Change in spending on educational core goods and services in tertiary institutions
Spending on educational core goods and services provides educational institutions with the necessary
resources to accomplish their main mission, developing the skills of students. Comparing the change in
expenditure on core services with the change in expenditure on all services provides a better understanding
of how changes in total expenditure on institutions affect the funds available for core educational goods and
services. This is particularly relevant at tertiary levels of education, where a greater share of total spending is
allocated to services other than core educational goods and services, such as ancillary services or research
and development (R&D). While there may be reasons to prioritise spending in these areas, a reduction in
investment in educational core services might affect the quality of learning and the material conditions under
which instruction takes place, particularly in countries where enrolment in tertiary education has increased
significantly.
Between 2012 and 2016, the rate of change of expenditure on core educational services and total expenditure
on tertiary educational institutions has varied significantly across countries (Figure C1.a). Total expenditure
on tertiary institutions increased in two-thirds of OECD and partner countries during this period. In most of
these, spending on core educational goods and services also increased, although to differing extents.
Spending on core educational goods and services increased by at least 24 percentage points more than total
spending on tertiary institutions in Estonia and the Slovak Republic. In contrast, spending on core educational
goods and services increased more slowly than total expenditure on tertiary institutions in Belgium, Finland,
Chile, Ireland, Israel, Lithuania, the Russian Federation, Sweden, the United Kingdom, and the United States.
Luxembourg is the only country to witness both an increase in total spending at tertiary level (+34%) and a

EDUCATION AT A GLANCE 2019 © OECD 2019

C1. HOW MUCH IS SPENT PER STUDENT ON EDUCATIONAL INSTITUTIONS?  271

decrease in spending on core educational services (-24%). This difference suggests increased investment in
ancillary services or R&D over this period at the expense of core educational service and is indicative of a
research based higher education policy system.
The other third of countries saw their total investments on tertiary institutions decline between 2012 and 2016.
However, Hungary and Portugal managed to increase total spending on core educational goods and services
in spite of these budget cuts by reallocating funds from ancillary services or R&D. In contrast, spending on
core educational goods and services fell in the Czech Republic, Italy, Latvia and Slovenia although to a lesser
extent than total spending on tertiary institutions.

Figure C1.a. Growth of core and total expenditure on tertiary educational institutions between 2012
and 2016

Note: Core educational expenditure has been obtained by subtracting expenditure devoted on ancillary services and R&D from the total expenditure
on educational institutions. A positive figure refers to a higher growth rate of the expenditure on core educational services compared to the growth
rate of total expenditure on all services. See Definitions and Methodology sections for more information.
1. Reference period 2012-2015.
2. Reference period 2013-2016.
Countries are ranked in descending order of the percentage-point difference.
Source: OECD/UIS/Eurostat (2019), Education at a Glance Database http://stats.oecd.org/. See Source section for more information and Annex 3
for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933978854

Definitions
Ancillary services are services provided by 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.

EDUCATION AT A GLANCE 2019 © OECD 2019

272  C1. HOW MUCH IS SPENT PER STUDENT ON EDUCATIONAL INSTITUTIONS?
Core educational services include all expenditure that is directly related to instruction in educational institutions,
including teachers’ salaries, construction and maintenance of school buildings, teaching materials, books, and
school administration.
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 currencies 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).
Data on subnational regions on how much is spent per student are adjusted using national purchasing power
parities (PPPs). Future work on the cost of living at subnational level is required to fully adjust expenditure per
student used in this section.
Expenditure per student on educational institutions relative to per capita GDP is calculated by dividing
expenditure per student on educational institutions by the 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 students’ intensity of participation by the credits that they obtain for the successful completion of
specific course units during a specified reference period. OECD countries that can accurately account for parttime enrolment have higher apparent expenditure per full-time equivalent student on educational institutions than
OECD countries that cannot differentiate between the different types of student attendance.
For more information please see the OECD Handbook for Internationally Comparative Education Statistics 2018
(OECD, 2018[3]) and Annex 3 for country-specific notes (https://doi.org/10.1787/f8d7880d-en).

Source
Data refer to the financial year 2016 (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 https://doi.org/10.1787/f8d7880d-en). Data from Argentina, the People’s Republic of China, India, Indonesia,
Saudi Arabia and South Africa are from the UNESCO Institute of Statistics (UIS).
The data on expenditure for 2005, 2011 to 2016 were updated based on a survey in 2018-19, and expenditure
figures for 2005 to 2015 were adjusted to the methods and definitions used in the current UOE data collection.
Data on subnational regions are currently available for three countries: Belgium, Canada and Germany.
Subnational estimates were provided by countries using national data sources. Subnational data are based on a
special survey administrated by the OECD in 2019.

EDUCATION AT A GLANCE 2019 © OECD 2019

C1. HOW MUCH IS SPENT PER STUDENT ON EDUCATIONAL INSTITUTIONS?  273
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 (2019), OECD Regional Statistics Database,
http://stats.oecd.org/Index.aspx?DataSetCode=REGION_DEMOGR.

[1]

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.

[3]

OECD (2017), Education at a Glance 2017: OECD Indicators, OECD Publishing, Paris,
http://dx.doi.org/10.1787/eag-2017-en.

[2]

Indicator C1 Tables
Table C1.1

Total expenditure on educational institutions per full-time equivalent student (2016)

Table C1.2

Total expenditure on educational institutions per full-time equivalent student for core
educational services, ancillary services and R&D (2016)

Table C1.3

Index of change in total expenditure on educational institutions per full-time equivalent student
(2005, 2011 and 2016)

WEB Table C1.4 Total expenditure on educational institutions per full-time equivalent student relative to GDP
per capita (2016)
WEB Table C1.5 Total expenditure on educational institutions per full-time equivalent student, by type of
institution (2016)
WEB Table C1.6 Cumulative expenditure on educational institutions per full-time equivalent student between
the age of 6 and 15 (2016)
Cut-off date for the data: 19 July 2019. Any updates on data can be found on line at
http://dx.doi.org/10.1787/eag-data-en. More breakdowns can be found at http://stats.oecd.org/, Education at
a Glance Database.
StatLink: https://doi.org/10.1787/888933981058

EDUCATION AT A GLANCE 2019 © OECD 2019

274  C1. HOW MUCH IS SPENT PER STUDENT ON EDUCATIONAL INSTITUTIONS?
Table C1.1. Total expenditure on educational institutions per full-time equivalent student (2016)
In equivalent USD converted using PPPs for GDP, direct expenditure within educational institutions, by level of education, based on fulltime equivalents

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 pre-primary programmes. Post-secondary non-tertiary figures are treated as negligible.
2. Year of reference 2017.
3. Data on expenditure on public vs. private educational institutions are displayed in Table C1.5 available on line.
Source: OECD/UIS/Eurostat (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888933978740

EDUCATION AT A GLANCE 2019 © OECD 2019

C1. HOW MUCH IS SPENT PER STUDENT ON EDUCATIONAL INSTITUTIONS?  275

Table C1.2. Total expenditure on educational institutions per full-time equivalent student for core educational services,
ancillary services and R&D (2016)
In equivalent USD converted using PPPs for GDP, direct expenditure within educational institutions, by level of education, based on fulltime equivalents

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 pre-primary programmes. Post-secondary non-tertiary figures are treated as negligible.
2. Year of reference 2017.
Source: OECD/UIS/Eurostat (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888933978759

EDUCATION AT A GLANCE 2019 © OECD 2019

276  C1. HOW MUCH IS SPENT PER STUDENT ON EDUCATIONAL INSTITUTIONS?
Table C1.3. Index of change in total expenditure on educational institutions per full-time equivalent student (2005, 2011 and
2016)
GDP deflator 2010 = 100, constant prices

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.
Source: OECD/UIS/Eurostat (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888933978778

EDUCATION AT A GLANCE 2019 © OECD 2019

278  C2. WHAT PROPORTION OF NATIONAL WEALTH IS SPENT ON EDUCATIONAL INSTITUTIONS?

Indicator C2. What proportion of national wealth
is spent on educational institutions?
Highlights


In 2016, OECD countries spent an average of 5% of their gross domestic product (GDP) on
educational institutions from primary to tertiary levels, with wide variations across OECD and
partner countries. On average, the share of national resources devoted to educational institutions in
non-tertiary education (primary, secondary and post-secondary non-tertiary levels) was 3.5% of GDP,
much larger than the share devoted to tertiary education (1.5% of GDP).



Private sources play a crucial role in financing tertiary education, accounting on average for around
one-third of expenditure on educational institutions or 0.5% of GDP. At non-tertiary levels, private
spending on education represents only one-tenth of the total expenditure on institutions, or 0.4% of
GDP.



Between 2010 and 2016, total expenditure on primary to tertiary educational institutions as a share of
GDP decreased in more than two-thirds of OECD and partner countries, mainly due to public
expenditure on educational institutions increasing more slowly than GDP.

Figure C2.1. Total expenditure on educational institutions as a percentage of GDP (2016)
From public, private and international sources, by level of education

1. Year of reference 2017.
2. Primary education includes pre-primary programmes.
Countries are ranked in descending order of total expenditure on educational institutions as a percentage of GDP.
Source: OECD/UIS/Eurostat (2019), Table C2.1. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880den
Statlink2 https://doi.org/10.1787/888933978930

EDUCATION AT A GLANCE 2019 © OECD 2019

C2. WHAT PROPORTION OF NATIONAL WEALTH IS SPENT ON EDUCATIONAL INSTITUTIONS?  279

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 school-age 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 aged 6 to 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 relevant population will have 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 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 heavily 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.

Other findings


The largest share of expenditure on educational institutions is devoted to primary and secondary levels
(69% of all OECD educational expenditure or 3.4% of GDP), and is a function of the total number of
students enrolled.



Spending by the private sector on primary to tertiary educational institutions, represented 0.9% of GDP
on average across OECD countries, after transfers between government and the private sector.



Between 2010 and 2016, public expenditure on educational institutions as a share of GDP decreased
slightly at tertiary levels (4% on average across OECD countries). However, for non-tertiary levels the
reduction has been more significant, at just over 8% on average across OECD countries.

EDUCATION AT A GLANCE 2019 © OECD 2019

280  C2. WHAT PROPORTION OF NATIONAL WEALTH IS SPENT ON EDUCATIONAL INSTITUTIONS?

Analysis
Overall investment relative to GDP
The share of national wealth devoted to educational institutions is substantial in all OECD and partner countries.
In 2016, 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% or more in Chile,
Israel, New Zealand, Norway, the United Kingdom and the United States, to 3%-4% in the Czech Republic,
Ireland, Italy, Japan, Lithuania, Luxembourg, the Russian Federation and the Slovak Republic (Figure C2.1 and
Table C2.1). Many factors influence the relative position of countries on this measure including the relative
number of students enrolled, the duration of studies and the effective allocation of funds. At the tertiary level,
spending may be influenced by the criteria for accessing 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, or 3.5% of GDP, is directed to non-tertiary levels, due to the high
enrolment rates at these levels. The share of resources devoted to educational institutions at non-tertiary levels
is around 4.5% of GDP in Israel, New Zealand and Norway while it accounts for 2% of GDP in
the Russian Federation.
On average across OECD countries, expenditure on educational institutions amounts to 1.5% of GDP at the
primary level and 1% at lower secondary level. However, the share of expenditure on educational institutions is
strongly influenced by the demographic composition of the country. Another factor that affects expenditure by level
of education is the duration of each level. Countries with relatively low fertility rates are more likely to spend a
lower share of their wealth on primary and lower secondary education. Indeed, the countries where investment in
primary education is below 1% of GDP also tend to be those with low birth rates (Austria, the Czech Republic,
Germany, Hungary, Lithuania and the Slovak Republic; Table C2.1). At upper secondary level, expenditure on
educational institutions accounts for 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. Less
than half of countries with available data spend more on vocational programmes than on general programmes,
with the largest differences found in the Czech Republic, Finland and the Netherlands (0.5-0.6 percentage points).
Tertiary education accounts for 1.5% of GDP on average. At this level, the various pathways and programmes
available to students, the duration of programmes, the organisation of teaching, and research and development
(R&D) activity all influence the level of expenditure at this level. In 2016, Canada, Chile and the United States were
the countries that spent the largest share of GDP on tertiary educational institutions (2%-3%). Unsurprisingly, these
countries also have some of the highest levels of expenditure from private sources of educational funding after
public-to-private transfers have been accounted for (1.1%-1.7% of GDP; 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 how the structure for publicly funded research is organises as well as the infrastructure and
facilities available. Australia, Norway, Sweden and other OECD countries in which most publicly funded R&D is
performed by tertiary educational institutions tend to report higher levels of expenditure on educational institutions
as a share of GDP than countries where R&D is mostly performed in other institutions. If R&D activities are
excluded, expenditure on tertiary educational institutions as a share of GDP decreases by 0.4 percentage points
on average across OECD countries, though the difference is at least 0.7 percentage points in Finland, Norway,
and Sweden (Table C2.1).
EDUCATION AT A GLANCE 2019 © OECD 2019

C2. WHAT PROPORTION OF NATIONAL WEALTH IS SPENT ON EDUCATIONAL INSTITUTIONS?  281

Expenditure on educational institutions by source of funds
Government spending remains the main source of educational funding in OECD countries. On average, public
expenditure on educational institutions from primary to tertiary educational levels (after transfers to the private
sector) accounts for 4% of GDP. However, large differences are observed across countries with available data.
In the Czech Republic, Italy, Japan, Lithuania, Luxembourg, the Slovak Republic and the Russian Federation,
public investment represents around 3% of GDP, while Belgium, Brazil, Finland, Iceland, Norway and Sweden
devote around 5%-7% of their GDP to direct public expenditure on educational institutions (Figure C2.2).

Figure C2.2. Total expenditure on educational institutions as a percentage of GDP, by source of funds
(2016)
After transfers; from public, private and international sources

Note: International expenditure is aggregated with public expenditure for display purposes.
1. Year of reference 2017.
2. The figures for the United States are for net student loans rather than gross, thereby underestimating public transfers.
3. Primary education includes pre-primary programmes.
Countries are ranked in descending order of total expenditure on educational institutions as a percentage of GDP.
Source: OECD/UIS/Eurostat (2019), Table C2.2. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933978949

EDUCATION AT A GLANCE 2019 © OECD 2019

282  C2. WHAT PROPORTION OF NATIONAL WEALTH IS SPENT ON EDUCATIONAL INSTITUTIONS?
With tightening public budgets, many educational systems are turning more towards the private sector for
additional investment, particularly at tertiary level. After transfers, private sector expenditure on primary to tertiary
educational institutions accounts for 0.9% of GDP on average. Countries nevertheless differ considerably in the
importance of private expenditure on educational institutions, ranging from 0.1% of GDP or less in Finland,
Luxembourg and Norway, to 1.9% or more in Australia, Chile, the United Kingdom and the United States
(Figure C2.2).
At non-tertiary levels of education, private investment is low and accounts for 0.4% of GDP on average across
OECD countries. However, it amounts to at least 0.7% of GDP in Australia, Colombia, Mexico, New Zealand,
Turkey and the United Kingdom, the countries with the largest relative shares of private funding of non-tertiary
education. At the tertiary level, private investment plays a more significant role, accounting on average for 0.5%
of GDP. In some countries, private sources contribute a larger share: private spending on tertiary institutions in
Chile and the United States accounts for more than 1.6% of GDP, the highest among OECD countries
(Table C2.2 and Figure C2.2).

Figure C2.3. Index of change in public expenditure on educational institutions as a percentage of GDP
(2010 and 2016)
Final sources of funds, by level of education, reference year 2010 = 100

1. Primary education includes pre-primary programmes.
Countries are ranked in descending order of the index of change in public expenditure on educational institutions as a percentage of GDP.
Source: OECD/UIS/Eurostat (2019), Table C2.4, available on line. See Source section for more information and Annex 3 for notes
(https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933978968

Changes in educational expenditure between 2010 and 2016
The effects of the global economic crisis that began in 2008 are still 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, and Figure C2.3). However, across

EDUCATION AT A GLANCE 2019 © OECD 2019

C2. WHAT PROPORTION OF NATIONAL WEALTH IS SPENT ON EDUCATIONAL INSTITUTIONS?  283

OECD countries, total average expenditure from all sources on primary to tertiary educational institutions as a
percentage of GDP fell by 7% between 2010 and 2016, mainly as a result of a lower increase in spending
compared to GDP (Table C2.3). Most countries with available data experienced a reduction in the total
expenditure on educational institutions as a share of GDP with Ireland and Lithuania among the countries with
the largest negative adjustments, all them with increases in GDP of over 20% over the same period. In contrast,
Chile and Israel were two of the major exceptions, with an increase of 7% or more in the total expenditure on
educational institutions despite also the significant increase of GDP.
Spending on the various levels of education evolved similarly between 2010 and 2016. Expenditure on
educational institutions at the non-tertiary and tertiary levels decreased by 8% relative to GDP. However, this
average masks significant changes in some countries. In Chile and Israel, for example, expenditure on
non-tertiary education as a share of GDP increased by at least 5% over the six-year period. The reduction
observed in Ireland (40%) can be mainly explained by a revision in its 2015 GDP data. Over the same period,
Estonia, Lithuania and Luxembourg experienced some of the highest decreases in the share of expenditure on
these educational levels (by over 20%).
At the tertiary level, about one-third of countries with available data increased their investments in tertiary
education between 2010 and 2016, although their spending at non-tertiary levels declined or remained almost
stable. Clear examples of this trend are Australia, Iceland, Israel, Norway and the Slovak Republic, which
increased the share of GDP invested tertiary educational institutions by over 10% but reduced the share invested
in non-tertiary educational institutions by at least 5% during this period. Israel’s increase in total tertiary spending
as a share of GDP, the largest across OECD and partner countries, was mainly driven by a substantial increase
in both public and private investment in education.

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).
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, after the flow of
transfers. Private spending also includes expenditure by private companies on the work-based element of schooland 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, after the flow of transfers.
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.

EDUCATION AT A GLANCE 2019 © OECD 2019

284  C2. WHAT PROPORTION OF NATIONAL WEALTH IS SPENT ON EDUCATIONAL INSTITUTIONS?

Methodology
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, are classified as either governmental (public) sources,
non-governmental (private) sources or international sources, such as international agencies and other foreign
sources. The 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.
For more information please see the OECD Handbook for Internationally Comparative Education Statistics 2018
(OECD, 2018[1]) and Annex 3 for country-specific notes (https://doi.org/10.1787/f8d7880d-en).

Source
Data refer to the financial year 2016 (unless otherwise specified) and are based on the UNESCO, the OECD and
Eurostat (UOE) data collection on education statistics administered by the OECD in 2018 (for details see Annex 3
at https://doi.org/10.1787/f8d7880d-en). Data from Argentina, the People’s Republic of China, India, Indonesia,
Saudi Arabia and South Africa are from the UNESCO Institute of Statistics (UIS).
The data on expenditure for 2005, 2011 to 2016 were updated based on a survey in 2018-19, and expenditure
for 2005 to 2015 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.

EDUCATION AT A GLANCE 2019 © OECD 2019

C2. WHAT PROPORTION OF NATIONAL WEALTH IS SPENT ON EDUCATIONAL INSTITUTIONS?  285

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.

[1]

Indicator C2 Tables
Table C2.1

Total expenditure on educational institutions as a percentage of GDP (2016)

Table C2.2

Total expenditure on educational institutions as a percentage of GDP, by final source of funds
(2016)

Table C2.3

Index of change in total expenditure on educational institutions as a percentage of GDP
(2005, 2011 and 2016)

WEB Table C2.4 Trends in public expenditure on educational institutions as a percentage of GDP (2005, 2011
and 2016)
Cut-off date for the data: 19 July 2019. 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.
StatLink https://doi.org/10.1787/888933981077

EDUCATION AT A GLANCE 2019 © OECD 2019

286  C2. WHAT PROPORTION OF NATIONAL WEALTH IS SPENT ON EDUCATIONAL INSTITUTIONS?
Table C2.1. Total expenditure on educational institutions as a percentage of GDP (2016)
Direct expenditure within educational institutions, by level of education

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 pre-primary programmes. Post-secondary non-tertiary figures are treated as negligible.
2. Year of reference 2017.
Source: OECD/UIS/Eurostat (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888933978873

EDUCATION AT A GLANCE 2019 © OECD 2019

C2. WHAT PROPORTION OF NATIONAL WEALTH IS SPENT ON EDUCATIONAL INSTITUTIONS?  287

Table C2.2. Total expenditure on educational institutions as a percentage of GDP, by final source of funds (2016)
Expenditure within educational institutions, by level of education

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 pre-primary programmes. Post-secondary non-tertiary figures are treated as negligible.
2. Year of reference 2017.
3. The figures for the United States are for net student loans rather than gross, thereby underestimating public transfers.
Source: OECD/UIS/Eurostat (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888933978892

EDUCATION AT A GLANCE 2019 © OECD 2019

288  C2. WHAT PROPORTION OF NATIONAL WEALTH IS SPENT ON EDUCATIONAL INSTITUTIONS?
Table C2.3. Index of change in total expenditure on educational institutions as a percentage of GDP (2005, 2011 and 2016)
GDP deflator 2010 = 100, constant prices, by level of education

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 pre-primary programmes. Post-secondary non-tertiary figures are treated as negligible.
Source: OECD/UIS/Eurostat (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888933978911

EDUCATION AT A GLANCE 2019 © OECD 2019

290  C3. HOW MUCH PUBLIC AND PRIVATE INVESTMENT IN EDUCATIONAL INSTITUTIONS IS THERE?

Indicator C3. How much public and private
investment in educational institutions is there?
Highlights


On average across OECD countries, public funds account for a larger share of total spending at
primary, secondary and post-secondary non-tertiary level (90%) than at the tertiary level of education
(66%).



The share of private investment on tertiary educational institutions depends mostly on the tuition fees
charged to students. More than 60% of total expenditure is privately sourced in Australia, Chile, Japan,
Korea, the United Kingdom and the United States.



Public-to-private transfers for tertiary education provide financial support to the private sector and
represents 9% of total spending on tertiary institutions on average across OECD countries. However,
they exceed 20% of spending in Australia and the United Kingdom.

Figure C3.1. Distribution of transfers and public and private expenditure on educational institutions
(2016)
Tertiary educational levels

Note: International expenditure is aggregated with public expenditure for display purposes.
1. Year of reference 2017.
Countries are ranked in descending order of the proportion of public-to-private transfers.
Source: OECD/UIS/Eurostat (2019), Tables C3.1 and C3.2. See Source section for more information and Annex 3 for notes
(https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933979044

EDUCATION AT A GLANCE 2019 © OECD 2019

C3. HOW MUCH PUBLIC AND PRIVATE INVESTMENT IN EDUCATIONAL INSTITUTIONS IS THERE?  291

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, there has been increasing focus on the balance between public
and private funding of 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, private sources of funding play an increasingly prominent role at
some educational levels.
Public sources dominate much of the funding of non-tertiary education, which is usually compulsory in most
countries. Across OECD countries, the balance between public and private financing varies mostly at
pre-primary (see Indicator C2) and tertiary levels of education, where full or nearly full public funding is less
common. At these levels, private funding comes mainly from households, raisin g 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 might discourage potential
students from entering tertiary education. Others believe that countries should significantly increase public
support to students such as student loans, while still others support efforts to increase the amount of funding
to tertiary education provided by private enterprises. Student loans can reduce the barriers to education
created by direct private spending and reduces the cost to taxpayers of direct government spending. In
particular, student loans transfer the cost of education in time from when students have little or no income
before graduation to when they generally have a larger income after graduation.
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 other private
entities. 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.

Other findings


Households account for the largest share of private expenditure devoted to tertiary educational
institutions (74% on average across OECD countries).



Between 2010 and 2016, the share of expenditure coming from private sources on educational
institutions from primary to tertiary level increased by 3 percentage points, while the share from public
sources decreased by the same amount on average across OECD countries.



The share of private expenditure on educational institutions varies across non-tertiary education levels.
At the primary and lower secondary levels, around 8% of expenditure on educational institutions
comes from private sources. This share reaches 14% at upper secondary education.

EDUCATION AT A GLANCE 2019 © OECD 2019

292  C3. HOW MUCH PUBLIC AND PRIVATE INVESTMENT IN EDUCATIONAL INSTITUTIONS IS THERE?

Analysis
Share of public and private expenditure on educational institutions
The largest share of funding on educational institutions in OECD countries comes from public sources, 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 the funds for primary to tertiary educational institutions come directly
from public sources and 17% from private sources (Table C3.1). However, there are many disparities across
countries. In Finland, Luxembourg, Norway and Sweden, private funds constitute 3% or less of expenditure on
educational institutions. In contrast, they make up around one-third of educational expenditure in Australia, Chile,
Colombia, Japan, Korea, the United Kingdom and the United States. International sources provide a very low
share of total expenditure on educational institutions. On average across OECD countries, they account for 1%
of total expenditure, reaching around 3% in Estonia, Luxembourg and Portugal.

Non-tertiary educational institutions
Public funding dominates non-tertiary education in all countries. Private funding accounts for 10% of expenditure
at these levels of education on average across OECD countries, although it exceeds 20% in Colombia and
Turkey (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. At the primary level, 8% of expenditure on educational institutions comes from private sources on
average across OECD countries. However in Norway and Sweden, all educational funding on primary institutions
is public, while in Chile, Colombia, Mexico, Spain and Turkey, more than 15% of funds come from private sources
(OECD, 2018[1]).
The share of private funding at the lower secondary level is similar to the share at primary level. Around 8% of
educational expenditure on lower secondary institutions is privately sourced on average across
OECD countries. In three-quarters of OECD countries for which data are available, private expenditure
accounts for less than 10% of total expenditure at this level compared to more than 20% in Australia, Colombia
and Turkey (OECD, 2018[1]).
Upper secondary education relies more on private funding than the primary and lower secondary levels, reaching
an average of 14% across OECD countries. Private sources contribute a similar share to the spending on
vocational and general programmes, at 13% of spending on upper secondary institutions on average across
OECD countries. However, in Germany, the Netherlands and New Zealand, the share of private funding in
vocational upper secondary education is at least 35 percentage points higher than in general education. On the
other hand, in Chile, Spain, Turkey and the United Kingdom the share of private funding of general programmes
exceeds that of vocational programmes by 10 percentage points or more (OECD, 2018[1]).
The level of public funding in post-secondary non-tertiary education stands at only 72% on average across OECD
countries. Unlike the three lower levels presented above, post-secondary non-tertiary education in Germany,
Israel, New Zealand, Poland and the United States relies more heavily on private than public sources of funding
(OECD, 2018[1]).

Tertiary educational institutions
The high private returns to tertiary education (see Indicator A5) have led a number of countries to expect a greater
financial contribution from the private sector at tertiary level. Some countries have implemented financial support
mechanisms to ease the burden on individuals when private contributions are expected, although this is not
always the case (see Indicator C5). In all OECD and partner countries, the proportion of private expenditure on
EDUCATION AT A GLANCE 2019 © OECD 2019

C3. HOW MUCH PUBLIC AND PRIVATE INVESTMENT IN EDUCATIONAL INSTITUTIONS IS THERE?  293

education after transfers is far higher at tertiary than it is at lower levels of education. On average across
OECD countries, nearly 32% of total expenditure on tertiary institutions is sourced from the private sector
(Table C3.1 and Figure C3.2).

Figure C3.2. Distribution of public and private expenditure on educational institutions (2016)
Final source of funds, by level of education

Note: International expenditure is aggregated with public expenditure for display purposes.
1. The figures for the United States are for net student loans rather than gross, thereby underestimating public transfers.
2. Primary education includes pre-primary programmes.
3. Year of reference 2017.
Countries are ranked in descending order of the proportion of public and international expenditure on educational institutions.
Source: OECD/UIS/Eurostat (2019), Table C3.1. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933979063

EDUCATION AT A GLANCE 2019 © OECD 2019

294  C3. HOW MUCH PUBLIC AND PRIVATE INVESTMENT IN EDUCATIONAL INSTITUTIONS IS THERE?
The share of private funding is strongly related to the level of tuition fees charged by tertiary institutions (see
Indicator C5). In countries where tuition fees tend to be low or negligible, such as Austria, Finland, Iceland,
Luxembourg and Norway, the share of expenditure on tertiary institutions sourced through the private sector
(including subsidised private payments such as tuition fee loans) is less than 10%. In contrast, more than 60% of
funding on tertiary institutions is privately sourced in Australia, Chile, Japan, Korea, the United Kingdom and
the United States, which also tend to charge students higher fees.
On average across OECD countries, households account for 74% of private expenditure on tertiary institutions.
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
(Figure C3.2).

Figure C3.3. Change in relative share of public, private and international expenditure on educational
institutions (2010 and 2016)
Final source of funds, primary to tertiary education

1. Year of reference 2017.
2. Primary education includes pre-primary programmes.
3. The figures for the United States are for net student loans rather than gross, thereby underestimating public transfers.
Countries are ranked in descending order of the percentage point change in the share of public expenditure on educational institutions.
Source: OECD/UIS/Eurostat (2019), Table C3.3. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933979082

Trends in the share of public and private expenditure on educational institutions
Although educational institutions from primary to tertiary level are still predominantly publicly funded, their reliance
on private funding is growing (Table C3.3). Between 2010 and 2016, the share of private spending after transfers
on primary to tertiary educational institutions increased by 3 percentage points on average across
OECD countries, while the share of public spending fell by about the same amount. Increases in the share of

EDUCATION AT A GLANCE 2019 © OECD 2019

C3. HOW MUCH PUBLIC AND PRIVATE INVESTMENT IN EDUCATIONAL INSTITUTIONS IS THERE?  295

private funding were observed in about half of OECD and partner countries, with Australia and Spain showing
the largest increase (7 percentage points). In contrast, Chile experienced the largest decrease in the share of
private spending, balanced by an equivalent increase from the public sector (Figure C3.3).
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 2016 was slightly stronger (3 percentage points) than for public
sources (of 2.6 percentage points). These figures, however, are strongly influenced by outliers like Estonia,
Portugal, Spain and the United Kingdom, where the share of private funding for non-tertiary education increased
by more than 5 percentage points between 2010 and 2016. In addition, large increases were observed during
the same period in the share of public funds, notably in Chile and the United Kingdom (around 5 percentage
points increase).
At tertiary level, although the share of public funding on institutions increased in some countries, they have fallen
below their 2010 levels in others. In many cases, these reductions have been reflected for by an equivalent
increase in private funding. This is the case for example for Australia, Belgium, Ireland, Spain and
the United States, where the share of public funds decreased by 5 percentage points in 2016 compared to 2010
but the share of private funds increased by the same amount (OECD, 2018[1]).

Public transfers to the private sector
A large share of government spending goes directly to educational institutions, but governments also transfer
funds to educational institutions through various other allocation mechanisms (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 to cover 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.
Public transfers to the private sector play an important role in the financing of tertiary education in some countries
(Figure C3.1). In countries where tertiary education is expanding, and particularly in those where students are
charged tuition fees, public-to-private transfers of funds are often seen as a means of expanding access for lowerincome 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 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, particularly in countries with high tuition fees and limited financial support mechanisms.
On average across OECD countries, 9% of the total funds devoted to tertiary institutions are transfers from the
public to the private sector. The countries with the highest transfers are also those that tend to have the highest
tuition fees. Transfers exceed 20% in Australia and the United Kingdom, all of which have high tuition fees. In
contrast, public transfers were below 1% in countries with no or lower tuition, such as the Czech Republic,
Estonia, Finland, Lithuania, Portugal, Slovenia, Sweden and Turkey. However, some countries have high levels
of private spending without high levels of support from the government, such as Chile and Korea (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 transfers
EDUCATION AT A GLANCE 2019 © OECD 2019

296  C3. HOW MUCH PUBLIC AND PRIVATE INVESTMENT IN EDUCATIONAL INSTITUTIONS IS THERE?
have been taken into account. 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, business and labour associations, and other non-profit organisations).
Public subsidies include public and international transfers such as scholarships and other financial aid to
students plus certain subsidies to other private entities.

Methodology
All entities that provide funds for education, either initially or as final payers, are classified as either government
(public) sources, non-government (private) sources or international sources such as international agencies and
other foreign sources. The figures presented here group together public and international expenditures for display
purposes. As the share of international expenditure is relatively small compared to other sources, its integration
into 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,
are 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.
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 public funding.
All government to private transfers are considered from the final source of funds in the analysis of this indicator.

EDUCATION AT A GLANCE 2019 © OECD 2019

C3. HOW MUCH PUBLIC AND PRIVATE INVESTMENT IN EDUCATIONAL INSTITUTIONS IS THERE?  297

For more information please see the OECD Handbook for Internationally Comparative Education Statistics 2018
(OECD, 2018[3]) and Annex 3 for country-specific notes (https://doi.org/10.1787/f8d7880d-en).

Source
Data refer to the financial year 2016 (unless otherwise specified) and are based on the UNESCO, OECD and
Eurostat (UOE) data collection on education statistics administered by the OECD in 2018 (for details see Annex 3
at https://doi.org/10.1787/f8d7880d-en). Data from Argentina, the People’s Republic of China, India, Indonesia,
Saudi Arabia and South Africa are from the UNESCO Institute of Statistics (UIS).
The data on expenditure for 2005, and 2010 to 2016 were updated based on a survey in 2018-19, and
expenditure for 2005 to 2015 was 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 6 July 2018).

[1]

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.

[3]

OECD (2017), “Who really bears the cost of education? : How the burden of education expenditure
shifts from the public to the private sector”, Education Indicators in Focus, No. 56, OECD
Publishing, Paris, http://dx.doi.org/10.1787/4c4f545b-en.

[2]

EDUCATION AT A GLANCE 2019 © OECD 2019

298  C3. HOW MUCH PUBLIC AND PRIVATE INVESTMENT IN EDUCATIONAL INSTITUTIONS IS THERE?

Indicator C3 Tables
Table C3.1

Relative share of public, private and international expenditure on educational institutions, final
source of funds (2016)

Table C3.2

Relative share of public, private and international expenditure on educational institutions, initial
source of funds (2016)

Table C3.3

Trends in the share of public, private and international expenditure on educational institutions
(2005, 2010 and 2016)

Cut-off date for the data: 19 July 2019. 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.
StatLink: https://doi.org/10.1787/888933981096

EDUCATION AT A GLANCE 2019 © OECD 2019

C3. HOW MUCH PUBLIC AND PRIVATE INVESTMENT IN EDUCATIONAL INSTITUTIONS IS THERE?  299

Table C3.1. Relative share of public, private and international expenditure on educational institutions, final source of funds (2016)
After transfers between public and private sectors, by level of education

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. Year of reference 2017.
3. The figures for the United States are for net student loans rather than gross, thereby underestimating public transfers.
Source: OECD/UIS/Eurostat (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888933978987
EDUCATION AT A GLANCE 2019 © OECD 2019

300  C3. HOW MUCH PUBLIC AND PRIVATE INVESTMENT IN EDUCATIONAL INSTITUTIONS IS THERE?
Table C3.2. Relative share of public, private and international expenditure on educational institutions, initial source of funds
(2016)
Before transfers between public and private sectors, by level of education

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 pre-primary programmes.
2. Year of reference 2017.
Source: OECD/UIS/Eurostat (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888933979006

EDUCATION AT A GLANCE 2019 © OECD 2019

C3. HOW MUCH PUBLIC AND PRIVATE INVESTMENT IN EDUCATIONAL INSTITUTIONS IS THERE?  301

Table C3.3. Trends in the share of public, private and international expenditure on educational institutions (2005, 2010 and 2016)
Final source of funds

Note: 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. The figures for the United States are for net student loans rather than gross, thereby underestimating public transfers.
Source: OECD/UIS/Eurostat (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888933979025
EDUCATION AT A GLANCE 2019 © OECD 2019

302  C4. WHAT IS THE TOTAL PUBLIC SPENDING ON EDUCATION?

Indicator C4. What is the total public spending
on education?
Highlights


Total public spending on primary to tertiary education as a percentage of total government expenditure
averages 11% across OECD countries, ranging from around 7% to around 17%.



In 2016, public transfers and payments to the non-educational private sector for primary to tertiary
education represented on average less than 1% of total government expenditure. This represents
8% of public expenditure on education, with the remaining 92% corresponding to direct public
expenditure on education.



Spending in non-tertiary education (primary, secondary and post-secondary non-tertiary levels) is
mostly decentralised, with 57% of final funds (after transfers between levels of government) managed
by regional and local governments. In contrast, spending at tertiary level is more centralised with only
17% of final public funds sourced from the regional and local level.

Figure C4.1. Composition of total public expenditure on education as a percentage of total
government expenditure (2016)
Primary to tertiary education

1. Year of reference 2017.
2. Primary education includes pre-primary programmes.
Countries are ranked in descending order of total public expenditure on education as a percentage of total government expenditure.
Source: OECD/UIS/Eurostat (2019), Table C4.1. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880den).
Statlink2 https://doi.org/10.1787/888933979158

EDUCATION AT A GLANCE 2019 © OECD 2019

C4. WHAT IS THE TOTAL PUBLIC SPENDING ON EDUCATION?  303

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 appropriate 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 in some countries. Budget cuts can represent improved 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.
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


Between 2010 and 2016, the average share of total government expenditure devoted to government
expenditure on primary to tertiary education remained relatively stable across OECD countries, at
around 11%. In half of OECD countries, the share decreased over the same period.



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 enrolment at lower levels.



The proportion of government expenditure devoted to primary to tertiary education fell between 2005
and 2016 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 and Israel, where
the increase was just over 2.7 percentage points.

EDUCATION AT A GLANCE 2019 © OECD 2019

304  C4. WHAT IS THE TOTAL PUBLIC SPENDING ON EDUCATION?

Analysis
Overall level of public resources invested in education
Countries differ in the share of total public expenditure they devote to education. In 2016, 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 7% in
Italy to around 17% in Chile (Table C4.1 and Figure C4.1).
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% of total government expenditure) was devoted to non-tertiary education (Table C4.1). 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, and the fact that in OECD countries, on average, the funding
structure for tertiary education is more private than non-tertiary levels.
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 Ireland, Israel, Japan, Latvia, Luxembourg
and Portugal to around 35% or more in Austria, Canada, Estonia, the Netherlands, Norway and Turkey
(Table C4.1).
Total public expenditure on education includes direct expenditure on institutions (such as the 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 C4.1). In 2016, this public expenditure represented less than 1% of total government expenditure and
accounted for 8% of public expenditure on education, with the remaining 92% corresponding to direct public
expenditure on education. However, the percentage varies by country: public transfers and payments to the noneducational private sector represent between 2% and 3% of total government expenditure in countries such as
Australia, the Netherlands, New Zealand and the United Kingdom, and less than 0.3% in the Czech Republic,
Luxembourg and the Russian Federation.
The relative size of public budgets must be taken into account when considering public spending on education
as a share of total government expenditure. The share of total government expenditure as a proportion of GDP
varies greatly among countries (Table C4.1 – web columns). In 2016, around 13% of countries with available
data reported that total government expenditure on all services was more than 50% of GDP. 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 (3.6% compared to the OECD average of 4.4%). This can be explained by Ireland’s
relatively low total government expenditure as a share of GDP (28%).

Trends in public expenditure on education as a percentage of total government expenditure,
2005-16
Total public spending on primary to tertiary education decreased slightly across OECD countries between 2005
and 2016 (Table C4.3), falling below 11% of total government expenditure. Over this period, the share of total
government expenditure on primary to tertiary education within total government expenditure decreased by
0.7 percentage points on average across OECD countries, and in more than 70% of countries with available data
for both 2005 and 2016. The fall was especially substantial (around 3 percentage points) in Estonia, Iceland,
EDUCATION AT A GLANCE 2019 © OECD 2019

C4. WHAT IS THE TOTAL PUBLIC SPENDING ON EDUCATION?  305

Lithuania, Mexico, Norway and Slovenia, while Chile experienced the largest increase (almost 3 percentage
points).
Total expenditure dropped slightly between 2005 and 2010, mainly due to the 2008 financial crisis. During this
period, total public expenditure on primary to tertiary education as a percentage of total government expenditure
decreased in two-thirds of OECD countries, and by 0.6 percentage points on average. Countries such as Iceland,
Ireland, Latvia and Mexico were severely hit during this period and total public expenditure on primary to tertiary
education as a percentage of total public expenditure fell by just over 2 percentage points.(Table C4.3).
A different tendency has been observed in the years following the crisis, between 2010 and 2016, probably due
in part to countries facing less pressure to pursue fiscal consolidation (Table C4.3 and Figure C4.2). Despite the
fact that public expenditure on primary to tertiary education increased over that period in a large number of
countries, large increases were also observed in total government expenditure. Over this six-year period, about
30% of countries with available data increased the public expenditure on education as a share of total government
expenditure, with Ireland showing the greatest increase (around 4 percentage points) while 75% of countries with
available data increased total government expenditure for all goods and services. However, in about half of OECD
and partner countries, the increase in public expenditure on education was lower than the increase in government
spending overall. Notable examples are Estonia and Norway, where the relative increase in total government
expenditure was between 10 and 20 percentage points higher than the increase in public expenditure on
education (Table C4.3 and Figure C4.2).

Figure C4.2. Index of change in total public expenditure on education as a share of total government
expenditure (2010 and 2016)
Primary to tertiary education (2010 = 100, constant prices)

1. Year of reference 2017
2. Primary education includes pre-primary programmes.
Countries are ranked in descending order of the change in total public expenditure on education as a percentage of total government expenditure.
Source: OECD/UIS/Eurostat (2019), Table C4.3. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933979177

EDUCATION AT A GLANCE 2019 © OECD 2019

306  C4. WHAT IS THE TOTAL PUBLIC SPENDING ON EDUCATION?
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 at
both the level of government where the funds originate and the level of government at which they are ultimately
spent. At the initial level, decisions are made about the volume of resources allocated and any restrictions on
how that money can be spent (see Box C4.1). 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).

Box C4.1. How is funding allocated to schools?
There are generally four main approaches to the allocation of funds to schools:
1. Administrative discretion is based on an individual assessment of the amount of resources that
each school needs.
2. Incremental costs takes into consideration historical expenditure to calculate the allocation for the
following year. This can incorporate minor modifications to take into account specific changes (e.g.
numbers, school facilities or input prices).
3. Bidding and bargaining involves schools responding to open competitions for additional funding
offered via participation in a particular programme or making a case for additional resources.
4. Formula funding involves the use of objective criteria with universally applied rules to establish the
amount of resources that each school is entitled to.
The distribution of funding on a discretional or incremental basis is rarely efficient or equitable and tends to
be associated with low levels of budget transparency. Schools do not have any incentive to increase their
efficiency nor reduce their expenditure. Both approaches are often combined, and mainly used in centralised
systems. In contrast, the use of formula funding provides a high degree of transparency to the allocation
system. Traditionally, formula funding relies on a mathematical formula taking into account four main groups
of variables: 1) student numbers and grade levels; 2) needs; 3) curriculum or educational programmes; and
4) school characteristics (OECD, 2017[1]).
In some countries, education funding is centralised, while in others it is decentralised with funds transferred
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 their ability to raise
education funds. Wide variations in education standards and resources can also lead to inequality of educational
opportunities and insufficient attention being paid 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 wider public 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[2]).
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 2016, on average across
OECD countries, 58% of the public funds for non-tertiary education came from the central government before
transfers to the various levels of government, compared to 87% of the funds for tertiary education (Table C4.2).

EDUCATION AT A GLANCE 2019 © OECD 2019

C4. WHAT IS THE TOTAL PUBLIC SPENDING ON EDUCATION?  307

Figure C4.3. Distribution of initial sources of public funds for education and change in government
levels’ share of funds after intergovernmental transfers (2016)
Primary, secondary and post-secondary non-tertiary education

1. Year of reference 2017
2. 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 (2019), Table C4.2. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933979196

EDUCATION AT A GLANCE 2019 © OECD 2019

308  C4. WHAT IS THE TOTAL PUBLIC SPENDING ON EDUCATION?
The division of responsibility for public 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 New Zealand. In countries such as Chile, Colombia,
France, Greece, Hungary, Ireland, Israel, Italy, Luxembourg, the Netherlands, Portugal, Slovenia, Turkey
and the United Kingdom, central government is the source of the majority of initial funds and the main
final purchaser of educational goods and services.



In Austria, Estonia, Korea, Latvia, Lithuania, Mexico, Poland and the Slovak Republic, central
government is the main initial source of funds, but regional and local authorities are the main final
purchasers of educational services in non-tertiary education.



Regional governments are both the main initial source and the main final spender of education funds in
Australia, Belgium, Germany, Spain and Switzerland. In Canada and Japan, regional governments are
the predominant source of initial funds, but local authorities are the main final purchasers of educational
services.



In Finland and Norway, local authorities are both the main initial source of funds and the main final
purchasers of educational services. In the United States, both regional and local governments are the
main initial sources of funds, but the local governments are the main final purchasers.

On average across OECD countries, more funds are transferred from central to regional and local levels of
government for non-tertiary education than for tertiary education. This extends the scope for decentralisation at
non-tertiary levels of education. On average across OECD countries, the share of public funds for non-tertiary
education provided by the central government falls from 58% to 43% after transfers to other levels of government
have been accounted for, while the share of local funds rises as a result from 25% to 42%. There is a great deal
of variation in the sources of funds before and after transfers from central to lower levels of government. In Korea,
Mexico, Poland 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 and Finland, the difference is between
25 and 40 percentage points. In Canada and the United States, where the regional level is mostly responsible
for transferring funds to schools, the share of regional funding falls 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 to lower levels of
government (Table C4.2). On average across the OECD, the central government manages 87% of funds before
transfers and this barely changes when intergovernmental transfers are taken into account. In most OECD and
partner countries with data available, central government directly provides more than 60% of public funds in
tertiary education; in 15 countries, 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 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 the United States, where it generates and spend more than 10% of the funds.

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

EDUCATION AT A GLANCE 2019 © OECD 2019

C4. WHAT IS THE TOTAL PUBLIC SPENDING ON EDUCATION?  309

institutions, in contrast to Indicators C1, C2 and C3, which focus only on spending on educational institutions.
Public expenditure on education includes expenditure by all public entities, including the education ministry 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.
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 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), including non-market producers
(e.g. providing services and goods free of charge, or at prices that are not economically significant) 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[3]).
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[4]) and Annex 3 for country-specific notes (https://doi.org/10.1787/f8d7880d-en).

Source
Data refer to the financial year 2016 (unless otherwise specified) and are based on the UOE data collection on
education statistics administered by the OECD in 2018 (for details see Annex 3 at
https://doi.org/10.1787/f8d7880d-en). Data from Argentina, the People’s Republic of China, India, Indonesia,
Saudi Arabia and South Africa are from the UNESCO Institute of Statistics (UIS).

EDUCATION AT A GLANCE 2019 © OECD 2019

310  C4. WHAT IS THE TOTAL PUBLIC SPENDING ON EDUCATION?
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 - EU Law and Publications”, Methodologies and Working papers, Eurostat,
Luxembourg, http://dx.doi.org/10.2785/16355.

[3]

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.

[4]

OECD (2017), The Funding of School Education: Connecting Resources and Learning, OECD Reviews
of School Resources, OECD Publishing, Paris, https://dx.doi.org/10.1787/9789264276147-en.

[1]

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.

[2]

Indicator C4 Tables
Table C4.1

Total public expenditure on education as a percentage of total government expenditure (2016)

Table C4.2

Share of sources of total public funds devoted to education (2016)

Table C4.3

Trends in total public expenditure on education as a percentage of total government
expenditure (2005, 2010 and 2016)

Cut-off date for the data: 19 July 2019. 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.
Statlink: https://doi.org/10.1787/888933981115

EDUCATION AT A GLANCE 2019 © OECD 2019

C4. WHAT IS THE TOTAL PUBLIC SPENDING ON EDUCATION?  311

Table C4.1. Total public expenditure on education as a percentage of total government expenditure (2016)
By level of education

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 Indicators C1, C2 and C3. Data on public expenditure as a share of GDP (i.e. Columns 16 to 19) are available for consultation on line (see StatLink below).
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. Year of reference 2017.
Source: OECD/UIS/Eurostat (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888933979101
EDUCATION AT A GLANCE 2019 © OECD 2019

312  C4. WHAT IS THE TOTAL PUBLIC SPENDING ON EDUCATION?
Table C4.2. Share of sources of total public funds devoted to education (2016)
Before and after transfers, by level of education

Note: Some levels of education are included with others. Refer to "x" code in Table C4.1 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 pre-primary programmes.
2. Year of reference 2017.
Source: OECD/UIS/Eurostat (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888933979120

EDUCATION AT A GLANCE 2019 © OECD 2019

C4. WHAT IS THE TOTAL PUBLIC SPENDING ON EDUCATION?  313

Table C4.3. Trends in total public expenditure on education as a percentage of total government expenditure (2005, 2010 and 2016)
Initial sources of funds, by level of education and by year

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 Indicators C1, C2 and C3. 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.
Source: OECD/UIS/Eurostat (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888933979139

EDUCATION AT A GLANCE 2019 © OECD 2019

314  C5. HOW MUCH DO TERTIARY STUDENTS PAY AND WHAT PUBLIC SUPPORT DO THEY RECEIVE?

Indicator C5. How much do tertiary students pay
and what public support do they receive?
Highlights


Tuition fees charged by institutions vary significantly across countries. In about one-third of countries,
public institutions do not charge any tuition fees for national students enrolled in bachelor’s or
equivalent programmes. In another third of countries, tuition fees are low or moderate (below
USD 2 600 per year). In the remaining countries, they are high and range from USD 3 000 to over
USD 9 000 per year.



Annual tuition fees vary not only across countries, but also within countries for a given level of
education. At bachelor’s or equivalent level, the countries with the highest average tuition fees also
tend to have wide ranges of tuition fees. In contrast, in countries with the lowest average tuition fees,
the range of tuition fees tends be very narrow – with the difference between the minimum and
maximum annual fees not exceeding USD 200.



Financial mechanisms to support students enrolled in tertiary education such as grants, scholarships
and loans tend to be more developed in countries that charge either relatively high tuition fees or no
tuition fees at all.

Context
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.
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: salaries of teachers and researchers; development of digital learning and non-teaching services;
changes in demand for tertiary education; investments to support internationalisation; and amount and type
of research activities undertaken by faculty and staff. Tertiary 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 is covered by student tuition fees and public sources.
Public support to students and their families can be a way 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 encourage them to 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. 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 may provide less support for low-income students than means-tested subsidies,
as tax reductions are not targeted specifically at low-income students. However, such measures may still help
to reduce the financial disparities between households with and without children in education.

Other findings


The level of tuition fees charged by institutions rarely reflects labour-market opportunities. In most
countries, the earnings advantage for completing a master’s programme or a doctorate is greater than

EDUCATION AT A GLANCE 2019 © OECD 2019

C5. HOW MUCH DO TERTIARY STUDENTS PAY AND WHAT PUBLIC SUPPORT DO THEY RECEIVE?  315

for attaining tertiary education at bachelor’s level. Nonetheless, in more than half of OECD countries,
public institutions charge similar tuition fees regardless of the level of education.


At the bachelors’ level, public institutions charge higher tuition fees for foreign students than for
national students in around one-third of countries with available data. Australia, Canada and Sweden
show the largest differences. In these three countries, public institutions charge foreign students on
average over USD 13 900 more per year than national students.



OECD governments support students’ living or educational costs through various combinations of
loans, grants or scholarships. In most countries with no tuition fees at the bachelor’s level, students
tend to receive financial support in the form of both loans and scholarships or grants. In countries with
low or moderate tuition fees (below USD 2 600 per year), less than half of students receive financial
support, and those who do mainly receive it in the form of grants or scholarships only. There is more
variation among countries with high tuition fees, but one common pattern is that students tend to rely
to some extent on income-contingent loans.

Figure C5.1. Tuition fees charged by public tertiary educational institutions to national students, by
level of education (2017/18)
Annual average (or most common) tuition fees charged to full-time national students, in equivalent USD converted using
PPPs for GDP

1. Data is presented for government-dependent institutions instead of public institutions.
2. Short-cycle tertiary programmes are included in bachelor's or equivalent programmes.
3. Estimates include universities only and exclude ISCED 6, such as postgraduate certificates and diplomas.
4. Government-dependent private institutions are included in public institutions.
5. Tuition fees are presented for total tertiary education instead of bachelor's or equivalent level. Tuition fees correspond to national and foreign
students. Only academic programmes are included.
Countries and economies are ranked in descending order of annual average (or most common) tuition fees at the bachelor's or equivalent level.
Source: OECD (2019), Table C5.1. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933979291

EDUCATION AT A GLANCE 2019 © OECD 2019

316  C5. HOW MUCH DO TERTIARY STUDENTS PAY AND WHAT PUBLIC SUPPORT DO THEY RECEIVE?

Analysis
Differentiation of tuition fees between tertiary degrees
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. Tuition
fees vary significantly across countries. This is true for instance at the bachelor’s level, which accounts for most
national entrants into tertiary programmes in OECD countries (see Indicator B4). Students in public institutions
paid no tuition fees in about one-third of the countries – including the Nordic countries (Denmark, Finland, Norway
and Sweden), and other countries such as Greece, the Slovak Republic and Slovenia. In another third of countries
(mostly European countries), tuition fees are low or moderate, with an average cost for students of below
USD 2 600 per year. In the remaining countries with available data (Australia, Canada, Chile, England (United
Kingdom), Israel, Japan, Latvia, Korea, New Zealand and the United States), tuition fees range from USD 3 000
to over USD 9 000 per year. For instance, tuition fees exceed USD 10 000 in England (United Kingdom), where
the majority of students enrol in government-dependent private institutions. Finally, a particular case is found in
Estonia, where public institutions charge no tuition fees for bachelor’s degrees, but government-dependent
private institutions (which account for 65% of students enrolled at that level) charge fees of USD 6 700
(Figure C5.1).
Attaining a higher tertiary qualification than a bachelor’s degree leads to better employment opportunities and
earnings prospects (see Indicator A4). If tuition fees reflected labour-market opportunities, they would therefore
tend to increase with the level of education. However, in the majority of OECD countries, public institutions charge
similar tuition fees for full-time national students in master’s and doctoral programmes than for students in
bachelor’s programmes (Figure C5.1). The additional costs that master’s and doctoral students face are thus
limited to the forgone earnings from the additional years of education and their delayed entry into the labour
market. For instance, in all countries with no tuition fees at bachelor’s level (except Greece for a number of
master’s programmes), tuition is also free of charge at master’s and doctoral levels. Similarly, several countries
with low, moderate or high tuition fees (such as Austria, Canada, France, Japan, the Netherlands and
New Zealand) also charge similar fees across all tertiary educational levels.
In contrast, in some countries, average tuition fees reflect labour-market opportunities more closely, as they
increase between the bachelor’s and master’s level. This is the case for instance in Chile, Korea and
the United States, where average tuition fees for master’s programmes in public institutions are about 30% higher
than for bachelor’s programmes. In Australia, the French Community of Belgium and Spain, they are over 50%
higher (Figure C5.1).
In a few countries, tuition fees are lower for doctoral programmes than for bachelor’s and master’s programmes.
This is the case in Australia, Italy and Switzerland (public institutions) and in Estonia (government-dependent
private institutions). In Australia, for example, the annual average tuition fees in public institutions for doctoral
programmes are about 20 times lower than for bachelor’s programmes (about USD 260 compared to
USD 5 000). In contrast, public institutions in Chile and Korea charge higher tuition fees for doctoral programmes
than for bachelor’s and master’s programmes. This is also true in Latvia for government-dependent private
institutions (Figure C5.1).

Variations within countries in tuition fees for bachelor’s programmes
Tuition fees vary not only across countries and educational levels, but also within countries for a given level of
education. At bachelor’s or equivalent level, the countries with the highest average tuition fees tend to have wider
ranges of tuition fees. For instance, in Canada, where annual average tuition fees in public institutions are around
USD 5 300, tuition fees range from USD 2 250 to USD 7 000. Similarly, in Chile, where average tuition fees are
around USD 7 500, they range from USD 5 450 to USD 10 400. In the United States (average fees of
USD 8 800), tuition fees range from USD 6 700 to USD 10 750 (Figure C5.2).

EDUCATION AT A GLANCE 2019 © OECD 2019

C5. HOW MUCH DO TERTIARY STUDENTS PAY AND WHAT PUBLIC SUPPORT DO THEY RECEIVE?  317

The range of tuition fees is also wide in a few countries with more moderate fees, such as the Netherlands (annual
average fees of USD 2 500) and Spain (annual average fees of USD 1 750). In the Netherlands, tuition fees
range from USD 1 500 to USD 12 700, and in Spain they range from USD 900 to USD 12 100. In these two
countries, the high tuition fees only apply for a small number of students.
In contrast, in the countries with the lowest average tuition fees (such as Denmark, Finland, France, Greece,
Norway, the Slovak Republic, Slovenia and Sweden), the range of tuition fees tends be very narrow – with the
difference between the minimum and maximum annual fees not exceeding USD 200.

Figure C5.2. Minimum, maximum and average (or most common) annual tuition fees charged by public
institutions for national students at bachelor's or equivalent level (2017/18)
Annual tuition fees charged to full-time national students, in equivalent USD converted using PPPs for GDP

Note: The year of reference may differ across countries and economies. Please see Annex 3 for details.
1. Data are presented for government-dependent institutions instead of public institutions.
2. Short-cycle tertiary programmes are included in bachelor's or equivalent programmes.
3. Estimates include universities only and exclude ISCED 6, such as postgraduate certificates and diplomas.
4. Government-dependent private institutions are included in public institutions.
5. Tuition fees are presented for total tertiary education instead of bachelor's or equivalent level. Tuition fees correspond to national and foreign students.
Only academic programmes are included.
Countries and economies are ranked in descending order of annual average (or most common) tuition fees.
Source: OECD (2019), Table C5.2. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933979310

EDUCATION AT A GLANCE 2019 © OECD 2019

318  C5. HOW MUCH DO TERTIARY STUDENTS PAY AND WHAT PUBLIC SUPPORT DO THEY RECEIVE?
Differentiation of tuition fees by type of institution for bachelor’s programmes
The need for financial resources and the goal of guaranteeing an affordable education for all lead to different
levels of tuition fees for different types institutions. Independent private institutions are often less affected by
government regulation and less reliant on public funds than public institutions. In some cases, they are also more
pressed by competition to provide the best possible services 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.
In over one-third of countries with available data, tuition fees are at least twice as high in independent private
institutions as in public institutions (Table C5.1). In the United States, the average annual tuition fee charged by
independent private institutions for national students at the bachelor’s or equivalent level is USD 29 500, more
than three times the average annual tuition fee in public institutions (USD 8 800). In Japan and Korea, the
average annual tuition fee at this level is between USD 8 700 and USD 8 800 in independent private institutions,
while it is closer to USD 5 000 in public institutions. Tuition fees are about four times higher in independent private
institutions than in public institutions in Spain, about three times higher in Italy, and about twice as high in Israel.
In the Slovak Republic, tuition fees for bachelor’s or equivalent programmes are around USD 2 150, while public
institutions do not charge tuition fees. Similarly, in Norway, tuition fees for bachelor’s and master’s degrees
(combined) are around USD 5 700 in independent private institutions, while there are no tuition fees in public
institutions.
In contrast, the difference between public institutions and government-dependent private institutions in average
annual tuition fees at the bachelor’s or equivalent level is minimal in most countries with available data. Neither
type of institution charges fees in Finland, Slovenia and Sweden, and private and public institutions charge very
similar average tuition fees in Austria and Israel (Table C5.1).

Differentiation of tuition fees between national and foreign students
National policies on tuition fees generally cover all students studying in the country’s educational institutions,
including foreign students (see Definitions section). However, tuition fees may be higher for foreign students, and
differences between national and foreign students in fees can have an impact on the international flows of
students, as can other factors, such as public support from their home countries (OECD, 2017[1]). 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 foreign 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, France, Greece, Israel, Italy, Japan,
Korea, Norway, the Slovak Republic and Spain (Table C5.1). In European Union (EU) and European Economic
Area (EEA), countries charge the same tuition fees to nationals and students from other EU and EEA countries.
In some countries, however, the difference in tuition fees for national and foreign students can be significant. For
instance, at the bachelor’s level, in Australia, Canada and the United States, public institutions charge on average
over USD 13 900 more per year for foreign students than for national students (Table C5.1). In the United States,
international students and national students who study outside their state 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 doctoral or
equivalent programmes). These fees, however, remain moderate (around USD 1 850 per year for foreign
students). In Sweden, tuition is free for national students and those from the European Union, while non-EU
students pay over USD 14 500 per year at the bachelor’s level. In Finland, as of academic year 2017/18, tuition
fees were introduced for students who are not citizens of EU or EEA countries and who are enrolled in bachelor's
or master's programmes taught in English.

EDUCATION AT A GLANCE 2019 © OECD 2019

C5. HOW MUCH DO TERTIARY STUDENTS PAY AND WHAT PUBLIC SUPPORT DO THEY RECEIVE?  319

Higher tuition fees do not necessarily discourage foreign students, however. For instance, in Australia, Austria
and Canada, international or foreign students make up over 11% of students enrolled at the bachelor’s level,
compared to only 4% on average across OECD countries (see Indicator B6).

Country approaches to funding tertiary education
OECD countries have different approaches to providing financial support to students enrolled in tertiary
education. Despite policy changes over time within individual countries (Box C5.1), and differences across
countries, national financing systems for higher education can be grouped together according to a number of
common characteristics. Countries and economies 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 support system for
tertiary education (OECD, 2015[2]):


Group 1: No tuition fees and generous student-support systems

This group includes all Nordic countries with available data: Denmark, Finland, Norway and Sweden.
Students do not pay tuition fees for bachelor’s degrees in public institutions, and they have access to
generous public subsidies for tertiary education, which help them cover their living costs. In these countries,
more than 55% of students benefit from public/government-guaranteed loans, scholarships/grants or a
combination of the two (Figure C5.3). These countries have more progressive tax structures and individuals
face high income tax rates (Indicator A5 and (OECD, 2015[2])).


Group 2: High tuition fees and well-developed student-support systems

This group is composed of Australia, Canada, England (United Kingdom), New Zealand and
the United States. In these countries and economies, the financial cost of entering tertiary education is
relatively high (with annual tuition fees over USD 4 400 for bachelor’s degrees in public institutions), but
students benefit from extensive financial support. In Canada, over 70% of students receive financial support
for bachelor’s and master’s long first degrees, and this proportion exceeds 85% in Australia, England
(United Kingdom), New Zealand and the United States (Figure C5.3).
England (United Kingdom) has moved into this group of countries since 1995, as both tuition fees and
financial support to students increased significantly. The Netherlands is gradually moving towards this group
from Group 1, as tuition fees have increased while its student-support system has developed (see
Figure B5.1 in (OECD, 2014[3])). Israel lies between Group 1 and Group 2, as participation in tertiary
education is based on relatively high levels of student support (two-thirds of students benefit from grants,
scholarships or loans), with annual tuition fees reaching around USD 3 000 in public institutions at bachelor’s
level (Table C5.1). In 2018, New Zealand began to move towards Group 1 by eliminating first-year fees for
national students entering tertiary education for the first time. By 2024, three years of tertiary education will
be free to all national first-time students.


Group 3: High tuition fees and less-developed student-support systems

In Chile (Figure C5.3), Japan and Korea (OECD, 2015[2]), students pay high tuition fees (over USD 4 800 per
year) for bachelor’s programmes in public institutions, but student-support systems are somewhat less
developed than in countries from Groups 1 and 2. However, Chile recently implemented important reforms
to its tertiary education system. Access to tertiary education has become completely free of charge for lowincome students. In addition, the maximum amount charged to students who do not benefit from free tuition
fees is now regulated and the amount of resources allocated to tertiary education scholarships has increased.
As for Japan, it recently adopted 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). Similarly, financial support has been
expanding in Korea, notably with the creation of income-contingent loans in 2010, and of a national
grants/scholarships programme in 2012.

EDUCATION AT A GLANCE 2019 © OECD 2019

320  C5. HOW MUCH DO TERTIARY STUDENTS PAY AND WHAT PUBLIC SUPPORT DO THEY RECEIVE?


Group 4: Low or moderate tuition fees and less-developed student-support systems

This group includes most other European countries and economies for which data are available: Austria, the
French Community of Belgium, France, Italy, Spain and Switzerland (Figure C5.3 and (OECD, 2015[2]). In
these countries, average annual tuition fees for bachelor’s degrees in public institutions are low or moderate
(below USD 2 600), and financial support is somewhat limited (targeting less than 45% of students).

Box C5.1. Changes in tuition fees and financial support to students (2007/08 to 2017/18)
Reforms related to the level of tuition fees and the availability of scholarships, grants and loans are highly
debated in national education policy. They are often discussed 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. Between the years 2007/08 and 2017/18, 15 out of 28 countries and economies with available
information have undertaken tuition fee reforms. In 12 of them, these reforms in tuition fees were accompanied
by changes in the level of public subsidies available to students (Table C5.4).
In about half of the countries with available data, tuition fees for bachelor’s degrees in public institutions
increased by over 20% over the past decade. This is the case in some countries with high average annual
tuition fees (fees over USD 4 400 in 2017/18) such as in Canada, England (United Kingdom), New Zealand
and the United States, but also in countries with more moderate fees (fees below USD 2 600 in 2017/18) such
as in the Netherlands, Spain and Switzerland.
In contrast, in countries that charged no tuition fees in 2007/08 (Denmark, Finland, Greece, Norway,
the Slovak Republic and Slovenia), there was no change in tuition fees over the past decade. Similarly, in
Austria and France, annual average tuition fees have remained fairly constant (at around USD 950 and
USD 200 respectively). Finally, Chile is the only country with available data where there was a sharp reduction
in tuition fees (from USD 8 050 to USD 7 500 per year).
Although there is little trend data available, it is also interesting to look at the change in the proportion of
students benefiting from loans, scholarships/grants, or a combination of both. Among the countries that
experienced a significant increase in tuition fees, in New Zealand, the share of students receiving financial
support remained rather constant (at around 85%) over the past decade (Table C5.4). At the same time, the
average annual amount of loans borrowed increased (from USD 6 400 to USD 7 600) while the average
amount of grants/scholarships slightly decreased (from USD 5 700 to USD 5 100) (see Annex 3 for details).
In the two countries with data available that did not charge tuition fees in either 2007/08 or 2017/18, there was
an increase in the share of students receiving financial support: from 69% to 83% in Denmark and from 55%
to 58% in Finland (Table C5.4). In Denmark, both the average annual amount of loans borrowed and the
amount of grants/scholarships increased, while in Finland there was an increase in the average annual
amount of loans and a decrease in the amount of grants/scholarships (see Annex 3 for details).
Finally, in Chile, where tuition fees decreased significantly over the past decade, there was also a sharp
increase in the percentage of students receiving public/government-guaranteed loans and/or
grants/scholarships. This share went from 17% in 2007/08 to 58% in 2017/18, which is the biggest increase
among countries with available data.
The level of tuition fees and financial support to students can have a significant impact on equity and access to
tertiary education. Evidence suggests that charging high tuition fees while simultaneously giving students
opportunities to benefit from comprehensive financial support systems can be a way for countries to increase
access to tertiary education, make efficient use of limited public funds, and acknowledge the significant private
returns that students receive from tertiary education (OECD, 2018[4]). For instance, Australia and New Zealand,

EDUCATION AT A GLANCE 2019 © OECD 2019

C5. HOW MUCH DO TERTIARY STUDENTS PAY AND WHAT PUBLIC SUPPORT DO THEY RECEIVE?  321

which have particularly well-developed financial support systems (including income-contingent loans), also have
above-average tertiary entry rates in spite of high tuition fees (see Indicator B4).
As for the high entry rates among some countries that charge no tuition fees, they may be due as much to their
highly developed student financial support systems to cover living expenses, as to the absence of tuition fees
(see Indicator B4). For instance, in Denmark and Norway – two countries with above-average tertiary entry rates
– there are no tuition fees and more than 80% of students benefit from loans, scholarships/grants or a
combination of both.

Figure C5.3. Distribution of students benefiting from public/government-guaranteed loans and
scholarships/grants in bachelor's and master's long first degrees or equivalent (2017/18)

Note: Annual average (or most common) tuition fees charged by public institutions for national students at the bachelor's level are indicated in parenthesis
(USD converted using PPPs). The year of reference may differ across countries and economies. Please see Annex 3 for details.
1. Tuition fees correspond to public institutions and government-dependent institutions combined.
2. Data on financial support corresponds to total tertiary instead of bachelor's and master's long first degree or equivalent.
3. The data on "public or government-guaranteed loans only" and "public scholarships/grants only" include anyone who received a loan or
scholarship/grant in the reference year (although they may have received other forms of financial support as well).
4. Tuition fees include short-cycle tertiary programmes and bachelor's or equivalent programmes.
5. Estimates include universities only and exclude ISCED 6, such as postgraduate certificates and diplomas.
6. Tuition fees are presented for government-dependent institutions instead of public institutions.
Countries and economies are ranked in descending order of the share of students who do not benefit from public/government-guaranteed loans or
scholarships/grants.
Source: OECD (2019), Table C5.2. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933979329

Financial support to students, in the form of loans, grants and scholarships
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 or scholarships. On the one hand,
advocates of student loans argue that they allow the number of students who can benefit from the available
EDUCATION AT A GLANCE 2019 © OECD 2019

322  C5. HOW MUCH DO TERTIARY STUDENTS PAY AND WHAT PUBLIC SUPPORT DO THEY RECEIVE?
resources to be scaled up (OECD, 2014[3]). If the funding spent on scholarships and grants was used instead 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[3]). A large share of graduates with debt could be a problem if employment prospects are not sufficient to
guarantee student loan repayments.
OECD governments support students’ living or education costs through different combinations of these two types
of support – and these combinations vary even among countries with similar levels of tuition fees. The
cross-country variation is significant, for instance, among countries and economies with high annual average
tuition fees for bachelor’s degrees in public institutions (around USD 4 500 and over). In England
(United Kingdom), more than 90% of students only receive loans (and not scholarships/grants) to cover the cost
of their studies (in bachelor’s and master’s long first degrees). In the United States, 53% of students benefit from
both loans and scholarships or grants, 26% from scholarships/grants alone and 10% from loans alone. In
Australia and New Zealand, most students receive either loans alone or both loans and scholarships or grants;
and in Canada, they receive loans, scholarships/grants, or a combination of both. (Figure C5.3).
In countries with available data where public institutions charge no tuition fees at the bachelor’s level, most
students receive financial support in the form of both loans and scholarships or grants, in order to cover their
living costs. This is true for 58% of students in Finland and around 75% in Norway and Sweden. In contrast, in
Denmark, most students receive financial support in the form of scholarships/grants alone (58%), and only 27%
receive both loans and scholarships or grants.
Finally, in countries and economies such as Austria, the French Community of Belgium, Italy, Portugal, Spain
and Switzerland, where annual average tuition fees for bachelor’s degrees are below USD 2 000, less than 45%
of students receive any form of financial support – and those who do tend to receive it in the form of grants or
scholarships only.

Type of loans systems, amounts borrowed and debt at graduation
There are two main types of student loans: mortgage-style loans and income-contingent loans. In a mortgagestyle loan system, students are obliged to repay the loan within a fixed period, regardless of their financial
situation after their studies. This may impose a heavy financial burden on graduates (or those who did not
graduate) with low incomes. In contrast, in income-contingent loan systems, repayment is conditional on the
borrower’s income reaching a threshold, and includes debt forgiveness after a certain period of time. This type
of repayment arrangement is considered to be more equitable, as it takes into account graduates’ ability to repay
their loan.
Both systems imply some costs for the government that guarantees the loan repayment. However, the potential
financial burden for the government is more uncertain with income-contingent loans, as these are contingent on
graduates’ ability to find work and earn income above the minimum threshold for reimbursement.
Several countries have introduced income-contingent loans in recent years. For example, the United Kingdom
replaced its mortgage-loan system with an income-contingent loan system in 1999 – and nowadays as much as
45% of student loans are not repaid. With the increase in student debt, some income-contingent loan systems
were also introduced in the United States: the income-based repayment programme in 2009 and the Pay-AsYou-Earn (PAYE) plan in 2012 (Table C5.3 and (OECD, 2015[2]). Among countries with available data, Australia,
Chile and New Zealand have also adopted an income-contingent loan system. Japan, Korea and the Netherlands
exhibit a hybrid system, which includes both income-contingent and mortgage-style loans (Table C5.3).
EDUCATION AT A GLANCE 2019 © OECD 2019

C5. HOW MUCH DO TERTIARY STUDENTS PAY AND WHAT PUBLIC SUPPORT DO THEY RECEIVE?  323

Previous sections have highlighted cross-country variations in the proportion of students benefiting from a loan;
but there is also variation in the average annual amount borrowed by each student. Among countries and
economies where most students receive loans (70% of students or more), this ranges from around USD 5 600
per year in Australia to around USD 7 000 in New Zealand and Sweden, USD 10 400 in Norway, and up to
USD 17 000 in England (United Kingdom). Similarly, in countries where about 25% to 35% of students receive
loans (Canada, Chile, Denmark and Japan), the average annual amount borrowed ranges from around
USD 3 900 in Denmark to around USD 7 700 in Japan (Table C5.3).
The debt burden that students accumulate is one factor that may affect individuals’ decisions to invest in tertiary
education. 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.
Among the countries and economies with high tuition fees, in Australia, England (United Kingdom) and
New Zealand, at least 70% of students are in debt at graduation as a result of taking loans. However, the average
amount of debt at graduation varies significantly, from USD 10 500 in Australia to USD 24 100 in New Zealand
and over USD 49 800 in England (United Kingdom). In countries where tertiary studies entail no or low tuition
fees, debt at graduation would typically be lower than in countries with high tuition fees, since student loans are
mainly needed to cover students’ living expenses. However, in Nordic countries, where there are low or no tuition
fees, the level of student debt at graduation may still be high because living expenses are high. This is the case
for instance in Norway, where students’ average debt amounts to over USD 28 700 (Table C5.3).

Box C5.2. What percentage of public student loans are repaid?
For some countries and economies, student public loans have become an important element of student
support. The variety of loan systems and repayment schemes across the world can present some challenges
in assessing the actual financial contribution of the public sector. To improve the comparability, an approach
is to estimate the repayment of loans. Two methods may be considered for this analysis:


Cash accounting basis: This method considers the repayment in the reference year of loans issued
in previous years. This figure is shown as a percentage of gross disbursement of loans in the reference
year in Figure C5.a.



Net present value: This method tries to capture the current choices made by governments by
measuring the expected repayment levels of loans issued in the reference year. The measure
presented in Figure C5.a is the discounted expected repayment of loans issued in the reference year,
as a percentage of the gross disbursement of loans in the reference year.

These two methods may yield very different results for a given country, because they are based on different
time periods and student cohorts. The cash accounting basis compares earlier loans (repayment of loans
issued in previous years) with current loans (disbursement of loans in the reference year). In other words, this
approach compares loans for several cohorts: 1) students who borrow loans in the reference year; and
2) people who are repaying loans in the same year. In countries with well-established loans systems, the
number of students who are repaying loans in the reference year can be significantly higher than the number
of students who borrow money.
On the other hand, the net present value approach focuses on current loans (disbursement of loans in the
reference year and their expected repayment). In other words, it takes into account the amounts of loans
borrowed by students in the reference year and an estimation of the future repayment by the same cohort.
Figure C5.a shows significant cross-country variation in the repayment of student loans, particularly when
using the cash accounting basis. In Australia, England (United Kingdom) and Finland, the repayment of
outstanding loans received in the reference year represents less than 40% of the gross disbursement of loans
issued that year. This value rises to around 65% in Norway and around 90% in Canada and the United States.

EDUCATION AT A GLANCE 2019 © OECD 2019

324  C5. HOW MUCH DO TERTIARY STUDENTS PAY AND WHAT PUBLIC SUPPORT DO THEY RECEIVE?
In Korea and the Slovak Republic, it even exceeds 100% (with values of 117% in Korea and 110% in the
Slovak Republic).
The results observed may reflect the maturity of student loans programmes: older programmes may have a
large number of people repaying student loans compared to those currently receiving loans, while newer
programmes may have relatively few people in the repayment phase of loans. High values may also reflect a
decrease in financial support to students in the reference year compared to previous years (e.g. lower average
amounts of loans, lower number of students benefiting from a loan etc.), or a high repayment of loans issued
in previous years. In Korea, for instance, the high value (117%) reflects 1) the high number of people repaying
loans in the reference year compared to students borrowing loans in the same year; 2) the increased reliance
on scholarships rather than students loans; and 3) the increased amount of loan repayments
It is important to note that loan repayments are not necessarily re-allocated to education. In fact, Korea is the
only country with available data where it is clearly stated that 100% of loan repayments are re-allocated to
student loans.
Considering the net present value of loans, in Australia and New Zealand, between 70% and 75% of student
loans issued in the reference year are expected to be repaid. In contrast, this proportion reaches around 90%
in Norway and around 100% in Finland and Sweden. In the Slovak Republic, it even exceeds 100% due to
interest rates.

Figure C5.a. What percentage of public student loans are repaid?

Note: The numbers in this figure should be interpreted with caution as they are based on estimations. The year of reference may differ across
countries. Please see Annex 3 for details.
1. Government-guaranteed private loans instead of public loans.
Countries and economies are ranked in descending order of the percentage of student loans repaid based on the cash accounting basis
methodology.
Source: OECD (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933979348

EDUCATION AT A GLANCE 2019 © OECD 2019

C5. HOW MUCH DO TERTIARY STUDENTS PAY AND WHAT PUBLIC SUPPORT DO THEY RECEIVE?  325

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 these
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. The 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.
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 expenditure on education.
OECD indicators take the full amount of scholarships/grants 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[5]) and Annex 3 for country-specific notes (https://doi.org/10.1787/f8d7880d-en).

Source
Data refer to the school year 2017/18 and are based on a special survey administered by the OECD in 2019
(for details see Annex 3 at https://doi.org/10.1787/f8d7880d-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.

EDUCATION AT A GLANCE 2019 © OECD 2019

326  C5. HOW MUCH DO TERTIARY STUDENTS PAY AND WHAT PUBLIC SUPPORT DO THEY RECEIVE?

References
OECD (2018), Education at a Glance 2018: OECD Indicators, OECD Publishing, Paris,
https://dx.doi.org/10.1787/eag-2018-en.

[4]

OECD (2018), OECD Handbook for Internationally Comparative Education Statistics: Concepts,
Standards, Definitions and Classifications, OECD Publishing, Paris,
https://dx.doi.org/10.1787/9789264304444-en.

[5]

OECD (2017), “Tuition fee reforms and international mobility”, Education Indicators in Focus, No. 51,
OECD Publishing, Paris, http://dx.doi.org/10.1787/2dbe470a-en.

[1]

OECD (2015), Education at a Glance 2015: OECD Indicators, OECD Publishing, Paris,
https://dx.doi.org/10.1787/eag-2015-en.

[2]

OECD (2014), Education at a Glance 2014: OECD Indicators, OECD Publishing, Paris,
https://dx.doi.org/10.1787/eag-2014-en.

[3]

Indicator C5 Tables
Table C5.1

Annual average (or most common) tuition fees charged by tertiary institutions to national and
foreign students (2017/18)

Table C5.2

Tuition fees charged by institutions for full-time students, in USD converted using PPPs, and
percentage of national students receiving financial support (2017/18)

Table C5.3

Public loans to students, repayment and remission in tertiary education (2017/18)

Table C5.4

Changes in tuition fee policies and public support to students (2007/08 to 2017/18)

Cut-off date for the data: 19 July 2019. 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.
StatLink: https://doi.org/10.1787/888933981134

EDUCATION AT A GLANCE 2019 © OECD 2019

C5. HOW MUCH DO TERTIARY STUDENTS PAY AND WHAT PUBLIC SUPPORT DO THEY RECEIVE?  327

Table C5.1. Annual average (or most common) tuition fees charged by tertiary institutions to national and foreign students
(2017/18)
In equivalent USD converted using PPPs, by type of institutions and level of education

EDUCATION AT A GLANCE 2019 © OECD 2019

328  C5. HOW MUCH DO TERTIARY STUDENTS PAY AND WHAT PUBLIC SUPPORT DO THEY RECEIVE?

Note: Enrolment data is presented for the year 2016/17. The year of reference may differ across countries. Please see Annex 3 for details. For European countries, tuition
fees for foreign students refer to students from outside the European Economic Area. For institutions charging no tuition fees, the fees are shown as 0.
The detailed disaggregation by type of institution is available on line (see StatLink below).
1. Government-dependent institutions are included in independent private institutions. For Austria and Germany, government-dependent institutions are included in
independent private institutions for enrolment data only.
2. Government-dependent institutions instead of public institutions.
3. Institutions have the autonomy to fix the amount of the tuition fee for degree programmes with study language other than Estonian, in public and government-dependent
private institutions.
4. Tuition fees are presented for total tertiary education instead of bachelor's or equivalent level. Only academic programmes are included.
5. Short-cycle tertiary programmes are included in bachelor's or equivalent programmes.
6. Estimates include universities only and exclude ISCED 6, such as postgraduate certificates and diplomas.
7. Government-dependent private institutions are included in public institutions.
8. Tuition fees for foreign students typically refer to tuition fees for out-of-state national students. However, in a minority of institutions, tuition fees can be lower for out-ofstate national students.
Source: OECD (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888933979215

EDUCATION AT A GLANCE 2019 © OECD 2019

C5. HOW MUCH DO TERTIARY STUDENTS PAY AND WHAT PUBLIC SUPPORT DO THEY RECEIVE?  329

Table C5.2. Tuition fees charged by institutions for full-time students, in USD converted using PPPs, and percentage of
national students receiving financial support (2017/18)
Bachelor's only for tuition fees, and bachelor's and master's long first degrees or equivalent programmes for financial support

Note: Enrolment data is presented for the year 2016/17. The year of reference may differ across countries. Please see Annex 3 for details. For institutions charging no
tuition fees, the fees are shown as 0.
The detailed disaggregation by type of institution is available on line (see StatLink below).
1. Government-dependent private institutions are included in independent private institutions. For Austria and Germany, government-dependent institutions are included in
independent private institutions for enrolment data only.
2. Data on financial support corresponds to total tertiary instead of bachelor's and long-cycle master's degrees or equivalent.
3. Data is presented for government-dependent institutions instead of public institutions.
4. Tuition fees are presented for total tertiary education instead of bachelor's or equivalent level. Tuition fees correspond to national and foreign students. Only academic
programmes are included.
5. Short-cycle tertiary programmes are included in bachelor's or equivalent programmes.
6. Estimates include universities only and exclude ISCED 6, such as postgraduate certificates and diplomas.
7. Government-dependent private institutions are included in public institutions.
Source: OECD (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888933979234

EDUCATION AT A GLANCE 2019 © OECD 2019

330  C5. HOW MUCH DO TERTIARY STUDENTS PAY AND WHAT PUBLIC SUPPORT DO THEY RECEIVE?
Table C5.3. Public loans to students, repayment and remission in tertiary education (2017/18)

Note: The year of reference may differ across countries. Please see Annex 3 for details.
1. Information on debt, repayment and remission refer to government-guaranteed private loans instead of public loans.
2. The two types of repayment are: fixed payment (depending on the total amount of loan and numbers of repayment times) and income-contingent payment (depending
on students' incomes in the previous year).
3. The share of students who benefit from a loan and the average annual amount of loan are presented for short-cycle tertiary, bachelor's and long-cycle master's degrees.
Source: OECD (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888933979253

EDUCATION AT A GLANCE 2019 © OECD 2019

C5. HOW MUCH DO TERTIARY STUDENTS PAY AND WHAT PUBLIC SUPPORT DO THEY RECEIVE?  331

Table C5.4. Changes in tuition fee policies and public support to students (2007/08 to 2017/18)
Tuition fees in equivalent USD converted using PPPs (2017 constant prices), full-time national students

Note: The year of reference may differ across countries. Please see Annex 3 for details.
1. Government-dependent institutions instead of public institutions.
2. Tuition fees are presented for total tertiary education instead of bachelor's or equivalent level. Tuition fees correspond to national and foreign students. Only academic
programmes are included.
3. Short-cycle tertiary programmes are included in bachelor's or equivalent programmes.
4. Estimates include universities only and exclude ISCED 6, such as postgraduate certificates and diplomas.
5. Government-dependent private institutions are included in public institutions.
Source: OECD (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888933979272

EDUCATION AT A GLANCE 2019 © OECD 2019

332  C6. ON WHAT RESOURCES AND SERVICES IS EDUCATION FUNDING SPENT?

Indicator C6. On what resources and services is
education funding spent?
Highlights


From primary to tertiary level, 92% of the spending of educational institutions is devoted to current
expenditure (goods and services consumed within the current year) on average across
OECD countries.



On average across OECD countries, staff compensation comprises the largest share of current
expenditure at all levels of education: 78% in non-tertiary education not including pre-primary (primary,
secondary and post-secondary non-tertiary education) and 69% in tertiary education.



OECD countries allocate on average 8% of their total education spending to capital expenditure. The
share is higher in tertiary education (10%) than in non-tertiary education (7%) and varies across
countries and type of educational institution.

Figure C6.1. Share of capital expenditure by type of institutions (2016)
Tertiary education

1. Year of reference 2017.
2. Tertiary education includes post-secondary non-tertiary education.
3. Tertiary education includes upper secondary (vocational).
Countries are ranked in descending order of the share of capital expenditure in public institutions.
Source: OECD/UIS/Eurostat (2019), Education at a Glance Database, http://stats.oecd.org/. See Source section for more information and Annex 3
for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933979424

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

EDUCATION AT A GLANCE 2019 © OECD 2019

C6. ON WHAT RESOURCES AND SERVICES IS EDUCATION FUNDING SPENT?  333

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 and institutions. 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 the
construction of new buildings. The indicator also presents details on how current expenditure is allocated,
between staff compensation and other services such as meals, transport, housing and/or research activities.

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 not including pre-primary
with the remainder going to other staff.



In non-tertiary education, the share of total expenditure allocated to current expenditures by public
institutions (93%) is similar to that of private institutions (94%). Conversely, at tertiary levels, private
institutions (92%) spend a larger share of total expenditure on current expenditures than public
institutions (89%).



The share of other staff expenditure varies in non-tertiary institutions, from a high of around 20% or
more in Estonia, France, Iceland, Lithuania and the United States to less than 10% in Austria,
Colombia and Luxembourg.

EDUCATION AT A GLANCE 2019 © OECD 2019

334  C6. ON WHAT RESOURCES AND SERVICES IS EDUCATION FUNDING SPENT?

Analysis
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).
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 2016, 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 81% in
Colombia to 96% in Belgium, Iceland, Italy, Portugal 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 (90%). At primary level, the share varies from 80% in Slovenia to 99% in Italy. At secondary level, the share
varies from 87% in Slovenia and Turkey to 98% in Austria. At the post-secondary non-tertiary level, the share
varies from 87% in Ireland to 100% in Israel and Luxembourg. At the tertiary level, it varies from 57% in Greece
to 97% in Estonia and Finland. The overall share of current expenditure does not differ by more than 3 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 Estonia, Finland, Ireland, Israel, Korea, Latvia, Norway, Slovenia,
Sweden and the United States.
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. On average across OECD countries, the share of capital expenditure is generally
higher in tertiary institutions (10%) than in non-tertiary institutions (7%). Capital expenditure on tertiary education
reaches highs of 21% in Turkey, 40% in Colombia and 43% in Greece. In non-tertiary education, Slovenia
allocates the highest shares of education budgets to capital expenditure across countries with available
data (16%).
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 the salaries of education personnel and the costs of maintaining
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 (69%), a difference of 9 percentage points. OECD countries spend on average 63% of
total current expenditure on teacher compensation and 15% on paying other staff in non-tertiary education,
leaving 22% for other current expenditure (Table C6.2 and Figure C6.2).

EDUCATION AT A GLANCE 2019 © OECD 2019

C6. ON WHAT RESOURCES AND SERVICES IS EDUCATION FUNDING SPENT?  335

Figure C6.2. Distribution of current expenditure in public and private educational institutions (2016)

1. Year of reference 2017.
2. Primary education includes pre-primary programmes.
3. Tertiary education includes post-secondary non-tertiary education.
4. Tertiary education includes upper secondary (vocational).
Countries are ranked in descending order of the share of all staff compensation.
Source: OECD/UIS/Eurostat (2019), Table C6.2. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933979443

There is significant variation within countries in how current expenditure is allocated across levels of education.
In most countries, tertiary education has the lowest share of total current spending allocated to staff compensation
across all 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), and their
differences between tertiary and non-tertiary levels exceeds 1 and 6 percentage points respectively. When
looking at all education levels together, Colombia stand out as distinctive. It tends to devote a larger share of

EDUCATION AT A GLANCE 2019 © OECD 2019

336  C6. ON WHAT RESOURCES AND SERVICES IS EDUCATION FUNDING SPENT?
current educational expenditure to staff compensation (92%) and less to other contracted and purchased
services, such as support services (e.g. building maintenance), ancillary services (e.g. meal programmes) and
the rent paid for school buildings and other facilities.
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 their premises, which can account for a substantial share of current
expenditure. The differences among countries in the shares allocated to paying non-teaching staff are likely to
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 of “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 (see Indicator C1).

Distribution of current and capital expenditure by public versus private educational
institutions
Public and private institutions generally allocate their spending between current and capital expenditure in a
similar way, although differences are more marked in tertiary education than in non-tertiary education. Across
OECD countries, the average share of current expenditure in private institutions is 94% in non-tertiary education,
1 percentage point higher than in public institutions (93%). At the tertiary level, the share of current expenditure
in private institutions (92%) is 3 percentage points higher than in public institutions (89%). This difference at
tertiary level is more marked in Colombia (21 percentage-point difference). In Australia, the share of current
expenditure is substantially higher in public institutions, with a difference of 12 percentage points (Table C6.3).
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 in private institutions (72%). This gap is most
pronounced in Italy, Portugal and Turkey, where the differences between the two sectors are greater than
20 percentage points. The pattern is reversed in Norway, 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 (69% on average across OECD countries)
than do private institutions (63%). However, the share of current spending devoted to staff compensation is lower
at tertiary level than at lower levels of education suggesting the existence of non-staff related services at tertiary
level that affects both public and private institutions.
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. For instance private institutions may be more
likely to contract services from external providers. They may be more likely to rent school buildings and other
facilities (as opposed to public institutions operating 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 in tertiary
education on average across OECD countries (11% and 9%). However, the share of capital expenditure in public
and private institutions varies to a large extent by country (Figure C6.1). Public institutions in Colombia, Greece
and Turkey allocate the highest share of capital spending in tertiary education, reaching more than 20% of total
expenditure. Some explanations for this might be related to the lower tertiary attainment rate in Colombia and
Turkey (see Indicator A1) and the fact that most students in Colombia are enrolled in private institutions (see
Indicator B1). Public institutions spend the lowest share on capital in Argentina, Estonia, Finland, Ireland, Latvia,
Portugal and Sweden (below 5%). The variation across countries is also high for private institutions, with private
institutions in Colombia and Turkey spending more than 25% of their total expenditure on capital, and those in
EDUCATION AT A GLANCE 2019 © OECD 2019

C6. ON WHAT RESOURCES AND SERVICES IS EDUCATION FUNDING SPENT?  337

Estonia, Finland, the Russian Federation and Sweden spending below 4%. The difference between public and
private institutions in the share of their allocations to capital expenditure is less than 3 percentage points for twothirds of the countries with data available. Colombia has the largest differences in the share of capital expenditure,
with its public institutions spending proportionally 20 percentage points more than its private 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 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 “nonteaching staff” category includes other pedagogical, administrative and professional personnel as well as
support personnel (e.g. head teachers, other school administrators, supervisors, counsellors, school
psychologists and health personnel, librarians, and 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
(https://doi.org/10.1787/f8d7880d-en).

Sources
Data refer to the financial year 2016 (unless otherwise specified) and are based on the UNESCO, the OECD and
Eurostat (UOE) data collection on education statistics administered by the OECD in 2018 (for details see Annex 3
at https://doi.org/10.1787/f8d7880d-en). Data from Argentina, the People’s Republic of China, India, Indonesia,
Saudi Arabia and South Africa are from the UNESCO Institute of Statistics (UIS).

EDUCATION AT A GLANCE 2019 © OECD 2019

338  C6. ON WHAT RESOURCES AND SERVICES IS EDUCATION FUNDING SPENT?
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.

[2]

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
Table C6.1

Share of current and capital expenditure, by education level (2016)

Table C6.2

Current expenditure, by resource category (2016)

Table C6.3

Share of current expenditure, by resource category and type of institution (2016)

Cut-off date for the data: 19 July 2019. Any updates on data can be found on line at
http://dx.doi.org/10.1787/eag-data-en. More breakdowns can be found at http://stats.oecd.org/, Education at
a Glance Database.
StatLink: https://doi.org/10.1787/888933981153

EDUCATION AT A GLANCE 2019 © OECD 2019

C6. ON WHAT RESOURCES AND SERVICES IS EDUCATION FUNDING SPENT?  339

Table C6.1. Share of current and capital expenditure, by education level (2016)
Distribution of current and capital expenditure by educational institutions from public and private sources

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 pre-primary programmes. Post-secondary non-tertiary figures are treated as negligible.
2. Year of reference 2017.
Source: OECD/UIS/Eurostat (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888933979367

EDUCATION AT A GLANCE 2019 © OECD 2019

340  C6. ON WHAT RESOURCES AND SERVICES IS EDUCATION FUNDING SPENT?
Table C6.2. Current expenditure, by resource category (2016)
Distribution of current expenditure by educational institutions from public and private sources as a percentage of total current
expenditure

Note: Some levels of education are included with others. Refer to "x" in Table C6.1 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 pre-primary programmes.
2. Year of reference 2017.
Source: OECD/UIS/Eurostat (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888933979386

EDUCATION AT A GLANCE 2019 © OECD 2019

C6. ON WHAT RESOURCES AND SERVICES IS EDUCATION FUNDING SPENT?  341

Table C6.3. Share of current expenditure, by resource category and type of institution (2016)
Distribution of current expenditure by educational institutions

Note: Some levels of education are included with others. Refer to "x" in Table C6.1 for details. Total data for expenditure on primary to tertiary education (i.e. Columns 17
to 24) are available for consultation on line (see StatLink below). 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. Year of reference 2017.Source: OECD/UIS/Eurostat (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888933979405

EDUCATION AT A GLANCE 2019 © OECD 2019

342  C7. WHICH FACTORS INFLUENCE TEACHERS' SALARY COST?

Indicator C7. Which factors influence teachers'
salary cost?
Highlights


This analysis calculates the salary cost of teachers per student using four factors: teachers’ salaries,
students’ instruction time, teachers’ teaching time and theoretical class size (see Definitions section).
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 rises from USD 2 784 in
primary education to USD 3 380 in lower secondary education.



The two main factors influencing the level of teachers’ salary costs are teachers’ salaries and
theoretical class sizes. Between 2005 and 2017, teachers’ salaries increased in most OECD countries,
and this additional cost was often offset by similar increases in the average class size.

Figure C7.1. Annual salary cost of teachers per student in public institutions, by level of education
(2017)
USD converted using PPPs for private consumption

1. Teachers' statutory salaries after 10 years of experience instead of 15 years.
2. Teachers' statutory salaries at the start of their career instead of after 15 years of experience.
Countries and economies are ranked in descending order of the annual salary cost of teachers per student in lower secondary education.
Source: OECD (2019), Table C7.1. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933979519

EDUCATION AT A GLANCE 2019 © OECD 2019

C7. WHICH FACTORS INFLUENCE TEACHERS' SALARY COST?  343

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. The salary cost of teachers per student, as calculated in this indicator, is a function
of students’ instruction time, teachers’ teaching time, teachers’ statutory salaries and theoretical class sizes
(see Methodology section).
Differences among countries in these 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 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 sizes would also shrink (assuming all other factors remain constant), unless there was also
a simultaneous drop in the number of teachers. This indicator does not distinguish between a reduction in
class size due to demographic changes and a deliberate policy decision to reduce class size.

Other findings


Similar levels of expenditure among countries can mask a variety of contrasting policy choices. For
example, France and Hungary have nearly the same salary cost of teachers per primary student, but
teachers’ statutory salaries in France are 80% higher than in Hungary, which is more than balanced
out by classes in France having about seven more students on average (based on the theoretical class
size).



On average across OECD countries, the salary cost of teachers per student represents 6.7% of gross
domestic product (GDP) per capita at primary level and 8.2% at lower secondary level.



Given a fixed level of salary cost, a reduction in class size can be compensated for by a decrease in
teachers’ salaries, a decrease in instruction time or an increase in teaching time. For example, in
Australia, in order to reduce theoretical class size by one student and keep the salary cost per student
constant, annual teacher salaries would have to fall by USD 3 600, annual instruction time would have
to be reduced by 57 hours, or annual teaching time would have to increase by 53 hours

Note
The salary cost of teachers per student is estimated based on values for teachers’ gross statutory salaries
after 15 years of experience and the most prevalent qualifications (see Indicator D3), the theoretical instruction
time for students (see Indicator D1) and teachers’ statutory teaching time (see Indicator D4). This measure
may differ from the actual salary cost of teachers (see Box C7.1).
The use of statutory salaries means that this indicator does not take into account the actual level of
qualifications and the seniority of the teaching workforce. The statutory salary also does not include employer’s
contribution to social security and pension and therefore does not represent the full cost incurred by the
employer (i.e. the government). As a result, this measure is not comparable to the indicator on expenditure on
teacher compensation (see Indicator B6).

EDUCATION AT A GLANCE 2019 © OECD 2019

344  C7. WHICH FACTORS INFLUENCE TEACHERS' SALARY COST?

Analysis
Variation in the salary cost of teachers per student by level of education
On average across OECD countries and economies, the salary cost of teachers is USD 2 784 per primary
student, USD 3 380 per lower secondary student and USD 3 274 per general upper secondary student (Figure
C7.1). 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 Germany (USD 4 679) is over six times the cost in Latvia
(USD 720). Higher salary costs are a result of higher teachers’ salaries and/or having more teachers per student,
which is itself pushed up by smaller classes, longer required instruction time for students or shorter teaching
hours for teachers.
The general increase in teachers’ salary cost between primary and lower secondary education is the result of
increases in teachers’ salaries and students’ instruction time, as well as a reduction in teaching time, all of which
push up the cost. In 2017, the OECD average annual statutory salary for teachers with 15 years of experience
was USD 43 007 at lower secondary level, around USD 1 950 more than the average salary at primary level.
Moreover, the average annual instruction time in lower secondary education was 124 hours longer than in primary
education, while average teaching time was 83 hours shorter, implying that more teachers were needed to teach
a given number of pupils.
In contrast to the other factors, theoretical 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 theoretical class
size increases from 15 students at primary level to 17 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,
Colombia and Mexico are the only OECD countries where the salary cost of teachers per student in lower
secondary is less than in primary education (Tables C7.5a and b, available on line). This is mainly due to an
increase in theoretical class size between primary and lower secondary levels in these countries.
In a few countries, the learning environment and the organisation of schools are relatively similar in primary and
lower secondary education. For example, in 2017, the difference in the salary cost of teachers per student
between primary and lower secondary was less than USD 100 in Canada, Hungary, Mexico and Turkey. The
greatest difference was in Slovenia, where it was of USD 4 036.

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 countries. On average across
OECD countries, the salary cost of teachers per student represents 6.7% of GDP per capita at primary level,
8.2% at lower secondary level and 8.0% 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 2 355. However, this
amount represents 7.9% of the country’s GDP per capita, above the OECD average of 6.7%. This means that
Poland devotes an above-average share of its GDP per capita to teachers’ salary cost, even if the absolute
amount is relatively low. The opposite is the case in Ireland, where the salary cost of teachers per student in
primary education (USD 3 844) is considerably above the OECD average, but represents only 5% of the country’s
GDP per capita, well below the OECD average.

EDUCATION AT A GLANCE 2019 © OECD 2019

C7. WHICH FACTORS INFLUENCE TEACHERS' SALARY COST?  345

Box C7.1. Methodological limitations and potential future developments
Teachers’ salary cost per student, as presented in this indicator, is an estimated measure of how much is
spent on teachers’ salaries in each country. In addition to teachers’ salaries themselves, the indicator takes
into account three factors that influence the number of teachers a system requires: the number of required
instruction hours, the number of hours teachers spend teaching and the theoretical class size. Please see the
Methodology section for more information on how these factors relate to each other and are combined to
calculate the salary cost.
It is important to consider the limitations of this indicator’s methodology when interpreting the results. First,
the indicator is calculated using the statutory values for teaching and instruction time and teachers’ statutory
salaries. Therefore, the results presented in this indicator are theoretical in nature, and do not reflect the actual
time teachers spend teaching or how much they actually earn each year. Indeed, even the concept of teaching
and instruction time have become increasingly theoretical in nature as learning settings become more flexible,
making it difficult to accurately measure the amount of time spent on these activities.
Second, by using national figures, the indicator misses the wide discrepancies that may exist within countries.
The trade-off between teachers’ salaries and class size, for example, may have very different effects
depending on the socio-economic status of students and schools. Moreover, the trade-offs highlighted in this
analysis are only a few of the many decisions countries must make when allocating their resources. Countries
must also examine potential trade-offs with other investment areas, such as teacher training and school
infrastructure, as well as trade-offs between different levels of education.
Although some of these limitations are difficult to address due to current data availability, there are several
possible avenues to take that would expand the analytical potential of this indicator once more data become
available. The first would be improving the measure used to estimate the cost of teachers. One way to achieve
this might be to use teachers’ average actual salaries, taking bonuses and allowances into account, instead
of the statutory salaries. Another possibility would be to take into account the full cost to the government of
teachers’ salaries, including costs that do not go directly to teachers, such as employer’s contributions and
pensions.
Other avenues for potential future development include exploring the link between teachers’ salary costs and
school funding formulae, and how the trade-offs associated with teachers’ salary costs may differ across
subnational levels of decision making, such as schools, school districts and municipalities.

Contribution of each factor to the salary cost of teachers per student
The four factors which determine the salary cost of teachers per student affect it in different ways. 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
sizes constant. Similarly, more teachers would need to be hired in order to reduce class sizes 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, longer instruction times, shorter teaching hours, smaller
class sizes or a combination of these four factors. Changing one of these factors may require compensatory
trade-offs among the other factors in order to keep the total salary cost constant (Box C7.2).

EDUCATION AT A GLANCE 2019 © OECD 2019

346  C7. WHICH FACTORS INFLUENCE TEACHERS' SALARY COST?
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 size 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 per student in primary education in Poland is USD 2 355, USD 429
lower than the OECD average. This difference is the result of the contributory effects of the four factors: belowaverage theoretical class size adds USD 521 to the difference, below-average teaching time adds USD 864,
below-average teachers’ salary subtracts USD 1 226 and below-average instruction time subtracts USD 588
(Table C7.2).

Figure C7.2. Contribution of various factors to salary cost of teachers per student in public institutions,
primary education (2017)
USD converted using PPPs for private consumption

1. Teachers' statutory salaries after 10 years of experience instead of 15 years.
2. Teachers' statutory salaries at the start of their career instead of after 15 years of experience.
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 (2019), Table C7.2. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933979538

EDUCATION AT A GLANCE 2019 © OECD 2019

C7. WHICH FACTORS INFLUENCE TEACHERS' SALARY COST?  347

Different policies in 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, each
with similar teachers’ salary cost per student, in order to better illustrate the range of policy choices that are
possible – and have been made by other countries – while spending similar amounts.

Group 1: High salary cost of teachers per student in primary education
This group, which has the highest salary cost of teachers per student in primary education, is composed of
Australia, Austria, the Flemish and French communities of Belgium, Canada, Germany, Norway and Switzerland.
The salary cost of teachers per student in this group ranges from USD 4 013 to USD 4 679. All of these countries
have above-average GDP per capita, but the relationship between salary cost and GDP per capita is not one-toone. Some countries allocate a larger share of their wealth to this type of expenditure than others (Table C7.1).
Compared to countries from the other groups, it may seem as though these high-spending countries do not face
trade-offs between the four factors analysed in this indicator. Indeed, most of the countries in this group can
afford both above-average teacher salaries and below-average theoretical class sizes. However, the magnitude
of the difference between these factors and the respective OECD averages differs considerably across these
countries. In Germany, for example, the high salary cost of teachers is mostly a result of high teachers’ salaries,
whereas in Austria it is mostly the result of small theoretical class sizes.

Group 2: Moderately high salary cost of teachers per student in primary education
This group is composed of 11 countries with above-average salary costs: Finland, Greece, Iceland, Ireland, Italy,
Japan, the Netherlands, Portugal, Slovenia, Spain and the United States. The salary cost of teachers per student
in this group ranges from USD 2 833 to USD 3 844 (Table C7.1). This group is highly heterogeneous in terms of
GDP per capita and education expenditure, which sheds light on the many different choices countries with similar
spending can make.
A potential trade-off observed in some countries is between students’ required instruction time and teachers’
teaching time. In the Netherlands, for example, students receive 147 hours more instruction time per year than the
OECD average, but this is almost entirely offset by teaching time that is 150 hours longer than the average.
Requiring longer 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
224 teaching hours above the OECD average helps offset for the additional USD 19 970 teachers receive each
year (the statutory teachers’ salary in the United States is USD 61 028 compared to the OECD average of
USD 41 058).

Group 3: Moderately low salary cost of teachers per student in primary education
This group is composed of six countries with below-average salary cost of teachers per student: Chile, France,
Hungary, Israel, Lithuania and Poland. Teachers’ salary cost in this group range from USD 1 875 per student to
USD 2 355 (Table C7.1). With the exception of France, all of these countries have below-average GDP per capita.
All six countries in this group have below-average teacher salaries, which is one of the main drivers of the belowaverage salary cost in primary education. However, there are considerable differences between them. In
Hungary, Lithuania and Poland, lower teachers’ salaries are partially compensated by shorter teaching hours and
smaller theoretical class sizes. This is not the case in the other three countries, where teaching time and
theoretical class sizes are both above average. France and Hungary have nearly the same salary cost of teachers

EDUCATION AT A GLANCE 2019 © OECD 2019

348  C7. WHICH FACTORS INFLUENCE TEACHERS' SALARY COST?
per student, but teachers’ statutory salaries in France are 80% higher than in Hungary, which is more than
compensated for by having about seven more students per class (based on the theoretical class size).

Group 4: Low salary cost of teachers per student in primary education
This group is composed of the seven countries with the lowest salary cost of teachers per student in primary
education: Colombia, the Czech Republic, Estonia, Latvia, Mexico, the Slovak Republic and Turkey. The salary
cost of teachers per student in this group ranges from USD 720 to USD 1 560 (Table C7.1). These countries all
have below-average GDP per capita.
In an overall cross-country comparison, Latvia and the Slovak Republic might be bundled together as having low
salary costs due to below-average salaries and below-average theoretical class sizes. However, there are
important differences in the education characteristics of these two countries. The Slovak Republic’s larger
theoretical class size (compared to Latvia’s) allows it to pay teachers over twice as much as Latvia, which has
the lowest teachers’ salaries and smallest theoretical class sizes of all OECD countries.

Evolution of average class size and teachers’ salaries
At each level of education, teachers’ salaries generally have the greatest 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
theoretical class size. The trade-off between these two variables, which are often the target of educational reforms
and policies, reflects the choice countries have to make between increasing teachers’ salaries and hiring more
teachers. In fact, controlling for the total salary cost of teachers, countries with higher teachers’ salaries tend to
have larger class sizes (OECD, 2018[2]).
Figure C7.3 plots the evolution of teachers’ statutory salaries and average class sizes between 2005 and 2017.
The average class size, unlike the theoretical class size discussed in the previous sections of this indicator, refers
to the average actual class size obtained by dividing the number of students enrolled by the number of classes
in each country (please see the Definitions section for more information on the difference between theoretical
and average class size).
The figure groups countries into four different categories, each represented in a quadrant of the chart. Countries
in the top-right and bottom-left quadrants exhibit a trade-off between average class size and teachers' salaries in
this period. Countries in the top-right quadrant increased average class sizes (which brings the salary cost of
teachers down) and increased teachers' salaries (which pushes the cost up). The most notable example among
this group of countries is Mexico, where the average class size increased by over 20% in the period, helping to
offset the cost of increasing teachers’ salaries by over 30%. Only two countries (Greece and Japan) faced the
opposite trade-off, where average class sizes were reduced, but the additional cost was somewhat compensated
for by lower teachers’ salaries. It is important to note that although these changes have opposite effects on the
salary cost, they are not necessarily taken in response to each other. In Japan, for example, the decrease in
average class size was mainly due to a demographic change whereas the decrease in teachers’ salaries was at
least partially due to a change in teachers’ generation.
No particular trade-off between these two variables seems to have taken place in this period in the countries and
economies in the top-left and bottom-right quadrants. Those in the top-left quadrant increased average class
sizes and reduced teachers’ salaries over this period, both measures that push down the salary cost of teachers.
In some countries and economies, the cost was mostly pushed down by larger average class sizes – in Portugal,
for example, average class size increased by 17% in this period – and in others the cost was mostly pushed
down by lower teachers’ salaries – in England (United Kingdom), teachers’ salaries decreased by 10%.
The opposite trend is found in countries in the bottom-right quadrant, which reduced average class sizes and
increased teachers’ salaries, both measures that increase the salary cost of teachers. Once again, the size of
the change in each variable differs across countries. Between 2005 and 2017, teachers’ salaries increased by
nearly 40% in Luxembourg, while average class sizes fell by nearly 30% in Korea.
EDUCATION AT A GLANCE 2019 © OECD 2019

C7. WHICH FACTORS INFLUENCE TEACHERS' SALARY COST?  349

It is interesting to observe countries that had a similar evolution in one of the factors, but followed a very different
path for the other. For example, between 2005 and 2017, both Austria and Hungary increased teachers’ salaries
by about 9%. However, during the same period, Hungary also increased average class sizes by 10%, thus
offsetting some of the additional cost of higher salaries, while Austria reduced average class sizes by about 8%,
thus increasing the salary cost of teachers even more.
Smaller class sizes are often seen as beneficial, but the evidence regarding their impact on student learning is
mixed. Results from the latest Programme for International Student Assessment (PISA) show that students in
larger classes have higher scores in science on average across OECD countries (OECD, 2016[3]). Other research
has found that smaller class sizes may be beneficial in some cases, such as for students from disadvantaged
backgrounds who may need more individualised attention (Dynarski, Hyman and Schanzenbach, 2013[4]). Given
that reducing class size is a costly measure (Box C7.2), it is important to compare its impact with other possible
interventions (OECD, 2016[1]).

Box C7.2. What might be the trade-offs of decreasing class size by one student?
This indicator assesses the impact of four factors (teachers’ salaries, instruction time, teaching time and
theoretical 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 are the potential trade-offs among the other factors which
would compensate for a smaller class size? More specifically, by how much would salaries or instruction time
have to fall, or teaching time have to increase, in order to maintain the same salary cost?
Table C7.a presents the simulation results for decreasing the theoretical class size by one student. For
each factor, the value is calculated keeping everything else constant. For example, in primary e ducation in
Australia, in order to reduce the theoretical class size by one student and keep the salary cost per student
constant, teachers’ salaries would have to fall by USD 3 600, annual instruction time would have to fall by
57 hours, or annual teaching time would have to increase by 53 hours. Any one of these trade-offs would
compensate for the additional cost of the smaller class size, without any change to the total salary cost of
teachers per student.
These results emphasise the fact that reducing class sizes, by as little as one student, comes with a price tag.
Indeed, class sizes have been decreasing in several OECD countries over recent years (see Indicator D2),
although often as a result of demographic changes rather than of active policy choices. Class sizes tend to
fall when student enrolment falls because of the political, economic and organisational challenges of
simultaneously reducing the number of teachers. However, in the long term, not reducing the teaching
workforce is in itself a policy choice that will keep classes smaller. Table C7.a shows that the price of smaller
class sizes can either be reflected in higher salary costs, 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 hours 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 for one factor at a time. In reality, trade-offs will often consist of changes
in several factors at the same time. Moreover, important regional variations, not captured by this indicator,
may require specific policies that would not necessarily be reflected in the national averages. Rather, 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 size of the potential trade-offs across the four factors assessed in this
indicator.

EDUCATION AT A GLANCE 2019 © OECD 2019

350  C7. WHICH FACTORS INFLUENCE TEACHERS' SALARY COST?

Table C7.a. Keeping salary cost constant, what might be the trade-offs of decreasing class size by one
student? (2017)
Trade-offs of decreasing theoretical class size in primary education, public institutions only

Note: Results for teachers' statutory salaries are rounded to the nearest hundred. 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 the 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 (2019), Table C7.5a, available on line. See Source section for more information and Annex 3 for notes
(https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933979576

EDUCATION AT A GLANCE 2019 © OECD 2019

C7. WHICH FACTORS INFLUENCE TEACHERS' SALARY COST?  351

As observed in Figure C7.3, one alternative measure is to increase teacher salaries. Evidence from PISA points
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,
attracting good candidates to the teaching profession and retaining the effective ones is not just a matter of raising
salaries. Other factors include the quality of training before and after entering the profession and the relationship
between teachers and society.

Figure C7.3. Index of change in teachers' salaries and in average class size in primary education between
2005 and 2017
Public institutions only

Note: The source for the average class size is the UOE CLASS questionnaire. The average class size does not correspond to the theoretical class size
(please see Definitions section).
1. Teachers' statutory salaries based on minimum qualifications instead of typical qualifications.
Source: OECD (2019), Education at a Glance database, http://stats.oecd.org. See Source section for more information and Annex 3 for notes
(https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933979557

Definitions
Average class size refers to number of students enrolled in a given education level divided by the number of
classes. It measures the average number of students that are grouped together in classrooms (see Indicator D2).
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 (see Indicator D1).

EDUCATION AT A GLANCE 2019 © OECD 2019

352  C7. WHICH FACTORS INFLUENCE TEACHERS' SALARY COST?
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 (see Indicator D4).
Teachers' salary refers to the annual statutory salary of teachers after 15 years of experience, converted to USD
using purchasing power parity (PPP) for private consumption (see Indicator D3).
Theoretical class size refers to the theoretical size of classes given the statutory – or theoretical – values of
instruction and teaching time and the student teacher ratio (see Methodology section). It does not reflect the
actual average class size in countries.

Methodology
The salary cost of teachers per student (SCS) is calculated as:
𝑆𝐶𝑆 = 𝑇𝑒𝑎𝑐ℎ𝑒𝑟 𝑠𝑎𝑙𝑎𝑟𝑦 ∗ 𝐼𝑛𝑠𝑡𝑟𝑢𝑐𝑡𝑖𝑜𝑛 𝑡𝑖𝑚𝑒 ∗

1
1
∗
𝑇𝑒𝑎𝑐ℎ𝑖𝑛𝑔 𝑡𝑖𝑚𝑒 𝑇ℎ𝑒𝑜𝑟𝑒𝑡𝑖𝑐𝑎𝑙 𝐶𝑙𝑎𝑠𝑠 𝑆𝑖𝑧𝑒

Where theoretical class size is calculated as:
𝑇ℎ𝑒𝑜𝑟𝑒𝑡𝑖𝑐𝑎𝑙 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 [5]). 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[6]) for
more information and Annex 3 for country-specific notes (http://dx.doi.org/10.1787/eag-2018-36-en).

Source
Data referring to the 2017 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 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.

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.

[4]

EDUCATION AT A GLANCE 2019 © OECD 2019

C7. WHICH FACTORS INFLUENCE TEACHERS' SALARY COST?  353

OECD (2018), Education at a Glance 2018: OECD Indicators, OECD Publishing, Paris,
https://dx.doi.org/10.1787/eag-2018-en.

[2]

OECD (2018), OECD Handbook for Internationally Comparative Education Statistics 2018: Concepts,
Standards, Definitions and Classifications, OECD Publishing, Paris,
https://dx.doi.org/10.1787/9789264304444-en.

[6]

OECD (2016), PISA 2015 Results (Volume I): Excellence and Equity in Education, PISA, OECD
Publishing, Paris, https://dx.doi.org/10.1787/9789264266490-en.

[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,
http://www.education.gouv.qc.ca/fileadmin/site_web/documents/PSG/statistiques_info_decisionnelle
/bulletin_29.pdf.

[5]

Indicator C7 Tables
Table C7.1

Salary cost of teachers per student, by level of education (2017)

Table C7.2

Contribution of various factors to salary cost of teachers per student in primary education
(2017)

Table C7.3

Contribution of various factors to salary cost of teachers per student in lower secondary
education (2017)

WEB Table C7.4 Contribution of various factors to salary cost of teachers per student in general programmes
of upper secondary education (2017)
WEB Table C7.5a Factors used to compute the salary cost of teachers per student in public institutions, in
primary education (2017)
WEB Table C7.5b Factors used to compute the salary cost of teachers per student in public institutions, in lower
secondary education (2017)
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 (2017)
Cut-off date for the data: 19 July 2019. 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.
StatLink: https://doi.org/10.1787/888933981172

EDUCATION AT A GLANCE 2019 © OECD 2019

354  C7. WHICH FACTORS INFLUENCE TEACHERS' SALARY COST?
Table C7.1. Salary cost of teachers per student, by level of education (2017)
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

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 the 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. 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.
3. The OECD average only includes countries and economies with data for all factors used to calculate salary cost.
Source: OECD (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888933979462

EDUCATION AT A GLANCE 2019 © OECD 2019

C7. WHICH FACTORS INFLUENCE TEACHERS' SALARY COST?  355

Table C7.2. Contribution of various factors to salary cost of teachers per student in primary education (2017)
In equivalent USD, converted using PPPs for private consumption

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 the 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 (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888933979481

EDUCATION AT A GLANCE 2019 © OECD 2019

356  C7. WHICH FACTORS INFLUENCE TEACHERS' SALARY COST?
Table C7.3. Contribution of various factors to salary cost of teachers per student in lower secondary education (2017)
In equivalent USD, converted using PPPs for private consumption

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 the 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 (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888933979500

EDUCATION AT A GLANCE 2019 © OECD 2019

 357

Chapter D. Teachers, the learning
environment and the organisation of
schools

Indicator D1 How much time do students spend in the classroom?
StatLink https://doi.org/10.1787/888933981191
Indicator D2 What is the student-teacher ratio and how big are classes?
StatLink https://doi.org/10.1787/888933981210
Indicator D3 How much are teachers and school heads paid?
StatLink https://doi.org/10.1787/888933981229
Indicator D4 How much time do teachers spend teaching?
StatLink https://doi.org/10.1787/888933981248
Indicator D5 Who are the teachers?
StatLink https://doi.org/10.1787/888933981267
Indicator D6 What are the admission systems for tertiary education?
StatLink https://doi.org/10.1787/888933981286

EDUCATION AT A GLANCE 2019 © OECD 2019

358  D1. HOW MUCH TIME DO STUDENTS SPEND IN THE CLASSROOM?

Indicator D1. How much time do students spend
in the classroom?
Highlights


Students in OECD countries and economies receive an average of 7 590 hours of compulsory
instruction during their primary and lower secondary education, ranging from 5 973 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 averages
799 hours per year, while lower secondary students receive an average of 120 more hours of
compulsory education per year than primary students (919 hours).



On average across OECD countries and economies, instruction in reading, writing and literature;
mathematics; and the arts represents 52% of compulsory instruction time for primary school students,
and instruction in reading, writing and literature; second and other languages; and mathematics
represents about 42% of compulsory instruction time for lower secondary school students.

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 the 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.

Other findings


The proportion of the compulsory curriculum for primary students devoted to reading, writing and
literature ranges from 18% in Portugal 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 33% 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 about 11% in Hungary,
Ireland and Korea to 16% in Chile, Latvia and the Russian Federation (and 20% in Italy, including
natural sciences).



Except for a few countries where the compulsory curriculum is mostly devoted to flexible subjects, in
OECD countries and economies, an average of 1% or less of compulsory instruction time for primary
students and lower secondary students is devoted to subjects with a flexible timetable. An average of

EDUCATION AT A GLANCE 2019 © OECD 2019

D1. HOW MUCH TIME DO STUDENTS SPEND IN THE CLASSROOM?  359

5% of compulsory instruction time both at the primary level and at the lower secondary level is devoted
to flexible subjects chosen by schools.


In one-quarter 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).

Figure D1.1. Compulsory instruction time in general education (2019)
Primary and lower secondary education, in public institutions

1. Estimated number of hours by level of education based on the average number of hours per year, as for some subjects, the allocation of instruction
time across multiple levels is flexible.
2. Year of reference 2018.
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 (2019), Table D1.1. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933979671

EDUCATION AT A GLANCE 2019 © OECD 2019

360  D1. HOW MUCH TIME DO STUDENTS SPEND IN THE CLASSROOM?

Analysis
Compulsory general education
Both annual instruction time and the length of compulsory education have an impact on the total instruction time
during compulsory education. In some countries, the duration of compulsory education is shorter, and students
could bear a heavier annual 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 the age of 6. In most other countries, students are not required to start until they are 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 these instruction days, countries also vary in the way they organise recess
and breaks (see Box D1.2 in OECD (2018[1])).

Box D1.1. Organisation of breaks within in the school year in lower secondary education (2019)
The length of the school year varies greatly between countries, implying that there is also wide variation in the
number of weeks students 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 breaks at the end of
the school year at lower secondary level are two weeks shorter than primary level in Greece, one week shorter
in the Russian Federation, one week longer in Iceland, Israel and Portugal, and three weeks longer in Ireland
(see Box D1.1 in OECD (2018[1]) for more information on breaks within the school year at the primary level).
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 the three zones of 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 lower
secondary education, and excluding Colombia, the break between two successive years varies from a
minimum of 5 weeks in some subnational entities in Switzerland up to 13 weeks in Chile (11-13 weeks), Italy

EDUCATION AT A GLANCE 2019 © OECD 2019

D1. HOW MUCH TIME DO STUDENTS SPEND IN THE CLASSROOM?  361

(12-13 weeks), Latvia, Lithuania, Portugal (12-13 weeks), 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 (see Figure D1.a).
In addition to this long break, students usually have three to four other shorter holiday periods during the school
year. 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.
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 an approximately two-week break (in the northern hemisphere), or
the end of the school year in the southern hemisphere. 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 Denmark, 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), Luxembourg
and Poland alternate one-week and two-week breaks during the school year.

Figure D1.a. School breaks in compulsory general lower secondary education (2019)

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.
2. Data for Nordrhein-Westfalen. The length of breaks for Germany are indicative only as variation between and among jurisdictions can occur.
Countries and economies are ranked in descending order of the number of weeks of breaks during the school year.
Source: OECD (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933979728

EDUCATION AT A GLANCE 2019 © OECD 2019

362  D1. HOW MUCH TIME DO STUDENTS SPEND IN THE CLASSROOM?
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 4 568 hours of compulsory instruction during
primary school and 3 022 hours during lower secondary education. While the total compulsory instruction time
for primary and lower secondary students averages 7 590 hours (in 9 years on average) across OECD countries
and economies, formal instruction-time requirements range from 5 973 hours in Hungary (in 8 years) to
11 000 hours in Australia (in 11 years) (Figure D1.1). In England (United Kingdom), New Zealand and Scotland
(United Kingdom), the regulations do not prescribe the 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
variations in instruction time at the subnational level, see Box D1.3).

Box D1.2. Comparability of data on instruction time (2019)
Data on (intended) instruction time as established in public regulations are gathered through a data collection
exercise based on agreed international standards and methodologies to ensure the comparability of the data
reported. However, comparability issues can arise not just because of deviations from these guidelines, but
due to differences in the way instruction time is defined in official documents.

Type of information on instruction time
Intended instruction time often refers to the minimum required instruction time, but it can also refer to
recommended instruction time. Both may imply that schools or local levels have some flexibility to adjust this
number of hours of instruction. In some countries, the data can refer to a mix of different types of data. For
example, Denmark reports minimum instruction time for three subjects (reading, writing and literature,
mathematics and history) for each grade, but recommended instruction time for other subjects.
Whereas intended instruction time is usually similar across schools throughout the whole country, in some
countries it is a weighted average based on various regulations. This is the case when intended instruction
times vary for different groups of the population (e.g. in Latvia and Lithuania, for schools for minority groups),
or for different tracks within general programmes (e.g. in Chile for tracks with or without Jornada Escolar
Completa, and in Italy for various upper secondary programmes in licei) or between subnational entities (often
the case in federal countries such as Australia, Canada, Germany and the United States).

Number of days of instruction per year
Most countries regulate the length of a school year as a number of days of instruction (either a number of
days per school year, or a number of days per week combined with a number of weeks per year). These
numbers do not take into account the fact that the (statutory) length of one school day may vary. For example
in Austria, Denmark and Korea, the number of lessons per week and therefore the length of the school day
varies from one grade to another within primary level. Few countries take into account different lengths of the
school day to determine the number of days of instruction per year. In the Flemish Community of Belgium and
France, 4.5 days of instruction per week are considered, as students do not go to school on Wednesday
afternoon. This may result in fewer days of instruction compared to countries with no differentiation of the
length of the school day across the week or year.

Number of hours of instruction.
Instruction time is displayed in hours (of 60 minutes) to ensure the comparability of data across countries.
However, official documents can define instruction time based on other units of time. About one-half of the

EDUCATION AT A GLANCE 2019 © OECD 2019

D1. HOW MUCH TIME DO STUDENTS SPEND IN THE CLASSROOM?  363

countries define instruction time as a number of periods of instruction and/or for a different reference unit of
time than the school year. Converting this information into hours per year may raise difficulties. In some
countries, the length of a period of instruction is not uniform across the country. In this case, an average (for
example in Costa Rica and Greece) or the most prevalent value (in Latvia) is used to convert periods into
hours of instruction. About one-third of countries and economies also define instruction time per week rather
than per school year, so the weekly values are multiplied by the defined or estimated number of weeks in the
school year.
To ensure the comparability of hours of instruction, breaks between period/sessions are excluded. However,
in some countries, breaks with educational activities are included in the prescribed intended instruction time,
although they are excluded from reported intended instruction time to comply with the international definition.
For example in Denmark, breaks are a part of regulated compulsory instruction time in both primary and lower
secondary education. Similarly, in Spain, primary education legislations in autonomous communities includes
breaks in compulsory instruction time (87.5 hours per year).
For more information on comparability issues, see notes for specific countries in Annex 3.
Instruction may also occur outside compulsory school hours and outside the classroom or school. In some
countries, secondary school students are encouraged to take after-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 D1.2 in OECD (2017[2])). These lessons can be financed
through public funds or by students and their families (see Box D1.1 in OECD (2011[3])).
This indicator on compulsory instruction time only captures the time spent by students in formal classroom
settings (as established in public regulations). This is only a part of the total time students spend receiving
instruction. 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. Subnational variation in compulsory instruction time at the primary and lower secondary levels
Compulsory instruction time varies across OECD countries at all levels of education. It can also vary
significantly among subnational entities within a single county, especially in federal countries where instruction
time requirements may be defined at the subnational level. These variations are illustrated by the subnational
data on compulsory instruction time at the primary and lower secondary levels in 2019 provided by four
countries (Belgium, Canada, the United Kingdom and the United States).
At the primary level, Belgium has the smallest variation in the total number of compulsory instruction hours
between subnational entities: the total number of compulsory instruction hours varies by less than 1%
(40 hours) between the French and Flemish communities (4 956 hours compared with 4 916 hours). The
difference between subnational entities exceeds 6% (342 hours) in the United Kingdom (Wales and Northern
Ireland only). In Canada, the variation in intended instruction hours (compulsory and non-compulsory hours)
between subnational entities reaches 15% (745 hours). It is even larger in the United States, where the
difference between the lowest and highest total compulsory instruction hours reaches 3 240 hours.
The same general pattern is observed at the lower secondary level, although all four countries have smaller
subnational variations at this level than at the primary level. The total number of compulsory instruction hours
at the lower secondary level varies very slightly between subnational entities in Belgium (2 hours). The
variation exceeds 3% (about 86 hours) in the United Kingdom (Wales and Northern Ireland only). In Canada,
intended instruction time varies by 13% (353 hours) across subnational entities. In the United States, the
difference between the subnational entities reaches 1 620 hours.

EDUCATION AT A GLANCE 2019 © OECD 2019

364  D1. HOW MUCH TIME DO STUDENTS SPEND IN THE CLASSROOM?
The extent of these variations may be related to differences across subnational entities in the number of annual
days of instruction at both the primary and lower secondary levels. In 2019, the number of annual days of
compulsory instruction varied by 10 days across subnational entities in Canada (from 180 to 190 days), in
Belgium by 19 days at the primary level (from 158 to 177 days) and 17 days at the lower secondary level (from
160 to 177 days), and by 26 days in the United States (from 160 to 186 days). In contrast, there is no difference
in the number of annual days of instruction across subnational entities in the United Kingdom (190 days).
Source: Education at a Glance Database. http://stats.oecd.org.

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 the same (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 (see Box D1.2).

Figure D1.2a. Instruction time per subject in primary education (2019)
As a percentage of total compulsory instruction time, in public institutions

1. Year of reference 2018.
2. Excludes England (United Kingdom), Flemish Comm. (Belgium), French Comm. (Belgium), Italy, the Netherlands and Portugal.
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 (2019), Table D1.3a. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933979690
EDUCATION AT A GLANCE 2019 © OECD 2019

D1. HOW MUCH TIME DO STUDENTS SPEND IN THE CLASSROOM?  365

Instruction time per subject
On average across OECD countries, primary students spend 52% 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 about 19% of the compulsory instruction time on average across
OECD countries (Table D1.3a and Figure D1.2a).
At the lower secondary level, on average across OECD countries and economies, about 42% of the compulsory
curriculum is composed of three subjects: reading, writing and literature (15%); second and other languages
(15%); and mathematics (13%). On average, an additional 12% of the compulsory curriculum is devoted to natural
sciences, 11% 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 (about 12%) of the non-flexible compulsory curriculum for students at
this level of education (Table D1.3b and Figure D1.2b).

Figure D1.2b. Instruction time per subject in general lower secondary education (2019)
As a percentage of total compulsory instruction time, in public institutions

1. Reading, writing and literature includes social studies. Mathematics includes natural sciences.
2. Excludes England (United Kingdom), Flemish Comm. (Belgium), Ireland, the Netherlands and Portugal.
3. Natural sciences includes information and communication technologies and practical and vocational skills.
4. Year of reference 2018.
Countries and economies are ranked in descending order of the proportion of instruction hours devoted to reading, writing and literature.
Source: OECD (2019), Table D1.3b. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933979709

EDUCATION AT A GLANCE 2019 © OECD 2019

366  D1. HOW MUCH TIME DO STUDENTS SPEND IN THE CLASSROOM?
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 15%,
and instruction in mathematics drops from 17% of compulsory instruction time to 13%. Conversely, instruction in
natural sciences climbs from 7% of the compulsory curriculum to 12%, and in social studies from 6% to 11%,
while instruction in other languages (second and others) climbs from 6% to 15%. 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, Luxembourg and Sweden (Table D1.3a
and b).
At the lower secondary level, there is substantial variation in how countries allocate time to 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, Japan and Sweden,
but more than 25% of compulsory instruction time in Greece and Italy (in Italy, this also includes time devoted to
social studies). In Ireland, reading, writing and literature are taught in two national languages, and therefore the
combined instruction time of two languages could reach about 15% of the total compulsory instruction time.
Compulsory instruction time devoted to second and other languages also varies widely between countries.
Second-language instruction accounts for less than 7% of compulsory instruction time in Greece and Ireland and
13% or more in the French Community of Belgium, Iceland and Japan. In addition, more than 4 out of 10 countries
with available data allocate some compulsory instruction time for lower secondary students to instruction in
another language in addition to a second language.
As the difference between the primary and lower secondary levels shows, 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 is devoted to reading, writing and literature for 7-year-olds, 19% for 11-year-olds and 12% for
15-year-olds. In contrast, while an average of 3% of instruction time for 7-year-olds is devoted to a second
language, 10% of instruction time for 11-year-olds is spent studying a second language and 1% studying other
languages, while for 15-year-olds, 9% of instruction time is devoted to a second language and 5% to other
languages. The share of instruction time dedicated to natural sciences increases from 6% for 7-year-olds to 9%
for 11-year-olds and 12% for 15-year-olds, while instruction time in social studies increases from 5% for 7-yearolds to 9% for 11-year-olds and 10% for 15-year-olds. The portion of instruction time dedicated to the arts
decreases from 11% for 7-year olds and 9% for 11-year-olds to 4% for 15-year-olds, and similarly the portion for
the physical education declines from 10% for 7-year-olds and 8% for 11-year-olds 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 one-quarter 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 (Table D1.2).
Setting compulsory subjects within a flexible timetable is the practice for most subjects in a few countries. In
Portugal, more than half of the compulsory curriculum at the primary level is organised within a flexible timetable,
and the proportion exceeds 80% in the Flemish and French communities of Belgium and Italy. In England
(United Kingdom) and the Netherlands, the whole curriculum at the primary level is organised as a flexible
timetable. At the lower secondary level, similar patterns are found in the Flemish Community of Belgium, England
(United Kingdom), the Netherlands and Portugal. In these countries and economies, compulsory subjects and/or
total instruction time are specified, but not how time should be allocated to each subject. Local authorities, schools
and/or teachers are free to decide how much time to allocate to each compulsory subject. In Scotland
EDUCATION AT A GLANCE 2019 © OECD 2019

D1. HOW MUCH TIME DO STUDENTS SPEND IN THE CLASSROOM?  367

(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 and economies, compulsory subjects with flexible timetables account for less than 1%
of the compulsory instruction time at both primary and lower secondary levels, even if they are 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, 5%
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, about 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 (60% at lower
secondary level) and Spain (23% at lower secondary level). In Australia, Iceland, Norway and Turkey, 15-20% of
compulsory instruction time is allocated to subjects chosen by lower secondary students (Table 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 4% of the total compulsory
instruction time for both primary students and 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, 14% 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
(Table 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 students 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.

EDUCATION AT A GLANCE 2019 © OECD 2019

368  D1. HOW MUCH TIME DO STUDENTS SPEND IN THE CLASSROOM?
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/afterschool activities that are formal parts of the compulsory programme. Instruction time excludes breaks between
classes or 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 that public schools
must offer on top of the compulsory instruction time, but which is not mandatory for all students. Subjects can
vary from school to school or from region to region and take the form of optional subjects. Additional activities
before/after classes offered by the school are not per se part of the non-compulsory curriculum, for instance, if
there is no obligation upon public schools to provide this instruction time or it is not part of the official curricula.
In particular, non-compulsory education excludes morning care classes or after-school care classes, even if they
are officially regulated.

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[4])).
The indicator also illustrates how minimum (and/or recommended) instruction hours are allocated across different
curricular areas. It shows the intended net hours of instruction for those grades that are part of compulsory fulltime 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 assuming equal
distribution of the total number of instruction hours between grades.
For more information please see the OECD Handbook for Internationally Comparable Education Statistics
(OECD, 2018[5]) and Annex 3 for country-specific notes (https://doi.org/10.1787/f8d7880d-en).

EDUCATION AT A GLANCE 2019 © OECD 2019

D1. HOW MUCH TIME DO STUDENTS SPEND IN THE CLASSROOM?  369

Source
Data on instruction time are from the 2018 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 2018/19.
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 2018: OECD Indicators, OECD Publishing, Paris,
https://dx.doi.org/10.1787/eag-2018-en.

[1]

OECD (2018), OECD Handbook for Internationally Comparative Education Statistics 2018: Concepts,
Standards, Definitions and Classifications, OECD Publishing, Paris,
https://dx.doi.org/10.1787/9789264304444-en.

[5]

OECD (2017), Education at a Glance 2017: OECD Indicators, OECD Publishing, Paris,
https://dx.doi.org/10.1787/eag-2017-en.

[2]

OECD (2011), Education at a Glance 2011: OECD Indicators, OECD Publishing, Paris,
https://dx.doi.org/10.1787/eag-2011-en.

[3]

OECD (2007), Education at a Glance 2007: OECD Indicators, OECD Publishing, Paris,
https://dx.doi.org/10.1787/eag-2007-en.

[4]

Indicator D1 Tables
Table D1.1.

Instruction time in compulsory general education (2019)

Table D1.2

Organisation of compulsory general education (2019)

Table D1.3a

Instruction time per subject in primary education (2019)

Table D1.3b

Instruction time per subject in general lower secondary education (2019)

WEB Table D1.4

Instruction time in compulsory general education, by age (2019)

WEB Table D1.5a Instruction time per subject for 6-year-olds (2019)
WEB Table D1.5b Instruction time per subject for 7-year-olds (2019)
WEB Table D1.5c Instruction time per subject for 8-year-olds (2019)
WEB Table D1.5d Instruction time per subject for 9-year-olds (2019)

EDUCATION AT A GLANCE 2019 © OECD 2019

370  D1. HOW MUCH TIME DO STUDENTS SPEND IN THE CLASSROOM?
WEB Table D1.5e Instruction time per subject for 10-year-olds (2019)
WEB Table D1.5f

Instruction time per subject for 11-year-olds (2019)

WEB Table D1.5g Instruction time per subject for 12-year-olds (2019)
WEB Table D1.5h Instruction time per subject for 13-year-olds (2019)
WEB Table D1.5i

Instruction time per subject for 14-year-olds (2019)

WEB Table D1.5j. Instruction time per subject for 15-year-olds (2019)
WEB Table D1.5k. Instruction time per subject for 16-year-olds (2019)
WEB Table D1.5l

Instruction time per subject for 17-year-olds (2019)

Cut-off date for the data: 19 July 2019. 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.
StatLink: https://doi.org/10.1787/888933981191

EDUCATION AT A GLANCE 2019 © OECD 2019

D1. HOW MUCH TIME DO STUDENTS SPEND IN THE CLASSROOM?  371

Table D1.1. Instruction time in compulsory general education1 (2019)
By level of education, in public institutions

Note: Columns showing instruction time combined for compulsory primary and lower secondary education (i.e. Columns 15-18) and compulsory upper secondary education (i.e. Columns 1925) 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 for some subjects, the allocation of instruction time across multiple levels is flexible.
3. Year of reference 2018.
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 (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888933979595
EDUCATION AT A GLANCE 2019 © OECD 2019

372  D1. HOW MUCH TIME DO STUDENTS SPEND IN THE CLASSROOM?
Table D1.2. Organisation of compulsory general education1 (2019)
By level of education, in public institutions

Note: Students go to school five days a week (six days in Israel and secondary education in Italy). In some countries, the statutory length of the school days varies within
the school week. Columns showing the organisation of compulsory upper secondary education (i.e. Columns 9-12) 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. For some subjects, allocation of instruction time across multiple levels of education is flexible.
3. Year of reference 2018.
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 (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888933979614
EDUCATION AT A GLANCE 2019 © OECD 2019

D1. HOW MUCH TIME DO STUDENTS SPEND IN THE CLASSROOM?  373

Table D1.3a. Instruction time per subject in primary education (2019)
As a percentage of total compulsory instruction time, in public institutions

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. For some subjects, allocation of instruction time across multiple levels of education is flexible.
2. Year of reference 2018.
3. The second language of instruction includes other national languages taught.
4. England (United Kingdom), Flemish Comm. (Belgium), French Comm. (Belgium), Italy, the Netherlands and Portugal 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 (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888933979633
EDUCATION AT A GLANCE 2019 © OECD 2019

374  D1. HOW MUCH TIME DO STUDENTS SPEND IN THE CLASSROOM?
Table D1.3b. Instruction time per subject in general lower secondary education (2019)
As a percentage of total compulsory instruction time, in public institutions

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. For some subjects, allocation of instruction time across multiple levels of education is flexible.
3. Year of reference 2018.
4. The second language of instruction includes other national languages taught.
5. England (United Kingdom), Flemish Comm. (Belgium), Ireland, the Netherlands and Portugal are not included in the averages.
6. Instruction time for other languages is included in instruction time for the second language for grade 9.
Source: OECD (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888933979652
EDUCATION AT A GLANCE 2019 © OECD 2019

376  D2. WHAT IS THE STUDENT-TEACHER RATIO AND HOW BIG ARE CLASSES?

Indicator D2. What is the student-teacher ratio
and how big are classes?
Highlights


On average across OECD countries, there are 15 students for every teacher in primary education and
13 students per teacher in lower secondary education. The average school class has 21 students in
primary education and 23 students in lower secondary education.



At tertiary level, the student-teacher ratios in public and private institutions are similar on average
across OECD countries, with about 15 students per teaching staff member in public institutions and
16 students per teaching staff member in private institutions. The difference in student-teacher ratios
across public and private institutions is larger in partner countries.



The average primary school class in OECD countries in 2017 had 21 students in public institutions
and 20 students in private institutions. The difference in class size between public and private primary
institutions varies substantially across OECD countries.

Figure D2.1. Ratio of students to teaching staff in tertiary education, by type of institution (2017)

1. Tertiary includes programmes outside tertiary level - see Annex 3 for further details.
Countries are ranked in descending order of the ratio of students to teaching staff in tertiary public institutions.
Source: OECD/UIS/Eurostat (2019), Education at a Glance Database, http://stats.oecd.org/. See Source section for more information and Annex 3
for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933979804

EDUCATION AT A GLANCE 2019 © OECD 2019

D2. WHAT IS THE STUDENT-TEACHER RATIO AND HOW BIG ARE CLASSES?  377

Context
Class sizes and student-teacher ratios are much-discussed aspects of education and are among the
determinants of the demand for teachers, along with students’ instruction time (see Indicator D1), and
teachers’ working time and the division of teachers’ time between teaching and other duties (see Indicator D4).
Together with teachers’ salaries (see Indicator D3), age distribution (see Indicator D5) and instruction time
(see Indicator C7), 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 M. Valdenaire, 2006[1]), overall evidence of the effect of class size
on student performance is mixed (Fredriksson, Öckert and Oosterbeek, 2013[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 measures such as 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.

Other findings


Across OECD countries, the numbers of teachers and students have grown at an average annual rate
of 1% between 2005 and 2017.



On average across OECD countries, the student-teacher ratio in lower secondary education is slightly
lower in private institutions than in public institutions. The difference is most striking in Mexico, where
at the lower secondary level there are more than 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 per
class in Costa Rica to 31 students per class in Chile.

EDUCATION AT A GLANCE 2019 © OECD 2019

378  D2. WHAT IS THE STUDENT-TEACHER RATIO AND HOW BIG ARE CLASSES?

Analysis
Student-teacher ratios
The ratio of students to teaching staff compares the number of students (full-time equivalents) to the number of
teachers (full-time equivalents) at a given level of education and in similar types of institutions. This ratio does
not take into account the amount of instruction time students have 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).
On average across OECD countries, there are 15 students for every teacher at primary level. The student-teacher
ratio ranges from 10 to 1 in Norway to 27 to 1 in Mexico. It is even higher in some partner countries, reaching
33 to 1 in India (Table D2.2).
On average, there are fewer students per teacher at secondary level (13 students per teacher) than at primary
level. 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 (teaching time decreases with the level of education as teacher
specialisation increases). There are also wider variations across countries at secondary level than at primary
level, from 8 students per teacher in Lithuania to 29 students per teacher in Mexico.
On average, the student-teacher ratio is about the same in lower secondary and upper secondary education
(13 students per teacher). In some countries, however, it varies widely between these two levels. This is the case
in Finland, where there are at least twice as many students per teacher at the upper secondary level than at the
lower secondary level.
At the upper secondary level, the difference in student-teacher ratios between general and vocational
programmes also varies across countries. On average, the ratio of students to teaching staff in upper secondary
vocational and general programmes are similar (14 to 1 and 13 to 1). 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 there are countries where it is lower. In Latvia, there are twice as many students per teacher in
vocational programmes (17 to 1) as general programmes (8 to 1). In the United Kingdom, there are 25 students
per teacher in vocational programmes and only 14 per teacher in general programmes. These large differences
may be due to the fact that in some countries, vocational programmes are significantly work based, so vocational
students spend considerable time outside the school. As a result, schools 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 OECD and partner countries with available data, the difference is
reversed: there are twice as many students per teacher in general programmes (26 to 1) as in vocational
programmes (13 to 1). In this case, this may reflect the fact that students in vocational education typically need
greater instructor attention, especially as they have access to more sophisticated equipment. Vocational students
require more careful supervision as skill specificity rises. This may in turn have important implications for 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, there are on average 16 students per teaching staff member. The student-teacher ratio
ranges from 9 to 1 in Norway to over 25 to 1 in Colombia, Indonesia and Turkey. The difference in studentteaching staff ratios across short-cycle tertiary and bachelor’s, master’s, doctoral or equivalent level varies across
countries with available data. These results should be interpreted with caution, however, as the student-teacher
ratio remains a limited measure of the level of teaching resources at tertiary level (Box D2.2). Moreover, the
relatively low enrolment in short-cycle tertiary in some countries limits comparability across tertiary levels
(see Indicator B1).

EDUCATION AT A GLANCE 2019 © OECD 2019

D2. WHAT IS THE STUDENT-TEACHER RATIO AND HOW BIG ARE CLASSES?  379

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 made by dividing the number of students by the number of classes.
The student-teacher ratio, as presented in Tables D2.2 and D2.3, is calculated by dividing the number of fulltime 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. Student-teacher
ratios provide information on the level of teaching resources available in a country, whereas class sizes
measure 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
may 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 students can be taught in
smaller classes (see Indicator C7).

Student-teacher ratios in public and private institutions
On average across OECD countries with available data, the ratios of students to teaching staff are slightly higher
in public institutions than in private institutions at the lower secondary level and about the same at upper
secondary level (Table D2.3).
At lower secondary level, the largest difference between public and private institutions is found in Mexico, where
there are more than twice as many students per teacher in public institutions as in private institutions. However,
only 10% of lower secondary students are enrolled in private institutions in Mexico (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 Chile, where the student-teacher ratio is 16 to 1 in public
institutions, compared to 24 to 1 in private institutions (Table D2.3). In Chile, almost 60% of lower secondary
students are enrolled in private institutions (Education at a Glance Database).
At the upper secondary level, the student-teacher ratio is larger in public institutions than in private institutions in
14 countries, smaller in public institutions in 15 countries, and similar for both sectors in 4 countries. Mexico is
once more the country with the largest difference in student-teacher ratios at this level, with 25 students per
teacher in public institutions and 16 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
student-teacher ratio is slightly lower than the ratio in general programmes (Education at a Glance Database and
Table D2.2).
At tertiary level, there is little difference between public and private institutions on average across OECD
countries, with 15 students per teaching staff member in public institutions and 16 in private institutions (Figure
D2.1). In 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 (see Indicator B1). The difference between public and private institutions is larger in some
partner countries: in India, there are over twice as many students per teachers in public institutions (42 to 1) as
in private institutions (19 to 1). The largest difference in student-teacher ratio between public and private
EDUCATION AT A GLANCE 2019 © OECD 2019

380  D2. WHAT IS THE STUDENT-TEACHER RATIO AND HOW BIG ARE CLASSES?
institutions is in Brazil where, interestingly, the ratio is much higher in private institutions, which enrol 73% of
tertiary students, than in public institutions, which are more selective. In Brazil, students thus face either a
performance barrier to accessing free but highly selective public institutions, or a financial barrier to accessing
private institutions, which could limit their opportunities and raises significant equity concerns (Figure D2.1).

Box D2.2. Calculating the student-teacher ratio in higher education
The student-teacher ratio measures the teaching resources that are available in a given country. When the
student-teacher ratio is low, students are more likely to receive more support and attention. However, at
tertiary level, the interpretation of this indicator is affected by the definition and function of academic staff.
Some may have limited teaching responsibilities and could for example spend most of their time doing
research. In such cases, the student-teacher ratio would not be representative of the level of support and
attention students receive in the classroom.
Currently the available data do not allow hours spent teaching to be distinguished from hours spent doing
research. Specifically, the UNESCO-UIS, OECD and Eurostat (UOE) manual defines academic staff as
personnel employed at the tertiary level of education whose primary assignment is instruction or research,
with no further distinction. Other authoritative sources on tertiary academic staff, including the Frascati Manual
(OECD, 2016[6]) and the European Tertiary Education Register (ETER[7]) also lack such distinction.
Eurydice’s 2017 report on academic staff at tertiary level across Europe (European
Commission/EACEA/Eurydice, 2017[8]) is one of the first attempts to map the different attributes of academic
staff onto a harmonised segmentation. The report draws on several data sources. It is based mainly on
qualitative data gathered from the Eurydice National Units and has been complemented by a range of
research reports and databases from other international organisations. In line with the UOE definition of
instructional staff, the data collection concentrated on tertiary staff primarily responsible for teaching and/or
research, including both academic staff and teaching/research aides. While this data collection did not
specifically consider the number of hours spent teaching and the number of hours spent doing research, it
included information on staff’s primary responsibilities, thus providing a first attempt to distinguish between
teaching and research.
Outside European countries, other OECD countries also collect data on the function of staff: instruction,
research, or a combination of both. However the definition of each differs across countries. For example,
Australia defines instruction staff as “teaching only” based on their formal job requirements. For these types
of staff, “work involves only teaching and associated activities […], or the management and leadership of
teaching staff and of staff who support teaching staff. There is no formal requirement that research be
undertaken” (Australian Government[9]). In contrast, the classification of instructional staff by function in
the United States is broader. Instructional staff includes faculty whose role is either primarily instructional or
instruction combined with research and/or public service (NCES National Center for Education Statistics,
2018[10]). Neither Canada nor New Zealand separate out instruction staff from research staff. In Korea,
instructors are only required for teaching, whereas professors usually have both teaching and research
responsibilities.
Overall, these attempts remain limited. Further efforts are needed to more accurately collect data on the
number of hours spent teaching and the number of hours spent doing research, in order to refine the
calculation of the student-teacher ratio in tertiary education.
The number of students per teacher remains an important concern, even though tertiary education may involve
more self-learning than primary and secondary education. Although student-teacher ratios are difficult to measure
at tertiary level, they could still shed some light on the level of available resources in higher education. In fact,

EDUCATION AT A GLANCE 2019 © OECD 2019

D2. WHAT IS THE STUDENT-TEACHER RATIO AND HOW BIG ARE CLASSES?  381

the student-teacher ratio is considered to be a proxy of quality in higher education (McDonald, 2013[11]), which
warrants efforts to improve the calculation of this indicator (Box D2.2).

Trends in the number of students and academic staff in tertiary education
Comparing the average annual growth rates of the numbers of tertiary students to the average annual growth
rates of the numbers of academic staff between 2005 and 2017 could shed light on the changes in human
resources over this period.
On average across OECD countries, the number of academic staff and students grew at an average annual rate
of 1% between 2005 and 2017. These averages, however, mask large disparities across countries. The largest
changes in the number of academic staff are found in Norway and Estonia: Norway recorded the highest average
annual growth rate in the number of teachers (+6%) and Estonia and Greece the lowest (-3%). The highest
average annual growth rate in the number of students is found in Mexico and the Netherlands (+5%) and the
lowest in Latvia (-4%; Figure D2.2).
In the majority of countries with available data, the number of academic staff and students have changed in a
similar way: both either increased or decreased between 2005 and 2017. However, the pace of change varies
widely. For example in Norway, the number of academic staff grew three times faster than the growth in the
number of students. In contrast, in Hungary and Lithuania, the decline in the number of students was at least
three times greater than the decline in the number of academic staff. In other countries, such as Finland and
Portugal, the pace of change was similar for students and academic staff. In Latvia, Korea, Poland and Slovenia,
however, the number of academic staff has on average increased every year, although the number of students
fell over the same period (Figure D2.2). This may reflect the difficulties in reducing the number of teachers in
academia following demographic shifts.

Figure D2.2. Average annual growth rates of the numbers of students and teaching staff in tertiary
education (2005-17)

Note: This figure cannot be interpreted as student-teacher ratio. Enrolment data coverage is not adjusted to personnel by level of education, programme
orientation, type of institution, and intensity of participation, as it is the case when calculating the student-teacher ratio (see Methodology section).
1. Year of reference is 2010 instead of 2005.
2. Tertiary includes programmes outside tertiary level - see Annex 3 for further details.
Countries are ranked in descending order of the average annual growth rate in the number of teachers in tertiary education, between 2005 and 2017.
Source: OECD/UIS/Eurostat (2019), Education at a Glance Database, http://stats.oecd.org/. See Source section for more information and Annex 3 for
notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933979823
EDUCATION AT A GLANCE 2019 © OECD 2019

382  D2. WHAT IS THE STUDENT-TEACHER RATIO AND HOW BIG ARE CLASSES?
Monitoring the number of students and academic staff at tertiary level could provide valuable insights into the
way education systems are responding to the changing demand for tertiary education. On average across OECD
and partner countries, tertiary attainment has been growing over the past 20 years, and it is expected to continue
growing in the next decade (OECD, 2018[12]). This increase reflects the rise in demand for skilled labour, in part
driven by technological changes (OECD, 2017[13]), and governments effort to promote access to tertiary
education, including through a variety of financial support policies (OECD, 2017[4]). In countries with the largest
increase in demand (see Indicator A1), the challenge is to limit the impact of such growing demands on the quality
of tertiary education systems and invest in human resources accordingly.

Class size
Average class size in primary and lower secondary education
The indicator on class size is limited to primary and lower secondary education. Class sizes are difficult to define
and compare at higher levels, as students are often split into several different classes at these levels, depending
on the subject area.
At the primary level, the average class in OECD countries has 21 pupils. There are fewer than 28 pupils per class
in nearly all of the countries with available data, with the exception of Chile (31 pupils) (Table D2.1).
At the lower secondary level, the average class in OECD countries has 23 students. Among all countries with
available data, the number varies from fewer than 20 students per class in Estonia, Finland, Latvia, Lithuania,
Luxembourg, 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 corresponds to almost 18 students. On the other hand, in the United Kingdom and, to
a lesser extent, Australia, Chile, Estonia, Finland, Hungary and the Russian Federation, the number of students
per class falls between these two levels of education (Table D2.1).

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.
Differences in class sizes between public and private institutions are similar to those observed for student-teacher
ratios. In most OECD countries, average class sizes do 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 has more than five additional students compared to the average class in private schools
(Table D2.1). However, 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, Luxembourg and Spain, the average class in private institutions is larger
than in public institutions by at least 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 private lower secondary
institutions is larger than in public institutions in 9 countries, smaller in 16 countries and the same in 7 countries.
The differences, however, tend to be smaller than in primary education.

EDUCATION AT A GLANCE 2019 © OECD 2019

D2. WHAT IS THE STUDENT-TEACHER RATIO AND HOW BIG ARE CLASSES?  383

Trends in average class size
Between 2005 and 2017, class size has remained about the same at primary level and fallen at lower secondary
level on average across OECD countries (Table D2.1). While 19 out of 27 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
27 countries at the primary level (Figure D2.3).
At the lower secondary level, the average class size fell by 6% between 2005 and 2017. 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 about 20% over the past decade. In Korea, classes at the primary
level are also, on average, 29% smaller than in 2005 – the largest decrease among OECD countries in the past
decade. This could reflect the declining number of students. Other countries, however, saw an increase in
average class sizes in primary schools: by 20% in Mexico, 14% in Portugal and 29% in the Russian Federation.
At the lower secondary level, average class sizes increased by 8% in Denmark, the largest increase among
OECD countries.

Figure D2.3. Average class size in primary education (2005 and 2017)

Countries are ranked in descending order of the average class size in primary education in 2005.
Source: OECD/UIS/Eurostat (2019), Table D2.1. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933979842

Definitions
There are two categories of instructional personnel (teachers):


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. Teaching staff also include departmental chairs 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 2019 © OECD 2019

384  D2. WHAT IS THE STUDENT-TEACHER RATIO AND HOW BIG ARE CLASSES?
Academic staff include personnel at tertiary level whose primary assignment is instruction or research.

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. At tertiary level, the student-teacher ratio is calculated using data on academic staff instead of
teachers.
For the ratio of students to teachers to be meaningful, consistent coverage of personnel and enrolment data are
needed. For instance, if teachers in religious schools are not reported in the personnel data, then students in
those schools must also be excluded.
For more information, please see the OECD Handbook for Internationally Comparative Education Statistics 2018:
Concepts, Standards, Definitions and Classifications (OECD, 2018[14]) and Annex 3 for country-specific notes
(https://doi.org/10.1787/f8d7880d-en).

Source
Data refer to the academic year 2016/17 and are based on the UNESCO-UIS/OECD/EUROSTAT data collection
on education statistics administered by the OECD in 2018 (for details, see Annex 3 at
https://doi.org/10.1787/f8d7880d-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
Australian Government (2019), HEIMSHELP,
https://heimshelp.education.gov.au/resources/glossary/glossaryterm?title=Function.

[9]

ETER (2019), ETER, https://eter-project.com/#/home.

[7]

European Commission/EACEA/Eurydice (2017), Modernisation of Higher Education in Europe:
Academic Staff – 2017, Publications Office of the European Union, Luxembourg,
https://publications.europa.eu/en/publication-detail/-/publication/40f84414-683f-11e7-b2f201aa75ed71a1/language-en (accessed on 18 October 2018).

[8]

Fredriksson, P., B. Öckert and H. Oosterbeek (2013), “Long-Term effects of class size”, Quarterly
Journal of Economics, Vol. 128/1, pp. 249-285, http://dx.doi.org/10.1093/qje/qjs048.

[2]

EDUCATION AT A GLANCE 2019 © OECD 2019

D2. WHAT IS THE STUDENT-TEACHER RATIO AND HOW BIG ARE CLASSES?  385

Klein, S. (2001), Financing Vocational Education: A State Policymaker’s Guide, RTI,
http://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.

[11]

NCES National Center for Education Statistics (2018), IPEDS 2017-18 Data Collection System,
https://nces.ed.gov/ipeds/UseTheData/ArchivedSurveyMaterialPdf?year=2017&fileName=package_
1_43.pdf.

[10]

OECD (2018), “How is the tertiary-educated population evolving?”, Education Indicators in Focus 61,
https://doi.org/10.1787/a17e95dc-en.

[12]

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.

[14]

OECD (2017), “Future of works and skills”, Paper presented at the 2nd Meeting of the G20
Employment Working Group, Hamburg, 15-17 February 2017,
http://www.oecd.org/els/emp/wcms_556984.pdf.

[13]

OECD (2017), Education at a Glance 2017: OECD Indicators, OECD Publishing, Paris,
http://dx.doi.org/10.1787/eag-2017-en.

[4]

OECD (2016), Frascati Manual 2015: Guidelines for Collecting and Reporting Data on Research and
Experimental Development (Korean version), Korea Institute of S&T Evaluation and Planning,
Seoul, https://doi.org/10.1787/9789264239012-en.

[6]

OECD (2016), PISA 2015 Results (Volume II): Policies and Practices for Successful Schools, PISA,
OECD Publishing, Paris, https://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: Enseignement scolaire, No. 173,
http://www.education.gouv.fr/cid3865/l-impact-de-la-taille-des-classes-sur-la-reussite-scolaire-dansles-ecoles-colleges-et-lycees-francais.html&xtmc=piketty&xtnp=1&xtcr=1 (accessed on
6 June 2019).

[1]

EDUCATION AT A GLANCE 2019 © OECD 2019

386  D2. WHAT IS THE STUDENT-TEACHER RATIO AND HOW BIG ARE CLASSES?

Indicator D2 Tables
Table D2.1

Average class size, by type of institution (2017) and index of change between 2005 and 2017

Table D2.2

Ratio of students to teaching staff in educational institutions, by level of education (2017)

Table D2.3

Ratio of students to teaching staff, by type of institution (2017)

Cut-off date for the data: 19 July 2019. 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.
StatLink: https://doi.org/10.1787/888933981210

EDUCATION AT A GLANCE 2019 © OECD 2019

D2. WHAT IS THE STUDENT-TEACHER RATIO AND HOW BIG ARE CLASSES?  387

Table D2.1. Average class size, by type of institution (2017) and index of change between 2005 and 2017
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 (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888933979747

EDUCATION AT A GLANCE 2019 © OECD 2019

388  D2. WHAT IS THE STUDENT-TEACHER RATIO AND HOW BIG ARE CLASSES?
Table D2.2. Ratio of students to teaching staff in educational institutions, by level of education (2017)
Calculations based on full-time equivalents

1. Primary includes pre-primary education.
2. Upper secondary includes programmes outside upper secondary level - see Annex 3 for further details.
3. For France, public and government-dependent private institutions only for all levels. For Ireland and Switzerland, public institutions only for all levels. For Israel, public
institutions only for upper secondary education and all secondary.
4. Tertiary includes programmes outside tertiary level - see Annex 3 for further details.
5. Year of reference is 2016 instead of 2017.
Source: OECD/UIS/Eurostat (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888933979766

EDUCATION AT A GLANCE 2019 © OECD 2019

D2. WHAT IS THE STUDENT-TEACHER RATIO AND HOW BIG ARE CLASSES?  389

Table D2.3. Ratio of students to teaching staff, by type of institution (2017)
By level of education, calculations based on full-time equivalents

1. Includes only general programmes in lower and upper secondary education.
2. Upper secondary includes programmes outside upper secondary level - see Annex 3 for further details.
3. Year of reference is 2016 instead of 2017.
Source: OECD/UIS/Eurostat (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888933979785

EDUCATION AT A GLANCE 2019 © OECD 2019

390  D3. HOW MUCH ARE TEACHERS AND SCHOOL HEADS PAID?

Indicator D3. How much are teachers and school
heads paid?
Highlights


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 52% higher than those of teachers across primary and
secondary levels of education.



Teachers’ actual salaries at pre-primary, primary and general secondary levels of education are 78%
to 93% of earnings of tertiary-educated workers on average across OECD countries.



On average across OECD countries and economies, school heads’ salaries are at least 25% higher
than earnings of tertiary-educated workers at primary and secondary levels.

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 a school head.
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 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 high-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 social benefits systems across OECD
countries. This, as well as potential comparability issues related to data collected (see Box D3.1 and Annex 3),
should be borne in mind when analysing teachers’ salaries and comparing them across countries.

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 86% and 89% higher than those of teachers on minimum salaries and with minimum
qualifications at the start of their career.



Between 2005 and 2018, on average across OECD countries and economies with available data,
statutory salaries of teachers with 15 years of experience and most prevalent qualifications increased

EDUCATION AT A GLANCE 2019 © OECD 2019

D3. HOW MUCH ARE TEACHERS AND SCHOOL HEADS PAID?  391

by 10% at primary level, 9% at lower secondary level (general programmes) and 6% at upper
secondary level (general programmes).


Statutory salaries of primary, lower secondary and upper secondary teachers with 15 years of
experience and minimum qualifications 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.

Figure D3.1. Lower secondary teachers' and school heads’ salaries relative to earnings for tertiaryeducated workers (2018)
Actual salaries (annual average salaries including bonuses and allowances) of teachers and school heads in general
lower secondary education in public institutions

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 (2019), Table D3.2a. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en.).
1 2 https://doi.org/10.1787/888933979937

EDUCATION AT A GLANCE 2019 © OECD 2019

392  D3. HOW MUCH ARE TEACHERS AND SCHOOL HEADS PAID?

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
Teachers’ salaries vary widely across countries. The salaries of lower secondary school teachers with 15 years
of experience and most prevalent qualifications (a 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
Australia, Canada, Germany, Ireland, the Netherlands and the United States, and they exceed USD 100 000 in
Luxembourg (Table D3.1a).
In most countries and economies with available information, teachers’ salaries increase with the level of education
they teach. In the Flemish and French communities of Belgium, and Norway, upper secondary teachers with
15 years of experience and the most prevalent qualifications earn between 25% and 30% more than pre-primary
teachers with the same experience, while in Lithuania, Finland and the Slovak Republic they earn 36 to 50%
more, and in Mexico, 89% 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 Australia, Chile, Costa Rica, France and Slovenia, and
teachers have the same salary irrespective of the level of education taught in Colombia, England
(United Kingdom), Greece, Poland, Portugal, Scotland (United Kingdom) and Turkey (Table D3.1a).
However, in Israel the salary of a pre-primary teacher is about 5% higher than the salary of an upper secondary
teacher. This 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,
Denmark, Hungary, Luxembourg, Poland, Spain and Switzerland require a higher degree (master’s or equivalent)
to teach either 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 the 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).

EDUCATION AT A GLANCE 2019 © OECD 2019

D3. HOW MUCH ARE TEACHERS AND SCHOOL HEADS PAID?  393

In the remaining countries and economies, 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 15 countries
with available data, the salaries of teachers with the most prevalent qualifications are at least 10% higher than
those of teachers with the minimum qualifications in Colombia (pre-primary and primary levels), 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 a teacher’s career only in Canada, Colombia (lower and upper secondary levels), the French
Community of Belgium, Greece, Mexico, New Zealand and Norway (primary and lower secondary levels). The
difference in teachers’ salaries between those with the most prevalent and the minimum qualifications exceeds
75% in Costa Rica. However, the salaries of teachers with the most prevalent qualifications are still at 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 only 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
teachers have. This is the case in a small number of countries (Hungary, Iceland, Ireland, Israel, Mexico, Norway
and the United States), 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) in one or several levels of
education. This is usually linked to recent reforms related to the compensation system and/or qualification
requirements for teachers. In Ireland, for example, the salary arrangements have changed for teachers who
entered the teaching profession from the beginning of 2011. The salaries related to most prevalent qualifications
for teachers with 10 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 10 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. For lower secondary teachers with the most prevalent
qualifications, average statutory salaries after 10 years of experience are 30% higher than average starting
salaries, and 38% higher with 15 years of experience. In addition, average salaries at the top of the scale (reached
after an average of 25 years of experience) are 67% higher than the average 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 6-7 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 wider the range between minimum and maximum salaries,
the more years it takes for teachers to achieve maximum status. For example, it takes only 6-7 years to reach
this level in Australia, New Zealand and Scotland (United Kingdom), but the maximum salary in these countries
and economies is only about 33-53% higher than starting salaries, compared to 66% on average across OECD
countries with available data for salaries at both starting point and top of the scale. However, this is not true of all

EDUCATION AT A GLANCE 2019 © OECD 2019

394  D3. HOW MUCH ARE TEACHERS AND SCHOOL HEADS PAID?
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 32% higher than starting statutory salaries, compared to 105% 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 the most prevalent
qualifications is USD 56 for primary teachers, USD 65 for lower secondary teachers and USD 75 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 28%. In Scotland (United Kingdom), there is no
difference, while in Mexico, the salary per teaching hour for an upper secondary teacher is at least 73% 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).
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 teachers’ statutory working time is usually similar at primary and secondary level (see
Indicator D4).

By level of experience and qualification: Minimum and maximum teachers’ salaries
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.
At the lower secondary level, the average statutory salary of a teacher with the most prevalent qualification level
with 15 years of experience is 40% 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 85% higher than the average
starting salary with the minimum qualification (Figure D3.2).
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, the most
notable exceptions are Colombia, England (United Kingdom), Korea and Mexico, where starting salaries are at
least 5% lower than the OECD average, but maximum salaries are 18% to 45% higher. These differences may
be reflective of the different career paths available to teachers’ with different qualifications in these countries. The
opposite is true in Denmark, Finland, Iceland, Norway and Sweden, where starting salaries are between 7% and
45% higher than the OECD average, while maximum salaries are at least 5% lower than the OECD average
(7% to 29% lower). This results from relatively flat/compressed salary scales in a number of these countries
(Tables D3.1c and D3.6, available on line).
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.

EDUCATION AT A GLANCE 2019 © OECD 2019

D3. HOW MUCH ARE TEACHERS AND SCHOOL HEADS PAID?  395

Figure D3.2. Lower secondary teachers’ statutory salaries at different points in teachers’ careers (2018)
Annual statutory salaries of teachers in public institutions, in equivalent USD converted using PPPs

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 (2019), Table D3.1a, Tables D3.1c and D3.6, available on line. See Source section for more information and Annex 3 for notes
(https://doi.org/10.1787/f8d7880d-en.).
1 2 https://doi.org/10.1787/888933979956

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, England (United Kingdom), France, Hungary, Ireland, Israel, Japan, Korea, the Netherlands,
Portugal and more than three times higher in Colombia and Mexico (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, Colombia, France,
Hungary, Israel, Mexico and Portugal (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 a couple of things. First, minimum
qualifications are the most prevalent in the majority of countries. Second, not all teachers may aim for or reach
the top of the salary scale and in some systems few of them may hold the minimum or maximum
qualifications (Table X2.5).

EDUCATION AT A GLANCE 2019 © OECD 2019

396  D3. HOW MUCH ARE TEACHERS AND SCHOOL HEADS PAID?

Box D3.1. Comparability issues related to data on salaries of teachers and school heads
Meaningful international comparisons rely on the provision and implementation of rigorous definitions and a
related statistical methodology. In view of the diversity across countries of both their education and their
teachers’ compensation systems, adhering to these guidelines and methodology is not always straightforward.
Some caution is therefore required when interpreting these data.
Teachers’ salaries at different level of experience are collected based on the qualification level of teachers.
The minimum and most prevalent qualification level are then used to distinguish pay scales. The number of
pay scales that exist and the proportion of teachers who are paid according to each one varies substantially
between countries. Some countries have many pay scales while others have few (or only one). In the case of
federal countries, such as Australia, Canada, Germany and the United States, the structure of pay scales
varies between states (and between municipalities in some cases), an average of pay scales from the
subnational entities (or actual salaries) is reported by countries. This means the data on statutory salaries do
not directly correspond to any particular group of teachers within these countries. Data at the subnational level
illustrate the variations in pay systems within countries (Box D3.2).
Multiple pay scales in a country can mean that only a small proportion of teachers are paid according to the
pay scale related to the most prevalent qualification. In contrast, in many countries the minimum qualification
is also the most prevalent one, and then the proportion of teachers paid according to the related salary scale
can represent the largest proportion of teachers at this level. There tends to be a greater number of pay scales
for school heads then for teachers, as several criteria are taken into account to determine the level of
compensation of school heads This means that the salaries for the most prevalent qualification maybe less
representative for school heads.
Salaries for teachers with minimum or maximum qualifications need to be compared with caution as in some
cases a large share of the teaching population in a country may have the minimum or maximum, while in other
cases there may be very few teachers in these positions. In some countries, maximum/top of the scale
statutory salaries for school heads may be notional. It is possible to be paid at that level, but few (if any) school
heads are actually paid the maximum salary. No inference can be drawn from the data about how school
heads are distributed between the minimum and maximum pay in each pay scale.
How schools grades are grouped together into levels of education also varies between countries. For example,
in New Zealand there is no separate lower secondary system. The first two years of lower secondary are part
of the primary system and the second two years are covered by the secondary system. As a result, statutory
salaries reported by level of education may be averages of different groups of teachers rather than relating to
specific pay scales for teaching at that level. In Norway, similar salary levels for primary and secondary school
teachers are reported as teachers often teach at both levels and the salary level of teachers depends on their
educational attainment rather than on the level of education at which they teach.
The role of teachers and school heads and also the way their compensation systems operate differ between
countries. The allowances given to teachers in addition to their salaries gives some insight into this. For
example, 13 countries give their lower secondary teachers an allowance for student counselling, while
18 countries give no such allowance but 4 of these countries (Greece, Latvia, Slovenia and Switzerland)
require teachers to perform this task without additional compensation. Differences in roles are even more
evident among school heads; the tasks that are required or expected of them vary between countries. Their
level of responsibility may also vary, as well as the scale of the institutions they manage.
For more information on comparability issues, see the notes for specific countries in Annex 3.

EDUCATION AT A GLANCE 2019 © OECD 2019

D3. HOW MUCH ARE TEACHERS AND SCHOOL HEADS PAID?  397

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 2018 (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), where there was a decline of 3%; France, where salaries declined by up to 6%; and Greece
where salaries decreased by 17%. There were also slight declines in teachers’ salaries in real terms (less than
2%) in Italy (for primary and secondary education). Salaries increased by more than 30% across primary and
secondary education levels in Ireland and Israel. However, in some countries, the overall increase in teachers’
salaries between 2000 and 2018 includes periods of decrease in salaries (in real terms), particularly from 2010
(Table D3.5a, available on line).
Over the period 2005-18, for which three-quarters of OECD countries and economies have comparable data for
at least one level of education, more than half 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 the reference years of 2005 and 2018, statutory salaries increased by 10% at
primary level, 9% at lower secondary level and 6% 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 also since 2017 and to improve the quality
of education by providing financial incentives to attract high-quality teachers) and also in Israel, Luxembourg (preprimary and primary), Norway and Sweden.

Figure D3.3. Change in teachers’ salaries in OECD countries (2005 to 2018)
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)

Source: OECD (2019), Table D3.5b, available on line. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en.).
1 2 https://doi.org/10.1787/888933979975

In most countries, the salary increases were similar across primary, lower secondary and upper secondary levels
between 2005 and 2018. However, this is not the case in Israel, where salaries increased by more than 56% at
pre-primary level, 40% at primary level, 52% at lower secondary level and 50% at upper secondary level. This is
largely the result of the gradual implementation of the “New Horizon” reform in primary and lower secondary
EDUCATION AT A GLANCE 2019 © OECD 2019

398  D3. HOW MUCH ARE TEACHERS AND SCHOOL HEADS PAID?
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 included raising teachers’ pay in exchange for
longer working hours (see Indicator D4).
By contrast, salaries have decreased slightly since 2005 in a few countries: France (secondary), Italy, Portugal,
Scotland (United Kingdom) and Spain, and they decreased by at least 10% in England (United Kingdom) and
Japan, and by more than 25% in Greece as the result of reductions in remuneration, implementation of new wage
grids and salary freezes since 2011 (Table D3.5a).
However, these overall changes in teachers’ salaries in OECD countries between 2005 and 2018 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). Statutory salaries for
primary, lower and upper secondary teachers with minimum qualifications have now exceeded pre-crisis levels,
on average across OECD countries with data for all reference years.

Statutory salaries of school heads
The 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 the timetable,
implementation of the curriculum, decisions about what is 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 school-head 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 teachers’ salary ranges
may reflect the fact that school heads are initially teachers with additional responsibilities. At lower secondary
level, school heads are paid according to teachers’ salary scales, with a school-head allowance, in 13 out of the
33 countries with available information, and according to a specific salary range in the other countries. Of these,
12 countries have no specific school-head allowance and 8 countries have a school-head allowance. The
amounts payable to school heads (through statutory salaries 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.). They could also vary according to the
individual characteristics of the school heads themselves, such as the duties they have to perform or their years
of experience (Table D3.9, available on line).
Considering the large number of criteria involved in teachers’ statutory salaries, the statutory salary data for
school heads focuses on the minimum qualification requirements to become a school head, and Table D3.10
shows only the minimum and maximum values. Caution is necessary when interpreting these values because
salaries often depend on many criteria and as a result few school heads may earn these amounts.
At lower secondary level, the minimum salary is USD 49 629 on average across OECD countries, varying from
USD 19 184 in Latvia to USD 116 560 in Luxembourg, and the maximum salary is USD 85 700 on average
across OECD countries, varying from USD 29 715 in the Czech Republic to USD 161 200 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.
On average across OECD countries and economies, the maximum statutory salary of a school head with
minimum qualifications is 80% higher than the minimum statutory salary in primary education, 77% higher than
in lower secondary and 74% higher than in upper secondary. There are only 12 countries where school heads at

EDUCATION AT A GLANCE 2019 © OECD 2019

D3. HOW MUCH ARE TEACHERS AND SCHOOL HEADS PAID?  399

the top of the scale can expect to earn twice the statutory starting salary in at least one of these levels of
education; in Costa Rica, they can expect to earn more than three times the starting salary.

Figure D3.4. Minimum and maximum statutory salaries for lower secondary teachers and school heads
(2018)
Based on teachers with most prevalent qualifications at a given level of education and school heads with minimum
qualifications

1. Actual base salaries.
Countries and economies are ranked in descending order of maximum salaries of school heads.
Source: OECD (2019), Table D3.1b available on line and Table D3.10. See Source section for more information and Annex 3 for notes
(https://doi.org/10.1787/f8d7880d-en.).
1 2 https://doi.org/10.1787/888933979994

The minimum statutory salaries for school heads with minimum qualifications are higher than the starting salaries
of teachers, except in Costa Rica and Lithuania (primary and secondary). The difference between minimum
salaries for school heads (with minimum qualifications) and starting salaries for teachers (with the most prevalent
qualifications) increases with levels of education: 23% on average across OECD countries and economies at
pre-primary level, 33% at primary level, 44% at lower secondary level and 45% 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, Canada, Denmark, England (United Kingdom), Finland,
Iceland, Israel, Italy, Japan, Mexico, New Zealand, Scotland (United Kingdom), Slovenia and the United States
(Figure D3.4).
Similarly, the 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 48% 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

EDUCATION AT A GLANCE 2019 © OECD 2019

400  D3. HOW MUCH ARE TEACHERS AND SCHOOL HEADS PAID?
salaries of school heads in Chile, Colombia, England (United Kingdom), Hungary, Iceland, Mexico and Scotland
(United Kingdom) are more than twice the statutory salaries at the 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 the 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
workforce. 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 36 247 at
pre-primary level, USD 40 580 at primary level, USD 42 553 at lower secondary level and USD 45 803 at upper
secondary level. Average actual salaries of school heads aged 25-64 vary from USD 61 791 at primary level,
USD 66 534 at lower secondary level and USD 72 081 at upper secondary level (Table D3.4) (see Box D3.2 for
variations at subnational level).
Among the 28 OECD countries and economies with available data on both the statutory salaries of teachers with
15 years of experience and most prevalent qualifications, and the 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.

Figure D3.5. Actual salaries of lower secondary teachers and school heads (2017)
Annual actual salaries of teachers and school heads in public institutions, in equivalent USD converted using PPPs

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 (2019), Table D3.4. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en.).
1 2 https://doi.org/10.1787/888933980013

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 52% higher
EDUCATION AT A GLANCE 2019 © OECD 2019

D3. HOW MUCH ARE TEACHERS AND SCHOOL HEADS PAID?  401

than those of teachers at primary level. The premium is 56% at lower secondary level, and 57% at upper
secondary level. The difference between actual salaries of school heads and teachers varies widely between
countries and between levels of education. The countries and economies with the highest premium for school
heads compared to teachers are England (United Kingdom) (secondary levels) and Italy (primary and secondary
levels), where the actual salaries of school heads are twice that of teachers. The lowest premiums, of less than
25%, are in Estonia (at primary and secondary), Finland (pre-primary), Latvia (lower secondary), Norway
(pre‑primary) and Turkey. 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 Denmark, actual
salaries of school heads are 28% higher than teachers at pre-primary level but the difference is 40% at lower
secondary and 59% 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).

Box D3.2. Subnational variations in teachers' salaries at pre-primary, primary and secondary levels
For each country, teachers’ statutory salaries can vary by level of education and by level of experience.
Salaries can also vary significantly among subnational entities within each country, especially in federal
countries where salary requirements may be defined at the subnational level. Subnational data provided by
four countries (Belgium, Canada, the United Kingdom and the United States) illustrate these variations at the
subnational level.
In these four countries, statutory salaries vary to a differing extent between subnational entities, depending on the
stage teachers have reached in their careers. In 2018 in Belgium, for example, the starting salary of a primary
school teacher varied by only 3% (USD 1 101), ranging from USD 36 589 in the French Community to USD 37 690
in the Flemish Community. In comparison, subnational variation was largest in Canada, where the starting salary
of a primary school teacher varied by 80% (USD 25 710) across subnational entities, ranging from USD 32 279 in
Quebec to USD 57 989 in the Northwest Territories. Similar patterns were observed in the starting salaries for lower
secondary and upper secondary teachers.
In Belgium, the extent of the variation of statutory salaries between subnational entities remains relatively
even across all levels of education and stages of teachers’ careers. In contrast, in both Canada and
the United Kingdom, the variation across subnational entities was greater for starting salaries than for salaries
at the top of the scale. For example, at the upper secondary level, starting salaries in the United Kingdom
varied by 23% (USD 6 583) between subnational entities, from USD 28 186 to USD 34 769, while salaries at
the top of the salary scale varied by only 6% (USD 2 728), from USD 46 227 to USD 48 956. In
the United States, there was no clear pattern in the extent of the variation of statutory salaries across
subnational entities at different levels of education and stages of teachers’ careers. At the lower secondary
level, the variation was the smallest for starting salaries, ranging from USD 34 243 to USD 59 927 (a
difference of 75%, or USD 25 684) and the largest for salaries at top of the salary scale, ranging from
USD 54 081 to USD 110 661 (a difference of 105%, or USD 56 580).
There is also large subnational variation in actual salaries of teachers and school heads among the three
countries (Belgium, the United Kingdom and the United States) with available data in 2017. In both
the United Kingdom and the United States, the subnational variation in actual salaries was much greater
among school heads than among teachers. For example, at the upper secondary level, teachers’ salaries in
the United Kingdom (among subnational entities with available data) ranged from USD 42 474 in Scotland to
USD 51 307 in Northern Ireland, a difference of 21% or USD 8 832. In comparison, school heads’ salaries
ranged from USD 66 023 in Scotland to USD 111 801 in England, a difference of 69% or USD 45 778.
Subnational variation in actual salaries was much smaller among both teachers and school heads in Belgium.
For example, the salaries of upper secondary school heads ranged from USD 92 707 in the French
Community to USD 94 989 in the Flemish Community, a difference of 2% or USD 2 283.

EDUCATION AT A GLANCE 2019 © OECD 2019

402  D3. HOW MUCH ARE TEACHERS AND SCHOOL HEADS PAID?
The extent of the subnational variation in actual salaries (for teachers and school heads) also varies according
to level of education. For both teachers and school heads in the United Kingdom (for subnational entities with
available data), subnational variation was greater in actual salaries at the lower and upper secondary levels
than at the primary level. In the United States, subnational variation in actual salaries of teachers was the
largest at the primary level, while subnational variation among school heads was largest at the upper
secondary level.
Source: Education at a Glance Database. http://stats.oecd.org.

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[2]). Teachers’ salaries relative to those of other occupations
(with similar education requirements) 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 the career progression pathways available to teachers and the compensation they
can expect in the longer term.

Box D3.3. How teachers’ salaries compare to similarly educated workers
Differences between actual salaries for male and female teachers are small: 3% or less in favour of men, on
average, at primary and secondary levels. However, 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, the actual salaries of male teachers (aged 25-64) range from 73% (at primary level) to 83%
(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 40 percentage
points higher among women than among the men at pre-primary, primary and secondary levels of education.
This higher earnings ratio among female teachers shows that teaching 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).
A survey launched in 2018 collected information on the distribution of teachers by attainment level, with a
breakdown of teachers by gender (and age groups). With these data, it was then possible to compute the
actual salaries of teachers relative to the weighted average earnings of similarly educated workers for a small
number of countries. This helps to remove the differences in educational attainment by gender between
teachers and tertiary-educated workers when comparing actual salaries to earnings.
Among the five countries with available data at the lower secondary level, these weighted ratios show an
impact on the value of the relative earnings, implying differences in the breakdown by attainment level and/or
salaries between teachers and tertiary-educated workers. However, the impact can result in either a decrease
or an increase in relative salaries. These ratios also show that female teachers earn salaries that are closer
to that of their peers than do their male colleagues. For example, in these countries a woman teaching at the
lower secondary level earns between 73% and 121% of the earnings of a similarly educated woman. In
contrast, men teaching at lower secondary earn between 53% and 78% of what similarly educated men earn
(Figure D3.a).
At primary and secondary levels, the actual salaries of older teachers (aged 55-64) are, on average, 35-37%
higher than those of younger teachers (aged 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

EDUCATION AT A GLANCE 2019 © OECD 2019

D3. HOW MUCH ARE TEACHERS AND SCHOOL HEADS PAID?  403

Australia, Latvia, Norway and Sweden, while it is 60% or more in Austria, Greece, Israel and Portugal
(Table D3.4).

Figure D3.a. Lower secondary teachers' actual salaries relative to earnings of tertiary-educated
workers, aged 25- 64 (2018)

Countries and economies are ranked in descending order of weighted relative salaries of women teachers
Source: OECD (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en.).
1 2 https://doi.org/10.1787/888933980032

Despite the increase in teachers’ salaries for older age groups, comparing teachers’ salaries with the earnings
of tertiary-educated workers seems to show that teachers’ salaries may evolve at a slower rate than the
earnings of other workers and that the teaching profession becomes less attractive as the workforce ages.
On average across OECD countries and economies, teachers’ actual salaries relative to the earnings of
tertiary-educated workers are about 10 percentage points higher among 25-34 year-olds than among the
older age groups (55-64 year-olds) 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.
The comparison of salaries of teachers and earnings of tertiary-educated workers might be biased by
differences in the attainment level and/or the earnings of teachers and tertiary-educated workers in the
different age groups. The survey on data availability on the distribution of teachers by attainment level
gathered data on these distributions by age group in a few countries. This made it possible to compute relative
salaries of teachers by age group, removing the differences in the attainment distribution between teachers
and tertiary-educated workers. As with the relative salaries by gender, this has a significant impact on the
relative measure of salaries of teachers by age group. The effect can either increase or decrease relative
salaries and the magnitude of the change varies between age groups. The relative salaries of teachers in this
group of countries follow a similar pattern across age groups. The youngest teachers (age 25-34) earn
between 66% and 110% of the earnings of similarly educated 25-34 year-olds. However older cohorts earn
notably less, with teachers aged 45-54 earning between 52% and 89% of the earnings of similarly educated,
similarly aged workers.
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 the earnings of other tertiary-educated professionals: 25-64 year-old full-time, full-year workers

EDUCATION AT A GLANCE 2019 © OECD 2019

404  D3. HOW MUCH ARE TEACHERS AND SCHOOL HEADS PAID?
with a similar tertiary education (ISCED levels 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 in the distribution of tertiary
attainment level among teachers and tertiary-educated workers more generally, actual salaries of teachers are
compared to a weighted average of earnings of similarly educated workers (the earnings of similarly educated
workers weighted by the proportion of teachers with similar tertiary attainment) (see Tables X2.11a and X2.11b
in Annex 2 for the proportion of teachers and school heads by attainment level).
Among the 22 countries and economies with available data (for at least one level), actual salaries of teachers
amount to 65% or less of earnings of similarly educated workers in the Czech Republic (primary and secondary)
and the United States. Very few countries and economies have actual teachers’ salaries that reach or exceed
those of similarly educated workers. However, in the Flemish Community of Belgium, actual salaries of teachers
are the same as those of similarly educated workers at pre-primary and primary levels, and in Latvia, they are
15% higher at the pre-primary level and 47-60% higher at primary and secondary levels (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 levels 5 to 8) (see the Methodology section). Against this benchmark, actual teachers’
salaries relative to other tertiary-educated workers increase with higher education levels. Pre-primary teachers’
salaries amount to 78% of full-time, full-year earnings, on average, among 25-64 year-olds with tertiary education.
Primary teachers earn 84% of the benchmark salary, lower secondary teachers 88% and upper secondary
teachers 93% (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 50% of those of tertiary-educated workers,
in the United States at the primary level (63% those of tertiary-educated workers), and in the Czech Republic at
primary and secondary levels where they reach 64% to 66% of those of tertiary-educated workers. However in
some countries, teachers earn more than tertiary-educated adults at all levels of education (Costa Rica, Latvia
and Portugal), or at some levels of education only (at upper secondary level in Finland and the Flemish and
French communities of Belgium, at lower and upper secondary levels in Germany). In Latvia and Portugal,
teachers earn at least 30% more than tertiary-educated workers. (Table D3.2a and Figure D3.1).
School heads earn more than teachers and, unlike teachers, typically earn more than similarly educated workers
at all the levels of education considered. This difference tends to increase with the level of education. Among the
17 OECD countries and economies with available data (for at least one level), it is only pre-primary school heads
in Estonia, Finland and Norway whose actual salaries are on average at least 5% lower than the earnings of
similarly educated workers. In contrast, school heads’ salaries are at least 40% higher than similarly educated
workers in the Flemish Community of Belgium (pre-primary, primary and lower secondary), England
(United Kingdom) (secondary), Latvia and New Zealand (primary and secondary). At the upper secondary level
in Latvia, school heads earn twice as much as similarly educated workers.
As with teachers, there are only a few countries with available data for this relative measure of school heads’
salaries. Hence, a second benchmark is based on the actual salaries of all school heads, relative to earnings for
full-time, full-year workers with tertiary education. Using this measure, on average across OECD countries and
economies, school heads earn 25% more than tertiary-educated adults at primary level, 34% more at lower
secondary level and 43% more at upper secondary level. School heads earn less than tertiary‑educated adults
only in the Czech Republic (pre-primary level), Denmark (pre-primary level), Estonia (pre-primary level), Finland
(pre-primary level), Norway (pre‑primary level) and in Turkey (for pre-primary, primary and secondary levels).

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,

EDUCATION AT A GLANCE 2019 © OECD 2019

D3. HOW MUCH ARE TEACHERS AND SCHOOL HEADS PAID?  405

bonuses or other rewards. These may take the form of financial remuneration and/or reductions 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 to merit 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 the tasks and responsibilities of
teachers).Taking on other responsibilities, however, often entails 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 two-thirds of countries and economies with available information.
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).
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, the French Community of Belgium and Portugal
(Table D3.11, available on line).
Among the 31 countries with available data, nearly one-third provide additional compensation to school heads
for participating 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, France, Ireland, Italy, Korea, Poland, Portugal, Slovenia, Spain and Switzerland)
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). The extent to which teachers receive
additional compensation for taking on extra responsibilities and the activities for which teachers are compensated
varies across these countries. As with 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 so they are not
compensated with any extra allowances.
At lower secondary level, additional compensation is also awarded to school heads for outstanding performance
in more than 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 Colombia, France and Spain,
where school heads are rewarded for high performance, but not teachers. In France, a part of the school-head
allowance is awarded according to the results of a professional interview and is paid every three years
(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 Australia, where such incentives are provided
only to teachers. (Tables D3.11 and D3.7, available on line).

EDUCATION AT A GLANCE 2019 © OECD 2019

406  D3. HOW MUCH ARE TEACHERS AND SCHOOL HEADS PAID?

Definitions
Teachers refer to professional personnel directly involved in teaching 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 fulltime 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 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 2017 to 30 June 2018 for
statutory data and from 1 July 2016 to 30 June 2017 for actual data. The reference date for PPPs is 2017/18 for
statutory data and 2016/17 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. 2018 and 2017). Tables with salaries in national currency are included in Annex 2. To
calculate 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).

EDUCATION AT A GLANCE 2019 © OECD 2019

D3. HOW MUCH ARE TEACHERS AND SCHOOL HEADS PAID?  407

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 (Columns 1 to 4 for teachers
and Columns 10 to 13 for school heads). The weights, collected for every country individually, are based on the
percentage of teachers or school heads by ISCED level of tertiary attainment (see Tables X2.11a. and X2.11b 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 2017 reference year used for salaries of
teachers or school heads, a deflator has been used to adjust earnings data to 2017 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[3]) and Annex 3 for country-specific notes (https://doi.org/10.1787/f8d7880d-en.).

Source
Data on salaries and bonuses for teachers and school heads are derived from the 2018 joint OECD/Eurydice
data collection on salaries of teachers and school heads. Data refer to the school year 2017/18 (for statutory
salaries) or 2016/17 (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.

References
Johnes, G. and J. Johnes (2004), International Handbook on the Economics of Education, Edward
Elgar, Cheltenham, UK; Northampton, MA.

[2]

OECD (2018), OECD Handbook for Internationally Comparative Education Statistics 2018: Concepts,
Standards, Definitions and Classifications, OECD Publishing, Paris,
https://dx.doi.org/10.1787/9789264304444-en.

[3]

OECD (2005), Teachers Matter: Attracting, Developing and Retaining Effective Teachers, Education
and Training Policy, OECD Publishing, Paris, https://dx.doi.org/10.1787/9789264018044-en.

[1]

EDUCATION AT A GLANCE 2019 © OECD 2019

408  D3. HOW MUCH ARE TEACHERS AND SCHOOL HEADS PAID?

Indicator D3 Tables
Table D3.1a

Teachers’ statutory salaries, based on the most prevalent qualifications at different points in
teachers’ careers (2018)

WEB Table D3.1b Teachers’ statutory salaries, based on the most prevalent qualifications at a given level of
education (2018)
WEB Table D3.1c Teachers’ statutory salaries, based on the minimum qualifications to enter the teaching
profession (2018)
Table D3.2a

Actual salaries of teachers and school heads relative to earnings of tertiary-educated workers
(2018)

WEB Table D3.2b Teachers’ statutory salaries relative to earnings of tertiary-educated workers (2018)
WEB Table D3.2c Teachers’ actual salaries relative to earnings of tertiary-educated workers, by age group and
by gender (2017)
WEB Table D3.2d School heads’ statutory salaries relative to earnings of tertiary-educated workers (2018)
WEB Table D3.3a Comparison of teachers’ statutory salaries, based on the most prevalent qualifications of
teachers by level of education (2018)
WEB Table D3.3b Comparison of teachers’ statutory salaries, based on the minimum qualifications required to
enter the teaching profession in the reference year (2018)
Table D3.4

Average actual salaries of teachers and school heads, by age group and by gender (2017)

WEB Table D3.5a Trends in teachers’ salaries, based on most prevalent qualifications at different points in
teachers’ careers, between 2000 and 2018
WEB Table D3.5b Trends in teachers’ salaries, based on minimum qualifications on entry to the profession,
between 2000 and 2018
WEB Table D3.6 Starting/maximum teachers’ statutory salaries, based on minimum/maximum qualifications
(2018)
WEB Table D3.7 Criteria used for base salaries and additional payments awarded to teachers in public
institutions, all level of education (2018)
WEB Table D3.8 Decision-making level for criteria used for determining teachers’ base salaries and additional
payments, by level of education (2018)
WEB Table D3.9 Structure of compensation system for school heads (2018)
Table D3.10

Minimum / maximum school heads’ statutory salaries, based on minimum qualifications
(2018)

WEB Table D3.11 Criteria used for base salaries and additional payments awarded to school heads in public
institutions, by level of education (2018)
WEB Table D3.12 Decision-making level for criteria used for determining schools heads’ base salaries and
additional payments, by level of education (2018)

EDUCATION AT A GLANCE 2019 © OECD 2019

D3. HOW MUCH ARE TEACHERS AND SCHOOL HEADS PAID?  409

Cut-off date for the data: 19 July 2019. Any updates on data can be found on line at
https://doi.org/10.1787/f8d7880d-en.. More breakdowns can also be found at http://stats.oecd.org/, Education
at a Glance Database.
1 2 https://doi.org/10.1787/888933981229

EDUCATION AT A GLANCE 2019 © OECD 2019

410  D3. HOW MUCH ARE TEACHERS AND SCHOOL HEADS PAID?
Table D3.1a. Teachers' statutory salaries, based on the most prevalent qualifications at different points in teachers' careers (2018)
Annual teachers' salaries, in public institutions, in equivalent USD converted using PPPs for private consumption

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
qualification is defined for each of the four stage of the career included in this table. In many cases, the minimum qualification is the same as the most prevalent qualification, see Table
X3.D3.2 in Annex 3. Please see 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 and Sweden, includes only those teachers teaching general subjects
within vocational programmes).
6. Actual base salaries.
Source: OECD (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en.
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933979861

EDUCATION AT A GLANCE 2019 © OECD 2019

D3. HOW MUCH ARE TEACHERS AND SCHOOL HEADS PAID?  411

Table D3.2a. Actual salaries of teachers and school heads relative to earnings of tertiary-educated workers (2017)
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

Note: See Definitions and Methodology sections for more information. Data available at http://stats.oecd.org/, Education at a Glance Database.
Source: OECD (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en.).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933979880

EDUCATION AT A GLANCE 2019 © OECD 2019

412  D3. HOW MUCH ARE TEACHERS AND SCHOOL HEADS PAID?
Table D3.4. Average actual salaries of teachers and school heads, by age group and by gender (2017)
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

Note: Columns showing average actual teachers' salaries, broken down by age groups (i.e. Columns 5-20), 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 (in Sweden, includes only those teachers teaching general subjects within vocational programmes).
2. Includes data on the majority, i.e. kindergarten teachers only for pre-primary education.
3. Year of reference 2016.
4. Includes unqualified teachers.
5. Includes salaries of school heads and teachers.
6. Includes all teachers, irrespective of their age.
7. Year of reference 2015.
Source: OECD (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en.).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933979899
EDUCATION AT A GLANCE 2019 © OECD 2019

D3. HOW MUCH ARE TEACHERS AND SCHOOL HEADS PAID?  413

Table D3.10. Minimum/maximum school heads' statutory salaries, based on minimum qualifications (2018)
Annual school heads' salaries, in public institutions, in equivalent USD converted using PPPs for private consumption (by level of education)

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. Includes the social security contributions and pension-scheme contributions paid by the employers.
3. Actual base salaries.
4. 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 (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en.).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
1 2 https://doi.org/10.1787/888933979918
EDUCATION AT A GLANCE 2019 © OECD 2019

414  D4. HOW MUCH TIME DO TEACHERS SPEND TEACHING?

Indicator D4. How much time do teachers spend
teaching?
Highlights


Based on official regulations or agreements, public school teachers in OECD countries and economies
are required to teach on average 1 024 hours per year at pre-primary level, 783 hours at primary level,
709 hours at lower secondary level (general programmes) and 667 hours at upper secondary level
(general programmes).



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
2018. However, in a few countries, teaching time changed by 10% or more in one or several levels
during this period.



Most countries regulate the number of hours teachers are required to work per year, 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.

Figure D4.1. Number of teaching hours per year in general lower secondary education (2000, 2005 and 2018)
Net statutory contact time in public institutions

Note: The OECD and EU23 averages refer to countries and economies with available data for 2000, 2005, 2010, 2015 and 2018.
1. Actual teaching time.
2. Reference year differs from 2018. Refer to the source table for details.
3. Average planned teaching time in each school at the beginning of the school year or semester.
Countries and economies are ranked in descending order of the number of teaching hours per year in general lower secondary education in 2018.
Source: OECD (2019), Table D4.2. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933980146

EDUCATION AT A GLANCE 2019 © OECD 2019

D4. HOW MUCH TIME DO TEACHERS SPEND TEACHING?  415

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 work more hours than
required by statutory working times.
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


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.



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
1 024 hours per year across OECD countries and economies, ranging from 519 hours per year in
Mexico to 1 755 in Germany.



Public primary school teachers are required to teach on average 783 hours per year across OECD
countries and economies, but this ranges from less than 590 hours in Estonia, Poland and
the Russian Federation to more than 1 050 hours in Chile and Costa Rica.



The number of teaching hours required in public lower secondary schools (general programmes)
averages 709 hours per year across OECD countries and economies, ranging from 481 hours in
Poland to over 1 050 hours in Chile and Costa Rica.



Teachers in public upper secondary schools (general programmes) are required to teach on average
667 hours per year across OECD countries and economies, but teaching time ranges from 405 hours
in Denmark to over 1 050 hours in Chile and Costa Rica.



At the lower secondary level, teachers spend 43% of their working time on teaching on average,
ranging from 35% or less in Austria, Iceland, Japan, Korea, Poland and Turkey to 63% in Scotland
(United Kingdom).

EDUCATION AT A GLANCE 2019 © OECD 2019

416  D4. HOW MUCH TIME DO TEACHERS SPEND TEACHING?

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 variations
in teaching time at the subnational level, see Box D4.1). Variations in how teaching time is regulated and/or
reported across countries may also explain some of the differences in statutory teaching time between countries
(Box D4.2).
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 159 days per year in
the Flemish Community of Belgium to 225 days in Germany, Iceland and Norway. Annual teaching time ranges
from 519 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 1 024 hours per year, spread over 40 weeks
or 195 days of teaching (Table D4.1a and Figure D4.2).
Primary school teachers are required to teach an average of 783 hours per year in public institutions. In most
countries with available data, daily teaching time ranges from three to six hours a day, with an OECD average of
more than four hours per day. There is no set rule on how teaching time is distributed throughout the year. For
example, primary school teachers in Costa Rica must teach 1 188 hours per year, over 160 hours more than in
Latvia. However as teachers teach more days in Costa Rica than in Latvia (198 days compared to 170 days),
teachers in both countries teach on average 6 hours a day (Table D4.1a).

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 four
countries (Belgium, Canada, Korea and the United Kingdom) reporting subnational data. In 2018, the number
of weeks of teaching (at pre-primary, primary, and lower and upper secondary levels) varied between regions
in two of these countries: by one week in Belgium (from 36 to 37 weeks) and by two weeks in Canada (from
36 to 38 weeks). In Korea and the United Kingdom, the number of weeks of teaching is the same across all
subnational regions. However, overall figures for the number of weeks of teaching can mask difference in
teaching time in terms of days or hours of teaching at the subnational level.
The countries show different patterns of variation at the subnational level. In Belgium, the number of days of
teaching varies much more (in relative terms) between the French and Flemish communities than the number
of hours of teaching (except in vocational upper secondary programmes). For example, in general upper
secondary programmes, the number of days of teaching is 12% higher in the French Community than in
the Flemish Community (179 days compared to 160 days) due to differences in how the number of school
days is defined in the regulations. However, teaching hours vary by only 4% between the two communities
(622 hours in the Flemish Community compared to 596 hours in the French Community). In contrast, the
number of days teaching at primary and secondary levels varies by up to 6% across the different
provinces/territories in Canada (ranging from 180 days to 190 days), but teaching hours vary much more
between subnational regions. At the primary level, teaching time in the region with the longest teaching hours
is 29% higher than teaching time in the region with the shortest teaching hours (905 hours compared to
700 hours). The difference between the regions reaches 58% for general programmes at the lower secondary
level (971 hours compared to 615 hours) and 52% for general programmes at the upper secondary level
(934 hours compared to 615 hours). In Korea, there is no variation between subnational entities in the number
of teaching days, but teaching hours for general programmes vary by 8% at upper secondary level (from 522
to 564 hours) and by 24% at lower secondary level (from 454 to 561 hours).

EDUCATION AT A GLANCE 2019 © OECD 2019

D4. HOW MUCH TIME DO TEACHERS SPEND TEACHING?  417

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 typical teaching time is reported for the
subnational regions of Belgium, but maximum or estimated teaching time is reported for the different subnational
regions in Canada (for more information on potential differences in the data reported, see Box D4.2).
Source: Education at a Glance Database. http://stats.oecd.org

Lower secondary school teachers in general programmes in public institutions are required to teach an average
of 709 hours per year. Teaching time is less than 600 hours in Finland, Korea, Poland, the Russian Federation
and Turkey, and exceeds 1 000 hours in Chile, Costa Rica, Latvia and Mexico. However, the reported hours in
Finland and Korea refer to the minimum time teachers are required to teach (Box D4.2) and 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).

Figure D4.2. Number of teaching hours per year, by level of education (2018)
Net statutory contact time in public institutions

1. Actual teaching time.
2. Reference year differs from 2018. Refer to the source table for details.
3. Average planned teaching time in each school at the beginning of the school year or semester.
Countries and economies are ranked in descending order of the number of teaching hours per year in general upper secondary education.
Source: OECD (2019), Table D4.1a. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933980165

A teacher in general upper secondary education in public institutions has an average teaching load of 667 hours
per year. Teaching time ranges from fewer than 500 hours per year in Denmark, Iceland, Poland,

EDUCATION AT A GLANCE 2019 © OECD 2019

418  D4. HOW MUCH TIME DO TEACHERS SPEND TEACHING?
the Russian Federation and Turkey to more than 1 000 hours in Chile, Costa Rica and Latvia, although in Chile
the reported hours refer to the maximum time teachers can be required to teach, not their typical teaching load
(Box D4.2). 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 Costa Rica and Latvia
(Table D4.1a).

Differences in teaching time by level of education
Teaching time tends to decrease as the level of education increases. In most countries, statutory teaching time
at the pre-primary level is more than at the upper secondary level (general programmes). 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, Lithuania and Mexico, where upper secondary school teachers are
required to teach more hours than pre-primary school teachers (Table D4.1a 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 31% 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 D4.1a).
In Austria, France, Korea, Portugal and Turkey, primary school teachers have at least 25% 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 Mexico
(Table D4.1a).
Teaching time at lower and upper secondary levels is similar across most countries. However, in Iceland, Norway
and Switzerland, annual required teaching time at the lower secondary level is at least 20% more than at the
upper secondary level (Table D4.1a).

Differences in teaching time by type of programmes
In most countries, statutory teaching time does not vary much 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 and Switzerland, and at least 40% higher in the Flemish Community of Belgium (for practical
courses in vocational programmes) and Denmark. 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, individual teachers’ teaching time may differ from the regulations, 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. However,
actual teaching time does not take into account that part of the teaching time in the classroom is spent on other
activities than teaching, such as keeping order and administrative tasks. On average across the OECD countries
participating in the Teaching and Learning International Survey (TALIS), lower secondary teachers self-reported
that they spent 78% of classroom time on teaching and learning in 2018 (OECD, 2019[1]).

EDUCATION AT A GLANCE 2019 © OECD 2019

D4. HOW MUCH TIME DO TEACHERS SPEND TEACHING?  419

Figure D4.3. Number of teaching hours per year in general and vocational programmes at upper
secondary level (2018)
Net statutory contact time in public institutions

1. Actual teaching time.
2. Reference year differs from 2018. Refer to the source table for details.
3. Average planned teaching time in each school at the beginning of the school year or semester.
Countries and economies are ranked in descending order of the number of teaching hours per year in general lower secondary education in 2018.
Source: OECD (2019), Table D4.1a. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933980184

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 from the statutory requirements. In Poland, for example, lower
secondary teachers actually teach up to 15% more than the statutory teaching time. In Slovenia, lower secondary
teachers teach around 6% more hours than the statutory benchmark time, and in Latvia and Lithuania, actual
teaching time is up to 5% more than statutory requirements. By contrast, in Portugal, actual teaching time is
about 1% 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 18 years, some countries with available
data (and no break in the time series) reported an increase or decrease of 10% or more in teaching time in one
or more educational levels between 2000 and 2018 (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 2018 in
Israel and Japan (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.

EDUCATION AT A GLANCE 2019 © OECD 2019

420  D4. HOW MUCH TIME DO TEACHERS SPEND TEACHING?
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 was also significant in Japan, albeit to a lesser extent (more
than 9% or 53 hours). At the upper secondary level, the largest increase in teaching time also occurred in Israel,
where teachers had to teach nearly 19% more hours (99 additional hours) in 2018 than they did in 2000. A large
increase also occurred in Latvia in recent years, as teaching time increased by 42% between 2016 and 2018 as
a consequence of a recent change in regulations (Table D4.2).
In contrast, net teaching time dropped between 2000 and 2018 in some countries and economies. At the
pre‑primary level, among the few countries and economies with available data for 2000 and 2018, teaching time
decreased by 10% 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 162 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 levels (by 117 hours). The
decrease exceeded 22% in Korea at the primary level (190 hours). In Scotland (United Kingdom), the reduction
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 in net contact time, the maximum time teachers at these levels in Scotland (United Kingdom)
can be required to teach is still longer than the OECD average (Table 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 exercise gathering this information ensures that similar definitions and
methodologies are used when compiling data in all countries. For example, teaching time is converted into
hours (of 60 minutes) to avoid differences resulting from the varying length of teaching periods between
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.
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).
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 all levels of education, at least two-fifths of countries and economies can
exclude all or most of these activities from statutory teaching time. However, excluding examination days may
be more challenging for countries. At the lower secondary level, about 40% of countries do not exclude them,
and in 10% of countries, the information on whether they are excluded or included is not available. This may
result in teaching time being overestimated by a few days in these countries.
Moreover, official documents regulate teaching time as a minimum, typical or maximum time, which may
explain some of the differences reported 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.

EDUCATION AT A GLANCE 2019 © OECD 2019

D4. HOW MUCH TIME DO TEACHERS SPEND TEACHING?  421

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 lesson 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 5%. However, in Hungary, Iceland, Latvia, Portugal, Sweden and
Turkey pre-primary teachers are required to be available at school at least 20% more hours than upper secondary
school teachers (although statutory total working time is the same for both levels in Hungary, Iceland, Latvia and
Turkey) (Table D4.1b).
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, Poland, the Slovak Republic and Switzerland (Table D4.1b). Of these, teachers in France,
Germany (in some Länder), Japan and Korea are subject to the same total statutory working time applied to civil
servants.
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, number of years in the profession or for doing extracurricular activities at school. Iceland reduces
the 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 teachers aged 38 and over have a 48-hour extra holiday per year. In addition,
upper secondary teachers aged 55 or over receive a reduction of teaching time (from 58 hours for 55-59 year-olds
to 290 hours for those aged 60 and over).

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. 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, they spend most of their working
time on activities other than teaching. In the 24 countries and economies with data for both teaching and total
working time for lower secondary teachers, 43% of teachers’ working time is spent on teaching on average, with
the proportion ranging from 35% or less in Austria, Iceland, Japan, Korea, Poland and Turkey to 63% in Scotland
(United Kingdom). While the proportion of working time spent teaching increases with the annual number of

EDUCATION AT A GLANCE 2019 © OECD 2019

422  D4. HOW MUCH TIME DO TEACHERS SPEND TEACHING?
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 612 hours in Portugal), but 32% of working time is
spent on teaching in Japan, compared to 48% 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, Israel, Latvia, Scotland (United Kingdom) and Spain spend at least 50% of their statutory working time
teaching (Figure D4.4).

Figure D4.4. Percentage of lower secondary teachers' working time spent teaching (2018)
Net teaching time (typical annual number of hours) as a percentage of total statutory working time in general programmes
in public institutions

1. Actual teaching time.
2. Reference year differs from 2018. Refer to the source table for details.
3. Average planned teaching time in each school at the beginning of the school year or semester.
Source: OECD (2019), Tables D4.1a and D4.1b. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933980203

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
EDUCATION AT A GLANCE 2019 © OECD 2019

D4. HOW MUCH TIME DO TEACHERS SPEND TEACHING?  423

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 D4.1b).

Box D4.3. Working and teaching time of school heads
School heads are valuable human resources in schools who not only perform managerial duties, but may also
be involved in teaching activities. On average across the OECD countries participating in TALIS study,
principals self-reported spending 16% of their working time to teaching and other teaching-related activities in
2018 (OECD, 2019[1]). These school heads may be former teachers who decided to take other responsibilities
in the school where they were teaching. A recent OECD survey gathered information on the way the working
time of school heads is defined. This information could shed some light on the differences in working time of
teachers and school heads.
Among the 27 countries participating in this survey, 21 reported that the same type of official document defines
the working time of both school heads and teachers, for at least one level of education. Although it is not
necessarily the same official document that is used as a reference for both teachers and school heads, this
may suggest that these two jobs are closely related. In four countries and economies – England
(United Kingdom), Israel, Slovenia and Spain – the definition of the working time of school heads explicitly
states that pedagogical activities may be designated as a part of their tasks. In Poland, school heads are
teachers entrusted with the position of school leader with teaching duty reduced or released. The working time
of teachers and school heads are even similar in a few countries that reported comparable data for both
teachers and school heads.
School heads may have some teaching duties in most of the 26 countries with available information. Teaching
is compulsory for school heads in about one-third of the countries, while it is also required from school heads,
but in specific circumstances related to the schools, in another third. In addition, in a few countries school
heads are able to take on some teaching duties on a voluntary basis (Figure D4.a).

Figure D4.a. Teaching requirement of school heads by levels of education (2018)

Note: Secondary level of education includes both general and vocational programmes in lower and upper secondary education.
Source: OECD (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933980222

EDUCATION AT A GLANCE 2019 © OECD 2019

424  D4. HOW MUCH TIME DO TEACHERS SPEND TEACHING?
In general, school heads’ teaching duties apply across different levels of education. However, in four countries,
these duties vary between levels of education. More countries include teaching duties for school heads at the
primary level than at the pre-primary or secondary levels of education.
In nearly all countries with information on the teaching time of school heads (16 out of 17 countries), the time
that school heads have to spend on teaching duties varies according to characteristics of the schools or
between subnational entities in the country. In 10 of these countries, the size and/or complexity of the school
affects the teaching duties of school heads. In general, the bigger and more complex the school (based on the
number of students enrolled, or the number of full-time teachers or classes), the less teaching school heads
are required to do. This implies that heads of smaller schools are expected to act as supplementary teaching
staff, providing support to full-time classroom teachers.

Non-teaching tasks and responsibilities of teachers
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 teachers’ actual participation in non-teaching activities, but they provide
an insight into the breadth and complexity of teachers’ roles (for information on the workload of school heads,
see Box D4.3).
Individual teachers often do not have the authority to choose whether to perform certain tasks, which are often
related to teaching. According to regulations in more than 31 out of 39 countries and economies with available
data, individual planning or preparing lessons, marking/correcting student work, and communicating and cooperating with parents are mandatory non-teaching tasks for lower secondary teachers (general programmes)
during their statutory working time at school or statutory total working time. General administrative work and
teamwork, and dialogue with colleagues are also required in at least 26 countries, and can be decided at the
school level in another one-fifth of countries with available data. In 21 countries, participation in professional
development activities is mandatory for teachers at all levels. For such mandatory tasks, incentives such as
reduction in teaching time and financial compensation are rare (Table D4.3a and D4.3b).
Responsibilities such as being class/form teacher or participating in school or other management in addition to
teaching duties are largely distributed among teachers at the school level. Teachers’ participation in school or
other management activities can result in specific compensation for teachers. In some countries, teaching time
might be reduced to balance the workload between teaching and managerial tasks, in addition to financial
compensation. Financial compensation and/or reductions in teaching time are often available when the tasks are
performed voluntarily by individual teachers (Table D4.3b).
Of the various tasks teachers might perform, full-time classroom teachers are either required or asked to perform
student counselling in more than two-thirds of countries and economies with available information. However, in
Israel, only teachers with master’s degree or higher can perform this duty (Table D4.3b).
Teachers do not only perform the tasks that are required by regulations or school heads; they often perform tasks
voluntarily, such as teaching more classes or hours than their full-time contract requires, engaging in
extracurricular activities, training student teachers, offering guidance counselling and participating in
mentoring/support programmes for new teachers. In almost one-half of countries, individual teachers decide
whether or not to perform these tasks. For these voluntary tasks, up to two-thirds of these countries offer financial
compensation (Table D4.3b).
In general, requirements to perform certain tasks and responsibilities do not vary much across levels of education.
However, there can be some differences according to the changing needs of students at different levels of
education. For example, lower secondary teachers are required to supervise students during breaks in

EDUCATION AT A GLANCE 2019 © OECD 2019

D4. HOW MUCH TIME DO TEACHERS SPEND TEACHING?  425

16 countries, but not as many countries as for teachers at pre-primary (22 countries) and primary (20 countries)
levels (Table D4.3a).

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, minus 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’ employment contracts 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 (https://doi.org/10.1787/f8d7880d-en).

Source
Data are from the 2018 OECD-INES Survey on Teachers and the Curriculum and refer to the school year 2017/18
(statutory information) or school year 2016/17 (actual data).
EDUCATION AT A GLANCE 2019 © OECD 2019

426  D4. HOW MUCH TIME DO TEACHERS SPEND TEACHING?
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 (2019), TALIS 2018 Results (Volume I): Teachers and School Leaders as Lifelong Learners,
TALIS, OECD Publishing, Paris, https://dx.doi.org/10.1787/1d0bc92a-en.

[1]

OECD (2018), OECD Handbook for Internationally Comparative Education Statistics 2018: Concepts,
Standards, Definitions and Classifications, OECD Publishing, Paris,
https://dx.doi.org/10.1787/9789264304444-en.

[2]

Indicator D4 Tables
Table D4.1a

Organisation of teachers' teaching time (2018)

Table D4.1b

Organisation of teachers' working time (2018)

Table D4.2

Number of teaching hours per year (2000, 2005 to 2018)

Table D4.3a

Tasks of teachers, by level of education (2018)

Table D4.3b

Other responsibilities of teachers, by level of education (2018)

WEB Figure D4.5 Actual and statutory teaching time in general lower secondary education (2017)
Cut-off date for the data: 19 July 2019. 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.
StatLink: https://doi.org/10.1787/888933981248

EDUCATION AT A GLANCE 2019 © OECD 2019

D4. HOW MUCH TIME DO TEACHERS SPEND TEACHING?  427

Table D4.1a. Organisation of teachers' teaching time (2018)
Number of statutory teaching weeks, teaching days and net teaching hours in public institutions over the school year

Note: See Definitions and Methodology sections for more information. Data on vocational programmes at lower secondary level (i.e. Columns 4, 10 and 16) 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).
2. Maximum teaching time.
3. Actual teaching time.
4. Year of reference 2017 for Denmark and Switzerland, 2016 for the United States.
5. Minimum teaching time.
6. Average planned teaching time in each school at the beginning of the school year or semester.
Source: OECD (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888933980051
EDUCATION AT A GLANCE 2019 © OECD 2019

428  D4. HOW MUCH TIME DO TEACHERS SPEND TEACHING?
Table D4.1b. Organisation of teachers' working time (2018)
Teachers' statutory working time at school and total working time in public institutions over the school year

Note: See Definitions and Methodology sections for more information. Data on vocational programmes at lower secondary level (i.e. Columns 4 and 10) are available for
consultation on line. Data available at http://stats.oecd.org/, Education at a Glance Database.
1. Year of reference 2016.
Source: OECD (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888933980070

EDUCATION AT A GLANCE 2019 © OECD 2019

D4. HOW MUCH TIME DO TEACHERS SPEND TEACHING?  429

Table D4.2. Number of teaching hours per year (2000, 2005 to 2018)
Net statutory contact time in public institutions, by level of education

Note: See Definitions and Methodology sections for more information. Data on years 2000 to 2018 for pre-primary education (i.e. Columns 1-15) are available for consultation on
line. Data on years 2006, 2007, 2008, 2009, 2011, 2012, 2013, 2014, 2016 and 2017 for primary education, lower secondary education and upper secondary education
(i.e. Columns 18-21; 23-26; 28-29; 33-36; 38-41; 43-44; 48-51; 53-56; 58-59) 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).
3. Average planned teaching time in each school at the beginning of the school year or semester.
Source: OECD (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888933980089

EDUCATION AT A GLANCE 2019 © OECD 2019

430  D4. HOW MUCH TIME DO TEACHERS SPEND TEACHING?
Table D4.3a. Tasks of teachers, by level of education (2018)
Teachers' tasks in public institutions as defined explicitly in regulations and/or steering documents

Note: Pre-primary, primary, lower secondary (vocational programmes) and upper secondary levels (added in separate rows) and data on reduced teaching time and
financial compensation (i.e. Columns 4, 5, 8, 9, 12, 13, 16, 17, 20, 21, 24 and 25) are available for consultation on line (see StatLink below). See Definitions and Methodology
sections for more information.
1. Criteria 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 (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888933980108
EDUCATION AT A GLANCE 2019 © OECD 2019

D4. HOW MUCH TIME DO TEACHERS SPEND TEACHING?  431

Table D4.3b. Other responsibilities of teachers, by level of education (2018)
Teachers' responsibilities in public institutions as defined explicitly in regulations and/or steering documents

EDUCATION AT A GLANCE 2019 © OECD 2019

432  D4. HOW MUCH TIME DO TEACHERS SPEND TEACHING?

Note: Pre-primary, primary, lower secondary (vocational programmes) and upper secondary levels (added in separate rows) and data on reduced teaching time and
financial compensation (i.e. Columns 3, 4, 7, 8, 11, 12, 15, 16, 19, 20, 23, 24, 27, 28, 31 and 32) are available for consultation on line (see StatLink below). See Definitions
and Methodology sections for more information.
1. Criteria 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 (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888933980127

EDUCATION AT A GLANCE 2019 © OECD 2019

434  D5. WHO ARE THE TEACHERS?

Indicator D5. Who are the teachers?
Highlights


On average across OECD countries, women form less than half the teaching workforce at tertiary
level, but the majority of teachers at primary and secondary levels. Within tertiary education, in most
countries with available data, the share of female teachers is higher in short-cycle tertiary programmes
than in bachelor’s, master’s and doctoral programmes.



In most OECD countries, the share of primary and secondary teachers within the wider population of
50-59 year-olds is larger than the share of primary and secondary teachers among 25-34 year-olds,
which may raise concerns about future teacher shortages.



On average across OECD countries less than 15% of teachers are aged less than 30 years old, at all
levels from primary to upper secondary.

Figure D5.1. Gender distribution of teachers in tertiary education (2017)
Percentage of women among teaching staff in public and private institutions

1. Tertiary includes programmes outside tertiary level.
2. Public institutions only.
Countries are ranked in descending order of the share of female teachers in bachelor's, master's and doctoral programmes.
Source: OECD/UIS/Eurostat (2019), Education at a Glance Database, http://stats.oecd.org. See Source section for more information and Annex 3
for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933980298

EDUCATION AT A GLANCE 2019 © OECD 2019

D5. WHO ARE THE TEACHERS?  435

Context
The demand for teachers depends on a range of factors, including average class size, required instruction
time for students, the use of teaching assistants and other non-classroom staff in schools, enrolment rates at
different levels of education, and the starting and ending age of compulsory education. With large proportions
of teachers in several OECD countries set to reach retirement age in the next decade and projected increases
in the size of the school-age population in some countries, 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])
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 possible effect on students’
learning warrant detailed study (OECD, 2017[2]).

Other findings


On average across OECD countries 70% of teachers are women, in all levels of education combined.
The highest proportions of female teachers are concentrated in the earlier years of schooling, and the
share shrinks at each successive level of education.



On average across OECD countries, the share of teachers over 50 years old at primary and secondary
levels combined has increased by 3 percentage points over the decade. However, the teaching
workforce has got younger in one-third of OECD countries.

EDUCATION AT A GLANCE 2019 © OECD 2019

436  D5. WHO ARE THE TEACHERS?

Analysis
Gender profile of teachers
On average across OECD countries 70% of teachers are women in all levels of education combined. The greatest
concentration of female teachers occurs in the earlier years of schooling, and the share shrinks at each
successive level of education. While women represent 97% of the teaching staff at pre‑primary level and 83% at
primary level, they make up 60% at upper secondary and only 44% at tertiary level on average across OECD
countries (Table D5.2).
Women make up over 85% of pre-primary teachers in all countries with available data, and over 60% of primary
teachers in all OECD and partner countries except India (51%). In lower and upper secondary education,
although female teachers continue to dominate, the proportion of male teachers is larger than at earlier levels.
The share of female teachers ranges from 43% in Japan to 88% in Slovenia in lower secondary education. At
the upper secondary level, it ranges from 31% in Japan (including part of post-secondary non-tertiary) to 80% in
Latvia.
Why do so few men decide to teach at pre-primary, primary and secondary levels? 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 might base their aspirations for their
children’s professions on gender stereotypes (Croft et al., 2014[3]; Kane and Mertz, 2012[4]; OECD, 2015[1]). Even
within the teaching profession, there are gender imbalances in the different fields of study. At the lower secondary
level, women make up a smaller share of teachers in science, mathematics and technology than in the overall
teaching population (OECD, 2014[5]; OECD, 2017[2]). This may result from the social perception of science and
technology as being a masculine domain, which may discourage women from pursuing tertiary studies in that
field (Indicator B4 and (OECD, 2014[5])).
From an economic point of view, the choice of future jobs is also influenced by young people’s expectations for
future earning potential. On average across OECD countries, 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 tertiary degrees in other fields (see Indicator D3 and (OECD, 2017[2])).
These differences in relative salaries are likely to make the teaching profession more appealing to women than
to men, compared to other professions.
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[6]; OECD, 2005[7]; OECD, 2009[8]). While there is little evidence that a teacher’s gender
has an effect on student performance (Antecol, Eren and Ozbeklik, 2012[9]; Holmlund and Sund, 2008[10]), aiming
for a better balance between genders could nevertheless have positive effects on all students. In particular, male
and female teachers can contribute to students developing positive gender identities and challenge stereotyped
views (Hutchings et al., 2008[11]). There is also some evidence that female teachers’ attitudes towards some
school subjects, such as mathematics, can influence their female students’ achievement (Beilock et al., 2010[12];
OECD, 2014[13]).

Gender profile of academic staff
At the tertiary level, the gender profile of teachers is reversed, with men making up the majority of academic staff
across OECD countries. On average across OECD countries, women represent 44% of tertiary academic staff,
ranging from 28% in Japan to 59% in the Russian Federation.
The gender profile of academic staff varies across programmes within tertiary education. Women are more
strongly represented in short-cycle tertiary programmes than in bachelor’s, master’s and doctoral programmes.
Specifically, women make up less than 50% of the teaching workforce at the bachelor’s, master’s and doctoral

EDUCATION AT A GLANCE 2019 © OECD 2019

D5. WHO ARE THE TEACHERS?  437

levels in over four-fifths of countries with available data and over 50% of the teaching workforce in short-cycle
tertiary programmes in about two-thirds of them (Figure D5.1).
The most prevalent fields at short-cycle tertiary level are also those that are typically dominated by women. For
example, in Latvia, where women make up over 60% of academic staff in short-cycle tertiary education, almost
60% of short-cycle tertiary programmes concern health and welfare, and services, which are fields where female
students tend to be over-represented (see Indicator B4 and Education at a Glance Database). Short-cycle tertiary
accounts for at most 20% of total tertiary enrolment in OECD countries, however, except in Australia, Canada,
Chile, Korea, New Zealand, Turkey and the United States (see Indicator B1 and Education at a Glance
Database). Although women may be over-represented in short-cycle tertiary education, they are still
under-represented among overall tertiary academic staff (Box D5.1).
Women represent less than 50% of academic staff at bachelor’s, master’s and doctoral level in all
OECD countries with available data except Finland (52%), Latvia (55%), Lithuania (57%) and New Zealand
(50%). They represent less than 40% in one-third of countries with available data and only make up 23% of the
academic staff in bachelor’s, master’s and doctoral programmes in Japan. Nonetheless, the representation of
women in tertiary education has been growing since 2005 in most OECD countries with available data (see
Education at a Glance Database).

Box D5.1. Representation of women in academia
Despite recent improvements, the gender imbalance in academia is still a challenge in most OECD countries,
starting among doctoral students and continuing throughout academic careers (Winslow and Davis, 2016[14]).
Specifically, women remain under-represented in the academic rank. Across European countries, women
account for only one-third of researchers and one-quarter of top academic rank (European Commission,
2019[15]), compared to nearly half at doctoral level (see Indicator B7). Female researchers are more likely than
men to work under contract arrangements that are considered “precarious employment” and considerable pay
gaps remain in scientific research and development occupations (European Commission, 2019[15]). Women
are similarly disadvantaged in other countries such as Australia (Winchester and Browning, 2015[16]) and the
United States (Curtis, 2011[17]). The gender imbalance is even more striking in certain fields, including the
science, technology, engineering and mathematics (STEM) fields.
Women’s career and progress in academia are more likely to be constrained by family obligations and the
lack of formal policies or programmes to reduce the gender gap (Winslow and Davis, 2016[14]). Recent policy
efforts across OECD countries have aimed to bring about structural change to increase women’s
representation in academia. For example, the European Union has heavily invested in the Institutional
Transformation for Effecting Gender Equality in Research (INTEGER) Project, in order to improve the career
paths of female researchers in European higher education and research institutions (European Commission,
2016[18]). In the United States, the National Science Foundation has funded research and interventions aiming
at increasing the representation of women in academic science and engineering, including the ADVANCE
Institutional Transformation grant programme (Winslow and Davis, 2016[14]). In Australia, the Universities
Australia Strategy for Women (2011-14) aimed at encouraging universities to include equity targets in their
strategic planning and promote women in academia (Winchester and Browning, 2015[16]). Most recently,
Australian universities have implemented gender quotas, with some opening academic positions in the faculty
of engineering, computer and mathematical sciences to women only (Pyke and White[19]). Nonetheless, the
continuing gender imbalance among academic staff in terms of participation, working conditions and pay
warrants further investments and research to close the gap in the future.

EDUCATION AT A GLANCE 2019 © OECD 2019

438  D5. WHO ARE THE TEACHERS?
Teachers’ age distribution
Teachers’ age distribution varies considerably across countries and levels of education, and can be affected by
a variety of factors, such as the size and age distribution of the population, the duration of tertiary education, and
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 to the labour market. Competitive
salaries, good working conditions and career development opportunities may attract young people to teaching in
some countries and, in others, help to retain effective teachers.
A large share of teachers are aged 50 and over. This share increases with the education level, from 33% in
primary education to 37% in lower secondary and 40% in upper secondary education. This pattern is quite striking
at the upper secondary level, where older teachers account for more than 30% of all teachers in more than twothirds of countries with available data. There is, however, a high level of cross-country variation, with figures
ranging from 15% in Turkey to 63% in Italy for upper secondary education. On average across OECD countries,
more than half of primary, lower secondary and upper secondary teachers are aged between 30 and 49.
At tertiary level, most academic staff are over the age of 40 in all countries with available data. In fact, at least
35% of academic staff are over 50 in all countries, except in Brazil (32%), Colombia (32%), Costa Rica (33%),
Germany (26%), Luxembourg (16%), the Netherlands (33%) and Turkey (19%). As for the share of tertiary
academic staff below the age of 30, it varies from less than 1% in Greece, Italy and Slovenia to 24% in Germany
(Education at a Glance Database).

Figure D5.2. Share of teachers less than 30 years old, by level of education (2017)

1. Upper secondary includes programmes outside upper secondary level.
2. Public and government-dependent private institutions only.
Countries are ranked in descending order of the share of teachers who are less than 30 years old in primary education.
Source: OECD/UIS/Eurostat (2019), Table D5.3. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933980317

In contrast, young teachers – under the age of 30 – make up only a small proportion of the teaching population,
at all levels of education: 13% in primary education, 11% in lower secondary and 8% in upper secondary on
average across OECD countries. This pattern is particularly striking at the upper secondary level: young teachers
make up less than 10% of the upper secondary teaching population in nearly two-third of countries with available
data and account for less than 5% in about one-third of them. Overall, teachers aged under 30 form less than
EDUCATION AT A GLANCE 2019 © OECD 2019

D5. WHO ARE THE TEACHERS?  439

25% of the teaching workforce at all levels of education and in all countries. The only exceptions are
the United Kingdom (where they make up over 30% of the teaching workforce at primary level) and Turkey (where
they make up 27% of the teaching force at the lower secondary level) (Table D5.1 and Figure D5.2).
The ageing of the teaching population has a number of implications for countries’ education systems. New
teachers will be needed to replace the staff who will reach retirement over the next decade, particularly in
countries where the school-age population is increasing (see Indicator B1). Governments may have to invest
further in the teaching profession to increase its attractiveness. In addition to these recruitment and training
needs, an ageing teaching workforce 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 2017
Trend data show that on average across OECD countries with available data, the share of teachers aged 50 and
older has increased by 5 percentage points over the past decade, for primary to upper secondary education
combined. Greece, Hungary, Lithuania, Poland, Portugal and Slovenia saw an increase of at least 13 percentage
points over this period (Education at a Glance Database), although in Poland the share of teachers aged 50 and
older remains lower than the OECD average. In contrast, in Estonia, Italy, Latvia and Lithuania the share of older
teachers is more than 10 percentage points higher than on average in other OECD countries and the teaching
population is still ageing.
Around one-third of countries with available data – namely Chile, France, Germany, Ireland, Luxembourg,
the United Kingdom and the United States – exhibit the opposite trend, and their teaching workforce has grown
younger. This may be explained, in part, by efforts to implement teacher recruitment policies. For instance,
the United Kingdom, which has seen the largest reduction in the share of older teachers, launched an ambitious
recruitment campaign in the early 2000s, aiming at improving the status of the teaching profession. The campaign
used slogans as “Use your head: teach” or “Turn your talent to teaching”, in order to appeal to youth who were
considering teaching as an option but were put off by several barriers, including the financial burden of the
training. In addition, the United Kingdom also provided financial support for teacher trainees (OECD, 2011[20]).
Similarly, Chile implemented the National Teachers Policy in 2017, which sets a new salary scale and
professional development system for teachers in publicly funded schools. It also introduced the “Teacher
Vocation” scholarship, which covers tuition fees for students in universities

Share of teachers in the population
Examining the share of teachers in the wider population by age group can provide another way to analyse the
evolution of the age distribution of the teaching workforce. In most OECD countries, primary and secondary
teachers make up a larger share of the wider population aged 50-59 years old than they do among the population
aged 25-34. The largest differences are in Greece, Italy, Lithuania and Portugal. Younger teachers make up a
larger share of the population than older teachers in less than one-quarter of countries (Figure D5.3).
Breaking down the share of primary and secondary teachers in the population by age group also highlights rising
concerns regarding possible future shortages. In Italy and Portugal, teachers represent only 0.6% or less of the
population aged 25-34, while they make up close to 3% of the population among 50-59 year-olds. The proportions
are similar across the two age groups in Brazil, Canada, France, Germany, Israel, the Netherlands, Norway,
Switzerland and the United States (Figure D5.3).
In most OECD countries, 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[21])). In parallel, fiscal constraints (particularly
driven by pension obligations and healthcare costs for retirees) may put pressure on governments to reduce
academic offerings, increase class sizes or integrate more self‑paced online learning (Peterson, 2011[22]).
EDUCATION AT A GLANCE 2019 © OECD 2019

440  D5. WHO ARE THE TEACHERS?

Figure D5.3. Share of primary and secondary teachers in the population, by age groups (2017)

1. Upper secondary includes programmes outside upper secondary level.
2. Primary includes pre-primary education.
3. Public and government-dependent private institutions only.
Countries are ranked in descending order of the share of teachers among 25-34 year-olds.
Source: OECD/UIS/Eurostat (2019), Education at a Glance Database, http://stats.oecd.org. See Source section for more information and Annex 3 for
notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933980336

Definitions
There are two categories of instructional personnel:


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 departmental chairs 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
The share of teachers in the population corresponds to the proportion of teachers in a given age group
(e.g.: 25-34 year-olds, 50-59 year-olds) among the total population of the same age group.
For more information, please see the OECD Handbook for Internationally Comparative Education Statistics 2018:
Concepts, Standards, Definitions and Classifications (OECD, 2018[23]) and Annex 3 for country-specific notes
(https://doi.org/10.1787/f8d7880d-en).

EDUCATION AT A GLANCE 2019 © OECD 2019

D5. WHO ARE THE TEACHERS?  441

Source
Data refer to the academic year 2016/17 and are based on the UNESCO-UIS/OECD/EUROSTAT data collection
on education statistics administered by the OECD in 2018 (for details, see Annex 3 at
https://doi.org/10.1787/f8d7880d-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: Evidence from a randomized experiment”, IZA Discusssion Papers, No. 6453,
http://ftp.iza.org/dp6453.pdf (accessed on 20 April 2018).

[9]

Beilock, S. et al. (2010), “Female teachers’ math anxiety affects girls’ math achievement.”, Proceedings
of the National Academy of Sciences of the United States of America, Vol. 107/5, pp. 1860-3,
http://dx.doi.org/10.1073/pnas.0910967107.

[12]

Croft, A. et al. (2014), “The second shift reflected in the second generation”, Psychological Science,
Vol. 25/7, pp. 1418-1428, http://dx.doi.org/10.1177/0956797614533968.

[3]

Curtis, J. (2011), Persistent Inequity: Gender and Academic Employment, American Association of
University Professors, Washington, DC, https://www.aaup.org/NR/rdonlyres/08E023AB-E6D84DBD-99A0-24E5EB73A760/0/persistent_inequity.pdf.

[17]

Drudy, S. (2008), “Gender balance/gender bias: the teaching profession and the impact of
feminisation”, Gender and Education, Vol. 20/4, pp. 309-323,
http://dx.doi.org/10.1080/09540250802190156.

[6]

European Commission (2019), She Figures 2018.

[15]

European Commission (2016), INTEGER Report Summary, http://www.integer-tools-for-action.eu.

[18]

Holmlund, H. and K. Sund (2008), “Is the gender gap in school performance affected by the sex of the
teacher?”, Labour Economics, Vol. 15/1, pp. 37-53, http://dx.doi.org/10.1016/j.labeco.2006.12.002.

[10]

Hutchings, M. et al. (2008), “Nice and kind, smart and funny: What children like and want to emulate in
their teachers”, Oxford Review of Education, Vol. 34/2, pp. 135-157,
http://dx.doi.org/10.1080/03054980701663959.

[11]

Kane, J. and J. Mertz (2012), “Debunking myths about gender and mathematics performance”, Notices
of the AMS, Vol. 59/1, http://dx.doi.org/10.1090/noti790.

[4]

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.

[23]

EDUCATION AT A GLANCE 2019 © OECD 2019

442  D5. WHO ARE THE TEACHERS?
OECD (2017), “Gender imbalances in the teaching profession”, Education Indicators in Focus, No. 49,
OECD Publishing, Paris, http://dx.doi.org/10.1787/54f0ef95-en.

[2]

OECD (2015), “What lies behind gender inequality in education?”, PISA in Focus, No. 49, OECD
Publishing, Paris, http://dx.doi.org/10.1787/5js4xffhhc30-en.

[1]

OECD (2014), Education at a Glance 2014 : OECD Indicators, OECD Publishing,
http://dx.doi.org/10.1787/eag-2014-en.

[21]

OECD (2014), PISA 2012 Results: What Students Know and Can Do (Volume I, Revised edition,
February 2014): Student Performance in Mathematics, Reading and Science, PISA, OECD
Publishing, Paris, http://dx.doi.org/10.1787/9789264208780-en.

[5]

OECD (2014), TALIS 2013 Results: An International Perspective on Teaching and Learning, OECD
Publishing, Paris, http://dx.doi.org/10.1787/9789264196261-en.

[13]

OECD (2011), Lessons from PISA for the United States, Strong Performers and Successful Reformers
in Education, OECD Publishing, Paris, https://dx.doi.org/10.1787/9789264096660-en.

[20]

OECD (2009), Creating Effective Teaching and Learning Environments: First Results from TALIS,
OECD Publishing, Paris, http://dx.doi.org/10.1787/9789264068780-en.

[8]

OECD (2005), Teachers Matter: Attracting, Developing and Retaining Effective Teachers, OECD
Publishing, Paris, http://dx.doi.org/10.1787/9789264018044-en.

[7]

Peterson, P. (2011), Saving schools : from Horace Mann to virtual learning, Belknap Press of Harvard
University Press.

[22]

Pyke, J. and K. White (n.d.), “Are gender quotas in academia a good idea?”,
https://www.weforum.org/agenda/2018/09/gender-quotas-may-speed-up-equity-in-academia
(accessed on 16 May 2019).

[19]

Winchester, H. and L. Browning (2015), “Gender equality in academia: a critical reflection”, Journal of
Higher Education Policy and Management, Vol. 37/3, pp. 269-281,
http://dx.doi.org/10.1080/1360080X.2015.1034427.

[16]

Winslow, S. and S. Davis (2016), “Gender inequality across the academic life course”, Sociology
Compass, Vol. 10/5, pp. 404-416, http://dx.doi.org/10.1111/soc4.12372.

[14]

Indicator D5 Tables
Table D5.1

Age distribution of teachers (2017)

Table D5.2

Gender distribution of teachers (2017)

Table D5.3

Gender distribution of teachers by age group (2017) and percentage of female teachers for
all ages (2005 and 2017)

Cut-off date for the data: 19 July 2019. 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.
StatLink: https://doi.org/10.1787/888933981267
EDUCATION AT A GLANCE 2019 © OECD 2019

D5. WHO ARE THE TEACHERS?  443

Table D5.1. Age distribution of teachers (2017)
Percentage of teachers in public and private institutions, by level of education and age group, based on head counts

1. Primary includes pre-primary education.
2. Upper secondary includes programmes outside upper secondary level - see Annex 3 for further details.
3. Public and government-dependent private 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.
Source: OECD/UIS/Eurostat (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888933980241

EDUCATION AT A GLANCE 2019 © OECD 2019

444  D5. WHO ARE THE TEACHERS?
Table D5.2. Gender distribution of teachers (2017)
Percentage of female teachers in public and private institutions by level of education, based on head counts

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 includes programmes outside upper secondary level - see Annex 3 for further details.
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. Year of reference 2016 instead of 2017
Source: OECD/UIS/Eurostat (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888933980260

EDUCATION AT A GLANCE 2019 © OECD 2019

D5. WHO ARE THE TEACHERS?  445

Table D5.3. Gender distribution of teachers by age group (2017) and percentage of female teachers for all ages (2005 and 2017)
Percentage of female teachers, by age group and level of education

1. Primary includes pre-primary education.
2. Upper secondary includes programmes outside upper secondary level - see Annex 3 for further details.
3. Public and government-dependent private institutions only for all levels except for tertiary. For tertiary education, public institutions only.
4. Year of reference 2006 instead of 2005.
5. For Ireland, public institutions only. For Israel, private institutions are included for all levels except for pre-primary and upper secondary levels.
6. Tertiary includes programmes outside tertiary level - see Annex 3 for further details.
Source: OECD/UIS/Eurostat (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888933980279

EDUCATION AT A GLANCE 2019 © OECD 2019

446  D6. WHAT ARE THE ADMISSION SYSTEMS FOR TERTIARY EDUCATION?

Indicator D6. What are the admission systems
for tertiary education?
Highlights


More than half of countries and economies with available data have open admissions systems
(meaning all applicants with the minimum qualification level required are admitted) to at least some
public and/or private institutions. Access to certain fields of education and/or institutions can still be
subject to some selection criteria in these countries.



National/central examinations, taken towards the end of upper secondary education, and entrance
examinations administered by tertiary institutions, are the most widely used examinations/tests for
entry into first-degree tertiary programmes.



Factors other than the results of national/central examinations are also taken into account by selective
institutions in most countries, although used to differing extents. The criteria most used for admission
to public tertiary institutions are grade point averages, candidate interviews and work experience.

Figure D6.1. Use of limits on number of students entering fields of education and institutions within
countries with open and selective systems (2017)

How to read this figure: First-degree tertiary programmes within countries with open admissions systems can still be subject to limitations on the
number of places available, either by field of education or institution. These limits may affect all fields of education or types of institutions, only some,
or none at all. Similarly, for countries with selective systems, limits may be set with reference to field of study and/or institutions. As such, a country
with a selective system may still report no limits (none) for one of these dimensions.
Note: Of the 38 countries that participated in the survey, this figure does not include those for which the information is missing or not applicable.
Source: OECD (2017), Tables D6.1a, D6.1b and D6.1c. See Source section for more information and Annex 3 for notes
(https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933980412

EDUCATION AT A GLANCE 2019 © OECD 2019

D6. WHAT ARE THE ADMISSION SYSTEMS FOR TERTIARY EDUCATION?  447

Context
Increasing numbers of students are enrolling in tertiary education across OECD countries. This expansion in
enrolment reflects a variety of factors. First, more students are achieving the minimum educational attainment
required to enter tertiary institutions, which in turn increases the potential demand for tertiary education
(see Indicator B3). At the same time, the positive relationship between educational attainment levels and
opportunities in the labour market may further increase demand, especially in countries with high
unemployment rates or when there is an economic crisis: the strong personal financial incentives to invest in
education could encourage individuals with a secondary qualification to continue their studies
(see Indicators A4 and A5).
Tertiary enrolment is also affected by the number of places available within tertiary institutions. Given the rising
demand for tertiary education, educational institutions and policy makers face new challenges in ensuring
there are enough student places. In the meantime, increased demand could result in increased competition
between students wishing to enter tertiary education. Decisions about the number of places available in the
different fields of tertiary education are more strongly linked to the needs of the labour market in some
countries than in others. This matching of skills of tertiary-educated people to meet labour-market demand
may have an impact on enrolment and the selectivity of admissions to different fields of tertiary education.
Admission systems to tertiary education may be designed to combine different objectives. On the one hand,
admission criteria may be used to ensure that applicants have the skills to successfully complete the
educational programme they apply to (see Indicator B5). On the other hand, fewer admission criteria may help
to provide a larger access to tertiary studies and meet equity concerns.
Analysis of the national criteria and admission systems for students to apply and enter first-degree tertiary
programmes highlights differences across countries between open and selective admission systems and the
proportions of applicants who successfully meet admission criteria and processes. However, this does not
cover the selectivity that may occur during studies (for example students dropping out of a programme as they
fail in intermediate tests or do not progress at the desired pace).

Other findings


In about half of countries and economies with available information, the government sets minimum
academic performance requirements for entry into tertiary education (for first degrees) by field of
education and/or by tertiary institution, on top of the usual qualification requirements. These
performance requirements are most often based on secondary school certificates or report cards,
including students’ grades or the results of upper secondary national/central examinations.



In more than two-thirds of the countries and economies with available data, national/central
examinations, other standardised tests at upper secondary level and/or entrance examinations to
tertiary institutions are compulsory requirements to enter at least some fields of study in public tertiary
institutions.



Students are required to apply directly to public tertiary institutions in nearly half the countries and
economies, while a similar number of countries use a centralised system or a combination of both
approaches for admission to public institutions. Applications to private tertiary institutions are less
frequently processed through a centralised application system.



Application and admission systems to first-degree tertiary programmes (in public and private
institutions) are similar for national and non-national or international students in about half the countries
and economies with available data.

EDUCATION AT A GLANCE 2019 © OECD 2019

448  D6. WHAT ARE THE ADMISSION SYSTEMS FOR TERTIARY EDUCATION?

Analysis
Organisation of the system: Open versus selective admissions
Admission systems to first-degree tertiary programmes reflect the way tertiary education is structured and
organised within countries. Public institutions are a common feature of tertiary education systems in nearly all
the countries and economies with available data and most tertiary students are enrolled in public institutions on
average across OECD countries (see Figure B1.3). Private tertiary institutions are almost as widespread, with
only Denmark and Greece not having any government-dependent or independent private institutions for
first-degree tertiary programmes. In around half the countries and economies with available data, governmentdependent private institutions are also part of the tertiary education landscape (Table D6.1a, and Tables D6.1b
and D6.1c available on line).
The use of open admissions, or unselective enrolment – the admission of all applicants with the required
attainment level into first-degree tertiary programmes –, is fairly common among both public and private tertiary
institutions. Half of the countries and economies with available information on public institutions have at least
some institutions with open admission systems. The prevalence of open admissions systems in private tertiary
institutions is similar: nearly half of all countries and economies with government-dependent private institutions
and nearly half of those with independent private institutions report the use of open admission systems in at least
some of these tertiary institutions. However, open admission systems may still include some limits on the number
of places available in first-degree tertiary programmes (Figure D6.1). Enrolment can be limited for specific fields
of education and/or for specific tertiary institutions, with entry decided on the basis of some selection criteria
(Table D6.1a, and Tables D6.1b and D6.1c, available on line).

Limitations on the number of places in specific fields of study
For public tertiary institutions, half of countries and economies with available data (18 out of 36 countries and
economies) have an open admission system, and most of these countries have some limitations in the admission
system for at least some fields of study. For example, in Germany, enrolment into some fields of study is limited,
using quotas if the total number of applicants exceeds the number of places available across all higher education
institutions. For these fields a selection procedure applies, which takes into account the grade obtained in the
Abitur (the upper secondary school-leaving examination in Germany, also used as the higher education entrance
qualification). In New Zealand, there is a fixed number of places for certain subjects, such as dentistry, aviation,
veterinary science and medical degrees. Limits on the number of students entering into health/medical
programmes are a feature of admission to public tertiary institutions in several other countries (Table D6.1a).
Similar use of numerical limits can be observed among government-dependent private and independent private
institutions (Tables D6.1b and D6.1c, available on line).
Half of the countries with available information operate selective admission systems for first-degree tertiary
programmes in public institutions. Compared with countries with an open system, a smaller proportion of these
countries have limitations on the number of places by field of study. However, when limitations are set, they are
usually for all fields rather than for some of them. Among government-dependent private and independent private
institutions, numerical limitations are also set for all fields of study in selective systems, and for some fields only
in open systems (Figure D6.1). These limitations on the number of places may affect the selectiveness of the
different fields (Box D6.1).

Limitations on the number of places in specific institutions
Countries with selective systems are more likely to have limits on enrolment into particular tertiary institutions
than on fields of studies. These limitations are then set for all institutions within public, government-dependent
and independent private institutions.

EDUCATION AT A GLANCE 2019 © OECD 2019

D6. WHAT ARE THE ADMISSION SYSTEMS FOR TERTIARY EDUCATION?  449

In public institutions, among the 18 countries with selective systems, 13 countries set limits on enrolment in
first-degree tertiary programmes for all institutions. For example, in Turkey these limits on enrolment are decided
by central authorities for all public institutions. However, countries with open admission systems may also have
limits on enrolment in tertiary institutions. For example in the United States, limits on enrolment are set by the
institutions themselves. In general, tertiary institutions within the United States encompass a broad range of
selectivity since admission decisions are made at the institution level. While many institutions are open admission,
others are moderately or highly selective (Figure D6.1).
There are similar patterns in admission systems for government-dependent private and independent private
institutions. However, the central level is less often the only responsible authority to set enrolment limits in these
types of institutions. The central level is the only responsible authority to set these limits on enrolment in Israel
(for all government-dependent private institutions) and in Turkey (for all independent private institutions)
(Tables D6.1b and D6.1c, available on line).

Box D6.1. Attractiveness and selectivity of different fields of study
In 2017, to complement the data collection on admission systems to first-degree tertiary programmes, the
OECD carried out a survey on the number of applicants and applications to first-degree tertiary programmes.
Among the 30 countries and economies that responded to the survey, about half provided some breakdown
of the data on applications and/or applicants by field of studies.
Only 11 countries provided the necessary data to compute the number of applications per applicant in the
different fields of study. These ratios vary widely across countries and across fields in these countries.
However, their interpretation is difficult as their values are related to the characteristics of the admission
system. For example, in countries with central admission systems, students make only one application with
different preferences (that are not necessarily counted as several applications), whereas in countries without
central admission systems, similar preferences would result in multiple applications. Moreover, the amount of
fees and their differentiation between fields may also have an impact on applications.
Another way to estimate the attractiveness and selectivity of a field is to look at the results of applicants’
applications, although this does not allow selectivity to be distinguished from attractiveness. As an applicant
can make several applications, the best result of these applications is taken into account for the analysis.
Either the applicant is accepted and studying; or the applicant is accepted but not studying; or the applicant
is rejected when all applications have failed. Only 14 out of 30 countries that submitted the questionnaire
provided a breakdown of the number of applicants in each field of education by the best results of their
applications, so that applicants are counted only once (Figure D6.a). The fact that this breakdown of the data
is not available in some countries may result from the existence of open admission systems allowing students
to enter the field of their choice without a specific application process. This is the case in the French and
Flemish communities of Belgium.
Among countries with available data, the distribution of applicants by the best result of their applications varies
widely between countries, and also between the different fields of education within countries. For example, in
Australia, the proportions of applicants accepted and studying varies by less than 10 percentage points across
fields of education, from 83% (agriculture, forestry, fisheries and veterinary) to 91% (information and
communication technologies), whereas in Denmark, it varies by 40 percentage points, from 32% (health and
welfare) to 73% (natural sciences, mathematics and statistics). Among these 14 countries, the fields with the
lowest or highest proportions of applicants accepted and studying also vary between countries. Health and
welfare is the broad fields with the lowest proportion of applicants accepted and studying in five countries,
whereas engineering, manufacturing and construction is the fields with the highest proportions in
five countries. Low proportions of applicants accepted and studying may result from fields being highly
attractive and/or highly selective (Figure D6.a).

EDUCATION AT A GLANCE 2019 © OECD 2019

450  D6. WHAT ARE THE ADMISSION SYSTEMS FOR TERTIARY EDUCATION?

Figure D6.a. Applicants to first-degree tertiary education by applicant status, by fields of study (2016)
Fields of studies with the minimum and maximum proportions of applicants accepted and studying.

1. Applicants accepted, not studying also includes applicants rejected.
2. Year of reference 2017.
Countries are ranked in decreasing order of the difference in the proportion of applicants accepted and studying between the two fields of studies
selected.
Source: 2017 OECD-INES NESLI survey on applicants and applications to tertiary education.
Statlink2 https://doi.org/10.1787/888933980450

The proportions of rejected applicants and applicants who have been accepted but are not studying (deferred),
also vary widely between countries and fields of education. However, the proportion of applicants accepted
but not studying is usually much smaller in all countries and in all fields.
These differences in the proportions of applicants accepted and studying, accepted and not studying, and
rejected according to fields of education provide some insight into the selectivity of these different fields and/or
their attractiveness. However, these figures should be interpreted with caution, because these results come
in the context of more general patterns in countries’ application systems. For example, these comparisons
can be affected by international students: large proportions of international students applying to tertiary
education can bias the comparison, especially if these students do not apply to similar fields as other students.

EDUCATION AT A GLANCE 2019 © OECD 2019

D6. WHAT ARE THE ADMISSION SYSTEMS FOR TERTIARY EDUCATION?  451

Qualification and performance requirements to enter first-degree tertiary programmes
In all countries, access to first-degree tertiary programmes (in public or private institutions) requires a minimum
qualification level, which is usually an upper secondary qualification. Governments may also require some
minimum academic performance from upper secondary graduates to access first-degree tertiary programmes
(Table D6.3).
In half of the countries and economies with available information (19 out of 38), the government also sets
minimum academic performance requirements for students to enter at least some first-degree tertiary
programmes or institutions. These minimum requirements are more often set for specific fields of study rather
than specific tertiary institutions. In 14 countries, minimum performance criteria are defined for some or all fields
of studies, whereas only 8 have minimum performance criteria for some or all tertiary institutions. In Colombia,
Greece and Portugal, these performance requirements relate to both fields of studies and tertiary institutions
(Table D6.3).
Countries may use a range of different tools to assess students’ minimum performance, but the most frequently
used are secondary school certificates or report cards (including students’ grades) and the results of upper
secondary national/central examinations (Table D6.3).

Examinations and tests used by public tertiary institutions to determine access to first-degree
programmes
On top of entrance examinations administered to applicants to tertiary institutions, several types of examinations
or tests administered to upper secondary students can also be used in the admission system (national/central
examinations, non-national/central standardised examinations and non-national/central non-standardised
examinations). There is wide variation among countries in the combination of different types of examinations
available and on the way these are used as criteria for access to tertiary education. Among all countries with
available information, only Latvia has all these types of examinations/tests (although they are not all used to
determine access to tertiary education). In contrast, in countries such as Brazil, Colombia, Denmark, Hungary,
Italy, Portugal and Spain, only national/central examinations exist (and are used in some of these countries to
determine access to tertiary education).
The completion of national/central examinations towards the end of upper secondary education and/or entrance
examinations to tertiary education (not administered by upper secondary schools) can be compulsory
requirements to access first-degree programmes. In more than half of countries, the completion of
national/central examinations (standardised tests that have a formal consequence for students) is compulsory to
enter most or all public tertiary institutions. Entrance examinations are compulsory to enter public tertiary
institutions for at least some fields of study in one-third of countries. In some countries, such as Estonia, Latvia,
Lithuania, Luxembourg, Norway, the Russian Federation, Slovenia and Switzerland, students must take both
types of tests to enter some fields of study. Other examinations (non-national/central examinations either
standardised or non-standardised) are compulsory in very few countries (Table D6.2a).
These examinations and tests can be used in the admission process even when they are not compulsory.
National/central examinations at the end of upper secondary level are used for entry into fields of study in public
institutions in most countries with available data (23 countries). Entrance examinations to public institutions are
also administered and used for admission in at least some fields of study in about half of the countries with
available data (17 countries) (Table D6.5a).
For public institutions, these two types of tests are of particular relevance for students wishing to access tertiary
institutions or specific fields or specialisations that are selective and/or in high demand. Public institutions in
six countries also use these results for making decisions about scholarships and other financial assistance
(Figure D6.2).

EDUCATION AT A GLANCE 2019 © OECD 2019

452  D6. WHAT ARE THE ADMISSION SYSTEMS FOR TERTIARY EDUCATION?

Figure D6.2. Purposes and uses of national/central examinations as admission criteria to tertiary
institutions (2017)
National/central examinations refer to examinations for students at the end of upper secondary level

Source: OECD (2017), Tables D6.5a, D6.5b and D6.5c. See Source section for more information and Annex 3 for notes
(https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933980431

Additional factors used for admission to first-degree tertiary programmes
Admission criteria for first-degree tertiary programmes extend beyond the results of examinations and tests of
students. For entry into public tertiary institutions, grade point averages from secondary school are used in onethird of countries (with either open or selective admission systems) with a further one-quarter of countries
reporting that institutions have autonomy over their use. However, this factor was considered to be of moderate
or high importance in determining the success of a student’s application in over half of these countries. More than
two-thirds of countries indicate that candidate interviews are used, either across all public tertiary institutions
(one-quarter of countries) or at the discretion of public tertiary institutions (more than one-third of countries)
(Table D6.2a).
In a significant number of countries, public institutions also use other factors to determine access to first-degree
programmes (e.g. past work experience, family income, recommendations). Most often, they are used in
combination. An exception is Hungary, which uses only one criterion (grade point average from secondary
schools) in addition to the successful completion of national examinations (Table D6.2a).
Grade point averages from secondary school, interviews and past work experience are also the most frequently used
criteria in the admission process to first-degree programmes in private tertiary institutions (government-dependent and
independent private institutions). However, in contrast to admission systems to public tertiary institutions, the use of
these criteria is largely at the discretion of institutions (Tables D6.2b and D6.2c available on line).
EDUCATION AT A GLANCE 2019 © OECD 2019

D6. WHAT ARE THE ADMISSION SYSTEMS FOR TERTIARY EDUCATION?  453

More generally, the number of factors used in the admission systems combined with the difficulty to meet these
criteria may increase the selectivity of these admission systems. Another proxy for the degree of selectivity may
relate to the proportion of applicants who are not successful in the applications. The most selective systems may
be those with the highest proportions of applicants whose applications were rejected (Box D6.2).

Box D6.2. Variation in the proportion of applicants 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, based on the best result of their applications (Figure D6.b). In this figure, the
proportion of rejected applicants reflects the share of applicants who did not receive a positive answer to any
of the applications that they may have made.
The proportion of rejected applicants 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. In
Australia, France, Portugal and the Slovak Republic, less than 15% of applicants are rejected, but these
countries’ admission systems differ widely. France has an open admission system with selection limited to
some fields or institutions (among public institutions that enrolled most of the students). In Australia, Portugal
and the Slovak Republic, there are different limitations in the number of places offered to students. In
Australia, there are no limitations in the number of available positions in different institutions or fields of study
(with the exception of medicine); in the Slovak Republic, there are limitations only on some public institutions;
and in Portugal, there are limitations on all fields and all institutions.

Figure D6.b. Applicants to first-degree tertiary education by applicant status (2016)

1. Including applicants to short-cycle tertiary programmes.
2. Year of reference 2017.
Countries are ranked in descending order of the proportion of applicants accepted and studying.
Source: 2017 OECD-INES NESLI survey on applicants and applications to tertiary education.
Statlink2 https://doi.org/10.1787/888933980469

These differences between countries show that limitations exist, but do not necessarily show the degree of
selectivity of the whole system. More details on the total number of positions available would be necessary to

EDUCATION AT A GLANCE 2019 © OECD 2019

454  D6. WHAT ARE THE ADMISSION SYSTEMS FOR TERTIARY EDUCATION?
assess how selective the tertiary education system is. Moreover, when the main selection of students to
academic tracks is done at secondary level, there might not need to be strong selection as such to enter
tertiary education, but the admission process could still be selective.
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 to defer enrolment
may explain the differences between the number of successful applicants and new entrants.

Student application and admission processes to tertiary institutions
Application and admission processes to first-degree tertiary programmes in public institutions vary significantly
between countries. Students are required to apply directly to public tertiary institutions in close to half of the
countries with available information, while in around one-quarter of countries students apply through a centralised
system. The remaining countries combine a centralised application system with direct applications to public
tertiary institutions.
When a centralised system is used (either as the only application system or in combination with direct applications),
the number of preferences that students can specify may be limited, as can the number of offers they receive
following their applications. The number of preferences an applicant can specify when applying to public institutions
cannot exceed 2 in Brazil and 3 in Canada, the Netherlands, Slovenia and the Russian Federation, but applicants
can specify 20 or more preferences in France and Turkey. In Italy and New Zealand, there is no maximum number
of applications. In Greece, the number of preferences is not restricted, except in the two scientific domains that a
candidate is eligible to choose (among the five scientific domains possible). Regardless of the maximum number of
applications, applicants receive just one offer in most countries with a centralised system. Nevertheless, there is no
limit on the number of offers made in Australia, Canada, Italy and Korea, which use combined centralised and direct
application systems to tertiary institutions (Table D6.1a).
Applications to private tertiary institutions are less likely to be processed through a centralised application system.
However, a central system is the only (or main) way to apply to private institutions in a few countries (Chile,
Finland and Sweden for government-dependent private institutions, and Hungary and Turkey for independent
private institutions). Applications are made directly to private institutions in nearly half of the countries with
government-dependent private institutions, and in most countries with independent private institutions. However,
one-third of countries with these types of tertiary institutions combine a centralised application system with a
direct application process (Tables D6.1b and D6.1c, available on line).

Application and admission process for non-national or international students
The international mobility of tertiary students has increased a lot in recent years (see Indicator B6) and admission
systems to tertiary education can play a role to promote (or not) this pattern. As noted in Education at a Glance
2017 (OECD, 2017[1]), around half of countries and economies have similar systems for non-national or
international students as for national students (either citizens or permanent residents in the country). In
one-quarter of countries, international applicants from some countries undergo a similar process as for national
applicants. This is usually the case for applicants from European Union (EU) countries applying to tertiary
institutions in another EU country but is also the case, for example, in Norway for national students and
international students from the other Nordic countries. In one-quarter of countries, the application and admission
process for non-national or international students is different to that for national students.
Even where application systems are similar for non-national or international and national students, additional or
specific admission criteria are used for international students (Table D6.9 in OECD (2017[1])). These differences,
combined with differences in tuition fees and other factors, may have an impact on the applications or on the
results of the applications of international students (Box D6.3).
EDUCATION AT A GLANCE 2019 © OECD 2019

D6. WHAT ARE THE ADMISSION SYSTEMS FOR TERTIARY EDUCATION?  455

Box D6.3. Applicants and applications to tertiary education, by international status of applicants
In the 2017 survey on the number of applicants and applications to first-degree tertiary programmes, about
one-third of the 30 countries and economies that responded to the survey provided some breakdown of the
data distinguishing international students from others.
Nine countries provided data to distinguish international applicants from others in the distribution of applicants
by the outcomes of their applications (accepted and studying, accepted and not studying, and rejected). In
these countries, the number of applications per applicant is usually similar for international students and others
(Figure D6.c). The proportions of rejected applicants are also mostly similar between international applicants
and others in Finland, Hungary and Israel (a difference of less than 10 percentage points). However, the
difference between these proportions exceeds 20 percentage points in Denmark (where international
applicants represent 18% of all applicants) and Slovenia (where international applicants account for less than
6% of applicants).

Figure D6.c. Applicants to first-degree tertiary education, by applicant status and international status
of applicants (2016)

Note: The figure in parentheses refers to the proportion of international applicants among all applicants.
Countries are ranked in descending order of the difference in the proportion of applicants rejected between international applicants and others.
Source: 2017 OECD-INES NESLI survey on applicants and applications to tertiary education.
Statlink2 https://doi.org/10.1787/888933980488

While in some countries, there are specific admissions processes for non-national/international students to
tertiary education, in these countries, there was no differentiation as such. However, additional or specific
admission criteria are used for international applicants in all these countries, except Denmark (the information
was missing for the Slovak Republic). The seven countries with available information request the successful
completion of home country school system and an accredited home country school certificate. Most of these
countries also required an international qualification and language proficiency as part of their criteria. None of
them requested proof of sufficient funds [Table D6.9 (OECD, 2017[1])].

EDUCATION AT A GLANCE 2019 © OECD 2019

456  D6. WHAT ARE THE ADMISSION SYSTEMS FOR TERTIARY EDUCATION?

Definitions
A standardised examination or test refers to a test that is administered and scored under uniform conditions
across different schools so that student scores are directly comparable between schools. In some cases, it also
refers to multiple choice or fixed answer questions as this makes it easy and possible to score the test uniformly.
However, with rubrics and calibration of test examiners (persons who manually score open-ended responses),
one can also find standardised tests that go beyond multiple choice and fixed answers.
National/central examinations are standardised tests that have a formal consequence for students, such as
their eligibility to progress to a higher level of education or to complete an officially recognised degree. They
assess a major portion of what students are expected to know or be able to do in a given subject. Examinations
differ from assessments in terms of their purpose. National assessments are mandatory but, unlike
examinations, they do not have an effect on students’ progression or certification.
Other (non-national/central) standardised examinations are standardised tests that are administered and
scored under uniform conditions across different schools at the state/territorial/provincial/regional or local level
so that student scores are directly comparable.
Entrance examinations are examinations not administered by upper secondary schools that are typically used
to determine, or help to determine, access to tertiary programmes. These examinations can be devised and/or
graded at the school level (i.e. by individual tertiary institutions or a consortium of tertiary institutions), or by
private companies.
First-degree tertiary programmes refer to first-degree bachelor's programmes/applied higher education
programmes and first-degree master's programmes as defined in ISCED 2011.
Open admission: An open or unselective admission system (as opposed to selective systems) to tertiary
programmes refers to a system in which all applicants with the required minimum attainment level can enrol in
the programme, without the need to meet other criteria.
Public tertiary institution: An institution is classified as public if it is: 1) controlled and managed directly by a
public education authority or agency of the country where it is located; or 2) controlled and managed by a
government agency directly or by a governing body (council, committee etc.), most of whose members are either
appointed by a public authority of the country where it is located or elected by public franchise.
A government-dependent private tertiary institution is one that either receives at least 50% of its core funding
from government agencies or one whose teaching personnel are paid by a government agency – either directly
or through government
An independent private tertiary institution is one that receives less than 50% of its core funding from
government agencies and whose teaching personnel are not paid by a government agency.

Methodology
This indicator is based on a survey on national criteria and admission systems for students to apply and enter
first-degree tertiary programmes focusing on formal requirements, rather than actual practice. As practices can
vary considerably within individual schools and tertiary institutions, this indicator cannot capture the diverse array
of practices that exist.
Please see Annex 3 for more information and for country-specific notes (https://doi.org/10.1787/f8d7880d-en).

EDUCATION AT A GLANCE 2019 © OECD 2019

D6. WHAT ARE THE ADMISSION SYSTEMS FOR TERTIARY EDUCATION?  457

Source
Data are from two surveys: the 2016 OECD-INES NESLI survey on national criteria and admission systems for
students to apply and enter first-degree tertiary programmes, which refers to the school year 2016/17, and the
2017 OECD-INES NESLI survey on applicants and applications to tertiary education, which refers to the school
year 2015/16.
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 (2017), Education at a Glance 2017: OECD Indicators, OECD Publishing,
Paris, https://dx.doi.org/10.1787/eag-2017-en.

[1]

Indicator D6 Tables
Table D6.1a

Organisation of admission system and application process to first-degree tertiary programmes
in public institutions (2017)

WEB Table D6.1b Organisation of admission system and application process to first-degree tertiary
programmes in government-dependent private institutions (2017)
WEB Table D6.1c Organisation of admission system and application process to first-degree tertiary programmes
in independent private institutions (2017)
Table D6.2a

Examinations and additional criteria used for admission to first-degree tertiary programmes in
public institutions (2017)

WEB Table D6.2b Examinations and additional criteria used in admission system to first-degree tertiary
programmes in government-dependent private institutions (2017)
WEB Table D6.2c Examinations and additional criteria used in admission system to first-degree tertiary
programmes in independent private institutions (2017)
Table D6.3

Minimum qualification and academic performance requirements for entry into tertiary
education (government perspective) (2017)

WEB Table D6.4 Authorities responsible for examination systems for entry/admission into first-degree tertiary
programmes (2017)
WEB Table D6.5a Purposes and uses of examinations/tests in criteria to determine entry/admission into firstdegree tertiary programmes at public institutions (2017)

EDUCATION AT A GLANCE 2019 © OECD 2019

458  D6. WHAT ARE THE ADMISSION SYSTEMS FOR TERTIARY EDUCATION?
WEB Table D6.5b Purposes and uses of examinations/tests in criteria to determine entry/admission into firstdegree tertiary programmes at government-dependent private institutions (2017)
WEB Table D6.5c Purposes and uses of examinations/tests in criteria to determine entry/admission into firstdegree tertiary programmes at independent private institutions (2017)
Cut-off date for the data: 19 July 2019. Any updates on data can be found on line at
https://doi.org/10.1787/f8d7880d-en.
StatLink: https://doi.org/10.1787/888933981286

EDUCATION AT A GLANCE 2019 © OECD 2019

D6. WHAT ARE THE ADMISSION SYSTEMS FOR TERTIARY EDUCATION?  459

Table D6.1a. Organisation of the admission system and application process to first-degree tertiary programmes in public
institutions (2017)

Note: See Definitions and Methodology sections for more information.
1. There is no maximum number of preferences an applicant can specify in a few fields. Certain constraints may apply in others.
2. For national universities, the fixed number of students is decided by each national university and is submitted as a part of its mid-term plan to be approved by the Minister
of Education, Culture, Sports, Science and Technology.
Source: OECD (2017). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888933980355

EDUCATION AT A GLANCE 2019 © OECD 2019

460  D6. WHAT ARE THE ADMISSION SYSTEMS FOR TERTIARY EDUCATION?
Table D6.2a. . Examinations and additional criteria used for admission to first-degree tertiary programmes in public
institutions (2017)

EDUCATION AT A GLANCE 2019 © OECD 2019

D6. WHAT ARE THE ADMISSION SYSTEMS FOR TERTIARY EDUCATION?  461

Note: See Definitions and Methodology sections for more information.
1. Except for first-degree tertiary programme entrance examinations administered by tertiary institutions, these examinations/tests are administered by upper secondary
institutions (for students at the end of this level).
2. For national universities, the fixed number of students is decided by each national university and is submitted as a part of its mid-term plan to be approved by the Minister
of Education, Culture, Sports, Science and Technology.
Source: OECD (2017). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888933980374

EDUCATION AT A GLANCE 2019 © OECD 2019

462  D6. WHAT ARE THE ADMISSION SYSTEMS FOR TERTIARY EDUCATION?
Table D6.3. Minimum qualification and academic performance requirements for entry into tertiary education (government
perspective) (2017)

Note: Typical minimum qualification for entry into first-degree tertiary programmes refers to the ISCED level required, but not all qualifications at this level allow entry into
these first-degree tertiary programmes. See Definitions and Methodology sections for more information.
1. Minimum qualification requirement is the Upper Secondary School Leaving Certificate (called MATURA); additional entry routes exist.
2. Some vocational programmes at upper secondary level allow access to tertiary education, whereas others do not.
3. In Lithuania, it is possible to enter tertiary programmes with a qualification level from upper secondary (all programmes) or post-secondary non-tertiary (vocational
programmes).
4. Information relates to the four separate systems across the United Kingdom. In each case, "yes" indicates the policy is in place in at least one of the four countries.
Source: OECD (2017). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888933980393

EDUCATION AT A GLANCE 2019 © OECD 2019

ANNEX 1. CHARACTERISTICS OF EDUCATION SYSTEMS  463

Annex 1. Characteristics of education systems

All tables in Annex 1 are available on line at:
StatLink: https://doi.org/10.1787/888933981305

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 2019 © OECD 2019

464  ANNEX 1. CHARACTERISTICS OF EDUCATION SYSTEMS
Table X1.1a. Typical graduation ages, by level of education (2017)
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.

1. Year of reference 2016.
Source: OECD (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888933980507

EDUCATION AT A GLANCE 2019 © OECD 2019

ANNEX 1. CHARACTERISTICS OF EDUCATION SYSTEMS  465

Table X1.1b. Typical age of entry, by level of education (2017)
The typical age refers to the age of the students at the beginning of the school year.

1. Year of reference 2016.
Source: OECD (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888933980526

EDUCATION AT A GLANCE 2019 © OECD 2019

466  ANNEX 1. CHARACTERISTICS OF EDUCATION SYSTEMS
Table X1.2a. School year and financial year used for the calculation of indicators, OECD countries

Source: OECD (2018). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933980545

EDUCATION AT A GLANCE 2019 © OECD 2019

ANNEX 1. CHARACTERISTICS OF EDUCATION SYSTEMS  467

Table X1.2b. School year and financial year used for the calculation of indicators, partner countries

Source: OECD (2018). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Statlink2 https://doi.org/10.1787/888933980564

EDUCATION AT A GLANCE 2019 © OECD 2019

468  ANNEX 1. CHARACTERISTICS OF EDUCATION SYSTEMS
Table X1.3. Starting and ending age for students in compulsory education and by level of education (2017)
The age refers to the age of the students at the beginning of the school year

Note: 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.
Source: OECD (2019). See Source section for more information and Annex 3 for notes https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888933980583

EDUCATION AT A GLANCE 2019 © OECD 2019

ANNEX 2. REFERENCE STATISTICS  469

Annex 2. Reference statistics

All tables in Annex 2 are available on line at:
StatLink: https://doi.org/10.1787/888933981324

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 2019 © OECD 2019

470  ANNEX 2. REFERENCE STATISTICS
Table X2.1. Basic reference statistics in current prices (reference period: calendar year, 2005, 2010, 2011, 2016)

Note: 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.
1. The GDP Mainland market value is used for Norway.
Source: OECD (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888933980602

EDUCATION AT A GLANCE 2019 © OECD 2019

ANNEX 2. REFERENCE STATISTICS  471

Table X2.2. Basic reference statistics in constant prices (reference period: calendar year, 2005, 2010, 2011, 2016)

Note: 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.
1. The GDP Mainland market value is used for Norway.
Source: OECD (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888933980621

EDUCATION AT A GLANCE 2019 © OECD 2019

472  ANNEX 2. REFERENCE STATISTICS
Table X2.3. Basic reference statistics in current prices (reference period: calendar year, 2007, 2012, 2016, 2017)

Note: 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.
1. The GDP Mainland market value is used for Norway.
2. These data are used in Indicator C1 in order to calculate total expenditure on educational institutions per full-time equivalent student relative to GDP per capita.
3. These data are used in Indicator C7 in order to calculate salary costs of teachers per student as a percentage of GDP per capita.
Source: OECD (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787888933980640

EDUCATION AT A GLANCE 2019 © OECD 2019

ANNEX 2. REFERENCE STATISTICS  473

Table X2.4a. Pre-primary and primary teachers' statutory salaries at different points in their careers, for teachers with
the most prevalent qualifications defined at different points in teachers' careers (2018)
Annual salaries in public institutions for teachers with the most prevalent qualifications, in national currency

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 qualification is defined for each of the four career stages included in this table. In many cases, the minimum qualification is the same as the most
prevalent qualification, see Table X3.D3.2 in Annex 3. Please see Annex 2 and 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 social security contributions and pension-scheme contributions paid by the employers.
4. Actual base salaries.
Source: OECD (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787888933980659

EDUCATION AT A GLANCE 2019 © OECD 2019

474  ANNEX 2. REFERENCE STATISTICS
Table X2.4b. Secondary teachers' statutory salaries at different points in their careers, for teachers with the most
prevalent qualifications defined at different points in teachers' careers (2018)
Annual salaries in public institutions for teachers with the most prevalent qualifications, in national currency

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 qualification is defined for each of the four career stages included in this table. In many cases, the minimum qualification is the same as the most
prevalent qualification, see Table X3.D3.2 in Annex 3. Please see Annex 2 and Definitions and Methodology sections for more information. Data available at
http://stats.oecd.org/, Education at a Glance Database.
1. Includes the average of fixed bonuses for overtime hours for lower and upper secondary teachers.
2. Includes the social security contributions and pension-scheme contributions paid by the employers.
3. At the upper secondary level includes teachers working in vocational programmes. (In Slovenia and Sweden, includes only those teachers teaching general
subjects within vocational programmes).
4. Excludes the social security contributions and pension-scheme contributions paid by the employees.
5. Actual base salaries.
Source: OECD (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888933980678

EDUCATION AT A GLANCE 2019 © OECD 2019

ANNEX 2. REFERENCE STATISTICS  475

Table X2.8. Reference statistics used in calculating teachers' salaries (2000, 2005 to 2018)

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 on PPPs and deflators refer to Belgium.
3. Data on PPPs and deflators refer to the United Kingdom.
Source: OECD (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888933980697

EDUCATION AT A GLANCE 2019 © OECD 2019

476  ANNEX 2. REFERENCE STATISTICS
Table X2.9. Trends in average teachers' actual salaries, in national currency (2000, 2005, 2010 to 2017)
Average annual salary (including bonuses and allowances) of teachers aged 25-64

EDUCATION AT A GLANCE 2019 © OECD 2019

ANNEX 2. REFERENCE STATISTICS  477

Note: Years 2011 to 2016 (i.e. Columns 4 to 9, 14 to 19, 24 to 29 and 34 to 39) 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 head teachers, 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 (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888933980716

EDUCATION AT A GLANCE 2019 © OECD 2019

478  ANNEX 2. REFERENCE STATISTICS
Table X2.10. Proportion of teachers, by level of qualification (2018)
Teachers who have either minimum or a higher than minimum (and most prevalent) qualification

Note: See Definitions and Methodology sections for more information. Data available at http://stats.oecd.org/, Education at a Glance Database.
Source: OECD (2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/f8d7880d-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888933980735

EDUCATION AT A GLANCE 2019 © OECD 2019

ANNEX 3. SOURCES, METHODS AND TECHNICAL NOTES  479

Annex 3. Sources, methods and technical notes

Annex 3 on sources and methods is available
in electronic form only. It can be found at:
https://doi.org/10.1787/f8d7880d-en

EDUCATION AT A GLANCE 2019 © OECD 2019

CONTRIBUTORS TO THIS PUBLICATION  481

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 2019: OECD Indicators.
The OECD wishes to thank them all for their valuable efforts.

INES Working Party
Ms Ana COPES (Argentina)

Mr Richard FRANZ (Canada)

Ms Inés CRUZALEGUI (Argentina)

Ms Amanda HODGKINSON (Canada)

Mr Juan Manuel CORVALAN ESPINA (Argentina)

Ms Robin Liu HOPSON (Canada)

Mr Karl BAIGENT (Australia)

Mr David McBRIDE (Canada)

Mr. Edward HARVEY (Australia)

Ms Klarka ZEMAN (Canada)

Mr Stuart FAUNT (Australia)

Ms Rosario DEL VILLAR (Chile)

Mr Steve NERLICH (Australia)

Mr Ignacio LARRAGUIBEL (Chile)

Ms Rebecca SMEDLEY (Australia)

Ms Paola LEIVA (Chile)

Mr Andreas GRIMM (Austria)

Ms.Francisca MÜLLER (Chile)

Ms Sabine MARTINSCHITZ (Austria)

Mr Fabián RAMÍREZ (Chile)

Mr Mark NÉMET (Austria)

Mr Juan SALAMANCA (Chile)

Mr Wolfgang PAULI (Austria)

Ms Constanza VIELMA (Chile)

Ms Helga POSSET (Austria)

Ms Claudia DÍAZ (Colombia)

Ms Natascha RIHA (Austria)

Ms Helga Milena HERNÁNDEZ (Colombia)

Mr Philippe DIEU (Belgium)

Mr Javier Andrés RUBIO (Colombia)

Ms Isabelle ERAUW (Belgium)

Ms Azucena Paola VALLEJO (Colombia)

Ms Nathalie JAUNIAUX (Belgium)

Ms Elsa Nelly VELASCO (Colombia)

Mr Guy STOFFELEN (Belgium)

Mr Wilfer VALERO (Colombia)

Mr Raymond VAN DE SIJPE (Belgium)

Ms Erika VILLAMIL (Colombia)

Ms Ann VAN DRIESSCHE (Belgium)

Ms Carolina CHAVES (Costa Rica)

Mr Pieter VOS (Belgium)

Mr Andrés FERNÁNDEZ (Costa Rica)

Mr Carlos Augusto DOS SANTOS ALMEIDA (Brazil)

Mr Vladimír HULÍK (Czech Republic)

Ms Juliana MARQUES DA SILVA (Brazil)

Ms Michaela MARŠÍKOVÁ (Czech Republic)

Ms. Rachel RABELO (Brazil)

Mr Lubomír MARTINEC (Czech Republic)

Mr Patric BLOUIN (Canada)

Mr Jens ANDERSEN (Denmark)

Mr Gregory BYLINSKI (Canada)

Mr Jens BJERRE (Denmark)

EDUCATION AT A GLANCE 2019 © OECD 2019

482  CONTRIBUTORS TO THIS PUBLICATION
Ms Susanne Irvang NIELSEN (Denmark

Ms Sára HATONY (Hungary)

Ms Signe Tychsen PHILIP (Denmark)

Mr Tibor KÖNYVESI (Hungary)

Ms Tiina ANNUS (Estonia)

Mr László LIMBACHER (Hungary)

Ms Katrin REIN (Estonia)

Ms Hedvig SZABÓ (Hungary)

Ms Kadi SERBAK (Estonia)

Mr Gunnar J. ÁRNASON (Iceland)

Mr Arnaud DESURMONT
Commission)

(Eurostat,

European

Ms Malgorzata
Commission)

(Eurostat,

European

STADNIK

Ms Swapna BHATTACHARYA (India)

Mr Mika TUONONEN (Finland)
Ms Kristiina VOLMARI (Finland)
Ms Nathalie CARON (France)
Ms Marion DEFRESNE (France)
Ms Emmanuelle FERARD (France)
Ms Roselyne KERJOSSE (France)
Ms Isaure LEFEUVRE (France)
Ms Pascaline FEUILLET (France)
Ms Stéphanie LEMERLE (France)
Ms Valérie LIOGIER (France)
Ms Clotilde LIXI (France)
Ms Pascale POULET-COULIBANDO (France)
Mr Robert RAKOCEVIC (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)
Mr Michael LENZEN (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 Dóra GÉCZI (Hungary)

Ms Ásta M. URBANCIC (Iceland)

Mr Tayyab MOHAMMAD (India)
Ms Deirdre CULLEN (Ireland)
Mr Pádraig MAC FHLANNCHADHA (Ireland)
Ms Violeta MOLONEY (Ireland)
Ms Sophie ARTSEV (Israel)
Mr Yoav AZULAY (Israel)
Ms Orit BARANY (Israel)
Mr Matan CHOCRON (Israel)
Ms Hana COHEN (Israel)
Mr Yosef GIDANIAN (Israel)
Ms Merav KATZ (Israel)
Ms Osnat LANDAU (Israel)
Mr Daniel LEVI-MAZLOUM (Israel)
Ms Silvia LIPLEWSKI (Israel)
Ms Iris Avigail MATATYAHU (Israel)
Mr Dov NATAN (Israel)
Mr Haim PORTNOY (Israel)
Ms Michal SALANSKI (Israel)
Ms Naama STEINBERG (Israel)
Ms Einat WEISS (Israel)
Mr Roman ZILBERSHLAG (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 TURCHETTI (Italy)
Ms Etsuko AOYAMA (Japan)
Mr Takashi FURUDATE (Japan)
Mr Yu KAMEOKA (Japan)
Mr Tetsuya KASHIHARA (Japan)

EDUCATION AT A GLANCE 2019 © OECD 2019

CONTRIBUTORS TO THIS PUBLICATION  483
Mr Takashi KIRYU (Japan)

Mr Héctor Virgilio ROBLES VASQUEZ (Mexico)

Ms Saki KISHIDA (Japan)

Mr Gerardo H. TERRAZAS GONZÁLEZ (Mexico)

Mr Mutsuhisa KISHIMOTO (Japan)

Mr Lorenzo VERGARA LÓPEZ (Mexico)

Mr Tetsuya KISHIMOTO (Japan)

Ms. Alicia del Rosario NAVA CARDONA (Mexico)

Mr Yuya OTSUBO (Japan)

Ms Danielle ANDARABI (Netherlands)

Ms Yu Kyung HA (Korea)

Mr Maarten BALVERS (Netherlands)

Ms Tae Yeon SHIN (Korea)

Mr.Thijs NOORDZIJ (Netherlands)

Ms Young Ok KIM (Korea)

Mr Joost SCHAACKE (Netherlands)

Mr Sung Ho PARK (Korea)

Ms Priscilla TEDJAWIRJA (Netherlands)

Ms Hyo Jung HAN (Korea)

Ms Anouschka VAN DER MEULEN (Netherlands)

Ms Won Hee NA (Korea)

Ms Floor VAN OORT (Netherlands)

Ms Eun Ji LEE (Korea)

Ms.Rebecca PARISH (New Zealand)

Mr Yeon Cheon KIM (Korea)

Ms Kirsti RAWSTRON (New Zealand)

Ms Sol Hwi KIM (Korea)

Mr David SCOTT (New Zealand)

Ms Young Ho SON (Korea)

Ms Alexandra MCGREGOR (New Zealand)

Ms Han Nah KIM (Korea)

Mr Gregory KEBBLE (New Zealand)

Ms Hyo Jin HAN (Korea)

Mr Sadiq Kwesi BOATENG (Norway)

Ms Mi Seon KANG (Korea)

Mr Øyvind KLUBBEN LEKNESSUND (Norway)

Ms Gui Ah KIM (Korea)

Mr Geir NYGÅRD (Norway)

Ms Moo Young YIM (Korea)

Ms Anne Marie RUSTAD HOLSETER (Norway)

Ms Evija JAUJA (Latvia)

Ms Kristin Mathilde DRAHUS (Norway)

Mr Viktors KRAVČENKO (Latvia)

Ms Alette SCHREINER (Norway)

Ms Anna LEIŠKALNE (Latvia)

Mr Piotr JAWORSKI (Poland)

Mr Rolands ŅIKITINS (Latvia)

Ms Renata KORZENIOWSKA-PUCUŁEK (Poland)

Ms Anita ŠVARCKOPFA (Latvia)

Mr Andrzej KURKIEWICZ (Poland)

Mr Ričardas ALIŠAUSKAS (Lithuania)

Ms Anna NOWOŻYŃSKA (Poland)

Ms Salvinija CHOMIČIENĖ (Lithuania)

Ms Magdalena WIKTOR (Poland)

Ms Rita DUKYNAITĖ (Lithuania)

Ms Hanna ZIELIŃSKA (Poland)

Ms Laura LIPKEVIČIENĖ (Lithuania)

Ms Mónica LUENGO (Portugal)

Ms Daiva MARCINKEVIČIENĖ (Lithuania)

Mr Carlos Alberto MALACA (Portugal)

Ms Elisa MAZZUCATO (Luxembourg)

Ms Rute NUNES (Portugal)

Mr Alberto MAYORGA RÍOS (Mexico)

Mr Marco PIMENTA (Portugal)

Ms Teresa BRACHO GONZÁLEZ (Mexico)

Ms Dora LEITÃO (Portugal)

Mr Marco CALDERÓN ARGOMEDO (Mexico)

Mr José RAFAEL (Portugal)

Mr Luis DEGANTE MÉNDEZ (Mexico)

Mr Nuno Miguel RODRIGUES (Portugal)

Mr René GÓMORA CASTILLO (Mexico)

Mr Joaquim SANTOS (Portugal)

Mr Rolando Erick MAGAÑA RODRIGUEZ (Mexico)

Mr Amaro VIEIRA (Portugal)

Mr Tomás RAMÍREZ REYNOSO (Mexico)

Mr Mark AGRANOVICH (Russian Federation)

Ms María del Carmen REYES GUERRERO (Mexico)

Ms Julia ERMACHKOVA (Russian Federation)

EDUCATION AT A GLANCE 2019 © OECD 2019

484  CONTRIBUTORS TO THIS PUBLICATION
Ms Irina SELIVERSTOVA (Russian Federation)

Mr Jesús IBAÑEZ MILLA (Spain)

Mr Abdulrahman S. AL-ANGARI (Saudi Arabia)

Mr Ricardo MARTÍNEZ ZAMORANO (Spain)

Mr Saad ALBAIZ (Saudi Arabia)

Ms Ana REVILLA TRUJILLO (Spain)

Mr Michal REVAK (Slovak Republic)

Ms Carmen TOVAR SÁNCHEZ (Spain)

Ms Eva HLADIKOVA (Slovak Republic)

Mr Jaime VAQUERO JIMÉNEZ (Spain)

Ms Danica OMASTOVA (Slovak Republic)

MS Isabel YUN MORENO (Spain)

Mr Roman SAJBIDOR (Slovak Republic)

Ms Anna ERIKSSON (Sweden)

Ms Gabriela SLODICKOVA (Slovak Republic)

Ms Maria GÖTHERSTRÖM (Sweden)

Ms Nina ČEŠEK VOZEL (Slovenia)

Ms Marie KAHLROTH (Sweden)

Ms Andreja KOZMELJ (Slovenia)

Mr Alexander GERLINGS (Switzerland)

Ms Barbara KRESAL STERNIŠA (Slovenia)

Ms Hasnie HANNO WEBER (Switzerland)

Ms Nada POŽAR MATIJAŠIČ (Slovenia)

Ms Katrin HOLENSTEIN (Switzerland)

Ms Duša MARJETIČ (Slovenia)

Ms Nicole SCHÖBI (Switzerland)

Ms Karmen SVETLIK (Slovenia)

Mr Emanuel VON ERLACH (Switzerland)

Ms Tatjana ŠKRBEC (Slovenia)

Ms Hatice Nihan ERDAL (Turkey)

Ms Jadranka TUŠ (Slovenia)

Ms Fatma Filiz ÇİÇEK (Turkey)

Ms Tanja DOMIJAN (Slovenia)

Ms Gülçin ÖZ (Turkey)

Ms Rirhandzu BALOYI (South Africa)

Mr Turgay ALTUN (Turkey)

Ms Mamphokhu KHULUVHE (South Africa)

Mr Friedrich HUEBLER (UNESCO)

Ms Letho MAPASEKA (South Africa)

Mr Said Ould Ahmedou VOFFAL (UNESCO)

Ms Bheki MPANZA (South Africa)

Ms Aliki PAREAS (United Kingdom)

Ms Hersheela NARSEE (South Africa)

Ms Melissa DILIBERTI (United States)

Ms Matome SEKGOTA (South Africa)

Ms Rachel DINKES (United States)

Ms Nthabiseng TEMA (South Africa)

Ms Jana KEMP (United States)

Mr Miguel Ángel ÁLVAREZ ESPINOSA (Spain)

Ms Lauren MUSU (United States)

Ms Elena BANDA LÓPEZ (Spain)

Ms Ashley ROBERTS (United States)

Mr José María GALLEGO ALONSO-COLMENARES
(Spain)

Mr Thomas SNYDER (Chair INES Working Party,
United States)

Network on Labour Market, Economic and Social Outcomes of Learning (LSO)
Mr Karl BAIGENT (Australia)

Ms Christyne CARVALHO DA SILVA (Brazil)

Mr Stuart FAUNT (Australia)

Ms Camila NEVES SOUTO (Brazil)

Mr Steve NERLICH (Australia)

Ms Rachel PEREIRA RABELO (Brazil)

Ms Rebecca SMEDLEY (Australia)

Mr Patric BLOUIN (Canada)

Mr Mark NÉMET (Austria)

Ms Dallas MORROW (Canada)

Ms Isabelle ERAUW (Belgium)

Ms Annik FOREMAN (Canada)

Ms Geneviève HINDRYCKX (Belgium)

Mr Marco SERAFINI (CEDEFOP)

Mr Kasper OSSENBLOK (Belgium)

Mr Daniel SCHEUREGGER (CEDEFOP)

Ms Naomi WAUTERICKX (Belgium)

Mr Ignacio LARRAGUIBEL (Chile)

EDUCATION AT A GLANCE 2019 © OECD 2019

CONTRIBUTORS TO THIS PUBLICATION  485
Ms Paola LEIVA (Chile)

Ms Rita JAKUBOVICS (Hungary)

Mr Fabián RAMÍREZ (Chile)

Ms Ásta M. URBANCIC (Iceland)

Mr Roberto SCHURCH (Chile)

Ms Sarah CRILLY (Ireland)

Ms Constanza VIELMA (Chile)

Ms Deirdre CULLEN (Ireland)

Mr Vladimír HULÍK (Czech Republic)

Ms Helen MAXWELL (Ireland)

Ms Michaela MARŠÍKOVÁ (Czech Republic)

Ms Violeta MOLONEY (Ireland)

Ms Carolina CHAVES (Costa Rica)

Ms Tracey SHANKS (Ireland)

Mr Andrés FERNÁNDEZ (Costa Rica)

Ms Sophie ARTSEV (Israel)

Mr Jens ANDERSEN (Denmark)

Ms Hana COHEN (Israel)

Ms Tiina ANNUS (Estonia)

Ms Lior DUPAZ (Israel)

Ms Kristel BANKIER (Estonia)

Mr Mark FELDMAN (Isreal)

Ms Ingrid JAGGO (Estonia)

Mr Yonatan HAYUN (Israel)

Mr Priit LAANOJA (Estonia)

Mr Haim PORTNOY (Israel)

Ms Marianne LEPPIK (Estonia)

Ms Hagit SARID (Israel)

Mr Marti LILLEMÄGI (Estonia)

Ms Raffaella CASCIOLI (Italy)

Ms Kaire RAASIK (Estonia)

Mr Gaetano PROTO (Italy)

Ms Aune VALK (Estonia)

Ms Liana VERZICCO (Italy)

Mr
Jens
FISHER-KOTTENSTEDE
Commission)

(European

Ms Tae Yeon SHIN (Korea)

Mr Mantas SEKMOKAS (European Commission)
Ms
Elodie
Commission)

CAYOTTE

(Eurostat,

Ms Yu Kyung HA (Korea)

European

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 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)
Mr László LIMBACHER (Hungary)
Mr István BUCSI SZABÓ (Hungary)
EDUCATION AT A GLANCE 2019 © OECD 2019

Ms Young Ok KIM (Korea)
Ms Hea Jun YOON (Korea)
Ms Sook Weon MIN (Korea)
Mr Sung Ho PARK (Korea)
Ms Hye Ja KIM (Korea)
Mr Yeon Cheon KIM (Korea)
Ms Ruta BEINĀRE (Latvia)
Ms Sandra CERIŅA (Latvia)
Mr Viktors KRAVČENKO (Latvia)
Ms Zaiga PRIEDE (Latvia)
Mr Ričardas ALIŠAUSKAS (Lithuania)
Mr Eduardas DAUJOTIS (Lithuania)
Ms Regina DEVEIKYTĖ (Lithuania)
Mr Gintautas JAKŠTAS (Lithuania)
Ms Julija UMBRASAITĖ (Lithuania)
Ms Elisa MAZZUCATO (Luxembourg)
Mr Héctor Virgilio ROBLES VÁSQUEZ (Mexico)
Mr Gerardo H. TERRAZAS GONZÁLEZ (Mexico)
Mr Ted REININGA (Netherlands)
Ms Francis VAN DER MOOREN (Netherlands)

486  CONTRIBUTORS TO THIS PUBLICATION
Ms Antoinette VAN WANROIJ (Netherlands)
Ms.Rebecca PARISH (New Zealand)
Ms Kirsti RAWSTRON (New Zealand)
Mr David SCOTT (New Zealand)
MS Alexandra MCGREGOR (New Zealand)
Mr Gregory KEBBLE (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)

Ms Melita
(Slovenia)

SELJAK

Tina

OSVALD

ZALETELJ

Mr Marko TOMAŽIČ (Slovenia)
Ms Barbara KRESAL STERNIŠA (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 Thomas LOCKHART (United Kingdom)
Ms Rachel DINKES (United States)
Ms Ashley ROBERTS (United States)
Mr Thomas SNYDER (United States)

Mr Matej DIVJAK (Slovenia)

Network for the Collection and Adjudication of System-level descriptive
Information on Educational Structures, Policies and Practices (NESLI)
Mr Karl BAIGENT (Australia)

Ms Klarka ZEMAN (Canada)

Mr Stuart FAUNT (Australia)

Mr Ignacio LARRAGUIBEL (Chile)

Mr Steve NERLICH (Australia)

Ms Paola LEIVA (Chile)

Ms Antonella SALPIETRO (Australia)

Mr Fabián RAMÍREZ (Chile)

Ms Rebecca SMEDLEY (Australia)

Mr Roberto SCHURCH (Chile)

Mr Andreas GRIMM (Austria)

Ms Constanza VIELMA (Chile)

Mr Stefan POLZER (Austria)

Mr Vladimír HULÍK (Czech Republic)

Mr Philippe DIEU (Belgium)

Ms Michaela MARŠÍKOVÁ (Czech Republic)

Ms Nathalie JAUNIAUX (Belgium)

Mr Lubomír MARTINEC (Czech Republic)

Ms Bernadette SCHREUER (Belgium)

Mr Jorgen Balling RASMUSSEN (Denmark)

Mr Raymond VAN DE SIJPE (Belgium)

Ms Tiina ANNUS (Estonia)

Ms Ann VAN DRIESSCHE (Belgium)

Ms Hanna KANEP (Estonia)

Ms Christyne CARVALHO DA SILVA (Brazil)

Ms Kristel VAHER (Estonia)

Ms Camila NEVES SOUTO (Brazil)

Ms Hille VARES (Estonia)

Ms Rachel PEREIRA RABELO (Brazil)

Ms Lene MEJER (European Commission)

Ms Jennifer CHEW LEUNG (Canada)

Ms Nathalie BAIDAK (Eurydice)

Mr Brett WILMER (Canada)

Ms Arlette DELHAXHE (Eurydice)
EDUCATION AT A GLANCE 2019 © OECD 2019

CONTRIBUTORS TO THIS PUBLICATION  487
Ms Petra PACKALEN (Finland)

Mr Viktors KRAVČENKO (Latvia)

Ms Kristiina VOLMARI (Finland)

Mr Ričardas ALIŠAUSKAS (Lithuania)

Ms Emmanuelle FERARD (France)

Mr Evaldas BAKONIS (Lithuania)

Mr Louis MEURIC (France)

Mr Eduardas DAUJOTIS (Lithuania)

Mr Robert RAKOCEVIC (France)

Ms Ingrida ŠIAUČIULIENĖ (Lithuania)

Mr Thomas ECKHARDT (Germany)

Ms Rima ZABLACKĖ (Lithuania)

Mr Benny SCHNEIDER (Germany)

Ms Charlotte MAHON (Luxembourg)

Mr Marco MUNDELIUS (Germany)

Ms Elisa MAZZUCATO (Luxembourg)

Ms Dimitra FARMAKIOTOU (Greece)

Mr Alberto MAYORGA RÍOS (Mexico)

Ms Maria FASSARI (Greece)

Mr Marco CALDERÓN ARGOMEDO (Mexico)

Ms Vassilliki MAKRI (Greece)

Mr Juan Martín SOCA DE IÑIGO (Mexico)

Mr Panagiotis PASSAS (Greece)

Mr Thijs NOORDZIJ (Netherlands)

Ms Sára HATONY (Hungary)

Mr Hans RUESINK (Chair of NESLI Network,
Netherlands)

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 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)
Mr Dov NATAN (Israel)
Ms Gianna BARBIERI (Italy)
Ms Lucia DE FABRIZIO (Italy)
Ms Annarita Lina MARZULLO (Italy)
Mr Takashi FURUDATE (Japan)
Mr Yu KAMEOKA (Japan)
Ms Saki KISHIDA (Japan)
Ms Yu Kyung HA (Korea)
Ms Tae Yeon SHIN (Korea)
Ms Young Ok KIM (Korea)
Mr Sung Ho PARK (Korea)
Ms Hyo Jung HAN (Korea)
Ms Han Nah KIM (Korea)
Ms Modra JANSONE (Latvia)

EDUCATION AT A GLANCE 2019 © OECD 2019

Mr Jerry STRATEN (Netherlands)
Mr Dick VAN VLIET (Netherlands)
Ms.Rebecca PARISH (New Zealand)
Ms Kirsti RAWSTRON (New Zealand)
Mr David SCOTT (New Zealand)
MS Alexandra MCGREGOR (New Zealand)
Mr Gregory KEBBLE (New Zealand)
Mr Øyvind KLUBBEN LEKNESSUND (Norway)
Ms Barbara ANTOSIEWICZ (Poland)
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)
Ms Inmaculada CABEZALÍ MONTERO (Spain)
Mr Juan Carlos GIRÓN ORTEGA (Spain)
Mr Jaime VAQUERO JIMÉNEZ (Spain)
Mr David VARAS DEL PESO (Spain)

488  CONTRIBUTORS TO THIS PUBLICATION
Mr Christian LOVERING (Sweden)

Ms Gülçin ÖZ (Turkey)

Mr Tomas GUSTAVSSON) (Sweden)

Ms Sarah CROSS (United Kingdom)

Ms Katrin MÜHLEMANN (Switzerland)

Ms Jana KEMP (United States)

Mr Osman Yıldırım UĞUR (Turkey)

Ms Lauren MUSU (United States)

Ms Fatma Filiz ÇİÇEK (Turkey)

Other contributors to this publication
BRANTRA SPRL (Translation)

Ms Fung Kwan TAM (Layout)

Ms Sally Caroline HINCHCLIFFE (Edition)

EDUCATION AT A GLANCE 2019 © OECD 2019

EDUCATION INDICATORS IN FOCUS  489

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 figures 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 can the comparability of early childhood education and care statistics be improved?”, Education
Indicators in Focus, No. 70 (2019)
https://doi.org/10.1787/9ac255e5-en
“How does socio-economic status influence entry into tertiary education?”, Education Indicators in Focus,
No. 69 (2019)
https://doi.org/10.1787/9ac255e5-en
“What characterises upper secondary vocational education and training?”, Education Indicators in Focus,
No. 68 (2019)
https://doi.org/10.1787/a1a7e2f1-en
“Why does the Sustainable Development Goal on Education (SDG 4) matter for OECD countries?”,
Education Indicators in Focus, No. 67 (2019)
https://doi.org/10.1787/cdc2482b-en
“How much would it cost to reduce class size by one student?”, Education Indicators in Focus, No. 66
(2019)
https://doi.org/10.1787/d773f268-en
How do the educational attainment and labour market outcomes of foreign-born adults compare to their
native-born peers? Education Indicators in Focus, No. 65 (2018)
https://doi.org/10.1787/cf52bacd-en
“How decentralised are education systems, and what does it mean for schools?”, Education Indicators in
Focus, No. 64 (2018)
https://doi.org/10.1787/e14575d5-en
“How do admission systems affect enrolment in public tertiary education?”, Education Indicators in Focus,
No. 63 (2018)
https://doi.org/10.1787/41bf120b-en
“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

490  EDUCATION INDICATORS IN FOCUS
“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
“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

EDUCATION AT A GLANCE 2019 © OECD 2019

EDUCATION INDICATORS IN FOCUS  491
“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
“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

EDUCATION AT A GLANCE 2019 © OECD 2019

492  EDUCATION INDICATORS IN FOCUS
“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
“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

EDUCATION AT A GLANCE 2019 © OECD 2019

EDUCATION INDICATORS IN FOCUS  493
“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

EDUCATION AT A GLANCE 2019 © OECD 2019

ORGANISATION FOR ECONOMIC CO-OPERATION
AND DEVELOPMENT
The OECD is a unique forum where governments work together to address the economic, social and
environmental challenges of globalisation. The OECD is also at the forefront of efforts to understand and to
help governments respond to new developments and concerns, such as corporate governance, the
information economy and the challenges of an ageing population. The Organisation provides a setting
where governments can compare policy experiences, seek answers to common problems, identify good
practice and work to co-ordinate domestic and international policies.
The OECD member countries are: Australia, Austria, Belgium, Canada, Chile, the Czech Republic,
Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Israel, Italy, Japan, Korea,
Latvia, Lithuania, Luxembourg, Mexico, the Netherlands, New Zealand, Norway, Poland, Portugal, the
Slovak Republic, Slovenia, Spain, Sweden, Switzerland, Turkey, the United Kingdom and the United States.
The European Union takes part in the work of the OECD.
OECD Publishing disseminates widely the results of the Organisation’s statistics gathering and
research on economic, social and environmental issues, as well as the conventions, guidelines and
standards agreed by its members.

OECD PUBLISHING, 2, rue André-Pascal, 75775 PARIS CEDEX 16
ISBN 978-92-64-80398-5 – 2019

Education at a Glance 2019
OECD INDICATORS
Education at a Glance 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 across OECD countries
and a number of partner economies. More than 100 charts and tables in this publication – as well as links
to much more available on the educational database – 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.
The 2019 edition includes a focus on tertiary education with new indicators on tertiary completion rates,
doctoral graduates and their labour market outcomes, and on tertiary admission systems, as well as
a dedicated chapter on the Sustainable Development Goal 4.
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-a-glance-19991487.htm. Updated data can be found online at
http://dx.doi.org/10.1787/eag-data-en.

Consult this publication on line at https://doi.org/10.1787/f8d7880d-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 978-92-64-80398-5

9HSTCQE*iadjif+