Education at a Glance 2020
OECD INDICATORS

Education at a Glance
2020
OECD INDICATORS

This work is published under the responsibility of the Secretary-General of the OECD. The opinions expressed and
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Please cite this publication as:
OECD (2020), Education at a Glance 2020: OECD Indicators, OECD Publishing, Paris, https://doi.org/10.1787/69096873-en.

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Education at a Glance
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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 Dirk
Van Damme and Marie-Hélène Doumet, and in co-operation with Étienne Albiser, Andrea Borlizzi, Éric
Charbonnier, Manon Costinot, Bruce Golding, Yanjun Guo, Hanna Jang, Corinne Heckmann, Karinne Logez,
Camila de Moraes, Simon Normandeau, Gara Rojas González, Daniel Sánchez Serra, Markus Schwabe,
Giovanni Maria Semeraro, Choyi Whang and Hajar Sabrina Yassine. Administrative support was provided by
Valérie Forges, and additional advice and analytical support were provided by Shinyoung Jeon and Pauline
Musset. 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
needs to be made in conceptual work. The OECD Programme for International Student Assessment (PISA) and
EDUCATION AT A GLANCE 2020 © OECD 2020

4  FOREWORD
its extension through the OECD Survey of Adult Skills, a product of the Programme for the International
Assessment of Adult Competencies (PIAAC), as well as the OECD Teaching and Learning International Survey
(TALIS), are major efforts to this end.

EDUCATION AT A GLANCE 2020 © OECD 2020

TABLE OF CONTENTS  5

Table of contents

Foreword

3

Editorial

9

Introduction: The indicators and their framework

12

Reader’s guide

17

Executive summary

24

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?

38

Indicator A2. Transition from education to work: Where are today's youth?

54

Indicator A3. How does educational attainment affect participation in the labour market?

68

Indicator A4. What are the earnings advantages from education?

86

Indicator A5. What are the financial incentives to invest in education?

102

Indicator A6. How are social outcomes related to education?

120

Indicator A7. To what extent do adults participate equally in education and learning?

136

Chapter B. Access to education, participation and progress

153

Indicator B1. Who participates in education?

154

Indicator B2. How do early childhood education systems differ around the world?

166

Indicator B3. Who is expected to complete upper secondary education?

186

Indicator B4. Who is expected to enter tertiary education?

198

Indicator B5. Who is expected to graduate from tertiary education?

214

Indicator B6. What is the profile of internationally mobile students?

226

Indicator B7. How do vocational education systems differ around the world?

242

EDUCATION AT A GLANCE 2020 © OECD 2020

6  TABLE OF CONTENTS

Chapter C. Financial resources invested in education

265

Introduction

266

Indicator C1. How much is spent per student on educational institutions?

270

Indicator C2. What proportion of national wealth is spent on educational institutions?

284

Indicator C3. How much public and private investment in educational institutions is there?

296

Indicator C4. What is the total public spending on education?

308

Indicator C5. How much do tertiary students pay and what public support do they receive?

322

Indicator C6. On what resources and services is education funding spent?

338

Chapter D. Teachers, the learning environment and the organisation of schools 349
Indicator D1. How does time spent by students in the classroom vary over the years?

350

Indicator D2. What is the student-teacher ratio and how big are classes?

370

Indicator D3. How much are teachers and school heads paid?

384

Indicator D4. How much time do teachers and school heads spend teaching and working?

408

Indicator D5. Who are the teachers?

428

Annex 1. Characteristics of education systems

441

Annex 2. Reference statistics

447

Annex 3. Sources, methods and technical notes

459

Contributors to this publication

461

Education Indicators in Focus

469

TABLES
Table A1.1. Educational attainment of 25-64 year-olds (2019)
50
Table A1.2. Trends in educational attainment of 25-34 year-olds, by gender (2009 and 2019)
51
Table A1.3. Educational attainment of 25-34 year-olds and 55-64 year-olds, by programme orientation (2019) 52
Table A2.1. Percentage of 18-24 year-olds in education/not in education, by work status (2019)
64
Table A2.2. Trends in the percentage of young adults in education/not in education, by age group and work status
(2009 and 2019)
65
Table A2.3. Young adults with upper secondary education in education/not in education, employed or not, by
years since graduation (2018)
66
Table A3.1. Employment rates of 25-64 year-olds, by educational attainment (2019)
80
Table A3.2. Trends in employment rates of 25-34 year-olds, by educational attainment and gender (2009 and
2019)
81
Table A3.3. Employment rates, by educational attainment and age group (2019)
82
Table A3.4. Unemployment and inactivity rates of 25-34 year-olds, by educational attainment (2019)
83
Table A3.5. Employment rates of young adults who have recently completed education, by educational
attainment and years since graduation (2018)
84
Table A4.1. Relative earnings of workers, by educational attainment (2018)
97
Table A4.2. Level of earnings relative to median earnings, by educational attainment (2018)
98
Table A4.3. Women’s earnings as a percentage of men's earnings, by educational attainment and age group
(2018)
99
Table A4.4. Relative earnings of workers, by educational attainment and age (2018)
100
Table A5.1. Private costs and benefits for a man attaining upper secondary education (2017)
115
Table A5.2. Private costs and benefits for a woman attaining upper secondary education (2017)
116

EDUCATION AT A GLANCE 2020 © OECD 2020

TABLE OF CONTENTS  7
Table A5.3. Public costs and benefits for a man attaining upper secondary education (2017)
117
Table A5.4. Public costs and benefits for a woman attaining upper secondary education (2017)
118
Table A6.1. Percentage of 15-year-old students who reported being exposed to different forms of bullying at least
a few times a month, by parents' educational attainment (2018)
132
Table A6.2. Percentage of 15-year-old students who agreed or strongly agreed with statements about bullying,
by parents' educational attainment (2018)
133
Table A6.3. Political engagement, by educational attainment (2016 or 2018)
134
Table A7.1. Share of employed adults participating in non-formal education and training, by size and sector of
enterprise, job-relatedness and employer sponsorship (2016)
149
Table A7.2. Annual hours of participation in formal and/or non-formal education and training, by educational attainment
(2016)
150
Table A7.3. Annual training costs, by size of enterprise (2015)
151
Table B1.1. Enrolment rates by age group (2005, 2010 and 2018)
163
Table B1.2. Enrolment rates of 15-19 and 20-24 year-olds in secondary and tertiary education, by level of education
(2018)
164
Table B1.3. Enrolment rates of students aged 25 and older in secondary and tertiary education, by level of education
(2018)
165
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 2018)
182
Table B2.2. Enrolment rates in early childhood education and care and primary education, by age (2005, 2010
and 2018)
183
Table B2.3. Enrolment of children in early childhood education and care (ISCED 0) in private institutions, ratio of
children to teaching staff and most prevalent qualification of ECEC staff (2018)
184
Table B2.4. Financing of early childhood education and care (ISCED 0) and expenditure on all children aged 3 to
5 (2017)
185
Table B3.1. Completion rate of upper secondary education, by programme orientation at entrance and gender
(2018)
196
Table B3.2. Distribution of entrants to upper secondary education by programme orientation and outcomes after
the theoretical duration and after the theoretical duration plus two years (2018)
197
Table B4.1. Entry rate and profile of first-time entrants into tertiary education (2018)
210
Table B4.2. Entry rate and profile of new entrants into short-cycle tertiary level (2018)
211
Table B4.3. Entry rate and profile of new entrants into bachelor's, master's and doctoral levels (2018)
212
Table B5.1. Graduation rate and profile of first-time tertiary graduates (2018)
223
Table B5.2. Distribution of tertiary graduates by field of study (2018)
224
Table B5.3. Graduation rate and profile of first-time tertiary graduates at short-cycle tertiary, bachelor's, master's
and doctoral or equivalent levels (2018)
225
Table B6.1. International and foreign student mobility in tertiary education (2010, 2014 and 2018)
238
Table B6.2. Distribution of international or foreign students by field of study (2018)
239
Table B6.3. Mobility patterns of foreign and international students (2018)
240
Table B7.1. Profile of students enrolled in vocational education from lower secondary to short-cycle tertiary, by
type of programme, age and gender (2018)
258
Table B7.2. Pathways between upper secondary or post-secondary non-tertiary education and higher levels of
education, by type of programme and programme orientation (2018)
260
Table B7.3. Main characteristics of combined school- and work-based programmes in upper secondary education
(2018)
262
Table C1.1. Total expenditure on educational institutions per full-time equivalent student (2017)
280
Table C1.2. Total expenditure on educational institutions per full-time equivalent student for core educational
services, ancillary services and R&D (2017)
281
Table C1.3. Average annual growth in total expenditure on educational institutions per full-time equivalent student
(2012 to 2017)
282
Table C2.1. Total expenditure on educational institutions as a percentage of GDP (2017)
292
Table C2.2. Total expenditure on educational institutions as a percentage of GDP, by source of funds (2017) 293
Table C2.3. Index of change in total expenditure on educational institutions as a percentage of GDP (2005, 2012
and 2017)
294
Table C3.1. Relative share of public, private and international expenditure on educational institutions, by final source of funds
(2017)
304
Table C3.2. Relative share of public, private and international expenditure on educational institutions, by source
of funds and public-to-private transfers (2017)
305
Table C3.3. Trends in the share of public, private and international expenditure on educational institutions (2005, 2012 and
2017)
306
EDUCATION AT A GLANCE 2020 © OECD 2020

8  TABLE OF CONTENTS
Table C4.1. Total public expenditure on education as a percentage of total government expenditure (2017)
318
Table C4.2. Distribution of sources of total public funds devoted to education, by level of government (2017) 319
Table C4.3. Index of change in total public expenditure on education as a percentage of total government
expenditure (2005, 2012 and 2017)
320
Table C5.1. Annual average (or most common) tuition fees charged by tertiary institutions to national and foreign
students (2017/18)
333
Table C5.2. Trends and reforms in tuition fees and public financial support to tertiary education (2007/08 to
2017/18)
334
Table C5.3. Public financial support to national students enrolled in tertiary programmes (2017/18)
335
Table C6.1. Share of current and capital expenditure, by education level (2017)
346
Table C6.2. Current expenditure, by resource category (2017)
347
Table C6.3. Share of current expenditure, by resource category and type of institution (2017)
348
Table D1.1. Instruction time in compulsory primary education1 (2011, 2014 to 2019)
365
Table D1.2. Instruction time in compulsory general lower secondary education 1 (2011, 2014 to 2019)
366
Table D1.3. Instruction time per subject in compulsory primary education (2014 and 2019)
367
Table D1.4. Instruction time per subject in compulsory general lower secondary education (2014 and 2019)
368
Table D2.1. Ratio of students to teaching staff in educational institutions, by level of education (2018)
381
Table D2.2. Ratio of students to teaching staff, by type of institution (2018)
382
Table D2.3. Average class size, by type of institution (2018) and index of change between 2005 and 2018
383
Table D3.1. Teachers' statutory salaries, based on the most prevalent qualifications at different points in teachers' careers
(2019)
403
Table D3.2. Teachers’ and school heads’ actual salaries relative to earnings of tertiary-educated workers (2019)404
Table D3.3. Teachers’ and school heads’ average actual salaries (2019)
405
Table D3.4. School heads’ minimum and maximum school heads' statutory salaries, based on minimum qualifications
(2019)
406
Table D4.1. Organisation of teachers’ teaching time (2019)
423
Table D4.2. Organisation of teachers’ working time (2019)
424
Table D4.3. Tasks of teachers, by level of education (2019)
425
Table D4.4. Other responsibilities of teachers, by level of education (2019)
426
Table D4.5. Organisation of school heads’ working time (2019)
427
Table D5.1. Gender distribution of teachers (2018)
437
Table D5.2. Gender distribution of teachers by age group (2018) and percentage of female teachers for all ages (2005
and 2018)
438
Table D5.3. Age distribution of teachers (2018)
439

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EDITORIAL  9

Editorial
The spread of COVID-19 has sent shockwaves across the globe. The public health crisis, unprecedented in our
current lifetime, has caused severe human suffering and loss of life. The exponential rise in infected patients and
the dramatic consequences of serious cases of the disease have overwhelmed hospitals and health professionals
and put significant strain on the health sector. As governments grappled with the spread of the disease by closing
down entire sectors of activity and imposing widespread restrictions on mobility, the sanitary crisis evolved into
a major economic crisis expected to burden societies for years to come. According to the OECD’s latest Economic
Outlook, even the most optimistic scenarios predict a brutal recession. Even if a second wave of infections is
avoided, global economic activity is expected to fall by 6% in 2020, with average unemployment in OECD
countries climbing to 9.2%, from 5.4% in 2019. In the event of a second outbreak triggering a return to lockdown,
the situation would be worse.
Education has not been spared. The lockdowns have interrupted conventional schooling with nationwide school
closures in most OECD and partner countries, lasting at least 10 weeks in the majority of them. While the
educational community has made important efforts to maintain learning continuity during this period, children and
students have had to rely more on their own resources to continue learning remotely through the Internet,
television or radio. Disadvantaged students have had the hardest time adjusting to distance learning. Spending
on education may also be compromised in the coming years. As emergency public funds might be directed to
health and social welfare, long-term public spending on education is at risk despite short-term stimulus packages
in some countries. Private funding will also become scarce as the economy weakens. More damagingly, the
lockdown has exacerbated inequality among workers. While teleworking is often an option for the most qualified,
it is seldom possible for those with lower levels of education, many of whom have been on the front lines in the
response to the pandemic, providing essential services to society.

Recognising the importance of vocational education
While remote learning has offered some educational continuity when it comes to academic learning, vocational
education has been particularly hard hit by the crisis. Social distancing requirements and the closure of
enterprises have made practical and work-based learning that are so crucial for the success of vocational
education, difficult or impossible. And yet, this sector plays a central role in ensuring the alignment between
education and work, the successful transition into the labour market, and for employment and the economic
recovery more generally. Not least, many of the professions that formed the backbone of economic and social
life during the lockdown hinge on vocational qualifications.
This year’s Education at a Glance therefore places the spotlight on vocational education and training (VET). Most
often provided at upper secondary level, but sometimes also at lower or post-secondary level, VET provides
trade, technical and professional skills for the workforce. Often neglected in favour of more prestigious academic
routes, VET has often been disregarded in educational policy debates. Indeed, on average across OECD
countries, young adults today are less likely to pursue a vocational path and more likely to pursue an academic
university degree than their parents were. This may partly reflect long-term labour-market prospects: although
young adults with an upper secondary vocational education as their highest attainment are more likely to be
employed than those with a general upper secondary one, their employment rate remains more or less stable
with age while that of adults with a general upper secondary education increases. In contrast, the employment

EDUCATION AT A GLANCE 2020 © OECD 2020

10  EDITORIAL
advantage of a tertiary education continues to increase with age. Earnings are also lower: adults with an upper
secondary vocational qualification have similar earnings to those with an upper secondary general qualification,
but they earn 34% less than tertiary-educated adults on average across OECD countries. With rising concerns
about the unpredictability of the job market and rapid technological advances making way for digitalisation and
automation, it is important for VET programmes to adapt and provide students with the skills needed for
tomorrow’s society.
Yet the evidence from countries with high-performing vocational systems is that they provide a very effective
means of integrating learners into the labour market and opening pathways for further learning and personal
growth. During the lockdown that followed the spread of COVID-19, the reliance on vital services such as
manufacturing and healthcare, many of which rely on vocational education, has brought to light, more than ever,
the need to look at VET with a fresh eye and implement measures to increase its attractiveness to potential
learners. One way to do that is to enhance work-based learning and strengthen ties with the private sector. In
contrast to exclusively school-based learning, combined school- and work-based programmes provide students
with a unique understanding of the workplace. By being placed in direct contact with employers, students
assimilate the most relevant skills and gain direct exposure to the labour market. Despite their advantages, these
types of VET programmes are still uncommon: they account for only one-third of upper secondary vocational
enrolment on average across OECD countries.
Improving the progression from VET into higher levels of education is also important to support students in
developing skills that provide value to the workplace. Enabling students to move between programme types,
including into higher education, also signals that VET programmes are not an educational dead-end, but can
open the door to further learning and self-development. Providing prospects for higher education also encourages
vocational students to complete their education. Although the completion rate of students in a vocational upper
secondary programme is lower than in general ones, vocational students are more likely to complete their
qualification when the programme provides access to tertiary education than when it does not.
Most countries have opened pathways between upper secondary vocational programmes and higher education.
On average across OECD countries, almost 7 out of 10 upper secondary vocational students are enrolled in
programmes that, in theory, allow them to progress to a higher-level degree. However, while these pathways
exist, few actually use them. A survey conducted across a few OECD countries for Education at a Glance 2019
found that the share of vocational students is lower among entrants to bachelor’s or equivalent programmes than
at upper secondary level. Although short-cycle tertiary programmes are usually more attractive to vocational
students than long-cycle degrees, these do not exist in all countries.

Education for resilience and recovery
As we enter the COVID-19 recovery phase, it will be critical to reflect on the role of educational systems – and
particularly vocational education – in fostering resilient societies. VET can support the training of professionals
such as healthcare or childcare workers, or those in manufacturing or agriculture, who have maintained essential
services to the public during the pandemic. The global health crisis and the generalised lockdown that followed
have brought to the fore professions that have often been taken for granted, renewing our awareness of their
value to society. This has helped restore a sense of esteem for those workers who have worked relentlessly
during this time to keep our world afloat.
The outlook is very uncertain. But, if anything, the pandemic has exposed our vulnerability to crises and revealed
how precarious and interdependent the economies we have built can be. Disruptions on the scale we have just
witnessed are not limited to pandemics, but may also result from natural, political, economic and environmental
disorder. Our capacity to react effectively and efficiently in the future will hinge on governments’ foresight,
readiness, and preparedness. Through their role in developing the competencies and skills needed for
tomorrow’s society, education systems will need to be at the heart of this planning. This includes rethinking how
the economy should evolve to guard against adversity, and defining the skills, education and training required to

EDUCATION AT A GLANCE 2020 © OECD 2020

EDITORIAL  11

support it. This also means working in close collaboration with other government sectors and the private sector
to increase the attractiveness and labour-market prospects of certain professions, including those considered
paramount for the common good.
More than ever, the pandemic is a call to renew our political commitment to the Sustainable Development Goals.
Ensuring that all young people have the opportunity to succeed at school and develop the skills that will allow
them to contribute to society is at the heart of the global agenda and education’s promise to our future society.
The current crisis has tested our ability to deal with large-scale disruptions. It is now up to us to build as its legacy
a more resilient society.

Angel Gurría
OECD Secretary-General

EDUCATION AT A GLANCE 2020 © OECD 2020

12  INTRODUCTION: THE INDICATORS AND THEIR FRAMEWORK

Introduction: The indicators and
their framework
The organising framework
Education at a Glance 2020: 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 2020 © OECD 2020

INTRODUCTION: THE INDICATORS AND THEIR FRAMEWORK  13

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 effects of the output of education systems, such as the employment and earning
benefits of pursuing higher education. Impact indicators analyse the long-term indirect effects of the
outcomes, such as the 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 2008 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 2020 © OECD 2020

14  INTRODUCTION: THE INDICATORS AND THEIR FRAMEWORK
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 2020 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 cover
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 inputs into educational systems (Figure A):


Chapter C, Financial resources invested in education, provides indicators on expenditure in education
and educational institutions, how that expenditure is shared between public and private sources, the
tuition fees charged by institutions and the financial mechanisms to support students. 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’ and school heads’ 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.

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INTRODUCTION: THE INDICATORS AND THEIR FRAMEWORK  15

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.
The United Nations Educational, Scientific and Cultural Organization (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.

Vocational education and training in Education at a Glance 2020
As the selected theme for this year’s publication, vocational education and training (VET) is at the forefront of
Education at a Glance 2020. there has been renewed interest in VET in recent years as an effective means to
open pathways for further learning and personal growth, and ease the transition of learners into the labour market.
There is increasing policy interest in providing comparative analysis of the progression of VET students, the
outcomes of its graduates and the resources invested. Therefore, a large number of indicators in this year’s
edition analyse students’ participation and progression through vocational education, from lower secondary to
short-cycle tertiary education. It also analyses the economic, labour-market and social outcomes of adults with a
vocational qualification as well as indicators on the resources invested in VET, both financial and human. This
year, two new indicators complement the set of indicators, offering additional analysis of how VET systems differ
around the world and upper secondary completion rates by programme orientation.
In line with this general focus, the SDG chapter in this year’s edition focuses on upper secondary education and
helps inform the debate on youth prospects and youth employment in OECD and partner countries, in the light
of the Sustainable Development Agenda. This chapter builds on a selection of SDG 4 indicators to investigate
the quality of and participation in secondary education, looking at aspects such as teaching resources in lower
secondary education, student outcomes, and the link between upper secondary attainment and access to the
labour market.
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16  INTRODUCTION: THE INDICATORS AND THEIR FRAMEWORK
Table A below summarises the indicators and chapters that contribute to the analysis of vocational education
and training in this year’s edition.

Table A. Indicators including an analysis of vocational education and training in Education at a Glance
2020
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
D1
D2
D3
D4
D5

Indicator
VET 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 complete upper secondary education?
Who is expected to enter tertiary education?
Who is expected to graduate from tertiary education?
What is the profile of internationally mobile students?
How do vocational education systems differ around the world?
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?
How does time spent by students in the classroom vary over the years?
What is the student-teacher ratio and how big are classes?
How much are teachers and school heads paid?
How much time do teachers and school heads spend teaching and working?
Who are the teachers?

X
X
X

X
X
X
X
X
X
X

X
X
X
X

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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
is not included in the basic education expenditure and enrolment data, with the exception of combined schooland work-based programmes that are explicitly deemed to be part of the education system.
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,
India, Indonesia, Saudi Arabia and South Africa). Data sources for the non-INES participating countries can come
from the regular INES data collections or from the UNESCO Institute of Statistics.
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.

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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, 2020[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 Survey of Adult Skills, a product
of the Programme for the International Assessment of Adults (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 the 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.
Data from the OECD Teaching and Learning International Survey (TALIS) present an OECD-31 average. This is
the unweighted mean based on ISCED 2 teacher data across the 31 OECD countries and economies
participating in TALIS with adjudicated data.
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 countries are considered
as a whole. This approach is taken for the purpose of comparing, for example, expenditure charts for individual
countries with those of all OECD countries for which data are available, 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 the OECD average to be compared over time with no distortion due to the exclusion of
some 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. The present publication presents time series compiled by the OECD Secretariat
for the EU23 which include the United Kingdom for the entire time series, even when data extend beyond the
date of the United Kingdom’s withdrawal from the European Union on 1 February 2020. The 23 countries
therefore included in this average are Austria, Belgium, the Czech Republic, Denmark, Estonia, Finland, France,

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READER’S GUIDE  19

Germany, Greece, Hungary, Ireland, Italy, Latvia, Lithuania, Luxembourg, the Netherlands, Poland, Portugal,
the Slovak Republic, Slovenia, Spain, Sweden and the United Kingdom. In future publications, the “European
Union” aggregate will change to exclude the UK for the entire time series.
The EU-23 total is calculated as the weighted mean of the data values of all OECD-EU countries for which data
are available or can be estimated. It reflects the value for a given indicator when the OECD-EU area is considered
as a whole. The coverage of countries is identical to the EU23 average.
For some indicators, a G20 average is presented. The G20 average is calculated as the unweighted mean of
the data values of all G20 countries for which data are available or can be estimated (Argentina, Australia, Brazil,
Canada, China, France, Germany, India, Indonesia, Italy, Japan, Korea, Mexico, the Russian Federation,
Saudi Arabia, South Africa, Turkey, the United Kingdom and the United States; the European Union is the 20th
member of the G20 but is not included in the calculation). The G20 average is not computed if data for both China
and India are not available.
OECD, 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 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 lists the ISCED 2011 levels used in the publication (OECD/Eurostat/UNESCO Institute for Statistics,
2015[3]).
In some indicators, intermediate programmes are also used. These correspond to recognised qualifications from
ISCED 2011 level programmes which are not considered as sufficient for ISCED 2011 completion and are
classified at a lower ISCED 2011 level.
The ISCED classification also allows for the analysis of complementary dimensions of programmes, such as their
orientation and direct access to higher education levels (Table C). Programme orientation, defined by the second
digit of the ISCED code, can be either general or vocational at ISCED levels 2 to 5. Vocational education and
training (VET), the focus of this year’s publication, is most often offered from lower secondary to short-cycle
tertiary level. Vocational programmes prepare students for skilled worker and/or technician-level jobs. They may
also include second chance or re-integration programmes which either review material already covered in upper
secondary programmes or provide opportunities for young people to change streams. The ISCED 2011
classification also allows for tertiary-level programmes (5 to 8) to be coded into academic or professional
orientations. However, in the absence of internationally agreed definitions on these categories for tertiary
education, the category “unspecified” is often used in international statistics at levels 6 to 8.
ISCED 2011 introduces a complementary dimension: completion of an ISCED level and direct access to higher
levels of education, which is represented by the third digit of the ISCED code (Table C). In the publication, this
dimension is used to analyse pathways from upper secondary vocational programmes to higher levels. For

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20  READER’S GUIDE
example, ISCED 354 is an upper secondary vocational programme that provides direct access to tertiary
education while ISCED 353 does not.

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) (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.

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.
Primary education
Designed to provide a sound basic education in reading, writing and mathematics and a basic understanding of
some other subjects. Entry age: between 5 and 7. Typical duration: 6 years.
Lower secondary education
Completes provision of basic education, usually in a more subject-oriented way with more specialist teachers.
Programmes may differ by orientation, general or vocational, though this is less common than at upper secondary
level. Entry follows completion of primary education and typical duration is 3 years. In some countries, the end of
this level marks the end of compulsory education.
Upper secondary education
Stronger specialisation than at lower secondary level. Programmes offered are differentiated by orientation:
general or vocational. Typical duration is 3 years.
Post-secondary non-tertiary education
Serves to broaden rather than deepen the knowledge, skills and competencies gained in upper secondary level.
Programmes may be designed to increase options for participants in the labour market, for further studies at
tertiary level, or both. Usually, programmes at this level are vocationally oriented.
Short-cycle tertiary education
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.
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. This
level is referred to as “bachelor’s” in the publication.
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. This level is
referred to as “master’s” in the publication.
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. This level is referred as “doctoral” in the
publication.

ISCED 0 (sub-categories: 01
for early childhood
educational development and
02 for pre-primary education)
ISCED 1

ISCED 2

ISCED 3

ISCED 4

ISCED 5

ISCED 6

ISCED 7

ISCED 8

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READER’S GUIDE  21

Table C. Complementary dimensions in the ISCED 2011 classification
Orientation – second-digit ISCED code
4
5
4
5
6
4
3
2
1

General education
Vocational education
Academic education
Professional education
Unspecified education
Completion and access – third-digit ISCED code
Sufficient for completion of the level with direct access
to a higher ISCED level
Sufficient for completion of the level without direct
access to the higher ISCED level
Partial completion of the level without direct access to
the higher ISCED level
Insufficient for completion of the level without direct
access to the higher ISCED level

ISCED levels
applied to
2 to 5
5 to 8
5 to 8
6 to 8
2 to 8
2 to 4
2 or 3
2 to 8

Note: In the absence of internationally agreed definitions for academic and professional orientations at the tertiary level, “general” or “vocational” will be
used at ISCED 2011 levels 2 to 5, and “unspecified orientation” may be used at ISCED 2011 levels 6 to 8.
Source: OECD/Eurostat/UNESCO Institute for Statistics (2015[3]), ISCED 2011 Operational Manual: Guidelines for Classifying National Education
Programmes and Related Qualifications, http://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
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.

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22  READER’S GUIDE
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).
The statistical software used in the computation of indicators in this publication may result in slightly different
values past the fourth significant digit after the decimal point when compared to national statistics.

Further resources
The website http://www.oecd.org/education/education-at-a-glance/ 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
2020 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”.

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 only available on line.

Abbreviations used in this report
AES

Adult Education Survey

CPD

Continuing professional development

CVTS Continuing Vocational Training Survey
ECEC Early childhood education and care
EEA

European Economic Area

ESS

European Social Survey

GDP

Gross domestic product

ICT

Information and communication technologies

ISCED International Standard Classification of Education

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READER’S GUIDE  23

LFD

Master’s long first degree

NEET Neither employed nor in education or training
NPV

Net present value

PIAAC Survey of Adult Skills
PISA

Programme for International Student Assessment

PPP

Purchasing power parity

R&D

Research and development

S.E.

Standard error

STEM Science, technology, engineering and mathematics
TALIS Teaching and Learning International Survey
UIS

UNESCO Institute of Statistics

UOE

Refers to the data collection managed by the three organisations, UNESCO, OECD, Eurostat

VET

Vocational education and training

References

OECD (2020), 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]

UIS (2014), ISCED Fields of Education and Training 2013 (ISCED-F 2013): Manual to Accompany the
International Standard Classificiation of Education 2011, UNESCO Institute for Statistics, Montreal,
http://dx.doi.org/10.15220/978-92-9189-150-4-en.

[4]

Notes
1 On 15 May 2020, the OECD Council invited Costa Rica to become a Member. While Costa Rica is included in the OECD

zone aggregates reported in this publication, at the time of its preparation, the deposit of Costa Rica’s instrument of
accession to the OECD Convention was pending.
2 See Note 1.
3 See Note 1.

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24  EXECUTIVE SUMMARY

Executive summary
The employment advantage of an upper secondary vocational qualification over a
general one tends to weaken over the life-course
Although the provision of formal vocational education and training (VET) can extend from lower secondary to
short-cycle tertiary level, more than two-thirds of VET students are enrolled at upper secondary level. In some
countries, where vocational education is more common, adults with VET qualifications enjoy high employment
rates. However, the employment advantage of a vocational qualification tends to weaken over the life-course. On
average across OECD countries, the employment rate of 25-34 year-old adults with an upper secondary or postsecondary non-tertiary vocational qualification (82%) is similar to that among 45-54 year-olds (83%), whereas
employment increases from 73% to 80% among those with a general qualification. In contrast, the employment
advantage for tertiary-educated adults widens among older age groups. Earnings are also lower: while adults
with an upper secondary vocational qualification have similar earnings to those with a general one, they earn
34% less than tertiary-educated adults on average across OECD countries. Poorer labour-market prospects may
have contributed to the decline in the share of adults with an upper secondary vocational qualification across the
generations: 21% of 25-34 year-olds held such a qualification in 2019 compared to 26% of 45-54 year-olds on
average. In contrast, the share of tertiary-educated adults has risen from 35% among the older generation to
45% among young adults.

Combined school- and work-based learning is relatively uncommon despite the
benefits
The countries with strong integrated school- and work-based learning vocational programmes are also those with
the highest employment rates for adults with vocational qualifications, even surpassing those for tertiary-educated
adults in some cases. However, only one-third of all upper secondary vocational students are enrolled in such
programmes on average across OECD countries. The duration of the work-based component varies across
countries, from less than 30% of the length of the programme in Estonia and Israel to at least 80% in Austria, Finland
and Switzerland. The most popular fields of study among vocational graduates vary at different levels of education.
While engineering, manufacturing and construction is the most common broad field at upper secondary level, at
short-cycle tertiary level, most students graduate from business, administration and law, or health and welfare.

Enabling VET students to pursue tertiary studies can improve their learning and
employment outcomes
Around two-thirds of OECD countries have introduced pathways for vocational upper secondary students to
continue their education at the tertiary level. On average across OECD countries, almost 7 out of 10 upper
secondary vocational students are enrolled in programmes that provide direct access to tertiary education after
completion. Better prospects for further education may encourage students to complete their upper secondary
vocational qualification. Although the share of vocational upper secondary students who complete their
programmes within the theoretical duration plus two years (70%) is lower than for general ones (86%), vocational
students are more likely to complete their qualification if their programme provides direct access to tertiary
EDUCATION AT A GLANCE 2020 © OECD 2020

EXECUTIVE SUMMARY  25

education than if it does not. The most common direct route from upper secondary vocational programmes to
tertiary education is through short-cycle tertiary programmes, which are predominantly vocational in most OECD
countries, but also through bachelor’s programmes or equivalent. On average across OECD countries, 17% of
first-time tertiary entrants enter short-cycle tertiary programmes. The employment rate of adults with a short-cycle
tertiary degree is 4 percentage points higher than those with an upper secondary vocational attainment and they
earn 16% more on average across OECD countries.
Vocational programmes are often designed to allow older students who wish to develop new skills to re-enter
education later in life. While 37% of 15-19 year-old upper secondary students are in vocational programmes, the
share increases to 61% among students over 25. Similarly, first-time entrants to short-cycle tertiary education
also tend to be older than entrants to long-cycle tertiary programmes (bachelor’s or master’s long first degrees).

Total spending on educational institutions has increased at a lower rate than GDP
In 2017, total expenditure amounted to approximately USD 9 100 per student in primary institutions and
USD 10 500 in secondary institutions on average across OECD countries. Programme orientation influences the
level of spending: at upper secondary level, vocational programmes cost around USD 1 500 more per student
than general ones on average, as they tend to require more sophisticated equipment and facilities, and training
in the workplace can incur additional costs. At the tertiary level, total spending amounted to USD 16 300 per
student in 2017 on average across OECD countries. At this level, 68% of total spending comes from public
sources compared to 90% at lower levels of education. The largest share is devoted to staff compensation, which
accounts for 77% of expenditure at pre-tertiary level, and 67% at tertiary level. After increasing between 2005
and 2012, total expenditure on primary to tertiary institutions as a share of gross domestic product (GDP) has
fallen to 4.9% in 2017 on average, below its 2005 value of 5.1%. This is due to educational expenditure rising
more slowly than GDP over this period, growing by 17% while GDP grew by 27%.

Instruction and teaching time have remained relatively stable over time
In 2019, compulsory instruction time was 804 hours per year on average at primary level and 922 hours at lower
secondary level. This has remained relatively stable since 2014, with changes exceeding 5% in only a few
countries. While instruction time for students increases at higher educational levels, statutory teaching time in
public institutions decreases: teachers in OECD countries and economies are required to teach on average
778 hours per year at primary level compared to 680 hours at upper secondary level (general programmes).
Since 2015, the number of teaching hours per year declined by about 2% at both primary and lower secondary
education. Between 2000 and 2019, on average across OECD countries and economies with available data, the
statutory salaries of primary and secondary general teachers – with 15 years of experience and the most
prevalent qualifications – increased by 2-3%, despite salaries falling after the 2008 economic crisis. However,
among countries with available data for all reference years, salaries have remained about constant since 2015.

Other findings
On average across OECD countries in 2018, 26% of children under 3 were enrolled in early childhood education
and care (ISCED 0).
The number of international and foreign tertiary students has grown on average by 4.8% per year between 1998
and 2018. Although OECD countries host the great majority of international and foreign students, the fastest
growth has been among internationally mobile students enrolled in non-OECD countries.
An upper secondary qualification still offers good protection against unemployment. On average across OECD
countries, 61% of 25-34 year-olds without upper secondary education are employed, compared with 78% of those
with upper secondary or post-secondary non-tertiary education as their highest attainment.
EDUCATION AT A GLANCE 2020 © OECD 2020

26  INFOGRAPHIC: THE INS AND OUTS OF VOCATIONAL EDUCATION AND TRAINING

Infographic 1. The Ins and Outs of Vocational Education and Training

EDUCATION AT A GLANCE 2020 © OECD 2020

INFOGRAPHICS: THE INS AND OUTS OF VOCATIONAL EDUCATION AND TRAINING  27

EDUCATION AT A GLANCE 2020 © OECD 2020

28  YOUTH IN THE EDUCATION SUSTAINABLE DEVELOPMENT GOAL

Youth in the Education Sustainable
Development Goal
Highlights






Teaching resources, student outcomes, educational attainment and access to the labour market are all
emphasised in the agenda for the fourth Sustainable Development Goal on Education (SDG 4), which aims to
ensure access, quality and equity in education.
On average across OECD countries, lower secondary teachers (aged 25-64) in general programmes earn 89%
of the actual salaries of other tertiary-educated workers. There is, however, significant variation between countries
and by gender (Indicator D3, used as a proxy for SDG Indicator 4.c.5).
In over half of the countries with available data, at least 95% of lower secondary teachers report having participated
in professional development activities over the past year (SDG Indicator 4.c.7). The format and content of continuous
professional development activities for teachers vary significantly across countries, however.

Figure 1. Percentage of lower secondary teachers who participated in professional development
activities (2018)
SDG Indicator 4.c.7
%
100
98
96
94
92
90
88
86
84

France

Chile

Brazil

Japan

Portugal

Mexico

Spain

Colombi a

Slovak Republic

Denmark

Italy

Finland

Turkey

Norway

Belgium

OECD average-31

Sweden

Hungary

Israel

Iceland

England (UK)

Flemish Comm. (Belgium)

Estonia

Czech Republic

Korea

United States

Netherlands

Russian Federation

Slovenia

Latvia

New Zealand

Austria

Alberta (Canad a)

Australia

Lithuania

82
80

Note: Refers to professional development activities in which teachers participated in the 12 months prior to the survey. Professional development activities include
“Courses/seminars attended in person”, “Online courses/seminars”, “Education conferences where teachers and/or researchers present their research or discuss
educational issues”, "Formal qualification programme (e.g. degree programme)", "Observation visits to other schools", "Observation visits to business premises, public
organisations or non-governmental organisations", "Peer and/or self-observation and coaching as part of a formal school arrangement", "Participation in a network of
teachers formed specifically for the professional development of teachers", "Reading professional literature" or any other activity ("Other").
Countries and economies are ranked in descending order of the percentage of teachers who participated in professional development activities in the 12 months prior
to the survey.
Source: OECD, TALIS 2018 Database, Table I.5.1. See Source section for more information (https://doi.org/10.1787/69096873-en).
Statlink2 https://doi.org/10.1787/888934161653

EDUCATION AT A GLANCE 2020 © OECD 2020

YOUTH IN THE EDUCATION SUSTAINABLE DEVELOPMENT GOAL  29

Context
In 2015, at the United Nations General Assembly, member states renewed their commitment to global development
by adopting the 2030 Agenda for Sustainable Development. The Agenda is divided into 17 Sustainable Development
Goals (SDGs), and constitutes a universal call for action to end poverty, protect the planet and ensure that all people
enjoy peace and prosperity. The fourth Sustainable Development Goal (SDG 4) is dedicated to education and aims
to “ensure inclusive and equitable quality education and promote lifelong learning opportunities” by 2030 (UNESCO,
2016[1]).
Unlike previous global targets, like the Millennium Development Goals, SDG 4 places a focus on the quality of
education, with indicators related to teacher training and student outcomes, alongside more traditional measures of
quantity, such as access and participation. It also emphasises the importance of learning at all stages of life, by
investigating education at all levels (from early childhood education and care to tertiary education) and adult learning.
For this edition of Education at a Glance, the SDG chapter will focus on secondary education, which is considered a
crucial step for continuing to further education and for successful entry in the labour market (see Indicators A3 and A4).
This chapter builds on a selection of SDG 4 indicators to investigate the quality of and participation in secondary
education, looking at aspects such as teaching resources in lower secondary education, student outcomes, and the
link between upper secondary attainment and access to the labour market.

Other findings


Student performance in reading varies significantly across countries. For instance, while over 85% of students in
Canada, Estonia, Finland and Ireland who took part in the Programme for International Student Assessment
(PISA) attained Level 2 or above, only half of the students in Brazil and Colombia attained this level
(SDG Indicator 4.1.1.c).



In all countries and economies that participated in PISA 2018, girls scored significantly higher than boys in reading,
a gap of 30 points on average across OECD countries (SDG Indicator 4.1.1.c).



On average across OECD countries, less than 3% of youth are out of school in primary and lower secondary
education, but this share rises to 8% at upper secondary level (SDG Indicator 4.1.5).



On average across OECD countries, 17% of 15-24 year-olds are enrolled in vocational education (at the
secondary, post-secondary non-tertiary and short-cycle tertiary levels combined). Most of them are enrolled at
secondary level (SDG Indicator 4.3.3).

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30  YOUTH IN THE EDUCATION SUSTAINABLE DEVELOPMENT GOAL

Analysis
SDG 4 and its associated targets set an ambitious agenda that encompasses access, participation, quality and equity in
education, at all levels of education. The analysis below focuses on secondary education, and builds on selected SDG 4
indicators to investigate teaching resources in lower secondary education, student outcomes, and the relationship between
upper secondary attainment and access to the labour market.

Teaching resources in lower secondary education
Teachers are often at the centre of initiatives to improve the quality of education, as their work can shape the quality of
instruction and student learning outcomes (Darling-Hammond, 2017[2]) (OECD, 2018[3]). The SDG agenda dedicates an entire
target (SDG 4.c) to teachers, with indicators that help monitor issues such as the attractiveness of the teaching profession,
the supply of qualified and trained teachers, and teachers’ professional development.

How attractive are teacher salaries?
Together with the intrinsic benefits of teaching, working conditions (such as working hours or salaries), can be crucial to
attracting and retaining effective teachers. One way the SDG agenda investigates the attractiveness of the teaching
profession is through SDG Indicator 4.c.5, which is defined as the average teacher salary relative to other professions
requiring a comparable level of qualification. Due to the lack of an internationally agreed methodology, this indicator has not
yet been approved for monitoring. Nonetheless, Indicator D3, which investigates the same question, helps shed light on
teachers’ relative salaries.
On average across OECD countries, lower secondary teachers (aged 25-64) in general programmes only earn 89% of the
actual salaries of other tertiary-educated workers. Relative salaries vary significantly across countries, however. For instance,
while teachers earn around 65% of the actual salaries of other tertiary-educated workers in the Czech Republic and
the United States, they earn at least 30% more in Costa Rica, Lithuania and Portugal. To try and capture relative salaries, it
is also important to investigate gender differences, which tend to be significant in most countries. On average across OECD
countries, while lower secondary male teachers earn 77% of the salaries of other tertiary-educated full-time male workers,
female teachers earn slightly more than their counterparts in other professions. This higher earnings ratio among female
teachers may make the teaching profession more attractive to women, but it also reflects the persistent gender wage gap in
favour of men in the labour market.

How many teachers are available?
One way to monitor the supply of teachers is through the ratio of students to teaching staff. The SDG agenda attempts to
capture this issue with an emphasis on teaching quality, by dedicating an indicator (SDG Indicator 4.c.2) to the ratio of
students to trained teachers. In the SDG context, trained teachers are defined as teachers who have received at least the
minimum organised pre-service and in-service pedagogical teacher training required for teaching at the relevant level in a
given country. In the absence of a common standard for teacher training, Indicator D2 (which takes all teachers into account),
can help shed light on teacher supply. On average across OECD countries, there are 13 students per teacher in lower
secondary education. This ratio varies significantly across countries, however, ranging from 8 students per teacher in Austria,
Greece and Lithuania to 33 students per teacher in Mexico.

What share of teachers participate in professional development activities?
While initial teacher education provides the foundations, continuous professional development provides a means to improve
the quality of the teaching workforce and to retain effective staff over time. The SDG agenda investigates teachers’
professional development through SDG Indicator 4.c.7, which measures the percentage of teachers who received in-service
training in the last 12 months by type of training. Data from the OECD Teaching and Learning International Survey (TALIS)
2018 can help monitor this measure. As shown in Figure 1, in over half of the countries and economies with available data,
at least 95% of lower secondary teachers declared they had participated in professional development activities over the past
year. Although there is variation across countries – with values ranging from 83% in France to 99% in Alberta (Canada),
Australia, Austria, Latvia and Lithuania – these results show that professional development has become a crucial part of
teachers’ career paths (OECD, 2019[4]). Participation in teacher training, however, does not always mean the same thing.

EDUCATION AT A GLANCE 2020 © OECD 2020

YOUTH IN THE EDUCATION SUSTAINABLE DEVELOPMENT GOAL  31
Box 1 discusses some of the differences in the format and content of lower secondary teachers’ training within TALISparticipating countries.

Box 1. Teacher professional development, by type of training and content
Teacher professional development can take different forms, from informal activities (e.g. networking, within-school peer
collaboration and reading professional literature) to formal activities (e.g. workshops, conferences and formal qualification
programmes). On average across OECD countries, as many as 76% of lower secondary teachers declared they had
attended courses or seminars in person over the past year, 72% had read professional literature, and 49% had participated
in education conferences where teachers, principals and/or researchers present their research or discuss educational
issues (Figure 2).
The forms teachers’ professional development take vary significantly across countries. For instance, while at least 90%
of teachers participate in courses/seminars in person in Australia, Austria, Latvia, Lithuania and Slovenia, only 50% or
less do so in France and Japan. Similarly, at least 70% of teachers in Alberta (Canada), Latvia and the Russian Federation
attend education conferences, compared to less than 30% of teachers in the Czech Republic and the Slovak Republic
(Figure 2).

Figure 2. Percentage of lower secondary teachers who participated in the following types of
professional development (2018)
OECD average-31
OECD and partner countries/economies
Courses and/or seminars attended in person
Reading professional literature
Education conferences
Peer and/or self-observation and coaching as part of a formal arrangement
Participation in a network of teachers formed specifically
for the professional development of teachers
Online courses and/or seminars
Formal qualification programme
0

10

20

30

40

50

60

70

80

90

100 %

Note: The following countries/economies are included: Alberta (Canada), Australia, Austria, Belgium, the Flemish Community of Belgium, Brazil, Chile, Colombia,
the Czech Republic, Denmark, England (United Kingdom), Estonia, Finland, France, Hungary, Iceland, Israel, Italy, Japan, Korea, Latvia, Lithuania, Mexico,
the Netherlands, New Zealand, Norway, Portugal, the Russian Federation, the Slovak Republic, Slovenia, Spain, Sweden, Turkey and the United States.
Data for additional types of professional development are available in the TALIS 2018 Database, Table I.5.7.
The types of professional development programmes are ranked from highest to lowest according to the share of lower secondary teachers participating in them, on
average across OECD countries participating in TALIS.
Source: OECD, TALIS 2018 Database, Table I.5.7. See Source section for more information (https://doi.org/10.1787/69096873-en).

Statlink2 https://doi.org/10.1787/888934161672

In terms of content, on average across OECD countries, a large share of teachers report participating in professional
development activities related to the “knowledge and understanding of my subject field(s)” (76%) and the “pedagogical
competencies in teaching my subject field(s)” (73%). This may reflect the fact that teacher training is often linked with
large-scale educational reforms leading to changes in subject and pedagogical content (Little, 1993[5]; Kennedy, 2014[6];
Avalos, 2011[7]). In contrast, teachers were less likely (around 20%) to participate in training activities about “school
management and administration”, “teaching in a multicultural or multilingual setting” and “communicating with people from

EDUCATION AT A GLANCE 2020 © OECD 2020

32  YOUTH IN THE EDUCATION SUSTAINABLE DEVELOPMENT GOAL
different cultures or countries”. As with the forms of teacher training, there is also variation across countries in the content
of training. For instance, while less than 60% of teachers participated in training related to the “knowledge and
understanding of my subject field(s)” in France and Sweden, this proportion exceeds 90% in Korea and Latvia (Figure 3).
This cross-country variation may reflect, in part, the type of initial training received by teachers. For instance, in France,
teachers’ initial training strongly emphasises field-specific knowledge, and a below-average share of lower secondary
teachers report needing training in this area (OECD, 2019[4]).

Figure 3. Percentage of lower secondary teachers who participated in professional development in the
following areas (2018)
OECD average-31
OECD and partner countries/economies
Knowledge and understanding of my subject field(s)
Pedagogical competencies in teaching my subject field(s)
Student assessment practices
Knowledge of the curr iculum
ICT skills for teaching
Student behaviour and classroom management
Teaching cross-curr icular skills
Analysis and use of student assessments
Approaches to individualised learning
Teaching students with special needs
Teacher-parent/guardian co-operation
School management and administration
Teaching in a multicultural or multilingual setting
Communicating with people from different cultures or countries
0

10

20

30

40

50

60

70

80

90

100 %

Note: The following countries/economies are included: Alberta (Canada), Australia, Austria, Belgium, the Flemish Community of Belgium, Brazil, Chile, Colombia,
the Czech Republic, Denmark, England (United Kingdom), Estonia, Finland, France, Hungary, Iceland, Israel, Italy, Japan, Korea, Latvia, Lithuania, Mexico,
the Netherlands, New Zealand, Norway, Portugal, the Russian Federation, the Slovak Republic, Slovenia, Spain, Sweden, Turkey and the United States.
Data for additional types of professional development are available in the TALIS 2018 Database, Table I.5.18.
Areas of professional development are ranked from highest to lowest according to the share of lower secondary teachers participating in them, on average across
OECD countries participating in TALIS.
Source: OECD, TALIS 2018 Database, Tables I.5.18. See Source section for more information (https://doi.org/10.1787/69096873-en).

Statlink2 https://doi.org/10.1787/888934161691

Student learning outcomes at age 15
The way teaching is organised and delivered, together with other factors such as class sizes or the human and financial
resources available in schools, can have a strong impact on student learning outcomes. The Programme for International

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YOUTH IN THE EDUCATION SUSTAINABLE DEVELOPMENT GOAL  33
Student Assessment (PISA) measures the performance of 15-year-olds, who are enrolled in either lower secondary or upper
secondary education. As such, it helps monitor SDG Indicator 4.1.1.c, which measures the proportion of youth at the end of
lower secondary education who achieve at least a minimum proficiency level (i.e. Level 2 or above in the PISA context) in
reading and mathematics.
As shown in Figure 4, student performance in reading varies significantly across countries. For instance, the vast majority of
students (over 85%) attained Level 2 or above in Canada, Estonia, Finland and Ireland, while only half of the students attained
this level in Brazil and Colombia. It is important, however, to look beyond national averages and examine results by gender.
In all countries and economies that participated in PISA 2018, girls scored significantly higher than boys in reading, by
30 points more on average across OECD countries. Finland had the widest gender gap (over 50 points), while the narrowest
gaps (under 20 points) were in Chile, Colombia and Mexico. These gender disparities in achievement raise concerns, as they
may have long-term consequences for boys’ and girls’ academic and professional lives (OECD, 2019[8]).

Figure 4. Percentage of 15-year-old students at Level 2 or above in the PISA reading assessment (2018)
SDG Indicator 4.1.1
%
100
90
80
70
60
50
40
30
20

(93%)
(96%)
(96%)
(86%)
(90%)
(88%)

(88%)
(91%)
(85%)
(98%)
(86%)

(89%)
(86%)
(91%)
(89%)
(87%)

(99%)
(95%)
(91%)
(94%)
(94%)
(89%)
(88%)
(85%)
(89%)
(89%)

(91%)
(90%)
(90%)
(73%)
(92%)
(87%)
(93%)
(81%)
(86%)
(89%)
(63%)
(66%)
(62%)
(65%)

Denmark
Japan
United Kingdom
Slovenia
Sweden

New Zealand
United States
Norway
Australia
Portugal

Germany
Czech Republic
France
Belgium
Russian Federation
Latvia
OECD average
Italy
Austria
Switzerland

Netherlands
Lithuania
Hungary
Turkey
Iceland
Luxembourg
Greece
Israel
Slovak Republic
Chile
Costa Rica
Mexico
Colombi a
Brazil

0

Estonia
Ireland
Finland
Canada
Poland
Korea

10

Note: The percentage in parentheses refers to the proportion of 15-year-olds in each country/economy who were covered by the PISA sample (Coverage Index 3). The
OECD average does not include Costa Rica.
Countries are ranked in descending order of the percentage of 15-year-old students who performed at or above Level 2.
Source: OECD, PISA 2018 Database, Tables I.B1.1 and I.A2.1. See Source section for more information (https://doi.org/10.1787/69096873-en).
Statlink2 https://doi.org/10.1787/888934161710

Participation in upper secondary education and potential impact on labour-market outcomes
Ensuring that all young people have the opportunity to succeed at school is key, as poor outcomes may translate into
difficulties in accessing further education and the labour market (OECD, 2019[8]). One way to capture access to education is
by measuring the out-of-school rate, which is defined as the percentage of children in the official age range for a given level
of education who are not enrolled in school (SDG Indicator 4.1.5). On average across OECD countries, less than 3% of youth
are out of school in primary and lower secondary education, but this share rises to 8% at the upper secondary level. This
increase is particularly striking in Colombia and Mexico, where over 20% of youth are out of upper secondary education,
compared to less than 3% at primary level (Figure 5).

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34  YOUTH IN THE EDUCATION SUSTAINABLE DEVELOPMENT GOAL

Figure 5. Out-of-school rate, by level of education (2018)
SDG Indicator 4.1.5
Upper secondary
Lower secondary
Primary

%
40

30

20

10

Netherlands

Estonia
Portugal

Ireland1

Spain
Belgium

New Zealand
Slovenia

Czech Republic

Russian Federation
Lithuania1

Poland
United States1

Finland

Latvia1
Kore a

Chile

France1
United Kingdom

Sweden
Greece

Italy
Israel1

EU23 average

OECD average
Norway

Austria
Australia

Denmark

Hungary
Slovak Republic

Brazil1

Germany
Iceland

Switzerland
Turkey

Luxembourg
Costa Rica

Mexico

Colombia

0

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 the out-of-school rate in upper secondary education.
Source: OECD (2020). 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 and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2 https://doi.org/10.1787/888934161729

One of the ways governments have attempted to increase upper secondary completion and facilitate young people’s entry
into the labour market is through the development of vocational programmes. The SDG agenda monitors vocational education
through Indicator 4.3.3, which measures the participation rate in technical and vocational programmes among 15-24 yearolds in formal education, work-based or in other settings. As shown in Error! Not a valid bookmark self-reference., on
average across OECD countries, 17% of 15-24 year-olds are enrolled in vocational education at the secondary, postsecondary non-tertiary and short-cycle tertiary levels combined. In almost all countries, the majority of students in vocational
programmes are enrolled at the secondary level. The exceptions include countries such as Chile, Korea and the Russian
Federation, where most students in vocational programmes are enrolled in short-cycle tertiary programmes. When analysing
SDG Indicator 4.3.3, it is important to note that the broad age range (15 to 24) may lead to an underestimation of vocational
enrolments in countries where vocational programmes are mainly attended by students from narrow age groups.
Increasing upper secondary attainment requires ensuring students can both access programmes and complete them. On
average across countries with available true cohort data1, 72% of students who entered upper secondary education graduated
within the theoretical duration of the programme in which they were enrolled. However, completion of upper secondary
education can be particularly challenging for students in vocational programmes. On average across countries with true cohort
data, the completion rate for vocational programmes within the theoretical duration is 62%, compared to 76% for general
programmes (Indicator B3). This gap raises equity concerns, as disadvantaged students are almost three times more likely
to be enrolled in a vocational track than advantaged students (OECD, 2016[9]).
Young people who leave school before completing upper secondary education tend to face challenges in the labour market,
including worse employment prospects. For instance, those who have not attained upper secondary education are more likely
to be neither employed nor in education or training (NEET). On average across OECD countries, as many as 39% of 25-to29 year-olds without upper secondary education are NEET, compared to 17% for those with an upper secondary or postsecondary non-tertiary qualification. In spite of differences in scope, these results can help shed light on SDG Indicator 8.6.1,

1 The true cohort method requires following an entry cohort through a specific time frame. For more information, see Indicator B3.

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YOUTH IN THE EDUCATION SUSTAINABLE DEVELOPMENT GOAL  35
which is defined as the proportion of youth (aged 15-24) who are not participating in any form of education (formal or nonformal) nor in employment or training.

Figure 6. Participation of 15-24 year-olds in vocational education and training, by level of education (2018)
SDG Indicator 4.3.3
Short-cycle tertiary
Post-secondary non-tertiary
Secondary

%
40
30
20
10

Brazil1

Colombia

Costa Rica

Lithuania1

Iceland

Estonia

New Zealand

Mexico

Denmark

Greece

Sweden

Chile

Australia

Korea

Spain

Israel1

Portugal

Latvia1

OECD average

Norway

Hungary

United Kingdom

EU23 average

Russian Federation

Poland

France1

Finland

Italy

Germany

Luxembourg

Netherlands

Slovak Republic

Belgium

Switzerland

Turkey

Austria

Slovenia

0

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 secondary, post-secondary and short-cycle tertiary
combined.
Source: OECD (2020). 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 and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2 https://doi.org/10.1787/888934161748

Definitions
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

Definition

4.1.1.c

Proportion of youth at the end of lower secondary education who achieve at least a minimum proficiency
level in reading and mathematics

4.c.2

Student-to-trained-teacher ratios

4.c.5

Average teacher salary relative to other professions requiring a comparable level of qualification

4.c.7

Percentage of teachers who received in-service training in the last 12 months by type of training

4.1.5

Upper secondary out-of-school rate

4.3.3

Participation rate in technical and vocational programmes (15- to 24-year-olds), by sex

8.6.1

Proportion of youth (aged 15-24 years) not in education, employment or training

EDUCATION AT A GLANCE 2020 © OECD 2020

36  YOUTH IN THE EDUCATION SUSTAINABLE DEVELOPMENT GOAL

Methodology
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/10.1787/69096873-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)

References

Avalos, B. (2011), “Teacher professional development in Teaching and Teacher Education over ten years”,
Teaching and Teacher Education, Vol. 27/1, pp. 10-20, http://dx.doi.org/10.1016/j.tate.2010.08.007.

[7]

Darling-Hammond, L. (2017), “Teacher education around the world: What can we learn from international
practice?”, European Journal of Teacher Education, Vol. 40/3, pp. 291-309,
http://dx.doi.org/10.1080/02619768.2017.1315399.

[2]

Kennedy, A. (2014), “Models of continuing professional development: A framework for analysis”, Professional
Development in Education, Vol. 40/3, pp. 336-351, http://dx.doi.org/10.1080/19415257.2014.929293.

[6]

Little, J. (1993), “Teachers’ professional development in a climate of educational reform”, Educational Evaluation
and Policy Analysis, Vol. 15/2, pp. 129-151, http://dx.doi.org/10.3102/01623737015002129.

[5]

OECD (2019), PISA 2018 Results (Volume II): Where All Students Can Succeed, PISA, OECD Publishing, Paris,
https://dx.doi.org/10.1787/b5fd1b8f-en.

[8]

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.

[4]

OECD (2018), Effective Teacher Policies: Insights from PISA, PISA, OECD Publishing, Paris,
https://dx.doi.org/10.1787/9789264301603-en.

[3]

OECD (2016), PISA 2015 Results (Volume I): Excellence and Equity in Education, PISA, OECD Publishing, Paris,
https://dx.doi.org/10.1787/9789264266490-en.

[9]

UNESCO (2016), Education for People and Planet: Creating Sustainable Futures for All, Global Education
Monitoring Report 2016, United Nations Educational, Scientific and Cultural Organization,
https://unesdoc.unesco.org/ark:/48223/pf0000245752.

[1]

Cut-off date for the data: 19 July 2020. Any updates on data can be found on line at http://dx.doi.org/10.1787/eag-dataen. More breakdowns can also be found at http://stats.oecd.org/, Education at a Glance Database.

StatLink: https://doi.org/10.1787/888934161634

EDUCATION AT A GLANCE 2020 © OECD 2020

| 37

Chapter A. The output of
educational institutions and
the impact of learning

EDUCATION AT A GLANCE 2020 © OECD 2020

38  A1. TO WHAT LEVEL HAVE ADULTS STUDIED?

Indicator A1. To what level have adults
studied?
Highlights


Younger adults (25-34 year-olds) are better educated than they were a decade ago. On average across OECD
countries, the share of younger adults without upper secondary education has decreased from 20% in 2009 to
15% in 2019.



On average across OECD countries, 40% of younger adults have upper secondary or post-secondary non-tertiary
education as their highest attainment. Of these, 59% held a vocational qualification. However, the share of adults
with a vocational qualification has decreased over the generations: the share is 66% among 35-44 year-olds and
72% among 55-64 year-olds.



Tertiary education is the most common attainment level among 25-34 year-olds on average in OECD countries
(45%). However, the share varies substantially across countries, ranging from 24% in Mexico to 70% in Ireland
and Korea. A bachelor’s degree or equivalent is the most common tertiary attainment level for younger adults in
most OECD and partner countries.

Figure A1.1. Educational attainment of 25-34 year-olds (2019)

%
100

Tertiary
Upper secondary or post-secondary non-tertiary (general orientation or no distinction by orientation)
Upper secondary or post-secondary non-tertiary (vocational orientation)
Below upper secondary

90
80
70
60
50
40
30
20
0

Korea
Russian Federation1
Slovenia
Poland
Canad a
Switzerland
Lithuania
Czech Republic
United States
Israel
Finland
Slovak Republic
Ireland
Australia
Austria
Latvia
Estonia
France
Netherlands
Greece
Hungary
Germany
EU23 average
Luxembourg
New Zealand
United Kingdom 2
Belgium
Chile1
OECD average
Sweden
Norway
Denmark
South Africa1
Iceland
Italy
Portugal
Colombi a
Argentina1
Spain
Brazil1
Turkey
Costa Rica
Mexico
Indonesia1
India1
China1

10

1. Year of reference differs from 2019. 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 (12% of adults aged 25-64 are in this group).
Countries are ranked in ascending order of the share of 25-34 year-olds who attained below upper secondary education.
Source: OECD (2020), Education at a Glance Database, http://stats.oecd.org. See Source section for more information and Annex 3 for notes
(https://doi.org/10.1787/69096873-en).
Statlink2https://doi.org/10.1787/888934161843

EDUCATION AT A GLANCE 2020 © OECD 2020

A1. TO WHAT LEVEL HAVE ADULTS STUDIED?  39

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.
Educational attainment is measured as the percentage of the population who have reached a certain level of education
and hold a formal qualification at that level. It is frequently used as a proxy measure of human 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, A6 and A7). Highly educated individuals tend to be more socially engaged and have higher
employment rates and higher relative earnings. Educational attainment is also positively associated with greater
participation in formal and non-formal adult education and training.
Individuals thus have incentives to pursue more education, and governments have incentives to provide the appropriate
infrastructure and policies to support higher levels of educational attainment across the population. Over past decades,
almost all OECD countries have seen a significant increase in educational attainment, especially among the young and
among women.

Other findings


In the majority of OECD countries, women are under-represented among adults who attained vocational upper
secondary or post-secondary non-tertiary education, and the gender gap in favour of men is wider among younger
adults than among older adults.



Vocational education often provides opportunities for work-based training. About three-quarters of younger adults
who attained vocational upper secondary or post-secondary non-tertiary education had some work experience
during their period of study, and work experience is often mandatory.



On average across OECD countries, the share of tertiary-educated younger adults has increased by roughly
10 percentage points between 2009 and 2019. For most countries, this has been associated with a simultaneous
decrease in the share of 25-34 year-olds with below upper secondary education or upper secondary or postsecondary non-tertiary education as their highest attainment.



Although short-cycle tertiary education only accounts for 8% of the attainment of 25-34 year-olds across OECD
countries, its share ranges from less than 1% in the Czech Republic, Germany, and Italy to more than 20% in
Canada and Korea. While vocational programmes are more common than general programmes at this level of
education, in some countries, such as Norway and the United States, more 25-34 year-olds attained a general
qualification at this level rather than a vocational one.

EDUCATION AT A GLANCE 2020 © OECD 2020

40  A1. TO WHAT LEVEL HAVE ADULTS STUDIED?

Analysis
Below upper secondary education
The attainment of upper secondary education has become a minimum requirement for navigating the modern economy and
society. Young people today who leave school before completing upper secondary education not only face difficulties in the
labour market, but also tend to have lower social connectedness than their higher-educated peers (OECD, 2019[1]). In most
OECD and partner countries, the majority of younger adults (25-34 year-olds) have attained at least upper secondary
education (Figure A1.1). On average across OECD countries, 31% of older adults (55-64 year-olds) did not attain an upper
secondary qualification, but this share falls to 15% among younger adults (25-34 year-olds). In all OECD member and partner
countries except Estonia, Latvia and Lithuania, 25-34 year-olds are more likely to have completed at least an upper secondary
education than 55-64 year-olds (Table A1.3).
On average across OECD countries, the share of younger adults with below upper secondary education as their highest level
of education has decreased from 20% in 2009 to 15% in 2019. The decrease has been more remarkable in countries which
initially had a high share of younger adults lacking upper secondary education. For example, in Costa Rica, Mexico, Portugal
and Turkey, more than 50% of 25-34 year-olds had not attained upper secondary education in 2009 and, although they are
still lagging behind the OECD average, this share has dropped by at least 10 percentage points over the last decade. In
Spain, the share of 25-34 year-olds without upper secondary education was also high in 2009 but it only fell by 5 percentage
points between 2009 and 2019, and it remains at 30%. Norway is the only country with comparable data for 2009 and 2019
where the proportion of younger adults with below upper secondary education increased over the last decade (Table A1.2
and Figure A1.2).

Figure A1.2. Changes in educational attainment of 25-34 year-olds between 2009 and 2019

Percentage
points
50

Tertiary education
Upper secondary or post-secondary non-tertiary education
Below upper secondary education

40
30
20
10
0
-10
-20
-30
-50

Ireland
Turkey
Slovak Republic
Portugal
Slovenia
Greece
Switzerland
Czech Republic
Latvia
Chile1
Lithuania
Iceland
Luxembourg
Brazil1
Denmark
EU23 average
United States
Korea
Netherlands
OECD average
Austria
Poland
Australia
Germany
Italy
Canad a
Spain
Indonesia1
United Kingdom 2
Mexico
Estonia
Sweden
Hungary
France
Belgium
Israel
Finland
Costa Rica
South Africa1
Norway

-40

Note: In most countries there is a break in the time series. Refer to Table A1.2 for more details.
1. Year of reference differs from 2019. 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 (12% of adults aged 25-64 are in this group).
Countries are ranked in descending order of the percentage-point change in tertiary-educated 25-34 year-olds between 2009 and 2019.
Source: OECD (2020), Table A1.2. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2https://doi.org/10.1787/888934161862

EDUCATION AT A GLANCE 2020 © OECD 2020

A1. TO WHAT LEVEL HAVE ADULTS STUDIED?  41
In most OECD and partner countries, young men are more likely than young women to lack an upper secondary qualification,
with an OECD average of 17% for young men and 14% for young women The gender gap is 10 percentage points or higher
in Iceland, Portugal and Spain. Indonesia and Turkey are the exceptions where the share of young women with only below
upper secondary education is at least 3 percentage points higher than the share of young men with the same educational
attainment. In addition, in about one-third of OECD and partner countries with comparable data for 2009 and 2019 –
Costa Rica, Iceland, Mexico, Norway and South Africa – the gender gap has increased over the last decade (Table A1.2).

Upper secondary and post-secondary non-tertiary education, by programme orientation
Among OECD countries, the share of 25-34 year-olds with upper secondary or post-secondary non-tertiary education as their
highest attainment ranges from 21% in Ireland to 60% in the Czech Republic (Figure A1.1). On average across the OECD,
this share has fallen from 44% in 2009 to 40% in 2019, as younger adults are more likely to pursue tertiary education than
they were a decade ago (Table A1.2). However, upper secondary or post-secondary non-tertiary education still represents
the most commonly attained level of education among 25-34 year-olds in 16 OECD countries: Austria, Chile, Colombia,
the Czech Republic, Estonia, Finland, Germany, Greece, Hungary, Italy, Latvia, Mexico, Poland, Portugal,
the Slovak Republic and Slovenia (Table A1.3).

Figure A1.3. Share of adults with a vocational qualification among those with upper secondary or
post-secondary non-tertiary qualifications as their highest attainment, by age group (2019)
55-64 year-olds
35-44 year-olds
25-34 year-olds

%
100
90
80
70
60
50
40
30
20

(2%)

(3%)

(2%)

Costa Rica

Israel

Mexico

Chile2 (10%)

Canada (10%)

Latvia (20%)

Czech Republic (24%)

Turkey (11%)

Greece (21%)

Lithuania (18%)

Spain (11%)

Iceland (17%)

Russian Federation2 (16%)

Portugal (19%)

Australia (20%)

Luxembourg (16%)

United Kingdom1 (19%)

Estonia (27%)

New Zealand (25%)

Sweden (21%)

Norway (21%)

OECD average (24%)

EU23 average (29%)

Belgium (27%)

Hungary (39%)

Poland (37%)

Denmark (25%)

Italy (35%)

Finland (39%)

Switzerland (31%)

France (31%)

Netherlands (31%)

Austria (39%)

Slovenia (41%)

Germany (46%)

0

Slovak Republic (47%)

10

Note: Only countries with available data on programme orientation are shown in the figure. The percentage in parentheses represents the share of 25-34 year-olds with a
vocational upper secondary or post-secondary non-tertiary qualification.
1. 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 (12% of adults aged 25-64 are in this group).
2. Year of reference differs from 2019. Refer to the Education at a Glance Database for more details.
Countries are ranked in descending order of the share of 25-34 year-olds with an upper secondary or post-secondary non-tertiary vocational qualification among all adults
who attained upper secondary or post-secondary education.
Source: OECD (2020), Education at a Glance Database, http://stats.oecd.org. See Source section for more information and Annex 3 for notes
(https://doi.org/10.1787/69096873-en).
Statlink2https://doi.org/10.1787/888934161881

EDUCATION AT A GLANCE 2020 © OECD 2020

42  A1. TO WHAT LEVEL HAVE ADULTS STUDIED?
Upper secondary education is often divided into two programmes: general programmes aim to prepare students for tertiary
education, while vocational ones are designed to lead directly to the labour market entry. In most countries, post-secondary
non-tertiary education is mainly vocationally oriented (Table A1.3).
On average across OECD countries, more adults with upper secondary or post-secondary non-tertiary qualifications as their
highest attainment completed vocational programmes than general programmes (27% of all adults compared to 16%).
However, in some countries, a higher share of adults with this attainment level have completed a general programme. The
difference is more than 10 percentage points in Canada, Chile, Costa Rica, Greece, Israel, Mexico, Portugal, and to a lower
extent (less than 5 percentage points) in the Czech Republic, Spain and Turkey (Table A1.1).
In most countries, the share of adults with vocational qualifications has decreased over the generations. On average across
OECD countries, among adults with upper secondary or post-secondary non-tertiary education as their highest attainment,
72% of 55-64 year-olds (older adults), 66% of 35-44 year-olds, and 59% of 25-34 year-olds (younger adults) held a vocational
qualification. In Luxembourg, Iceland and Mexico, the difference between older and younger adults exceeds 30 percentage
points (Figure A1.3). Technological innovations and economic integration have pushed many industries to upgrade their
required skills or qualifications. Young adults may have more interest than their older peers in pursuing general upper
secondary education and continuing their studies at tertiary level.
However, not all countries have followed the same trend. In Greece, Portugal and Spain, the share of vocational qualifications
has increased by more than 10 percentage points between the two extreme age groups, though these countries still lag
behind the OECD average. In France, Italy, the Netherlands and the Slovak Republic, the share has remained mainly stable
across generations and higher than the OECD average (Figure A1.3).

Figure A1.4. Share of women among those with vocational upper secondary or post-secondary nontertiary qualifications as their highest attainment, by age group (2019)

%
80

55-64 year-olds
25-34 year-olds

Women are more likely to attain
a vocational upper secondary
or post-secondary non-tertiary
qualification than men

70
60
50
40

Women are less likely to attain
a vocational upper secondary
or post-secondary non-tertiary
qualification than men

30
20

0

Mexico
Costa Rica
Chile1
Spain
Germany
United Kingdom2
Luxembourg
Netherlands
France
Switzerland
Portugal
New Zealand
Austria
Finland
Greece
OECD average
EU23 average
Belgium
Turkey
Slovak Republic
Hungary
Italy
Denmark
Israel
Estonia
Sweden
Australia
Poland
Russian Federation1
Latvia
Czech Republic
Slovenia
Norway
Lithuania
Iceland
Canada

10

1. Year of reference differs from 2019. Refer to the Education at a Glance Database 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 (12% of adults aged 25-64 are in this group).
Countries are ranked in descending order of the share of women among 25-34 year-olds with an upper seconday or post-secondary non-tertiary vocational qualification.
Source: OECD (2020), Education at a Glance Database, http://stats.oecd.org. See Source section for more information and Annex 3 for notes
(https://doi.org/10.1787/69096873-en).
Statlink2https://doi.org/10.1787/888934161900

EDUCATION AT A GLANCE 2020 © OECD 2020

A1. TO WHAT LEVEL HAVE ADULTS STUDIED?  43

Gender differences in vocational upper secondary and post-secondary non-tertiary education
In most OECD and partner countries, women are under-represented among adults who attained vocational upper secondary
or post-secondary non-tertiary education. In Canada, Iceland and Lithuania, women make up less than 35% of the 25-34 yearolds with this level of attainment. Chile, Costa Rica, Spain and Mexico are the only countries where women are more likely
than men to attain vocational upper secondary or post-secondary non-tertiary education (Figure A1.4).
The under-representation of women in vocational upper secondary or post-secondary non-tertiary education level is related
to fields of study and their minimum entry level. Women generally dominate in the field of health and welfare, reflecting their
supposed aptitutde for caring poisitions. On average across OECD countries, women make up more than 80% of vocatioanl
upper secondary or post-secondary non-tertiary graduates with a specialisation in health and welfare (OECD, 2019[1]). In
addition, this field of study often requires degrees beyond upper secondary level. Across OECD conuntries, only 13% of upper
secondary vocational graduates held a qualification in health and welfare (see Indicator B7). However, adults who attained
upper secondary or post-secondary non-tertiary education are predominated by those who only attained upper secondary
education. On average across the OECD, 36% of adults attained upper secondary education, while only 6% attained postsecondary non-tertiary education (Table A1.1).
In most OECD and partner countries, the gender gap in vocational upper secondary or post-secondary non-tertiary education
has widened over the generations. On average across OECD countries, women make up 46% of 55-64 year-olds with
vocational qualifications, while the share falls to 42% among 25-34 year-olds. In Australia, Chile, Costa Rica, Iceland,
Luxembourg, Turkey and the United Kingdom younger women are more likely to have a vocational qualification than older
women. Moreover, in Mexico and Spain, younger men and women are more equally attained vocational upper secondary or
post-secondary non-tertiary education than the older generation, though the gender gap is always in favour of women.
(Figure A1.4).

Box A1.1. Work experience during vocational upper secondary and post-secondary non-tertiary
education
Despite the expansion of tertiary education, upper secondary and post-secondary non-tertiary education remain commonly
attained levels of education in most countries. Secondary education today needs not only to provide basic knowledge for
students to continue studying, but also to enable graduates to enter the labour market (Musset, 2019[2]).
Vocational education and training can improve the school-to-work transition and the employment rate for young people
(OECD, 2017[3]) (see textbox in indicator A3). Over the past decade, many countries have launched initiatives to combine
formal study with work experience within the framework of vocational education. Despite their growing relevance in public
policy discourse, internationally comparable indicators fail to highlight the outcomes of such work-study programmes or
even to measure their prevalence.
In 2016, Eurostat included an ad-hoc module on young people on the labour market in its Labour Force Survey (EU-LFS).
The data, recently released, filled this gap for younger adults by identifying the labour-market status of young adults and
their work experience during their highest level of education. The ad-hoc module considers six types of work experience
the person might have had:
Apprenticeship: working experience which was a mandatory part of the curriculum, the work lasted at least
6 months and was paid.
Mandatory traineeship: working experience which was a mandatory part of the curriculum and the work was not
paid.
Other mandatory work-based training: working experience which was a mandatory part of the curriculum, but
with no further information on its duration or if it was paid or not.
Optional traineeship: working experience which was an optional part of the curriculum, but with no further
information on its duration, or if it was paid or not.
Work outside the curriculum: carried out work while being a student, but the work was not connected to the
ongoing studies.
No work experience: did not carry out any form of work (paid or unpaid) while being a student or pupil.

EDUCATION AT A GLANCE 2020 © OECD 2020

44  A1. TO WHAT LEVEL HAVE ADULTS STUDIED?
Figure A1.5 shows some results from 2016 EU LFS ad-hoc module. Among 25-34 year-olds who attained vocational upper
secondary or post-secondary non-tertiary education, 28% of them did not have any work experience while completing their
highest level of education. There are, however, significant variations across countries, with the share ranging from 3% in
Switzerland to 65% in Greece.

Figure A1.5. Distribution of 25-34 year-olds with vocational upper secondary or post-secondary nontertiary education as their highest level of attainment by type of work experience while studying (2016)
No work experience
Other types of work experience
Apprenticeship
Mandatory traineeship

%
100
90
80
70
60
50
40
30
20

Greece (20%)

Spain (12%)

Italy (36%)

Norway (21%)

Portugal (15%)

Ireland1 (15%)

Poland (39%)

Latvia (19%)

Slovenia (42%)

Estonia (27%)

Slovak Republic (56%)

United Kingdom (15%)

Belgium (28%)

Denmark (28%)

Average (28%)

Lithuania (18%)

Czech Republic1 (24%)

France (33%)

Turkey (11%)

Austria (41%)

Finland (39%)

Sweden (21%)

Germany (49%)

Netherlands (34%)

Hungary (23%)

0

Switzerland (32%)

10

Note: Data for "Other types of work experience" are calculated as 100% minus the share of the other three categories shown in the chart (Mandatory traineeship,
Apprenticeship and No work experience). Refer to Table A1.4., available on line, for more information. The percentage in parentheses represents the share of 25-34
year-olds who attained vocational upper secondary or post-secondary non-tertiary education.
1. Year of reference for the share of 25-34 year-olds who attained vocational upper secondary or post-secondary non-tertiary education differs from 2016. See Annex 3
for more information.
Countries are ranked in ascending order of the share of 25-34 year-olds with vocational upper secondary or post-secondary non-tertiary qualifications who had no work
experience during their highest level of education.
Source: OECD/Eurostat (2020), Table A1.4, available on line. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2https://doi.org/10.1787/888934161938

On average, roughly 80% of younger adults who did work experience while completing vocational upper secondary or postsecondary non-tertiary education had mandatory work-based training of some kind, but there are significant differences
across countries as to which type was most common. For some countries, such as Belgium, Estonia, Finland, France,
Hungary, Latvia, Lithuania, the Slovak Republic, Sweden and Turkey, mandatory traineeships were the most common form
among all types of work experience, whereas in Austria, Denmark, Germany, Switzerland and the United Kingdom,
apprenticeships were the most prevalent form (Figure A1.5). (Table A1.4, available on line).

EDUCATION AT A GLANCE 2020 © OECD 2020

A1. TO WHAT LEVEL HAVE ADULTS STUDIED?  45

Tertiary education
In all OECD and partner countries, except South Africa, tertiary attainment is higher among younger adults than older adults.
On average across OECD countries, 45% of 25-34 year-olds have a tertiary education, compared to 28% of 55-64 year-olds.
In more than half of OECD countries, tertiary education is the most common attainment level reached by all 25-34 year-olds
(Table A1.3). However, the share of tertiary-educated younger adults varies substantially across OECD countries, ranging
from 24% in Mexico to 70% in Ireland and Korea (Figure A1.1).
The share of 25-34 year-olds with a tertiary degree has also increased between 2009 and 2019 in all OECD and partner
countries. This rising share implies a falling share of younger adults without one. In most countries, there has been a reduction
in the shares of younger adults with either below upper secondary or upper secondary or post-secondary non-tertiary
education as their highest attainment. However, in Brazil, Costa Rica, Indonesia, Mexico, Portugal and South Africa, the share
of younger adults with tertiary education has increased alongside a rise in the share of those with upper secondary or postsecondary non-tertiary education as their highest attainment (Figure A1.2). In these countries, educational expansion started
relatively late, and the share of younger adults lacking upper secondary education is still large compared to other countries
(Figure A1.1).
From the gender perspective, younger women are more likely than younger men to achieve tertiary education in all OECD
countries. On average in the OECD, 51% of younger women have a tertiary degree, compared to 39% of younger men, and
the average gender gap in favour of women has widened between 2009 and 2019. Among countries with comparable data
between 2009 and 2019, only in Finland, Norway and the United States has the gender gap narrowed over the last decade
(Table A1.2). However, the aggregate data mask important gender disparities in fields of study: in most countries, women
dominate in health and welfare, but they are under-represented in the broad field of science, technology, engineering and
mathematics (OECD, 2019[1]).
In most OECD and partner countries, the largest share of tertiary-educated 25-34 year-olds have attained a bachelor’s or
equivalent degree, though the share varies substantially across countries. In the Czech Republic, France, Hungary, Italy,
Luxembourg, Poland, the Russian Federation, the Slovak Republic, Slovenia and Spain, those with a master’s degree
represent the largest share (Figure A1.6). For some countries, this might be related to their strong tradition of long first degree
programmes that lead directly to a master’s degree (OECD, 2019[1]). While for the Russian Federation, it is related to the fact
that implementation of programmes leading to a university bachelor’s degree is relatively recent.
On average across OECD countries, 8% of 25-34 year-olds have a short-cycle tertiary degree as their highest attainment, but
the share varies widely across countries. In the Czech Republic, Germany and Italy, less than 1% of younger adults have this
level of educational attainment while the share exceeds 20% in Canada and Korea. In Austria,, the most common attainment
among tertiary-educated 25-34 year-olds is a short-cycle degree. (Figure A1.6).
For most countries where short-cycle tertiary education exists, vocational programmes are more common than general ones.
However, in some countries, such as Canada, Norway and the United States, short-cycle tertiary degrees combine general
and vocational programmes. Argentina and Turkey only have general short-cycle tertiary programmes (Table A1.3).
Short-cycle tertiary education could have strong influence on tertiary attainment across countries. For example, 37% of
younger adults have a bachelor’s, master’s or doctoral or equivalent degree in both Portugal and in Sweden. However, as
younger adults in Portugal do not tend to attain short-cycle tertiary degrees, Portugal has much smaller share of tertiaryeducated younger adults than Sweden does (Figure A1.6).

EDUCATION AT A GLANCE 2020 © OECD 2020

46  A1. TO WHAT LEVEL HAVE ADULTS STUDIED?

Figure A1.6. Share of 25-34 year-olds with tertiary education, by level of tertiary education (2019)

%
80

Short-cycle tertiary
Bachelor’s or equivalent
Master’s or equivalent
Doctoral or equivalent

70
60
50
40
30
20
10
0

Note: Some categories might be included in other categories. Refer to Table A1.1 for more information. The percentage in parentheses represents the share of 25-34 yearolds adults with a bachelor's, master's or doctoral or equivalent degree.
1. Year of reference differs from 2019. Refer to the source table for more details.
Countries are ranked in descending order of the percentage of 25-34 year-olds with a bachelor's, master's or doctoral or equivalent degree, which is included in the
parentheses in the country data labels.
Source: OECD (2020), Table A1.1. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2https://doi.org/10.1787/888934161919

Box A1.2. Educational expectations and attainment among young people
Technological progress and globalisation mean in many countries deteriorating labour-market conditions for young people
without tertiary education or for those lacking the skills needed for the world of tomorrow (OECD, 2019[4]). Results from the
Programme for International Student Assessment (PISA) show that, on average across OECD countries, in 2018, 7 out of
10 15-year-old students expected to complete tertiary education. Furthermore, the share increased from 2009 to 2018 in
all countries with available trend data. Notably, in Latvia and Slovenia, it increased by more than 30 percentage points
(Figure A1.7).
However, not all 15-year-old students are likely to have achieved their expectations by the time they become 25-34 yearolds. In less than half of countries with available data for PISA 2009 did the share of tertiary-educated 25-34 year-olds in
2019 exceed the share of 15-year-old students who expected to complete a tertiary degree in 2009 (Figure A1.7).
On average in the OECD, the gap between the share of tertiary-educated 25-34 year-olds in 2019 and the share of 15year-old students who expect in 2018 to become tertiary educated is about 26 percentage points. The difference is over
50 percentage points in Brazil, Chile, Costa Rica, Indonesia, Mexico and Turkey. Given the current rate of increase in
tertiary attainment, it is unlikely that, in most countries, all the students expecting to earn a tertiary degree will be able to
do so within the next decade or so. Students may rely largely on their test scores received at school to form their
expectations about their future attainment. In some countries, teachers use marks as an important lever to motivate
students to put more effort into learning, and so students’ marks could be therefore higher than their real performance. The
difference between students’ ability to learn and the marks received could be one factor explaining the gap between their
expectations and their peer group’s eventual educational attainment (OECD, 2012[5]).

EDUCATION AT A GLANCE 2020 © OECD 2020

A1. TO WHAT LEVEL HAVE ADULTS STUDIED?  47

Figure A1.7. Percentage of 15-year-old students who expect to attain tertiary education (2009 and 2018)
and percentage of 25-34 year-olds with a tertiary degree (2019)
Percentage of 25-34 year-olds with a tertiary degree (2019)
Percentage of 15 year-old students who expect to attain tertiary education (2018)
Percentage of 15 year-old students who expect to attain tertiary education (2009)

%
100
90
80
70
60
50
40
30
20
0

United States
Korea
Canada
Turkey
Chile1
Costa Rica
Mexico
Brazil1
France
Ireland
Israel
Spain
Colombia
Japan2
Greece
Portugal
Indonesia1
Sweden
Lithuania
Argentina1
Belgium
Estonia
OECD average
Norway
Netherlands
Australia
United Kingdom
Slovak Republic
EU23 average
Slovenia
Russian Federation1
Czech Republic
Latvia
Denmark
Finland
Luxembourg
Italy
Iceland
New Zealand
Poland
Switzerland
Hungary
Austria
Germany

10

1. Year of reference differs from 2019. See Source section 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 percentage of 15-year-old students who expect to attain tertiary education (2018).
Source: OECD (2010), PISA 2009 Results: What Makes a School Successful?: Resources, Polices and Practices (Volume IV), https://doi.org/10.1787/9789264091559en; OECD (2019), PISA 2018 Results (Volume I): What Students Know and Can Do, https://doi.org/10.1787/5f07c754-en; and OECD/ILO/UIS (2020). See Source
section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2https://doi.org/10.1787/888934161957

Definitions
Age groups: Adults refer to 25-64 year-olds; younger adults refer to 25-34 year-olds; and older adults refer to 55-64 year-olds.
Completion of intermediate programmes for educational attainment (ISCED 2011) corresponds to a recognised
qualification from an ISCED 2011 level programme that is not considered sufficient for ISCED 2011 level completion and is
classified at a lower ISCED 2011 level. In addition, this recognised qualification does not give direct access to an upper ISCED
2011 level programme.
Educational attainment refers to the highest level of education reached by a person.
Levels of education: See the Reader’s Guide at the beginning of this publication for a presentation of all ISCED 2011 levels.
Vocational programmes: The international Standard Classification of Education (ISCED 2011) defines vocational
programmes as education programmes that are designed for learners to acquire the knowledge, skills and competencies
specific to a particular occupation, trade, or class of occupations or trades. Such programmes may have work-based
components (e.g. apprenticeships and dual-system education programmes). Suceessful completion of such programmes
leads to vocational qualifications relevant to the labour market and acknowledged as occupationally oriented by the relevant
national authorities and/or the labour market.

EDUCATION AT A GLANCE 2020 © OECD 2020

48  A1. TO WHAT LEVEL HAVE ADULTS STUDIED?

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/10.1787/69096873-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, 2020[8]).

References

Musset, P. (2019), “Improving work-based learning in schools”, OECD Social, Employment and Migration Working
Papers, No. 233, OECD Publishing, Paris, https://dx.doi.org/10.1787/918caba5-en.

[2]

OECD (2020), Regional Statistics Database - Educational attainment, by age group,
http://stats.oecd.org/Index.aspx?datasetcode= REGION_EDUCAT.

[8]

OECD (2019), Education at a Glance 2019: OECD Indicators, OECD Publishing, Paris,
https://doi.org/10.1787/f8d7880d-en.

[1]

OECD (2019), OECD Employment Outlook 2019: The Future of Work, OECD Publishing, Paris,
https://dx.doi.org/10.1787/9ee00155-en.

[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.

[7]

OECD (2017), Education at a Glance 2017: OECD Indicators, OECD Publishing, Paris,
https://dx.doi.org/10.1787/eag-2017-en.

[3]

OECD (2012), Grade Expectations: How Marks and Education Policies Shape Students’ Ambitions, PISA, OECD
Publishing, Paris, https://dx.doi.org/10.1787/9789264187528-en.

[5]

UNESCO Institute for Statistics (2012), International Standard Classification of Education (ISCED) 2011,
UNESCO-UIS, Montreal, http://uis.unesco.org/sites/default/files/documents/international-standardclassification-of-education-isced-2011-en.pdf.

[6]

EDUCATION AT A GLANCE 2020 © OECD 2020

A1. TO WHAT LEVEL HAVE ADULTS STUDIED?  49

Indicator A1 Tables
Table A1.1

Educational attainment of 25-64 year-olds (2019)

Table A1.2

Trends in educational attainment of 25-34 year-olds, by gender (2009 and 2019)

Table A1.3

Educational attainment of 25-34 year-olds and 55-64 year-olds, by programme orientation (2019)

WEB Table A1.4

Distribution of 25-34 year-olds with vocational upper secondary or post-secondary non-tertiary
education as their highest level of attainment by type of work experience while studying (2016)

Cut-off date for the data: 19 July 2020. Any updates on data can be found on line at http://dx.doi.org/10.1787/eag-dataen. More breakdowns can also be found at http://stats.oecd.org/, Education at a Glance Database.
StatLink: https://doi.org/10.1787/888934161767

EDUCATION AT A GLANCE 2020 © OECD 2020

50  A1. TO WHAT LEVEL HAVE ADULTS STUDIED?
Table A1.1. Educational attainment of 25-64 year-olds (2019)
Percentage of adults with a given level of education as the highest level attained
Upper secondar y
or post-secondar y non-tertiary

Bachelor's
or equivalent

Master's
or equivalent

Doctoral
or equivalent

All levels of education

(11)

(12)

(13)

(14)

(15)

0
12
0
16
0
1
0
26
0
9
33
x(12)
0
6
0
0
0
5
0
6
0
10
0
15
0
1
0
2
0
1
0
2
20
8
0
13
0
0
d
47
21 d
0
14
0
3
0
a
0
5
0
0
0
2
0
4
0
11
0
0
0
c
0
0
0
7
0
12
0
10
0 x(12, 13, 14)
0
6
0
10
0
11

27
4
22
22
15
24 d
16
6
20
13
18
11
16
23
13
24
35
24
5
31 d
32
16
28
17
16
24
29
20
7
7
3
7
11
18
22 d
13
24
24

8
13
17
11 d
2d
x(12)
3
17
14
21
16
12
12
7
11
18
15
13
14
x(12)
5d
16
15
28
2
14
5
12
24
18
22
15
16
14
19 d
2
12
12

1
1
1
x(13)
x(13)
x(12)
0
1
1
1
1
1
1
1
1
1
2
1
1
x(12)
x(13)
0
1
2
0
1
1
1
1
1
1
5
1
2
3d
0
1
2

100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100

27
33

3
1

7
5

18
15

13
16

1
1

100
100

28
35 d
x(10)
x(10)
x(10)
19
x(10)
x(10)

a
x(8)
x(10)
x(10)
x(10)
20
x(10)
x(10)

0
0
15
18
26
0
33
67

14
x(12)
6
1
3
25
0
1

20
17 d
3
10 d
8
3
24 d
5

1d
1
0d
x(12)
1
28
0
1d

x(13)
0
x(13)
x(12)
0
1
x(12)
x(13)

100
100
100
100
100
100
100
100

m

m

11

9

16

7

m

100

Prima ry

Completion
of intermediate
lower secondar y
prog rammes

Lower
secondary

Completion
of intermediate
upper secondary
prog rammes

Upper secondar y

Post-secondar y
non-tertiar y

General

Vocation al

No distinction

Tertiar y

Less than
primar y
OECD
Par tners

By progr amme
orientation

Shor t-cycle
ter tiar y

By level
of education

Below upper secondar y

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

Countries
Australia
Austria
Belgium
Canada
Chile 1
Colombia
Costa Rica
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Lithuania
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Por tugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
Unite d Kingdom2
United States

0
x(2)
3
x(2)
7
x(4)
11
0
x(2)
0
x(2)
2
x(2)
1
x(2)
x(2)
0
3
1
x(6)
x(2)
0
0
c
11
1
x(4)
0
0
2
0
0
2
x(2)
0
5
0
1

4
1d
5
2d
5
x(4)
27
0
2d
0
1d
5
4d
12
0
0d
6
4
4
x(6)
4d
0
0
7
16
5
x(4)
1
6
26
1
1
7
3d
2
38
0
3

a
a
a
a
a
a
8
a
a
a
a
a
a
0
1
a
a
a
a
a
a
a
0
a
2
a
a
a
a
a
0
a
a
a
a
a
a
a

13
13
14
6
21
38 d
8
6
16
9
8
13
10
10
14
21
14
7
33
x(6)
7
8
4
17
27
14
19 d
17
1
20
7
10
30
11
9
15
20
6

a
a
a
a
a
5
3
a
a
a
a
a
a
3
a
a
a
a
a
a
a
3
2
a
4
a
a
a
a
a
0
a
a
2
a
a
12
a

30
49
37
22
42
33 d
17
70 d
41
39
43
42
44
32
51
26
2
37
42
47 d
39
39
32
21
22
39
28
37
58
25
63
56
23
32
45 d
20
21
42 d

5
3
2
10
a
x(6)
0
x(6)
0
10
1
0
13
10
8
7
19
a
1
x(11)
a
13
18
2
a
0
14
2
3
1
2
a
0
7
x(6)
a
a
x(6)

15
6
12
22
34
x(10)
16
35
7
19
6
10
3
27
12
11
x(10)
30
10
x(10)
39 d
25
20
5
18
7
16
12
9
18
4
5
13
15
8
11
15
42 d

20
46
26
10
9
x(10)
2
34
35
30
38
32
53
15
47
22
x(10)
6
33
x(10)
x(8)
28
30
18
4
32
25
26
52
8
62
51
9
25
36
9
18
x(8)

OECD average
EU23 average

2
1

6
4

m
m

14
13

m
m

36
39

6
6

16
13

Argentina3
Brazil 3
China 4
Ind ia 5
Indonesia1
Russian Federation 3
Saudi Arabia 6
South Africa 3

5
14
3
46
17
x(2)
12
x(2)

17
20
25
14
27
1d
14
14 d

7
a
a
a
a
a
a
a

5
14
47
11
18
4
18
12

3
a
a
a
a
a
a
a

28
35
15 d
18
26
19
27
59

a
a
x(6)
0
0
20
6
8

G20 average

9

12

m

16

m

31

m

Note: In most countries, data refer to ISCED 2011. For Indonesia and Saudi Arabia, data refer to ISCED-97. See Definitions and Methodology sections for more information.
Data and more breakdowns are available at http://stats.oecd.org/, Education at a Glance Database.
1. Year of reference 2017.
2. Data for upper secondary attainment by programme orientation include completion of a sufficient volume and standard of programmes that would be classified individually
as completion of intermediate upper secondary programmes (12% of adults aged 25-64 are in this group).
3. Year of reference 2018.
4. Year of reference 2010.
5. Year of reference 2011.
6. Year of reference 2016.
Source: OECD/ILO/UIS (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2https://doi.org/10.1787/888934161786

EDUCATION AT A GLANCE 2020 © OECD 2020

A1. TO WHAT LEVEL HAVE ADULTS STUDIED?  51

Table A1.2. Trends in educational attainment of 25-34 year-olds, by gender (2009 and 2019)
Percentage of 25-34 year-olds with a given level of education as the highest level attained
Upper secondar y or post-secondar y
non-ter tiar y

Below upper secondar y

Par tners

OECD

Men

Women

Total

Men

Women

Ter tiar y

Total

Men

Women

Total

2009
(1)

2019
(2)

2009
(3)

2019
(4)

2009
(5)

2019
(6)

2009
(7)

2019
(8)

2009
(9)

2019
(10)

2009
(11)

2019
(12)

2009
(13)

2019
(14)

2009
(15)

2019
(16)

2009
(17)

2019
(18)

Countries
Australia
Austria
Belgium
Canada
Chile 1
Colombia
Costa Rica
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan 2
Korea
Latvia
Lithuania
Luxembourg
Mexico
Netherlands
New Zealand
Nor way
Poland
Por tugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
Unite d Kingdom3
United States

19 b
10
18 b
10
26 b
m
58
5b
22
18
12
17
14 b
30 b
14
33
17 b
16 b
33 b
m
3b
25
15 b
17 b
63
20 b
22
19
8b
57
5b
8b
41
10 b
8b
53 b
18 b
13

10
10
16
7
16
31
51
7
20
15
10
14
14
14
13
24
12
10
27
m
2
15
9
17
49
14
14
20
7
30
9
6
36
18
7
39
16
8

15 b
13
16 b
7
25 b
m
54
7b
16
10
7
15
14 b
19 b
14
24
12 b
10 b
26 b
m
2b
14
10 b
16 b
63
15 b
19
14
6b
46
5b
5b
30
8b
12 b
64 b
18 b
10

9
11
13
5
13
24
42
7
15
8
7
11
13
11
13
13
7
7
21
m
2
8
5
9
48
11
13
15
5
20
9
4
25
14
6
43
13
6

17 b
12
17 b
8
26 b
m
56
6b
19
14
10
16
14 b
25 b
14
28
15 b
13 b
30 b
m
2b
19
12 b
16 b
63
18 b
21
16
7b
52
5b
7b
35
9b
10 b
58 b
18 b
12

9
11
15
6
15
28
46
7
18
11
9
13
13
13
13
19
9
9
24
m
2
11
7
13
49
12
13
17
6
25
9
5
30
16
6
41
15
7

43 b
59
46 b
42
54 b
m
14
77 b
47
55
58
44
62 b
45 b
65
37
42 b
49 b
51 b
m
39 b
53
49 b
41 b
20
43 b
m
44
64 b
25
77 b
71 b
25
53 b
49 b
30 b
38 b
51

44
52
44
38
53
43
21
67
42
55
56
42
54
51
62
37
21
53
51
m
34
52
46
34
28
42
47
40
59
41
60
60
24
41
43
26
35
46

33 b
51
36 b
30
52 b
m
15
71 b
39
43
44
38
59 b
47 b
56
34
34 b
40 b
50 b
m
35 b
45
39 b
37 b
20
41 b
m
29
52 b
25
71 b
55 b
25
44 b
51 b
20 b
34 b
44

32
43
32
24
50
42
23
53
29
36
43
37
53
39
51
31
20
36
45
m
21
37
29
30
28
35
39
27
42
35
43
41
23
29
39
21
32
39

38 b
55
41 b
36
53 b
m
15
74 b
43
49
51
41
60 b
46 b
61
36
38 b
44 b
50 b
m
37 b
49
44 b
39 b
20
42 b
m
37
58 b
25
74 b
63 b
25
49 b
50 b
25 b
36 b
47

38
48
38
31
51
42
22
60
35
46
50
39
54
45
57
34
21
44
48
m
28
45
38
32
28
39
43
34
51
38
51
51
23
35
41
24
34
42

38 b
31
36 b
49
20 b
m
27
18 b
30
27
30
39
24 b
25 b
20
30
41 b
35 b
16 b
52 b d
58 b
22
36 b
42 b
17
37 b
m
38
28 b
18
17 b
22 b
34
37 b
43 b
17 b
43 b
36

46
37
40
55
30
26
28
26
39
30
34
44
32
35
25
39
68
37
22
59 d
64
34
45
49
23
44
39
40
34
29
31
34
41
41
51
35
49
46

52 b
36
49 b
63
23 b
m
31
22 b
45
46
49
48
27 b
34 b
30
42
54 b
51 b
25 b
59 b d
63 b
41
51 b
47 b
17
43 b
m
56
43 b
29
24 b
40 b
45
48 b
37 b
16 b
47 b
46

59
46
55
71
37
34
35
39
56
56
50
52
34
50
37
56
72
57
34
64 d
76
55
66
61
24
54
48
58
54
45
48
55
52
56
55
36
55
55

45 b
33
42 b
56
22 b
m
29
20 b
37
37
39
43
26 b
30 b
25
36
48 b
43 b
20 b
56 b d
61 b
32
44 b
44 b
17
40 b
m
47
35 b
23
21 b
30 b
39
42 b
40 b
17 b
45 b
41

52
42
47
63
34
30
31
33
47
43
42
48
33
42
31
47
70
47
28
62 d
70
44
55
55
24
49
44
49
43
37
39
44
47
48
53
35
52
50

OECD average
EU23 average

22
19

17
15

18
15

14
11

20
17

15
13

47
52

44
47

41
45

35
37

44
48

40
42

32
29

39
38

41
40

51
51

36
35

45
44

Argentina 4
Brazil 4
China 5
India 6
Indonesia 1
Russian Federation 4
Saudi Arabia
South Africa 4

m
51 b
63
58
60 b
m
m
27

32
37
m
m
48
6
m
21

m
44 b
66
70
65 b
m
m
23

24
28
m
m
51
4
m
15

m
47 b
64
64
62 b
m
m
25

28
33
m
m
50
5
m
18

m
39 b
19
26
32 b
m
m
70

33
45
m
m
37
39
m
74

m
43 b
16
18
25 b
m
m
73

31
47
m
m
31
27
m
79

m
41 b
18
22
28 b
m
m
72

32
46
m
m
34
33
m
77

m
10 b
18
16
8b
m
m
3

34
18
m
m
14
55
m
5

m
13 b
18
12
10 b
m
m
4

45
25
m
m
18
69
m
6

m
12 b
18
14
9b
m
m
3

40
21
m
m
16
62
m
6

G20 average

m

27

m

25

m

26

m

40

m

34

m

37

m

35

m

42

m

39

Note: In most countries there is a break in the time series, represented by the code "b", as data for 2019 refer to ISCED 2011 while data for 2009 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 2019.
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 (12% of adults aged 25-64 are in this group).
4. Year of reference 2018 instead of 2019.
5. Year of reference 2010 instead of 2009.
6. Year of reference 2011 instead of 2009.
Source: OECD/ILO/UIS (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2https://doi.org/10.1787/888934161805
EDUCATION AT A GLANCE 2020 © OECD 2020

52  A1. TO WHAT LEVEL HAVE ADULTS STUDIED?
Table A1.3. Educational attainment of 25-34 year-olds and 55-64 year-olds, by programme orientation (2019)
Percentage of 25-34 year-olds and 55-64 year-olds with a given level of education as the highest level attained
Upper secondary

55 -64
year-olds

25 -34
year-olds

55 -64
year-olds

25 -34
year-olds

55 -64
year-olds

25 -34
year-olds

55 -64
year-olds

25 -34
year-olds

55 -64
year-olds

25 -34
year-olds

55 -64
year-olds

Vocational

25 -34
year-olds

General

55 -64
year-olds

Tertiary

25 -34
year-olds

Vocational

55 -64
year-olds

General

25 -34
year-olds

Vocational

of which: Short-cycle tertiary

55 -64
year-olds

General

Upper
secondary or
post-secondary
non-tertiary

25 -34
year-olds
Par tners

OECD

Below upper
secondary

Post-secondary non-tertiary

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

(13)

(14)

(15)

(16)

(17)

(18)

Countries
Australia
Austria
Belgium
Canada
Chile 1
Colombia
Costa Rica
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungar y
Iceland
Ireland
Israel
Italy
Japan 2
Korea
Latvia
Lithuania
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
Unite d Kingdom 3
United States

9
11
15
6
15
28
46
7
18
11
9
13
13
13
13
19
9
9
24
m
2
11
7
13
49
12
13
17
6
25
9
5
30
16
6
41
15
7

30
20
33
13
54
64
64
9
24
8
15
31
13
44
19
30
41
19
50
m
33
9
5
42
71
31
28
22
11
69
12
19
52
19
15
75
27
10

18
8
11
21
42
x(11)
20
36 d
10
19
11
9
8
24
17
17
x(11)
41
13
m
28 d
25
20
15
26
8
18
13
14
19
4
10
12
7
10 d
13
15
42 d

14
5
13
26
25
x(12)
14
31 d
5
21
3
11
2
25
9
6
x(12)
24
9
m
43 d
27
24
c
10
8
15
10
7
14
4
3
14
15
8d
8
16
46 d

15
37
25
a
10
x(11)
1
24 d
25
17
38
31
30
8
23
13
x(11)
3
35
m
x(3)
13
10
14
2
31
10
19
34
17
46
41
11
19
31 d
11
19
a

16
48
22
a
5
x(12)
1
42 d
39
21
40
34
49
2
49
21
x(12)
10
28
m
x(4)
15
11
19
6
30
13
31
63
2
66
57
7
26
44 d
6
18
a

a
a
a
a
a
x(11)
a
x(3)
a
a
a
0
a
a
a
0
x(11)
a
a
x(13)
a
a
a
m
a
a
a
a
0
a
a
a
a
7
x(3)
a
a
a

a
a
a
a
a
x(12)
a
x(4)
a
a
a
0
a
a
a
0
x(12)
a
a
x(14)
a
a
a
m
a
a
a
a
0
a
a
a
a
3
x(4)
a
a
a

5
3
2
10
a
x(11)
1
x(5)
0
10
1
a
16
12
16
3
x(11)
a
1
x(13)
a
7
8
2
a
0
15
1
3
2
2
a
0
2
x(5)
a
a
x(3)

5
2
1
11
a
x(12)
c
x(6)
0
10
2
a
9
5
3
10
x(12)
a
0
x(14)
a
21
29
3
a
0
14
2
4
0
2
a
0
5
x(6)
a
a
x(4)

38
48
38
31
51
42
22
60
35
46
50
39
54
45
57
34
21
44
48
m
28
45
38
32
28
39
43
34
51
38
51
51
23
35
41
24
34
42

35
55
36
38
30
20
16
74
45
52
44
45
60
33
62
38
18
34
38
m
43
63
64
22
15
38
42
44
73
15
72
60
21
49
52
14
34
46

52
42
47
63
34
30
31
33
47
43
42
48
33
42
31
47
70
47
28
62 d
70
44
55
55
24
49
44
49
43
37
39
44
47
48
53
35
52
50

35
25
31
50
16
16
20
18
31
40
41
24
27
23
19
33
41
47
13
44 d
24
28
30
36
14
31
30
34
16
15
16
22
27
32
34
11
39
43

c
a
a
2
a
x(13)
a
x(13)
0
a
a
0
a
a
a
x(13)
x(13)
a
a
m
a
a
a
3d
a
a
a
10
0
a
a
a
a
0
x(13)
10
a
6

0
a
a
3
a
x(14)
a
x(14)
0
a
a
1
a
a
a
x(14)
x(14)
a
a
m
a
a
a
5d
a
a
a
6
0
a
a
a
a
0
x(14)
4
a
6

10
15
x(13)
22
10
x(13)
2
x(13)
0
c
c
14
0
1
3
x(13)
x(13)
10
0
m
21
7
a
x(15)
1
1
3
2
c
c
c
7
14
4
x(13)
a
7
4

10
14
x(14)
23
6
x(14)
2
x(14)
0
13
20
10
1
3
0
x(14)
x(14)
15
c
m
5
1
a
x(16)
0
2
5
5
0
c
0
8
7
2
x(14)
a
12
5

OECD average
EU23 average

15
13

31
26

18
14

15
13

21
25

26
31

m
m

m
m

5
5

6
5

40
42

42
47

45
44

28
27

m
m

m
m

7
m

7
6

Argentina 4
Brazil 4
China 5
Ind ia 6
Indonesia1
Russian Federation 4
Saudi Arabia
South Africa 4

28
33
64
64
50
5
m
18

47
63
88
81
81
5
m
48

32
46 d
x(11)
x(11)
x(11)
17
m
x(11)

23
22 d
x(12)
x(12)
x(12)
22
m
x(12)

a
x(3)
x(11)
x(11)
x(11)
a
m
x(11)

a
x(4)
x(12)
x(12)
x(12)
a
m
x(12)

a
a
x(11)
x(11)
x(11)
a
m
x(11)

a
a
x(12)
x(12)
x(12)
a
m
x(12)

a
a
x(11)
x(11)
x(11)
16
m
x(11)

a
a
x(12)
x(12)
x(12)
22
m
x(12)

32
46
18
22
34
33
m
77

23
22
8
12
12
44
m
43

40
21
18
14
16
62
m
6

29
14
4
7
7
50
m
9

13
x(13)
x(13)
x(13)
x(13)
a
m
x(13)

12
x(14)
x(14)
x(14)
x(14)
a
m
x(14)

a
x(13)
x(13)
x(13)
x(13)
22
m
x(13)

a
x(14)
x(14)
x(14)
x(14)
28
m
x(14)

G20 average

26

45

m

m

m

m

m

m

m

m

37

31

39

25

m

m

m

m

Note: In most countries data refer to ISCED 2011. For Indonesia and Saudi Arabia, data refer to ISCED-97. See Definitions and Methodology sections for more information.
Data and more breakdowns are available at http://stats.oecd.org/, Education at a Glance Database.
1. Year of reference 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 (12% of adults aged 25-64 are in this group).
4. Year of reference 2018.
5. Year of reference 2010.
6. Year of reference 2011.
Source: OECD/ILO/UIS (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2https://doi.org/10.1787/888934161824

EDUCATION AT A GLANCE 2020 © OECD 2020

54  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, one in two (53%) 18-24 year-olds are still in education. In Greece,
the Netherlands and Slovenia, two out of three young adults this age are still students, the highest share in
education. In contrast, in Colombia at most 30% of young adults are still in education.



On average across OECD countries, 14% of young adults aged 18-24 years old are neither employed nor in
education or training (NEET). In Argentina, Brazil, Chile, Colombia, Costa Rica, Greece, Italy, Mexico,
South Africa and Turkey at least 20% or more young adults are NEET.



In 2018, one in seven (14%) young adults with upper secondary attainment who had completed their education
up to two years earlier were NEET, on average across OECD countries. The share falls two years after graduation
from upper secondary education, but increases slightly in the longer run. Among young adults who had completed
their education two to three years earlier the share of NEETs was 10%, while among those who had finished four
to five years earlier the share was 12%.

Figure A2.1. Percentage of 18-24 year-olds not in education, by labour-market status (2019)

%
80

Unemployed
Inactive
Employed

70
60
50
40
30
20
0

Colombi a
Israel
Brazil1
New Zealand
Mexico
Turkey
South Africa1
United Kingdom
Argentina1
United States1
Austria
Chile1
Canada
Hungary
Costa Rica
Australia
Norway
Russian Federation
Italy
OECD average
Portugal
France
Poland
Ireland
Iceland
Estonia
Switzerland
Slovak Republic
EU23 average
Sweden
Finland
Denmark
Spain
Latvia
Belgium
Lithuania
Germany
Slovenia
Greece
Netherlands
Luxembourg

10

Note: NEET refers to young people neither employed nor in education or training.
1. Year of reference differs from 2019. 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 (2020), Table A2.1. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2https://doi.org/10.1787/888934162052

EDUCATION AT A GLANCE 2020 © OECD 2020

A2. TRANSITION FROM EDUCATION TO WORK: WHERE ARE TODAY'S YOUTH?  55

Context
The length and the quality of the schooling that individuals receive have an impact on their transition from education to
work, as do labour-market conditions, the economic environment and the cultural context. In some countries, young people
traditionally complete education before they look for work, while in other countries education and employment are
concurrent. In some countries, there is little difference between how young women and young men experience the
transition from education to work, while in other countries significant proportions of young women 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 develop 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


In general, the larger a country’s share of low-performing 15-year-old students in the Programme for International
Student Assessment (PISA), the larger the share of NEETs among young adults. For instance, the share of
NEETs is lowest in countries with only a small share of young adults with low skills in reading, mathematics and
science (below PISA Level 2) – such as in Canada and Denmark– while it is highest in countries with the highest
share of low-skilled students, such as Brazil and Costa Rica.



In 2019, the share of young adults who were neither employed nor in education or training was one of the lowest
since 2000. On average across OECD countries, 15.2% of 20-24 year-olds were NEET, while a decade earlier
the share of NEETs was about 4 percentage points higher (18.7%). Only Brazil, Denmark, Greece and Italy have
seen an increase in the share of NEETs since 2009.



More education reduces the risk of becoming NEET. Across OECD countries, 25-29 year-olds with below upper
secondary education are four times more likely to be NEET than those with a tertiary education.

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 are no longer in compulsory education
but a significant proportion of them will still be continuing their studies. However, due to the limited availabilty of historical
data on NEETs for 18-24 year-olds in the majority of countries, the analysis of trends focuses on 20-24 year-olds.

EDUCATION AT A GLANCE 2020 © OECD 2020

56  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 Brazil, Colombia, Israel and New Zealand, more than 65% of these
young adults are no longer in education, while the pattern is reversed in Greece, the Netherlands and Slovenia where two out
of three young adults are still in education (Figure A2.1).
Among 25-29 year-olds, only 16% are still in education on average across OECD countries, and the share is less than 10%
in Belgium, France, Hungary, Mexico, Poland, the Slovak Republic, South Africa and the Russian Federation. However, in
Denmark, Finland, Iceland and Israel, over 25% of 25-29 year-olds remain in education. Compulsory military service for both
men and women of at least two years explain why the proportion of 18-24 year-olds in education in Israel is relatively low
while the opposite is true among its 25-29 year-olds (OECD, 2020[1]).
Young adults no longer in education may be employed, unemployed or inactive. Among the 47% of young adults aged
18-24 years who are not in education, 70% are employed and 30% are inactive or unemployed. However, the proportion of
young adults who are employed varies considerably from country to country. 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, Italy, Turkey and South Africa, less than half of 18-24 year-olds who are not in education are employed (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 Estonia,
Germany, Iceland, the Netherlands, Norway, Slovenia, Sweden and Switzerland the share of NEETs is below 10%, while it
is 20% or more in Argentina, Chile, Colombia, Costa Rica, Greece, Italy, Mexico, and more than 30% in Brazil, South Africa
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, Iceland, Latvia, Portugal,
the Slovak Republic, Slovenia and Spain the share of unemployed NEETs exceeds that of inactive NEETs (Figure A2.1).

Trends in the transition from education to work
In 2019, the share of young adults neither employed nor in education or training was one of the lowest since 2000. On average
across OECD countries, 15.2% of 20-24 year-olds were NEET, while a decade earlier in 2009 the share of NEETs was about
3 percentage points higher (18.7%). This trend decline is largely explained by the negative effects on youth employment of
the 2008 financial crisis. 2009 was the first year after the onset of the financial and economic crisis in many countries, which
explains why the share of NEETs increased significantly in 2009 going on to reach its peak in many countries in 2010-11. On
average across OECD countries, the share of NEETs among 20-24 year-olds reached 19.2% in 2010 and gradually
decreased each year after that date (Table A2.2 and (OECD, 2020[1])).
Among the countries with comparable data for both 2009 and 2019, the relative decrease was the largest in Latvia and Turkey
where the share of NEETs among 20-24 year-olds fell by more than 10 percentage points. In a number of other countries
including Chile, Estonia, Germany, Hungary, Ireland, Mexico, the Slovak Republic, Sweden, the United Kingdom and
the United States, the share of NEETs still decreased by more than 5 percentage points over this period. In contrast, in a few
countries including Brazil, Denmark, Greece and Italy, the share of NEETs increased between 2009 and 2019 (Figure A2.2).
Part of the decline in the share of NEETs over the past decade is due to a growing number of young people continuing their
education. On average across OECD countries the percentage of 20-24 year-olds in education has increased from 42% in
2009 to 45% in 2019, while the increase exceeded 10 percentage points in some countries. This is the case in Greece,
Ireland, Latvia, Spain, Sweden and Turkey. Some of these countries have put policies in place to reduce early school leaving
and/or increase access to tertiary education (OECD, 2018[2]). Further education comprises different types of programmes,
including short-cycle vocational training combined with practical training to equip young adults with the necessary skills
needed in the labour market, and higher educational programmes leading to bachelor’s, master’s or equivalent degrees
(Figure A2.2).
In most countries, the fact that young people are staying in education longer has not just resulted in a decline in the proportion
of NEETs between 2009 and 2019. Another direct consequence has been the decline in the share of young adults not in

EDUCATION AT A GLANCE 2020 © OECD 2020

A2. TRANSITION FROM EDUCATION TO WORK: WHERE ARE TODAY'S YOUTH?  57
education and in employment. Among OECD countries with comparable data for 2009 and 2019, the decrease in the share
of 20-24 year-olds not in education and in employment over this period was at least 5 percentage points in Australia, Belgium,
Italy, the Netherlands, Norway and Portugal, and over 10 percentage points in Brazil, Greece and Spain. Some countries
show the opposite trend: in Estonia, Hungary, New Zealand, Poland and Slovenia, the share of employed adults aged 20-24
not in education increased between 2009 and 2019 while the share of young adults in education has fallen over the same
period (Table A2.2).

Figure A2.2. Trends in the percentage of NEETs among 20-24 year-olds (2009 and 2019)
2019
2009

%
50
45
40
35
30
25
20
15
10
5

South Africa1
Turkey
Brazil1
Italy
Colombia
Argentina1
Costa Rica
Mexico
Greece
Spain
Chile1
France
Israel
Russian Federation
Hungary
Belgium
Portugal
OECD average
United States1
Lithuania
EU23 average
Poland
New Zealand
Latvia
United Kingdom
Ireland
Finland
Denmark
Canada
Slovak Republic
Australia
Austria
Estonia
Sweden
Czech Republic
Germany
Norway
Slovenia
Switzerland
Netherlands
Iceland

0

1. Year of reference differs from 2019. Refer to Table A2.2 for more details.
Countries are ranked in descending order of the percentage of NEETs in 2019.
Source: OECD (2020), Table A2.2. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2https://doi.org/10.1787/888934162071

The diversity of the NEET population
Various dimensions such as gender, age, educational attainment and migration status affect the risk of becoming NEET.
Young women are more likely to be NEET than young men. Across OECD countries, 15.4% of 18-24 year-old women are
NEET while the share among men of the same age is slightly lower (13.2%). Although women are more likely to be NEET,
the reasons are not the same as for men. Some 10.7% of young women are inactive and not in education, compared to only
8.6% of men, while only 4.8% of women are unemployed and not in education, compared to 6.6% of men (OECD, 2020[1]).
The main reasons for inactivity among women are childcare responsibilities, while health and other factors are more prevalent
among men (OECD, 2016[3]). When interpreting the figures for inactive NEETs, it should be noted that some are only
temporarily inactive and may soon re-enter employment, education or training. Nevertheless, a small share may also have
become discouraged and stopped looking for work because they believe that there are no job opportunities for them
(Eurofound, 2016[4]).
In Argentina, Brazil, Colombia, Costa Rica, the Czech Republic, Mexico and Turkey, the gender gap in inactivity rates is at
least 10 percentage points among 18-24 year-olds. Mexico and Turkey are the only two OECD countries where the gender
gap is over 20 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, 2020[1]).

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58  A2. TRANSITION FROM EDUCATION TO WORK: WHERE ARE TODAY'S YOUTH?
Young adults in their upper twenties are more likely to be NEET than their younger peers. This is particularly true for women.
Among women, the share of inactive NEETs increases with age, while it is more or less stable among men. On average
across OECD countries, among 18-24 year-olds, 10.4% of women and 6.5% of men are inactive NEETs, a gender gap of 4
percentage points. Among 25-29 year-olds the share increases to 22.4% for women and to 11.8% for men, a gender gap of
more than 10 percentage points. At the same time, the differences in the share of unemployed NEETs by gender and age
are small, with shares all at about 5-7% (OECD, 2020[1]).
More education reduces the risk of becoming NEET. Across OECD countries 10.7% of tertiary-educated young adults aged
25-29 are NEET, compared to 16.7% of those with an upper secondary or post-secondary non-tertiary education and 39.2%
of those without upper secondary education. In other words, across OECD countries, young adults aged 25-29 without upper
secondary education are four times more likely to be NEET than those with tertiary education. The situation is especially
severe for 25-29 year-olds with below upper secondary education in the Czech Republic, France, Greece, Ireland, Italy,
the Slovak Republic, Slovenia, South Africa and Poland, where half or more of these young adults are NEET (OECD, 2020[1]).
Attaining at least upper secondary education considerably reduces the risk of becoming NEET. The positive impact of upper
secondary attainment is especially great in Austria, Germany, the Slovak Republic, Slovenia, and Switzerland. In all these
countries, the share of NEETs among 25-29 year-olds with an upper secondary or post-secondary non-tertiary education is
about one-quarter the share among those with below upper secondary education (OECD, 2020[1]). All of these countries have
a well-developed vocational education and training (VET) system at upper secondary level. VET programmes in Austria,
Germany and Switzerland also have a strong work-based component, which generally offer the best labour-market outcomes
to their graduates (see Indicators A3 and B7).
In most OECD and partner countries, foreign-born young adults are also more likely to be NEET. On average across OECD
countries, 18% of foreign-born 15-29 year-olds are NEET, compared to 13% of their native-born peers. The differences are
largest in Austria and Germany, where the percentage is about 25% among foreign-born 15-29 year-olds and below 10%
among native-born 15-29 year-olds. Early arrival in the country can reduce the risk of being NEET. For instance, among
foreign-born young adults who arrived in Germany at the age of 16 or older, one-third (32%) are NEET, compared with only
11% of those who arrived by the age of 15. This underlines the importance of education in helping young people acquire
sufficient literacy skills to participate in society and other key skills required by the labour market. (OECD, 2018[5]).

Transition from education to work among recent upper secondary graduates
Young adults are generally about 17-18 years old when they graduate from upper secondary education (see Table X1.1a).
From there, they can pursue different pathways. Typically, some will continue education, mostly at the tertiary level, but also
at the same level or in post-secondary non-tertiary programmes. Others leave education to seek employment or become
inactive for various reasons. The use of data from the European Labour Force Survey (EU-LFS) complemented by data from
administrative sources and graduate or non-graduate surveys for non-EU-LFS countries allows a more in-depth analysis of
the transition from school to work.
The share of NEETs by years since completing education is typically used to assess how smoothly young adults make the
school-to-work transition. In 2018, one in seven (14%) young adults with an upper secondary education who completed their
education up to two years earlier were NEET, on average in OECD countries. The share of NEETs falls at first following
graduation from upper secondary education, but increases slightly in the longer run: 10% of those who graduated two to three
years earlier are NEET, but this rises to 12% among those who graduated four to five years earlier (Figure A2.3).
The share of NEETs among recent upper secondary graduates varies considerably across countries. Among young adults
who completed upper secondary education less than two years ago, the percentage of NEETs is less than 5% in
the Czech Republic, the Netherlands and New Zealand and exceeds 30% in Greece and Turkey (Figure A2.3).
In most countries, the percentage of NEETs decreases during the first years following graduation from upper secondary
education. In Turkey, the share was 57% among graduates who graduated less than two years earlier, falling to 25% among
those who graduated between two and three years earlier, a difference of 32 percentage points. Similarly, in Greece the
difference between the two graduation cohorts is 21 percentage points. In Denmark, Finland, Italy, Latvia, Poland, Portugal
and Switzerland, even though the overall share of NEETs is lower, the difference between the two cohorts still exceeds
5 percentage points (Figure A2.3).
In many countries, the share of NEETs among upper secondary graduates tends to stabilise three or more years after leaving
education. The difference in the share of NEETS between those who completed upper secondary education two to three

EDUCATION AT A GLANCE 2020 © OECD 2020

A2. TRANSITION FROM EDUCATION TO WORK: WHERE ARE TODAY'S YOUTH?  59
years before and those who did so four to five years earlier is small in many countries. However, in some countries, the share
of NEETs rises among those who graduated four to five years earlier. For instance, in Latvia the difference is 13 percentage
points (8% of those who graduated two to three years ago and 21% of those who graduated earlier) while in Lithuania it is
6 percentage points (8% of the more recent cohort and 14% of the earlier one) (Figure A2.3).
In a few countries including Belgium, the Czech Republic, France, the Netherlands, New Zealand, Slovenia and
the United Kingdom, the share of NEETs increases steadily in the years after graduation from upper secondary. For instance
in France, the share of NEETs is 12% of young adults with upper secondary attainment who completed education less than
two years earlier, 15% of those who graduated two to three years earlier and 20% of those who graduated four to five years
earlier (Figure A2.3).
There are various reasons which may explain the increase in the share of NEETs over time. One reason may be the role of
active labour-market policies in the school-to-work transition. Many countries have adopted such policies to facilitate the
transition from education to work. Programmes promoting initial work experience, such as employment subsidy programmes,
may provide first-time work experience, but may not necessarily lead to permanent employment (Crépon and van den Berg,
2016[6]). Another reason may the higher risk for women of becoming NEET when starting a family. Care-giving and family
responsibilities may force young women to abandon their jobs after some years of professional experience and to become
inactive (OECD, 2016[3]).

Figure A2.3. Percentage of young adults with upper secondary education who are NEET, by years since
graduation (2018)
Adults aged 15-34 at graduation
Four to five years
Two to three years
Less than two years

57%

%
35
30
25
20
15
10

New Zealand3, 4

Czech Republic

Netherlands

United Kingdom

Slovenia

Norway

Germany

Austria

Belgium

Australia1, 3

Luxembourg

Ireland

Estonia

Lithuania

Slovak Republic

France3

Hungary

Sweden

Switzerland

United States1, 2, 3

EU23 average

Spain

OECD average

Denmark

Latvia

Poland

Finland

Portugal

Italy

Turkey

0

Greece

5

Note: NEET refers to young people neither employed nor in education or training. The time periods of “less than two years”, “two to three years” and “four to five years”
since graduation refer to 0-23 months, 24-47 months and 48-71 months since graduation respectively.
1. Year of reference differs from 2018. Refer to the source table for more details.
2. Data refer to 15-29 year-olds. Data reported under the category "Less than two years" refer to "One year" since graduation.
3. The source is different from EU-LFS.
4. General programmes only.
Countries are ranked in descending order of the percentage of young adults with upper secondary attainment who are NEET less than two years after completion.
Source: OECD (2020), Table A2.3. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2https://doi.org/10.1787/888934162090

EDUCATION AT A GLANCE 2020 © OECD 2020

60  A2. TRANSITION FROM EDUCATION TO WORK: WHERE ARE TODAY'S YOUTH?

Box A2.1. Basic skills and future labour-market outcomes among 15-19 year-olds
In most OECD countries compulsory education lasts until at least the age of 16 (see Indicator B1 and Table X1.3). In
most countries, the majority of students continue education well beyond this age. On average across OECD countries
86% of 15-19 year-olds are still in education.

Figure A2.4. Relationship between the percentage of 15-year-old students who were low performers
in PISA (2015) and the share of NEETs among 15-19 year-olds (2017)

OECD average

Proficiency below Level 2
in all three domains (%)
50

Brazil

40
Colombia
Mexico
Turkey

R² = 0.7063

30

Chile

Slovak Republic1
Israel

20

Hungary
Luxembourg
Belgium
Lithuania
Iceland1
Austria
Czech
Republic
Netherlands Sweden
Latvia
Germany
Australia
Norway
Canada
Poland
Slovenia
Finland Estonia
Portugal
Denmark
Switzerland

10

0
0

5

Greece

France
United States

OECD average

Italy

OECD
average
New
Zealand

Spain
United Kingdom
Ireland

10

15

20
NEETs (%)

Note: NEET refers to young people neither in employment nor in education or training. Low-skilled students refers to 15-year-old students who were below Level 2 in
mathematics, reading and science proficiency in PISA 2015.
1. Year of reference 2018 for the share of NEETs.
Source: NEETs: OECD (2020), Education at a Glance Database. PISA 2015 proficiency levels: OECD, PISA 2015 Database, Tables I.2.4a, I.2.6, I.2.7, I.4.4a and
I.5.4a (http://dx.doi.org/10.1787/888933431961). See Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2https://doi.org/10.1787/888934162109

Young adults, who have left education at an early age often have difficulty finding employment. On average in OECD
countries, 6.6% of 15-19 year-olds are neither employed nor in education or training (NEET) which amounts to almost
half of the young adults of this age who are not in education. The share of NEETs among 15-19 year-olds is at least 15%

EDUCATION AT A GLANCE 2020 © OECD 2020

A2. TRANSITION FROM EDUCATION TO WORK: WHERE ARE TODAY'S YOUTH?  61
in Brazil, Colombia, Costa Rica, and Turkey, while it is lowest (3% or less) in the Czech Republic, Latvia, Lithuania,
Luxembourg and Norway (OECD, 2020[1]).
To what extent are NEET rates related to skill levels among young people? The OECD Programme for International
Student Assessment (PISA) measures the proficiency in literacy, mathematics and science of 15-year-old students. PISA
results show that in many countries a large share of students have not even reached Level 2 on the six-level PISA scale.
Such students lack the elementary skills required to read and understand simple texts, or to master basic mathematical
and scientific concepts and procedures (OECD, 2016[7]).
The literature shows that low skills among 15-year-old students have a negative impact on the economy as a whole, as
well as on the labour-market outcomes of individuals (Hanushek and Woessmann, 2015[8]). Moreover, a Canadian study
has shown that 15-year-old students with higher PISA scores stay longer in education and attain higher qualifications
(OECD, 2010[9]).
Figure A2.4 compares the share of 15-year-old students with a proficiency level below Level 2 in reading, mathematics
and science with the share of NEETs among 15-19 year-olds. Data suggest that there is a relationship between the share
of low-skilled 15-year-old students and the percentage of NEETs among 15-19 year-olds (R2 = 0.71). In general, the
higher the percentage of low-skilled 15-year-old students in PISA, the higher the percentage of NEETs among
15-19 year-olds. The share of NEETs is lowest in countries with a small share of low performers in all three domains,
such as Canada, Estonia, Finland and Ireland, and highest in countries with the highest share of low-skilled students,
such as Brazil, Colombia, Mexico and Turkey (Figure A2.4).
On average across OECD countries, 20% of 15-year-old students have low skills in reading, measured as having a
reading proficiency below Level 2. Some 23% of students have low skills in mathematics and 21% of students in science,
while 13% perform below Level 2 in all three domains. The percentage of low performers in all three domains is about
5% in Canada, Estonia and Finland, but is at least 30% in Brazil, Colombia, Cost Rica, Mexico and Turkey. The share is
highest in Brazil (44%) ((OECD, 2016[7]) and Figure A2.4).

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 from the national labour force surveys 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 second three months (i.e. April,
May and June).
Education or training corresponds to formal education; therefore, someone not working but following non-formal studies is
considered NEET.
Data on the education and labour-market status of recent graduates by years since graduates are from the EU-LFS for all
countries participating in this survey. Different graduation cohorts have been combined (cross-cohort analysis) for the
retrospective analysis of the school-to-work transitions over a period of five years following their graduation. The most
important drawback of the data source is that it does not allow the changes in the education and labour force status to be
tracked between the assessment points in time. The data from the EU-LFS have been complemented by data from

EDUCATION AT A GLANCE 2020 © OECD 2020

62  A2. TRANSITION FROM EDUCATION TO WORK: WHERE ARE TODAY'S YOUTH?
administrative source and graduate or non-graduate surveys for non-EU-LFS countries. The recent graduate cohorts have
been restricted to adults who were 15-34 years old at the time of graduation.
Please see the OECD Handbook for Internationally Comparative Education Statistics 2018 (OECD, 2018[10]) for more
information and Annex 3 for country-specific notes (https://doi.org/10.1787/69096873-en).

Source
For information on the sources, see Indicator A1.
Data on subnational regions for selected indicators are
(http://stats.oecd.org/Index.aspx?datasetcode=REGION_EDUCAT).

available

in

the

OECD

Regional

database

Crépon, B. and G. van den Berg (2016), “Active labor market policies”, Annual Review of Economics, Vol. 8/1,
pp. 521-546, https://EconPapers.repec.org/RePEc:anr:reveco:v:8:y:2016:p:521-546.

[6]

Eurofound (2016), Exploring the diversity of NEETs, Publications Office of the European Union, Luxembourg,
http://dx.doi.org/10.2806/62307.

[4]

Hanushek, E. and L. Woessmann (2015), Universal Basic Skills: What Countries Stand to Gain, OECD Publishing,
Paris, https://dx.doi.org/10.1787/9789264234833-en.

[8]

OECD (2020), Education at a Glance Database - Transition from education to work,
http://stats.oecd.org/Index.aspx?datasetcode=EAG_TRANS.

[1]

OECD (2018), Education at a Glance 2018: OECD Indicators, OECD Publishing, Paris,
https://dx.doi.org/10.1787/eag-2018-en.

[5]

OECD (2018), Education Policy Outlook 2018: Putting Student Learning at the Centre, OECD Publishing, Paris,
https://dx.doi.org/10.1787/9789264301528-en.

[2]

OECD (2018), OECD Handbook for Internationally Comparative Education Statistics 2018, OECD Publishing,
Paris, https://doi.org/10.1787/9789264304444-en (accessed on 16 April 2020).

[10]

OECD (2016), PISA 2015 Results (Volume I): Excellence and Equity in Education, PISA, OECD Publishing, Paris,
https://dx.doi.org/10.1787/9789264266490-en.

[7]

OECD (2016), Society at a Glance 2016: OECD Social Indicators, OECD Publishing, Paris,
https://dx.doi.org/10.1787/9789264261488-en.

[3]

OECD (2010), Pathways to Success: How Knowledge and Skills at Age 15 Shape Future Lives in Canada, PISA,
OECD Publishing, Paris, https://dx.doi.org/10.1787/9789264081925-en.

[9]

References

EDUCATION AT A GLANCE 2020 © OECD 2020

A2. TRANSITION FROM EDUCATION TO WORK: WHERE ARE TODAY'S YOUTH?  63

Indicator A2 Tables
Table A2.1

Percentage of 18-24 year-olds in education/not in education, by work status (2019)

Table A2.2

Trends in the percentage of young adults in education/not in education, by age group and work status
(2009 and 2019)

Table A2.3

Young adults with upper-secondary education in education/not in education, employed or not, by years
since graduation (2018)

Cut-off date for the data: 19 July 2020. Any updates on data can be found on line at http://dx.doi.org/10.1787/eag-dataen. More breakdowns can also be found at http://stats.oecd.org/, Education at a Glance Database.
StatLink: https://doi.org/10.1787/888934161976

EDUCATION AT A GLANCE 2020 © OECD 2020

64  A2. TRANSITION FROM EDUCATION TO WORK: WHERE ARE TODAY'S YOUTH?
Table A2.1. Percentage of 18-24 year-olds in education/not in education, by work status (2019)
In education

Not in education

Inactive

Total

Employed

Unemployed

Inactive

(3) = (1) +(2)

(4)

(5)

(6) = (3) +(4) +(5)

(7)

(8)

(9)

5
9
0
x(2)
x(2)
a
a
m
x(2)
m
x(2)
7
17
a
a
a
a
x(2)
a
m
m
a
a
a
a
x(2)
a
1
a
a
c
x(2)
x(2)
a
16
a
5
x(2)

27
13
7
23 d
9d
10
16
m
32 d
21
22 d
5
16
5
3
39
22
11 d
2
m
m
18
17
c
10
42 d
17
20
10
6
2
17 d
8d
18
18
13
14
20 d

33
21
8
23
9
10
16
m
32
21
22
13
33
5
3
39
22
11
2
m
m
18
17
c
10
42
17
21
10
6
2
17
8
18
34
13
19
20

3.4
0.9
0.6
2.2
3.0
2.8
8.4
m
3.3
2.6
5.9
0.9
1.0
1.1
0.3
2.8
1.6
0.7
0.8
m
m
c
0.3
c
0.7
2.6
1.5
3.6
0.9
1.2
c
0.5
3.8
7.9
1.6
4.4
1.4
1.3

15
26
53
25
38
17
26
m
23
33
30
41
29
58
46
15
32
19
49
m
m
40
44
52
26
21
15
27
44
47
55
47
47
31
21
21
23
26

51
48
61
50
50
30
50
m
59
56
58
54
63
65
50
56
55
30
52
m
m
59
61
68
38
65
33
51
54
54
57
64
59
58
57
38
43
47

37
41
25
38
28
43
27
m
30
35
30
28
29
15
35
38
33
52
22
m
m
29
27
26
41
28
54
40
34
32
32
27
21
34
36
29
43
39

5.0
4.2
5.4
5.0
6.6
11.2
9.3
m
3.9
3.2
4.7
9.5
2.8
12.7
4.4
3.4
4.5
2.9
11.1
m
m
6.2
5.7
c
3.4
1.6
5.5
2.4
3.8
7.2
5.7
4.3
11.3
3.8
2.9
11.1
5.2
3.9

6
7
8
7
15
16
13
m
8
6
8
8
5
8
10
3
8
15
14
m
m
5
6
c
18
5
8
6
8
6
5
4
8
5
4
21
8
10

11.4
10.8
13.5
11.8
21.9
27.6
22.8
m
11.7
9.3
12.3
17.3
8.1
20.7
14.5
6.1
12.0
17.5
25.5
m
m
11.4
12.0
c
21.5
6.9
13.4
8.1
11.9
13.3
10.6
8.5
19.7
8.4
7.3
32.2
13.3
14.2

49
52
39
50
50
70
50
m
41
44
42
46
37
35
50
44
45
70
48
m
m
41
39
32
62
35
67
49
46
46
43
36
41
42
43
62
57
53

100
100
100
100
100
100
100
m
100
100
100
100
100
100
100
100
100
100
100
m
m
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100

OECD average
EU23 average

m
m

16
14

17
16

2.3
2.0

33
40

53
57

33
30

5.7
5.8

9
7

14.3
12.9

47
43

100
100

Argentina 2
Brazil 2
China
India
Indonesia
Russian Federation
Saudi Arabia
South Africa 2

a
a
m
m
m
m
m
a

12
14
m
m
m
7
m
1

12
14
m
m
m
7
m
1

4.3
5.2
m
m
m
2.1
m
0.8

31
14
m
m
m
42
m
41

47
33
m
m
m
52
m
42

29
37
m
m
m
34
m
16

8.8
13.1
m
m
m
5.4
m
18.3

15
18
m
m
m
9
m
24

24.1
30.6
m
m
m
14.3
m
41.9

53
67
m
m
m
48
m
58

100
100
m
m
m
100
m
100

G20 average

m

m

m

m

m

m

m

m

m

m

m

m

Total

Unemployed

(2)

Total

Total

(1)
Countries
Australia
Austria
Belgium
Canada
Chile 1
Colombia
Costa Rica
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungar y
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Lithuania
Luxembourg
Mexico
Netherlands
New Zealand
Nor way
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
Unite d Kingdom
United States 2

Total

Other
employed

NEE T

Students in
work-study
programmes
Par tners

OECD

Employed

(10) = (8) +(9) (11) =(7) +(10) (12) = (6) +(11)

Note: NEET refers to young people neither employed nor in education or training. See Definitions and Methodology sections for more information. Data and more
breakdowns are available at http://stats.oecd.org/, Education at a Glance Database.
1. Year of reference 2017.
2. Year of reference 2018.
Source: OECD (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2https://doi.org/10.1787/888934161995

EDUCATION AT A GLANCE 2020 © OECD 2020

A2. TRANSITION FROM EDUCATION TO WORK: WHERE ARE TODAY'S YOUTH?  65

Table A2.2. Trends in the percentage of young adults in education/not in education, by age group and work status (2009 and 2019)

Par tners

OECD

20 -24 year-olds

15 -29 year-olds

2009

2019

2009

2019

Not in education
In
education Employed
NEE T

Not in education
In
education Employed
NEE T

Not in education
In
education Employed
NEE T

Not in education
In
education Employed
NEE T

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

Countries
Australia
Austria
Belgium
Canada
Chile 1
Colombia
Costa Rica
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungar y
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Lithuania
Luxembourg
Mexico
Netherlands
New Zealand
Nor way
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United Kingdom
United States2

40
35
45
38
36
m
m
46
51
47
49
40
48
48
49
c
34
29 b
42
33
m
38
51
c
26
53
39
42
54
38
45
63
35
39
45
24
32
39

49
53
39
47
36
m
m
41
37
33
36
40
38
34
30
c
45
34 b
33
55
m
35
33
c
47
40
43
49
29
46
38
26
39
44
44
30
49
41

11.6
12.0
16.1
15.5
27.5
m
m
13.1
12.1
19.8
15.1
20.0
13.7
17.8
20.9
c
20.8
37.5 b
24.8
12.6
m
27.3
15.9
c
27.4
7.9
17.6
9.4
16.4
15.7
17.1
11.4
25.9
16.5
10.9
46.1
19.1
20.1

47
40
51
43
44
24
45
48
53
45
51
43
55
59
41
51
45
29
43
m
m
48
51
64
31
59
27
47
42
43
47
56
51
50
48
34
35
39

42
49
33
44
34
49
32
43
35
44
36
38
36
19
43
43
42
53
28
m
m
39
34
29
46
34
59
44
44
42
41
35
27
41
44
33
52
47

11.0
10.9
15.4
12.6
21.8
27.5
23.0
8.9
12.7
10.8
12.9
19.5
8.8
22.0
15.5
6.1
13.0
18.2
28.5
m
m
13.9
14.5
c
22.9
7.4
13.9
8.7
14.0
15.3
11.8
8.7
21.9
9.0
8.1
33.3
13.6
14.8

44
44
47
43
44
m
m
47
58
47
54
45
52
44
48
51
38
42 b
45
40
m
46
56
54
34
54
45
46
51
42
46
58
37
51
47
30
40
46

44
44
40
43
32
m
m
40
33
34
34
40
36
39
34
38
44
29 b
34
48
m
34
33
39
41
39
40
46
35
45
38
33
41
38
43
31
44
37

12.3
11.4
12.7
13.4
23.6
m
m
12.8
8.8
19.0
12.0
15.6
11.6
16.6
17.7
11.2
18.6
28.7 b
21.2
12.2
m
20.2
11.4
7.9
24.4
7.0
14.8
8.0
14.2
12.8
16.1
9.0
22.6
11.0
10.7
39.6
15.7
16.9

47
45
49
43
46
33
47
46
55
47
55
49
54
55
42
49
50
44
48
m
m
47
50
57
38
56
37
46
42
49
43
53
51
53
49
41
36
44

42
45
39
45
35
43
32
45
33
42
34
36
38
26
44
45
39
43
29
m
m
43
39
38
42
37
52
46
45
40
44
38
30
40
43
31
51
43

10.4
10.4
12.6
11.3
18.4
23.7
20.2
9.8
11.6
10.4
11.0
15.4
8.2
19.6
13.3
6.3
11.0
12.9
23.7
m
m
10.0
11.3
5.5
20.7
6.9
11.8
7.9
12.5
11.5
13.3
9.4
18.3
7.0
7.3
28.8
12.3
12.7

OECD average
EU23 average

42
45

40
38

18.7
17.2

45
49

40
38

15.2
14.0

46
48

38
38

15.5
14.2

47
49

40
39

13.0
12.0

Argentina 2
Brazil 2
China
India
Indonesia
Russian Federation
Saudi Arabia
South Africa 2

m
24 b
m
m
m
m
m
m

m
53 b
m
m
m
m
m
m

m
23.3 b
m
m
m
m
m
m

41
28
m
m
m
43
m
31

34
42
m
m
m
41
m
20

25.0
29.8
m
m
m
15.5
m
48.6

m
36 b
m
m
m
m
m
m

m
45 b
m
m
m
m
m
m

m
19.6 b
m
m
m
m
m
m

48
38
m
m
m
39
m
41

32
37
m
m
m
48
m
22

20.4
24.9
m
m
m
12.6
m
37.7

G20 average

m

m

m

m

m

m

m

m

m

m

m

m

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 2019.
2. Year of reference 2018 instead of 2019.
Source: OECD (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2https://doi.org/10.1787/888934162014

EDUCATION AT A GLANCE 2020 © OECD 2020

66  A2. TRANSITION FROM EDUCATION TO WORK: WHERE ARE TODAY'S YOUTH?
Table A2.3. Young adults with upper secondary education in education/not in education, employed or not, by years since
graduation (2018)
Adults aged 15-34 at graduation
Less than two years

Two to thr ee years

Par tners

OECD

Not in education

Four to five years

Not in education

Not in education

In education
(1)

Employed
(2)

NEET
(3)

In education
(4)

Employed
(5)

NEE T
(6)

In education
(7)

Employed
(8)

NEE T
(9)

Countries
Australia 1, 2
Austria
Belgium
Cana da
Chile
Colombia
Costa Rica
Czech Republic
Denmark
Estonia
Finland
France 3
Germany
Greece
Hungar y
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Lithuania
Luxembourg
Mexico
Netherlands
New Zealand 1, 4
Nor way
Poland
Por tugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United Kingdom
United States 1, 5

32
53
75
m
m
m
m
69
19
66
30
73
53
61
67
45
73
m
55
m
m
55
68
66
m
65
61
53
56
58
57
80
74
33
39
19
73
68

57
38
14
m
m
m
m
26
65
23
51
14
40
5
20
51
16
m
15
m
m
28
20
23
m
30
36
39
27
23
31
14
12
54
47
24
21
19

11
9
11
m
m
m
m
5
16
11 r
19
12
7
33
12
c
11
m
29
m
m
17
12
11 r
m
5
3
8r
18
19
12
7r
13
13
13
57
6
13

24
52
69
m
m
m
m
58
52
58
45
57
60
80
63
48
72
m
55
m
m
63
67
48
m
63
57
57
50
60
49
62
73
26
47
53
60
m

59
42
19
m
m
m
m
37
39
32
44
28
35
9
29
49
20
m
23
m
m
30
25
41
m
32
40
37
40
30
44
31
17
62
46
22
31
m

16
7
12
m
m
m
m
5
10
10 r
11
15
5
12
8
c
8
m
21
m
m
8r
8
11 r
m
5
3
5r
10
10
8
7r
10
11
6
25
8
m

21
31
39
m
m
m
m
32
49
39
47
37
49
75
43
48
52
m
42
m
m
36
54
30
m
49
42
43
27
39
27
45
66
17
37
57
33
m

67
57
48
m
m
m
m
60
42
50
44
44
45
13
46
49
37
m
34
m
m
44
32
61
m
45
52
50
60
49
62
43
21
73
56
25
55
m

12
11
13
m
m
m
m
8
9
11 r
9
20
7
11
11
c
11
m
23
m
m
21
14
c
m
6
5
7r
14
12
11
12 r
13
10
7
18
12
m

OECD average
EU23 average

57
60

29
27

14
13

56
58

34
32

10
9

42
42

47
46

12
12

Argentina
Brazil
China
India
Indonesia
Russian Federation
Saudi Arabia
South Africa

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

G20 average

m

m

m

m

m

m

m

m

m

Note: NEET refers to young people neither employed nor in education or training. The time periods of “less than two years”, “two to three years” and “four to five years”
since graduation refer to 0-23 months, 24-47 months and 48-71 months since graduation respectively. See Definitions and Methodology sections for more information.
1. Source different from the EU-LFS.
2. Year of reference 2019.
3. Data from national LFS.
4. General programmes only.
5. Year of reference 2017 and 2018 combined. The age group refers to 15-29 year-olds. Data reported under the category "Less than two years" refer to "One year" since
graduation.
Source: OECD (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2https://doi.org/10.1787/888934162033

EDUCATION AT A GLANCE 2020 © OECD 2020

68  A3. HOW DOES EDUCATIONAL ATTAINMENT AFFECT PARTICIPATION IN THE LABOUR MARKET?

Indicator A3. How does educational
attainment affect participation in the
labour market?
Highlights


Higher educational attainment increases the likelihood of being employed. On average across OECD countries,
the employment rate is 61% for 25-34 year-olds without upper secondary education, 78% for those with upper
secondary or post-secondary non-tertiary education as their highest attainment and 85% for those with tertiary
education.



On average across OECD countries, among 25-34 year-olds with upper secondary or post-secondary non-tertiary
attainment, the employment rate is roughly 10 percentage points higher for younger adults with a vocational
qualification (82%) than for those with a general qualification (73%).



In more than one-third of OECD and partner countries, the employment rates for 25-34 year-olds with vocational
upper secondary or post-secondary non-tertiary attainment are equal to or higher than the employment rates for
those with tertiary education. Most of these countries have upper secondary or post-secondary vocational
programmes with strong and integrated work-based learning or/and vocational programmes designed to offer
students direct entry to the labour market.

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 are more likely to find
employment. In contrast, 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. The health crisis we are experiencing linked to the spread of COVID-19 will undoubtedly
have an impact on unemployment, and those with lower educational attainment might be the most vulnerable. The impact
will have to be monitored in the coming years.
Young people often struggle to enter the labour market (see Indicator A2). Many OECD countries are increasingly
interested in the development of vocational education and training system to tackle youth unemployment. While vocational
education improves the school-to-work transition, it may become a challenge for vocationally trained individuals to learn
new skills later on (Hanushek, Woessmann and Zhang, 2011[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.

EDUCATION AT A GLANCE 2020 © OECD 2020

A3. HOW DOES EDUCATIONAL ATTAINMENT AFFECT PARTICIPATION IN THE LABOUR MARKET?  69

Figure A3.1. Employment rates of 25-34 year-olds, by educational attainment and programme
orientation (2019)
Tertiary
Upper secondary or post-secondary non-tertiary (general or no distinction by programme orientation)
Upper secondary or post-secondary non-tertiary (vocational orientation)
Below upper secondary

%
100

%
100

80

80

70

70

60

60

50

50

40

40

30

30

Argentina1
United States
Ireland
Colombia
Brazil1
Indonesia1
Korea
South Africa1

90

Luxembourg (16%)
Iceland (17%)
Sweden (21%)
Norway (21%)
Switzerland (31%)
Austria (39%)
Canada (10%)
Germany (46%)
Netherlands (31%)
Portugal (19%)
Slovenia (41%)
Russian Federation1 (16%)
Denmark (25%)
United Kingdom 2 (19%)
Hungary (39%)
New Zealand (25%)
Belgium (27%)
Czech Republic (24%)
Australia (20%)
EU23 average (29%)
OECD average (24%)
Lithuania (18%)
Slovak Republic (47%)
Israel (3%)
Estonia (27%)
Poland (37%)
Finland (39%)
Chile1 (10%)
France (31%)
Mexico (2%)
Spain (11%)
Costa Rica (2%)
Italy (35%)
Turkey (11%)
Greece (21%)

90

Note: The percentage in parentheses represents the percentage of 25-34 year-olds whose highest level of education is vocational upper secondary or post-secondary
non-tertiary education.
1. Year of reference differs from 2019. 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 (12% of adults aged 25-64 are in this group).
Countries in the left panel are ranked in descending order of the employment rate of 25-34 year-olds who attained vocational upper secondary or post-secondary nontertiary education, and those in the right panel are ranked in descending order of the employment rate of 25-34 year-olds who attained upper secondary or postsecondary non-tertiary education (general or no distinction by programme orientation).
Source: OECD (2020), Table A3.3. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2https://doi.org/10.1787/888934162242

Other findings


Work experience during study is associated with higher employment rates later on in adults’ careers. However,
rates vary greatly across countries and by the type of work experience acquired while studying.



Among adults with upper secondary or post-secondary non-tertiary education as their highest attainment, the
employment advantage for those with a vocational qualification as compared to those with a general qualification
tends to weaken over their lifetimes. In some countries, such as the Czech Republic, France and Mexico, the
initial employment benefit of a vocational qualification turns into a disadvantage for adults age 35 and over.



In all OECD countries, employment rates increase with time since graduation. In 2018, on average across OECD
countries, two out of three (66%) young adults with an upper secondary education were employed within two
years of graduation. The employment rate rises to 76% two to three years after graduation and to 79% four to five
years after graduation.



The unemployment rate of women who completed a vocational upper secondary or post-secondary non-tertiary
programme is higher than that of men. On average across OECD countries, 9% of young women with a vocational
programme as their highest attainment are unemployed, compared to 6% of young men.

EDUCATION AT A GLANCE 2020 © OECD 2020

70  A3. HOW DOES EDUCATIONAL ATTAINMENT AFFECT PARTICIPATION IN THE LABOUR MARKET?

Analysis
Educational attainment and employment
Upper secondary education is often considered the minimum requirement for successful labour-market integration. Adults
without this level of education are less employed, regardless of their age (Figure A3.2). On average across OECD countries,
the employment rate is 59% for adults (25-64 year-olds) without upper secondary education, 77% for those with upper
secondary or post-secondary non-tertiary education as their highest attainment, and 86% for tertiary-educated adults
Table A3.1).
In all OECD and partner countries, attainment of upper secondary or post-secondary non-tertiary education is associated with
higher employment rates. On average across OECD countries, the employment premium for adults with this level of education
as their highest attainment is roughly 20 percentage points more than those without upper secondary education. However,
the employment premium varies markedly across OECD and partner countries, ranging from 1 percentage point in Indonesia
to 40 percentage points in the Slovak Republic (Table A3.1).
Employment rates also tend to increase between upper secondary education and post-secondary non-tertiary education. On
average across the OECD, adults with post-secondary non-tertiary education enjoy better employment prospects than those
with only upper secondary education (81% compared to 76%). However, in Estonia, France, Spain and Sweden, the
employment rate is slightly lower for adults with post-secondary non-tertiary education than for adults with upper secondary
attainment (Table A3.1)
On average across OECD countries, the employment rate for tertiary-educated adults increases by a further 9 percentage
points, compared to those with upper secondary or post-secondary non-tertiary education as their highest attainment.
Furthermore, employment rates continue to increase with higher levels of tertiary education, from 82% for adults with a
short-cycle tertiary degree, to 84% for those with a bachelor’s or equivalent degree, 88% for those with a master’s or
equivalent degree and 93% for those with a doctoral or equivalent degree ( Table A3.1).
Adults with the most advanced qualifications (master’s and doctoral) generally have the best employment prospects. In most
countries with available data, the employment advantage for the additional step of earning a master’s qualification is
considerable, reaching at least 10 percentage points in Argentina and the Slovak Republic. In all countries except Greece,
the Slovak Republic and the Russian Federation, at least 90% of doctorate holders are employed (Table A3.1).

By age group and programme orientation
On average across OECD countries, higher educational attainment increases is associated with higher employment rates for
each age group. Among younger adults (25-34 year-olds), the average employment rate is 61% for those without upper
secondary education, 78% for those with upper secondary or post-secondary non-tertiary education as their highest
attainment, and 85% for those with a tertiary degree. Compared to the other age groups, employment rates are lowest for
55-64 year-olds, regardless of educational attainment level. This is mainly due to retirement, as a large proportion of
60-64 year-olds have already left the labour force (Figure A3.2).
In addition to increasing with educational attainment, employment rates also vary by the type of programme pursued. In the
majority of OECD and partner countries, upper secondary and post-secondary non-tertiary education consists of both general
and vocational programmes. Across OECD countries, 24% of younger adults attained a vocational upper secondary or
post-secondary non-tertiary education and 16% attained a general one (see Indicator A1). This greater prevalence of
vocational attainment is associated with strong employability in the labour market. On average in OECD countries, among
younger adults with upper secondary or post-secondary non-tertiary education as their highest attainment, the employment
rate is about 10 percentage points higher for those with a vocational qualification than for those with a general qualification,
at 82% compared to 73% (Figure A3.1).
The difference in employment rates between younger adults with a vocational or a general qualification is 27 percentage
points in Germany, but some of those with a general qualification are still enrolled in education. In Germany, younger adults
who completed a vocational programme account for more than 80% of all those with upper secondary or post-secondary
non-tertiary education as their highest attainment (see Indicator A1). Conversely, in Costa Rica, Estonia and

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A3. HOW DOES EDUCATIONAL ATTAINMENT AFFECT PARTICIPATION IN THE LABOUR MARKET?  71
the United Kingdom, younger adults with a general qualification at this level have better employment prospects than those
with a vocational qualification (Figure A3.1).
In some countries, such as Hungary, Iceland, Ireland, New Zealand, Norway and Sweden, most upper secondary vocational
programmes are not in theory designed to provide access to tertiary education, but rather to offer students direct entry to the
labour market or to pursue post-secondary non-tertiary education (see Indicator B7). Interestingly, those who leave education
with an upper secondary or post-secondary non-tertiary vocational qualification in most of these countries have excellent
employment prospects, significantly higher than those with a general qualification, and also higher than the OECD average.
The employment rates of younger adults with an upper secondary or post-secondary non-tertiary vocational qualification are
at least 90% in Iceland, Norway and Sweden (Figure A3.1).
Moreover, in more than one-third of OECD and partner countries, the employment rates for younger adults with vocational
upper secondary or post-secondary non-tertiary education are equal to or higher than the employment rates for those with
tertiary education (Figure A3.1). Some of these countries have vocational programmes with a strong and integrated
work-based learning component at upper secondary or post-secondary non-tertiary level. For example, in Austria, Germany,
Hungary, Sweden and Switzerland, at least 90% of younger adults with a vocational qualification obtained a work experience
while completing upper secondary or post-secondary non-tertiary education (see Box A1.1 in Indicator A1). However, the
employment advantage of a vocational qualification as compared to those with a general qulaification tends to weaken over
people’s lifetimes. On average across OECD countries, among adults with upper secondary or post-secondary non-tertiary
qualification as their highest attainment, the employment premium of vocational qualifications is 9 percentage points over a
general one for 25-34 year-olds, 5 percentage points for 35-44 year-olds, 3 percentage points for 45-54 year-olds and
1 percentage points for 55-64 year-olds (Figure A3.2). In the Czech Republic, France and Mexico, only 25-34 year-olds enjoy
any employment advantage from a vocational qualification. For adults age 35 and over, the employment rates are higher for
those with a general qualification than for those with a vocational qualification ( Table A3.3 and (OECD, 2020[3])).
At least two factors could explain this phenomenon of declining employment advantages. First, vocational programmes
generally aim to provide students with specific skills that are immediately valuable for employers. This occupational specificity
may cause some difficulties if they need to adapt to technological and structural changes in the economy (Hanushek,
Woessmann and Zhang, 2011[2]). Second, the proportion of younger adults who only have a general upper secondary or postsecondary non-tertiary qualification is small since most of them pursue further education and do not enter the labour market
at this stage.

Figure A3.2. Employment rates, by age group, educational attainment and programme orientation (2019)
OECD average
Below upper secondary
%
100

Upper secondary or
post-secondary non-tertiary
(general orientation)

Upper secondary
or post-secondary non-tertiary
(vocational orientation)

Short-cycle tertiary

Bachelor's, master's
or doctoral or equivalent

90
80
70
60
50
40
25-34 year-olds

35-44 year-olds

45-54 year-olds

55-64 year-olds

Note: The share of adults with a given educational attainment varies across age groups. See Indicator A1 for more information.
Source: OECD (2020), Education at a Glance Database, https://stats.oecd.org/. See Source section for more information and Annex 3 for notes
(https://doi.org/10.1787/69096873-en).
Statlink2https://doi.org/10.1787/888934162261

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72  A3. HOW DOES EDUCATIONAL ATTAINMENT AFFECT PARTICIPATION IN THE LABOUR MARKET?
On average across OECD countries, the employment rates for adults with a short-cycle tertiary degree are lower than those
with a bachelor’s, master’s or doctoral or equivalent degree, and the difference tends to increase with age (Figure A3.2). In
some countries, where short-cycle tertiary education is more common than the OECD average, employment rates are
relatively high for short-cycle tertiary degree holders at the beginning of their career. For example, in France, 14% of younger
adults have attained short-cycle tertiary education, compared to 8% on average across OECD countries. Their employment
rate is 88%, compared to 86% for those with at least a bachelor’s degree. No such employment premium is observed among
older age cohorts. In contrast, Latvia is the only country with a reversed trend: the employment rate for short-cycle tertiary
degree holders is higher than for those with a bachelor’s, master’s or doctoral degree among adults aged 35-64 (Table A3.3
and (OECD, 2020[3])).

Box A3.1.Work experiences during vocational upper secondary and post-secondary non-tertiary
education
It has been widely accepted that vocational education can ease the transition from school to work and improve employment
outcomes, as it provides opportunities for students to acquire skills relevant to the workplace during their studies. However,
vocational programmes at upper secondary or post-secondary non-tertiary level vary by type of work experience. Data
from the European Labour Force Survey (EU-LFS) ad-hoc module show that, among 25-34 year-olds with a vocational
upper secondary or post-secondary non-tertiary qualification as their highest attainment, apprenticeships, mandatory
traineeships and work outside the curriculum are the most common types of work experience among countries that
participated in the survey (see Box A1.1 in Indicator A1).

Figure A3.3. Employment rate of 25-34 year-olds who attained vocational upper secondary or postsecondary non-tertiary education, by type of work experience while studying (2016)
Apprenticeship
Mandatory traineeship
Work outside the curr iculum
No work experience

%
100
90
80
70
60

Iceland

Turkey

Finland

Greece

Italy

Ireland

France

Lithuania

Spain

Portugal

United Kingdom

Average

Denmark

Estonia

Poland

Sweden

Netherlands

Germany

Slovak Republic

Czech Republic

Belgium

Hungary

Slovenia

Latvia

Norway

Austria

40

Switzerland

50

Note: For the percentage of the population in each category, please refer to Table A1.4, available on line.
Countries are ranked in descending order of the employment rate of 25-34 year-olds with a vocational upper secondary or post-secondary non-tertiary educational
attainment who had no work experience during that period of study.
Source: OECD/Eurostat (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2https://doi.org/10.1787/888934162280

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A3. HOW DOES EDUCATIONAL ATTAINMENT AFFECT PARTICIPATION IN THE LABOUR MARKET?  73

In about half of countries with available data, the employment rate for 25-34 year-olds who completed an apprenticeship
is higher than the rate for those who did a mandatory traineeship, worked outside the curriculum, or did not gain any work
experience. This is most evident in Spain, where the employment rate for adults who did an apprenticeship is 14 percentage
points higher than those who had work experience outside the curriculum, and 28 percentage points higher than those who
did not have any work experience while studying. Younger adults who did a mandatory traineeship enjoy the highest
employment rate in Latvia, Lithuania and Portugal, though in these countries the types of work experience for vocational
work-study programmes are very limited (Figure A3.3 and Table A3.6, available online).
Having work experience unrelated to their studies can also have a positive impact on younger adults’ labour-market
outcomes. In about half of countries with available data, the 25-34 year-olds who had work experience outside the
curriculum have the highest employment rates among all younger adults with a vocational education. In Turkey, for
example, those who worked outside the curriculum have an employment rate at least 10 percentage points higher than
those with any other type of work experience (Figure A3.3).
The lack of work experience while studying is associated with lower employment rates later in life: 25-34 year-olds with
vocational upper secondary or post-secondary non-tertiary attainment who did not gain any work experience during study
have the lowest employment rates in about half of countries, and often by a large margin. However, not all types of work
experience are associated with better labour-market outcomes. In Poland, out of all types of work experience, young adults
who did an apprenticeship have the lowest employment rate. In Belgium, the Czech Republic, Greece, Hungary and
the Slovak Republic, the employment rates for those who did a mandatory traineeship are even lower than for those who
did not have any work experience at all (Figure A3.3). This finding is particularly unexpected for Belgium, Hungary and
the Slovak Republic, where more than 40% of 25-34 year-olds held a vocational qualification that required a mandatory
traineeship (see Box A1.1 in Indicator A1).

By gender
In all OECD and partner countries except Norway and Portugal, young women have lower employment rates than young
men, regardless of educational attainment (Table A3.2). Gender disparities in employment rates narrow as educational
attainment increases. On average across OECD countries, the gender difference in employment rates among 25-34 year-olds
without upper secondary education is 27 percentage points (72% for men and 45% for women). The difference shrinks to
16 percentage points among younger adults with upper secondary or post-secondary non-tertiary education as their highest
attainment (85% for men and 69% for women), and 8 percentage points among tertiary-educated younger adults (89% for
men and 81% for women). However, in the Czech Republic and the Slovak Republic, gender differences in employment rates
are not very sensitive to educational attainment, varying by no more than 5 percentage points across educational attainment
levels (Table A3.2).

Educational attainment and part-time or part-year employment
Greater educational attainment can also reduce worker’s likelihood of only working part-time or part-year for men and women.
On average across OECD countries, 25% of male workers without upper secondary education work part-time or part-year,
compared with 19% of those with upper secondary or post-secondary non-tertiary education as their highest attainment and
17% among those with tertiary education. However, it is tertiary-educated male workers who have the highest probability of
working part-time or part-year in Colombia (9%), Mexico (11%) and Portugal (5%) (Figure A3.4). In nearly all OECD and
partner countries, women are more likely to be in part-time or part-year employment than men. On average across OECD
countries, women are about twice as likely to work part-time or part-year than men, regardless of educational attainment
(OECD, 2020[4]).
On average across OECD countries, 20% of male workers with a general upper secondary or post-secondary non-tertiary
qualification as their highest attainment work part time, compared to 18% of those with a vocational qualification. The
difference exceeds 10 percentage points in Austria, Germany and Switzerland. Conversely, in the Czech Republic, Mexico
and the Slovak Republic, male workers with a vocational qualification are more likely to have a part-time or part-year job than
those with a general qualification (Figure A3.4). A similar situation is observed for female workers in most OECD and partner

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74  A3. HOW DOES EDUCATIONAL ATTAINMENT AFFECT PARTICIPATION IN THE LABOUR MARKET?
countries: female workers with a vocational qualification are more likely to have a part-time or part-year job than those with a
general qualification (OECD, 2020[4]).

Figure A3.4. Male workers in part-time or part-year employment as a percentage of all men in
employment, by educational attainment and programme orientation (2018)
25-64 year-old men
Tertiary
Upper secondary or post-secondary non-tertiary (general orientation or no distinction by orientation)
Upper secondary or post-secondary non-tertiary (vocational orientation)
Below upper secondary

%
60
50
40
30
20

Korea

Costa Rica

Latvia

Estonia

Portugal

New Zealand

Finland1

United Kingdom

Israel

Colombi a

Mexico

Hungary

Greece

Australia

Turkey

France1

United States

Italy1

Spain1

Belgium1

Germany

OECD average

Switzerland

EU23 average

Norway

Sweden

Poland

Brazil1

Ireland

Austria

Denmark

Canad a1

Lithuania1

Slovak Republic

Netherlands

Czech Republic

0

Chile1

10

1. Year of reference differs from 2018. Refer to the Table A4.1 for more details.
Countries are ranked in descending order of the share of tertiary-educated men who are in part-time or part-year employment.
Source: OECD (2020), Data collection on education and earnings. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2https://doi.org/10.1787/888934162299

Educational attainment and unemployment
In many OECD and partner countries, unemployment rates are especially high among younger adults with lower educational
attainment levels. On average across OECD countries, the unemployment rate for younger adults lacking upper secondary
education is 13%, almost twice as high as for those with upper secondary or post-secondary non-tertiary attainment (7%).
The unemployment rate for tertiary-educated younger adults is only 5% (Table A3.4).
The situation is especially severe for younger adults without upper secondary education in the Slovak Republic and
South Africa, where more than 35% of them are unemployed. The unemployment rate is also high in France, Greece, Italy
and Spain, where about one-quarter of these younger adults are unemployed (Table A3.4).
Having attained upper secondary education or post-secondary non-tertiary education reduces the risk of unemployment in
most OECD and partner countries. In Austria, the Czech Republic, Germany, Hungary, Poland, the Slovak Republic and
Sweden, the unemployment rate for younger adults with upper secondary or post-secondary non-tertiary education as their
highest attainment is less than one-third the rate of younger adults with below upper secondary education (Table A3.4).
In most OECD and partner countries, among younger adults with upper secondary or post-secondary non-tertiary attainment,
those with a vocational qualification have lower risk of unemployment than those with a general one. The difference in
employment rates is most pronounced in Austria, Germany, Iceland, Norway, Sweden and Switzerland, where the
unemployment rate among those with a vocational qualification is less than half the rate of those with a general qualification

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A3. HOW DOES EDUCATIONAL ATTAINMENT AFFECT PARTICIPATION IN THE LABOUR MARKET?  75
(Table A3.4). In all of these countries, except Iceland, more than 55% of younger adults with upper secondary or postsecondary non-tertiary attainment completed a vocational programme (see Indicator A1).

Figure A3.5. Unemployment rates of 25-34 year-olds with vocational upper secondary or post-secondary
non-tertiary educational attainment, by gender (2019)
Women
Men

Greece
Spain
Italy
France
Turkey
Latvia
Chile1
Finland
Lithuania
EU23 average
OECD average
Portugal
Canad a
Slovak Republic
Belgium
Russian Federation1
Israel
Denmark
Slovenia
Mexico
New Zealand
Switzerland
Australia
Austria
Germany
United Kingdom
Poland
Norway
Netherlands
Iceland
Hungary
Estonia
Sweden
Czech Republic

%
40
38
36
34
32
30
28
26
24
22
20
18
16
14
12
10
8
6
4
2
0

1. Year of reference differs from 2019. Refer to the Education at a Glance Database for more details.
Countries are ranked in descending order of the unemployment rate of men with vocational upper secondary or post-secondary non-tertiary educational attainment.
Source: OECD (2020), Education at a Glance Database, https://stats.oecd.org/. See Source section for more information and Annex 3 for notes
(https://doi.org/10.1787/69096873-en).
Statlink2https://doi.org/10.1787/888934162318

The unemployment rate of 25-34 year-old women who completed a vocational programme is higher than that of 25-34 yearold men. On average across OECD countries, 9% of young women with vocational upper secondary or post-secondary nontertiary education as their highest attainment are unemployed, compared to 6% of young men. In Australia, the Czech
Republic, Estonia, Israel, Poland, Slovenia, and Turkey, the unemployment rate for these young women is at least twice that
of their male peers. Only in Canada, Germany and Latvia, do young men with this level of educational attainment experience
higher unemployment than young women (Figure A3.5).
In many OECD and partner countries, younger adults with a tertiary degree are less likely to be unemployed compared to
those with upper secondary or post-secondary non-tertiary education as their highest attainment. The positive effect of a
tertiary education on unemployment rates is particularly high in Ireland, Lithuania, South Africa and the United States. In these
countries, the unemployment rate among tertiary-educated younger adults is less than half the rate of younger adults who
only have upper secondary or post-secondary non-tertiary attainment (Table A3.4).

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76  A3. HOW DOES EDUCATIONAL ATTAINMENT AFFECT PARTICIPATION IN THE LABOUR MARKET?
Educational attainment and inactivity
On average across OECD countries, 31% of 25-34 year-olds who have not completed upper secondary education are inactive
(i.e. not employed and not looking for a job). In Finland, Poland and the Slovak Republic, over 40% of younger adults without
upper secondary education are inactive, and at most 50% of this group are employed ( Table A3.3 and Table A3.4).
Inactivity rates fall substantially for younger adults with at least upper secondary education. On average across OECD
countries, 16% of younger adults with upper secondary or post-secondary non-tertiary education as their highest attainment
are inactive, and this falls to 10% for those with a tertiary degree (Table A3.4).
Across OECD countries, among younger adults with upper secondary or post-secondary non-tertiary education as their
highest attainment, 12% of those with a vocational qualification are inactive, compared to 21% of those with a general
qualification. In Austria, Germany, Iceland and Sweden, the inactivity rates among those with a vocational qualification are
about one-third of the rates of those with a general qualification. In most OECD countries, the difference in inactivity rates by
programme orientation are higher for 25-34 year-olds than for 25-64 year-olds, as younger adults who only completed general
upper secondary or post-secondary non-tertiary education may still enrolled in education and are not seeking for job.
Conversely, in Costa Rica and Estonia, younger adults who completed a vocational programme have higher inactivity rates
than those from a general pathway (Table A3.4 and (OECD, 2020[3])).
Women have consistently higher inactivity rates than men across all attainment levels, but the rates are especially high among
those who have not completed upper secondary education. On average across OECD countries, the gender difference in
inactivity rate is 29 percentage points for 25-34 year-olds with below upper secondary education, compared to 16 percentage
points among those with upper secondary or post-secondary non-tertiary attainment and 8 percentage points for those with
tertiary attainment. These differences in inactivity rates largely explain the differences in employment rates between men and
women (OECD, 2020[3])

Employment rates of recent upper secondary graduates
The transition from school to work is a major step in people’s lives. Young adults who leave the education system often face
different challenges in finding employment. The health crisis we are experiencing linked to the spread of COVID-19 will
undoubtedly have an impact on youth employment that will have to be monitored in the coming years. The use of data from
the EU-LFS, complemented by data from administrative sources and other surveys for non-EU-LFS countries allows a more
in-depth analysis of these school-to-work transitions (see also Indicator A2).
In all OECD countries with available data on recent upper secondary graduates, employment rates increase with time since
graduation. In 2018, on average across OECD countries, 66% of young adults who had recently completed upper secondary
education and were not studying any further were able to find employment within two years of graduation. Their employment
rates increase significantly during the first years following graduation, but then tend to stabilise. Thus, the employment rate
among young adults with an upper secondary education who graduated two to three years earlier is 76%, 10 percentage
points higher than among those who graduated less than two years earlier. Among young adults who graduated four to five
years earlier, 79% are employed, which is only 3 percentage points higher (Figure A1.2).
The differences in employment rates of recent upper secondary graduates across OECD countries are larger than the overall
differences in employment rates among the wider population. Among adults who completed upper secondary education less
than two years ago, the lowest employment rate is found in Greece (14%) and it is below 50% in Chile, Italy, Spain and
Turkey. At the other end of the spectrum, the employment rate of these recent graduates reaches or exceeds 85% in
the Czech Republic, Germany, Iceland, the Netherlands and New Zealand. The difference between the countries with the
lowest and highest rates is almost 80 percentage points, much larger than the differences observed across countries for all
adults with upper secondary attainment. The country with the lowest employment rate for upper secondary educated
25-64 year-olds is Greece (62%) and the country with the highest is Portugal (86%), a difference of 24 percentage points
(Figure A1.2 and Table A3.1).
The change in employment rates over time since graduation indicates the smoothness of the school-to-work transition. In
some countries, including Denmark, Iceland, Germany, the Netherlands and New Zealand, the difference in employment
rates among different graduation cohorts is negligible and the employment rates of recent graduates have already reached

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A3. HOW DOES EDUCATIONAL ATTAINMENT AFFECT PARTICIPATION IN THE LABOUR MARKET?  77
their highest level in the first two years following the graduation. With the exception of Denmark, these countries also belong
to the OECD countries with the highest employment rates (Figure A1.2).
In contrast, in other countries, school-to-work transitions are more difficult and labour-market outcomes remain challenging
after some years since graduation. For instance, in Greece, Italy and Turkey, less than 35% of recent upper secondary
graduates have found employment within two years of graduation, but in the long run more and more recent graduates are
able to find a job. Four to five years after completing their education their employment rates are at least 25 percentage points
higher than their more recently graduated peers. However, even then their employment rates do not exceed 60%, which is
well below the average for OECD countries (79%) (Figure A1.2).

Figure A3.6. Employment rates of recent upper secondary graduates, by years since graduation (2018)
Adults aged 15-34 at graduation, not in education
Less than two years
Two to three years
Four to five years

%
100
90
80
70
60
50
40
30
20

Greece

Italy

Turkey

Spain

Chile5

France

Belgium

Portugal

Ireland

United States1, 4

Poland

Hungary

Latvia

Lithuania

EU23 average

Estonia

OECD average

Slovenia

Luxembourg

Slovak Republic

Finland

Switzerland

Denmark

United Kingdom

Sweden

Austria

Norway

Australia1, 3

Czech Republic

Germany

Netherlands

New Zealand1, 2

0

Iceland

10

1. Data source differs from the EU-LFS.
2. Upper secondary general programmes only.
3. Year of reference differs from 2018. Refer to the source table for more details.
4. Year of reference 2017 and 2018 combined. Data reported under the category "Less than two years" refer to one year since completing education. The age group refers
to 15-34 year-olds.
5. Data reported under the category "Less than two years" refer to one year since completing education.
Countries are ranked in descending order of the employment rate of young adults less than two years after completion of upper secondary education.
Source: OECD (2020), Table A3.5. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2https://doi.org/10.1787/888934162337

In some other countries, recent upper secondary graduates face major difficulties in their first years in the labour market, but
have relatively good outcomes in the long run. For instance, in Portugal, only 54% of upper secondary graduates were
employed within two years of graduation, but 80% of those who completed their education four to five years earlier are in
employment, an increase of 25 percentage points. Similarly, in Belgium, Luxembourg and Poland, employment rates increase
by about 20 percentage points, meaning that despite the difficulties that recent graduates face at the start of their professional
career, their labour-market outcomes in the longer run are very good (Figure A1.2).

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78  A3. HOW DOES EDUCATIONAL ATTAINMENT AFFECT PARTICIPATION IN THE LABOUR MARKET?

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.
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 population.
EU-LFS countries are all countries for which data on recent graduates from the European Union Labour Force Survey are
used. These are the following 27 countries: Austria, Belgium, the Czech Republic, Denmark, Estonia, Finland, France,
Germany, Greece, Hungary, Iceland, Ireland, Italy, Latvia, Lithuania, Luxembourg, the Netherlands, Norway, Poland,
Portugal, the Slovak Republic, Slovenia, Spain, Sweden, Switzerland, Turkey and the United Kingdom.
Inactive individuals are those who, during the survey reference week, were neither employed nor unemployed. Individuals
enrolled in education are also considered as inactive if they 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.
Part-time or part-year workers: the population who have had earnings from work, but not worked full-time, full-year,
i.e. people who have either worked part-time or worked only a part of the reference period for the earnings data. The scope
of the concept of part-time or part-year workers is broader than the concept of part-time employment used in most labourforce surveys which usually refer to a reference period of four weeks prior to the survey. Therefore, the share of individuals
working part-time or part-year during the whole year is higher than the respective share of individuals working part-time during
a reference period of four weeks.
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).

Methodology
For information on methodology, see Indicator A1.
Data on the education and labour-force status of recent graduates by years since graduates are from the EU-LFS for all
countries participating in this survey. The data from the EU-LFS have been complemented by data from administrative source
and graduate or non-graduate surveys for non-EU-LFS countries. For information on the methodology, see Indicator A2.
Please see the OECD Handbook for Internationally Comparative Education Statistics (OECD, 2018[5]) for more information
and Annex 3 for country-specific notes (https://doi.org/10.1787/69096873-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, 2020[6]).

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A3. HOW DOES EDUCATIONAL ATTAINMENT AFFECT PARTICIPATION IN THE LABOUR MARKET?  79

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,
https://dx.doi.org/10.1787/5jlz9h56dvq7-en.

[1]

Hanushek, E., L. Woessmann and L. Zhang (2011), “General education, vocational education, and labor-market
outcomes over the life-cycle”, NBER Working Paper Series, No. 17504, National Bureau of Economic
Research, Cambridge, MA, http://dx.doi.org/10.3386/w17504.

[2]

OECD (2020), Education at a Glance Database - Education and earnings,
http://stats.oecd.org/Index.aspx?datasetcode=EAG_EARNINGS.

[4]

OECD (2020), Education at a Glance Database - Educational attainment and labour-force status,
http://stats.oecd.org/Index.aspx?datasetcode=EAG_NEAC.

[3]

OECD (2020), Regional Statistics Database - Educational attainment, by 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.

[5]

Indicator A3 Tables
Table A3.1

Employment rates of 25-64 year-olds, by educational attainment (2019)

Table A3.2

Trends in employment rates of 25-34 year-olds, by educational attainment and gender (2009 and 2019)

Table A3.3

Employment rates, by educational attainment and age group (2019)

Table A3.4

Unemployment and inactivity rates of 25-34 year-olds, by educational attainment (2019)

Table A3.5

Employment rates of young adults who have recently completed education, by educational attainment
and years since graduation (2018)

WEB Table A3.6

Employment rate of 25-34 year-olds who attained vocational upper secondary or post-secondary
non-tertiary education, by type of work experience while studying (2016)

Cut-off date for the data: 19 July 2020. Any updates on data can be found on line at http://dx.doi.org/10.1787/eag-dataen. More breakdowns can also be found at http://stats.oecd.org/, Education at a Glance Database.
StatLink: https://doi.org/10.1787/888934162128

EDUCATION AT A GLANCE 2020 © OECD 2020

80  A3. HOW DOES EDUCATIONAL ATTAINMENT AFFECT PARTICIPATION IN THE LABOUR MARKET?
Table A3.1. Employment rates of 25-64 year-olds, by educational attainment (2019)
Percentage of employed 25-64 year-olds among all 25-64 year-olds
Upper secondar y
or post-secondary non-ter tiar y

Bachelor’s
or equivalent

Master’s
or equivalent

Doctoral
or equivalent

(9)

(10)

Total
(11)

79
78
75
75
72
74
73
84
82
81
77
73
83
62
80
86
77
73
71
m
72
75
75
75
72
82
83
81
71
85
78
77
72
86
82
60
81
71

82
87
81
82
81
x(8)
73
86
87
84
84
84
90
65
83
82
80
83
81
82 d
77
89
a
83
75
89
88
84
73
c
91
86
79
85
x(8, 9, 10)
65
83
78

84
79
85
84
85
81 d
84
83
85
85
85
84
89
75
84
89
85
88
74
89 d
77
90
91
81
79
88
88
91
87
83
75
90
81
91
89 d
75
87
82

87
88
88
85 d
93 d
x(8)
89
88
91
89
89
89
89
82
87
96
89
91
83
x(8)
85 d
89
91
88
85
91
87
93
89
90
85
91
84
93
89 d
84
88
86

97
90
93
x(9)
x(9)
x(8)
c
94
94
91
97
92
93
88
95
98
93
92
94
x(8)
x(9)
98
100
91
91
96
92
91
98
95
85
95
90
93
92 d
92
90
90

85
86
86
83
84
81
82
87
88
87
86
86
89
76
86
92
86
88
81
86 d
78
89
91
86
80
90
88
89
89
89
84
90
82
90
89
74
87
83

79
78
74
78
72
74
71
83
80
81
79
74
82
64
78
87
77
78
66
84
74
79
81
77
69
81
83
81
75
79
76
78
71
85
84
57
81
75

78
78

77
77

82
83

84
84

88
88

93
93

86
87

77
77

74 d
72 d
m
m
x(6)
69
x(6)
x(6)

x(4)
x(4)
m
m
x(6)
77
x(6)
x(6)

74
72
m
m
74
73
65
57

79
x(8)
m
m
78
79
x(8)
80

82
82 d
m
m
87
88
74 d
85

94
84
m
m
94
87
x(8)
88 d

m
91
m
m
98
63
x(8)
x(8)

81
83
m
m
85
83
74
85

73
68
m
m
75
78
66
56

m

m

m

m

m

m

m

m

m

Vocation al

(8)

General

(7)

Below
upper
secondary

Postsecondary
non-tertiar y

Shor t-cycle tertiary

By progr amme
orientation

Upper
secondary

Par tners

OECD

By level
of education

Tertiar y

(1)

(2)

(3)

(4)

(5)

Total
(6)

Countries
Australia
Austria
Belgium
Canada
Chile 1
Colombia 2
Costa Rica
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungar y
Iceland
Ireland 2
Israel
Italy
Japan3
Korea
Latvia
Lithuania
Luxembourg
Mexico
Netherlands
New Zealand
Nor way
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
Unite d Kingdom4
United States

62
56
47
56
62
69
66
55
61
62
55
53
62
52
57
76
53
51
53
x(2)
64
65
55
62
66
63
72
62
45
70
38
51
59
67
69
50
65
56

79
78
74
71
72
74 d
73
84 d
82
81
76
73
82
62
79
85
73
73
71
81 d
72
75
73
75
72
82
81
81
71
85
78
77
72
86
82 d
60
81
71 d

81
82
87
81
a
x(2)
c
x(2)
87
80
95
68
87
65
85
92
77
a
75
x(7)
a
75
77
75
a
87
86
87
73
85
82
a
70
82
x(2)
a
a
x(2)

75
75
70
71
71
x(6)
73
86
73
81
73
75
67
60
78
80
x(6)
72
63
m
72 d
74
72
80
73
76
81
75
71
84
76
78
71
80
77
57
80
71 d

82
78
77
81
77
x(6)
72
82
84
81
77
73
84
67
80
89
x(6)
80
74
m
x(4)
77
77
73
63
84
84
83
71
87
79
77
73
89
83
64
82
x(4)

OECD average
EU23 average

59
57

76
77

81
80

74
75

Argentina 5
Brazil 5
China
India
Indonesia 1, 2
Russian Federation 5
Saudi Arabia 2 , 6
South Africa 2 , 5

64
59
m
m
73
54
62
44

74 d
72
m
m
74 d
69
61
55

x(2)
a
m
m
x(2)
77
82
75

G20 average

m

m

m

All
levels
of
education
(12)

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. There is no distinction by programme orientation at upper secondary or post-secondary non-tertiary level of education.
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 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 (12% of adults aged 25-64 are in this group).
5. Year of reference 2018.
6. Year of reference 2016.
Source: OECD/ILO (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2https://doi.org/10.1787/888934162147

EDUCATION AT A GLANCE 2020 © OECD 2020

A3. HOW DOES EDUCATIONAL ATTAINMENT AFFECT PARTICIPATION IN THE LABOUR MARKET?  81

Table A3.2. Trends in employment rates of 25-34 year-olds, by educational attainment and gender (2009 and 2019)
Percentage of employed 25-34 year-olds among all 25-34 year-olds
Upper secondar y
or post-secondar y non-ter tiar y

Below upper secondary

Par tners

OECD

Men

Women

Total

Men

Women

Tertiar y

Total

Men

Women

Total

2009
(1)

2019
(2)

2009
(3)

2019
(4)

2009
(5)

2019
(6)

2009
(7)

2019
(8)

2009
(9)

2019
(10)

2009
(11)

2019
(12)

2009
(13)

2019
(14)

2009
(15)

2019
(16)

2009
(17)

2019
(18)

Countries
Australia
Austria
Belgium
Canada
Chile 1
Colombia
Costa Rica
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungar y
Iceland
Ireland
Israel
Italy
Japan 2
Korea
Latvia
Lithuania
Luxembourg
Mexico
Netherlands
New Zealand
Nor way
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
Unite d Kingdom 3
United States

74 b
72
65 b
69
79 b
m
89
56 b
76
55
74
74
65 b
87 b
58
73
54 b
59 b
76 b
m
70 b
56
51 b
bc
90
85 b
78
72
65 b
83
bc
bc
66
69 b
81 b
79 b
71 b
66

74
70
62
67
77
88
86
70
64
80
59
63
70
68
75
82
61
69
66
m
73
74
67
78
91
73
77
69
61
84
47
74
71
75
81
79
77
72

46 b
51
39 b
44
38 b
m
42
33 b
58
47
c
45
43 b
44 b
32
60
38 b
22 b
40 b
m
43 b
50
59 b
bc
40
58 b
50
62
37 b
69
bc
bc
52
51 b
61 b
21 b
42 b
39

45
46
39
41
48
47
42
43
45
44
33
37
45
35
41
80
33
41
34
m
52
49
30
75
44
53
61
55
23
71
19
44
52
51
56
26
53
39

62 b
60
53 b
59
58 b
m
67
44 b
69
53
65
61
54 b
70 b
46
68
48 b
45 b
61 b
m
59 b
54
54 b
bc
64
73 b
64
68
53 b
77
27 b
bc
60
61 b
70 b
48 b
56 b
55

61
58
52
57
64
70
67
57
56
69
49
51
59
54
58
82
49
58
53
m
62
65
55
77
67
64
69
63
47
79
33
62
63
65
69
52
67
57

91 b
87
86 b
81
80 b
m
92
91 b
85
80
81
87
82 b
85 b
82
82
74 b
72 b
80 b
x(13)
71 b
74
71 b
bc
88
92 b
88
90
86 b
82
86 b
86 b
75
85 b
89 b
82 b
86 b
74

88
90
87
83
80
87
90
95
84
92
82
83
88
71
91
88
85
74
74
x(14)
71
85
84
87
90
88
90
88
92
86
92
91
75
86
88
82
92
81

69 b
79
75 b
71
54 b
m
65
60 b
79
65
70
70
73 b
63 b
59
70
66 b
59 b
62 b
x(15)
48 b
65
71 b
bc
57
85 b
70
85
62 b
78
62 b
78 b
68
76 b
78 b
31 b
70 b
65

70
82
72
71
59
61
60
64
72
63
71
68
80
52
70
81
64
65
53
x(16)
56
70
71
85
55
82
72
77
60
85
65
77
66
79
84
34
76
67

81 b
84
81 b
76
67 b
m
78
77 b
82
74
76
79
77 b
74 b
72
76
71 b
66 b
71 b
x(17)
61 b
70
71 b
bc
72
89 b
80
88
75 b
80
75 b
83 b
72
81 b
83 b
62 b
79 b
70

81
86
81
79
69
74
74
82
79
81
77
75
84
63
82
85
74
71
64
x(18)
66
79
79
86
72
85
82
84
79
86
81
86
71
83
86
61
85
74

90 b
90
91 b
86
87 b
m
90
88 b
88
94
92
89
92 b
84 b
91
88
85 b
87 b
72 b
91 bd
84 b
90
88 b
bc
88
95 b
89
91
92 b
86
90 b
91 b
83
87 b
93 b
85 b
90 b
87

92
88
90
89
88
88
88
93
87
96
90
89
92
80
94
90
91
89
69
94 d
81
92
95
92
88
93
93
89
95
85
93
92
81
89
93
83
93
89

80 b
83
89 b
83
79 b
m
83
68 b
88
70
80
84
84 b
78 b
72
83
83 b
80 b
67 b
71 bd
64 b
79
86 b
bc
76
92 b
76
89
83 b
87
72 b
88 b
79
84 b
86 b
68 b
84 b
80

82
84
86
84
83
76
77
67
82
75
82
85
85
68
77
90
84
86
67
82 d
72
87
90
86
75
91
85
90
85
87
70
87
76
86
87
62
88
82

84 b
86
90 b
84
83 b
m
87
77 b
88
79
85
86
88 b
81 b
80
85
84 b
83 b
69 b
80 bd
74 b
83
87 b
87 b
82
94 b
82
90
87 b
87
80 b
89 b
81
86 b
90 b
77 b
87 b
83

86
86
88
86
85
81
82
78
84
83
85
87
88
73
84
90
88
87
68
88 d
76
89
92
89
81
92
89
89
89
86
79
89
79
87
90
72
90
85

OECD average
EU23 average

71
68

72
69

46
47

45
43

58
57

61
58

83
83

85
86

67
70

69
71

76
77

78
80

88
89

89
90

80
81

81
82

84
84

85
85

Argentina 4
Brazil 4
China
India
Indonesia 1
Russian Federation4
Saudi Arabia
South Africa 4

m
88 b
m
m
91 b
m
m
52

82
76
m
m
91
68
m
49

m
55 b
m
m
48 b
m
m
30

40
45
m
m
47
48
m
30

m
72 b
m
m
68 b
m
m
42

64
62
m
m
68
60
m
41

m
90 b
m
m
87 b
m
m
66

91
84
m
m
90
90
m
56

m
69 b
m
m
46 b
m
m
48

58
63
m
m
49
71
m
43

m
79 b
m
m
68 b
m
m
57

75
73
m
m
71
83
m
49

m
92 b
m
m
84 b
m
m
88

83
89
m
m
91
95
m
83

m
86 b
m
m
63 b
m
m
84

74
82
m
m
79
83
m
80

m
88 b
m
m
72 b
m
m
86

78
85
m
m
84
88
m
81

G20 average

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

Note: In most countries, there is a break in the time series, represented by the code "b", as data for 2019 refer to ISCED 2011 while data for 2009 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 the 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 (12% of adults aged 25-64 are in this group).
4. Year of reference 2018.
Source: OECD/ILO (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2https://doi.org/10.1787/888934162166

EDUCATION AT A GLANCE 2020 © OECD 2020

82  A3. HOW DOES EDUCATIONAL ATTAINMENT AFFECT PARTICIPATION IN THE LABOUR MARKET?
Table A3.3. Employment rates, by educational attainment and age group (2019)
Percentage of employed adults among all adults in a given age group
Upper secondary or post-secondary non-tertiar y

Below
upper secondar y

General

Vocation al

Tertiar y

Total

Short-cycle ter tiary

Total

Par tners

OECD

25 -34 35- 44 45 -54 25 -34 35 -44 45 -54 25 -34 35 -44 45 -54 25-34 35 - 44 45 -54 25-34 35 - 44 45-54 25 -34 35 - 44 45-54
year- year- year- year- year- year- year- year- year- year- year- year- year- year- year- year- year- yearolds olds olds olds olds olds olds olds olds olds olds olds olds olds olds olds olds olds
(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

(13)

(14)

(15)

(16)

(17)

(18)

Countries
Australia
Austria
Belgium
Canada
Chile1
Colombia 2
Costa Rica
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungar y
Iceland
Ireland 2
Israel
Italy
Japan 3
Korea
Latvia
Lithuania
Luxembourg
Mexico
Netherlands
New Zealand
Nor way
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
Unite d Kingdom4
United States

61
58
52
57
64
70
67
57
56
69
49
51
59
54
58
82
49
58
53
m
62
65
55
77
67
64
69
63
47
79
33
62
63
65
69
52
67
57

64
67
55
61
67
75
72
69
63
68
60
60
66
63
68
80
54
57
60
m
64
76
61
84
70
68
76
64
56
83
47
66
69
72
78
57
69
63

70
69
61
63
66
73
68
66
68
60
66
65
69
62
69
77
59
52
61
m
67
64
56
72
68
70
77
64
58
77
46
70
64
67
76
53
71
60

78
71
74
74
67
x(10)
75
81
66
82
69
72
61
62
76
77
x(10)
70
51
m
66 d
78
77
79
71
75
79
74
76
83
77
78
66
72
75
57
85
74 d

78
86
77
77
76
x(11)
80
91
76
91
78
83
73
70
86
79
x(11)
76
68
m
74 d
78
79
c
77
80
83
77
79
90
88
89
78
87
84
67
85
76 d

80
84
78
79
74
x(12)
75
95
79
85
81
85
79
67
89
88
x(12)
76
72
m
77 d
80
77
m
77
83
87
76
80
87
87
87
78
89
81
55
86
75 d

83
89
83
88
77
x(10)
70
83
85
81
80
77
88
64
84
93
x(10)
81
69
m
x(4)
80
81
93
76
88
83
90
80
88
81
88
75
91
90
66
84
x(4)

87
88
84
87
77
x(11)
81
90
90
88
84
81
89
73
89
92
x(11)
84
79
m
x(5)
86
85
83
73
87
86
88
83
91
86
90
79
93
87
72
85
x(5)

86
88
82
85
77
x(12)
70
92
87
84
84
82
89
71
89
91
x(12)
84
81
m
x(6)
81
83
80
67
86
87
86
80
86
88
89
76
93
87
64
86
x(6)

81
86
81
79
69
74
74
82
79
81
77
75
84
63
82
85
74
71
64
m
66
79
79
86
72
85
82
84
79
86
81
86
71
83
86
61
85
74

83
88
82
81
76
78
80
91
88
89
83
82
88
72
89
88
80
77
76
m
74
82
82
84
77
86
85
84
82
90
86
90
78
91
86
69
85
76

84
87
81
81
75
75
75
94
86
85
84
83
88
68
89
90
80
78
79
m
77
81
81
80
75
86
87
83
80
87
88
89
77
92
86
59
86
75

84
89
85
86
84
x(16)
71
c
85
c
c
88
92
c
82
c
80
84
93
84 d
77
82
a
92 r
82
92
89
79
c
c
m
89
78
80
x(16)
65
87
81

85
91
91
88
85
x(17)
85
69 r
92
85
92
90
94
98
86
92
85
87
c
84 d
76
95
a
88
77
91
89
88
c
c
m
95
85
90
x(17)
74
90
84

86
94
86
87
81
x(18)
82
c
91
92
93
90
95
72
94
88
83
87
c
85 d
81
98
a
92
74
93
91
88
80 r
c
c
97
81
89
x(18)
73
89
82

86
86
88
86
85
81
82
78
84
83
85
87
88
73
84
90
88
87
68
88 d
76
89
92
89
81
92
89
89
89
86
79
89
79
87
90
72
90
85

87
91
92
88
88
85
89
90
93
88
90
90
92
85
89
93
89
91
86
87 d
78
93
94
89
85
92
89
92
92
92
88
95
87
93
91
83
91
86

88
93
91
88
87
84
85
97
93
94
92
91
94
84
95
93
88
91
90
89 d
82
91
94
88
83
92
91
91
94
93
94
97
86
93
91
77
90
86

OECD average
EU23 average

61
58

66
65

66
65

73
73

80
82

80
82

82
82

85
86

83
84

78
80

83
84

82
84

84
86

87
89

87
89

85
85

89
91

90
92

Argentina 5
Brazil 5
China
India
Indonesia1, 2
Russian Federation 5
Saudi Arabia
South Africa 2, 5

64
62
m
m
68
60
m
41

72
67
m
m
76
66
m
52

70
63
m
m
77
63
m
51

75 d
73 d
m
m
x(10)
78
m
x(10)

78 d
77 d
m
m
x(11)
83
m
x(11)

77 d
74 d
m
m
x(12)
80
m
x(12)

x(4)
x(4)
m
m
x(10)
88
m
x(10)

x(5)
x(5)
m
m
x(11)
90
m
x(11)

x(6)
x(6)
m
m
x(12)
87
m
x(12)

75
73
m
m
71
83
m
49

78
77
m
m
78
87
m
64

77
74
m
m
79
84
m
67

78
x(16)
m
m
80
89
m
75

85
x(17)
m
m
80
93
m
84

83
x(18)
m
m
82
89
m
91

78
85
m
m
84
88
m
81

88
88
m
m
88
93
m
88

86
85
m
m
91
92
m
91

G20 average

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

Note: In most countries, data refer to ISCED 2011. For Indonesia and Saudi Arabia, data refer to ISCED-97. See Definitions and Methodology sections for more information.
Data and more breakdowns are available at http://stats.oecd.org/, Education at a Glance Database.
1. Year of reference 2017.
2. There is no distinction by programme orientation at upper secondary or post-secondary non-tertiary level of education.
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 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 (12% of adults aged 25-64 are in this group).
5. Year of reference 2018.
Source: OECD/ILO (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
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A3. HOW DOES EDUCATIONAL ATTAINMENT AFFECT PARTICIPATION IN THE LABOUR MARKET?  83

Table A3.4. Unemployment and inactivity rates of 25-34 year-olds, by educational attainment (2019)
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
Unemployment rate

Inactivity rate

Upper secondar y
or post-secondar y non-ter tiary

OECD

Ter tiary

Tertiar y

Total

Shortcycle
tertiar y

Total

Shortcycle
ter tiary

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

Countries
Australia
Austria
Belgium
Canada
Chile 1
Colombia 2
Costa Rica
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungar y
Iceland
Ireland 2
Israel
Italy
Japan 3
Korea
Latvia
Lithuania
Luxembourg
Mexico
Netherlands
New Zealand
Nor way
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
Unite d Kingdom4
United States

10
15
17
12
11
10
14
13
10
7
17
24
12
30
11
6
11
4
21
m
6
14
19
c
3
7
7
8
13
9
37
13
23
17
10
16
7
10

6
8
7
8
10
x(4)
12
2
7
5
9
11
6
21
3
7
x(4)
5
16
m
7d
7
9
c
4
5
4
5
4
6
c
8
17
8
9
17
3
6d

4
4
6
5
7
x(4)
14
3
5
5
7
12
3
30
3
3
x(4)
6
13
m
x(2)
8
8
c
5
3
4
2
4
6
6
5
16
3
4
13
3
x(2)

5
4
6
7
10
12
12
2
6
5
7
11
3
26
3
4
8
5
14
x(5, 6)
7
7
8
c
4
3
4
3
4
6
6
6
17
5
5
15
3
6

4
3
c
5
7
x(6)
14
x(6)
6
x(6)
x(6)
5
c
x(6)
5
x(6)
6
5
c
3d
5
10
a
c
3
c
2
6
x(6)
c
x(6)
6
14
8
x(6)
17
4
3

3
4
4
5
8
12
9
1
7
3
5
6
3
19
2
4
4
4
12
3d
6
4
3
4
6
2
2
3
3
7
3
5
12
4
4
15
2
2

32
31
38
36
29
22
22
34
37
26
41
33
33
23
34
13
45
40
33
m
34
24
33
c
31
31
26
31
46
14
47
29
17
22
23
38
28
37

17
23
20
19
25
x(10)
15
18
29
14
25
19
35
22
21
17
x(10)
27
40
m
29 d
16
16
c
26
21
18
22
20
11
18
15
20
22
17
32
12
21 d

13
7
11
7
17
x(10)
18
14
11
15
14
13
9
9
13
4
x(10)
14
20
m
x(8)
13
12
c
20
10
13
8
17
6
14
8
10
7
7
24
13
x(8)

15
10
14
16
23
16
16
16
16
14
17
15
13
16
16
11
19
26
25
x(11, 12)
29
14
14
8
25
12
15
13
18
9
14
9
15
13
9
28
13
21

13
8
10
10
10
x(12)
17
x(12)
10
x(12)
x(12)
8
c
x(12)
14
c
15
12
c
13 d
19
9
a
c
15
c
9
16
x(12)
c
m
6
10
13
x(12)
21
9
16

11
11
9
10
8
8
10
21
9
14
11
8
9
10
14
6
9
9
23
10 d
19
7
4
7
14
6
9
8
9
7
18
6
11
9
6
15
7
13

OECD average
EU23 average

13
16

8
8

7
7

7
7

6
m

5
5

31
32

21
21

12
12

16
14

12
m

10
10

Argentina 5
Brazil 5
China
India
Indonesia1, 2
Russian Federation 5
Saudi Arabia
South Africa 2, 5

12
14
m
m
3
14
m
37

9d
13 d
m
m
x(4)
8
m
x(4)

x(2)
x(2)
m
m
x(4)
5
m
x(4)

9
13
m
m
5
7
m
35

9
x(6)
m
m
5
4
m
12

7
8
m
m
5
4
m
10

27
27
m
m
30
30
m
35

18 d
16 d
m
m
x(10)
16
m
x(10)

x(8)
x(8)
m
m
x(10)
7
m
x(10)

18
16
m
m
25
12
m
24

14
x(12)
m
m
16
8
m
15

17
8
m
m
11
8
m
10

G20 average

m

m

m

m

m

m

m

m

m

m

m

m

Below
upper
secondar y

Par tners

Upper secondary
or post-secondar y non-tertiar y

General Vocation al

Total

Below
upper
secondary General Vocation al

Total

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. There is no distinction by programme orientation at upper secondary or post-secondary non-tertiary level of education.
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 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 (12% of adults aged 25-64 are in this group).
5. Year of reference 2018.
Source: OECD/ILO (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
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EDUCATION AT A GLANCE 2020 © OECD 2020

84  A3. HOW DOES EDUCATIONAL ATTAINMENT AFFECT PARTICIPATION IN THE LABOUR MARKET?
Table A3.5. Employment rates of young adults who have recently completed education, by educational attainment and years
since graduation (2018)
Adults aged 15-34 at graduation, not in education
Upper secondar y

Short-cycle ter tiary

Bachelor’s or equivalent

Master’s or equivalent

Par tners

OECD

Less than
Two to
Four to Less than
Two to
Four to Less than
Two to
Four to Less than
Two to
Four to
two years three years five years two years three years five years two years three years five years two years three years five years
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
(9)
(10)
(11)
(12)
Countries
Australia 1, 2
Austria
Belgium
Cana da 1, 3
Chile1
Colombia
Costa Rica 1, 4
Czech Republic
Denmark
Estonia
Finland
France 5
Germany
Greece
Hungar y
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Lithuania
Luxembourg
Mexico
Netherlands
New Zealand 1, 6
Nor way
Poland
Por tugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
Unite d Kingdom
United States 1, 7

84
81
58
m
45
m
m
85
80
67
73
54
86
14
62
93
59
m
34
m
m
63
63
68
m
87
93
83
61
54
73
68
48
81
78
29
79
59

78
86
63
m
61
m
m
87
80
75
80
66
88
42
78
93
70
m
53
m
m
80
75
79
m
86
92
87
80
74
85
82
64
85
89
47
79
m

85
83
79
m
m
m
m
88
81
82
83
69
87
55
81
95
78
m
60
m
m
68
69
87
m
88
91
88
81
80
85
79
62
88
89
57
82
m

88
81
c
87
74
m
m
m
73
m
m
69
c
m
94 r
c
88
m
c
m
m
c
m
c
m
94
95
89
c
c
m
75 r
64
86
m
48
92
83

91
91
c
88
79
m
m
m
80
m
c
83
90
m
94
c
85
m
59 r
m
m
94
m
c
m
96
94
93
m
c
m
87 r
76
95
m
60
89
m

87
93
c
88
m
m
m
m
96
m
c
89
100
m
83
c
91
m
87 r
m
m
88
m
c
m
93
92
93
c
m
c
90 r
78
91
m
62
91
m

92
88
82
81
74
m
m
89
81
90
93
75
94
43
83
91
86
m
51
m
m
89
80
80
m
91
96
90
80
64
82 r
78 r
62
92
90
47
78
82

91
88
89
80
78
m
m
87
89
87
88
85
94
63
92
96
91
m
66
m
m
97
91
97
m
96
97
99
90
89
85
87
72
96
94
66
89
m

91
86
92
81
m
m
89
79
87
82
90
87
93
67
86
95
88
m
80
m
m
78
95
89
m
92
96
92
88
86
73
88
75
96
94
75
93
m

89
84
87
81
89
m
m
92
71
93
96
80
91
58
86
96
87
m
51
m
m
c
85 r
92
m
88
98
91 r
85
69
78
73 r
74
97
89
78
79
79

89
95
89
82
90
m
m
94
91
93
85
89
94
76
91
95
94
m
68
m
m
74
97
93
m
96
97
95
91
91
81
88
79
96
96
84
92
m

84
90
91
81
m
m
m
85
91
88
86
91
91
81
93
96
91
m
78
m
m
95
95
91
m
97
95
96
90
95
77
87
83
93
92
83
97
m

OECD average
EU23 average

66
65

76
76

79
78

m
m

m
m

m
m

80
80

87
87

87
86

83
82

89
89

89
89

Argentina
Brazil
China
India
Indonesia
Russian Federation
Saudi Arabia
South Africa

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

G20 average

m

m

m

m

m

m

m

m

m

m

m

m

Note: The time periods of “less than two years”, “two to three years” and “four to five years” refer to 0-23 months, 24-47 months and 48-71 months since completion
respectively. 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. Data source differs from the EU-LFS.
2. Year of reference 2019.
3. Year of reference 2017.
4. Year of reference 2016. Data reported for the category "Four to five years" refer to five years since completion.
3. Data from national LFS.
6. Upper secondary general programmes only.
7. Year of reference 2017 and 2018 combined. The age group refers to 15-29 year-olds. Data reported under the category "Less than two years" refer to "One year" since
graduation.
Source: OECD (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2https://doi.org/10.1787/888934162223

EDUCATION AT A GLANCE 2020 © OECD 2020

86  A4. WHAT ARE THE EARNINGS ADVANTAGES FROM EDUCATION?

Indicator A4. What are the earnings
advantages from education?
Highlights


Greater educational attainment brings increasing rewards. On average across OECD countries, full-time workers
with upper secondary or post-secondary non-tertiary education earn 23% more than those without, while those
with a tertiary degree earn 54% more than those with an upper secondary education. However, these averages
mask significant variation depending on the fields studied.



Among adults with upper secondary or post-secondary non-tertiary attainment, those with a general qualification and
those with a vocational qualification have similar relative earnings. The difference in relative earnings between adults
with a general and vocational qualification is 5 or less percentage points in about one third of the countries with data.
However, in a small group of countries, Austria, Finland, France, Germany and the United Kingdom, the difference in
the earnings advantage is between 15 and 20 percentage points in favour of a general qualification.



Three years after graduation, young graduates with a bachelor’s or equivalent degree earn 62% more than those
with an upper secondary qualification who completed their education at the same time. The earnings advantage
varies from less than 25% in Norway and Sweden to about 100% or more in Chile, Lithuania and Turkey.

Figure A4.1. Relative earnings of adults with an upper secondary or post-secondary non-tertiary
education compared to earnings of adults with below upper secondary education, by programme
orientation (2018)
25-64 year-old workers (full-time full-year workers); below upper secondary education = 100
Upper secondary or post-secondary non-tertiary
Upper secondary or post-secondary non-tertiary – general
Upper secondary or post-secondary non-tertiary – vocational

186

Index
170
160
150
140
130
120
110

Ireland

Finland1

Estonia

France1

Latvia2

Australia

Denmark

New Zealand

Belgium1

Lithuania1

Norway

United Kingdom

Poland

Netherlands

Spain1

Sweden

EU23 average

Slovenia

Luxembourg2

Greece

OECD average

Mexico2

Canad a1

Switzerland

Italy1

Korea

Portugal

Turkey2

Hungary

Slovak Republic

Germany

Israel

Austria

Costa Rica

Chile1

Colombia

Brazil1

United States

90

Czech Republic

100

1. Year of reference differs from 2018. Refer to Table A4.1 for details.
2. Earnings net of income tax.
Countries are ranked in descending order of the relative earnings of 25-64 year-olds with an upper secondary or post-secondary non-tertiary education as the highest
educational attainment level.
Source: OECD (2020). Education at a Glance Database, http://stats.oecd.org/. See Source section for more information and Annex 3 for notes
(https://doi.org/10.1787/69096873-en).
Statlink2https://doi.org/10.1787/888934162451

EDUCATION AT A GLANCE 2020 © OECD 2020

A4. WHAT ARE THE EARNINGS ADVANTAGES FROM EDUCATION?  87

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.
The earnings advantage with higher educational attainment levels can vary according to age, gender, level of tertiary
education, programme orientation and field of study. Individuals with higher qualifications and more experience are more
likely to earn higher wages. However, in all countries, gender gaps in earnings persist regardless of age, level of education,
programme orientation or field of study.
A number of factors beyond education 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


The earnings advantage of educational attainment generally widens as peoples’ careers progress. On average
across OECD countries, 25-34 year-olds with tertiary education can expect to be earning nearly 50% more when
they reach 45-54 years old. Those with an upper secondary or post-secondary non-tertiary education will earn
about 20% more on average and those with below upper secondary education earn about 10% more. On average,
salaries rise faster for those with a general upper secondary or post-secondary non-tertiary qualification than for
those who with a vocational one. However, the differences between the two streams remain small in most
countries.



Across all levels of attainment, the gender gap in earnings persists. Women in OECD countries with below upper
secondary education who work full time earn 77% of the earnings of their male peers. The gender gap is similar
for women with an upper secondary or post-secondary non-tertiary education and for women with tertiary
education.



Three years after graduation, young adults with a master’s or equivalent degree earn more than their peers with
a bachelor’s or equivalent degree as well as those who only attained upper secondary education. In half of
countries with available data, the earnings of recent master’s graduates are more than double the earnings of
recent graduates from upper secondary programmes, and the earnings advantage varies from about 50% in
Latvia, Norway and Sweden to almost 200% in Chile.

Note
This indicator presents three types of relative earnings. The first uses the earnings of adults with below upper secondary
education as a baseline. The results reflect the difference in earnings between adults without upper secondary education
and those with upper secondary or post-secondary non-tertiary education. The second 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 or post-secondary non-tertiary education and those with different levels of
attainment. The third,on gender disparities in earnings, uses men’s earnings as a baseline. In all 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 2020 © OECD 2020

88  A4. WHAT ARE THE EARNINGS ADVANTAGES FROM EDUCATION?

Analysis
Relative earnings of workers without tertiary education, by programme orientation
Upper secondary education is commonly considered the minimum educational attainment level for successful labour-market
participation. Adults who did not attain upper secondary education not only have the lowest employment rate (see
Indicator A3), but also the lowest earnings. The level of earnings increases with increased educational attainment.
On average across OECD countries, 25-64 year-olds in full-time employment with upper secondary or post-secondary nontertiary education earn 23% more than those who have not attained upper secondary education. The relative earnings for
these workers are highest in Brazil, Chile, Colombia, the Czech Republic and the United States, where adults with an upper
secondary or post-secondary non-tertiary education earn at least 40% more than those with below upper secondary education
(Figure A4.1).
In contrast, in a few countries, the earnings advantage of an upper secondary or post-secondary qualification is minor or
negligible compared to someone with below upper secondary education. This is the case in Australia, Estonia, France and
Ireland, where the earnings advantage does not exceed 10%. Interestingly, adults who have attained upper secondary or
post-secondary education in these countries have still much better labour-market outcomes than those with below upper
secondary education, indicated by a difference in employment rates of about 20 percentage points (see Indicator A3).
On average across OECD countries, adults with general and vocational qualifications at the upper secondary education or
post-secondary non-tertiary attainment level have similar earnings levels. Their earnings are about 25% higher than that of
their peers with below upper secondary education (Figure A4.1).
In about one third of OECD and partner countries, the difference in relative earnings of adults with a general and vocational
upper secondary or post-secondary non-tertiary qualification is 5 or less percentage points. However, in some countries such
as Austria, Finland, France, Germany or the United Kingdom, the difference in the earnings advantage is between 15 and
20 percentage points in favour of a general qualification. In some countries, a vocational qualification has a comparative
earnings advantage over a general one. In Canada, Costa Rica and the Czech Republic the difference is about 20 percentage
points or more in favour of a vocational qualification (Figure A4.1).

Relative earnings of tertiary-educated workers, by levels of tertiary education
In all OECD countries, earning differentials are generally wider between tertiary and upper secondary education than between
upper secondary or post-secondary non-tertiary education and below upper secondary education. On average across OECD
countries, 25-64 year-olds with a tertiary degree earn on average 54% more for full-time employment than those with upper
secondary attainment (Figure A4.2).
Indeed, having a tertiary degree carries a considerable earnings advantage in most OECD and partner countries. Relative
earnings for full-time workers are highest in Brazil, 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 (see Indicator A1; Figure A4.2).
The earnings advantage for tertiary-educated workers varies considerably by level of tertiary attainment, however. In most
OECD member and partner countries, workers with a master’s or doctoral degree or equivalent earn more than those with a
bachelor’s degree or equivalent, who in turn earn more than those with a short-cycle tertiary degree. On average across
OECD countries, adults with a short-cycle tertiary degree earn about 20% more than those with an upper secondary
education. The earnings advantage increases to 43% for those with a bachelor’s degree and to nearly 90% for those with a
master’s or doctoral degree.
There are some important exceptions to this general pattern. In Estonia and Portugal, adults with a short-cycle tertiary degree
earn less than those with an upper secondary education. In both cases, however, these groups represent relatively small
shares of the tertiary-educated population.
Moreover, the earnings of workers with a short-cycle tertiary degree are higher than those of workers with a bachelor’s degree
in Austria, Greece and Norway. With the exception of Greece, which is one of the countries with the highest short-cycle tertiary
attainment rates, with at least 10% of adults having attained this level (see Indicator A1).

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A4. WHAT ARE THE EARNINGS ADVANTAGES FROM EDUCATION?  89
According to the analysis of data on recent graduates, available for 12 countries, relative earnings advantages are also
substantial for young graduates who recently earned a bachelor’s, master’s or equivalent degree compared to those who
recently completed their upper secondary qualification (Box A4.1).

Figure A4.2. Relative earnings of tertiary-educated adults compared to earnings of adults with an upper
secondary education (2018)
25-64 year-old workers (full-time full-year workers); upper secondary education = 100
Master’s, Doctoral or equivalent
Bachelor’s or equivalent
Short-cycle tertiary
All tertiary

457

445

279

345
308

Index
240
220
200
180
160
140
120

Norway

Sweden

Australia

Denmark

Estonia

New Zealand

Korea

Finland1

Italy1

Greece

United Kingdom

Belgium1

Canada1

Switzerland2

Latvia4

Luxembourg4

France1

Austria

Netherlands

Spain1

Israel

EU23 average

Poland

OECD average

Ireland

Slovak Republic2

Czech Republic2

Mexico4

Germany

Turkey4

Slovenia

Portugal

Hungary

United States

Lithuania1

Colombia

Costa Rica

Brazil1, 2, 3

80

Chile1

100

1. Year of reference differs from 2018. Refer to the source table for details.
2. Index 100 refers to the combined ISCED levels 3 and 4 of the educational attainment levels in the ISCED 2011 classification.
3. Bachelor's or equivalent includes short-cycle tertiary.
4. Earnings net of income tax.
Countries are ranked in descending order of the relative earnings of workers with any tertiary level of education.
Source: OECD (2020). Education at a Glance Database, http://stats.oecd.org/. See Source section for more information and Annex 3 for notes
(https://doi.org/10.1787/69096873-en).
Statlink2https://doi.org/10.1787/888934162470

Earnings increases over time, by educational attainment
Higher educational attainment is associated with faster increases in earnings throughout a person’s working life, meaning the
wage differentials across educational attainment levels tend to widen with age. On average across OECD countries, 4554 year-olds without upper secondary education earn 10% more than their 25-34 year-old peers. Among adults with an upper
secondary or post-secondary non-tertiary education, 45-54 year-olds earn 20% more and tertiary-educated older adults earn
about 50% more than their younger peers (Figure A4.3).
Higher earnings among older age groups could mean either that earnings increase with experience or that earnings have
fallen for younger generations (or a combination of both effects). In most OECD countries, increases over the course of a
career is mainly determined by seniority-based pay schemes (where wages rise with seniority) and wage progression from
growing work experience and responsibilities (OECD, 2019[1]). Despite the rapid rise in the share of adults who have attained
tertiary education, the difference in earnings between older and younger tertiary-educated workers has changed only slightly
over the last decade. In most countries, the relative earnings advantage by age has slightly increased but the change is less
than 10 percentage points (OECD, 2020[2]). Therefore, the differences in earnings between older and younger adults are

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90  A4. WHAT ARE THE EARNINGS ADVANTAGES FROM EDUCATION?
mostly the result of a positive relationship between the level of earnings and work experience. The differences can be
interpreted as a proxy for the expected earnings development over the career.
The size of age-related earnings increases varies considerably across OECD and partner countries. In more than half of
countries, the difference in the average earnings of 45-54 year-old and 25-34 year-old workers with below upper secondary
education is less than 10%. This narrow gap may be due to greater work experience among 25-34 year-olds without upper
secondary education, in contrast with young tertiary-educated adults who would only have left education recently. However,
in Germany, Greece, Italy, the Netherlands, Norway, Spain and the United Kingdom the earnings difference between these
workers amounts to 25% or more (Figure A4.3).
In most OECD and partner countries, the difference in earnings between 45-54 year-olds and 25-34 year-olds is larger for
those with upper secondary or post-secondary non-tertiary education than for those with below upper secondary education.
The size of the difference varies from about 40% or more in Brazil, Italy, Ireland, the Netherlands, Portugal and Spain to less
than 10% in Chile, the Czech Republic, Hungary and Poland. In a few countries, however, young workers with an upper
secondary or post-secondary non-tertiary education earn more than older workers. This is the case in Estonia, Latvia,
Lithuania and the Slovak Republic (Figure A4.3).

Figure A4.3. Earnings of 45-54 year-olds relative to earnings of 25-34 year-olds, by educational
attainment and programme orientation (2018)
Full-time full-year workers; earnings of 25-34 year-olds = 100
Tertiary
Upper secondary or post-secondary non-tertiary
Upper secondary or post-secondary non-tertiary – general
Upper secondary or post-secondary non-tertiary – vocational
Below upper secondary

%
200
180
160
140
120

Latvia 2
Estonia

Slovak Republic

Hungary

Lithuania1

Poland

Czech Republic

Chile1

Colombia

Finland1

Slovenia
Belgium1

Korea

Australia

Canada1

OECD average
Norway

Mexico2

Costa Rica

EU23 average

New Zealand

United Kingdom

Denmark

Germany

Switzerland

France1
Austria

United States

Turkey2

Sweden
Israel

Greece

Spain1

Luxembourg2

Italy1
Brazil1

Netherlands

Ireland

80

Portugal

100

1. Year of reference differs from 2018. Refer to Table A4.1 for details.
2. Earnings net of income tax.
Countries are ranked in descending order of the share of 25-64 year-olds with upper secondary or post-secondary non-tertiary education.
Source: OECD (2020). 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/10.1787/888934162489

In contrast, in about half of OECD and partner countries with available data, older adults with tertiary education earn at least
50% more than their younger peers. The difference in earnings between older and younger tertiary-educated adults is below
10 percentage points only in Estonia, Latvia and Lithuania, while it exceeds 60% in Austria, Israel, Italy, Luxembourg,
the Netherlands, Portugal and Spain. 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 A4.3).

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A4. WHAT ARE THE EARNINGS ADVANTAGES FROM EDUCATION?  91
The earnings gap between older and younger workers with upper secondary or post-secondary non-tertiary education is wider
for those who attended a general programme rather than a vocational one in most OECD and partner countries. In Austria,
Denmark, Finland, Norway, Spain and Sweden the difference in earnings is over 20 percentage points more for those with a
general qualification, while in Chile, Hungary and Israel, the earnings increase is larger for those with a vocational one (about
10 percentage points in all three countries).
The observed difference in earnings between older and younger adults with general or vocational qualifications seems to be
consistent with the observation made by some researchers that vocational graduates have a comparative employment and
earnings advantage at the beginning of their careers that diminishes over time and turns into an employment and earnings
disadvantage compared with general graduates in the long term (Hanushek et al., 2017[3]; Brunello and Rocco, 2017[4]).

Box A4.1. Relative earnings of recent graduates
Some countries have longitudinally linked administrative data for students, combining study information with post-study
employment information. Along with existing sample-based graduate and non-graduate surveys available in other
countries, these data can provide further insights into the education-related growth in earnings of recent graduates aged
15-34 at the time of graduation.
In the 12 countries with available data, young adults with a bachelor’s or equivalent degree earn 62% more 3 years after
graduation than those who completed their upper secondary education in the same year and are no longer in education.
This earnings advantage for part-time and full-time young workers with a bachelor’s degree varies considerably across
countries, from about 100% or more in Chile, Lithuania and Turkey to less than 25% in Norway and Sweden (Figure A4.4 –
Panel A).
In all countries, the earnings advantage of recent bachelor’s graduates over those with upper secondary education is
lower when comparing those in the same age group instead of the same number of years after graduation. For instance
in Norway or Sweden – the two countries with the lowest earnings advantage three years after graduation – the earnings
advantage vanishes when looking at 25-34 year-olds as a group. This shows that the earnings disadvantage of young
upper secondary graduates has been partly compensated for by their additional years of professional experience at
25-34 years old. However, in the long run the comparative advantage of tertiary-educated graduates increases five years
after graduation (Table A4.4 and Figure A4.4 – Panel A).
Among countries with available data, three years after graduation, those with a master’s or equivalent degree earn more
than their peers with a bachelor’s or equivalent degree and those who only attained upper secondary education. In about
half of countries, the earnings of recent graduates with a master’s degree are more than double the earnings of those with
an upper secondary qualification and the earnings advantage ranges from about 50% in Latvia, Norway and Sweden to
almost 200% in Chile (Figure A4.4 – Panel B).
The evolution of the salaries of young master's graduates follows the same trend in most countries with data. Their
earnings advantage over their peers with an upper secondary education decreases during the first five years after
graduation. In Lithuania, for example, one year after graduation, master's degree holders earn about three times more
than upper secondary school graduates. Three years on, the wage premium is only 150%, while five years after graduation
it has fallen to 100%. On the other hand, in some countries, most notably Finland, New Zealand, Norway and Sweden,
the variations over time in the relative earnings advantage of a master's degree compared to an upper secondary
qualification are much smaller (Figure A4.4 – Panel B).

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92  A4. WHAT ARE THE EARNINGS ADVANTAGES FROM EDUCATION?

Figure A4.4. Relative earnings of recent bachelor's and master's or equivalent graduates compared to
those with an upper secondary education, by years since graduation (2018)
Full- and part-time workers aged 15-34 years, not in education, upper secondary education = 100
Five years
Three years
One year

Panel A
Index
400

Recent graduates with a bac helor’s or equivalent degr ee

Panel B
Index
400

Rec ent gr aduates with a master’s or equivalent degree

Sweden

Norway

Austria

Finland1

Latvia3

United Kingdom

Luxembourg 3

Average

New Zealand 4

Estonia

Turkey 3

Lithuania

Chile1, 2

Sweden

Norway

100

Austria

100

Finland1

150

Latvia3

150

United Kingdom

200

Luxembourg 3

200

Average

250

New Zealand 4

250

Estonia

300

Turkey 3

300

Lithuania

350

Chile1, 2

350

1. Year of reference 2017.
2. The category "three years" since graduation refers to two years.
3. Earnings net of income tax.
4. Upper secondary general graduates only.
Countries are ranked in descending order of the relative earnings of workers with a bachelor's or equivalent degree three years after graduation.
Source: OECD (2020), Data collection on labour-market outcomes of recent graduates.
Statlink2https://doi.org/10.1787/888934162508

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, women with below upper
secondary education who work full time earn 77% of the earnings of their male peers, a gender gap of 23%. A similar gender
gap in earnings is observed for women with an upper secondary or post-secondary non-tertiary education (22%), or women
with tertiary education (24%) (Table A1.3).
As women are more likely to work part-time than men, the gender gap in the average earnings of all workers (including fulltime and part-time earners) is even wider. On average across OECD countries, women with below upper secondary education
in full-time or part-time work earn only 69% of the earnings of similarly educated men and women with secondary or postsecondary non-tertiary education and tertiary-educated women earn only 70% of the earnings of similarly educated men
(OECD, 2020[2]).
The reasons for the gender gap in earnings include gender stereotyping, social conventions and discrimination against
women, but also differences between men and women in their choice of fields of study. Gender stereotypes and social
conventions may also contribute to the observed differences in fields of study between men and women. Men are more likely
than women to study in fields associated with higher earnings, such as engineering, manufacturing and construction, and
information and communication technologies (ICT), while a larger share of women enrol in fields associated with lower
earnings, including education, and arts and humanities (OECD, 2019[5]).
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[6]). In most of the

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A4. WHAT ARE THE EARNINGS ADVANTAGES FROM EDUCATION?  93
countries with available data, the gender gap between the earnings of tertiary-educated men and women narrowed between
2010 and 2018. On average across the 18 OECD countries with data for both years, the gap fell by about 3 percentage points,
reaching over 5 percentage points in Australia, Estonia, Korea, Luxembourg, the Netherlands and Norway (OECD, 2020[2]).

Box A4.2. Choice of field of studies and expected earnings
Data on education and earnings by field of study have been collected for Education at a Glance 2019 and are available
for 12 countries: Austria, Chile, Denmark, Estonia, Finland, Germany, Latvia, Norway, Portugal, Sweden, Switzerland and
the United Kingdom. The data combined with the data collected in the annual UOE data collection on new entrants by
field of study allow to gain more insights in the students’ choice of fields of study and the earnings levels in these fields.
The earnings advantage for tertiary-educated adults also varies by their field of study. The two broad fields of study most
commonly associated with the highest earnings are engineering, manufacturing and construction, and information and
communication technologies (ICT). While tertiary-educated adults earned 56% more for part-time and full-time work in
2017 than adults with upper secondary education, regardless of their field of study, on average in the 12 OECD countries
with available data, the earnings advantage for the best-paid fields is about 80%. The two broad fields of studies
associated with the lowest earnings are arts and humanities, and education. Adults who graduated from these fields earn
about 25% more than their peers with an upper secondary education do (Figure A4.5).
From an economic point of view, one might expect the choice of field of study of young students to be strongly determined
by the expected employment and earnings outcomes. In other words, the field of study with the highest expected earnings
level should also attract the largest share of new entrants into tertiary education. A comparison of the earnings advantage
by field of study with the share of new entrants into each field, using the average across the 12 OECD countries with
available data, shows that the correlation between them is only weak.
Only half of the broad fields shown in Figure A4.5 support the hypothesis that students’ preferences in field of study are
related to relative earnings. For arts and humanities (earnings advantage of 17%), and education (25%) the low level of
relative earnings correspond to low shares of new entrants (10% for arts and humanities, and 8% for education).
Conversely, the high relative earnings for graduates in engineering, manufacturing and construction, and business,
administration and law correspond to high shares of new entrants (16% for engineering, manufacturing and construction,
and 23% for business, administration and law). In contrast, the relative earnings advantage for ICT graduates is 78% but
the share of new entrants is 5%, while the earnings advantage for natural sciences, mathematics and statistics is 66% but
only 7% of new entrants chose this broad field. However, in some countries access to some fields of study is limited to
the number of places available and students have to pass successfully the selection process (see Indicator D6 in (OECD,
2019[5]) and Figure A4.5).
Although not shown in the figure, the conclusion remains the same when analysing countries individually, except for Chile,
Portugal and Sweden, where the fields of study with the highest relative earnings are also the most popular (see
Table A4.4 and (OECD, 2019[5]; OECD, 2020[7])).
A number of reasons explain the weak effect of wages on enrolment. These include limitations in the number of admissions
of students in some fields of study, the corresponding labour markets, lack of information on expected earnings in different
fields, and students’ personal interests and motivation.
Moreover, using higher earnings as a proxy for market demand, these figures also suggest a potential imbalance in some
countries between the fields most in demand by the labour market and the current supply of graduates (see also Education
at a Glance 2017 (OECD, 2017[8]), Indicator A6). Therefore, understanding students’ choice of fields is critical for policy
makers, as the distribution of new tertiary entrants in different fields of study may predict a lack of qualified workers in
some fields.

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94  A4. WHAT ARE THE EARNINGS ADVANTAGES FROM EDUCATION?

Figure A4.5. Relationship between the share of tertiary new entrants and relative earnings, by field of
study (2017)
Average across OECD countries with available data
Average (all fields): 156

Share of new entrants (%)
30

High relative earnings
High share of new entrants

25
Business,
administration and law

20
Health
and welfare

15

Engineering, manufacturing
and construction

Average
(all fields): 12
Arts and humanities

10

Social sciences,
journalism and information

Education

Natural sciences,
mathematics
and statistics

5
Low relative earnings
Low share of new entrants

Information and
communication
technologies (ICTs)

0
100

110

120

130

140

150

160

170

180
190
Relative earnings
(upper secondary education = 100)

Source: OECD (2020). 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/10.1787/888934162527

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).
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.

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A4. WHAT ARE THE EARNINGS ADVANTAGES FROM EDUCATION?  95
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 selfemployed 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.
Data presented at the country level are average earnings, but there can be significant variations for individuals. Data shown
in Table A4.2 “Level of earnings relative to median earnings, by educational attainment (2018)” illustrate the earnings
variations among individuals.
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[9]) for more
information and Annex 3 for country-specific notes (https://doi.org/10.1787/69096873-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 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 country-specific notes on the national sources (https://doi.org/10.1787/69096873-en).

References

Brunello, G. and L. Rocco (2017), “The labor market effects of academic and vocational education over the life
cycle: Evidence based on a British cohort”, Journal of Human Capital, Vol. 11/1, pp. 106-166,
http://dx.doi.org/10.1086/690234.

[4]

Hanushek, E. et al. (2017), “General education, vocational education, and labor-market outcomes over the life
cycle”, The Journal of Human Resources, Vol. 52/1, pp. 48-87, http://dx.doi.org/10.3368/jhr.52.1.0415-7074R.

[3]

OECD (2020), Education and earnings, Education at a Glance Database, OECD.Stat,
http://stats.oecd.org/Index.aspx?datasetcode=EAG_EARNINGS.

[2]

OECD (2020), Education at a Glance Database - Entrants by field,
http://stats.oecd.org/Index.aspx?datasetcode=EDU_ENTR_FIELD.

[7]

OECD (2019), Education at a Glance 2019: OECD Indicators, OECD Publishing, Paris,
https://dx.doi.org/10.1787/f8d7880d-en.

[5]

OECD (2019), Working Better with Age, Ageing and Employment Policies, OECD Publishing, Paris,
https://dx.doi.org/10.1787/c4d4f66a-en.

[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.

[9]

EDUCATION AT A GLANCE 2020 © OECD 2020

96  A4. WHAT ARE THE EARNINGS ADVANTAGES FROM EDUCATION?
OECD (2017), Education at a Glance 2017: OECD Indicators, OECD Publishing, Paris,
https://dx.doi.org/10.1787/eag-2017-en.

[8]

OECD (2017), The Pursuit of Gender Equality: An Uphill Battle, OECD Publishing, Paris,
http://dx.doi.org/10.1787/9789264281318-en.

[6]

Indicator A4 Tables
Table A4.1

Relative earnings of workers, by educational attainment (2018)

Table A4.2

Level of earnings relative to median earnings, by educational attainment (2018)

Table A4.3

Women’s earnings as a percentage of men's earnings, by educational attainment and age group (2018)

Table A4.4

Relative earnings of workers, by educational attainment and age (2018)

Cut-off date for the data: 19 July 2020. Any updates on data can be found on line at http://dx.doi.org/10.1787/eag-dataen. More breakdowns can also be found at http://stats.oecd.org/, Education at a Glance Database.
StatLink: https://doi.org/10.1787/888934162356

EDUCATION AT A GLANCE 2020 © OECD 2020

A4. WHAT ARE THE EARNINGS ADVANTAGES FROM EDUCATION?  97

Table A4.1. Relative earnings of workers, by educational attainment (2018)
25-64 year-olds with income from employment (full-time full-year workers)
Baseline: Upper secondary education = 100
Upper secondary or post-secondary
non-tertiary

Partners

OECD

Tertiary

Countries
Australia
Austria
Belgium 1
Canada 1
Chile 1
Colombia 2
Costa Rica
Czech Republic 2
Denmark
Estonia
Finland 1
France 3
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy 3
Japan
Korea
Latvia 4
Lithuania 5
Luxembourg 4
Mexico 4
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic 2
Slovenia
Spain 1
Sweden
Switzerland 2
Turkey 4
United Kingdom
United States

Below upper Post-secondary Short-cycle
secondary
non-tertiary
tertiary
(1)
(3)
(4)

Bachelor's or
equivalent
(5)

Master's,
doctoral or
equivalent
(6)

Total
(7)

Total
(11)

General
programmes
(12)

Vocational
programmes
(13)

91
76
90
83
71
72
74
63
90
90
101
93
78
81
77
m
96
75
79
m
79
91
94
83
80
86
89
86
85
78
78
82
84
85
79
78
87
71

101
106
c
115
a
m
c
m
122
91
114
m
113
102
101
m
104
a
m
m
a
103
108
c
a
117
99
101
100
107
m
a
89r
114
m
a
a
m

104
131
c
115
138
x(7)
123
116
110
95
119
121
132
162
111
m
132
106
x(7)
m
111
124
a
121
117
126
107
120
m
95
114
136
113
105
x(5, 6)
x(7)
121
113

127
101
124
145
279
x(7)
199
128
113
135
120
136
162
132
158
m
157
139
x(7)
m
139
138
152
147
153
130
125
106
141
169 d
123
140
142
112
132 d
x(7)
132
166

142
175
162
177
457
x(7)
345
166
147
145
159
184
175
170
209
m
181
200
x(7)
m
185
161
211
149
308
173
160
134
159
x(5)
160
185
174
143
158 d
x(7)
157
221

125
148
139
139
241
228
200
158
124
135
135
146
161
138
177
m
157
149
137
m
136
146
177
146
158
147
129
118
155
169
155
165
148
122
145
167
137
171

110
132
112
126
141
140
134
160
111
109
99
107
132
124
129
m
106
133
127
m
127
111
112
121
125
117
112
117
118
128
129
122
120
120
127
128
115
141

x(11)
149
116
120
141
x(11)
129
132
123
116
118
120
143
x(11)
128
m
x(11)
133
x(11)
m
126
109
x(11)
103
125
x(11)
111
121
x(11)
129
138
x(11)
123
124
131
126
125
141

x(11)
130
110
138
143
x(11)
186
166
109
105
97
103
128
x(11)
134
m
x(11)
136
x(11)
m
128
112
x(11)
c
127
x(11)
112
115
x(11)
125
128
x(11)
115
117
126
131
108
m

OECD average
EU23 average

83
85

m
106

119
120

143
136

189
169

154
149

123
120

126
125

125
119

Argentina
Brazil 6
China
India
Indonesia
Russian Federation
Saudi Arabia
South Africa

m
68
m
m
m
m
m
m

m
m
m
m
m
m
m
m

m
x(5)
m
m
m
m
m
m

m
231 d
m
m
m
m
m
m

m
445
m
m
m
m
m
m

m
244
m
m
m
m
m
m

m
146
m
m
m
m
m
m

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

G20 average

m

m

m

m

m

m

m

m

m

Note: See Definitions and Methodology sections for more information. Additional columns showing data for additional educational attainment levels are available for
consultation on line. Data and more breakdowns are available at http://stats.oecd.org/, Education at a Glance Database.
1. Year of reference 2017.
2. Index 100 refers to the combined ISCED levels 3 and 4 in the ISCED 2011 classification.
3. Year of reference 2016.
4. Earnings net of income tax.
5. Year of reference 2014.
6. Year of reference 2015.
Source: OECD (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2https://doi.org/10.1787/888934162375

EDUCATION AT A GLANCE 2020 © OECD 2020

98  A4. WHAT ARE THE EARNINGS ADVANTAGES FROM EDUCATION?
Table A4.2. Level of earnings relative to median earnings, by educational attainment (2018)
Median earnings from work for 25-64 year-olds with earnings (full- and part-time workers) for all levels of education
Below upper secondary

Upper secondary or post-secondary non-tertiary

Tertiary

Partners

OECD

More
More
More
than 1.5
More
More
More than 1.5
than
than the times the
than
half the than the times the
At or
half the median median
At or
At or median median median
below
below median but at or but at or More
below but at or but at or but at or More
half
than
but at or below 1.5 below
half
than
below below 1.5 below
half
the times the twice the twice the of the below the times the twice the twice the of the
of the
median median median median median median median median median median median

More
More
More than 1.5
than
half the than the times the
median median median
but at or but at or but at or More
than
below below 1.5 below
the times the twice the twice the
median median median median

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

(13)

(14)

(15)

Countries
Australia
Austria
Belgium 1
Canada 2
Chile 2
Colombia
Costa Rica
Czech Republic
Denmark
Estonia
Finland 2
France 3
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy 3
Japan
Korea
Latvia 1
Lithuania 4
Luxembourg 1
Mexico 1
Netherlands 5
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain 2
Sweden
Switzerland
Turkey 1
United Kingdom
United States

20
32
9
39
25
36
20
29
30
27
29
31
42
33
1
m
41
27
30
m
23
5
31
20
32
33
21
51
0
9
36
0
37
25
30
32
26
44

47
45
66
31
50
37
50
58
40
41
36
40
37
38
80
m
26
49
34
m
58
67
44
59
31
36
43
30
72
54
44
83
31
45
51
43
42
40

21
18
23
17
18
20
23
12
24
12
25
20
16
21
15
m
20
16
26
m
15
21
13
15
21
24
25
14
21
25
15
15
21
25
17
19
19
11

7
4
1
7
4
4
4
1
4
11
6
5
3
5
3
m
6
5
7
m
3
4
8
5
8
5
7
3
5
7
4
1
6
4
1
4
7
3

5
2
c
5
3
3
3
0
2
9
3
3
c
3
1
m
7
3
4
m
c
2
3
c
8
2
5
2
2
5
2
0
5
1
c
2
6
2

15
17
5
29
13
19
10
5
17
20
22
21
22
18
0
m
25
19
18
m
10
5
20
10
16
23
19
24
0
5
17
0
25
15
22
18
20
25

42
32
59
29
41
30
39
49
38
41
38
37
36
34
60
m
30
44
30
m
48
61
43
51
21
35
36
35
59
36
35
63
29
36
40
34
38
40

25
30
32
21
26
33
29
34
34
12
29
28
27
34
26
m
23
21
30
m
26
25
19
27
25
27
27
29
28
29
29
28
22
35
30
29
26
20

10
12
3
11
10
9
12
8
8
13
7
8
10
10
8
m
12
8
12
m
10
5
11
8
15
10
10
8
8
12
12
6
13
9
6
12
11
9

8
8
c
11
10
8
11
3
4
13
3
5
5
5
5
m
9
9
10
m
5
4
7
3
24
5
8
4
5
17
7
2
10
4
2
7
6
7

12
13
2
22
4
7
4
3
14
12
13
10
12
10
c
m
14
10
15
m
5
2
15
3
6
15
13
17
0
3
12
0
14
14
10
12
10
13

30
16
28
22
16
13
12
20
24
25
23
21
18
21
18
m
20
27
20
m
26
35
22
28
10
21
27
22
30
12
17
23
20
25
23
14
24
24

28
20
50
20
18
22
19
39
38
17
33
31
26
35
33
m
18
23
28
m
29
33
20
30
15
26
27
37
35
17
27
34
20
37
34
17
27
22

15
19
15
15
14
14
15
18
13
20
17
18
20
19
19
m
19
15
14
m
20
10
17
21
16
18
15
13
16
18
19
22
16
14
19
27
19
16

16
32
5
21
48
44
50
21
11
26
15
19
24
14
30
m
29
26
24
m
20
20
27
17
53
21
17
11
19
50
24
20
30
10
14
30
20
25

OECD average
EU23 average

27
24

46
49

19
19

5
5

3
3

16
14

40
42

27
28

10
9

7
6

10
9

22
22

27
29

17
17

25
22

Argentina
Brazil 6
China
India
Indonesia
Russian Federation
Saudi Arabia
South Africa

m
29
m
m
m
m
m
m

m
42
m
m
m
m
m
m

m
15
m
m
m
m
m
m

m
6
m
m
m
m
m
m

m
7
m
m
m
m
m
m

m
9
m
m
m
m
m
m

m
40
m
m
m
m
m
m

m
22
m
m
m
m
m
m

m
12
m
m
m
m
m
m

m
18
m
m
m
m
m
m

m
2
m
m
m
m
m
m

m
12
m
m
m
m
m
m

m
13
m
m
m
m
m
m

m
13
m
m
m
m
m
m

m
60
m
m
m
m
m
m

G20 average

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

Note: See Definitions and Methodology sections for more information. Data and more breakdowns are available at http://stats.oecd.org/, Education at a Glance Database.
1. Earnings net of income tax.
2. Year of reference 2017.
3. Year of reference 2016.
4. Year of reference 2014.
5. Data refer to full-time, full-year earners only.
6. Year of reference 2015.
Source: OECD (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2https://doi.org/10.1787/888934162394

EDUCATION AT A GLANCE 2020 © OECD 2020

A4. WHAT ARE THE EARNINGS ADVANTAGES FROM EDUCATION?  99

Table A4.3. Women’s earnings as a percentage of men's earnings, by educational attainment and age group (2018)
Average earnings of adults with income from employment (full-time full-year workers)
Upper secondary or post-secondary
non-tertiary

Below upper secondary

Tertiary

Partners

OECD

25-64 year-olds 35-44 year-olds 55-64 year-olds 25-64 year-olds 35-44 year-olds 55-64 year-olds 25-64 year-olds 35-44 year-olds 55-64 year-olds
(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

Countries
Australia
Austria
Belgium 1
Canada 1
Chile 1
Colombia
Costa Rica
Czech Republic
Denmark
Estonia
Finland 1
France 2
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy 2
Japan
Korea
Latvia 3
Lithuania 4
Luxembourg 3
Mexico 3
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain 1
Sweden
Switzerland
Turkey 3
United Kingdom
United States

78
81
83
67
81
85
84
86
83
56
81
75
71
72
87
m
72
67
80
m
73
80
79
80
66
87
79
82
75
78
77
83
79
84
74
71
78
69

80
83
c
72
89
82
88
86
82
54
81
c
c
64
87
m
c
63
81
m
71
82
76
c
66
90
78
80
73
78
81
81
81
82
73
73
73
65

74
76
c
63
74
80
78
87
82
70
80
c
c
70
84
m
c
77
85
m
72
76r
73
c
68
88
75
81
76
75
73
83
85
85
67
c
76
72

77
84
88
69
76
81
80
81
80
63
78
78
84
83
90
m
81
67
77
m
69
75
79
87
72
83
78
79
79
75
76
85
75
82
84
80
72
71

75
79
84r
64
76
76
83
75
79
60
76
81
87
85
86
m
77
62
76
m
71
75
76
91
72
89
77
77
73
76
72
81
76
82
88
78
76
71

75
87
c
75
71
77
c
89
81
71
78
83
84
78
94
m
82
65
75
m
63
78
85
c
78
79
74
79
86
69
83
92
80
82
83
c
75
70

81
72
82
72
68
82
97
73
76
75
77
72
74
78
69
m
69
69
68
m
73
75
75
86
75
77
76
75
71
73
70
82
81
78
79
84
77
72

86
74
85
77
71
81
88
69
78
76
76
75
71
80
64
m
78
69
72
m
77
69
70
87
77
87
77
76
69
76
65
80
79
79
87
87
78
76

72
68
85
66
68
77
125
84
71
79
74
54
82
81
77
m
55
70
68
m
80
82
80
c
71
76
77
72
73
71
76
86
82
75
80
c
74
m

OECD average
EU23 average

77
79

77
79

77
79

78
80

77
79

79
82

76
75

77
75

76
75

Argentina
Brazil 5
China
India
Indonesia
Russian Federation
Saudi Arabia
South Africa

m
69
m
m
m
m
m
m

m
69
m
m
m
m
m
m

m
68
m
m
m
m
m
m

m
65
m
m
m
m
m
m

m
66
m
m
m
m
m
m

m
60
m
m
m
m
m
m

m
65
m
m
m
m
m
m

m
66
m
m
m
m
m
m

m
63
m
m
m
m
m
m

G20 average

m

m

m

m

m

m

m

m

m

Note: See Definitions and Methodology sections for more information. Data and more breakdowns are available at http://stats.oecd.org/, Education at a Glance Database.
1. Year of reference 2017.
2. Year of reference 2016.
3. Earnings net of income tax.
4. Year of reference 2014.
5. Year of reference 2015.
Source: OECD (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2https://doi.org/10.1787/888934162413

EDUCATION AT A GLANCE 2020 © OECD 2020

100  A4. WHAT ARE THE EARNINGS ADVANTAGES FROM EDUCATION?
Table A4.4. Relative earnings of workers, by educational attainment and age (2018)
25-64 year-olds with income from employment (full-time full-year workers); upper secondary education = 100
Tertiary
Bachelor's or
equivalent

35-44
year-olds

55-64
year-olds

25-34
year-olds

35-44
year-olds

55-64
year-olds

35-44
year-olds

25-34
year-olds

25-34
year-olds

55-64
year-olds

55-64
year-olds

35-44
year-olds

35-44
year-olds

(2)

(3)

(4)

(5)

(6)

(7)

(8)

97
86
86 r
92
78
74
85
63
93
89
102
c
82
80
83
m
c
81
84
m
86
87
85
c
86
92
94
83
88
86
83
90
82
91
83
85
83
81

93
77
86
78
69
73
72
61
90
83
102
97
71
89
79
m
88 r
66
78
m
86
84
98
82
79
84
89
86
86
79
79
84
86
85
77
77
97
72

86
68
83
80
70
60
67
68
89
79
100
91
87
74
74
m
88
71
72
m
76
93
93
c
72
79
84
89
81
62
78
77
80
87
75
c
81
65

100
111
c
117
a
m
c
m
c
90
113
m
113
100
100
m
131
a
m
m
a
107
101
c
a
c
108
101
96
112
m
a
c
87
m
a
a
m

100
107
c
119
a
m
c
m
117
91
112
m
111
110
104
m
100
a
m
m
a
110
108
c
a
c
98
97
98
114
m
a
c
100
m
a
a
m

96
c
c
108
a
m
m
m
113
87
112
m
118
100
m
m
111
a
m
m
a
105
115
c
a
c
95
109
103
97
m
a
c
132
m
a
a
m

OECD average
EU23 average

86
86

82
84

79
81

m
m

m
m

m
m

110
112

118
120

Argentina
Brazil
China
India
Indonesia
Russian Federation
Saudi Arabia
South Africa

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

G20 average

m

m

m

m

m

m

m

Total

25-34
year-olds

25-34
year-olds

(1)
Countries
Australia
Austria
Belgium 1
Canada 1
Chile 1
Colombia 2
Costa Rica
Czech Republic2
Denmark
Estonia
Finland 1
France 3
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy 3
Japan
Korea
Latvia 4
Lithuania 5
Luxembourg4
Mexico 4
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic2
Slovenia
Spain 1
Sweden
Switzerland 2
Turkey 4
United Kingdom
United States

Master's, doctoral
or equivalent

55-64
year-olds

55-64
year-olds

Short-cycle tertiary

35-44
year-olds

Post-secondary
non-tertiary

25-34
year-olds
Partners

OECD

Below upper
secondary

(9)

(10)

(11)

(12)

(13)

(14)

(15)

(16)

(17)

(18)

116
104
109
128
214
x(16)
179
116
108
119
110
119
143
113
142
m
185
131
x(16)
m
120
121
147
133
139
120
122
97
129
150 d
113
123
148
99
125 d
x(16)
125
157

131
121
121
150
291
x(17)
207
134
112
126
118
138
165
135
164
m
160
140
x(17)
m
145
145
154
155
147
137
134
107
149
174 d
127
143
130
110
137 d
x(17)
142
171

137
110
135
162
298
x(18)
224
137
118
154
142
c
161
154
159
m
196
150
x(18)
m
173
125
141
c
179
135
124
114
152
214 d
125
167
156
134
136 d
x(18)
142
170

120
146
124
134
345
x(16)
c
137
128
131
137
152
148
186
161
m
199
164
x(16)
m
137
158
191
134
209
145
124
114
137
x(10)
127
144
148
123
132 d
x(16)
154
194

136
175
162
165
432
x(17)
290
178
144
150
150
195
184
166
219
m
167
178
x(17)
m
174
165
241
156
274
185
154
134
162
x(11)
163
174
172
138
158 d
x(17)
161
225

170
208
182
222
602
x(18)
c
170
168
150
181
c
191
196
235
m
263 r
196
x(18)
m
220
150
218
c
391
183
168
159
170
x(12)
173
217
187
163
168 d
x(18)
170
216

113
126
114
121
190
188
170
130
115
124
120
133
142
123
148
m
180
129
111
m
117
130
158
132
139
130
122
104
135
150
125
132
136
106
128
152
131
157

126
153
138
136
252
241
205
166
124
137
132
146
169
142
183
m
153
145
132
m
140
151
180
152
151
155
135
118
160
174
158
159
144
121
148
178
146
178

134
166
153
157
262
268
232
168
131
138
144
184
166
159
189
m
184
153
159
m
176
140
189
159
195
151
129
132
167
214
169
189
167
137
152
c
143
m

123
122

130
126

146
139

156
148

154
148

185
172

210
188

135
132

156
151

169
164

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

m

m

m

m

m

m

m

m

m

m

m

94
105
100
118
130
137
c
c
c
105
110
127
123
135
143
x(16)
x(17)
x(18)
117
117
c
c
107
117
104
112
109
c
112
102
106
112
119
122
118
c
123
135
129
c
167
c
108
118
m
m
m
m
118
118
114 r
100
109
103
x(16)
x(17)
x(18)
m
m
m
106
116
134
114
126
120 r
a
a
a
c
c
c
109
103
181
125
124
117
119
105
102
101
116
131
m
m
m
105
105
c
100
113
121
111
127
145
114
108
142
97
104
110
x(10, 13) x(11, 14) x(12, 15)
x(16)
x(17)
x(18)
111
132
123
110
115
110

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. 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 2016.
4. Earnings net of income tax.
5. Year of reference 2014.
Source: OECD (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2https://doi.org/10.1787/888934162432

EDUCATION AT A GLANCE 2020 © OECD 2020

102  A5. WHAT ARE THE FINANCIAL INCENTIVES TO INVEST IN EDUCATION?

Indicator A5. What are the financial
incentives to invest in education?
Highlights





Despite the rising share of tertiary-educated adults over recent decades, investing in upper secondary attainment
continues to pay off in the long run for both individuals and society, compared to not completing upper secondary.
On average across OECD countries, for each USD invested in upper secondary education, men can expect to
receive USD 9 over the course of their working-age life, while women can expect to receive USD 11.6. The gender
difference is related to the fact that women’s foregone earnings while they continue their education are much
lower than men’s, even though women receive a smaller net financial return from upper secondary attainment
than men.
Individuals’ net financial returns from tertiary education are generally higher than from upper secondary education.
On average across OECD countries, the net financial return for tertiary-educated men or women is around
1.5 times as much as for those with upper secondary education as their highest attainment.

Context
Investing time and money in education is an investment in human capital. Better chances of employment (see Indicator A3)
and higher earnings (see Indicator A4) are strong incentives for adults to invest in education and postpone employment.
Although women currently have higher levels of education than men on average (see Indicator A1), men enjoy better
employment and earning outcomes from education, on average.
Countries benefit from having more highly educated individuals through higher revenues from the taxes and social
contributions paid by those individuals once they 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. Financial returns may be affected by the
field of study and by the specific economic, labour-market and institutional context in each country, 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 sporting
activities (see Indicator A6).

Other findings







For nearly all countries with available data, the private and public net financial returns from obtaining a bachelor's,
master's or doctoral or equivalent degree are greater than from obtaining a short-cycle tertiary degree.
The public benefits of education outweigh the costs, through greater tax revenues and social contribution from
higher-paid workers. For instance, on average across OECD countries, the internal rate of return to governments
from upper secondary education is 6% for a man and 3% for a woman.
In most OECD countries, the main cost of education for individuals are not direct payments, such as tuition fees
and living expenses, but the earnings that individuals forego while they are in education. These vary substantially
by gender and across countries, depending on the length of education, overall earning levels, differences in
earnings across levels of educational attainment and students’ earnings.
For governments, direct costs (such as public expenditure on educational institutions and student grants)
represent the largest share of the total public costs of education (composed of these direct costs and foregone
taxes on earnings). Since the direct costs are the same for men as for women, total public costs are also quite
similar for men and women.

EDUCATION AT A GLANCE 2020 © OECD 2020

A5. WHAT ARE THE FINANCIAL INCENTIVES TO INVEST IN EDUCATION?  103

Figure A5.1. Private net financial returns to education for a man or a woman, by educational
attainment (2017)
In equivalent USD converted using PPPs for GDP; future costs and benefits are discounted at a rate of 2%
Man
In equivalent
USD converted
using PPPs
450 000

Woman

Upper secondary education
As compared with returns to below upper secondary education

400 000
350 000
300 000
250 000
200 000
150 000
100 000

Turkey2

Latvia2

Luxembourg1, 2

Portugal

Slovenia

Hungary

Chile

Spain

Estonia

New Zealand

France1

Poland1

Belgium

Italy1

Israel

Canad a

EU23 average

Finland

Kore a

OECD average

Czech Republic1

Germany

Slovak Republic

Sweden1

Denmark

Australia1

United States

Ireland

Norway

Austria

In equivalent
USD converted
using PPPs
700 000

Switzerland

0

United Kingdom

50 000

600 000
500 000
400 000
300 000
200 000
100 000
0

Tertiary education
As compared with returns to upper secondary education

1. Year of reference differs from 2017. Refer to the source tables for details.
2. Only net earnings are available and the calculations are using these values as if they were gross earnings.
Countries are ranked in descending order of the private net financial returns of upper secondary education for a man.
Source: OECD (2020), Tables A5.1 and A5.2, and Tables A5.5 and A5.6, available on line. See Source section for more information and Annex 3 for notes
(https://doi.org/10.1787/69096873-en).
Statlink2https://doi.org/10.1787/888934162641

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 upper secondary education versus
entering the labour market without an upper secondary qualification; 2) investing in tertiary education versus entering the
labour market with an upper secondary qualification.
It considers two types of investors: 1) 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) governments (referred to here as “public”)
that decide to invest in education and the additional revenue they 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. 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.

EDUCATION AT A GLANCE 2020 © OECD 2020

104  A5. WHAT ARE THE FINANCIAL INCENTIVES TO INVEST IN EDUCATION?

Analysis
Financial incentives to invest in upper secondary education
Financial incentives 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 the direct costs of attaining education and foregone earnings, while the benefits
correspond to earnings from employment after paying income taxes and social contributions (see Definitions section). 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 their working-age life. The financial
incentives to invest in education can also be expressed as total benefits relative to total costs (benefit-cost ratio). This is
expressed as the financial benefit of attaining an additional level of education for each USD invested in it. Depending on which
measure is used, the relative incentives to invest in additional educational attainment differ between men and women.
In all OECD countries, investing in upper secondary education pays off in the long run for both men and women. The gains
associated with this level of education that individuals can expect to receive over their career exceed the costs they bear
during their studies. On average across OECD countries, the private net financial return for each individual attaining upper
secondary education, compared to an individual with below upper secondary education, is USD 186 100 for a man and
USD 150 400 for a woman (Figure A5.1).
The private financial returns from upper secondary education are higher for men than for women in most OECD countries
with available data. In Korea, the private financial return from upper secondary education is more than three times higher for
men than for women. The only countries where women have higher private financial returns than men are Belgium, Finland,
France, Israel and Slovenia (Figure A5.1).
Direct costs refer to the total expenditure on education, which are the same for men and women. On average across OECD
countries, the direct costs for both men and women of attaining upper secondary education are USD 2 700. While direct costs
are the most obvious element, in most countries the main costs are foregone earnings, i.e. the earnings individuals could
expect to receive if they decide not to pursue further education. Foregone earnings depend on the length of education,
earnings levels, employment rates and the difference in earnings and employment between 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 (OECD, 2017[1]). On average across OECD countries,
the foregone earnings of attaining upper secondary education are about USD 20 500 for a man and USD 11 500 for a woman
(Table A5.1 and Table A5.2). When direct costs and foregone earnings are combined, the average total costs of attaining
upper secondary education, compared to not continuing in education, are USD 14 200 for women, representing about 60%
of the total costs for men (USD 23 200). In Sweden, men can expect their total costs to be nearly four times those of women.
Luxembourg is the only country where women face higher total costs than men (Figure A5.2).
Differences in labour-market outcomes lead to a wide variation in the private total benefits associated with investment in upper
secondary education for men and women. On average across OECD countries, the total benefits of attaining upper secondary
education are USD 209 300 for men and USD 164 600 for women. This is mainly due to gender gaps in earnings, but is also
related to lower employment levels for women with an upper secondary education than for men (see Indicators A3 and A4
and Figure A5.2).
While further education yields higher earnings over the course of a working life, the private benefits from investing in education
also depend on countries’ tax and social contribution systems (Brys and Torres, 2013[2]). For instance, in Chile, Estonia,
Korea and Switzerland, income taxes and social contributions amount to less than one-fifth of the gross earnings benefits for
a man attaining upper secondary education, while in Belgium they add up to more than 40% 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 Korea, the
income tax and social contributions for a woman who attained upper secondary education are less than one-third those of a
man with the same level of attainment (Table A5.1 and Table A5.2). Note that taxes and social contributions also relate to
pensions and retirement programmes, which are not considered in this indicator.

EDUCATION AT A GLANCE 2020 © OECD 2020

A5. WHAT ARE THE FINANCIAL INCENTIVES TO INVEST IN EDUCATION?  105

Figure A5.2. Private costs and benefits for a man or a woman attaining upper secondary education (2017)
As compared with returns to below upper secondary education, in equivalent USD converted using PPPs for GDP; future
costs and benefits are discounted at a rate of 2%

Woman

Total costs
Man

Total benefits
Man

Woman

Turkey1
Latvia1
Luxembourg1, 2
Chile
Hungary
Slovenia
Portugal
Spain
Estonia
France2
New Zealand
Finland
Italy2
Poland 2
EU23 average
Canada
Israel
OECD average
Belgium
Korea
Slovak Republic
Germany
Czech Republic2
United Kingdom
Denmark
Sweden2
Australia2
United States
Ireland
Austria
Norway
Switzerland
-500 000
-400 000
In equivalent USD
converted using PPPs

-300 000

-200 000

-100 000

0

0

100 00 0

200 000

300 00 0

400 000
500 00 0
In equivalent USD
converted using PPPs

1. Only net earnings are available and the calculations are using these values as if they were gross earnings.
2. Year of reference differs from 2017. Refer to the source tables for details.
Countries are ranked in ascending order of the total private benefits for a man.
Source: OECD (2020), Tables A5.1 and A5.2. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2https://doi.org/10.1787/888934162660

Across OECD countries, the average internal rate of return to upper secondary education is 25% for men and 32% for women.
However, there are wide variations across countries, particularly for women. The internal rate of return to upper secondary
education for women ranges from 7% in Luxembourg to more than 70% in Denmark and Ireland ( Table A5.1 and
Table A5.2).
Looking at the benefit-cost ratio, on average across OECD countries, for each USD invested in upper secondary education,
men can expect to receive USD 9 over the course of their working-age life, while women can expect to receive USD 11.6 The
private benefits for each USD invested in upper secondary education is the lowest in Luxembourg (USD 3.3 for a man and
USD 2.2 for a woman) and the highest in Denmark (USD 31.2 for a man and USD 63.9 for a woman). In Luxembourg, women
face the highest total costs of pursuing upper secondary education among OECD countries, and the fifth lowest total benefits.

EDUCATION AT A GLANCE 2020 © OECD 2020

106  A5. WHAT ARE THE FINANCIAL INCENTIVES TO INVEST IN EDUCATION?
In contrast, women in Denmark pay the lowest costs for upper secondary education and can expect to receive the second
highest total benefits from it (Figure A5.3).
In most OECD countries with available data, women enjoy higher financial benefits than men for each USD invested in upper
secondary education, even though their private net financial returns from upper secondary education are lower. This is due
to the fact that, compared to the difference in total benefits, total costs are disproportionally lower for women than for men.
For instance in Sweden, although women’s total benefits from upper secondary education are about 85% of the total benefits
for men, their total costs are just one-quarter of the total for men. However, in Australia, Korea, Luxembourg, Norway and
the United Kingdom, men receive greater financial benefits for each USD they invest in upper secondary education than
women do (Figure A5.2 and Figure A5.3).

Figure A5.3. Financial benefits for each equivalent USD invested in upper secondary education, by
gender (2017)
As compared with returns to below upper secondary education, in equivalent USD converted using PPPs for GDP; future
costs and benefits are discounted at a rate of 2%
Man

In equivalent
USD converted
using PPPs
for GDP
40

Woman

Private financial benefits for each equivalent USD
invested in upper secondary education

63.9

35
30
25
20
15
10
5

Portugal

Luxembourg1, 2

Slovenia

Hungary

Belgium

New Zealand

Estonia

Poland1

Chile

Turkey2

Israel

Latvia 2

Czech Republic1

Korea

Canada

Italy1

EU23 average

OECD average

Sweden1

Spain

United States

United Kingdom

Australia1

Finland

Norway

France1

Slovak Republic

Germany

Switzerland

Austria

Ireland

In equivalent
USD converted
using PPPs
for GDP
5

Denmark

0

4
3
2
1
0

Public financial benefits for each equivalent USD
invested in upper secondary education

Note: Private financial benefits are net of income taxes and social contributions. The financial benefits for each equivalent USD invested in education are sensitive to the
total costs of education. Readers would need to combine Figure A5.2 and Figure A5.3 to interpret the results. For example, in Denmark, the private total benefits from upper
secondary education are similar for men and for women (USD 268 400 and USD 262 000), but the private total costs of upper secondary education are twice as high for
men as for women (USD 8 600 compared with USD 4 100) (see Figure A5.2, and Tables A5.1 and A5.2).
1. Year of reference differs from 2017. Refer to the source tables for details.
2. Only net earnings are available and the calculations are using these values as if they were gross earnings.
Countries are ranked in descending order of the private financial benefits for each dollar invested in upper secondary education for a man.
Source: OECD (2020), Tables A5.1, A5.2, A5.3 and A5.4. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2https://doi.org/10.1787/888934162679

EDUCATION AT A GLANCE 2020 © OECD 2020

A5. WHAT ARE THE FINANCIAL INCENTIVES TO INVEST IN EDUCATION?  107

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.

Table A5.a. Net financial returns for a man attaining upper secondary education, by discount rate (2017)
As compared with a man attaining below upper secondary education, in equivalent USD converted using PPPs for GDP

OECD

Discount rate
2%

3.75%

8%

Countries
Australia 1
Austria
Belgium2
Canada
Chile
Czech Republic 2 , 3
Denmark
Estonia
Finland 2
France 1, 2
Germany
Hungary 2
Ireland 2
Israel 2
Italy 1
Korea
Latvia 4
Luxembourg 1, 2 , 4
New Zealand
Nor way
Poland 1, 2
Por tugal 2
Slovak Republic 2
Slovenia 2
Spain
Sweden 1
Switzerland
Turkey 2 , 4
Unite d Kingdom
United States

252 900
297 400
169 000
173 400
102 100
200 100
259 800
132 300
177 700
157 300
214 100
98 500
296 200
169 600
170 100
190 600
66 100
77 700
147 900
293 700
158 600
96 500
209 700
96 400
131 700
247 900
428 000
59 000
242 100
268 900

174 300
195 900
101 600
109 700
59 500
128 400
177 800
87 800
126 300
106 300
145 700
59 000
208 200
103 600
97 900
117 200
44 400
45 900
88 800
198 200
100 600
50 500
140 700
64 600
76 800
168 900
295 500
31 900
154 100
175 500

82 300
83 200
28 700
38 400
15 300
47 200
82 000
36 500
63 100
47 000
67 000
16 000
102 800
33 800
26 900
38 700
19 200
9 800
25 700
87 100
34 100
5 200
60 900
25 600
21 300
75 600
145 300
4 600
57 500
72 500

OECD average
EU23 average

186 100
174 900

121 200
114 100

48 400
45 500

Note: Values are based on the difference between men who attained an upper secondary education compared with those who have attained a below upper secondary
education. Values have been rounded up to the nearest hundred. Direct costs to education do not include student loans.
1. Year of reference 2016.
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 2015.
4. Only net earnings are available and the calculations are using these values as if they were gross earnings.
Source: OECD (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
Statlink2https://doi.org/10.1787/888934162736

EDUCATION AT A GLANCE 2020 © OECD 2020

108  A5. WHAT ARE THE FINANCIAL INCENTIVES TO INVEST IN EDUCATION?
The results presented in the tables and figures of this indicator are calculated using a discount rate of 2%, based on the
average real interest on government bonds across OECD countries. However, it can be argued that education is not a
risk-free investment, and that the discount rate should therefore be higher. The OECD countries that perform similar costbenefit analysis use higher discount rates than 2%, but the rate used varies across countries (OECD, 2018[3]).
In order to assess the size of the impact of the discount rate it is helpful to perform a sensitivity analysis. Table A5.1
shows how the private financial returns for a man attaining upper secondary 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 at least 29% in all
countries with available data. If a discount rate of 8% is used, the NPV falls by over 50% in all countries. These
comparisons highlight the sensitivity of the NPV results to changes in the discount rate.

Financial incentives for governments
Governments are major investors in education, especially at non-tertiary levels of 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. Higher levels of educational attainment tend to translate into higher earnings (see Indicator A4),
which in turn generate higher income taxes and social contributions for governments. On average across OECD countries,
the public net financial returns from upper secondary education are about USD 44 600 for a man and USD 13 700 for a
woman. The internal rate of return from upper secondary education to governments is 6% for a man and 3% for a woman
(Table A5.4, and Table A5.5 available on line).
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 the direct public costs of supporting education and
foregone taxes on earnings, while the benefits are calculated using income tax and social contributions (see Definitions
section).
On average across OECD countries, the total public costs for an individual to attain upper secondary education are
USD 38 400 for a man and USD 35 900 for a woman. For governments, direct costs (including student grants) represent the
largest share of total public costs for upper secondary education, even though student loans are not taken into account in this
indicator. On average across the OECD, direct costs account for roughly 90% of total government costs of upper secondary
education for men and women. Since the direct costs are the same for men as for women, the total public costs are quite
similar for men and women. The countries with high direct costs are also the countries with the largest total public costs.
Luxembourg has the highest direct costs (USD 80 200) and total public costs for men (USD 86 700) and for women
(USD 85 900). In contrast, Turkey has the lowest direct costs (USD 11 900) and total public cost for men (USD 13 700) and
women (USD 12 400) of all OECD countries with available data (Table A5.3 and Table A5.4).
Governments offset the costs associated with education through the additional tax revenues and social contributions from
higher-paid workers, who often have greater educational attainment. On average, the total public benefits amount to
USD 83 000 for a man with upper secondary education as his highest attainment. The total can be broken down into income
tax effects (USD 54 600) and social contribution effects (USD 28 400). For a women with upper secondary attainment, the
total public benefits are USD 49 600 on average, composed of income tax effects of USD 29 100 and social contribution
effects of USD 20 500. Across OECD countries, Austria and Denmark gain the largest total public benefits of upper secondary
education for men (over USD 150 000) and Denmark and Germany gain the largest benefits for women (over USD 100 000)
(Table A5.3 and Table A5.4).
In relative terms, the public benefits for each USD invested in upper secondary education are generally much lower than
private ones, as the total costs are greater for governments than for individuals. On average across OECD countries, each
USD that governments invest in upper secondary education generates a public benefit of USD 2.2 for a man, and USD 1.4
for a woman. In Chile, Korea and Luxembourg, the public benefits from investment in upper secondary education do not cover
the total public costs for both men and women. In Estonia, Ireland and New Zealand, the public benefit-cost ratio is below
one for women, but not for men (Figure A5.3). The gender difference is mainly due to the fact that, while the public costs are
similar for men and women, the public benefits for men are greater than for women ( Table A5.3 and Table A5.4). This
suggests that governments have a role to play in improving the integration and participation of women in the labour market.

EDUCATION AT A GLANCE 2020 © OECD 2020

A5. WHAT ARE THE FINANCIAL INCENTIVES TO INVEST IN EDUCATION?  109

Financial incentives to invest in tertiary education
Financial incentives for individuals
As with upper secondary education, adults completing tertiary education benefit from positive financial returns over their
working-age life. On average across OECD countries, the financial returns from tertiary education are about 1.5 times higher
than the returns from upper secondary education for both men and women. In Chile and Luxembourg, the financial returns
from tertiary education are at least five times higher than those from upper secondary education for both men and women.
However, the returns from upper secondary education is higher than from tertiary education in Australia (for men),
the Czech Republic (for women), Denmark (for men and women), Finland (for women), Germany (for women), Norway (for
men), Sweden (for men and women), Switzerland (for women) and the United Kingdom (for men) (Figure A5.1).

Figure A5.4. Private costs and benefits for a man or a woman attaining tertiary education (2017)
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%

Woman

Total costs
Man

Total benefits
Man

Woman

Latvia1
Sweden2
Estonia
Turkey1
Italy2
Belgium
Portugal
Norway
Spain
Korea
Denmark
Slovak Republic
New Zealand
Finland
United Kingdom
Australia2
EU23 average
Czech Republic2
Canada
OECD average
Slovenia
Germany
Israel
France2
Austria
Hungary
Poland 2
Ireland
Switzerland
Chile
United States
Luxembourg1, 2
-800 000
-600 00 0
In equivalent USD
converted using PPPs

-400 000

-200 000

0

0

200 000

400 000

600 000
800 00 0
In equivalent USD
converted using PPPs

1. Only net earnings are available and the calculations are using these values as if they were gross earnings.
2. Year of reference differs from 2017. Refer to the source tables for details.
Countries are ranked in ascending order of the total private benefits for a man.
Source: OECD (2020), Tables A5.5 and A5.6, available on line. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2https://doi.org/10.1787/888934162698
EDUCATION AT A GLANCE 2020 © OECD 2020

110  A5. WHAT ARE THE FINANCIAL INCENTIVES TO INVEST IN EDUCATION?
Although young women are more likely to complete tertiary education than young men (see Indicator A1), women generally
receive lower returns than men from tertiary education. Across OECD countries, the average private financial return from
tertiary education is USD 295 400 for a man and USD 225 400 for a woman. In the Czech Republic and Hungary, the financial
returns for women are only about half of the returns for men. The only countries where women have higher private financial
returns than men are Latvia, Norway, Spain, Sweden and Turkey. Moreover, the gender difference in net financial returns to
education tends to increase with the level of educational attainment (Figure A5.1).
Across OECD countries, the average internal rate of return to tertiary education is 16% for men and 19% for women. The
lower internal rate of return from tertiary education compared to upper secondary education is due to the higher total costs of
attaining tertiary education (Table A5.1, Table A5.2, and Tables A5.5 and A5.6, available on line).
On average across OECD countries, the direct costs of tertiary education amount to USD 9 100 for both men and women,
which is more than three times the direct costs of upper secondary education. The direct costs are particularly high in
the United Kingdom and the United States: tuition fees and living expenses during tertiary education amount to more than
USD 30 000 and exceed foregone earnings, although even in these countries the earnings advantage associated with tertiary
education compensates for the costs. In most OECD countries, however, the main costs of tertiary education are still foregone
earnings. The average foregone earnings for attaining tertiary education are about USD 38 900 for a man and USD 28 500
for a woman (Table A5.1, Table A5.2, and Tables A5.5 and A5.6, available on line). When direct costs and foregone
earnings are combined, Turkey has the lowest total costs for both men and women (USD 12 400 for men and USD 5 800 for
women), while Switzerland has the highest total costs for women (USD 87 100) and the United Kingdom the highest for men
(USD 79 300) across all OECD countries with available data (Figure A5.4).
Further education yields higher gross earnings benefits over an individual’s career. Across OECD countries, the average
gross earnings benefits are USD 543 300 for a tertiary-educated man and USD 388 200 for a tertiary-educated woman
compared with their peers with upper secondary attainment. Countries’ tax and social benefit systems also have an impact
on the benefits of attaining tertiary education. Income taxes and social contributions account for the lowest share of the
benefits in Chile and Korea (less than one-fifth of the gross earnings benefits), while in Belgium and Italy (for men only) they
account for more than half (Tables A5.5 and A5.6, available on line). On average across OECD countries, the total benefits
net of income taxes and social contributions are about USD 343 400 for a tertiary-educated man and USD 263 000 for a
tertiary-educated woman. Norway, Sweden and Turkey are the only OECD countries where women enjoy higher total benefits
from tertiary education than men (Figure A5.4).
In two-thirds of OECD countries, the gender difference in the private financial benefits for each USD invested in tertiary
education is less than USD 2. On average across OECD countries, the private financial benefits for each USD invested in
tertiary education are very close for men and women (around USD 7), although women receive lower private net financial
returns than men from tertiary education. This is due to the fact that, on average, women’s total costs and total benefits
represent a similar proportion of men’s total costs and total benefits, around 77%. (Figure A5.1, Figure A5.4 and Figure A5.5).

Financial incentives for governments
Higher levels of educational attainment also lead to higher returns for the public sector. On average across OECD countries,
the net public return for an individual attaining tertiary education is about USD 137 700 for a man and USD 67 900 for a
woman. The internal rate of return from tertiary education to governments is 8% for a man and 6% for a woman (Tables A5.7
and A5.8, available on line).
Across OECD countries, the average total costs of tertiary education for governments amount to USD 62 200 for a man and
USD 57 300 for a woman. As with upper secondary education, direct costs (including student grants) represent the largest
share of the total public cost of 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 no tuition fees and have access
to generous public subsidies for higher education (see Indicator C5). Countries with high direct public costs (more than
USD 80 000 and up to USD 175 600 for both men and women), such as Denmark, Luxembourg, Norway, Sweden and
Switzerland, also tend to have large total public costs. In contrast, Chile has the lowest total public costs (around USD 16 000)
across all OECD countries with available data (Tables A5.7 and A5.8, available on line).
On average, the total public benefits are USD 199 900 for a tertiary-educated man, broken down into income tax effects
(USD 144 300) and social contribution effects (USD 55 600). For a tertiary-educated women, the total public benefits are
USD 125 200, composed of income tax effects (USD 83 900) and social contribution effects (USD 41 300). Among OECD
countries, Ireland and Luxembourg have the largest total public benefits for tertiary-educated men (over USD 400 000) and

EDUCATION AT A GLANCE 2020 © OECD 2020

A5. WHAT ARE THE FINANCIAL INCENTIVES TO INVEST IN EDUCATION?  111
Belgium and Luxembourg have the largest public benefits for tertiary-educated women (over USD 240 000) (Tables A5.7 and
A5.8, available on line).

Figure A5.5. Financial benefits for each equivalent USD invested in tertiary education, by gender (2017)
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%
Man
In equivalent
USD converted
using PPPs
25

Woman

Private financial benefits for each equivalent USD
invested in tertiary education

33.8

20
15
10
5

United Kingdom

New Zealand

Czech Republic2

Portugal

Australia2

Norway

Belgium

Latvia1

Estonia

Austria

Slovak Republic

Spain

EU23 average

Slovenia

Denmark

Switzerland

Poland2

OECD average

Finland

Sweden2

France2

Hungary

Italy2

United States

Korea

Germany

Canada

Ireland

Luxembourg1, 2

Israel

In equivalent
USD converted
using PPPs
10
9

Turkey1

Chile

0

8
7
6
5
4
3
2
1
0

Public financial benefits for each equivalent USD
invested in tertiary education

Note: Private financial benefits are net of income taxes and social contributions. The financial benefits for each equivalent USD invested in tertiary education are sensitive
to the total costs of education. Readers would need to combine Figure A5.4 and Figure A5.5 to interpret the results. For example, in Spain, the private total benefits from
tertiary education are similar for men and for women (USD 273 400 and USD 271 900), but the private total costs of tertiary education are roughly 1.5 times higher for men
than for women (USD 43 500 compared with USD 30 400) (see Figure A5.4 and Tables A5.5 and A5.6, available on line).
1. Only net earnings are available and the calculations are using these values as if they were gross earnings.
2. Year of reference differs from 2017. Refer to the source tables for details.
Countries are ranked in descending order of the private financial benefits for each equivalent USD invested in tertiary education for a man.
Source: OECD (2020), Tables A5.5, A5.6, A5.7 and A5.8, available on line. See Source section for more information and Annex 3 for notes
(https://doi.org/10.1787/69096873-en).
Statlink2https://doi.org/10.1787/888934162717

In relative terms, the public benefit from each USD invested in tertiary education are generally much lower than the private
benefit, as the total costs are higher for governments than for individuals. On average across OECD countries, each USD
that governments invest in tertiary education generates a public benefit of USD 3.2 for a man, and USD 2.2 for a woman. In
Estonia, Sweden (only for women) and Switzerland (only for women), the total public benefits do not cover the total public
costs of tertiary education. In all countries except Belgium and Latvia, governments receive more benefit from each USD
invested in tertiary education for a man than for a woman (Figure A5.5). The difference by gender is mainly due to the fact
that the public benefits for men are greater than the public benefits for women (Tables A5.7 and A5.8, available on line). As

EDUCATION AT A GLANCE 2020 © OECD 2020

112  A5. WHAT ARE THE FINANCIAL INCENTIVES TO INVEST IN EDUCATION?
with upper secondary education, this suggests that governments have a role to play in improving women’s integration into the
labour market.

Financial incentives by level of tertiary education
The returns for tertiary education are divided into two categories for analysis: short-cycle tertiary attainment and attainment
of a bachelor's, master's and doctoral or equivalent degree. The share of the population with qualifications at each tertiary
level differs across countries (see Indicator A1), and the mix of qualifications can impact the financial returns to education for
tertiary education overall.
For 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 from obtaining a short-cycle tertiary degree. Although the total costs of a bachelor's, master's
or doctoral degree tend to be higher, the total benefits accrued during individuals’ working lives compensate for the higher
initial costs (Tables A5.9 and A5.10, available online). Private financial returns for tertiary education overall would therefore
underestimate the value of investing in bachelor’s, master’s and doctoral degrees, especially in countries with a relatively
large share of adults whose highest level of attainment is short-cycle tertiary (see Indicator A1).

Definitions
Adults refer to 15-64 year-olds.
The benefit-cost ratio is total benefits relative to total costs, representing the financial benefits of attaining an additional level
of education for each USD invested in it.
Direct costs are the direct expenditure on education per student during the time spent in school. Direct costs of education
do 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.

EDUCATION AT A GLANCE 2020 © OECD 2020

A5. WHAT ARE THE FINANCIAL INCENTIVES TO INVEST IN EDUCATION?  113

Methodology
This indicator estimates the financial returns on investment in education from the age of 15 to a theoretical retirement age of
64. The effective retirement age could be slightly above the theoretical retirement age of 64 in some OECD countries (OECD,
2019[4]). Returns to education are studied from the perspective of financial investment.
Two periods are considered (Diagram 1):
time spent in education during which the private individual and the government pay the cost of education
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 A5.1. 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).

Source
The source for the direct costs of education is the UOE data collection on finance (year of reference 2017 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-, gender- and attainment-level specific. For the
calculation of this indicator, data on earnings have been pooled from three different years (2015-17).
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]).
EDUCATION AT A GLANCE 2020 © OECD 2020

114  A5. WHAT ARE THE FINANCIAL INCENTIVES TO INVEST IN EDUCATION?

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 (2019), Pensions at a Glance 2019: OECD and G20 Indicators, OECD Publishing, Paris,
https://dx.doi.org/10.1787/b6d3dcfc-en.

[4]

OECD (2018), Education at a Glance 2018: OECD Indicators, OECD Publishing, Paris,
https://dx.doi.org/10.1787/eag-2018-en.

[3]

OECD (2018), Taxing Wages 2018, OECD Publishing, Paris, https://dx.doi.org/10.1787/tax_wages-2018-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 A5.1

Private costs and benefits for a man attaining upper secondary education (2017)

Table A5.2

Private costs and benefits for a woman attaining upper secondary education (2017)

Table A5.3

Public costs and benefits for a man attaining upper secondary education (2017)

Table A5.4

Public costs and benefits for a woman attaining upper secondary education (2017)

WEB Table A5.5

Private costs and benefits for a man attaining tertiary education (2017)

WEB Table A5.6

Private costs and benefits for a woman attaining tertiary education (2017)

WEB Table A5.7

Public costs and benefits for a man attaining tertiary education (2017)

WEB Table A5.8

Public costs and benefits for a woman attaining tertiary education (2017)

WEB Table A5.9

Private/public costs and benefits for a man attaining tertiary education, by level of tertiary education
(2017)

WEB Table A5.10

Private/public costs and benefits for a woman attaining tertiary education, by level of tertiary education
(2017)

Cut-off date for the data: 19 July 2020. Any updates on data can be found on line at http://dx.doi.org/10.1787/eag-dataen. More breakdowns can also be found at http://stats.oecd.org/, Education at a Glance Database.
StatLink: https://doi.org/10.1787/888934162546

EDUCATION AT A GLANCE 2020 © OECD 2020

A5. WHAT ARE THE FINANCIAL INCENTIVES TO INVEST IN EDUCATION?  115

Table A5.1. Private costs and benefits for a man attaining upper secondary education (2017)
As compared with a man attaining below upper secondary education, in equivalent USD converted using PPPs for GDP; future costs
and benefits are discounted at a rate of 2%

OECD

Earnings benefits decomposition
(taking into account the employment effect)

Direct costs

Foregone
earnings

Total costs

Gross
earni ngs
benefits

Income tax
effect

Social
contribution
effect
Total benefits

Net
financial
returns

(7) =(4) + (5) + (6) (8) = (7) + (3)

Internal
rate of
return

Benefitcost ratio

(9)

(10) =(7)/(3)

(1)

(2)

(3) = (1) + (2)

(4)

(5)

(6)

Countries
Australia 1
Austria
Belgium 2
Canada
Chile
Colombia
Costa Rica
Czech Republic 2 , 3
Denmark
Estonia
Finland 2
France1, 2
Germany
Greece 2
Hungar y 2
Iceland
Ireland 2
Israel 2
Italy 1
Japan
Korea
Latvia 4
Lithuania
Luxembourg 1, 2 , 4
Mexico
Netherlands
New Zealand
Norway
Poland 1, 2
Portugal 2
Slovak Republic 2
Slovenia 2
Spain
Sweden1
Switzerland
Turkey 2, 4
Unite d Kingdom
United States

- 4 300
0
- 1 400
- 1 400
- 2 700
m
m
- 2 500
0
0
0
- 2 900
- 6 600
m
- 5 500
m
0
- 4 500
- 6 400
m
- 8 100
- 1 700
m
- 1 600
m
m
- 6 300
0
- 3 600
- 4 500
- 2 200
0
- 2 400
0
- 500
- 3 400
- 4 200
- 4 200

- 17 400
- 14 500
- 40 100
- 26 900
- 18 900
m
m
- 32 000
- 8 600
- 29 600
- 14 700
- 8 200
- 4 900
m
- 20 900
m
- 9 900
- 28 700
- 16 300
m
- 18 900
- 11 100
m
- 31 500
m
m
- 32 300
- 20 800
- 34 500
- 26 700
- 11 800
- 28 600
- 9 700
- 26 000
- 21 400
- 9 600
- 17 400
- 22 200

- 21 700
- 14 500
- 41 500
- 28 300
- 21 600
m
m
- 34 500
- 8 600
- 29 600
- 14 700
- 11 100
- 11 500
m
- 26 400
m
- 9 900
- 33 200
- 22 700
m
- 27 000
- 12 800
m
- 33 100
m
m
- 38 600
- 20 800
- 38 100
- 31 200
- 14 000
- 28 600
- 12 100
- 26 000
- 21 900
- 13 000
- 21 600
- 26 400

365 500
478 800
359 700
271 000
133 000
m
m
313 500
431 800
200 400
269 600
242 300
369 400
m
187 900
m
413 600
259 600
315 000
m
250 500
111 500
m
156 000
m
m
245 900
450 100
263 600
197 500
297 900
193 300
193 100
368 100
553 100
107 300
359 200
411 100

- 90 900
- 78 800
- 93 800
- 49 000
0
m
m
- 44 400
- 163 400
- 35 300
- 52 000
- 39 300
- 67 100
m
- 28 200
m
- 90 800
- 32 300
- 92 300
m
- 11 800
- 20 900
m
- 25 200
m
m
- 59 400
- 98 700
- 19 900
- 48 100
- 33 700
- 25 600
- 37 000
- 68 400
- 68 800
- 19 200
- 58 300
- 84 300

0
- 88 100
- 55 400
- 20 300
- 9 300
m
m
- 34 500
0
- 3 200
- 25 200
- 34 600
- 76 700
m
- 34 800
m
- 16 700
- 24 500
- 29 900
m
- 21 100
- 11 700
m
- 20 000
m
m
0
- 36 900
- 47 000
- 21 700
- 40 500
- 42 700
- 12 300
- 25 800
- 34 400
- 16 100
- 37 200
- 31 500

274 600
311 900
210 500
201 700
123 700
m
m
234 600
268 400
161 900
192 400
168 400
225 600
m
124 900
m
306 100
202 800
192 800
m
217 600
78 900
m
110 800
m
m
186 500
314 500
196 700
127 700
223 700
125 000
143 800
273 900
449 900
72 000
263 700
295 300

252 900
297 400
169 000
173 400
102 100
m
m
200 100
259 800
132 300
177 700
157 300
214 100
m
98 500
m
296 200
169 600
170 100
m
190 600
66 100
m
77 700
m
m
147 900
293 700
158 600
96 500
209 700
96 400
131 700
247 900
428 000
59 000
242 100
268 900

38%
36%
13%
17%
13%
m
m
18%
51%
20%
41%
32%
42%
m
13%
m
68%
16%
15%
m
17%
23%
m
11%
m
m
14%
32%
15%
9%
31%
17%
15%
29%
54%
10%
21%
27%

12.7
21.5
5.1
7.1
5.7
m
m
6.8
31.2
5.5
13.1
15.2
19.6
m
4.7
m
30.9
6.1
8.5
m
8.1
6.2
m
3.3
m
m
4.8
15.1
5.2
4.1
16.0
4.4
11.9
10.5
20.5
5.5
12.2
11.2

OECD average
EU23 average

- 2 700
- 2 300

- 20 500
- 19 900

- 23 200
- 22 200

292 300
286 100

- 54 600
- 56 100

- 28 400
- 32 900

209 300
197 100

186 100
174 900

25%
26%

9.0
8.9

Note: Values are based on the difference between men who attained an upper secondary education compared with those who have attained a below upper secondary
education. Values have been rounded up to the nearest hundred. Direct costs to education do 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 2016.
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 2015.
4. Only net earnings are available and the calculations are using these values as if they were gross earnings.
Source: OECD (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
Statlink2https://doi.org/10.1787/888934162565

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116  A5. WHAT ARE THE FINANCIAL INCENTIVES TO INVEST IN EDUCATION?
Table A5.2. Private costs and benefits for a woman attaining upper secondary education (2017)
As compared with a woman attaining below upper secondary education, in equivalent USD converted using PPPs for GDP; future costs
and benefits are discounted at a rate of 2%

OECD

Earnings benefits decomposition
(taking into account the employment effect)

Direct costs

Foregone
earnings

Total costs

Gross
earni ngs
benefits

Income tax
effect

Social
contribution
effect
Total benefits

Net
financial
returns

(7) =(4) + (5) + (6) (8) = (7) + (3)

Internal
rate of
return

Benefitcost ratio

(9)

(10) = (7)/(3)

(1)

(2)

(3) = (1) + (2)

(4)

(5)

(6)

Countries
Australia1
Austria
Belgium 2
Canada
Chile
Colombia
Costa Rica
Czech Republic 2 , 3
Denmark
Estonia
Finland 2
France 1, 2
Germany
Greece 2
Hungar y 2
Iceland
Ireland 2
Israel 2
Italy 1
Japan
Korea
Latvia 4
Lithuania
Luxembourg 1, 2 , 4
Mexico
Netherlands
New Zealand
Norway
Poland 1, 2
Portugal 2
Slovak Republic 2
Slovenia 2
Spain
Sweden 1
Switzerland
Turkey 2 , 4
Unite d Kingdom
United States

- 4 300
0
- 1 400
- 1 400
- 2 700
m
m
- 2 500
0
0
0
- 2 900
- 6 600
m
- 5 500
m
0
- 4 500
- 6 400
m
- 8 100
- 1 700
m
- 1 600
m
m
- 6 300
0
- 3 600
- 4 500
- 2 200
0
- 2 400
0
- 500
- 3 400
- 4 200
- 4 200

- 12 800
- 9 700
- 21 200
- 15 300
- 6 800
m
m
- 12 700
- 4 100
- 15 600
- 6 600
- 5 500
- 1 700
m
- 11 900
m
- 6 300
- 6 400
- 6 600
m
- 10 200
- 4 100
m
- 33 500
m
m
- 14 900
- 16 400
- 12 900
- 22 200
- 5 700
- 26 400
- 6 400
- 6 700
- 16 100
- 2 600
- 15 500
- 9 100

- 17 100
- 9 700
- 22 600
- 16 700
- 9 500
m
m
- 15 200
- 4 100
- 15 600
- 6 600
- 8 400
- 8 300
m
- 17 400
m
- 6 300
- 10 900
- 13 000
m
- 18 300
- 5 800
m
- 35 100
m
m
- 21 200
- 16 400
- 16 500
- 26 700
- 7 900
- 26 400
- 8 800
- 6 700
- 16 600
- 6 000
- 19 700
- 13 300

225 100
284 500
290 200
214 200
79 600
m
m
208 200
405 100
122 400
269 000
228 400
319 600
m
143 000
m
240 500
256 700
237 800
m
84 800
84 700
m
98 500
m
m
164 900
315 400
187 000
152 900
170 800
216 100
141 000
307 100
406 800
52 200
212 700
308 00 0

- 34 100
- 21 100
- 54 300
- 28 200
0
m
m
- 25 700
- 143 100
- 19 900
- 33 000
- 20 000
- 38 800
m
- 21 500
m
- 20 200
- 12 100
- 39 700
m
- 1 100
- 13 500
m
- 9 200
m
m
- 25 300
- 57 500
- 13 100
- 26 100
- 14 900
- 25 400
- 14 700
- 49 700
- 33 000
- 4 800
- 23 400
- 50 900

0
- 51 900
- 40 200
- 15 200
- 5 600
m
m
- 22 900
0
- 2 000
- 25 100
- 32 700
- 66 600
m
- 26 500
m
- 9 200
- 14 200
- 22 600
m
- 7 100
- 8 900
m
- 12 500
m
m
0
- 25 900
- 33 300
- 16 800
- 24 400
- 47 800
- 9 000
- 21 500
- 25 300
- 7 800
- 16 400
- 23 600

191 000
211 500
195 700
170 800
74 000
m
m
159 600
262 000
100 500
210 900
175 700
214 200
m
95 000
m
211 100
230 400
175 500
m
76 600
62 300
m
76 800
m
m
139 600
232 000
140 600
110 000
131 500
142 900
117 300
235 900
348 500
39 600
172 900
233 500

173 900
201 800
173 100
154 100
64 500
m
m
144 400
257 900
84 900
204 300
167 300
205 900
m
77 600
m
204 800
219 500
162 500
m
58 300
56 500
m
41 700
m
m
118 400
215 600
124 100
83 300
123 600
116 500
108 500
229 200
331 900
33 600
153 200
220 200

43%
40%
18%
22%
17%
m
m
24%
71%
23%
63%
34%
49%
m
14%
m
80%
38%
19%
m
17%
36%
m
7%
m
m
21%
29%
21%
10%
29%
16%
16%
67%
56%
17%
19%
36%

11.2
21.8
8.7
10.2
7.8
m
m
10.5
63.9
6.4
32.0
20.9
25.8
m
5.5
m
33.5
21.1
13.5
m
4.2
10.7
m
2.2
m
m
6.6
14.1
8.5
4.1
16.6
5.4
13.3
35.2
21.0
6.6
8.8
17.6

OECD average
EU23 average

- 2 700
- 2 300

- 11 500
- 11 800

- 14 200
- 14 100

214 200
216 000

- 29 100
- 31 400

- 20 500
- 24 500

164 600
160 100

150 400
146 000

32%
33%

11.6
11.4

Note: Values are based on the difference between men who attained an upper secondary education compared with those who have attained a below upper secondary
education. Values have been rounded up to the nearest hundred. Direct costs to education do 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 2016.
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 2015.
4. Only net earnings are available and the calculations are using these values as if they were gross earnings.
Source: OECD (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
Statlink2https://doi.org/10.1787/888934162584

EDUCATION AT A GLANCE 2020 © OECD 2020

A5. WHAT ARE THE FINANCIAL INCENTIVES TO INVEST IN EDUCATION?  117

OECD

Table A5.3. Public costs and benefits for a man attaining upper secondary education (2017)
As compared with a man attaining below upper secondary education, in equivalent USD converted using PPPs for GDP; future costs
and benefits are discounted at a rate of 2%
Earnings benefits decomposition
(taking into account the employment effect)

Direct costs
(1)

Foregone
taxes on
earnings
(2)

Total costs
(3) = (1) + (2)

Income tax effect
(4)

Social
contribution effect
(5)

Total
benefits
(6) =(4) + (5)

Net financial
returns
(7) = (6) + (3)

Internal
rate of
return
(8)

Benefitcost ratio
(9) = (6)/(3)

Countries
Australia 1
Austria
Belgium 2
Canada
Chile
Colombia
Costa Rica
Czech Republic 2 , 3
Denmark
Estonia
Finland 2
France 1, 2
Germany
Greece 2
Hungar y 2
Iceland
Ireland 2
Israel 2
Italy 1
Japan
Korea
Latvia 4
Lithuania
Luxembourg 1, 2 , 4
Mexico
Netherlands
New Zealand
Nor way
Poland 1, 2
Portugal 2
Slovak Republic 2
Slovenia 2
Spain
Sweden 1
Switzerland
Turkey 2 , 4
Unite d Kingdom
United States

- 16 100
- 63 700
- 56 400
- 36 400
- 16 100
m
m
- 29 200
- 51 800
- 20 600
- 25 000
- 38 300
- 39 700
m
- 27 800
m
- 30 000
- 21 800
- 35 300
m
- 32 600
- 21 100
m
- 80 200
m
m
- 27 600
- 52 100
- 25 100
- 26 300
- 28 100
- 31 600
- 19 300
- 38 700
- 45 200
- 11 900
- 22 800
- 39 700

- 2 600
- 2 500
- 12 000
- 7 000
- 1 400
m
m
- 9 300
- 6 100
- 6 200
- 2 100
- 2 300
- 2 400
m
- 10 500
m
0
- 1 200
- 1 700
m
- 1 700
- 3 800
m
- 6 500
m
m
- 5 100
- 5 000
- 11 300
- 6 400
- 2 500
- 13 200
- 700
- 5 400
- 3 600
- 1 800
- 1 00 0
- 5 400

- 18 700
- 66 200
- 68 400
- 43 400
- 17 500
m
m
- 38 500
- 57 900
- 26 800
- 27 100
- 40 600
- 42 100
m
- 38 300
m
- 30 000
- 23 000
- 37 000
m
- 34 300
- 24 900
m
- 86 700
m
m
- 32 700
- 57 100
- 36 400
- 32 700
- 30 600
- 44 800
- 20 000
- 44 100
- 48 800
- 13 700
- 23 800
- 45 100

90 900
78 800
93 800
49 000
0
m
m
44 400
163 400
35 300
52 000
39 300
67 100
m
28 200
m
90 800
32 300
92 300
m
11 800
20 900
m
25 200
m
m
59 400
98 700
19 900
48 100
33 700
25 600
37 000
68 400
68 800
19 200
58 300
84 300

0
88 100
55 400
20 300
9 300
m
m
34 500
0
3 200
25 200
34 600
76 700
m
34 800
m
16 700
24 500
29 900
m
21 100
11 700
m
20 000
m
m
0
36 900
47 000
21 700
40 500
42 700
12 300
25 800
34 400
16 100
37 200
31 500

90 900
166 900
149 200
69 300
9 300
m
m
78 900
163 400
38 500
77 200
73 900
143 800
m
63 000
m
107 500
56 800
122 200
m
32 900
32 600
m
45 200
m
m
59 400
135 600
66 900
69 800
74 200
68 300
49 300
94 200
103 200
35 300
95 500
115 800

72 200
100 700
80 800
25 900
- 8 200
m
m
40 400
105 500
11 700
50 100
33 300
101 700
m
24 700
m
77 500
33 800
85 200
m
- 1 400
7 700
m
- 41 500
m
m
26 700
78 500
30 500
37 100
43 600
23 500
29 300
50 100
54 400
21 600
71 700
70 700

13%
7%
6%
4%
0%
m
m
6%
8%
4%
9%
5%
9%
m
5%
m
9%
6%
7%
m
2%
4%
m
-1%
m
m
5%
7%
6%
5%
7%
5%
6%
6%
6%
6%
9%
7%

4.9
2.5
2.2
1.6
0.5
m
m
2.0
2.8
1.4
2.8
1.8
3.4
m
1.6
m
3.6
2.5
3.3
m
1.0
1.3
m
0.5
m
m
1.8
2.4
1.8
2.1
2.4
1.5
2.5
2.1
2.1
2.6
4.0
2.6

OECD average
EU23 average

- 33 700
- 35 600

- 4 700
- 5 300

- 38 400
- 40 900

54 600
56 100

28 400
32 900

83 000
89 000

44 600
48 100

6%
6%

2.2
2.2

Note: Values are based on the difference between men who attained an upper secondary education compared with those who have attained a below upper secondary
education. Values have been rounded up to the nearest hundred. Direct costs to education do 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 2016.
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 2015.
4. Only net earnings are available and the calculations are using these values as if they were gross earnings.
Source: OECD (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
Statlink2https://doi.org/10.1787/888934162603

EDUCATION AT A GLANCE 2020 © OECD 2020

118  A5. WHAT ARE THE FINANCIAL INCENTIVES TO INVEST IN EDUCATION?

OECD

Table A5.4. Public costs and benefits for a woman attaining upper secondary education (2017)
As compared with a woman attaining below upper secondary education, in equivalent USD converted using PPPs for GDP; future costs
and benefits are discounted at a rate of 2%
Earnings benefits decomposition
(taking into account the employment effect)

Direct costs

Foregone
taxes on
earnings

Total costs

Income tax effect

Social
contribution effect

Total
benefits

Net financial
returns

Internal
rate of
return

Benefitcost ratio

(1)

(2)

(3) = (1) + (2)

(4)

(5)

(6) = (4) +(5)

(7) =(6) + (3)

(8)

(9) = (6)/(3)

Countries
Australia 1
Austria
Belgium 2
Canada
Chile
Colombia
Costa Rica
Czech Republic 2 , 3
Denmark
Estonia
Finland 2
France 1,2
Germany
Greece 2
Hungar y 2
Iceland
Ireland 2
Israel 2
Italy 1
Japan
Korea
Latvia 4
Lithuania
Luxembourg 1, 2, 4
Mexico
Netherlands
New Zealand
Norway
Poland 1, 2
Portugal 2
Slovak Republic 2
Slovenia 2
Spain
Sweden1
Switzerland
Turkey 2,4
Unite d Kingdom
United States

- 16 100
- 63 700
- 56 400
- 36 400
- 16 100
m
m
- 29 200
- 51 800
- 20 600
- 25 000
- 38 300
- 39 700
m
- 27 800
m
- 30 000
- 21 800
- 35 300
m
- 32 600
- 21 100
m
- 80 200
m
m
- 27 600
- 52 100
- 25 100
- 26 300
- 28 100
- 31 600
- 19 300
- 38 700
- 45 200
- 11 900
- 22 800
- 39 700

- 1 400
- 3 100
- 2 900
- 2 000
- 500
m
m
- 3 200
- 2 000
- 2 900
- 800
- 1 600
- 1 200
m
- 6 000
m
- 100
- 200
- 700
m
- 900
- 1 200
m
- 5 700
m
m
- 2 000
- 3 600
- 4 100
- 2 700
- 1 100
- 11 900
- 400
- 600
- 1 900
- 500
- 300
- 1 600

- 17 500
- 66 800
- 59 300
- 38 400
- 16 600
m
m
- 32 400
- 53 800
- 23 500
- 25 800
- 39 900
- 40 900
m
- 33 800
m
- 30 100
- 22 000
- 36 000
m
- 33 500
- 22 300
m
- 85 900
m
m
- 29 600
- 55 700
- 29 200
- 29 000
- 29 200
- 43 500
- 19 700
- 39 300
- 47 100
- 12 400
- 23 100
- 41 300

34 100
21 100
54 300
28 200
0
m
m
25 700
143 100
19 900
33 000
20 000
38 800
m
21 500
m
20 200
12 100
39 700
m
1 100
13 500
m
9 200
m
m
25 300
57 500
13 100
26 100
14 900
25 400
14 700
49 700
33 000
4 800
23 400
50 900

0
51 900
40 200
15 200
5 600
m
m
22 900
0
2 000
25 100
32 700
66 600
m
26 500
m
9 200
14 200
22 600
m
7 100
8 900
m
12 500
m
m
0
25 900
33 300
16 800
24 400
47 800
9 000
21 500
25 300
7 800
16 400
23 600

34 100
73 000
94 500
43 400
5 600
m
m
48 600
143 100
21 900
58 100
52 700
105 400
m
48 000
m
29 400
26 300
62 300
m
8 200
22 400
m
21 700
m
m
25 300
83 400
46 400
42 900
39 300
73 200
23 700
71 200
58 300
12 600
39 800
74 500

16 600
6 200
35 200
5 000
- 11 000
m
m
16 200
89 300
- 1 600
32 300
12 800
64 500
m
14 200
m
- 700
4 300
26 300
m
- 25 300
100
m
- 64 200
m
m
- 4 300
27 700
17 200
13 900
10 100
29 700
4 000
31 900
11 200
200
16 700
33 200

6%
2%
4%
3%
-2%
m
m
4%
7%
2%
7%
3%
7%
m
4%
m
2%
3%
4%
m
-4%
2%
m
-3%
m
m
1%
4%
4%
3%
3%
5%
3%
5%
3%
2%
4%
5%

1.9
1.1
1.6
1.1
0.3
m
m
1.5
2.7
0.9
2.3
1.3
2.6
m
1.4
m
1.0
1.2
1.7
m
0.2
1.0
m
0.3
m
m
0.9
1.5
1.6
1.5
1.3
1.7
1.2
1.8
1.2
1.0
1.7
1.8

OECD average
EU23 average

- 33 700
- 35 600

- 2 200
- 2 600

- 35 900
- 38 200

29 100
31 400

20 500
24 500

49 600
55 900

13 700
17 700

3%
4%

1.4
1.5

Note: Values are based on the difference between men who attained an upper secondary education compared with those who have attained a below upper secondary
education. Values have been rounded up to the nearest hundred. Direct costs to education do 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 2016.
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 2015.
4. Only net earnings are available and the calculations are using these values as if they were gross earnings.
Source: OECD (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
Statlink2https://doi.org/10.1787/888934162622

EDUCATION AT A GLANCE 2020 © OECD 2020

120  A6. HOW ARE SOCIAL OUTCOMES RELATED TO EDUCATION?

Indicator A6. How are social outcomes
related to education?
Highlights






A larger share of children from low-educated families report being bullied. On average across OECD countries,
26% of 15-year-old students whose parents did not complete upper secondary education report experiencing at
least one form of bullying, compared to 22% of students who have at least one parent with upper secondary or
post-secondary non-tertiary education, and 23% of students who have at least one tertiary-educated parent.
Verbal bullying tends to be more common than physical forms of bullying. For example, across OECD countries,
15% of 15-year-old students whose parents did not complete upper secondary education report that other
students made fun of them at least a few times a month, compared to 10% who report being hit or pushed around.
Students with more highly educated parents are also more likely to agree with statements about bullying
prevention. This trend is more pronounced than for exposure to bullying; on average across OECD countries the
differences are statistically significant between the three aggregated levels of parents’ educational attainment.

Figure A6.1. Exposure and attitudes related to bullying, by parents' educational attainment (2018)
Programme for International Student Assessment (PISA), OECD average
Below upper secondary
Upper secondary or post-secondary non-tertiary
Tertiary
%
30

Percentage of 15-year-old students who reported being
exposed to different forms of bullying at least a few times a month

Percentage of 15-year-old students who agreed
or strongly agreed with statements about bullying

%
95

25

90

20

85

15

80

10

75

5

70

0

Any
type of
bullying
act

Other
students
made fun
of me

Other
Other
I got hit or
Other
I was
students
students
pushed
students thre atened
spre ad
left me out around
took away by other
nasty
of things
by other or destroyed students
rumours on purpose students
things
about me
that belonged
to me

It irr itates
I feel bad
me when seeing other
nobody
students
defends
bullied
bullied
students

It is
a wrong
thing
to join in
bullying

It is
I like it
a good
when
thing
someone
to help
stands up
students
for other
who can’t students who
defend
are being
themselves
bullied

65

Note: All differences are statistically significant, except for those between upper secondary or post-secondary non-tertiary and tertiary education for all items on
exposure to bullying (left panel).
Left panel: Items are ranked in descending order of the percentage of 15-year-old students whose parents have not completed upper secondary education. Right panel:
Items are ranked in ascending order of the percentage of 15-year-old students whose parents have not completed upper secondary education.
Source: OECD (2020), Tables A6.1 and A6.2. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2https://doi.org/10.1787/888934162831

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A6. HOW ARE SOCIAL OUTCOMES RELATED TO EDUCATION?  121

Context
Personal safety is a core element of well-being and an important indicator of good governance in societies (OECD, 2011[1];
OECD, 2017[2]). Feelings of insecurity have a variety of negative effects and tend to limit people’s daily activities. For
example, a safe and supportive learning environment maximises educational attendance and the effectiveness of learning
time. When students feel safe at school, they tend to have better educational outcomes. In contrast, an environment
characterised by disrespect, bullying, victimisation or violence can act as a barrier to learning. Bullying at school can have
long-lasting negative consequences for students’ psychological well-being and increases the likelihood of dropping out of
school (Burns and Gottschalk, 2019[3]; OECD, 2017[4]). Students at schools without supportive norms, structures and
relationships are more likely to experience violence and victimisation which is often associated with reduced academic
achievement (Astor, Guerra and Van Acker, 2010[5]).
The promotion of social cohesion, often reflected in levels of civic and social engagement, is another policy priority in
OECD countries. Civic participation helps maintaining and improving our societies. People are more likely to be politically
engaged when they feel they can make a difference in how their country is run and when they understand the political
issues facing their country (OECD, 2013[6]). Education can play an important role in ensuring social cohesion by fostering
the social and emotional skills that can contribute to enhancing civic engagement.

Other findings


Data by country show some geographical patterns in exposure to bullying. In the four PISA-participating
provinces/municipalities of the People’s Republic of China: Beijing, Shanghai, Jiangsu and Zhejiang (hereinafter
referred as China), Japan and Korea, only 7% or less of 15-year-old students reported that other students had
spread nasty rumours about them at least a few times a month, regardless of parents’ educational attainment. In
contrast, in the Czech Republic, Hungary, Latvia and the Slovak Republic, at least 19% of students whose parents
did not complete upper secondary education reported suffering from this type of bullying.



Students who expect to leave school before completing an upper secondary education are twice as likely on
average across OECD countries to report that other students spread nasty rumours about them (20%) as those
who expect to complete tertiary education (10%).



Data from the European Social Survey (ESS) and the International Social Survey Programme (ISSP) show that
political efficacy and interest in politics increases with educational attainment. For example, on average across
OECD countries that participated in ESS, 26% of 25-64 year-olds who did not complete upper secondary
education feel that their political system allows people like them to have some say in what the government does.
This share increases to 35% among those who completed upper secondary or post-secondary non-tertiary
education, and to 52% among tertiary-educated adults.



On average across OECD countries participating in the ESS, 57% of tertiary-educated adults report being quite
or very interested in politics. This share falls to 40% among those who completed upper secondary or postsecondary non-tertiary education, and to 30% among those who did not complete upper secondary education.

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 be interpreted with caution.

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122  A6. HOW ARE SOCIAL OUTCOMES RELATED TO EDUCATION?

Analysis
Bullying and educational attainment
Societies are increasingly concerned by the effects and the extent of bullying (Nansel et al., 2004[7]; Rigby, 2007[8]; National
Academies of Sciences, Engineering, and Medicine, 2016[9]). The potential effect of bullying on psychological well-being and
school dropout rates is well documented, but less is known about how people become bullies or the bullied. Traditionally
bullying occurs at school, implying that bullied students can escape mistreatment when they leave the school premises. But
with the development of technology, cyberbullying is now reaching beyond the school gate (Burns and Gottschalk, 2019[3]).
Through instant messaging, social media and other forms of digital communication bullies can now reach their victim anytime,
anywhere (National Academies of Sciences, Engineering, and Medicine, 2016 [9]). Data from the Programme for International
Student Assessment (PISA) do not yet distinguish cyberbullying from traditional bullying, but research show that girls tend to
be more involved in this type of bullying than boys, both as victims and perpetrators (OECD, 2019[10]).
PISA data show that low performers, especially boys, and students whose parents are less educated (often the same
students), tend to report greater exposure to bullying (OECD, 2017[4]). Tippett and Wolke (2014[11]) found that low socioeconomic status is associated with a greater likelihood of being involved in bullying, either as a bully or a victim. Parents’
educational attainment is one of the most important predictors of school performance and educational attainment (OECD,
2016[12]; Dubow, Boxer and Huesmann, 2009[13]). It is also a good proxy for socio-economic status. It is therefore interesting
to study the association between parents’ educational attainment and exposure to bullying to see if the virtuous circle of high
educational attainment is also associated with lower exposure to bullying. In other words, do students whose parents are
highly educated suffer less from bullying than those coming from a low-educated family?

Exposure to bullying, by parents’ educational attainment
The data also show that the share of 15-year-old students who reported being exposed to different forms of bullying is highest
among those whose parents did not complete upper secondary education. Students with at least one parent who completed
at least upper secondary education are less likely to report being victimised. Surprisingly, the difference in exposure to bullying
is not statistically significant when comparing students with parents who completed upper secondary or post-secondary nontertiary education and those with at least one tertiary-educated parent. This means that, on average across OECD countries,
there is no extra advantage to a tertiary education over an upper secondary one in this area (Figure A6.1, left panel).
The OECD average hides important variations across countries. Figure A6.2 shows that in about half of countries, there is no
statistically significant difference by parents’ educational attainment in the percentage of 15-year-old students who report
being bullied at least a few times a month. In Brazil, Indonesia, Mexico, the Russian Federation and Saudi Arabia, it is actually
students from tertiary-educated families who are more likely to report being bullied. Across OECD and partner countries, the
largest differences by parents’ educational attainment are observed in Canada, Hungary, Norway and the Slovak Republic
where the share of students from tertiary-educated families reporting experiencing any type of bullying is at least
10 percentage points lower than the share of students whose parents did not complete upper secondary education
(Figure A6.2).
A pattern emerges when analysing the different forms that bullying may take. Data from PISA 2018 show that, on average
across OECD countries, students were more likely to report experiencing verbal forms of bullying than physical forms. For
example, 15% of 15 year-old students whose parents did not complete upper secondary education reported that other
students made fun of them at least a few times a month. The share drops to 10% when they were asked about being hit or
pushed around. When reports of all forms of bullying are combined, 26% of these students reported experiencing some form
of bullying at least a few times a month (Figure A6.1, left panel).
Figure A6.1 (left panel) shows that the widest gap by parents’ educational attainment relates to being the subject of nasty
rumours. Data by country show similar pattern in some Asian countries in the likelihood of being exposed to this form of
bullying. In China, Japan and Korea, 7% or less of 15-year-old students reported that other students spread nasty rumours
about them at least a few times a month, regardless of their parents’ educational attainment. This implies that this form of
bullying is not common in these Asian countries. In contrast, in some Baltic and East European countries such as
the Czech Republic, Hungary, Latvia and the Slovak Republic, at least 19% of students whose parents did not complete upper
secondary education reported suffering from the spread of nasty rumours about them. This implies that in these countries,

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A6. HOW ARE SOCIAL OUTCOMES RELATED TO EDUCATION?  123
students from low-educated families are more likely to report that other students are spreading nasty rumours about them
(Figure A6.1 and Table A6.1).

Figure A6.2. Percentage of 15-year-old students who reported being exposed to any type of bullying at
least a few times a month, by parents' educational attainment (2018)
Programme for International Student Assessment (PISA)
Below upper secondary
Upper secondary or post-secondary non-tertiary
Tertiary

%
50
45
40
35
30
25
20
15
10
0

Slovak Republic
Indonesia
Canada
Australia
Hungary
Russian Federation
Latvia
Czech Republic
Argentina
New Zealand
Colombi a
Poland
Lithuania
Greece
Estonia
Norway
Austria
United Kingdom
Saudi Arabia
France
Switzerland
Brazil
EU23 average
OECD average
Italy
Germany
Denmark
Turkey
Ireland
United States
Chile
Costa Rica
Mexico
Luxembourg
Iceland
Japan
Belgium
Netherlands
Spain
Slovenia
Sweden
B-S-J-Z (China)
Finland
Portugal
Korea

5

Note: The blue zones denote cases where the differences between any parents' educational attainment levels are not statistically significant. B-S-J-Z (China) refers to the
four PISA-participating provinces/municipalities of the People’s Republic of China: Beijing, Shanghai, Jiangsu and Zhejiang.
Countries are ranked in descending order of the percentage of 15-year-old students who report being exposed to any type of bullying act at least a few times a month and
whose parents have not completed upper secondary education.
Source: OECD (2020), Table A6.1. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2https://doi.org/10.1787/888934162850

Exposure to bullying, by expectations of educational attainment
Differences in reported exposure to bullying are statistically significant in a larger number of countries when considering
students’ own expectations of educational attainment rather than their parents’ attainment. This implies that exposure to
bullying is not only higher for students from low-educated families, but it also associated with lower educational aspirations at
the age of 15 (Table A6.1 and Table A6.4, available on line).
On average across OECD countries, only 3% of 15-year-old students do not expect to complete upper secondary education,
but this group is twice as likely to report that other students spread nasty rumours about them (20%) than those who expect
to complete tertiary education (10%). In Greece, Hungary and Norway, they are over three times more likely to suffer from
this type of bullying. In contrast, in China, Japan, Korea and the Netherlands, less than 10% of students reported being
targeted by the spread nasty rumours, regardless of their educational expectations (Table A6.4, available on line).

Attitudes towards bullying, by parents’ educational attainment
In 2018, PISA included five new questions on attitudes towards bullying in its background questionnaire (Figure A6.1, right
panel). These five questions allow the survey to capture 15-year-olds’ attitudes towards bullying and weigh their opinions
about actions to protect the bullied or discourage bullying. On average across OECD countries, higher parental educational
attainment is associated with a higher likelihood of students agreeing or strongly agreeing with statements about bullying
prevention. This is true for all five questions on attitudes towards bullying and the differences are statistically significant
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124  A6. HOW ARE SOCIAL OUTCOMES RELATED TO EDUCATION?
between each level of parental educational attainment: below upper secondary education, upper secondary or post-secondary
non-tertiary education and tertiary education. The question that gives rise to the largest gaps asks students if they agree that
it is a wrong thing to join in bullying. On average, 82% of 15-year-old students whose parents had below upper secondary
attainment agreed or strongly agreed with this statement. The share reaches 89% among students with at least one tertiaryeducated parent. Among other factors, the higher social desirability among students from highly educated families could partly
explain why the differences in attitudes towards bullying by parents’ educational attainment are higher than the differences in
exposure to bullying. (Figure A6.1, right panel).

Figure A6.3. Percentage of 15-year-old students who think that it is wrong to join in bullying, by parents'
educational attainment (2018)
Programme for International Student Assessment (PISA)

%
100

Tertiary
Upper secondary or post-secondary non-tertiary
Below upper secondary

95
90
85
80
75
70
65
60
50

B-S-J-Z (China)
United Kingdom
Netherlands
Belgium
Denmark
Ireland
Korea
United States
Norway
Japan
France
New Zealand
Finland
Canada
Australia
Sweden
Germany
Spain
Czech Republic
Iceland
Estonia
Luxembourg
EU23 average
OECD average
Costa Rica
Chile
Austria
Portugal
Switzerland
Slovenia
Greece
Israel
Italy
Brazil
Mexico
Russian Federation
Poland
Latvia
Argentina
Lithuania
Turkey
Slovak Republic
Hungary
Saudi Arabia
Colombi a
Indonesia

55

Note: The blue zones denote cases where the differences between any parents' educational attainment levels are not statistically significant. B-S-J-Z (China) refers to the
four PISA-participating provinces/municipalities of the People’s Republic of China: Beijing, Shanghai, Jiangsu and Zhejiang.
Countries are ranked in descending order of the percentage of 15-year-old students who agreed or strongly agreed that it is a wrong thing to join in bullying and whose
parents' highest attainment is tertiary education.
Source: OECD (2020), Table A6.2. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2https://doi.org/10.1787/888934162869

At the country level, the attitude of 15-year-old students towards this specific question on bullying shows a similar association
with parents’ educational attainment. Figure A6.3 shows that in 3 out of 4 countries, there is a statistically significant difference
in the percentage of 15-year-old students who agreed or strongly agreed that it is a wrong thing to join in bullying by parents’
educational attainment (Figure A6.3).
Generally, the countries with smaller gaps on this measure also have a high share of students who agreed or strongly agreed
that it is a wrong thing to join in bullying. For example, in Belgium, China, Denmark, Finland, Ireland, the Netherlands,
the United Kingdom and the United States, at least 90% of students agreed or strongly agreed that it is a wrong thing to join
in bullying, regardless of their parents’ educational attainment. In contrast, in Israel, Latvia, Lithuania, the Russian Federation
and the Slovak Republic, the share of students who agreed or strongly agreed is 85% or less, and the gap by parents’
educational attainment is over 10 percentage points. Despite what the list of countries may suggest, there is no strong
relationship between the gap in attitudes by parents’ educational attainment and PISA performance. For example, the gap is
similar in both Indonesia and Sweden but students perform much better in Sweden (OECD, 2019[14]) (Figure A6.3).

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A6. HOW ARE SOCIAL OUTCOMES RELATED TO EDUCATION?  125

Attitude towards bullying, by expectations of educational attainment
On average across OECD countries, 90% of 15-year-old students who expect to attain tertiary education agreed or strongly
agreed that it is a wrong thing to join in bullying. This falls to 83% among students who expect to complete upper secondary
or post-secondary non-tertiary education, and 73% of those who do not even think they will complete upper secondary
education. As with exposure to bullying, differences in attitudes towards preventing bullying are greater when the analysis
focuses on students’ educational expectations rather than their parents’ attainment: the difference between those who expect
to attain a below upper secondary and a tertiary education is 17 percentage points, 10 percentage points more than the gap
relating to parents’ educational attainment (Table A6.2 and Table A6.5, available on line).
In the Czech Republic, Lithuania, Norway and the Slovak Republic, the share of students who agreed or strongly agreed that
it is a wrong thing to join in bullying is over 25 percentage points more among those who expect to complete tertiary education
than among those who do not expect to complete upper secondary education. The largest gap is observed in
the Czech Republic where 91% of students who expect to complete tertiary education agreed or strongly agreed with this
statement, but only 57% of students who do not expect to complete upper secondary education. In contrast, the smallest gap
was in Belgium where 91-95% of students agreed or strongly agreed, regardless of their educational attainment expectations
(Table A6.5, available on line).

Box A6.1. Cyberbullying during the COVID-19 lockdown
During the lockdown, Internet use has increased by 50% in some parts of the world (World Economic Forum, 2020[15]).
Children and students are massively turning on line to study, socialise and play. According to the latest PISA survey, on
average, 9 out of 10 students have computers at home for homework and are connected to the Internet. While online
material represents great learning opportunities, the virtual world also represents threats for children and teenagers.
Cyberbullying, online sexual exploitation and harmful content are examples of the potential risks related to Internet use
(UNICEF, 2020[16]). This can particularly be the case if security measures are not implemented for distance learning.
According to the latest PISA survey, only 35% of schools had an effective platform to support online learning. With the
increase in time spent on line, countries are also observing increases of online hacking and abuse. For example, since
December 2019, the AI-based start-up L1ght recorded a 70% increase in hate speech among children and teenagers
during online chats (L1ght, 2020[17]).
The OECD publication How’s Life in the Digital Age? (OECD, 2019[10]) evaluates the opportunities and risks associated
with digital technologies across 11 key dimensions of well-being, including personal security and civic engagement and
governance. Data collected prior to the outbreak show that on average across OECD countries, 9% of 15-year-olds
reported experiencing cyberbullying at least once in their life, with a larger share of girls than boys reporting being
victimised. With the rise of cyberbullying during the confinement period, these numbers are likely to underestimate the
share of children who will suffer from this type of harassment in 2020.
While the Internet may help people overcome loneliness and social exclusion, cyberbullying and online harassment can
negatively affect children’s social experiences. Parents therefore have an important role to play in providing the skills and
information their children need to navigate the online world safely. Setting appropriate parental controls and maintaining
an open dialogue with their children can help parents prevent online harm. But parents themselves need to be aware of
the risks and have sufficient digital skills to guide their children. The digital generation divide is likely to be smaller for
families with highly educated parents.
Some countries have developed policies and guides around cyberbullying. For example, Saskatchewan (Canada)
developed a policy guide for school division officials to work with school administrators and teachers to help students build
an understanding of safe and appropriate online behaviour (Government of Saskatchewan, 2019[18]; OECD, 2019[19]).
France developed a bullying prevention programme aiming at increasing awareness and addressing this issue in schools.
Its 2018-19 programme focused on the prevention of cyberbullying and sexting (Ministère de l'éducation nationale et de
la jeunesse, 2020[20]). Another example is Chile where the Ministry of Education developed orientations for schools to
regulate the safe use of mobile devices in the school, as well to engage with parents and guardians in promoting
responsible use. On 14 March 2019, schools organised workshops and documentary screenings to increase awareness
for the National Day Against Cyberbullying (Ministry of Education - Chile, 2019[21])

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126  A6. HOW ARE SOCIAL OUTCOMES RELATED TO EDUCATION?
Political efficacy and interest in politics, by educational attainment
Political efficacy refers to people’s feeling that their political views can affect the political process and, therefore, that it is
worthwhile for them to perform their civic duties (Acock, Clarke and Stewart, 1985[22]). Political efficacy is related to different
elements of citizens’ lives. For example, diverse media, the ability to create petitions, the right to protest and fair elections all
contribute to increased political efficacy. In contrast, political efficacy will be low when citizens feel powerless in their own
country. Personal characteristics, socio-economic background and people’s experiences with their political institutions
therefore also influence political efficacy (Miller and Listhaug, 1990[23]; OECD, 2017[2]).
Political efficacy is closely related to interest in politics. People with a high level of political efficacy are likely to report being
interested in politics. Overall interest in politics is an important factor for social cohesion as it influences behaviour such as
voting and other civic engagement. Personal characteristics are also related to interest in politics; for example younger adults
generally report a lower level of interest. It is however a policy priority that most citizens feel concerned about politics and
actively take part in the political life of society (OECD, 2016[24]).
The European Social Survey (ESS) and the International Social Survey Programme (ISSP) ask respondents about their
general interest in politics and if they think that their government allows people like them to have a say in what the government
does. Combining these questions with information about educational attainment provides information on how political efficacy
and interest in politics vary according to education levels. As for PISA question on attitude towards bullying, it is possible that
social desirability influences the answers to these questions. For countries having participated in ISSP and ESS, only data
from one of the two sources is kept. Generally the source with the better data on educational attainment is selected.

Figure A6.4. Percentage of adults who feel they have a say in what the government does, by educational
attainment (2016 or 2018)
European Social Survey (ESS-2018) and International Social Survey Programme (ISSP-2016), 25-64 year-olds
Tertiary
Upper secondary or post-secondary non-tertiary
Below upper secondary
%
100

European Social Survey (ESS) (2018)

%
100

International Social Survey Programme (ISSP) (2016)

Lithuania1

India

Latvia

Spain

Slovak Republic

Chile

Israel

Australia

Average

Iceland1

Turkey

United States

Sweden1

0

New Zealand

0

Korea

10

Norway

10

Italy

20

Slovenia

20

Hungary

30

France

40

30

Estonia

40

Belgium

50

United Kingdom

50

Ireland

60

Finland

60

Average

70

Czech Republic

80

70

Germany1

80

Netherlands

90

Switzerland

90

Note: Refer to the source table and Annex 3 for more information on the questions asked in the two surveys. The blue zones denote cases where the differences between
any educational attainment levels are not statistically significant.
1. The distribution of educational attainment varies by 10-15 percentage points compared to data published in Indicator A1. Results by educational attainment are deemed
reliable (see Annex 3).
Countries are ranked in descending order of the percentage of tertiary-educated 25-64 year-olds who reported that the government allows people like them to have a say.
Source: OECD (2020), Table A6.3. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2https://doi.org/10.1787/888934162888

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A6. HOW ARE SOCIAL OUTCOMES RELATED TO EDUCATION?  127

Political efficacy, by educational attainment
On average, across selected OECD countries participating in the ESS, 52% of tertiary-educated adults report that their political
system allows people like them to have some or a great deal of say in what the government does. This share falls to 35%
among those who completed upper secondary or post-secondary non-tertiary education, and to 26% among those who did
not complete upper secondary education. Similar findings are observed in the selected countries that participated in the ISSP,
where educational attainment is positively associated with political efficacy (Figure A6.4).
The Netherlands shows the greatest variation by educational attainment among selected OECD countries participating in the
ESS: 74% of tertiary-educated adults feel that their political system allows people like them to have some or a great deal of
say in what the government does, but only 32% of adults with below upper secondary education. In contrast, Italy has the
smallest difference by educational attainment. Italians also report a low level of political efficacy overall: only 22% of tertiaryeducated adults think that their political system allows some or a great deal of say in what the government does, while for
adults with below upper secondary education the share is 9% (Figure A6.4).
Data from Korea show high levels of political efficacy regardless of educational attainment. Among the selected OECD
countries that participated in the ISSP, Korea has the second highest share of tertiary-educated adults who disagreed or
strongly disagreed that people like them don't have any say about what the government does (67%). It scores the highest for
adults with upper secondary or post-secondary non-tertiary education (60%) and for adults with below upper secondary
education (58%). In contrast, in India, Latvia, Lithuania and the Slovak Republic, less than 30% of adults disagreed or strongly
disagreed with this statement, regardless of their educational attainment (Figure A6.4).

Figure A6.5. Percentage of adults who reported being interested in politics, by educational attainment
(2016 or 2018)
European Social Survey (ESS-2018) and International Social Survey Programme (ISSP-2016), 25-64 year-olds
Tertiary
Upper secondary or post-secondary non-tertiary
Below upper secondary
%
100

European Social Survey (ESS) (2018)

%
100

International Social Survey Programme (ISSP) (2016)

Chile

Slovak Republic

Korea

Latvia

New Zealand

Lithuania¹

Israel

Australia

Average

Turkey

India

Spain

Iceland¹

0

United States

0

Norway

10

Sweden¹

10

Hungary

20

Czech Republic

30

20

Slovenia

30

Estonia

40

Italy

40

France

50

Average

50

Ireland

60

Belgium

70

60

United Kingdom

70

Finland

80

Switzerland

80

Netherlands

90

Germany¹

90

Note: Refer to the source table and Annex 3 for more information on the questions asked in the two surveys. The blue zones denote cases where the differences between
any educational attainment levels are not statistically significant.
1. The distribution of educational attainment varies by 10-15 percentage points compared to data published in Indicator A1. Results by educational attainment are deemed
reliable (see Annex 3).
Countries are ranked in descending order of the percentage of tertiary-educated 25-64 year-olds who reported being interested in politics.
Source: OECD (2020), Table A6.3. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2https://doi.org/10.1787/888934162907

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128  A6. HOW ARE SOCIAL OUTCOMES RELATED TO EDUCATION?
Interest in politics, by educational attainment
On average across selected OECD countries participating in the ESS, 57% of tertiary-educated adults reported being quite
or very interested in politics. The share falls to 40% among those who completed upper secondary or post-secondary nontertiary education, and to 30% among those who did not complete upper secondary education. Similar findings are observed
among selected countries that participated in the ISSP, where educational attainment is also positively associated with interest
in politics (Figure A6.5).
Austria shows the greatest variation by educational attainment among selected OECD countries participating in the ESS: 68%
of tertiary-educated adults reported being quite or very interested in politics, while the share is only 24% among those with
below upper secondary education. In contrast, the Czech Republic and Hungary have the smallest difference by educational
attainment. Adults in these countries show little interest in politics, with 30% or less reporting being quite or very interested in
politics, regardless of their educational attainment (Figure A6.5).
Data from Norway show that interest in politics is high regardless of educational attainment. Among the selected OECD
countries taking part in the ISSP, Norway has the highest share of adults who reported being somewhat to very interested in
politics, regardless of educational attainment: 90% among tertiary-educated adults, 85% among those with upper secondary
or post-secondary non-tertiary education and 83% among adults with below upper secondary education. In contrast, in Chile
less than 52% of tertiary-educated adults report being somewhat to very interested in politics, and it reaches a low of 19% for
those who did not complete upper secondary education (Figure A6.5).

Definitions
Age groups: Adults refer to 25-64 year-olds.
Bullying (exposure): PISA measures exposure to bullying by asking 15-year-old students: During the past 12 months, how
often have you had the following experiences in school? Some experiences can also happen in social media. / Please select
one response: Never or almost never, A few times a year, A few times a month, Once a week or more.


Other students left me out of things on purpose.



Other students made fun of me.



I was threatened by other students.



Other students took away or destroyed things that belonged to me.



I got hit or pushed around by other students.



Other students spread nasty rumours about me.

Bullying (attitudes): PISA measures attitudes associated to bullying by asking 15-year-old students: To what extent do you
agree with the following statements? Please select one response: Strongly disagree, Disagree, Agree, Strongly agree.


It irritates me when nobody defends bullied students.



It is a good thing to help students who can’t defend themselves.



It is a wrong thing to join in bullying.



I feel bad seeing other students bullied.



I like it when someone stands up for other students who are being bullied.

Educational attainment refers to the highest level of education reached by a person.
Expected level of education refers to the level of education 15-year-old students selected when they were asked about the
level of education they expect to complete.
Interest in politics is measured by the ESS by asking adults: How interested would you say you are in politics, are you: Very
interested, Quite interested, Hardly interested, or Not at all interested? For the ISSP, it is measured by asking adults: How
interested would you say you personally are in politics? Please select one response: Very interested, Fairly interested,
Somewhat interested, Not very interested, Not at all interested, Can't choose.
Levels of education: See the Reader’s Guide at the beginning of this publication for a presentation of all ISCED 2011 levels.

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A6. HOW ARE SOCIAL OUTCOMES RELATED TO EDUCATION?  129
Parents’ educational attainment: Below upper secondary means that both parents have attained ISCED 2011 levels 0 to
2; upper secondary or post-secondary non-tertiary means that at least one parent (whether mother or father) has attained
ISCED-2011 levels 3 or 4; and tertiary means that at least one parent (whether mother or father) has attained ISCED-2011
levels 5 to 8.
Political efficacy is measured by the ESS by asking adults: And how much would you say that the political system in [country]
allows people like you to have an influence on politics? Please select one response: Not at all, Very little, Some, A lot, A great
deal. For the ISSP, it is measured by asking adults: How much you agree or disagree with the following statement: People
like me don't have any say about what the government does. Please select one response: Strongly agree, Agree, Disagree,
Neither agree nor disagree, Disagree, Strongly disagree, Can't choose.

Methodology
For the 2018 European Social Survey (ESS) and the 2016 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 countries participating in the ISSP:


Chile, France, Hungary, Israel, New Zealand, Norway, the Russian Federation, the Slovak Republic, Slovenia,
Sweden, the United Kingdom and the United States.

See Annex 3 (https://doi.org/10.1787/69096873-en) for more information on the discrepancies in the survey sample
distribution.
Information regarding the proportion of the PISA sample covered for each variable is included in Annex 3
(https://doi.org/10.1787/69096873-en). For the tables presented in the Annex, no symbol means at least 75% of the population
were covered; one dagger (†) means at least 50% but less than 75%; and one double-dagger (‡) means less than 50% were
covered. The PISA threshold for publication is at least 30 students and 5 schools.

Source
Data from the Programme for International Student Assessment (PISA) 2018 provided evidence on bullying for OECD
member and partner countries (OECD, 2019[14]).
Data from the European Social Survey (ESS) (2018) provided evidence on political efficacy and interest in politics for
European OECD member countries (ESS, 2019[25]).
Data from the International Social Survey Programme (ISSP) (2016) provided evidence on political efficacy and interest in
politics for non-European OECD member and partner countries (ISSP Research Group, 2018[26]).

References
Acock, A., H. Clarke and M. Stewart (1985), “A new model for old measures: A covariance structure analysis of
political efficacy”, The Journal of Politics, Vol. 47/4, pp. 1062-1084, https://doi.org/10.2307/2130807.

[22]

Astor, R., N. Guerra and R. Van Acker (2010), “How can we improve school safety research?”, Educational
Researcher, Vol. 39/1, pp. 69-78, http://dx.doi.org/10.3102/0013189x09357619.

[5]

Burns, T. and F. Gottschalk (eds.) (2019), Educating 21st Century Children: Emotional Well-being in the Digital
Age, Educational Research and Innovation, OECD Publishing, Paris, https://dx.doi.org/10.1787/b7f33425-en.

[3]

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130  A6. HOW ARE SOCIAL OUTCOMES RELATED TO EDUCATION?
Dubow, E., P. Boxer and L. Huesmann (2009), “Long-term effects of parents’ education on children’s educational
and occupational success: Mediation by family interactions, child aggression, and teenage aspirations”, MerrillPalmer Quarterly, Vol. 55/3, pp. 224-249, http://dx.doi.org/10.1353/mpq.0.0030.

[13]

ESS (2019), Round 9 Data. Data File Edition 1.1., European Social Survey, http://dx.doi.org/10.21338/NSD-ESS92018.

[25]

Government of Saskatchewan (2019), Digital Citizenship in Saskatchewan Schools: K-12, Government of
Saskatchewan, https://publications.saskatchewan.ca/#/products/74037.

[18]

ISSP Research Group (2018), International Social Survey Programme: Role of Government V - ISSP 2016,
ZA6900 Data file Version 2.0.0, GESIS Data Archive, Cologne, http://dx.doi.org/10.4232/1.13052.

[26]

L1ght (2020), Rising Levels of Hate Speech & Online Toxicity During This Time of Crisis, L1ght,
https://l1ght.com/Toxicity_during_coronavirus_Report-L1ght.pdf (accessed on 27 April 2020).

[17]

Miller, A. and O. Listhaug (1990), “Political parties and confidence in government: A comparison of Norway,
Sweden and the United States”, British Journal of Political Science, Vol. 20/3, pp. 357-386,
http://dx.doi.org/10.1017/s0007123400005883.

[23]

Ministère de l’éducation nationale et de la jeunesse (2020), Non au harcèlement website,
http://www.nonauharcelement.education.gouv.fr (accessed on 4 May 2020).

[20]

Ministry of Education - Chile (2019), National Day Against Cyberbullying,
http://convivenciaescolar.mineduc.cl/compromiso-sana-convivencia/dia-contra-el-ciberacoso/ (accessed on
16 July 2020).

[21]

Nansel, T. et al. (2004), “Cross-national consistency in the relationship between bullying behaviors and
psychosocial adjustment”, Archives of Pediatrics & Adolescent Medicine, Vol. 158/8, p. 730,
http://dx.doi.org/10.1001/archpedi.158.8.730.

[7]

National Academies of Sciences, Engineering, and Medicine (2016), Preventing Bullying Through Science, Policy,
and Practice, The National Academies Press, Washington, DC, https://doi.org/10.17226/23482.

[9]

OECD (2019), Education Policy Outlook 2019: Working Together to Help Students Achieve their Potential, OECD
Publishing, Paris, https://dx.doi.org/10.1787/2b8ad56e-en.

[19]

OECD (2019), How’s Life in the Digital Age?: Opportunities and Risks of the Digital Transformation for People’s
Well-being, OECD Publishing, Paris, https://dx.doi.org/10.1787/9789264311800-en.

[10]

OECD (2019), PISA 2018 Results (Volume I): What Students Know and Can Do, PISA, OECD Publishing, Paris,
https://dx.doi.org/10.1787/5f07c754-en.

[14]

OECD (2017), “Bullying”, in PISA 2015 Results (Volume III): Students’ Well-Being, OECD Publishing, Paris,
https://dx.doi.org/10.1787/9789264273856-12-en.

[4]

OECD (2017), How’s Life? 2017: Measuring Well-being, OECD Publishing, Paris,
https://dx.doi.org/10.1787/how_life-2017-en.

[2]

OECD (2016), Education at a Glance 2016: OECD Indicators, OECD Publishing, Paris,
https://dx.doi.org/10.1787/eag-2016-en.

[12]

OECD (2016), Society at a Glance 2016: OECD Social Indicators, OECD Publishing, Paris,
https://dx.doi.org/10.1787/9789264261488-en.

[24]

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A6. HOW ARE SOCIAL OUTCOMES RELATED TO EDUCATION?  131
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.

[6]

OECD (2011), How’s Life?: Measuring Well-being, OECD Publishing, Paris,
https://dx.doi.org/10.1787/9789264121164-en.

[1]

Rigby, K. (2007), Bullying in Schools: And What to Do About It, ACER Press.

[8]

Tippett, N. and D. Wolke (2014), “Socioeconomic status and bullying: A meta-analysis”, American Journal of Public
Health, Vol. 104/6, pp. e48-e59, http://dx.doi.org/10.2105/ajph.2014.301960.

[11]

UNICEF (2020), COVID-19 and Its Implications for Protecting Children Online, Unicef,
https://www.unicef.org/media/67396/file/COVID19%20and%20Its%20Implications%20for%20Protecting%20Children%20Online.pdf (accessed on
23 April 2020).

[16]

World Economic Forum (2020), Will the coronavirus break the internet?, World Economic Forum website,
https://www.weforum.org/agenda/2020/03/will-coronavirus-break-the-internet/ (accessed on 23 April 2020).

[15]

Indicator A6 Tables
Table A6.1

Percentage of 15-year-old students who reported being exposed to different forms of bullying at least a
few times a month, by parents' educational attainment (2018)

Table A6.2

Percentage of 15-year-old students who agreed or strongly agreed with statements about bullying, by
parents' educational attainment (2018)

Table A6.3

Political engagement, by educational attainment (2016 or 2018)

WEB Table A6.4

Percentage of 15-year-old students who reported being exposed to different forms of bullying at least a
few times a month, by students' expected level of educational attainment (2018)

WEB Table A6.5

Percentage of 15-year-old students who agreed or strongly agreed with statements about bullying, by
students' expected level of educational attainment (2018)

WEB Table A6.6

Distribution of parents' educational attainment and expected level of educational attainment of 15-yearold students (2018)

Cut-off date for the data: 19 July 2020. Any updates on data can be found on line at http://dx.doi.org/10.1787/eag-dataen. More breakdowns can also be found at http://stats.oecd.org/, Education at a Glance Database.
StatLink: https://doi.org/10.1787/888934162755

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132  A6. HOW ARE SOCIAL OUTCOMES RELATED TO EDUCATION?
Table A6.1. Percentage of 15-year-old students who reported being exposed to different forms of bullying at least a few times
a month, by parents' educational attainment (2018)
Programme for International Student Assessment (PISA)

Note: More data on students whose parents have below upper secondary education or tertiary education are available for consultation on line (see StatLink below).
"Exposure to any type of bullying act" is a measure that combines all six items on bullying. Parents' educational attainment refers to the highest level attained by at least
one parent.
1. B-S-J-Z (China) refers to the four PISA-participating provinces/municipalities of the People’s Republic of China: Beijing, Shanghai, Jiangsu and Zhejiang.
2. India and South Africa did not participate in PISA (2018).
Source: OECD (2020), PISA 2018 Results (Volume I): What Students Know and Can Do, https://doi.org/10.1787/5f07c754-en. See Source section for more information
and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2https://doi.org/10.1787/888934162774

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A6. HOW ARE SOCIAL OUTCOMES RELATED TO EDUCATION?  133

Table A6.2. Percentage of 15-year-old students who agreed or strongly agreed with statements about bullying, by parents'
educational attainment (2018)
Programme for International Student Assessment (PISA)

Note: More data on students whose parents have below upper secondary education or tertiary education are available for consultation on line (see StatLink below). Parents'
educational attainment refers to the highest level attained by at least one parent.
1. B-S-J-Z (China) refers to the four PISA-participating provinces/municipalities of the People’s Republic of China: Beijing, Shanghai, Jiangsu and Zhejiang.
2. India and South Africa did not participate in PISA (2018).
Source: OECD (2020), PISA 2018 Results (Volume I): What Students Know and Can Do, https://doi.org/10.1787/5f07c754-en. See Source section for more information
and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2https://doi.org/10.1787/888934162793

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134  A6. HOW ARE SOCIAL OUTCOMES RELATED TO EDUCATION?
Table A6.3. Political engagement, by educational attainment (2016 or 2018)
European Social Survey (ESS) or International Social Survey Programme (ISSP), 25-64 year-olds

1. The distribution of educational attainment varies by 10-15 percentage points compared to data published in Indicator A1. Results by educational attainment are deemed
reliable (see Annex 3).
Source: OECD (2020), European Social Survey (ESS) (2018) and the International Social Survey Programme (ISSP) (2016). See Source section for more information and
Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2/https://doi.org/10.1787/888934162812

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136  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


The most common form of participation in adult learning is non-formal education, and most of the time it is jobrelated and employer-sponsored. On average across OECD countries taking part in the Adult Education Survey
(AES), 44% of working adults had participated in at least one job-related and employer-sponsored non-formal
training activity, but only 9% had taken part in one that was neither job-related nor sponsored by their employer.



Large enterprises provide more training than small ones. On average across OECD countries taking part in AES,
30% of adults employed in enterprises with fewer than 10 employed persons participated in at least one
non-formal job-related and employer-sponsored education and training activity. This share is twice as high (60%)
among adults working in firms with over 249 employed persons.



Large enterprises invest more of their total labour costs in training than smaller ones. On average across OECD
countries participating in the Continuing Vocational Training Survey (CVTS), training costs in the form of courses
represent 2.1% of total labour costs in enterprises with over 249 employed persons, 1.5% in enterprises with 50249 employed persons, and 1.3% in enterprises with 10-49 employed persons.

Figure A7.1. Share of employed 25-64 year-olds participating in non-formal education and training, by
job relatedness, employer sponsorship and size of enterprise (2016)
Adult Education Survey (AES), average for OECD countries participating in AES
%
70

1-9 employed persons

10-49 employed persons

50-249 employed persons

Over 249 employed persons

60
50
40
30
20
10
0
Total participation in non-formal
education and training
(regardless of job-relatedness and
employer sponsorship)

Participation in job-related
non-formal education and training
sponsored by the employer

Participation in job-related
non-formal education and training
not sponsored by the employer

Participation in non-job-related
non-formal education and training
not sponsored by the employer

Note: Total participation is not equal to the sum of the disaggregated categories because the same person can be included in more than one
category.
Source: OECD (2020), Table A7.1. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2https://doi.org/10.1787/888934163002

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A7. TO WHAT EXTENT DO ADULTS PARTICIPATE EQUALLY IN EDUCATION AND LEARNING?  137

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]).
The adults already in the workforce may have to continue to fill a significant share of the jobs of the future, requiring them
to learn new skills and update existing ones. With the recent COVID-19 crisis, workers in some areas have had to change
their working habits, relying more than ever on technology and teleworking and requiring them to be flexible and adaptable,
which in some cases has had to be accompanied by additional training.
Adult learning can also contribute to non-economic goals, such as personal fulfilment, improved health, civic participation
and social inclusion. For example, during the COVID-19 lockdown, learning to use new technology may help people to
stay in contact with friends and family. 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, in learning opportunities at work and in adult education systems (Borkowsky, 2013[2]).

Other findings


Enterprise size has a large impact on employees’ participation in job-related education and training, but when the
training is not sponsored by the employer, then the size of the enterprise no longer affects participation.



Adults are less likely to participate in formal than in non-formal education and training, but if they do, then the
intensity is much higher than for non-formal education. On average across the OECD countries participating in
AES, those taking part in formal education and training spend 406 hours per year on average, against only
73 hours for non-formal education and training.



Working in the public sector is associated with greater participation than in the private sector. On average across
OECD countries participating in AES, 57% of adults working in the public sector participated in at least one nonformal job-related and employer-sponsored education and training activity, compared to 40% of adults working in
the private sector.



Adults with higher educational attainment are more likely to participate. On average across OECD countries taking
part in AES, 24% of 25-64 year-olds with below upper secondary education participated in at least one non-formal
education and training activity in the 12 months preceding the survey. This rose to 41% for those with upper
secondary or post-secondary non-tertiary education and 62% for those with a tertiary degree.

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138  A7. TO WHAT EXTENT DO ADULTS PARTICIPATE EQUALLY IN EDUCATION AND LEARNING?

Analysis
Participation in adult learning is often motivated by the social context. People choose to invest in what they value and devote
energy towards becoming more effective in what they find relevant (Wlodkowski and Ginsberg, 2017[3]). Research show that
adults participate in educational and learning activities for both intellectual reasons and for the usefulness of what they learn
(Dench and Regan, 2000[4]). Intellectual reasons include wanting to keep the brain active, the enjoyment of the challenge of
learning new things and an interest in acquiring knowledge, while the practical reasons are more related to enhancing
employment prospects and remaining competitive in the labour market. Participation in high-quality formal and non-formal
professional development enables employees to update their skills to be effective workers in the 21st century global economy.
Data from the Adult Education Survey (AES) and from the Survey of Adult Skills, a product of the Programme for the
International Assessment of Adult Competencies (PIAAC), show that non-formal education and training is the most common
type of adult learning. On average across OECD countries taking part in AES, 44% of 25-64 year-olds participated in at least
one non-formal education and training activity in the 12 months preceding the survey, compared to only 7% taking part in
formal education and training. Among these countries, participation in non-formal education ranges from less than 30% in
Greece, Lithuania, Poland and Turkey to more than 60% in the Netherlands and Switzerland. Among countries that only
participated in the Survey of Adult Skills (PIAAC), participation in non-formal education ranges from less than 30% in Mexico
and the Russian Federation to 63% in New Zealand (Table A7.5, available on line).
The data also show that most non-formal education and training is job-related and sponsored by the employer. Among
employed adults, only 9% participated in any non-formal education activity that was not job-related and not sponsored by the
employer while 44% participated in at least one job-related and employer-sponsored training activity (Table A7.1 and
Table A7.5, available on line).

Participation of employed adults in non-formal education and training
Participation by size of enterprise
Equity in access to adult learning is a policy concern across OECD countries (OECD, 2019[5]; European Commission, 2019[6]).
Low-educated and economically inactive adults are less likely to participate in education and training because they are less
exposed to learning opportunities than highly educated and employed adults. But inequalities are not limited to educational
attainment and employment status. They arise even among employed adults depending of the size of their enterprise. For
example, there is a common pattern across OECD countries: large enterprises provide more training to their employees than
small ones (Figure A7.1).
Employers have a key role to play in providing and financing job-related adult learning, but many small and medium-sized
enterprises lack the capacity to offer training opportunities to their employees. These employers may therefore benefit less
from training effects such as increased productivity, higher employee retention, better engagement and improved
management-worker interactions. For their employees this translates into fewer opportunities to participate in adult learning
and, in turn, fewer possibilities to benefit from its positive outcomes. They could be missing out on higher incomes and
improved employability, improved general well-being and health, and improved engagement in community and civic activities
(OECD, 2019[5]; European Commission, 2015[7]).
Figure A7.1 shows that, on average across the 26 OECD countries taking part in AES, 30% of adults employed in enterprises
with under 10 employed persons participated in at least one non-formal job-related and employer-sponsored education and
training activity. This share is twice as high (60%) among adults working in firms with over 249 employed persons. The largest
differences are observed in Ireland, Lithuania and Turkey where the gap is more than 35 percentage points between the
participation rates of adults employed in the smallest enterprises and those in enterprises with over 249 employed persons.
In contrast, the gap is below 25 percentage points in the Czech Republic, Estonia, Germany, Norway and Slovenia. Across
the OECD member and partner countries that only participated in the Survey of Adult Skills (PIAAC), the gap is at least
40 percentage points in Chile, Korea and Mexico and is below 30 percentage points in Japan, New Zealand and
the Russian Federation (Table A7.1).
In all OECD countries, those employed in larger enterprises are more likely than those in smaller ones to participate in jobrelated adult learning sponsored by their employer. In contrast, when training is not sponsored by the employer, participation
is much lower, regardless of the size of the enterprise. On average across the 26 OECD countries taking part in AES, about
10% of employed 25-64 year-olds participated in at least one non-job related education or training activity that was not
EDUCATION AT A GLANCE 2020 © OECD 2020

A7. TO WHAT EXTENT DO ADULTS PARTICIPATE EQUALLY IN EDUCATION AND LEARNING?  139
sponsored by their employers, regardless of the size of the enterprise they work in. This implies that the size of the enterprise
has a large impact on training opportunities available to employees, but when training is not sponsored, whether it is
job-related or not, then the size of the company makes almost no difference (Figure A7.1).
There is a positive relationship between the size of the enterprise (in terms of number of employees) and participation in
job-related employer-sponsored non-formal education and training in all the OECD member and partner countries that
participated in AES and the Survey of Adult Skills (PIAAC). However, the extent of participation varies significantly across
countries. For example, adults in Switzerland working for firms with under 10 employed persons are more likely to take part
in such training than those working for enterprises with over 249 employed persons in Lithuania and Poland. This also holds
true in the non-European countries that participated in the Survey of Adult Skills (PIAAC): the participation among employed
persons even of the smallest enterprises in New Zealand (47%) is higher than for those in the Russian Federation, even
among those working for large firms (28%) (Figure A7.2).

Figure A7.2. Share of employed 25-64 year-olds participating in non-formal job-related and employersponsored education and training, by size of enterprise (2016)
Adult Education Survey (AES) or Survey of Adult Skills (PIAAC)

Russian Federation*3

Japan3

Mexico3

Israel3

Chile3

Korea3

Canada3

United States3

Australia3

New Zealand3

Poland

%
100
90
80
70
60
50
40
30
20
10
0

Greece2

Turkey

Lithuania

Estonia

Slovenia

Italy

Belgium

Czech Republic

Hungary

Luxembourg

Spain

Denmark

Survey of Adult Skills (PIAAC)

Average

Adult Education Survey (AES)

Germany

Over 250 employed persons
51-250 employed persons
11-50 employed persons
1-10 employed persons

Latvia
France

Finland

Norway

United Kingdom

Austria

Portugal

Ireland

Slovak Republic

Sweden

Netherlands1

70
60
50
40
30
20
10
0

Switzerland

%
100
90
80

Over 249 employed persons
50-249 employed persons
10-49 employed persons
1-9 employed persons

1. The category "50-249 employed persons" should be interpreted as "over 50 employed persons". The category "over 249 employed persons" is therefore
missing for the Netherlands.
2. Data for the categories "50-249 employed persons" and "over 249 employed persons" have a low reliability and are therefore not presented.
3. 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 25-64 year-olds employed in enterprises with over 249 (or 250) employed persons and
participating in non-formal job-related and employer-sponsored education and training.
Source: OECD (2020), Table A7.1. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2https://doi.org/10.1787/888934163021

In all countries participating in AES and the Survey of Adult Skills (PIAAC), except for Estonia, Lithuania,
the Russian Federation and Slovenia, the largest difference in participation in job-related and employer-sponsored non-formal
education and training occurs between adults working in enterprises with 1-9 employed persons and those working in
enterprises with 10-49 employed persons (the categories in the Survey of Adult Skills [PIAAC] are 1-10 and 11-50 employed
EDUCATION AT A GLANCE 2020 © OECD 2020

140  A7. TO WHAT EXTENT DO ADULTS PARTICIPATE EQUALLY IN EDUCATION AND LEARNING?
persons). On average, across OECD countries participating in AES, 30% of adults employed in enterprises with fewer than
10 employed persons took part in such activities, but the rate jumped to 45% for enterprises with 10-49 employed persons,
53% for enterprises with 50-249 employed persons, and 60% for those working in enterprises with over 249 employed
persons (Figure A7.2).
A similar pattern emerges when enterprises are asked if they provide training to their staff, large firms tend to report providing
training more widely than small firms. On average across OECD countries taking part in the Continuing Vocational Training
Survey (CVTS), 74% of enterprises with 10-49 employed persons provide training, compared with 96% of enterprises with
over 249 employed persons. There are also large differences between countries on this measure, with almost every enterprise
in Latvia and Norway providing training but less than 30% of enterprises in Greece doing so (Table A7.4, available on line).
Enterprise size seems to play a more prominent role in the countries where a lower share of firms provide training. For
example, in Greece, Hungary and Poland, less than 40% of enterprises with 10-49 employed persons provide training, but
the share is at least 40 percentage points higher among enterprises with over 249 employed persons. In contrast, in Latvia,
Norway and Sweden, the share of enterprises providing training is very high, regardless of size. In these three countries, even
the smallest firms consistently provide training: over 90% of the enterprises with 10-49 employed persons provide training
(Table A7.4, available on line).

Figure A7.3. Share of employed 25-64 year-olds participating in non-formal job-related and employersponsored education and training, by public / private sector (2016)
Adult Education Survey (AES) or Survey of Adult Skills (PIAAC)
Public1
%
80

Private

Adult Education Survey (AES)

%
80

Survey of Adult Skills (PIAAC)

Russian Federation*2

Mexico2

Japan2

Chile2

Israel2

Korea2

United States2

Canada2

New Zealand2

Australia2

Greece

Poland

Lithuania

Slovak Republic
Turkey

Italy

Luxembourg

Belgium

Hungary

Spain

France
Portugal

0

Average

0

Denmark

10

Czech Republic

20

10

Latvia

20

Finland
Germany

30

Norway

30

United Kingdom

40

Ireland

40

Sweden

50

Estonia
Austria

60

50

Slovenia

60

Switzerland

70

Netherlands

70

1. For the Survey of Adult Skills (PIAAC): includes non-profit organisations.
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 25-64 year-olds employed in the public sector and participating in non-formal job-related
and employer-sponsored education and training.
Source: OECD (2020), Table A7.1. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2https://doi.org/10.1787/888934163040

Participation in the public and private sector
Working in the public sector is associated with greater participation in non-formal training than in the private sector. This could
be related to different culture and governance structures in the two sectors. It could also be associated with the size of
enterprises in the private sector compared with public sector employers. In all countries, the public sector employs large
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A7. TO WHAT EXTENT DO ADULTS PARTICIPATE EQUALLY IN EDUCATION AND LEARNING?  141
numbers of staff while private firms can vary in size. On average across OECD countries participating in AES, 57% of adults
working in the public sector took part at least one non-formal job-related and employer-sponsored education and training
activity, compared to 40% of adults working in the private sector. This trend is observed across all OECD and member
countries participating in AES and the Survey of Adult Skills (PIAAC), with the exception of the Slovak Republic where 51%
of adults participated in such training, regardless of the economic sector (Figure A7.3).
The largest difference across OECD countries participating in AES are observed in Estonia and Slovenia where the
participation rate of those working in the public sector is at least 29 percentage points higher than those working in the private
sector. In contrast, in Greece, Hungary and the Slovak Republic, the difference is below 10 percentage points (Figure A7.3).

Participation by all adults in non-formal education and training activities by level of education
Adults with higher educational attainment are more likely to participate in non-formal education and training activities. On
average across OECD countries taking part in AES, 24% of all 25-64 year-olds – regardless of whether they are working or
not – with below upper secondary education participated in at least one non-formal education and training activity in the
12 months preceding the survey. The rate is 41% for those with upper secondary or post-secondary non-tertiary education
and reaches 62% for those with a tertiary degree (Table A7.5, available on line).
In Austria, the Czech Republic and Switzerland the difference between adults with and without upper secondary or postsecondary non-tertiary education is at least 25 percentage points. The difference between those with a tertiary degree and
those with below upper secondary education is over 20 percentage points in all OECD countries participating in AES, and
reaches 50 percentage points or more in Slovenia and Switzerland (Table A7.5, available on line).

Relationship between participation rates and intensity for all adults
Non-formal education and training
Figure A7.4 depicts the association between the participation rate in non-formal education and training and the average
number of instruction hours per year, for the OECD countries that participated in AES. On average, 44% of 25-64 year-olds
participated in non-formal education and training, and those who did so spent an average of 73 hours on these activities. Both
participation rates and the average number of hours devoted to training vary widely across countries. These differences point
to different policy choices, which may explain the low correlation between the two variables. Austria is the only country where
more than 55% of 25-64 year-olds participate in non-formal education and training and do so for over 80 hours per year on
average. In contrast, in Lithuania, less than 30% of adults participate in non-formal education and training and for an annual
average of only 42 hours (Figure A7.4).
The distribution of countries in the four quadrants in Figure A7.4 shows that there is no clear correlation between participation
rates and intensity. Countries with similar participation rates exhibit large differences in average hours of participation per
year. For example, the participation rates in the Czech Republic and the Slovak Republic are similar to Slovenia’s, but their
intensity of participation is much lower, with both countries averaging around 35 hours compared to 142 hours in Slovenia.
This shows that even when countries succeed in engaging a similar share of the population in adult education and training,
the amount of training undertaken could be very different (Figure A7.4).
The participation gap according to educational attainment narrows when intensity of participation, in terms of hours of
instruction, is considered, rather than the overall participation rate. The longest hours are not always associated with the
highest educational attainment. For example, in 9 of the 26 OECD countries participating in AES, it is the adults with below
upper secondary education who have the longest average instruction hours in non-formal education and training. In Denmark,
the highest intensity is among those with upper secondary or post-secondary non-tertiary education, while in 15 countries the
intensity is the highest among tertiary-educated adults. Therefore, for some countries, educational attainment is positively
associated with participation in adult learning, but not its intensity (Table A7.2).
It should also be noted that the average number of instruction hours per year is generally much higher among OECD member
and partner countries that participated in the Survey of Adult Skills (PIAAC) than among those participating in AES. For
countries that participated in the Survey of Adult Skills (PIAAC), the lowest average number of instruction hours per year in
non-formal education is found in Australia with 103 hours, while it reaches over 225 hours per year in Korea and Mexico
(Table A7.2). In comparison, the lowest value for OECD countries participating in AES is 35 hours in the Czech Republic,

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142  A7. TO WHAT EXTENT DO ADULTS PARTICIPATE EQUALLY IN EDUCATION AND LEARNING?
while the highest is 142 hours in Slovenia. The important differences between the two surveys is probably associated with
the survey design.

Figure A7.4. Relationship between the intensity of participation (in hours) and the share of 25-64 yearolds participating in non-formal education and training (2016)
Adult Education Survey (AES)
Participation (%)
80
70

Switzerland

60

Hungary

Netherlands

Norway

Sweden

Ireland

50

Czech Republic Slovak Republic

France
Latvia
Finland
Austria
Luxembourg
Portugal

Germany

United Kingdom

Average

40

Estonia

30

Slovenia

Italy
Denmark

Belgium

Spain

Lithuania
Poland

20

Turkey

Greece

10
0
0

20

40

60

80

100

120

140

160
Hours

Note: The intensity of participation (in hours) is based on 25-64 year-olds who participated in non-formal education and training activities.
Source: OECD (2020), Tables A7.2 and A7.5, available on line. See Source section for more information and Annex 3 for notes
(https://doi.org/10.1787/69096873-en).
Statlink2https://doi.org/10.1787/888934163059

Formal education and training
Participation in formal education and training is less widespread among 25-64 year-olds, but when they do participate in
formal education, the intensity is much higher than for non-formal education. On average across OECD countries participating
in AES, participants in formal education and training devote 406 hours per year to it, against only 73 hours for non-formal
education and training (Table A7.2).
Among participating countries, adults in Germany spend the largest number of hours on formal education and training
(872 hours per year). Portugal has the second highest intensity at 653 hours per year. In contrast, in Luxembourg, Norway,
Spain, Turkey and the United Kingdom, adults spend less than 300 hours on formal learning; the United Kingdom ranks
lowest on this measure, at only 169 hours per year (Table A7.2).

Training costs
According to a recent report of the European Commission Working Group on Adult Learning (2019[6]), adult learning has not
benefited from the increased financial investment in education over the last decade, despite covering the largest group of
learners. During this period, countries have increased their spending in education (see Indicators C2 and C4), but public
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A7. TO WHAT EXTENT DO ADULTS PARTICIPATE EQUALLY IN EDUCATION AND LEARNING?  143
expenditure on adult education has lagged behind and it remains the least well-funded sector of education. This implies that
providers of adult learning are forced to work with limited financial resources despite the growing need to train adults and
provide them with the skills they need to remain employable and competitive in the context of the digitalisation of the economy
and the fast-changing labour market.
Employers are the main provider of non-formal education and therefore contribute a substantial share of the financial
resources invested in adult learning (Eurostat, 2020[8]; European Commission/EACEA/Eurydice, 2015[9]). Providers of adult
education can also face barriers in delivering training if they lack the resources. Employers may also be reluctant to invest in
their staff if they do not see immediate benefits, or they may not be aware of funding available to train their staff. For example,
in some countries, employers can receive financial support to provide training opportunities to staff who usually do not take
part in company-funded activities. This could take the form of a reduction in tuition fees when enrolling employees in training
courses or they can be reimbursed for education and training costs. Financial support is more widespread when it comes to
training low-qualified or low-skilled staff or people who have been out of the labour market (European
Commission/EACEA/Eurydice, 2015[9]).
The size of the enterprise plays an important role in the amount devoted to the provision of training. Larger enterprises will
be able to spread the costs of training over a greater number of employees. Large firms are more likely to have several
workers performing the same job, triggering the need to provide group training (Black, Noel and Wang, 1999[10]). In contrast,
smaller enterprises have greater unit costs that may discourage this investment.
Data from the CVTS show a clear trend across European countries: large enterprises with over 249 employed persons invest
a greater share of their total labour costs in training than either enterprises with 10-49 employed persons or with 50249 employed persons. On average across the OECD countries participating in the CVTS, training costs in the form of courses
made up 2.1% of the total labour costs of enterprises with over 249 employed persons, 1.5% of costs in enterprises with 50249 employed persons, and 1.3% in enterprises with 10-49 employed persons (Figure A7.5).

Figure A7.5. Training costs as a share of total labour costs, by size of enterprise (2015)
Continuing Vocational Training Survey (CVTS) or national surveys
Over 249 employed persons
50-249 employed persons
10-49 employed persons
%
4.5

National
surveys

Continuing Vocational Training Survey (CVTS)

%
4.5

4.0

4.0

3.5

3.5

3.0

3.0

2.5

2.5

2.0

2.0

1.5

1.5

Switzerland

Latvia

Finland

Lithuania

Greece

Germany

Austria

United Kingdom

Czech Republic¹

Sweden

Poland

Italy

Slovak Republic

Norway

Average

Spain

Portugal

Hungary

Luxembourg

Ireland

Estonia

Netherlands

Belgium

0

Slovenia

0.5

0

France

1.0

Denmark

1.0
0.5

1. Data were mainly collected on line and via interactive PDF forms, only small part of questionnaires was distributed in a paper form. See metadata for
more information at https://ec.europa.eu/eurostat/cache/metadata/EN/trng_cvt_esqrs_cz.htm.
Countries are ranked in descending order of the training costs of enterprises of over 249 employed persons as a share of their total labour costs.
Source: OECD (2020), Table A7.3. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2https://doi.org/10.1787/888934163078

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144  A7. TO WHAT EXTENT DO ADULTS PARTICIPATE EQUALLY IN EDUCATION AND LEARNING?
The largest difference by size of enterprise is in Denmark where enterprises with over 249 employed persons invest 4.1% of
their total labour costs in training courses, compared to only 1.1% for enterprises with 10-49 employed persons. In contrast,
in Finland, Norway and Sweden, training costs as a share of labour costs are almost identical, regardless of the size of the
firm. The only country where the pattern is reversed is the United Kingdom where firms with fewer than 250 employed persons
invest a greater percentage of their total labour costs in training courses than large enterprises (Figure A7.5).
Across most of the OECD countries participating in the CVTS, the largest difference in the share of labour costs invested in
courses is between enterprises with 50-249 employed persons and those with over 249 employed persons. Out of the
24 OECD countries taking part, only 8 countries have a larger difference between enterprises with 10-49 employed persons
and those with 50-249 employed persons. This supports the idea that larger firms benefit from lower costs associated with
the scale of their training activities and are therefore willing to invest a larger share of their labour costs in courses
(Figure A7.1).

Box A7.1. Teachers’ training and preparedness to support digital learning
Teachers, even more than in many professions, need to renew their skills regularly in order to be able to innovate their
teaching practices and adapt to the ultra-rapid transformations inherent in the 21st century. This is even more important
in the current context, where the health crisis we are experiencing has led to the closure of schools and the extensive use
of online learning to ensure pedagogical continuity. This unprecedented situation has pushed teachers to adapt very
quickly, especially in countries where they do not necessarily have the pedagogical and technical skills to integrate digital
tools into learning.
Data from the Teaching and Learning International Survey (TALIS) provide an interesting perspective on the training
undertaken by teachers before the outbreak. They provide some measure of the frequency and intensity of teachers’
continued professional development. The data show that, on average, teachers attended about four different types of
continuous professional development activity in the 12 months prior to the survey, and 82% of teachers report that the
professional development activities they participated in had an impact on their teaching practices (Reimers and Schleicher,
2020[11]; OECD, 2019[12]).
Most teachers participate in professional development, but not necessary in the most impactful programmes. According
to teachers, the professional development programmes that have the most impact are those based on strong subject and
curriculum content and which involve collaborative approaches to instruction, as well as the incorporation of active learning
(OECD, 2019[12]). Perhaps because of the lack of supply, teachers do not participate that much in training which includes
these elements. Teachers are most likely to participate in courses or seminars attended in person, with 76% of lower
secondary teachers reporting taking part in such activity on average across OECD countries. Participation is lower for
more collaborative forms of professional development, with only 44% of teachers participating in peer and/or selfobservation and coaching as part of a formal school arrangement (Figure A7.6).
Teachers also report a high need for training in the use of information and communication technologies (ICT) for teaching,
with 18% on average across OECD countries identifying this as a high training need (OECD, 2019[12]). This is the second
commonest training need teachers identified, just after teaching special needs students. ICT skills are particularly
important given the radical shift towards online teaching during the COVID-19 lockdown in many OECD countries. Data
on professional development show that on average across OECD countries, 36% of lower secondary teachers reported
participating in online courses or seminars, less than half the share participating in courses or seminars in person. This
shows that not only are teachers reporting a need for ICT training, but also that they are not relying heavily on distance
learning for their own professional development. Although this is the case in most countries, there are some exceptions
such as Korea and Shanghai (People’s Republic of China) where over 90% of teachers reported undertaking online
professional development in the past year. This practice is also widespread in Australia, Chinese Taipei, England
(United Kingdom), Israel, Mexico, the Russian Federation and the United States, where the share is over 50%
(Figure A7.6).
The frequency with which teachers have students use ICT for projects or class work has risen in almost all countries since
2013, to the point where 53% of teachers across the OECD now report frequently or always using this practice (OECD,
2019[12]). This reflects the broader trend of digitalisation and the spread of ICT across all spheres of society. Younger
teachers may be more familiar with new technologies but, surprisingly, they do not report much greater use of ICT for

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A7. TO WHAT EXTENT DO ADULTS PARTICIPATE EQUALLY IN EDUCATION AND LEARNING?  145
students’ projects than older teachers. This implies that while younger teachers may be more familiar with these tools,
more experienced ones may be more at ease with other teaching practices and therefore be more willing to innovate using
ICT. Across the OECD, only 56% of teachers had participated in training in the use of ICT for teaching as part of their
initial education or training, and only 43% of teachers felt well or very well prepared for this element when they began
teaching (Reimers and Schleicher, 2020[11]).

Figure A7.6. Percentage of lower secondary teachers who participated in selected types of
professional development (2018)
Teaching and Learning International Survey (TALIS)

%
100

Courses/seminars attended in person
Peer and/or self-observation and coaching as part of a formal school arrangement
Online courses/seminars
Formal qualification programme¹

90
80
70
60
50
40
30
20

0

Lithuania
Latvia
Slovenia
Australia
Austria
Estonia
Netherlands
Flemish Comm. (Belgium)
Alberta (Canada)
New Zealand
Turkey
Russian Federation
Iceland
Czech Republic
Israel
United States
Italy
OECD average
Korea
Chinese Taipei
England (UK)
Shanghai (China)
Sweden
Norway
Denmark
Saudi Arabia
Spain
South Africa
Finland
Portugal
CABA (Argentina)2
Brazil
Belgium
Slovak Republic
Hungary
Colombia
Chile
Mexico
France
Japan
French Comm. (Belgium)

10

Note: The OECD average is the arithmetic average based on lower secondary teacher data across 31 OECD countries and economies with
adjudicated data.
1. For example, a degree programme.
2. Refers to the adjudicated region of Ciudad Autónoma de Buenos Aires (CABA).
Countries and economies are ranked in descending order of the percentage of lower secondary teachers who attended courses/seminars in person
in the 12 months prior to the survey.
Source: OECD (2018), TALIS 2018 Results (Volume I): Teachers and School Leaders as Lifelong Learners, https://dx.doi.org/10.1787/1d0bc92aen, Web table 1.5.7. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2https://doi.org/10.1787/888934163097

Of all the stages of a teacher’s career, their first working years are those that merit the greatest support and attention.
TALIS data show that teachers in their early careers tend to work in more challenging schools, and 22% of them report
that they would like to change to another school if that were possible (OECD, 2019[12]). Novice teachers also have less
confidence in their ability to teach, particularly in their classroom management skills and their capacity to use a wide range
of effective instructional practices. Induction to teaching and mentoring can support teachers who are new to a school or
the profession. But despite empirical evidence showing that teachers’ participation in induction and mentoring is beneficial
to student learning, and the fact that school principals generally consider mentoring to be important for supporting less
experienced teachers, induction and mentoring are not yet commonplace. On average, 51% of novice teachers report not
having participated in any formal or informal induction at their current school, and only 22% have an assigned mentor
(Reimers and Schleicher, 2020[11]).

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146  A7. TO WHAT EXTENT DO ADULTS PARTICIPATE EQUALLY IN EDUCATION AND LEARNING?

Definitions
Adults refer to 25-64 year-olds.
Adult education and learning: Formal education is planned education provided in the system of schools, colleges,
universities and other formal educational institutions that normally constitutes a continuous “ladder” of full-time education for
children and young people. The providers may be public or private. Non-formal education is sustained educational activity
that does not correspond exactly to the definition of formal education. Non-formal education may take place both within and
outside educational institutions and cater to individuals of all ages. Depending on country contexts, it may cover education
programmes in adult literacy, basic education for out-of-school children, life skills, work skills and general culture.
Economic sector refers to the distinction between public and private sector. Public sector is a constructed measure in
Adult Education Survey (AES) while the Survey of Adult Skills (PIAAC) uses three categories in its questionnaire: public
sector, private sector and non-profit organisation. The public sector for AES data refer to NACE sectors O, P and Q. The nonprofit organisation category was merged with the public sector category for the Survey of Adult Skills (PIAAC). The private
sector is also a constructed measure in AES while the Survey of Adult Skills (PIAAC) uses this specific term. The private
sector for AES data refer to NACE sectors B to N, R and S (for a description of NACE sectors, see
https://ec.europa.eu/eurostat/ramon).
Employer-sponsored education: Employer support can be offered in the form of time (i.e. educational activities that take
place fully or partly during paid working hours), or financial support (giving grants to employees to participate in educational
activities).
Job-related education and training: Taking part in training activity in order to obtain knowledge and/or learn new skills
needed for a current or future job, to increase earnings, to improve job and/or career opportunities in a current or another field
and generally to improve opportunities for advancement and promotion.
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 nontertiary 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/d14c857a601d-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, A7.2 and A7.5 on adult education and training are based on:


Adult Education Survey (AES) for European OECD member countries.



The OECD Programme for the International Assessment of Adult Competencies (the Survey of Adult Skills [PIAAC])
for: Australia, Canada, Chile, Israel, Japan, Korea, Mexico, New Zealand, the Russian Federation and
the United States.

Table A7.3 and Table A7.4 are based on the Continuing Vocational Training Survey (CVTS) for European countries.
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
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A7. TO WHAT EXTENT DO ADULTS PARTICIPATE EQUALLY IN EDUCATION AND LEARNING?  147
the Russian Federation excluding the population residing in the Moscow municipal area. More detailed information regarding
the data from the Russian Federation as well as that of other countries can be found in the Technical Report of the Survey of
Adult Skills, Second Edition (OECD, 2016[13]).

References

Black, D., B. Noel and Z. Wang (1999), “On-the-job training, establishment size, and firm size: Evidence for
economies of scale in the production of human capital”, Southern Economic Journal, Vol. 66/1, p. 82,
http://dx.doi.org/10.2307/1060836.

[10]

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]

Dench, S. and J. Regan (2000), “Learning in later life: Motivation and impact.”, Research Brief, No. 183,
Department for Education and Employment, https://lemosandcrane.co.uk/resources/DfEE%20%20Learning%20in%20later%20life.pdf.

[4]

European Commission (2019), Achievements under the Renewed European Agenda for Adult Learning: Report of
the ET 2020 Working Group on Adult Learning (2018-2020), European Commission,
http://dx.doi.org/10.2767/583401.

[6]

European Commission (2015), An In-Depth Analysis of Adult Learning Policies and their Effectiveness in Europe,
European Commission, http://dx.doi.org/10.2767/076649.

[7]

European Commission/EACEA/Eurydice (2015), Adult Education and Training in Europe: Widening Access to
Learning Opportunities, Publications Office of the European Union, http://dx.doi.org/10.2797/8002.

[9]

Eurostat (2020), Adult Education Survey, online codes: trng_aes_170 and trng_aes_190, Eurostat website,
https://ec.europa.eu/eurostat (accessed on 4 February 2020).

[8]

OECD (2019), Getting Skills Right: Future-Ready Adult Learning Systems, Getting Skills Right, OECD Publishing,
Paris, https://dx.doi.org/10.1787/9789264311756-en.

[5]

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.

[12]

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.

[13]

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]

Reimers, F. and A. Schleicher (2020), A Framework to Guide an Education Response to the COVID-19 Pandemic
of 2020, OECD, https://read.oecd-ilibrary.org/view/?ref=126_126988-t63lxosohs&title=A-framework-to-guidean-education-response-to-the-Covid-19-Pandemic-of-2020.

[11]

Wlodkowski, R. and M. Ginsberg (2017), Enhancing Adult Motivation to Learn: A Comprehensive Guide for
Teaching All Adults, Jossey-Bass.

[3]

EDUCATION AT A GLANCE 2020 © OECD 2020

148  A7. TO WHAT EXTENT DO ADULTS PARTICIPATE EQUALLY IN EDUCATION AND LEARNING?

Indicator A7 Tables
Table A7.1

Share of employed adults participating in non-formal education and training, by size and sector of
enterprise, job-relatedness and employer sponsorship (2016)

Table A7.2

Annual hours of participation in formal and/or non-formal education and training, by educational
attainment (2016)

Table A7.3

Annual training costs, by size of enterprise (2015)

WEB Table A7.4

Share of enterprises providing continuing vocational training, by size of enterprise and type of training
(2015)

WEB Table A7.5

Share of adults participating in formal and/or non-formal education and training, by educational
attainment (2016)

Cut-off date for the data: 19 July 2020. Any updates on data can be found on line at http://dx.doi.org/10.1787/eag-dataen. More breakdowns can also be found at http://stats.oecd.org/, Education at a Glance Database.
StatLink: https://doi.org/10.1787/888934162926

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A7. TO WHAT EXTENT DO ADULTS PARTICIPATE EQUALLY IN EDUCATION AND LEARNING?  149

Table A7.1. Share of employed adults participating in non-formal education and training, by size and sector of enterprise, jobrelatedness and employer sponsorship (2016)
Adult Education Survey (AES) or Survey of Adult Skills (PIAAC), employed 25-64 year-olds
Adult Education Survey (AES)
Total participation in non-formal education and training (regardless of job-relatedness and employer sponsorship)
Size of enterprise
Total
OECD

(1)

Economic sector

1-9
10-49
50-249
Over 249
employed persons employed persons employed persons employed persons
(2)
(3)
(4)
(5)

Private
(6)

Public
(7)

Countries
Austria
Belgium
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Ireland
Italy
Latvia
Lithuania
Luxembourg
Netherlands1
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United Kingdom

67
51
53
51
48
56
58
56
19
66
59
52
54
33
53
72
65
31
54
57
55
47
63
72
28
55

60
39
43
40
41
44
47
50
15
50
40
45
43
22
41
59
54
20
42
46
49
35
51
64
13
41

67
50
54
49
50
59
59
54
27
67
63
52
56
33
52
73
64
30
56
62
49
50
64
73
34
53

69
58
59
53
49
61
64
60
27 r
75
69
59
63
42
59
76
71
39
63
69
60
59
69
78
45
60

77
62
60
61
59
68
70
66
30 r
76
75
62
66
52
64
m
72
44
71
72
61
66
77
84
52
68

62
46
50
46
41
51
56
52
18
64
55
48
49
28
48
66
61
29
52
56
49
43
58
70
27
49

82
66
64
61
76
70
68
69
29
72
76
66
75
56
66
84
72
48
65
61
78
67
73
84
47
69

Average

53

42

54

60

65

49

67

Survey of Adult Skills (PIAAC)
Total participation in non-formal education and training (regardless of job-relatedness and employer sponsorship)
Size of enterprise

Economic sector
Over 250
employed persons
(5)

Private
(6)

Public2
(7)

OECD

51-250
employed persons
(4)

Countries
Australia3
Canada3
Chile 4
Israel 4
Japan 3
Korea3
Mexico 5
New Zealand4
United States5

65
64
55
57
49
59
42
74
68

49
48
38
42
36
39
24
63
52

59
63
60
56
48
60
46
74
61

72
67
62
62
53
72
57
81
75

81
77
76
71
63
84
67
85
78

54
54
47
44
46
51
31
65
60

82
80
67
72
63
84
57
85
79

Partner

Total
(1)

1-10
11-50
employed persons employed persons
(2)
(3)

Russian Federation* 3

23

14

19

27

33

17

29

Note: Participation in non-formal education and training during previous 12 months. Additional columns showing data for participation in "job-related non-formal education and
training sponsored by the employer", "job-related non-formal education and training not sponsored by the employer", "not job-related non-formal education and training sponsored
by the employer", and "not job-related non-formal education and training not sponsored by the employer" are available for consultation on line (see StatLink below). The average
differs from the one published by Eurostat as this is an unweighted average and the country coverage is different. For data from AES, total participation is not equal to the sum of
the disaggregated categories because the same person can be included in more than one category. This is not the case for data from the Survey of Adult Skills (PIAAC).
1. The category "50-249 employed persons" should be interpreted as "over 50 employed persons". The category "over 249 employed persons" is therefore missing for the Netherlands.
2. Includes non-profit organisations.
3. Year of reference 2012.
4. Year of reference 2015.
5. Year of reference 2017.
* See note on data for the Russian Federation in the Source section.
Source: OECD (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
StatLink 2https://doi.org/10.1787/888934162945

EDUCATION AT A GLANCE 2020 © OECD 2020

150  A7. TO WHAT EXTENT DO ADULTS PARTICIPATE EQUALLY IN EDUCATION AND LEARNING?
Table A7.2. Annual hours of participation in formal and/or non-formal education and training, by educational attainment (2016)
Adult Education Survey (AES) or Survey of Adult Skills (PIAAC), 25-64 year-olds who participated in formal and/or non-formal education
and training activities
Adult Education Survey (AES)
Total
(all levels of educational attainment)

Below upper secondary

Upper secondary
or post-secondary non-tertiary

Tertiary

OECD

Formal
Formal
Formal
Formal
and/or
and/or
and/or
and/or
non-formal Formal Non-formal non-formal Formal Non-formal non-formal Formal Non-formal non-formal Formal Non-formal
education education education education education education education education education education education education
and
and
and
and
and
and
and
and
and
and
and
and
training
training
training
training
training
training
training
training
training
training
training
training
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
(9)
(10)
(11)
(12)
Countries
Austria
Belgium
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Ireland
Italy
Latvia
Lithuania
Luxembourg
Netherlands
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United Kingdom

132
112
51
167
113
156
106
124
141
89
86
115
109
58
125
89
82
145
133
49
180
148
133
129
154
121

457
325
338
370
507
342
519
872
468
322
329
394
375
414 r
298
328
224
464
653
499 r
375
284
462
532
229
169

87
85
35
82
52
78
75
68
63
54
36
89
76
42
78
62
50
78
80
36
142
106
56
71
116
91

81
142
40
186
71
281
86
128
169 r
65
56
60
130
c
83
73
104
218
88
c
55
111
201
112
135
51

c
c
c
498 r
c
508 r
c
c
c
425 r
267 r
c
c
c
197 r
c
c
c
478
c
c
280
600 r
c
106
55 r

78
123
34
74
52
139
81
80
56 r
23
39
60
95
c
58
60
64
51 r
63
c
45
90
78
78
133
48

103
137
36
185
113
170
100
123
111
58
82
120
90
54
114
81
65
129
147
36
139
136
98
103
171
126

531
409
271
446
534
364
522
978
519 r
263
384
419
351
c
275
360 r
241
541
674
c
305
290
460
518
286
171

69
102
29
91
45
72
75
64
52
34
38
85
60
35
80
57
41
67
89
29
111
97
47
57
113
94

175
94
84
135
118
115
116
126
161
155
92
142
121
60
138
95
88
154
171
73
237
168
149
156
160
131

426
283
368
259
489
251
525
747
432
366
314
363
365
391 r
319
325
208
419
734
537 r
441
283
423
538
274
185

109
70
47
75
57
70
75
72
72
101
35
114
87
45
80
65
52
86
90
50
185
116
60
84
103
98

Average

117

406

73

114

m

71

109

421

67

131

395

81

Survey of Adult Skills (PIAAC)
Total
(all levels of educational attainment)

Below upper secondary

Upper secondary
or post-secondary non-tertiary

Tertiary

OECD

Countries
Australia1
Canada1
Chile2
Israel2
Japan1
Korea1
Mexico3
New Zealand2
United States3

m
m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m
m

103
119
121
135
148
248
226
113
140

m
m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m
m

84
78
77
114
136
177
187
115
209

m
m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m
m

108
114
112
126
142
226
236
99
167

m
m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m
m

106
125
145
138
152
271
260
118
120

Partner

Formal
Formal
Formal
Formal
and/or
and/or
and/or
and/or
non-formal Formal Non-formal non-formal Formal Non-formal non-formal Formal Non-formal non-formal Formal Non-formal
education education education education education education education education education education education education
and
and
and
and
and
and
and
and
and
and
and
and
training
training
training
training
training
training
training
training
training
training
training
training
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
(9)
(10)
(11)
(12)

Russian Federation* 1

m

m

117

m

m

132

m

m

137

m

m

113

Note: Participation in formal and/or non-formal education and training during previous 12 months. 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.
3. Year of reference 2017.
* See note on data for the Russian Federation in the Source section.
Source: OECD (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
StatLink 2https://doi.org/10.1787/888934162964

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A7. TO WHAT EXTENT DO ADULTS PARTICIPATE EQUALLY IN EDUCATION AND LEARNING?  151

Table A7.3. Annual training costs, by size of enterprise (2015)
Continuing Vocational Training Survey (CVTS) or national surveys, costs as reported by enterprises
Continuing Vocational Training Survey (CVTS)

OECD

Training costs per participant in equivalent USD
converted using PPP for GDP

Training costs as a share of total labour costs

Total
(5)

10-49
employed
persons
(6)

50-249
employed
persons
(7)

Over 249
employed
persons
(8)

1 688
3 581
743
6 556
1 624
1 414
3 132
2 748
1 803
2 842
2 332
1 678
758
853
2 056
2 785
2 277
1 111
1 115
965
2 042
1 729
1 739
843

1.3
2.4
1.5
2.7
1.8
1.1
2.5
1.4
1.1
1.8
2.2
1.3
0.8
1.1
2.1
2.3
1.8
1.2
1.5
1.6
2.5
1.8
1.6
1.8

1.1
1.7
1.1
1.1
1.1
1.1
1.4
1.0
0.8
1.1
2.0
0.9
0.6
0.9
1.4
1.8
1.9
0.5
1.0
1.3
1.7
1.2
1.5
2.4

1.4
2.4
1.4
1.6
1.7
1.0
2.0
1.2
0.8
1.3
2.0
1.1
0.8
1.0
2.2
2.0
1.7
0.7
1.3
1.3
2.4
1.6
1.6
2.5

1.5
2.8
1.6
4.1
2.5
1.2
3.2
1.5
1.4
2.2
2.4
1.7
1.0
1.3
2.4
2.5
1.9
1.7
2.2
1.9
3.1
2.1
1.6
1.5

2 017

1.7

1.3

1.5

2.1

Total
(1)

10-49
employed
persons
(2)

50-249
employed
persons
(3)

Over 249
employed
persons
(4)

Countries
Austria
Belgium
Czech Republic1
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Ireland
Italy
Latvia
Lithuania
Luxembourg
Netherlands
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
United Kingdom

1 709
3 251
600
4 811
1 690
1 385
2 896
2 314
1 724
2 438
2 331
1 556
736
936
2 086
2 660
1 887
1 007
968
918
1 983
1 600
1 771
985

1 515
2 414
367
2 266
1 503
1 419
2 251
1 359
1 353
1 251
2 467
1 337
657
1 153
2 094
2 422
1 624
699
807
899
1 858
1 220
1 755
1 201

1 943
3 201
544
2 937
1 965
1 296
2 573
1 665
1 632
2 011
2 204
1 461
754
938
2 140
2 520
1 581
786
876
822
1 966
1 630
1 854
1 222

Average

1 843

1 496

1 688

National surveys

OECD

Training costs per participant in equivalent USD
converted using PPP for GDP

Countries
Switzerland

Training costs as a share of total labour costs

Total
(1)

10-49
employed
persons
(2)

50-249
employed
persons
(3)

Over 249
employed
persons
(4)

Total
(5)

10-49
employed
persons
(6)

50-249
employed
persons
(7)

Over 249
employed
persons
(8)

1 320

1 256

1 357

1 331

0.8

0.6

0.6

0.9

Note: Training costs during previous 12 months. Note that the average differs from the one published by Eurostat as this is an unweighted average and the country coverage
is different.
1. Data were mainly collected on line and via interactive PDF forms, only small part of questionnaires was distributed in a paper form. See metadata for more information
at https://ec.europa.eu/eurostat/cache/metadata/EN/trng_cvt_esqrs_cz.htm.
* See note on data for the Russian Federation in the Source section.
Source: OECD (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
StatLink 2https://doi.org/10.1787/888934162983

EDUCATION AT A GLANCE 2020 © OECD 2020

| 153

Chapter B. Access to
education, participation and
progress

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154  B1. WHO PARTICIPATES IN EDUCATION?

Indicator B1. Who participates in
education?
Highlights


Between 2010 and 2018, policies to increase access to early childhood education and care and participation in
upper secondary education have widened the age range of full enrolment (the ages at which at least 90% of the
population are enrolled in education) in 10 OECD countries. The largest increases in the duration of full enrolment
were observed in Belgium, Korea, Norway and Portugal.



A small number of countries have significant levels of enrolment in post-secondary non-tertiary and short-cycle
tertiary programmes. For example, the enrolment rate for post-secondary non-tertiary education reaches up to
5% among 15-19 year-olds in Germany, Greece and Hungary and 9% among 20-24 year-olds in Germany.
Enrolment levels in short-cycle tertiary programmes reach at least 10% among 15-19 year-olds in Austria, Korea
and the Russian Federation and among 20-24 year-olds in Chile, Korea, Turkey and the United States.



The share of upper secondary students enrolled in vocational education and training (VET) averages 37% among
15-19 year-olds, across OECD countries, and increases to 62% of upper secondary students aged 20-24 and
61% among older upper secondary students.

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 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.

EDUCATION AT A GLANCE 2020 © OECD 2020

B1. WHO PARTICIPATES IN EDUCATION?  155

Figure B1.1. Share of upper secondary students enrolled in vocational education and training
programmes, by age group (2018)
Full- and part-time students enrolled in public and private institutions
Age 25 and older
Age 20 to 24
Age 15 to 19

%
100
90
80
70
60
50
40
30
20

Israel
Japan

Poland
Korea

Colombia

Turkey

Mexico
Chile

Brazil
Saudi Arabia

Latvia
Russian Federation 3

Costa Rica

Hungary
Portugal

Sweden
Lithuania

OECD average

South Africa 2
Iceland

Denmark
Norway

EU23 average

Luxembourg
Estonia

Spain

Austria
Switzerland

Italy1
Slovak Republic

Slovenia

Australia
New Zealand

Germany
Finland

Czech Republic

Ireland
Netherlands

0

United Kingdom
France

10

1. Includes post-secondary non-tertiary programmes.
2. Year of reference 2017.
3. Excludes part of upper secondary vocational programmes.
Countries and economies are ranked in descending order of the highest share of upper secondary enrolment in vocational education and training programmes among
students aged 25 years and older.
Source: OECD (2020), Tables B1.2 and B1.3. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2https://doi.org/10.1787/888934163192

Other findings


Enrolment rates of 15-19 year-olds in upper secondary general programmes range from 19% in Austria and
Colombia to 50% or more in Canada, Chile, Iceland, Ireland, New Zealand, Saudi Arabia and the United States.
In contrast, enrolment rates in upper secondary vocational education and training range from 5% or less in
Australia, the United States and OECD partner countries like Argentina, Brazil, Saudi Arabia and South Africa (in
Argentina and the United States VET programmes are not offered at upper secondary level), to over 50% in
the Czech Republic and Slovenia.



Enrolment in long-cycle tertiary programmes – bachelor’s, master’s and doctoral or equivalent– is most common
in the 20-24 year-old age group. The OECD average enrolment rate at this level reaches 30% among 20-24 yearolds, compared to 9% among 15-19 year-olds and 2.3% among the older population.

EDUCATION AT A GLANCE 2020 © OECD 2020

156  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 andSouth 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 the age of 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 partial
compulsory education (i.e. students must attend some form of education for at least two days a week) from the age of 16 until
they are 18 or 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. The period of full enrolment lasts for between 11
and 16 years in most countries and reaches 17 years in Norway. It is shorter in Colombia, Costa Rica, Mexico, the Slovak
Republic and Turkey, and in partner countries such as Indonesia and Saudi Arabia (Table B1.1).
In almost all OECD countries, the enrolment rate among 4-5 year-olds in education exceeded 90% in 2018. Enrolment at an
early age is relatively common in OECD countries, with about one-third achieving full enrolment for 3-year-olds. Iceland,
Korea and Norway also have full enrolment for 2-year-olds (see Indicator B2). In other OECD countries, full enrolment is
achieved for children at the age of 5, but this rises to the age of 6 in Finland and Turkey and 7 or later in Colombia,
the Slovak Republic and, among partner countries, in Saudi Arabia and the Russian Federation (Box B1.1).
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. 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%),
Indonesia (93%) and the Slovak Republic (95%) (Table B1.1).

Box B1.1. Evolution of full enrolment between 2010 and 2018
Education systems in all OECD countries have provided universal access to basic education in past decades, and
participation is now expanding to upper and lower levels of education. OECD countries have implemented reforms to
support full enrolment and increase enrolment rates at all ages. As of 2018, full enrolment covers a 14-year-long period
on average across OECD countries. In 10 out of the 23 OECD countries with data available, the age range for full
enrolment was longer in 2018 than in 2010 (Figure B1.2), with Belgium, Korea, Norway and Portugal recording the largest
increases. Access to upper secondary education is becoming universal in most countries, as is pre-primary education
(Figure B1.2).
Countries have focused on expanding access to early childhood education and care by improving equity in the participation
of very young children (OECD, 2017[2]); this lowers further the youngest age at which full enrolment begins. More and
more, early childhood education and care policies aim to reach high enrolment rates at the age of 2 or 3 (see Indicator B2).
Between 2010 and 2018, seven countries succeeded in adding at least one additional year of full enrolment for young
children. The largest extension among young children was observed in Korea where the age at which full enrolment began
changed from 5 years old to 2 over this period (Figure B1.2).
The expansion of upper secondary education is driven by increasing labour-market demand, more flexible curricula, the
promotion and reshaping of vocational education and training programmes (see Indicator B7), and governments’ efforts
to expand access to education to the entire population. Making sure that young people stay in education, ensuring
teenagers have access to and participate in education, and reducing the risk of dropping out were a priority in the last
decade in the 7 countries (out of 23 with available data) where the upper age limit for full enrolment was higher in 2018
than in 2010 (Figure B1.2). Among these countries, the upper limit of full enrolment increased to 18 years old from 16 years
in Belgium and from 17 years in Norway.

EDUCATION AT A GLANCE 2020 © OECD 2020

B1. WHO PARTICIPATES IN EDUCATION?  157

Figure B1.2. Age range in which at least 90% of the population are enrolled (2010 and 2018)
Highest age (2018)
Lowest age (2018)
Lowest – highest age (2010)

Age
20
18
16
14
12
10
8
6
4

0

Norway
Belgium
Sweden
Latvia
Slovenia
Lithuania
Poland
Finland
Korea
Denmark
France
Germany
Ireland
Israel
Italy
Spain
United Kingdom
Estonia
EU23 average
Japan
Netherlands
OECD average
Portugal
Chile
Czech Republic
Greece
Switzerland
United States
Russian Federation
Iceland
Austria
Brazil
Hungary
Luxembourg
New Zealand
Argentina1
Australia
Canada 2
Slovak Republic
Turkey
Costa Rica
Mexico
Indonesia
Saudi Arabia
Colombia

2

1. Year of reference 2017.
2. Excludes post-secondary non-tertiary education.
Countries and economies are ranked in descending order of the highest age at which at least 90% of the population are enrolled.
Source: OECD/UIS/Eurostat (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2https://doi.org/10.1787/888934163211

Participation of 15-19 year-olds in education
In recent years, countries have increased the diversity of their upper secondary programmes. This diversification is both a
response to the growing demand for upper secondary education and a result of changes in curricula and labour-market needs.
Curricula have gradually evolved from separating general and vocational programmes to offering more comprehensive
programmes that include both types of learning, leading to more flexible pathways into further education or the labour market.
Overall, 84% of the population are enrolled in education between the age of 15 and 19 on average across OECD countries.
The share is highest in Belgium, the Czech Republic, Ireland, Latvia, Lithuania, the Netherlands, Poland, Slovenia and
Sweden, where the overall enrolment rate reaches at least 90%, and is between 80% and 90% in half of the countries with
data available. Enrolment levels for 15-19 year-olds were 1 percentage point higher in 2018 than in 2010, with the largest
increases observed in Chile, Mexico, Poland, Spain and the United Kingdom (5 percentage points or more). Enrolment levels
did not improve in all OECD countries: for example, they fell by more than 3 percentage points among 15-19 year-olds in
Estonia, Hungary and Lithuania (Table B1.1).
The share of students enrolled in each education level and at each age illustrates the different educational systems and
pathways in countries. As they get older, students move on to higher educational levels or types of programmes, and the
enrolment rate in upper secondary education (both general and vocational) decreases. The main component of enrolment
among 15-19 year-olds is related to upper secondary education; none of the OECD and partner countries have greater
enrolment in lower secondary education among this age group (OECD average: 14%) than in upper secondary programmes
(OECD average: 58%). However, lower secondary education represents a significant share of enrolment for 15-19 year-olds
in Denmark, Germany and Lithuania, where enrolment rates at this level reach at least 30% (Figure B1.3). At least 70% of all

EDUCATION AT A GLANCE 2020 © OECD 2020

158  B1. WHO PARTICIPATES IN EDUCATION?
15-19 year-olds in the Czech Republic, Italy and Slovenia are enrolled in upper secondary education while the share is as
low as 35% in Costa Rica, 27% in Colombia and 26% in the Russian Federation, although this figure excludes some of the
Russian students enrolled in upper secondary vocational education (Figure B1.3).

Figure B1.3. Enrolment rates of 15-19 year-olds, by level of education (2018)
Full- and part-time students enrolled in secondary and tertiary programmes in public and private institutions

%
100

Lower secondary
Upper secondary general programmes
Upper secondary vocational programmes
Upper secondary (no breakdown)

Post-secondary non-tertiary
Short-cycle tertiary
Bachelor’s, master’s, doctoral or equivalent

90
80
70
60
50
40
30
20

0

Belgium
Slovenia
Lithuania
Latvia
Ireland
Netherlands1
Poland
Czech Republic
Sweden
Portugal
Estonia
EU23 average
Russian Federation2
Norway
Spain
Iceland
Finland
France
Germany
Denmark
Greece
Switzerland
Italy3
Korea
OECD average
United States
Australia
Slovak Republic
Hungary
United Kingdom
Chile
New Zealand1
Austria
Indonesia1
South Africa1, 4
Canada 5
Luxembourg
Turkey
Saudi Arabia 6
Brazil
Israel
Argentina4
Mexico
Colombia
Costa Rica 6

10

1. Short-cycle tertiary programmes included with bachelor's, master's and doctoral programmes.
2. Post-secondary non-tertiary and short-cycle tertiary programmes include part of upper secondary vocational programmes.
3. Upper secondary vocational programmes include post-secondary non-tertiary education.
4. Year of reference 2017.
5. Excludes post-secondary non-tertiary education and short-cycle tertiary private institutions.
6. Excludes tertiary programmes.
Countries and economies are ranked in descending order of the enrolment rate of 15-19 year-olds in secondary to short-cycle tertiary programmes.
Source: OECD (2020), Table B1.2. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2https://doi.org/10.1787/ 888934163230

Depending on the structure of the educational system, students across OECD countries may enrol in general or vocational
upper secondary programmes. 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, while vocational education and training (VET) programmes prepare participants for direct entry into
specific occupations without further training (OECD, 2018[3]). On average across OECD countries, the enrolment rates among
15-19 year-olds in upper secondary general education reach 37%, while the rate for upper secondary vocational education
and training is 22%. Nearly two-thirds of upper secondary students (63%) across OECD countries are enrolled in general
programmes, while the remainder (37%) are enrolled in VET. There are only nine countries where the majority of
15-19 year-old upper secondary students are enrolled in vocational programmes. Among those, 7 out of 10 students are
enrolled in VET programmes in the Czech Republic. In the remaining countries general programmes account for the most

EDUCATION AT A GLANCE 2020 © OECD 2020

B1. WHO PARTICIPATES IN EDUCATION?  159
significant portion of enrolment in upper secondary education, with 8 or more in every 10 students enrolled in general
programmes in 11 of the OECD and partner countries with data available (Figure B1.1).
Enrolment rates in upper secondary general programmes for 15-19 year-olds range from 19% in Austria and Colombia to
50% or more in Canada, Chile, Iceland, Ireland, New Zealand, Saudi Arabia and the United States. This compares to
enrolment rates in vocational upper secondary programmes that range from 5% or less in Australia, the United States and
OECD partner countries like Argentina, Brazil, Saudi Arabia and South Africa (in Argentina and the United States VET
programmes are not offered at upper secondary level) to over 50% in the Czech Republic and Slovenia (Table B1.2). Within
the age group of 15-19 year-olds enrolment rates may be higher for some specific ages (or for narrower age groups),
especially for countries where vocational programmes have a shorter duration.
Not all OECD and partner countries offer both post-secondary non-tertiary and short-cycle tertiary programmes, but all OECD
countries offer programmes in at least one of these two educational levels. Post-secondary non-tertiary programmes provide
learning experiences that build on secondary education and prepare for labour-market entry and/or tertiary education. The
content is broader than secondary but not as complex as tertiary education. Short-cycle tertiary programmes refer to first
tertiary programmes that are typically practically based, occupationally specific and prepare for labour-market entry. These
programmes may also provide a pathway to other tertiary programmes (UNESCO-UIS, 2012[4]). Post-secondary non-tertiary
and short-cycle tertiary programmes often, but not always, represent shorter vocational or technical alternatives to higher
education. Post-secondary non-tertiary enrolment rates among 15-19 year-olds reach up to 5% in Germany, Greece and
Hungary and short-cycle tertiary enrolment rates for this age group peak at 10% in Austria and Korea and 25% in
the Russian Federation, although this latter figure includes a small share of upper secondary vocational students. However,
the average enrolment rate of 15-19 year-olds in these two educational levels combined remains low, at 3% on average
across OECD countries (Figure B1.3).
Enrolment in long-cycle tertiary education, which includes bachelor’s, master’s and doctoral or equivalent programmes, is
limited among the 15-19 year-old population: only 9% of young people in this age group on average across OECD countries.
However, enrolment rates do vary significantly at this level and range from 1% in Denmark, Iceland and Luxembourg to 16%
in Ireland and the United Kingdom, 18% in Belgium, and 20% or more in Greece and Korea, where enrolment in tertiary
programmes typically starts at an earlier age (see Indicator B4).

Participation of 20-24 year-olds in education
The transition from secondary to tertiary education is characterised by a drop in enrolment rates on average. The 20-24 yearold age group does not include any years of compulsory education (in contrast to ages 15 to 19) and is the one that most
typically corresponds to the ages of enrolment in tertiary education in OECD countries. The average enrolment rate of
20-24 year-olds across OECD countries is about half that of 15-19 year-olds: only 41% of the population aged 20 to 24 are
enrolled in education. Enrolment rates among 20-24 year-olds are highest in Greece and Slovenia, where 55% or more are
in education. In contrast, the enrolment rate is as low as 21% in Israel (partly related to the compulsory nature of military
service at the age of 18) and 20% in Luxembourg (where studying abroad in neighbouring countries is relatively common,
see Indicator B6). Enrolment levels overall have not changed between 2010 and 2018 on average across the OECD
(remaining at 41%), but enrolment levels have increased significantly in a number of countries, especially in Ireland and Spain,
where the enrolment rate was at least 11 percentage points higher in 2018 than in 2010. At the other end of the spectrum,
the largest drop in enrolment in the same period was observed in Iceland, Lithuania and New Zealand where rates fell by
8 percentage points or more (Table B1.1).
In general, across OECD countries 20-24 year-old students are most commonly enrolled in tertiary education, typically in
long-cycle programmes, but not entirely. On average across OECD countries, 30% of the population in this age group are
enrolled in long-cycle tertiary education and this share ranges from 7% in Luxembourg to 40% or more in Greece, Korea,
Lithuania, the Netherlands and Poland. Enrolment levels in post-secondary non-tertiary and short-cycle tertiary programmes
are generally lower and reach 5% of 20-24 year-olds on average across the OECD for these two levels combined. However,
short-cycle tertiary enrolment rates reach 10% or more in Chile, Korea, Turkey and the United States. Enrolment rates in
post-secondary non-tertiary programmes are below 10% in all OECD and partner countries and peak at 9% for Germany
(Table B1.2).
Only 4% of 20-24 year-olds are enrolled in upper secondary vocational programmes on average across the OECD, compared
to 22% of 15-19 year-olds. Enrolment rates of 20-24 year-olds for these programmes exceed 10% only in Denmark, Finland,
the Netherlands and Slovenia. Upper secondary general programmes play a smaller role in the education of 20-24 year-olds:

EDUCATION AT A GLANCE 2020 © OECD 2020

160  B1. WHO PARTICIPATES IN EDUCATION?
the OECD average enrolment rate reaches only 2% and the highest values are 8% in Iceland and Sweden and 11% in
South Africa. Unlike among 15-19 year-olds, vocational programmes are strongly preferred by 20-24 year-old upper
secondary students: on average across the OECD, 62%of students in this age group and at this level are enrolled in vocational
programmes, compared to 37% among 15-19 year-old students (a 25 percentage-point increase). The largest jumps in the
share of vocational upper secondary students between 15-19 year-olds and 20-24 year-olds are observed in Australia,
France, Ireland, New Zealand and the United Kingdom; in these countries, VET programmes form an important part of adult
education (Figure B1.1).

Participation of adults aged 25 and older in education
Enrolment in education is less common among the older population, as students graduate and transition to the labour market:
the OECD average enrolment rates in all levels of education reach 16% among 25-29 year-olds, 6% among 30-39 year-olds
and 2% among 40-64 year-olds. The highest enrolment rates among 25-29 year-olds are in Denmark, Finland, Sweden and
Turkey, where more than 25% of the population in this age group are still in education. Enrolment levels are lower among
30-39 year-olds and reach at least 10% only in Australia, Finland, Greece, Iceland, Sweden and Turkey. The highest
enrolment rate among 40-64 year-olds is 6% and is observed in Australia and Finland (Table B1.1).

Figure B1.4. Enrolment rates of the population aged 25 years or older, by level of education (2018)
Full- and part-time students enrolled in secondary and tertiary programmes in public and private institutions

%
10

Lower secondary
Upper secondary general programmes
Upper secondary vocational programmes
Upper secondary (no breakdown)

Post-secondary non-tertiary
Short-cycle tertiary
Bachelor’s, master’s, doctoral or equivalent

9
8
7
6
5
4
3
2

0

Turkey
Finland
Australia
Iceland
Sweden
Ireland
New Zealand1
Denmark
Norway
Greece
Israel
Brazil
Belgium
Chile
OECD average
Colombia
Mexico
United States
Estonia
Netherlands1
Austria
EU23 average
Latvia
Spain
United Kingdom 2
Switzerland
Germany
South Africa1, 3
Lithuania
Hungary
Poland
Portugal
Canada4
Czech Republic
Slovenia
Italy5
Costa Rica6
Indonesia1
Korea
Slovak Republic
Russian Federation
Luxembourg
France
Argentina3, 6
Saudi Arabia 6

1

1. Short-cycle tertiary programmes included with bachelor's, master's and doctoral programmes.
2. Short-cycle tertiary programmes include a small number of bachelor's professional programmes.
3. Year of reference 2017.
4. Excludes post-secondary non-tertiary education and short-cycle tertiary private institutions.
5. Upper secondary vocational programmes include post-secondary non-tertiary education.
6. Excludes tertiary programmes.
Countries and economies are ranked in descending order of the enrolment rate of students aged 25 years and older in secondary to tertiary education programmes.
Source: OECD (2020), Table B1.3. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2https://doi.org/10.1787/888934163249

EDUCATION AT A GLANCE 2020 © OECD 2020

B1. WHO PARTICIPATES IN EDUCATION?  161
Long-cycle tertiary education has the most significant enrolment rates among those aged over 24, even though enrolment
levels are much lower compared to younger age groups. On average across OECD countries, 0.5% of the population aged
over 24 are enrolled in upper secondary vocational education, 0.2% in post-secondary non-tertiary education, 0.4% in shortcycle tertiary programmes and 2.3% in bachelor’s, master’s and doctoral or equivalent programmes (Figure B1.4). Enrolment
rates in long-cycle tertiary education range from 1% or less in France, Luxembourg, the Slovak Republic and the Russian
Federation to 4.5% in Iceland and 4.9% in Turkey. Enrolment of adults aged 25 and older in short-cycle tertiary programmes
reaches up to 1.2% in Australia, 1.3% in the United States and 3% in Turkey. Some older students also enrol in post-secondary
non-tertiary education, with the highest enrolment rate observed in Australia (1.3%).
The highest upper secondary vocational enrolment rates found among those aged over 24 are 1.9% in Australia and 3.3% in
Finland. On average across OECD countries, VET programmes represent the great majority of enrolment among older adults
at upper secondary level and accounts for 61% of all upper secondary students over 24 enrolled in general and vocational
programmes combined. This share reaches or exceeds 90% in 14 countries and is higher than among 20-24 year-olds in the
majority of countries. In Iceland, South Africa and Spain, the share of upper secondary students enrolled in VET programmes
is at least 19 percentage points higher among those aged 25 and over than among 20-24 year-olds (Figure B1.1).

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.

Methodology
Except where otherwise noted, figures are based on head counts, because of the difficulty for some countries to quantify parttime 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[3]) and Annex 3 for country-specific notes
((https://doi.org/10.1787/69096873-en).

EDUCATION AT A GLANCE 2020 © OECD 2020

162  B1. WHO PARTICIPATES IN EDUCATION?

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/10.1787/69096873-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, 2020[5]).

References

OECD (2020), “Regional education”, OECD Regional Statistics (database), https://dx.doi.org/10.1787/213e806cen (accessed on 27 July 2020).

[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), 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 (2017), Starting Strong 2017: Key OECD Indicators on Early Childhood Education and Care, Starting
Strong, OECD Publishing, Paris, https://dx.doi.org/10.1787/9789264276116-en.

[2]

UNESCO-UIS (2012), International Standard Classification of Education ISCED 2011, http://www.uis.unesco.org.

[4]

Indicator B1 Tables
Table B1.1

Enrolment rates by age group (2005, 2010 and 2018)

Table B1.2

Enrolment rates of 15-19 and 20-24 year-olds in secondary and tertiary education, by level of education
(2018)

Table B1.3

Enrolment rates of students aged 25 and older in secondary and tertiary education, by level of education
(2018))

Cut-off date for the data: 19 July 2020. Any updates on data can be found on line at http://dx.doi.org/10.1787/eag-dataen. More breakdowns can also be found at http://stats.oecd.org/, Education at a Glance Database.
StatLink: https://doi.org/10.1787/888934163116

EDUCATION AT A GLANCE 2020 © OECD 2020

B1. WHO PARTICIPATES IN EDUCATION?  163

Table B1.1. Enrolment rates by age group (2005, 2010 and 2018)
Students in full-time and part-time programmes in both public and private institutions
Students as a percentage of the population of a specific age group
Number of years
Age range
for which
at which
at least 90%
at least 90%
of the population of the population
of school age
of school age
are enrolled
are enrolled
6 to 14 15 to 19 20 to 24 25 to 29 30 to 39 40 to 64 15 to 19 20 to 24 25 to 29 15 to 19 20 to 24 25 to 29

Partners

OECD

2018
Countries
Australia
Austria
Belgium
Canada1
Chile
Colombia
Costa Rica
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan 2
Korea
Latvia
Lithuania
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey 3
United Kingdom
United States

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

2010
(10)

(11)

(12)

2005
(13)

(14)

12
13
16
12
13
5
10
13
15
14
13
15
15
13
13
15
15
15
15
14
15
15
14
13
10
14
13
17
14
14
10
15
15
16
13
10
15
13

5-16
4-16
3-18
5-16
5-17
9-13
5-14
5-17
3-17
4-17
6-18
3-17
3-17
5-17
4-16
2-16
3-17
3-17
3-17
4-17
2-17
4-18
5-18
4-16
4-13
4-17
4-16
2-18
5-18
4-17
7-16
4-18
3-17
3-18
5-17
6-15
3-17
5-17

100
99
99
100
98
88
95
98
100
97
98
100
99
97
95
99
100
97
98
100
99
99
100
97
100
100
99
99
96
99
94
99
97
99
100
100
98
100

84
79
94
77
82
58
m
90
86
88
87
87
86
86
83
87
93
66
85
m
84
93
94
76
62
92
80
87
93
89
84
94
87
90
85
71
83
84

50
35
49
33
44
25
m
41
53
38
50
38
49
55
35
43
45
21
37
m
49
46
46
20
26
53
34
46
50
37
32
58
48
45
40
52
32
36

24
18
14
10
15
11
m
10
29
14
31
8
21
22
10
23
13
19
13
m
8
16
13
7
11
17
13
19
11
10
6
12
16
27
17
32
10
13

14
6
7
4
6
6
m
3
9
7
17
2
5
10
4
10
7
6
3
m
2
6
6
2
4
5
9
8
3
4
2
2
6
16
5
14
6
7

6
1
3
1
1
2
m
1
2
2
6
0
0
3
1
4
5
2
1
m
1
1
1
0
2
2
4
3
1
2
1
1
2
5
1
3
2
2

83
78
92
76
76
m
m
91
85
91
87
84
89
m
92
88
91
65
85
m
85
94
98
m
51
90
80
87
84
85
m
94
82
86
85
m
76
80

45
33
52
36
37
m
m
39
49
44
53
34
45
m
41
51
32
24
35
m
54
44
56
m
19
47
42
48
m
37
m
54
37
44
34
m
27
38

19
15
17
m
13
m
m
m
27
12
31
6
17
m
11
26
9
21
m
m
10
11
16
m
5
12
19
19
m
14
m
16
12
28
14
m
m
15

82
m
94
m
m
m
m
91
84
91
87
84
88
m
87
85
89
m
82
m
87
m
98
m
48
m
74
89
84
74
m
93
78
m
83
m
m
77

44
m
42
m
m
m
m
34
48
40
55
32
41
m
38
49
32
m
33
m
46
m
49
m
17
m
41
46
m
35
m
50
34
m
31
m
m
32

21
m
15
m
m
m
m
m
27
12
30
7
18
m
13
25
10
m
m
m
9
m
17
m
5
m
20
19
m
12
m
17
11
m
13
m
m
13

14

4-17

98

84

41

16

6

2

84

41

16

84

m

m

87

43

16

86

43

16

84

m

m

OECD average
Average for countries
with available data
for all reference years
EU23 average

14

4-17

98

88

43

15

6

2

88

42

m

m

m

m

Argentina 4
Brazil
China
India
Indonesia
Russian Federation
Saudi Arabia
South Africa

12
13
m
m
9
11
7
m

5-16
4-16
m
m
5-13
7-17
7-13
m

100
99
m
m
93
98
95
m

75
69
m
m
78
87
m
m

38
29
m
m
26
37
m
m

20
15
m
m
5
6
m
m

m
8
m
m
2
2
m
m

m
3
m
m
1
0
m
m

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

m
m
m
m
m
82
m
m

m
m
m
m
m
34
m
m

m
m
m
m
m
13
m
m

G20 average

m

m

m

m

m

m

m

m

m

m

m

m

m

m

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 2017.
Source: OECD/UIS/Eurostat (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2https://doi.org/10.1787/888934163135

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164  B1. WHO PARTICIPATES IN EDUCATION?
Table B1.2. Enrolment rates of 15-19 and 20-24 year-olds in secondary and tertiary education, by level of education (2018)
Students enrolled in full-time and part-time programmes in both public and private institutions
Enrolment rate

All programmes

General
programmes

Vocational
programmes

Post-secondary nontertiary

Short-cycle tertiary

Bachelor's, master's and
doctoral or equivalent

Lower secondary

All programmes

General
programmes

Vocational
programmes

Post-secondary nontertiary

Short-cycle tertiary

Bachelor's, master's and
doctoral or equivalent

Age 20 to 24

Lower secondary
Partners

OECD

Age 15 to 19

Share of upper
secondary
students
enrolled in
vocational
programmes

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

(13)

(14)

(15)

(16)

Countries
Australia
Austria
Belgium
Canada1
Chile
Colombia
Costa Rica
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy2
Japan
Korea
Latvia
Lithuania
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United Kingdom3
United States

26
2
5
0
3
18
22
12
33
26
22
4
30
3
4
19
15
4
1
0
1
24
38
13
7
24
4
19
21
12
12
2
10
21
16
1
7
8

39
61
69
59
62
27
35
73
52
56
62
62
46
57
69
67
59
57
75 d
58
54
60
43
62
44
53
58
64
63
61
65
80
59
65
65
59
59
56

33
19
31
58
50
19
23
22
42
40
33
39
30
45
44
58
52
34
35
45
45
37
32
27
28
25
52
36
28
38
22
28
46
44
26
30
36
56

5
42
m
m
12
8
11
51
9
16
29
23
15
m
25
9
6
24
41 d
13
10
23
10
35
16
29
7
28
35
23
44
53
13
20
39
29
23
a

1
1
1
m
a
0
a
m
a
0
0
0
5
5
5
0
2
0
x(2, 4)
0
a
1
2
0
a
a
3
0
1
0
1
a
0
0
0
a
a
1

3
10
0
5
5
5
m
0
0
a
a
7
0
a
0
0
1
3
0
m
10
1
a
0
1
x(7)
x(7)
0
0
1
0
1
4
0
0
4
1d
7

15
5
18
13
12
8
m
5
1
5
3
13
6
21
5
1
16
2
8
m
20
7
12
1
10
15
15
4
8
14
5
10
14
3
3
7
16
11

2
0
2
0
0
1
4
0
0
0
0
0
1
1
0
0
1
0
0
m
0
0
1
1
3
0
0
0
0
0
0
0
1
1
0
0
1
0

8
4
5
2
2
2
6
5
15
7
14
3
9
2
4
15
5
0
2d
m
0
5
2
10
2
13
3
9
4
5
2
13
7
12
11
6
6
0

1
0
2
1
2
1
4
0
5
2
1
0
1
0
2
8
0
0
0
m
0
2
1
1
1
0
0
2
3
2
0
1
2
8
3
4
0
0

7
4
m
m
0
0
2
5
10
4
13
3
8
m
2
7
5
0
2d
m
0
2
1
9
1
13
3
7
1
3
2
12
5
4
8
1
6
a

2
1
3
m
a
0
a
m
a
2
0
0
9
6
6
1
3
1
x(9, 11)
m
a
2
4
1
a
a
3
0
6
0
1
a
0
1
1
a
a
2

4
2
1
6
10
5
m
0
4
a
a
5
0
a
1
0
1
3
0
m
10
5
a
2
1
x(14)
x(14)
1
0
1
1
6
8
1
0
16
2d
11

34
27
38
24
31
17
m
36
33
30
35
30
30
46
25
26
35
16
34
m
40
34
40
7
21
40 d
28 d
36
40
30
28
39
32
26
28
30
23
23

14
68
m
m
20
29
32
70
18
29
47
36
33
m
36
14
11
41
54 d
22
18
39
24
57
37
54
11
43
56
38
67
65
22
32
60
50
39
a

86
89
m
m
13
6
30
96
65
69
93
96
89
m
43
45
98
7
88 d
m
22
53
54
92
27
97
90
77
19
65
88
94
74
32
75
24
100
a

OECD average
EU23 average

14
15

58
61

37
35

22
27

1
1

2
1

9
9

1
1

6
7

2
2

4
5

2
2

3
2

30
32

37
43

62
76

Argentina4
Brazil
China
India
Indonesia
Russian Federation5
Saudi Arabia
South Africa4

17
14
m
m
29
20
7
28

48
46
m
m
45
26
62
44

48
42
m
m
25
20
62
43

a
4
m
m
20
7
1
1

a
1
m
m
a
0d
0
1

m
0
m
a
x(7)
25 d
m
x(7)

m
7
m
m
4d
15
m
4d

3
2
m
m
0
0
2
1

3
5
m
m
3
1
4
15

3
5
m
m
2
0
4
11

a
1
m
m
1
1
0
4

a
2
m
m
a
0d
0
5

m
0
m
a
x(14)
5d
m
x(14)

m
21
m
m
22 d
31
m
9d

a
9
m
m
44
25
1
2

a
11
m
m
37
61
4
27

G20 average

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

Upper secondary

Upper secondary

Age
Age
15 to 19 20 to 24

1. Excludes private institutions at short-cycle tertiary level.
2. Upper secondary vocational programmes include post-secondary non-tertiary programmes.
3. Short-cycle tertiary programmes include a small number of bachelor's professional programmes; upper secondary figures are split into general and vocational based on
institution type.
4. Year of reference 2017.
5. Post-secondary non-tertiary and short-cycle tertiary programmes include part of upper secondary vocational programmes.
Source: OECD/UIS/Eurostat (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2https://doi.org/10.1787/888934163154

EDUCATION AT A GLANCE 2020 © OECD 2020

B1. WHO PARTICIPATES IN EDUCATION?  165

Table B1.3. Enrolment rates of students aged 25 and older in secondary and tertiary education, by level of education (2018)
Students enrolled in full-time and part-time programmes in both public and private institutions
Enrolment rate

Partners

OECD

Upper secondary

Share of upper
secondary
students
enrolled in
vocational
programmes
(8)

Lower
secondary
(1)

All
programmes
(2)

General
programmes
(3)

Vocational
programmes
(4)

Post-secondary
non-tertiary
(5)

Short-cycle
tertiary
(6)

Bachelor's,
master's
and doctoral
or equivalent
(7)

Countries
Australia
Austria
Belgium
Canada 1
Chile
Colombia
Costa Rica
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy 2
Japan
Korea
Latvia
Lithuania
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United Kingdom 3
United States

0.6
0.0
0.8
0.0
0.1
0.3
0.7
0.0
0.0
0.1
0.1
0.0
0.0
0.1
0.0
0.0
1.1
0.0
0.1
m
0.0
0.0
0.2
0.0
1.6
0.0
0.0
0.0
0.0
0.2
0.0
0.0
0.2
0.5
0.0
0.3
0.2
0.0

2.0
0.2
1.6
0.2
0.3
0.2
0.7
0.2
1.3
0.7
3.4
0.1
0.2
0.0
0.5
1.6
1.8
0.0
0.1 d
m
0.0
0.3
0.2
0.3
0.5
1.0
1.2
0.5
0.1
0.5
0.1
0.3
0.6
1.7
0.3
1.0
1.0
0.0

0.1
0.0
0.7
0.1
0.3
0.2
0.5
0.0
0.3
0.2
0.1
0.0
0.0
0.0
0.3
0.5
0.0
0.0
0.0
m
0.0
0.2
0.1
0.0
0.4
0.0
0.1
0.1
0.1
0.3
0.0
0.0
0.0
0.9
0.0
0.8
0.0
0.0

1.9
0.2
m
m
0.0
0.0
0.2
0.2
0.9
0.5
3.3
0.1
0.2
m
0.2
1.1
1.8
0.0
0.1 d
m
0.0
0.1
0.1
0.2
0.1
1.0
1.2
0.3
0.0
0.2
0.1
0.3
0.6
0.8
0.2
0.1
1.0
a

1.3
0.1
0.4
m
a
0.0
a
m
a
0.3
0.6
0.0
0.2
0.3
0.3
0.5
0.3
0.1
x(2, 4)
m
a
0.1
0.5
0.1
a
a
0.7
0.2
0.3
0.0
0.2
a
0.1
0.2
0.1
a
a
0.3

1.2
0.2
0.1
0.4
1.1
0.9
m
0.0
0.5
a
a
0.1
0.0
a
0.0
0.2
0.4
0.4
0.0
m
0.2
0.6
a
0.0
0.0
x(7)
x(7)
0.1
0.0
0.0
0.0
0.2
0.4
0.3
0.0
3.0
0.4 d
1.3

3.2
2.8
1.1
1.5
2.5
2.2
m
1.4
3.4
2.3
4.3
1.0
2.4
4.2
1.4
4.5
1.9
4.0
1.4
m
1.2
2.0
1.7
0.8
1.5
2.4 d
3.4 d
3.9
1.7
1.3
1.0
1.1
1.7
3.2
2.4
4.9
1.3
2.1

96
90
m
m
9
0
30
99
75
77
98
100
98
m
41
67
100
a
94 d
m
a
28
42
82
10
99
94
73
0
36
94
98
94
49
89
14
100
a

OECD average
EU23 average

0.2
0.2

0.7
0.7

0.2
0.2

0.5
0.6

0.2
0.2

0.4
0.1

2.3
2.0

61
76

Argentina 4
Brazil
China
India
Indonesia
Russian Federation 5
Saudi Arabia
South Africa 4

0.4
0.4
m
m
0.0
0.0
0.0
0.2

0.2
0.6
m
m
0.0
0.0
0.2
0.5

0.2
0.5
m
m
0.0
0.0
0.1
0.1

a
0.1
m
m
0.0
0.0
0.0
0.3

a
0.3
m
m
a
0.0 d
0.0
0.4

m
0.0
m
a
x(7)
0.3 d
m
x(7)

m
3.1
m
m
1.4 d
1.0
m
1.5 d

a
21
m
m
a
25
17
69

G20 average

m

m

m

m

m

m

m

m

1. Excludes private institutions at short-cycle tertiary level.
2. Upper secondary vocational programmes include post-secondary non-tertiary programmes.
3. Short-cycle tertiary programmes include a small number of bachelor's professional programmes; upper secondary figures are split into general and vocational based on
institution type.
4. Year of reference 2017.
5. Post-secondary non-tertiary and short-cycle tertiary programmes include part of upper secondary vocational programmes.
Source: OECD/UIS/Eurostat (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2https://doi.org/10.1787/888934163173

EDUCATION AT A GLANCE 2020 © OECD 2020

166  B2. HOW DO EARLY CHILDHOOD EDUCATION SYSTEMS DIFFER AROUND THE WORLD?

Indicator B2. How do early childhood
education systems differ around the
world?
Highlights


Early childhood education and care (ECEC) has experienced a surge of policy attention in OECD countries in
recent decades, with a focus on children under the age of 3. On average across OECD countries in 2018, 26%
of children under 3 were enrolled in early childhood education (ISCED 0).



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 was at or above 90% in all
countries with available data in 2018 except Colombia, Finland, the Russian Federation, Saudi Arabia,
the Slovak Republic and Turkey.



The ECEC workforce is at the heart of high-quality education. On average across OECD countries, there are
7 children for every teacher working in early childhood educational development services (ISCED 01) and 14 in
pre-primary education (ISCED 02).

Context

The benefits of ECEC services are not limited to better labour-market outcomes and higher 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 large share of the population in employment, 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 starting 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.

EDUCATION AT A GLANCE 2020 © OECD 2020

B2. HOW DO EARLY CHILDHOOD EDUCATION SYSTEMS DIFFER AROUND THE WORLD?  167

Figure B2.1. Enrolment rates of children under the age of 3 in early childhood education and care, by age (2018)
All ECEC services (Early childhood education [ISCED 0] and other registered ECEC services outside the scope of ISCED 0)

Turkey (m)

Poland1 (3 years)

Mexico (1.5 months)

Hungary 1 (20 weeks)

Slovak Republic (2-3 years)

Russian Federation 1 (0 years)

Austria (0 years)

Chile (3 months)

Brazil (0 years)

Lithuania (0 years)

Latvia (1.5 years)

Colombia 1 (0 years)

Estonia (0 years)

Japan (3 years)

Finland1 (9 months)

Germany (0 years)

Spain1 (0 years)

Australia (0 years)

Portugal (0 years)

Slovenia1 (11 months)

Belgium1, 2 (see note 2)

Sweden (1 year)

New Zealand (0 years)

Denmark 1 (26 weeks)

Norway 1 (0 years)

Israel (0 years)

Korea (0 years)

Iceland (0 years)

%
100
90
80
70
60
50
40
30
20
10
0

OECD average

Age 2
Age 1
Under the age of 1
Under the age of 3

Note: Figures in parentheses refer to the age when ECEC systems start offering intentional education objectives.
1. Excludes other registered ECEC services.
2. Age at which ECEC services start offering intentional education objectives: 3-6 months for the Flemish Community and 2 years for the French Community. ISCED 0
enrolment rates are underestimated since only the Flemish Community of Belgium has reported data on ISCED 01.
Countries are ranked in descending order of the enrolment rates in ISCED 0 of children under the age of 3.
Source: OECD (2020), Table B2.1. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).

Other findings

Statlink2https://doi.org/10.1787/888934163363



On average, 34% of 1-year-olds and 46% of 2-year-olds were already enrolled in ISCED 0 programmes in 2018.
In Japan, 33% of 1-year-olds and 50% of 2-year-olds are enrolled in ECEC services outside ISCED 0.



A bachelor’s degree or equivalent (ISCED 6) is the most prevalent qualification for teachers in ECEC (ISCED 0)
in around three-quarters of OECD countries with available data.



The estimated expenditure on all children aged 3 to 5 enrolled in ECEC and primary education amounts to an
average of 0.6% of gross domestic product (GDP). Only in Iceland and Norway does it equal or exceed 1.0%.

EDUCATION AT A GLANCE 2020 © OECD 2020

168  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 of high-quality early childhood education and
care (ECEC). However, the type of 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 partday attendance) and the location of provision, whether in centres or schools, or at home (OECD, 2017[1]).
The organisation of national ECEC systems is diverse across countries, primarily regarding the highest administrative
authorities in charge and whether the system is split or integrated at the national level. More than 70% of the OECD countries
with available data have integrated early childhood education and care services, where one or more authorities are
responsible for administering the whole ECEC system and setting adequate intentional education for children from the ages
of 0 or 1 until they start primary education (see Box B2.1 in (OECD, 2019[6])).
Generally, formal ECEC services can be further classified into two categories:
The ECEC services reported in the ISCED 2011 classification (OECD/Eurostat/UNESCO Institute for Statistics, 2015[7]). To
be classified as ISCED level 0, ECEC services should:


have adequate intentional educational properties



be institutionalised (usually school-based or otherwise institutionalised for a group of children)



have an intensity of at least 2 hours per day of educational activities and a duration of at least 100 days a year



have a regulatory framework recognised by the relevant national authorities (e.g. a curriculum)



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). Many
countries do have such programmes but not all are able to report the number of children enrolled in them. For this reason,
the data are explicitly presented separately in Tables B2.1 and B2.2. This distinction is also made in the analysis below where
averages can only be presented for ECEC services reported in the ISCED 2011 classification.
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 in the first years of children lives can have a positive effect on their well-being, learning
and development in the short and the long terms (OECD, 2018[8]) (OECD, 2018[2]). The length of parental leave and the age
when ECEC services start becoming available influence the age at which children start 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,
Belgium, Ireland, Israel, Korea, Portugal and Spain. In contrast, once children reach the age of 1, 34% will be enrolled in
ECEC (ISCED 0) on average, with enrolment rates of at least 50% at this age in Israel, Korea, Norway and Slovenia. Iceland
also belongs to this group of countries (where enrolment rates exceed 50%) when the number of children in ECEC services
outside ISCED 0 are taken into account. In Japan, one-third of 1-year-olds are enrolled in ECEC services outside the scope
of ISCED 0. By the age of 2, enrolment in ECEC services has become the norm in many OECD countries. On average across
OECD countries in 2018, 46% of 2-year-olds were enrolled in ECEC (ISCED 0). This proportion is 80% or more in Belgium,
Denmark, Iceland, Korea, Norway and Sweden but less than 10% in Costa Rica, Japan, Luxembourg, Mexico,
the Netherlands, Poland, Switzerland and Turkey. This latter group of countries do have children in ECEC services outside
ISCED 0: in particular, in Japan half of children are enrolled in ECEC services outside ISCED 0 (Figure B2.1).
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 the years 2005 and 2018. The rise has been particularly
marked in many European countries (i.e. by 15 percentage points or more in Germany, Lithuania, Norway, Portugal, Slovenia
EDUCATION AT A GLANCE 2020 © OECD 2020

B2. HOW DO EARLY CHILDHOOD EDUCATION SYSTEMS DIFFER AROUND THE WORLD?  169
and Spain), 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 2018 tend to be
those in which the employment rates of mothers are highest (see Table B2.1 in (OECD, 2018[2])).

Enrolment of children from age 3 until entry to primary education
In many OECD countries, ECEC begins for most children long before they turn 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 (Box B2.1).
On average, 88% of 3-5 year-olds are enrolled in ECEC (ISCED 0) and primary education – usually in pre-primary education
(ISCED 02) at that age. In about half of the 41 countries with available data, the enrolment of children between the ages of 3
and 5 is near universal, i.e. at least 90% (Table B2.2).
The highest enrolment rates of 3-year-olds in ECEC (ISCED 0) are found in Belgium, Denmark, France, Iceland, Ireland,
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), 91% of 4-year-olds are enrolled. OECD enrolment rates at this age vary from 98% or more in Belgium,
Denmark, France, Ireland, Israel, Spain and the United Kingdom, to less than 50% in Saudi Arabia, Switzerland and Turkey
(Table B2.2).

Figure B2.2. Change in enrolment rates of children aged 3 to 5 years (2005, 2010 and 2018)
Early childhood education (ISCED 0) and primary education
2005
2010
2018

%
100
90
80
70
60
50
40
30
20
0

France
Ireland
Israel
United Kingdom
Denmark
Belgium
Spain
Iceland
Norway
Korea
Germany
Sweden
Italy
New Zealand
Latvia
Hungary
Japan
Estonia
Slovenia
EU23 average
Portugal
Austria
Netherlands
OECD average
Luxembourg
Czech Republic
Lithuania
Poland
Brazil
Australia
Russian Federation
Mexico
Finland
Chile
Slovak Republic
Argentina
Colombia
Indonesia
United States
Costa Rica
Switzerland
Turkey
Saudi Arabia

10

Countries are ranked in descending order of the enrolment rates of 3-5 year-olds in 2018.
Source: OECD (2020), Table B2.2. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2https://doi.org/10.1787/888934163382

This situation is the result of the expansion of ECEC services over recent years in many countries. Between 2005 and 2018,
the average enrolment of 3-5 year-olds in pre-primary or primary education in OECD countries rose by more than
10 percentage points. A few countries have seen spectacular increases in ECEC over this period, for example Lithuania,
Poland, the Russian Federation and Turkey. In contrast, other countries have not shown much change. For instance,
Switzerland reported one of the lowest enrolment rates in 2005 and this is still the case in 2018 (Figure B2.2). This is due to

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170  B2. HOW DO EARLY CHILDHOOD EDUCATION SYSTEMS DIFFER AROUND THE WORLD?
the fact that there are almost no compulsory education programmes for 3-year-olds in Switzerland and the offer corresponding
to ISCED level 02 is intended for children aged 4 and over.
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 2018 and
at the age of 3 in France (from September 2019), Hungary, Israel and Mexico (Table B2.2 and Box B2.2).

Enrolment of children 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 early childhood education than
at primary and secondary levels. Private institutions can be classified into two categories: independent and governmentdependent. Independent private institutions are controlled by a non-governmental organisation or by a governing board not
selected by a government agency and receive less than 50% of their core funding from government agencies. Governmentdependent private institutions have similar governance structures but they rely on government agencies for more than 50%
of their core funding (OECD, 2018[10]).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, Hungary, Latvia, Lithuania, the Russian Federation, Slovenia and
Sweden, 20% or less of the children in early childhood educational development programmes attend private ECEC
institutions, while in Indonesia, Ireland, Israel, Korea, New Zealand, Portugal, Turkey and the United Kingdom, more than
three-quarters of all children attend private institutions (Table B2.3).
Public institutions are usually less 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 almost three-quarters of
children across EU23 countries, reflecting the development of policies promoting the public provision of ECEC among most
European countries. In a few countries, however, pre-primary remains mostly private: in Australia, Indonesia, Ireland, Japan,
Korea and New Zealand, at least 75% of children attending pre-primary programmes are in private institutions (Table B2.3).

Staffing of early childhood education and care
Qualifications among 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 et al., 2017[11]). Highly qualified staff result in a more stimulating environment and high-quality pedagogical
practices, which boost children’s well-being and learning outcomes (Box B2.2).
The most prevalent level of qualification for almost all ECEC teaching staff is a tertiary qualification. In 18 out of the 25
countries with available data, an individual can teach in ECEC (ISCED 0) with at least a bachelor’s degree or equivalent
(ISCED level 6). 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 master’s degree. In Germany,
they can begin teaching after graduating from a tertiary professional programme (e.g. Erzieherausbildung, at ISCED level 6);
in Austria and Israel, they typically graduate from a two-year short-cycle tertiary programme (ISCED 5). At the other end of
spectrum, in France (since the academic year 2010/11) and Portugal pre-primary school teachers are required to have a
master’s degree or equivalent (ISCED 7). In Poland, the master’s or equivalent degree is not a prerequisite, but most ECEC
teachers enter the profession with this level (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’

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B2. HOW DO EARLY CHILDHOOD EDUCATION SYSTEMS DIFFER AROUND THE WORLD?  171
careers, and the need to update knowledge and competencies, initial teacher education must be viewed as only the starting
point for teachers’ ongoing development. Recent research also shows that in pre-primary education, the effects of specialised
in-service training on process quality are greater than those of pre-service training, particularly when it comes to collaborative
work, support for play and support for early literacy, mathematics and science (Assel et al., 2006[12]; de Haan et al., 2013[13]).

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, 2020[14]).
The ratio of children to teaching staff is an important indicator of the resources devoted to education. Child-staff ratios and
group sizes are part of the regulations used to improve ECEC quality. On average across OECD countries, there are
14 children for every teacher working in pre-primary education but wide variations are observed across countries. The ratio
of children to teaching staff, excluding teachers’ aides, ranges from fewer than 10 children per teacher in Denmark, Finland,
Germany, Iceland, Latvia, New Zealand and Slovenia, to 20 or more in Brazil, Chile, Colombia, France, Israel and Mexico. In
some countries, this ratio has decreased significantly over the last years. Over the last years, t fell by 3-4 students per teacher
in Chile (2013-18), in Germany (2005-13), in Korea (2010-2018) and Latvia (2010-18). In Saudi Arabia, the child-teaching
staff ratio increased by 5 children between 2013 and 2018 but the ratio in 2018 remains comparable to the OECD average
(Figure B2.3).

Figure B2.3. Ratio of children to staff in pre-primary (ISCED 02) education (2005 and 2018)
Public and private institutions, calculation based on full-time equivalents
Children to contact staff (teachers and teachers’ aides) in 2018
Children to teaching staff in 2018
Children to teaching staff in 2005

%
40
35
30
25
20
15
10

(a)
Iceland1

New Zealand1 (m)

(a)
Slovenia

Denmark (m)

(9)
Germany

Finland2 (m)

(a)

Latvia1 (m)

(1)

Greece1

(a)

Slovak Republic1

Lithuania (35)

(a)
Italy1

Luxembourg1

(a)

United States (16)

Korea2

Hungary1

(a)

Czech Republic1

Indonesia1 (m)

(a)

(9)

Costa Rica1

Austria1 (35)

Norway1 (59)

EU23 average (21)

Japan1,3 (m)

Spain2 (m)

(a)
Belgium

OECD average (30)

Poland1 (m)

Saudi Arabia1 (m)

Portugal1 (m)

China (m)

Netherlands1 (14)

Turkey1 (m)

Switzerland (m)

Israel (61)

Brazil 2 (14)

(33)
France2

Chile1 (59)

(a)
Mexico1

0

Colombi a1 (m)

5

Note: Figures in parentheses show the percentages of teachers' aides among ECEC contact staff (teachers and teachers' aides).
1. Year of reference 2013 instead of 2005.
2. Year of reference 2010 instead of 2005.
3. Data does not cover day care centres and integrated centres for early childhood education and care.
Countries are ranked in descending order of the ratio of children to teaching staff in pre-primary education in 2018.
Source: OECD (2020), Table B2.3 and Education at a Glance database. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2https://doi.org/10.1787/888934163401

Some countries – Austria, Chile, France, Israel, Lithuania and Norway – also make extensive use of teachers' aides, which
can be seen from the smaller ratios of children to contact staff compared to children to teaching staff. Teachers' aides assist

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172  B2. HOW DO EARLY CHILDHOOD EDUCATION SYSTEMS DIFFER AROUND THE WORLD?
teachers in their daily tasks and deal with children with special needs. In most countries, they have an upper secondary
qualification, often vocationally oriented (Figure B2.3).
Child-to-staff ratios matter more for interactions with children under the age of 3 than for 3-5 year-olds (OECD, 2018[8]). On
average across OECD countries, there are 7 children for every teacher working in early childhood educational development
services (ISCED 01) and this ratio reaches more than 20 to 1 in Indonesia. As with pre-primary education, the ratio decreases
when teachers’ aides are taken into account. 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 (Table B2.3).

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 in ECEC among children
from disadvantaged socio-economic backgrounds (OECD, 2017[1]).

Expenditure per child
In pre-primary education, annual expenditure for both public and private settings averages about USD 9 000 per child in
OECD countries in 2017, ranging from less than USD 1 600 in Colombia to more than USD 15 000 in Denmark, Iceland,
Luxembourg and Norway. Annual expenditure per child enrolled in early childhood educational development services
(ISCED 01) is significantly higher than for pre-primary education (ISCED 02), averaging about USD 12 800 for ISCED 01.
The smaller child-to-staff ratio in early childhood development services 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[15])).

Expenditure as a percentage of gross domestic product
Spending on ECEC can also be analysed relative to a nation’s wealth. Expenditure on all ECEC settings accounts in 2017
for an average of 0.9% of gross domestic product (GDP) across OECD countries, of which more than two-thirds is allocated
to pre-primary education. While 0.3% or less of GDP is spent on pre-primary education (ISCED 02) in Australia, Colombia,
Greece, Japan and Turkey, countries such as Denmark, Iceland, Israel, Norway and Sweden spend at least 1% of GDP
(Table B2.4).
The differences on expenditure 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 a result of children’s earlier transition from pre-primary to primary education in Australia, Ireland and the United Kingdom,
partly explains why the expenditure on ECEC as a percentage of GDP is below the OECD average in these three countries.
Similarly, late entry into primary education, as in Estonia, Finland, Latvia 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 information
on starting ages for primary education in Table B2.2).
To avoid this distortion, the indicator on the financing of ECEC has been presented by age as well as by ISCED level since
the 2019 edition of Education at a Glance. This 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. As this indicator is presenting estimates then the data should be interpreted with caution. 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 0.3% of GDP in Greece, to 1% or more in Iceland and Norway. While the share remained constant on
average among OECD countries with available data, there are marked differences in trends across countries. About half of
countries experienced a decrease between 2013 and 2017, while in contrast Chile displayed the most notable increase, from
0.7% of GDP to 0.9% (Figure B2.4).

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B2. HOW DO EARLY CHILDHOOD EDUCATION SYSTEMS DIFFER AROUND THE WORLD?  173

Figure B2.4. 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 (2013 and 2017)
Public and private institutions
2017
2013

% of GDP
1.2
1.0
0.8
0.6
0.4
0.2

Greece 2

Turkey 2

Netherlands

United States 2

Colombia

Czech Republic

Korea 2

Austria

Slovak Republic

Luxembourg

Italy

Lithuania

Spain

Germany

Finland

Australia

EU23 average

Mexico

Portugal 2

Poland

Belgium2

OECD average

Latvia

Slovenia

United Kingdom

Estonia1

France

Chile

New Zealand

Israel

Sweden

Norway

Iceland

0.0

1. Year of reference 2014 instead of 2013.
2. Excludes ISCED 01 programmes.
Countries are ranked in descending order of expenditure as a percentage of GDP in 2017.
Source: OECD (2020), Table B2.4. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2https://doi.org/10.1787/888934163420

Box B2.1. Legal entitlements and free access to early childhood education and care
Early childhood education and care (ECEC) remains high on the policy agenda in many OECD countries. Enrolment rates
increase for children aged 3 and over, as well as for children under the age of 3, thanks to the extension of legal
entitlements to a place in ECEC and to the efforts to ensure free access for older children (e.g. 3-5 year-olds). The rising
enrolment rates are also likely due to the increased free access for selected population groups such as children under the
age of 2 or disadvantaged children.
Countries guarantee an ECEC place for all children either by establishing a legal entitlement to participate in ECEC, or by
making participation compulsory. A legal entitlement is a right for a child and his/her family. In countries with a legal
entitlement, children may attend ECEC, but families may choose other options. In contrast, in countries with compulsory
ECEC, children have to attend ECEC for a defined number of hours and parents may be asked to justify absences or face
disciplinary measures. Often, a certificate of completion of a compulsory ECEC programme is required to enter primary
education (European Commission/EACEA/Eurydice, 2019[16]).
There are significant differences in the age at which countries guarantee children a place in an ECEC institution. While
most countries ensure a place in publicly subsidised ECEC from the age of 3 or a little earlier, seven countries (Denmark,
Estonia, Finland, Germany, Latvia, Norway and Slovenia) guarantee a place in ECEC for all children soon after birth, often
immediately after the end of parental leave. In Australia, Austria, Brazil, Chile, Costa Rica, Greece, Lithuania,
the Netherlands, Portugal and Switzerland, the education systems only provide guaranteed places from higher ages: at
4, 5 or 6 years old, or for the last one or two years of ECEC. Often, this provision is explicitly directed at preparation for
school with a specific programme to smooth the transition to primary education. However, a guaranteed ECEC place at a

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174  B2. HOW DO EARLY CHILDHOOD EDUCATION SYSTEMS DIFFER AROUND THE WORLD?
given age does not mean that attendance is compulsory at this age. Indeed, Australia, Chile and Portugal provide a legal
entitlement from the last one or two years of ECEC without making attendance compulsory. Despite a legal framework
that guarantees a place in ECEC for all children, in reality some municipalities in some countries may still struggle to
balance supply with demand. Moreover, many countries have introduced targeted measures to ensure the availability of
ECEC for certain groups of children or families (European Commission/EACEA/Eurydice, 2019[16]).
The type of ECEC guarantee – a legal right to a place or compulsory attendance – influences the way in which the number
of guaranteed hours is prescribed. Legal entitlements define the number of guaranteed publicly subsidised (or free-ofcharge) ECEC hours that every family can claim. A child may use fewer hours than the guarantee entitles them to. In
contrast, compulsory ECEC specifies the minimum number of ECEC hours that a child is required to attend. In both cases,
the child may still benefit from additional (top-up) hours of ECEC that are not guaranteed for everyone (European
Commission/EACEA/Eurydice, 2019[16]). The time per week covered by the legal entitlements to a free place in ECEC
differs greatly across countries. Most countries guarantee 20-29 hours of ECEC per week, i.e. school-time hours, but the
number increases to over 30 hours per week in Chile, the Czech Republic, Denmark, Israel, Italy, Slovenia and to 50 hours
in Greece. In Australia, Ireland, Mexico, Scotland, Sweden and Switzerland, the number of hours covered is less than
20 hours per week (Figure B2.5).

Figure B2.5. Number of hours per week and ages at which children have free access entitlement to
ECEC (2018)
Unconditional free access refers to
provision free of charge for all children
of the concerned age group

Hours
60

Conditional free access, based on
certain conditions, such as income,
benefit entitlements, etc.

50
40
30
20

(6)

(3 to 5)

(3 to 5)

(0 to 6)

(3 to 5)

(1 to 5)

(3 to 4)

(4 to 5)

(3 to 5)

(3 to 5)

(3 to 5)

(4 to 5)

Hungary

Japan2, 3

Lithuania

New Zealand

Norway

Scotland (UK)

Australia

Ireland

Mexico

Sweden

Switzerland1

(3 to 5)

Finland

(3 to 5)
Spain

France

(5)

(4 to 5)
Portugal

(3 to 4)

(3 to 6)
Poland

Austria

(3 to 5)
Luxembourg

England (UK)1

(3 to 5)
Israel

(4 to 5)

(0 to 5)
Denmark

Costa Rica

(4 to 5)

(3 to 5)

(<1 to 5)

Chile

Korea1

(3 to 5)

Slovenia1

French comm. (Belgium) (2.5 to 5)

(3 to 5)

Italy1

Flemish comm. (Belgium) (2.5 to 5)

(4 to 5)

Czech Republic1

0

Greece

10

Note: The age groups covered by the free access are added into brackets next to the country names.
1. The Czech Republic (32.5-60 hours), England (15-32 hours), Italy (25-50 hours), Korea (20-25 hours), Slovenia (30-45 hours), Switzerland (10-20 hours)
2. From 1 October 2019, free early childhood education and care is a universal legal entitlement for children age 3-5 years.
3. Data does not cover day care centres and integrated centres for early childhood education and care.
Countries and economies are ranked in descending order of the number of hours per week children have free access entitlement to ECEC (ISCED 02).
Source: OECD (2020), 2018 ECEC survey; TALIS Starting Strong; European Commission/EACEA/Eurydice. See Source section for more information and Annex 3
for notes (https://doi.org/10.1787/69096873-en).
Statlink2https://doi.org/10.1787/888934163439

Affordability is a very important factor in ensuring that the largest number of children possible have access to ECEC, and
legal entitlement to a place in ECEC is not a guarantee of free access. Countries may provide conditional or unconditional
free access for a set number of hours. Generally, unconditional free access to ECEC is less common for younger children
than for older ones across countries (Figure B2.5). Although most countries provide free access to pre-primary education
to all children for at least the year before entering primary school, the number of years covered and hours per week offered

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B2. HOW DO EARLY CHILDHOOD EDUCATION SYSTEMS DIFFER AROUND THE WORLD?  175
differ substantially. Chile (for all 4-5 year-olds), the Czech Republic (for the year before starting primary school only),
Greece, Italy, Israel and Luxembourg (for all 3-5 year-olds) offer more than 25 hours of free ECEC for all children enrolled
in pre-primary education. In contrast, Australia, Ireland, Mexico, Scotland, Sweden and Switzerland offer less than
20 hours of free ECEC per week. From 1 October 2019, free early childhood education and care is a universal legal
entitlement for children age 3-5 years in Japan. From September 2019, instruction has been compulsory from the age of
3 in France. Pre-primary education then became a universal legal entitlement and an obligation for 3-5 year-olds.
In contrast, a few countries regulate the provision of free access to ECEC based on a set of conditions, such as income
level or the entitlement to certain benefits. This is the case in Norway and Slovenia, where free access to the last year of
ECEC is provided on a needs basis only.

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. 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[15]). 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 70% 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, 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 B2.2. The Starting Strong Teaching and Learning International Survey
In October 2019, the OECD launched the first international survey of the early childhood education and care (ECEC)
workforce. The Starting Strong Teaching and Learning International Survey (TALIS Starting Strong) aims to generate
robust international information relevant to developing and implementing policies focused on ECEC staff and leaders and
their pedagogical and professional practices, with an emphasis on those aspects that promote the right condition for
children’s learning, development and well-being. Staff are defined as those working regularly in a pedagogical way with
children, including both teachers and assistants in countries where the distinction can be made. The survey collects data
on learning and well-being environments, the work that staff and centre leaders carry out with children in ECEC settings,
how staff are prepared for and trained within the profession, and what motivates staff to join the ECEC profession.
TALIS Starting Strong 2018 covers nine countries: Chile, Denmark, Germany, Iceland, Israel, Japan, Korea, Norway and
Turkey. These countries collected data from staff and leaders in pre-primary education (ISCED level 02) settings. In
addition, four of the countries (Denmark, Germany, Israel and Norway) collected data from staff and leaders in settings
serving children under the age of 3. A more detailed description of the survey design and its implementation can be found
in the TALIS Starting Strong 2018 Technical Report (OECD, 2019[17]).
This first volume of findings from TALIS Starting Strong examined multiple factors that can affect the quality of ECEC and
could thereby influence children’s learning, development and well-being. The main findings of this publication are:
First, staff with more education and training and more responsibility are more likely to report that they adapt their practices
in the classroom or playroom to individual children’s development and interests. The majority of the workforce has postsecondary education, but training specifically to work with children is not universal, and participation in professional
development, while common, is not equal among early childhood staff. Whether staff are trained specifically to work with
children, which is also important for ECEC quality, is a somewhat separate issue from their level of educational attainment
(Figure B2.6). For example, in Japan, where the most common qualifications for ECEC staff were short-cycle tertiary
education, nearly all staff are trained specifically to work with children. In Turkey, where the most typical attainment was
a bachelor’s degree or higher for ECEC staff, more than one-quarter of staff had no specific training on working with
children. In Iceland, where almost half the workforce are highly educated and the other half at most secondary education,
one-third of staff lack specific training to work with children (OECD, 2019[17]).

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176  B2. HOW DO EARLY CHILDHOOD EDUCATION SYSTEMS DIFFER AROUND THE WORLD?

Figure B2.6. Educational attainment of staff and content of pre-service training
Staff reports of their highest level of education and whether they received training specifically to work with children
ISCED level 6 or above
ISCED level 4 or 5
Below ISCED level 4
Trained to work with children
Pre-primary education
(ISCED 02)

%
100

Centres for children
under age 3

%
100

10

10

0

0

Israel

20

Norway

30

20

Germany*

40

30

Iceland

40

Israel

50

Norway

60

50

Germany*

70

60

Chile

70

Turkey

80

Korea

90

80

Japan

90

Note: Respondents in the "Below ISCED level 4" group are those whose highest education is at a secondary level or below. Respondents in the "ISCED level 4 or 5"
group are those whose highest education is beyond secondary schooling but less than a bachelor's degree (or equivalent), including post-secondary non-tertiary
education (generally vocationally oriented) and short-cycle tertiary education. Respondents in the "ISCED level 6 or above" group are those whose highest education
is at the level of a bachelor's degree or higher.
* Estimates for subgroups and estimated differences between subgroups need to be interpreted with care. See Annex B in (OECD, 2019[17]) for more information.
Countries are ranked in ascending order of the percentage of staff (both teachers and assistants) below ISCED level 4.
Source: (OECD, 2019[17]), Tables D.3.1, D.3.2 and D.3.3.
Statlink2https://doi.org/10.1787/888934010736

Second, staff who feel more valued by society report more use of practices in the classroom or playroom adapted to
individual children’s development and interests. With regard to job satisfaction, a majority of staff in all countries report
feeling valued by the children and parents or guardians they serve. However, in all countries, staff were less likely to report
feeling valued by society (Figure B2.7). Staff generally like their jobs, but fewer than 40% are satisfied with their salaries
and little more than half think their job is valued in society (OECD, 2019[17]).
Third, reducing group sizes, improving staff salaries and receiving support for children with special needs were the top
spending priorities identified by early childhood education and care staff if the sector’s budget was increased. For staff in
centres for children under age 3, high-quality professional development also appears in the top three priorities (OECD,
2019[17]).
Fourth, pre-school staff are much more likely to report using practices to facilitate children’s socio-emotional development
or oral language development than those geared towards literacy and numeracy skills. Related to this, being able to cooperate easily with others is at the top of the list of skills and abilities that ECEC staff regard as important for young
children to develop (OECD, 2019[17]).
The findings presented in this report suggest several major objectives for policies to ensure high-quality ECEC. These
include promoting practices that foster children’s learning, development and well-being, attracting and retaining a highquality workforce, and ensuring smart spending in view of complex governance and service provision. Policies to raise the
quality of ECEC face a number of trade-offs in terms of the areas to invest in and the areas to spend less on. TALIS
Starting Strong sheds light on what the priorities could be for each country (OECD, 2019[17]).

EDUCATION AT A GLANCE 2020 © OECD 2020

B2. HOW DO EARLY CHILDHOOD EDUCATION SYSTEMS DIFFER AROUND THE WORLD?  177

Figure B2.7. Staff feelings of being valued by children, families and society
Average percentage of staff who "agree" or "strongly agree" with each of the following statements
I think that ECEC staff
are valued in society

Parents or guardians value
me as an ECEC sta ff

Pre-primary education
(ISCED 02)

%
100

The children value me
as ECEC staff
Centres for children
under age 3

%
100

20

10

10

0

0

Germany*

20

Israel

30

Norway

40

30

Japan

50

40

Iceland

50

Germany*

60

Chile

70

60

Korea

80

70

Turkey

80

Norway

90

Israel

90

Note: Staff in centres serving children under the age of 3 were not asked the extent to which they feel valued by the children they serve.
* Estimates for subgroups and estimated differences between subgroups need to be interpreted with care. See Annex B in (OECD, 2019[17]) for more information.
Countries are ranked in descending order of the percentage of staff agreeing that ECEC staff are valued in society.
Source: (OECD, 2019[17]), Table D.3.18.
Statlink2https://doi.org/10.1787/888934011002

Definitions
ECEC services: The types of ECEC services available to children and parents differ greatly. Despite those differences, most
ECEC settings typically fall into one of the following categories ( (OECD, 2017[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: 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).

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178  B2. HOW DO EARLY CHILDHOOD EDUCATION SYSTEMS DIFFER AROUND THE WORLD?
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, available on line, 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 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.
Most prevalent level of qualification: Higher than minimum qualification (if most prevalent) to enter the teaching profession
in the reference year refers to the level of qualification higher than the minimum that is held by the largest proportion of
teachers (among all teachers at a given level of education, and not only among starting teachers) and recognised through a
specific salary range (see Indicator D3).
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 and C2 for definitions of expenditure per student on educational institutions and expenditure
on educational institutions relative to GDP, and Indicator D2 for the definition of 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

EDUCATION AT A GLANCE 2020 © OECD 2020

B2. HOW DO EARLY CHILDHOOD EDUCATION SYSTEMS DIFFER AROUND THE WORLD?  179
personnel at levels 01 and 02. For more information please see the OECD Handbook for Internationally Comparative
Education Statistics (OECD, 2018[10]) and Annex 3 for country-specific notes (https://doi.org/10.1787/69096873-en).
Estimated expenditure for all children aged 3 to 5 enrolled in ECEC and primary education as a percentage of GDP
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 2018 (school year 2017/18) and financial year 2017.
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 2019 (for details, see Annex 3 at https://doi.org/10.1787/69096873-en) and on a special survey administered by the OECD
in 2019.
Data on subnational regions for selected indicators are available in the OECD Regional database (OECD, 2020[18]).

References

Assel, M. et al. (2006), “An evaluation of curriculum, setting, and mentoring on the performance of children
enrolled in pre-kindergarten”, Reading and Writing, Vol. 20/5, pp. 463-494, http://dx.doi.org/10.1007/s11145006-9039-5.

[12]

de Haan, A. et al. (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, pp. 177-194, http://dx.doi.org/10.1080/09243453.2012.749792.

[13]

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]

European Commission/EACEA/Eurydice (2019), Key Data on Early Childhood Education and Care in Europe.
Eurydice Report, Publications Office of the European Union, Luxembourg, https://eacea.ec.europa.eu/nationalpolicies/eurydice/content/key-data-early-childhood-education-and-care-europe-%E2%80%93-2019-edition_en.

[16]

Manning, M. et al. (2017), “The relationship between teacher qualification and the quality of the early childhood
education and care environment”, Campbell Systematic Reviews, Vol. 13/1, pp. 1-82,
http://dx.doi.org/10.4073/csr.2017.1.

[11]

OECD (2020), OECD Education at a Glance database, https://stats.oecd.org/.

[14]

OECD (2020), “Regional education”, OECD Regional Statistics (database), https://dx.doi.org/10.1787/213e806cen (accessed on 27 July 2020).

[18]

EDUCATION AT A GLANCE 2020 © OECD 2020

180  B2. HOW DO EARLY CHILDHOOD EDUCATION SYSTEMS DIFFER AROUND THE WORLD?
OECD (2019), Education at a Glance 2019: OECD Indicators, OECD Publishing, Paris,
https://doi.org/10.1787/f8d7880d-en.

[6]

OECD (2019), TALIS Starting Strong 2018 Technical Report, OECD, Paris,
http://www.oecd.org/education/talis/TALIS-Starting-Strong-2018-Technical-Report.pdf.

[17]

OECD (2018), Education at a Glance 2018: OECD Indicators, OECD Publishing, Paris,
https://dx.doi.org/10.1787/eag-2018-en.

[15]

OECD (2018), Engaging Young Children: Lessons from Research about Quality in Early Childhood Education and
Care, Starting Strong, OECD Publishing, Paris, https://dx.doi.org/10.1787/9789264085145-en.

[8]

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,
https://dx.doi.org/10.1787/232211ca-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.

[10]

OECD (2017), Starting Strong 2017: Key OECD Indicators on Early Childhood Education and Care, Starting
Strong, OECD Publishing, Paris, https://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-parents-work-life-balance-stageschildhood.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,
https://dx.doi.org/10.1787/9789264228368-en.

[7]

Shin, E., M. Jung and E. Park (2009), A Survey on the Development of the Pre-School Free Service Model,
Korean Educational Development Institute, Seoul.

[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 2018)

Table B2.2

Enrolment rates in early childhood education and care and primary education, by age (2005, 2010 and
2018)

Table B2.3

Enrolment of children in early childhood education and care (ISCED 0) in private institutions, ratio of
children to teaching staff and most prevalent qualification of ECEC staff (2018)

EDUCATION AT A GLANCE 2020 © OECD 2020

B2. HOW DO EARLY CHILDHOOD EDUCATION SYSTEMS DIFFER AROUND THE WORLD?  181
Table B2.4

Financing of early childhood education and care (ISCED 0) and expenditure on all children aged 3 to 5
(2017)

WEB Table B2.5

Coverage of early childhood education and care in OECD and partner countries (2019)

Cut-off date for the data: 19 July 2020. Any updates on data can be found on line at http://dx.doi.org/10.1787/eag-dataen. More breakdowns can also be found at http://stats.oecd.org/, Education at a Glance Database.
StatLink: https://doi.org/10.1787/888934163268

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182  B2. HOW DO EARLY CHILDHOOD EDUCATION SYSTEMS DIFFER AROUND THE WORLD?
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 2018)
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. Age at which ECEC services start offering intentional education objectives: 3-6 months for the Flemish Community and 2 years for the French Community. ISCED 0
enrolment rates are underestimated since only the Flemish Community of Belgium has reported data on ISCED 01.
2. Year of reference 2017 instead of 2018.
Source: INES ad hoc survey and OECD/UIS/Eurostat (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2https://doi.org/10.1787/888934163287

EDUCATION AT A GLANCE 2020 © OECD 2020

B2. HOW DO EARLY CHILDHOOD EDUCATION SYSTEMS DIFFER AROUND THE WORLD?  183

Table B2.2. Enrolment rates in early childhood education and care and primary education, by age (2005, 2010 and 2018)
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. From September 2019, instruction is compulsory from the age of 3 in France
2. Excludes ISCED 01 programmes.
3. Year of reference 2017 instead of 2018.
Source: INES ad hoc survey and OECD/UIS/Eurostat (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2https://doi.org/10.1787/888934163306

EDUCATION AT A GLANCE 2020 © OECD 2020

184  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 most prevalent qualification of ECEC staff (2018)

Children to contact staff
(teachers and teachers’
aides)

Children
to teaching staff

Share of teachers’ aides
among contact staff

Children to contact staff
(teachers and teachers’
aides)

Children
to teaching staff

Share of teachers’ aides
among contact staff

Children to contact staff
(teachers and teachers’
aides)

Children
to teaching staff

Total (ISCED 0)

Share of teachers’ aides
among contact staff

ISCED 02

Total (ISC ED 0)

ISCED 01

ISC ED 02

Countries
Australia
Austria
Belgium
Canada
Chile
Colombia
Costa Rica
Czech Republic
Denmark
Estonia
Finland
France 1
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan 2
Korea
Latvia
Lithuania
Luxembourg
Mexico
Netherlands
New Zealand
Nor way
Poland 3
Por tugal
Slovak Republic
Slovenia

Ratio of children to staff in full-time equivalents
by type of ECEC ser vice (public and private insti tution s)

ISC ED 01
Par tners

OECD

Percentage of children
enrolled in private
institutions
(government-dependent
and independent private
insti tution s)

Teachers

Teachers’ aides

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

(13)

(14)

m
65
m
m
10
m
74
a
14
x(3)
23
a
73
m
16
21
100
100
a
a
89
17
11
a
68
a
99
52
a
96
a
7

85
29
53
m
63
21
10
4
23
x(3)
13
13
65
10
11
14
99
36
28
76
77
7
4
11
15
28
99
48
25
47
7
5

m
36
m
m
51
14
14
4
20
4
15
13
67
m
11
16
99
59
28
76
82
9
5
11
18
28
99
50
25
62
7
5

m
31
m
m
43
m
a
a
m
m
m
a
8
m
a
a
x(10)
m
a
a
a
m
36
a
60
a
m
59
a
m
a
a

m
6
m
m
6
m
5
a
m
m
m
a
4
m
14
3
x(11)
m
a
a
5
m
7
a
5
a
m
3
a
m
a
6

m
9
m
m
10
m
5
a
3
x(12)
m
a
5
m
14
3
x(12)
m
a
a
5
7
10
a
12
a
3
8
a
m
a
6

m
35
a
m
59
m
a
9
m
m
m
33
9
a
a
a
x(10)
61
a
m
a
m
35
a
a
14
m
59
m
m
1
a

m
9
14
m
9
m
13
12
m
m
m
16
9
10
12
5
x(11)
8
12
13
13
m
7
12
24
14
m
6
m
m
12
9

m
14
14
m
23
36
13
13
7
x(12)
9
23
9
10
12
5
x(12)
21
12
14
13
9
10
12
24
16
6
14
15
16
12
9

m
34
m
m
59
m
a
9
m
m
m
33
9
m
a
a
7
m
a
m
a
m
35
a
11
14
m
59
m
m
1
a

m
8
m
m
9
m
12
12
m
m
m
16
7
m
12
4
4
m
12
13
8
m
7
12
21
14
m
4
m
m
12
8

m
13
m
m
22
m
12
13
5
8
m
23
7
m
12
4
4
m
12
14
8
9
10
12
23
16
5
11
15
m
12
8

m
ISCED 5
ISCED 6
m
ISCED 6
ISCED 6
m
m
ISCED 6
ISCED 6
ISCED 6 or 7
ISCED 7
ISCED 6, professional
m
m
m
m
ISCED 5
m
ISCED 5 or 6
ISCED 5
m
ISCED 6
m
ISCED 6
m
ISCED 6
ISCED 6
ISCED 7
ISCED 7
ISCED 3
ISCED 6
ISCED 5 for ISCED 01;
ISCED 6 for ISCED 02
ISCED 6
ISCED 6
m
m
m

m
ISCED 3
ISCED 3
m
ISCED 3, vocational
m
m
m
x(13)
m
m
ISCED 3, vocational
ISCED 3, vocational
a
a
m
m
ISCED 3
a
m
m
m
ISCED 3
m
ISCED 2 and training
m
m
ISCED 3
m
m
m
ISCED 3, vocational

m
ISCED 6
m
m
m
m
m
m

m
ISCED 3
m
m
m
m
m
m

Most prevalent ISC ED qualification
required to enter ECEC profession

Spain

49

33

37

m

m

9

m

m

14

m

m

13

Sweden
Switzerland
Turkey
Unite d Kingdom
United States

20
a
100
82
m

18
5
16
53
40

18
5
16
59
m

m
a
m
m
m

5
a
m
m
m

x(5)
a
m
m
m

m
m
m
m
16

6
m
m
m
10

x(8)
18
18
m
12

m
m
m
m
m

6
m
m
m
m

x(11)
18
m
m
m

OECD average
EU23 average

54
44

33
27

32
27

m
m

m
m

7
8

30
21

11
11

14
14

m
m

m
m

12
11

Argentina 4
Brazil
China
India
Indonesia
R u s s i a n Fe de r a t i o n
Saudi Arabia
South Africa 4

57
34
a
a
100
2
a
m

31
23
56
m
95
2
47
6

33
28
56
m
98
2
47
m

m
37
a
a
m
m
a
m

m
9
a
a
m
m
a
m

m
14
a
a
21
x(12)
a
m

m
14
m
m
m
m
m
m

m
17
m
m
m
m
m
m

m
20
17
m
13
x(12)
15
m

m
27
m
m
m
m
m
m

m
12
m
m
m
m
m
m

m
17
17
m
17
11
15
m

G20 average

m

33

34

m

m

m

m

m

16

m

m

15

Total (ISCED 0)

m
m
m
m
m
m

Note: Early childhood educational development programmes = ISCED 01, pre-primary education = ISCED 02 ; ISCED 5 = short-cycle tertiary; ISCED 6 = bachelor's degree
or equivalent; ISCED 7 = master's degree or equivalent.
1. Data on ratios of children to staff are for public institutions and government-dependent private institutions.
2. Data does not cover day care centres and integrated centres for early childhood education and care.
3. A master’s or equivalent degree is not a prerequisite, but most ECEC teachers enter the profession with this level.
4. Year of reference 2017 instead of 2018.
Source: INES ad hoc survey and OECD/UIS/Eurostat (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2https://doi.org/10.1787/888934163325

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B2. HOW DO EARLY CHILDHOOD EDUCATION SYSTEMS DIFFER AROUND THE WORLD?  185

Table B2.4. Financing of early childhood education and care (ISCED 0) and expenditure on all children aged 3 to 5 (2017)
Public and private institutions

1. Expenditure on all children aged 3 to 5 excludes expenditure and enrolment in ISCED 01 programmes.
2. Data does not cover day care centres and integrated centres for early childhood education and care.
3. Public sources only.
Source: INES ad hoc survey and OECD/UIS/Eurostat (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2https://doi.org/10.1787/888934163344

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186  B3. WHO IS EXPECTED TO COMPLETE UPPER SECONDARY EDUCATION?

Indicator B3. Who is expected to
complete upper secondary education?
Highlights






On average across countries with true cohort data, 72% of students who enter upper secondary education
graduate from any programme within its theoretical duration. Two years after the end of the theoretical duration,
average completion increases to 81%. For countries with cross cohort data, the average completion rate is 83%.
The completion rate (within the theoretical duration of the programme plus two years) of students in a general
upper secondary programme (86%) is higher than for students in a vocational one (70%), on average across
countries with data.
In all countries with available data, women have higher completion rates than men in upper secondary education.
The gender gap decreases with time, as men take longer to complete their programmes.

Context
Upper secondary completion rates measure how many of the students who enter an upper secondary programme
ultimately graduate from it. One of the challenges facing education systems in many countries is students disengaging
and consequent dropping out of the education system, meaning that they leave school without an upper secondary
qualification. These young people tend to face severe difficulties entering – and remaining in – the labour market. Leaving
school early is a problem for both individuals and society. Graduating with excessive delays is another source of concern,
raising the issue of a later entry into the labour market and hence delaying the time when they are typically able to start
contributing financially to society.
This indicator is restricted to initial education only, meaning it only captures students who are entering upper secondary
education for the first time. For those students, it measures the successful completion of upper secondary programmes
and the proportion of students still in education at two specific points: 1) the theoretical duration of the programme they
entered; and 2) two years after the end of the theoretical duration. The difference between these two time frames sheds
light on the extent to which students tend to graduate “on time” (or within the amount of time expected given the theoretical
duration of the programme). It also allows completion rates by gender and programme orientation to be compared.
Like graduation rates, completion rates do not indicate the quality of upper secondary education; they do, however indicate
to some extent the capacity of this education level to engage students to complete their programmes within a specific
period.

Other findings







For nearly all countries, the completion rate is higher for upper secondary general programmes than for vocational
ones, within the theoretical duration. In Estonia and Norway, the difference in completion rates is at least
30 percentage points higher for general programmes than for vocational ones.
On average, 3% of students who enter an upper secondary general programme are still in education two years
after the end of the theoretical duration of the programme and 12% have not graduated and are no longer enrolled.
In some countries and economies, upper secondary students transfer between programme orientations before
graduating, meaning that they could graduate from a programme orientation that is different from the one they
entered. In the Flemish Community of Belgium, Chile and Iceland, at least 10% of students who enter an upper
secondary general programme graduate from a vocational one. Similarly, in Brazil, Iceland, Israel and Norway, at
least 10% of upper secondary students graduate from a general programme after entering a vocational one.
In all countries with available data, the completion rate of students who entered a general programme is higher
than that of students who entered either type of vocational programme.

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B3. WHO IS EXPECTED TO COMPLETE UPPER SECONDARY EDUCATION?  187

Figure B3.1. Distribution of upper secondary students by their status at the end of the theoretical
duration of their programme and two years later
True cohort only
Graduated from a general programme
Not enrolled and not in education

Graduated from any vocational programme
No breakdown

By the theoretical duration

Still in education

By the theoretical duration plus two years
Iceland
Brazil
Portugal
Austria
Norway
Latvia
Italy
Chile1
Netherlands
Average
Finland2
Belgium2, 3
Switzerland
Sweden
France2
Estonia
Canada 2
Lithuania
Colombia
New Zealand1
Denmark1
United States1, 4
Israel

% 100

90

80

70

60

50

40

30

20

10

0

0

10

20

30

40

50

60

70

80

90

100 %

1. Students enter a general upper secondary education programme and only split into general and vocational programmes after one or more academic years
2. Year of reference 2017.
3. The data refer only to the Flemish Community.
4. Year of reference 2013 for the theoretical duration and 2015 for the theoretical duration plus two years.
Countries are ranked in descending order of the share of students who graduated from any programme.
Source: OECD (2020), Table B3.2. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en)
Statlink2 https://doi.org/10.1787/888934163553

Note

Completion, graduation and attainment rates are three different measures. Completion describes the percentage of
students who enter an upper secondary programme for the first time and graduate from it a given number of years after
they entered. The restriction to first-time entrants to upper secondary education means that adult-education programmes
and students entering upper secondary education again after their initial schooling are excluded. For example, students
who enter a vocational upper secondary programme after having completed a general upper secondary programme are
not captured by this indicator.
This measure of upper secondary completion rates should not be confused with upper secondary graduation rates. The
graduation rate represents the estimated percentage of people from a certain age cohort who are expected to graduate at
some point during their lifetime. It measures the number of graduates from upper secondary education relative to the
country’s population. For each country, for a given year, the number of students who graduate is broken down into age
groups (for example, the number of 16-year-old graduates divided by the total number of 16-year-olds in the country). The
overall graduation rate is the sum of these age-specific graduation rates.
A third indicator in Education at a Glance uses the notion of educational attainment (see Indicator A1). Attainment
measures the percentage of a population who have reached a certain level of education, in this case those who graduated
at least from upper secondary education. It represents the relationship between all graduates (in the given year and
previous years) and the total population.

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188  B3. WHO IS EXPECTED TO COMPLETE UPPER SECONDARY EDUCATION?

Analysis
Completion rates for true cohort and cross cohort data
Completion rates are calculated using two different methods, depending on data availability. The first method, true cohort,
follows individual students from entry into an upper secondary programme until a specified number of years later. Completion
is then calculated as the share of entrants who have graduated in that time frame. The second method, cross cohort, is used
when data on individuals are not available. It calculates completion by dividing the number of graduates in a year by the
number of new entrants to that programme a certain number of years before, where the number of years corresponds to the
theoretical duration of the programme.
Because of the difference in methodologies, caution must be exercised when comparing true cohort and cross cohort
completion rates. On the one hand, countries with true cohort data are able to report exactly how many students from a given
entry cohort have graduated within a specific time frame. That means that the true cohort completion rate includes students
who graduated before or exactly at the end of the time frame (even if they graduated from a different upper secondary
programme than the one they began) and excludes students who took longer than the time frame to graduate.
On the other hand, the number of graduates used in the cross cohort calculation corresponds to the total number of graduates
of an upper secondary programme in a given calendar year. Thus, it includes every student who graduated that year,
regardless of the time they took to successfully complete the programme. As an example, consider a programme with a
theoretical duration of three years. Completion rates will then be calculated using the graduation cohort in 2018 and an entry
cohort two academic years earlier, in 2015/16. For countries with cross cohort data, the graduation cohort in 2018 will include
students who entered in 2015/16 and graduated on time (within three years) as well as all others who entered before 2015/16
and graduated in 2018. As a result, in countries where a significant share of students take longer to graduate, the cross cohort
method will overestimate completion rates compared to the true cohort method, for which the time frame is limited.
The theoretical duration of upper secondary programmes may vary across countries. Therefore, despite having the same
reference year for graduates (2018 unless specified otherwise), the year used for the entry cohort differs across countries.
Please see Annex 3 (https://doi.org/10.1787/69096873-en) for more information on each country’s theoretical duration of
upper secondary programmes.

True cohort completion
On average across countries and economies with true cohort data, 72% of students who enter upper secondary education
graduate from any programme within the theoretical duration of the programme. Two years after the end of the theoretical
duration, the average completion rate increases to 81%. The completion rate increases between the theoretical duration and
two years on, but for some countries and economies the increase is substantial. Notably, the completion rate at this level
increases by at least 15 percentage points in Austria, the Flemish Community of Belgium, France, Norway, Portugal and
Switzerland (Table B3.1).
A significant difference in completion rates between the shorter and longer time frames is not necessarily a negative outcome.
It could reflect a more flexible upper secondary system, where it is common for students to transfer between different
programmes or programme orientations, thus delaying their graduation. In the Flemish Community of Belgium, for example,
19% of students who enter a general upper secondary programme graduate instead from a vocational programme within the
theoretical duration of their original programme plus two years. In Iceland and Norway, the opposite pathway is more common:
more than 20% of students who enter a vocational programme transfer and graduate instead from a general programme
(Table B3.2).
More generally, in countries that provide broad access to upper secondary education, flexibility may be important to give
students more time to meet the standards set by their educational institution. In countries where upper secondary education
is restricted either by admissions criteria or because students from disadvantaged backgrounds have less access to this level,
completion rates may be higher because of the selection bias.
Nevertheless, students who graduate after excessive delays, or who leave the system without graduating are indeed a source
of concern. Analysing how many of the students who are still in education by the theoretical duration leave the education
system within the following two years may shed light on whether these students are delayed because of system characteristics
or because they are falling behind and at risk of dropping out.

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B3. WHO IS EXPECTED TO COMPLETE UPPER SECONDARY EDUCATION?  189
On average across countries and economies with available data, 51% of students who entered an upper secondary
programme have graduated from a general programme and 24% from a vocational programme by the end of its theoretical
duration. About 16% were still in education (even if at a different level) and 12% were no longer enrolled and had not graduated
from any upper secondary programme. The picture evolves quite considerably two 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, 55% of students have graduated from a general programme and 28% from a vocational programme. Some 3%
are still in education and 16% are no longer enrolled and have not graduated (Figure B3.1).

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. Although they cannot be used to assess whether students are graduating with excessive delays, cross
cohort completion provides valuable information on the share of students who are not graduating at all.
On average across the eight countries that submitted cross cohort data, 83% of students who enter an upper secondary
programme complete it. There is, however, a wide variation among countries, ranging from 65% in Costa Rica to 96% in
Korea (Table B3.1).
The completion rate pattern by programme orientation shows that in most countries with available data, cross cohort
completion is higher in general programmes than in vocational programmes, except in the Slovak Republic (Figure B3.2). On
average, the cross cohort completion rate is 10 percentage points higher for general programmes, ranging from 2 percentage
points in Japan to 22 percentage points in Spain (Table B3.1).

Figure B3.2. Cross cohort completion of upper secondary education by programme orientation at
graduation (2018)
General programmes

%
100

Vocational programmes

90
80
70
60
50
40
30
20
10
0

Korea

Japan

Greece

Poland

Slovenia

Spain

Slovak
Republic

Costa Rica

Countries are ranked in descending order of the general programme completion rate.
Source: OECD 2020, Table B3.1. Ad-hoc survey on completion rates. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2 https://doi.org/10.1787/888934163572

Completion rate by programme orientation
The flexibility to transfer between upper secondary programmes is important to ensure that students do not get locked into a
programme that does not reflect their interest or ability. However, in most countries with true cohort data, students tend to
graduate from the programme they entered: 73% of entrants to upper secondary general programme graduate from the same
programme and 4% graduate from a vocational programme within the theoretical duration. Similarly, 58% of entrants to upper

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190  B3. WHO IS EXPECTED TO COMPLETE UPPER SECONDARY EDUCATION?
secondary vocational programmes graduate from the same programme and only 4% have gained a general qualification
within the theoretical duration.
In all countries with true cohort data, except Israel and Switzerland, the completion rate within the theoretical duration for
students who enter a general upper secondary programme is higher than for students who enter a vocational one. On average
across countries with true cohort data, the completion rate for general programmes within the theoretical duration is 76%,
compared to 62% for vocational programmes. In Estonia and Norway, the completion rate for general programmes is at least
30 percentage points higher than that for vocational programmes. The completion rates of vocational programmes within the
theoretical duration range from 41% in Iceland to 94% in Israel. For countries with cross cohort data, the figures range from
53% in Costa Rica to 93% in Japan and Korea (Table B3.1).
In most countries, the difference in completion rates between the two orientations does not change significantly after two
years following the end of the theoretical duration. One notable exception is Norway, where the gap reduces by 12 percentage
points between the shorter and longer time frames. In contrast, the gap actually increases by 10 percentage points in France
and by 17 percentage points in Portugal as the completion rate for general programmes increases considerably more than
that of vocational programmes during the two years after the end of the theoretical duration (Table B3.1).
For the first time, the ad-hoc survey on upper secondary completion rates disaggregates vocational programmes into those
which give access to tertiary education and without access to tertiary education (but may give direct access to post-secondary
non-tertiary education). This further disaggregation is meant to shed light on the different pathways through upper secondary
education but also on the differences in completion rates between these vocational programmes.

Figure B3.3. Completion rate of upper secondary education within the theoretical duration plus two years,
by programme orientation at entrance (2018)
Entered a general programme

Entered a vocational programme
without access to tertiary education

Entered a vocational programme
with access to tertiary education

%
100
90
80
70
60
50
40
30
20

Brazil

Latvia

Iceland

Chile

Portugal

Colombia

Austria

Sweden

Norway

New Zealand

Lithuania

Italy

Canada2

Netherlands

Estonia

Finland2

Denmark

Switzerland

Belgium 2, 3

France2,4

0

United States1

10

1. Year of reference 2013 for the theoretical duration and 2015 for the theoretical duration plus two years.
2. Year of reference 2017.
3. The data only refer to the Flemish Community.
4. The standard errors are included when data are provided through a survey.
Countries are ranked in descending order of completion rate of students who entered a general programme (for true cohort, by the theoretical duration plus two years).
Source: OECD (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2 https://doi.org/10.1787/888934163591

The entry into general upper secondary programmes may be subject to stricter admission criteria than into vocational ones
(Box B3.1).In all countries and economies with available data, the completion rate of students who entered a general

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B3. WHO IS EXPECTED TO COMPLETE UPPER SECONDARY EDUCATION?  191
programme is higher than that of students who entered either type of vocational programme (with or without access to tertiary
education). However, many countries have substantial differences in completion rates between vocational programmes. In
the Flemish Community (Belgium), France, Italy, Latvia and Switzerland, students who entered a vocational programme
without access to tertiary education are considerably less likely to complete upper secondary education than those who
entered one with access to tertiary education. In contrast, the difference in completion rates between vocational programmes
is low in Austria (Figure B3.3).
Among countries with cross cohort data, completion is also higher for general programmes than for vocational programmes.
The average completion rate for general programmes is 87%, compared to 77% for vocational ones. The largest difference
is found in Spain, where the completion rate for general programmes is 22 percentage points higher than for vocational
programmes. One exception is the Slovak Republic, where completion is higher in vocational programmes than in general
ones (Table B3.1).
As many countries aim to develop their upper secondary vocational programmes in the hope of better preparing students for
the labour market, the comparatively lower completion rate for these programmes is concerning. It highlights the challenge
faced by educators and policy makers alike of not only attracting students to vocational tracks, but also of supporting them
through successful completion. Some countries have been successful in considerably increasing completion rates in
vocational programmes and diminishing the gap between vocational and general programmes, however (Box B3.2). It is
important to note, however, that there is a wide variation in size, duration and even completion rates of vocational programmes
across countries.

Box B3.1. Transition between lower and upper secondary education
The transition from lower secondary to upper secondary education is an important step in students’ academic trajectory.
Ensuring a smooth transition helps to foster higher achievement gains and prevent students from dropping out (OECD,
2011[1]).
After having completed lower secondary education, students face many options: transition courses between lower and
upper secondary level, basic vocational education, general education courses or no immediate entry into upper secondary
level. Whatever the programme orientation chosen, the rate of immediate transition to upper secondary level shows the
percentage of students who complete lower secondary education and start upper secondary education straight away. This
rate varies widely across countries with available data, reaching almost 100% in Belgium, Japan, Korea, Latvia and
Slovenia (metadata questions on policies and system characteristics). However, lower rates of immediate transition are
not necessarily a negative outcome; they could reflect a more flexible educational system in which it is common for students
to re-enter education later on, thus delaying their entry into upper secondary education.
In most countries with available data, successful completion of lower secondary level is sufficient to give students access
to upper secondary education. However, when a national end-of-year examination is required to move from one level to
another, some education authorities have introduced stricter conditions for entry into general upper secondary programmes
than into vocational ones. In Norway, students must pass an exam with a minimum score to enter a general programme,
whereas they need an educational agreement with a company to enter a vocational pathway. In Iceland, longer general
programmes require higher grades than short ones but no specific exam is needed to enter upper secondary education.
Overall, countries have a distinct structure for lower and upper secondary education. Some studies have highlighted the
benefits of combining primary, lower and upper secondary education in terms of school belonging (OECD, 2011[1]), which in
turn is inversely related to depression, social rejection and school problems (Anderman, 2002[2]). However, there is no onesize-fits-all solution, and the choice of a particular pattern depends on the characteristics of the national educational
system.

Completion rate by gender
In every country with available data (both true and cross cohort), women are more likely than men to complete upper
secondary education, both within the theoretical duration and two years after (Table B3.1). On average across countries and
economies with true cohort data, 76% of women graduated from upper secondary education within the theoretical duration of
the programme, compared to only 68% of men. The difference in completion rates between women and men by the theoretical

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192  B3. WHO IS EXPECTED TO COMPLETE UPPER SECONDARY EDUCATION?
duration is at least 11 percentage points in the Flemish Community of Belgium, Iceland, Italy, Norway and Portugal. The
gender gap narrows two years after the theoretical duration of the programme, when the completion rate among women
increases to 84% and among men to 78% (Table B3.1).
In all countries and economies except Finland and Sweden, the gap in completion rate between men and women narrows or
remains the same within the two years after the end of the theoretical duration of programmes, meaning relatively more men
tend to delay graduation. Many factors may contribute to this delay, one of which is the higher incidence of grade repetition
among men, who are more likely than women to repeat a grade even after accounting for students’ academic performance
and self-reported behaviour and attitudes (OECD, 2016[3])
The difference between upper secondary completion rates for women and men tends to be smaller among countries with
cross cohort data. On average, the completion rate for women is 4 percentage points higher than for men, and the difference
reaches 8 percentage points in Slovenia and Spain.
The gender gap also varies considerably depending on the programme orientation at entrance. In all countries with true cohort
data, the completion rate of women is higher than that of men, whatever their programme orientation (Figure B3.4), except in
Lithuania for students who entered a vocational programme. While the gender gap in favour of women tends to be similar for
students entering a general or vocational programme (7 percentage points) within the theoretical duration plus two years, the
completion rate of men in vocational programmes is equal or significantly higher than that of women in some countries
(Table B3.1).

Figure B3.4. Completion rate of upper secondary education within the theoretical duration plus two years,
by gender and programme orientation at entrance (2018)
Entered a general pr ogr amme
Women
Men

%
100

Entered a vocational pr ogr amme
Women
Men

90
80
70
60
50
40
30
20

Brazil

Latvia

Chile

Portugal

Iceland

Austria

Colombia

Sweden

New Zealand

Italy

Norway

Lithuania

Netherlands

Canada 2

Estonia

Denmark

Finland2

Switzerland

Belgium2, 3

France2,4

0

United States 1

10

1. Year of reference 2013 for the theoretical duration and 2015 for the theoretical duration plus two years.
2. Year of reference 2017.
3. The data only refer to the Flemish Community.
4. The standard errors are included when data are provided through a survey.
Countries are ranked in descending order of the completion rates of women who entered a general programme.
Source: OECD (2020). OECD (2020), Table B3.1. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2 https://doi.org/10.1787/888934163610

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B3. WHO IS EXPECTED TO COMPLETE UPPER SECONDARY EDUCATION?  193

Box B3.2. Trends in completion rates of upper secondary education, by programme orientation, within
the theoretical duration plus two years
Increasing the number of students who complete upper secondary education is a priority for many education policy makers.
However, this is a challenging goal, which may require changes at the system, school and classroom levels. Figure B3.5
shows trends in completion rates broken down by programme orientation. The reference years used for the trend
comparison in each country vary according to data availability (as indicated below the country’s name on the horizontal
axis), and therefore cross-country comparisons cannot be made from these data.
It is, however, possible to observe that the Flemish Community (Belgium), Finland, France and Norway have been able to
increase completion rates over recent years for both general and vocational programmes in upper secondary education.
In all four countries, the completion rate for vocational programmes has increased by more than for general programmes.
In France, the total upper secondary completion rate increased by 8 percentage points between 2005 and 2017, driven
mostly by an increase of 10 percentage points in the completion rate for vocational programmes. A sharp increase in
completion rates for vocational programmes can also be observed in the Flemish Community of Belgium and Finland from
2010 to 2017 and in Norway between 2012 and 2018. In the Netherlands and Estonia, an increase in completion rates for
vocational programmes was accompanied by a decrease in completion rates for general programmes.
In Sweden, an upper secondary school reform in 2011 may help explain the trend between 2010 and 2018. This has
meant, among other things, that higher demands have been introduced for completion/graduation.

Figure B3.5. Trends in completion rates of upper secondary education within the theoretical duration
plus two years, by programme orientation
Percentage point di fference
in completion rate

Total upper secondary

(most recent year – less recent year)

General programmes

Vocational programmes

12
10
8
6
4
2
0
-2
-4
-6

France
(2005-2017)

Iceland
(2010-2018)

Norway
(2012-2018)

Chile
(2010-2018)

Belgium1
(2010-2017)

Finland
(2010-2017)

Netherlands
(2010-2018)

Denmark
(2010-2018)

Austria
(2012-2018)

Estonia
(2011-2018)

Sweden2
(2010-2018)

How to read this figure: In France, the completion rate for total upper secondary education increased by 8 percentage points from 2005 to 2017. In Sweden, it
decreased by 3 percentage points from 2010 to 2018.
Note: Completion rate by the theoretical duration of the programme plus two years.
1. The data only refer to the Flemish Community.
Countries are ranked in descending order of the percentage-point change in completion rates of upper secondary programmes.
Source: OECD 2020 ad-hoc survey on completion rates. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2 https://doi.org/10.1787/888934163629

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194  B3. WHO IS EXPECTED TO COMPLETE UPPER SECONDARY EDUCATION?

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 N and the theoretical duration plus two years (N+2). 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 ID numbers for students) or a cohort of students used for conducting a
longitudinal survey.
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. Under the assumption of constant student
flows (constant increase or decrease in the number of students entering a given ISCED level throughout the years), the cross
cohort completion is closer to a total completion rate (i.e. the completion rate of all students, regardless of the time it took
them to graduate). As such, in countries where a large share of students do not graduate “on time” given the theoretical
duration of the programme, the cross cohort completion may be more comparable to longer time frames of the true cohort
completion.
The theoretical duration of studies is the regulatory or common-practice time it takes a full-time student to complete a level
of education. True cohort completion is measured within two time frames: by the end of the theoretical duration and by the
end of the theoretical duration plus two years. The theoretical duration always refers to the programme in which the student
originally entered upper secondary education. This means that even if a student transfers to a different programme with a
different duration they will still be registered according to the programme in which they originally entered the level. Please see
Annex 3 (https://doi.org/10.1787/69096873-en) for information on each country’s theoretical duration for general and
vocational upper secondary programmes.
The programme orientation can refer either to the programme in which the student originally entered upper secondary
education or to the programme from which the student graduated. Both types of analysis are included in the indicator. The
titles, subtitles or axis titles of the figures (and tables) will clarify which programme is being disaggregated by programme
orientation. Only programmes sufficient for level completion are included. Four programme orientations are considered in the
analysis:


general programmes (ISCED-P 343 and 344)



vocational programmes without access to tertiary education (ISCED-P 353)



vocational programmes with access to tertiary education (ISCED-P 354)



combined vocational programmes (ISCED-P 353 and 354).

The reference year for the survey is 2018 and refers to the academic year 2017/18 in countries where the academic year
runs from Sept-June. For countries submitting true cohort data, the reference year should be two years after the end of the
theoretical duration of the programme. For example, if a programme has a duration of two years, the cohort reported must
have entered upper secondary education in the academic year 2014/15. Their status is then recorded by the end of the
theoretical duration of the programme (academic year 2015/16) and two years later (academic year 2017/18). For countries
submitting cross cohort data, the year of reference corresponds to the reference year for the graduate data. Reference years
that differ from 2018 will be clearly indicated throughout the indicator (even if not noted below the charts in this paper).

Methodology
Data on completion rates refer to the academic year 2017/18 and were collected through a special survey undertaken in 2019.
Countries could submit data either using either the true cohort or cross cohort methodology.
The completion rate for both methods is calculated as the number of graduates divided by the number of entrants N or N+2
years before (where N is the theoretical duration of the programme).
For countries that submit true cohort data it is also possible to calculate the share of students still in education and the share
of students who have neither graduated nor are still enrolled – all of which is calculated within the timeframes of N and N+2.
Both shares are calculated by dividing the number of students in the given situation by the number of new entrants N or N+2
years before.

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B3. WHO IS EXPECTED TO COMPLETE UPPER SECONDARY EDUCATION?  195

References
Anderman, E. (2002), “School effects on psychological outcomes during adolescence”, Journal of Educational
Psychology, Vol. 94/4, pp. 795-809, http://dx.doi.org/10.1037/0022-0663.94.4.795.

[2]

CEDEFOP (2011), The Benefits of Vocational Education and Training, Publication Office of the European Union,
Luxembourg.

[4]

OECD (2016), Education at a Glance 2016, OECD Publishing, Paris, https://dx.doi.org/10.1787/eag-2016-en.

[3]

OECD (2011), Reviews of National Policies for Education, Improving Lower Secondary Schools in Norway,
Reviews of National Policies for Education, OECD Publishing, Paris, https://doi.org/10.1787/9789264114579en.

[1]

Indicator B3 Tables
Table B3.1 Completion rate of upper secondary education, by programme orientation at entrance and gender (2018)
Table B3.2 Distribution of entrants to upper secondary education by programme orientation and outcomes after the theoretical
duration and after the theoretical duration plus two years (2018)
Cut-off date for the data: July 19th, 2020. Any updates on data can be found on line at http://dx.doi.org/10.1787/eag-dataen. More breakdowns can also be found at http://stats.oecd.org/, Education at a Glance Database.
StatLink: https://doi.org/10.1787/888934163496

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196  B3. WHO IS EXPECTED TO COMPLETE UPPER SECONDARY EDUCATION?
Table B3.1. Completion rate of upper secondary education, by programme orientation at entrance and gender (2018)
Completion rate of full-time students who graduated from any programme

Note: The data presented in this table come from an ad-hoc survey and only concern initial education programmes. For true cohorts, the reference year (2018, unless noted
otherwise) refers to the year of graduation by the theoretical duration plus two years. See Definitions and Methodology sections for more information.
1. Year of reference 2017.
2. Students enter a general upper secondary education programme and only split into general and vocational programmes after one or more academic years.
3. Year of reference 2013 for the theoretical duration and 2015 for the theoretical duration plus two years.
Source: OECD/UIS/Eurostat (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888934163515
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B3. WHO IS EXPECTED TO COMPLETE UPPER SECONDARY EDUCATION?  197

Table B3.2. Distribution of entrants to upper secondary education by programme orientation and outcomes after the
theoretical duration and after the theoretical duration plus two years (2018)
True cohort only

Note: The data presented in this table come from an ad-hoc survey and only concern initial education programmes. See Definitions and Methodology sections for more
information.
The columns for "not graduated and not enrolled" may include students who left the country before graduation.
Students who continued their studies in the adult-education system are included in the columns for “not graduated and not enrolled”
1. Year of reference 2017.
2. Students enter a general upper secondary education programme and only split into general and vocational programmes after one or more academic years.
3. Year of reference 2013 for the theoretical duration and 2015 for the theoretical duration plus two years.
Source: OECD/UIS/Eurostat (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888934163534

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198  B4. WHO IS EXPECTED TO ENTER TERTIARY EDUCATION?

Indicator B4. Who is expected to enter
tertiary education?
Highlights


If current entry patterns continue, it is estimated that 49% of young adults (excluding international students) will
enter tertiary education for the first time before the age of 25 on average across OECD countries. Most of them
will enter a bachelor‘s or equivalent programme.



Short-cycle tertiary programmes are the second most common route of entry into tertiary education after
bachelor’s programmes. Men are more likely than women to enter short-cycle tertiary programmes in countries
where science, technology, engineering and mathematics (STEM) fields are more prevalent at this level. In
contrast, where health and education fields are more prevalent, then the share of women at this level increases.



At higher levels of education, 14% of young adults are expected to enter master’s or equivalent programmes
(excluding international students) before the age of 30, dropping to 1% at doctoral level.

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 and too uncertain. Not all students develop skills at the same pace, and the 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 educational level 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 further 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,
and 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 by looking at
differences in entry rate across different demographic groups. 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.

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B4. WHO IS EXPECTED TO ENTER TERTIARY EDUCATION?  199

Figure B4.1. Share of women and distribution by field of study of new entrants into short-cycle tertiary
level (2018)
Share of women among new entrants into short-cycle tertiary education
Science, technology, engineering and mathematics
Agriculture, forestry, fisheries and veterinary + Generic programmes
Services
Arts and humanities
Business, administration and law
Social sciences, journalism and information
Health and welfare
Education

%
100
90
80
70
60
50
40
30
20

(4%)

(23%)

(6%)

(1%)

(6%)

Slovenia

Portugal

Italy

Norway

(2%)

Mexico

Netherlands

(28%)

(9%)

(34%)
Spain

Denmark

Ireland

(9%)
Sweden

(7%)

(19%)
Israel

(17%)

(28%)
France

Iceland

(31%)
Korea

Colombi a

(5%)

(49%)

(16%)

Luxembourg

(44%)
Turkey

OECD average

Russian Federation

(14%)

Chile

(35%)

(44%)

United Kingdom

Austria

(15%)

Costa Rica

EU23 average

(3%)

(7%)

Switzerland

(4%)

(30%)
New Zealand

(28%)
Japan2

Hungary

(27%)
Latvia

Germany (0.03%)

(1%)

(0.5%)
Czech Republic

Poland (0.02%)

Slovak Republic

Belgium1

0

(1%)

10

How to read this figure: In Norway, the entry rate for short-cycle tertiary is 6% and women make up 19% of short-cycle tertiary new entrants. At this level 65% of new
entrants are studying science, technology, engineering and mathematics (STEM), 22% arts and humanities, 12% services and 1% business.
Note: The percentage in parenthesis is the total entry rate in short-cycle tertiary programmes. It informs on how prevalent these types of programmes are in the
education system of each country.
1. Short-cycle tertiary: data refer to the Flemish Community of Belgium only.
2. All fields of study include information and communication technologies (ICT).
Countries are ranked in descending order of the share of women among short-cycle tertiary new entrants in 2018.
Source: OECD/UIS/Eurostat (2020), Table B4.2 and Education at a Glance Database (http://stats.oecd.org/). See Source section for more information and Annex 3
for notes (https://doi.org/10.1787/69096873-en).
Statlink2 https://doi.org/10.1787/888934163724

Other findings


Short-cycle tertiary programmes are mostly vocational, and they provide access to higher tertiary education in
most OECD countries.



The entry rate into short-cycle tertiary programmes by the age of 25 is about the same among women as among
men, on average across OECD countries. In most countries with high short-cycle tertiary entry rates (20% and
more), the entry rate among women is higher than among men.

Note
Short-cycle tertiary and master’s long first degree programmes may not exist or are rare in a number of educational
systems. To highlight the diversity of vocational education and training (VET) programmes at tertiary level across OECD
member and partner countries, the analysis includes countries where short-cycle tertiary programmes, mostly vocational,
may represent a very small part of the educational system.

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200  B4. WHO IS EXPECTED TO ENTER TERTIARY EDUCATION?

Analysis
First-time entrants to tertiary education
If current entry patterns continue, it is estimated that 49% of young adults (excluding international students) will enter tertiary
education for the first time before the age of 25 on average across OECD countries. However, first-time entry rates into tertiary
education can vary significantly across countries and depend on the context within countries, the availability of programmes
and their prevalence within the educational landscape. For example, Chile and Turkey have some of the highest first-time
tertiary entry rates among OECD countries, mostly inflated by a high rate of entry into short-cycle tertiary education
(Table B4.1). Conversely, Luxembourg reports the lowest first-time tertiary entry rates among OECD countries, due to the
very high share of national tertiary students enrolled abroad (see Indicator B6).

Pathways into tertiary education
In slightly more than half of OECD and partner countries, first-time entrants into tertiary education can choose from one of the
three types of programme: short-cycle tertiary, bachelor’s or a master’s long first degree. A short-cycle tertiary programme
(ISCED 5) is typically a short two to three year programme that develops occupation-specific skills and that most often
prepares students for direct entry into the labour market. A bachelor’s or equivalent programme (ISCED 6), allows students
to obtain a first degree qualification over three to four years, that would then be required if they wish to access a master’s or
equivalent programme (ISCED 7), which is a second stage qualification (one to two years), and then a doctoral or equivalent
programme (ISCED 8). A master’s long first degree (ISCED 7-LFD) does not require students to first obtain a bachelor’s
degree, but when completed, after at least five years, the qualification attained is at the same level as a second stage master’s
degree (OECD/Eurostat/UNESCO Institute for Statistics, 2013[1]).
The level at which students first enter tertiary education is indicative of the length of their studies and the employment or
further learning opportunities they will have access to once they graduate. The distribution of students across each tertiary
entry-level programme depends on each programme’s availability, capacity and entry requirements within the national
education system. The transition between programmes at the tertiary level is not always clearly distinguished and it may be
possible to combine programmes and transfer credits from one programme to another.
On average across OECD countries, in 2018, more than three-quarters of first-time tertiary entrants enrolled in a bachelor’s
programme. However, the predominance of such programmes in the educational landscape varies greatly from country to
country. In Belgium, the Czech Republic, Estonia, Finland, Greece, India, Lithuania, Mexico, the Netherlands and
the Slovak Republic, more than 90% of first-time tertiary students 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, Colombia, Japan, the Russian Federation, Saudi Arabia, Spain, Turkey and
the United States, more than one-third of first-time entrants into tertiary education entered short-cycle programmes, twice the
OECD average of 17% (Figure B4.2).
Despite the benefits offered by short-cycle tertiary programmes, they are not available in all countries. Where they are, they
are not always very attractive to students. In 12 OECD countries, short-cycle tertiary programmes represent less than 10%
of first-time entrants into tertiary education (Figure B4.2). Master's programmes are the least common entry point into tertiary
level. On average across OECD countries with available data, 6% of first-time entrants into tertiary education are in master's
programmes, and this only exceeds 15% in Austria, Germany, Hungary and Sweden. They include highly specialised fields
such as medicine, dentistry or, in some cases, law and engineering (OECD/Eurostat/UNESCO Institute for Statistics, 2015[2]).
In most countries, the majority of first-time tertiary entrants at master's level enter through master’s long first degrees. In
the United Kingdom, where master’s long first degrees are not available, first-time tertiary entrants at master's level are
students who are entering programmes based on industry experience rather than academic qualifications.

Profile of first-time entrants to tertiary education
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). On average across OECD countries, the average age of first-time entrants was 22 years old in 2018.
However, there are large disparities among countries. The average age ranges from younger than 20 years old in Belgium
and Japan, to over 24 years old in Denmark, Sweden and Switzerland (Table B4.1).

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B4. WHO IS EXPECTED TO ENTER TERTIARY EDUCATION?  201
Average ages can mask variations in the age distribution across first-time tertiary entrants. Although there are 10 OECD
countries where the average age of first-time entrants is 22 years old, within these countries the share below the age of 25
ranges from 87% in the Czeck Republic and Poland to 74% in Colombia. However, the average age is generally correlated
with the share of first-time entrants below the age of 25 across OECD countries. This ranges from almost 100% in Japan,
which is one of the countries with the lowest average age (18 year-old), to 66% in Sweden, which is one of the countries with
the highest age (25 year-old) (Table B4.1).
Various factors may explain the differences in the age of first-time entrants into tertiary education. 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 in (OECD, 2019[3])). This is the case in Israel, for
example, where military service is compulsory. Delayed entry can indicate difficulties in access to tertiary education, either
through selective entry requirements or numerus clausus (a fixed maximum number of entrants admissible to an academic
institution). In Finland and Sweden, admissions are restricted for many programmes and fields of study, resulting in more
than 60% of applicants being rejected (Indicator D6 in (OECD, 2019[3])). A wide age distribution may also reflect the existence
of second-chance and lifelong learning programmes characteristic of flexible pathways allowing for re-entry into the education
system. It can also reflect financial challenges in affording the private costs associated with higher education.
Countries with lower average entry ages are 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 education 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[4]).
The prevalence of the different entry-level programmes and the student profile each programme tends to attract also affect
the average age of first-time entrants. Students tend to enrol in bachelor’s programmes shortly after upper secondary school,
while short-cycle tertiary programmes tend to attract older adults, potentially with some employment experience. Belgium and
the Netherlands, where 98-99% of first-time entrants into tertiary education are bachelor’s students, are unsurprisingly among
the countries with the lowest average entry age.
International mobility has expanded significantly in the past two decades. Higher demand for high-quality tertiary education
worldwide, coupled with specific policies to promote student mobility within a geographic region (as is the case in Europe), or
to support students in studying abroad specific fields of high relevance in the country of origin have largely driven the growth
of international student mobility. For example, among European countries, the Erasmus Programme (European Action
Scheme for the Mobility of University Students) plays an important role in students’ mobility whatever the entry-level
programme. International students provide an additional income stream for educational institutions and contribute to the
economy of their host country. 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 (see Indicator B6). On average across OECD countries, 10% of first-time entrants into
tertiary education were international students in 2018. Some countries are better than others at attracting international
students. The share of international students among first-time entrants to tertiary programmes ranges from 1% or less in
Chile, Colombia and Mexico to 22-23% in Austria, Hungary and Luxembourg and 31% in New Zealand (Table B4.1).
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[5]). Women are more likely to enter tertiary
education before the age of 25 than men, and this is true in all OECD countries. On average across OECD countries in 2018,
the first-time tertiary entry rate (excluding international students) among women below the age of 25 was 55% compared to
44% for men. Nonetheless, the gender gap varies in favour of women from less than 2 percentage points in Luxembourg and
Mexico to 18 or more percentage points in the Czech Republic, Iceland and New Zealand (Table B4.1).
On average across OECD countries, 54% of first-time entrants into tertiary education are women. In some countries, men are
particularly under-represented, for example in the Czech Republic, Iceland and Sweden, where women make up 58-60% of
first-time entrants into tertiary education. Conversely, women are mainly under-represented in few non-OECD G20 countries
with available data. In India and Saudi Arabia they make up 45-47% of first-time entrants into tertiary education (Table B4.1).

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202  B4. WHO IS EXPECTED TO ENTER TERTIARY EDUCATION?

Figure B4.2. Distribution of first-time entrants into tertiary education by level of education (2018)
Master’s or equivalent
Bachelor’s or equivalent
Short-cycle tertiary

%
100
90
80
70
60
50
40
30
20

Lithuania

India

Finland

Greece

Estonia

Germany

Belgium1

Czech Republic

Italy

Netherlands

Slovak Republic

Switzerland

Mexico

Norway

Iceland

Portugal

Hungary

EU23 average

Sweden

Indonesia

OECD average

Slovenia

United Kingdom

Denmark

New Zealand

Israel

Luxembourg

Saudi Arabia

Japan

Colombia

Chile

Spain

Turkey

Austria

Russian Federation

0

China

10

1. Short-cycle tertiary: data refer to the Flemish Community of Belgium only.
Countries are ranked in descending order of the share of first-time entrants going into short-cycle tertiary programmes.
Source: OECD/UIS/Eurostat (2020), Table B4.1. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2 https://doi.org/10.1787/888934163743

Short-cycle tertiary education
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. Unsurpringly, most programmes at this level have a vocational orientation. Only in Australia, Iceland, Japan,
New Zealand, Sweden and the United Kingdom do some short-cycle tertiary programmes have a general orientation (see
Indicator B7).
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. In most countries, the employment rates for adults with shortcycle tertiary attainment are lower than for those with a bachelor’s degree, but there are exceptions in countries where shortcycle education is especially prevalent. For example, employment rates are slightly higher among adults with a short-cycle
tertiary degree than among those with a bachelor’s in Austria, Denmark and Korea (see Indicator A3). In these countries,
short-cycle tertiary entry rates below the age of 25 (including international students) range from 12% to 30%, higher than the
OECD average of 11%. Similarly, the earnings of workers with a short-cycle tertiary degree are the same or higher than those
of workers with a bachelor’s degree in Austria (see Indicator A4).
Short-cycle tertiary education is the second most common route into tertiary education on average across OECD countries
after the bachelor’s degree. The short-cycle tertiary entry rate for students below the age of 25 (excluding international
students) varies from 1% or less in Belgium, the Czech Republic, Germany, Italy, Poland, the Slovak Republic and
Switzerland, to 29-30% in Austria, Chile and the United States. In 2018, it was the main route of entry to tertiary education in
Austria, China, and the Russian Federation (Figure B4.2). In some countries, this is due to the particular structure of these
programmes. For example, in Austria and in the Russian Federation, short-cycle tertiary programmes span upper secondary
and tertiary levels of education, leading to the wider take up of this level of education (Table B4.2).
On average across OECD countries, 96% of students in short-cycle tertiary education are enrolled in vocational education
and training (VET) programmes. In about three-quarters of countries with available data, all students in short-cycle tertiary
education are enrolled in VET programmes, and for the remaining countries, the percentage varies from 50% in
the United Kingdom to 96% in Australia (see Indicator B7).

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B4. WHO IS EXPECTED TO ENTER TERTIARY EDUCATION?  203

Pathways into and out of short-cycle tertiary programmes
Although short-cycle tertiary programmes are primarily vocational, students from upper secondary vocational programmes
are not necessarily more likely to enter them. In 2017, only 21% of entrants to short-cycle tertiary programmes had completed
an upper secondary vocational programme in France compared to 69% in Norway (Table B5.2 in (OECD, 2019[3])). Students
from upper secondary vocational programmes represent between 43% and 60% of entrants into short-cycle tertiary
programmes in Sweden, Chile and Slovenia (OECD, 2019[3]). Direct access from upper secondary vocational to tertiary
programmes varies across countries: in 2018, the share of upper secondary vocational students enrolled in programmes
giving direct access to tertiary education varied from 0% in Norway and Sweden to 62% in France, 70% in Slovenia and 100%
in Chile. However, these differences also highlight the various pathways available for upper secondary vocational students
wishing to pursue tertiary education. For instance, in Sweden, students enrolled in upper secondary vocational programmes
can add more academic courses to their curriculum in order to access higher education. In some countries, access is indirect
and requires the prior completion of an intermediate level. In Hungary, for example, non-tertiary post-secondary education is
a stepping stone for upper secondary vocational graduates into tertiary education (see Indicator B7).
While short-cycle tertiary programmes in most countries give access to further studies at bachelor’s or master’s level, in some
countries they do not, even if they are sufficient for this level completion (Figure B4.3). In Colombia, Germany, Israel, Italy
and Sweden, it is not possible for students to access directly to the higher educational level after graduating from a shortcycle tertiary programme. In Colombia and Israel, programmes at this level are dedicated to adults wishing to develop new
skills. Adult programmes may be second-chance programmes, where individuals who did not obtain the qualifications they
need during their initial education are provided another opportunity to do so. Such programmes may also aim to get individuals
back into employment as quickly as possible. In these situations, flexible pathways from short-cycle tertiary to higher levels
of education may not then be necessary.

Figure B4.3. Distribution of students enrolled in short-cycle tertiary programmes by level of access to the
higher educational level (2018)
%
100

No access
Direct access to the higher educational level

90
80
70
60
50
40
30
20
10
0

Countries and economies are listed in alphabetical order.
Source: OECD/UIS/Eurostat (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2 https://doi.org/10.1787/888934163762

In some countries, different short-cycle tertiary programmes are offered, some of which do provide access to the higher
educational level, and some of which do not (Austria, France and Iceland). For example, in Austria, Berufsbildende höhere
Schule provides access to the higher educational level whereas Meisterschule, Werkmeister and Bauhandwerkerschule do
not. In some countries, programmes classified as insufficient for level completion may still provide access to the higher
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204  B4. WHO IS EXPECTED TO ENTER TERTIARY EDUCATION?
educational level. For example, in France, students who complete a one-year short-cycle tertiary programme classified as
insufficient for level completion may enter a bachelor programme (mostly vocational) in the first year of the programme. In
contrast, those that completed a longer short-cycle tertiary programme may enter directly in the third year of the bachelor
programme after graduation.
Countries are promoting the development of pathways from initial VET programmes to further and higher educational levels.
Tertiary education allows students to acquire the skills they require to respond to today’s labour-market needs. On the one
hand, there is continued demand for employees with skills that are not typically taught in academically oriented tertiary
programmes. On the other hand, some people find academic learning unattractive, too long and too uncertain. Short-cycle
tertiary vocational education matches those labour-market needs and those students’ expectations. Vocational education and
training, may have been primarily designed to train people for a lifetime occupation, but rapid changes in the labour market,
driven by technology, changing the skillsets required in many occupations and eliminating some types of job altogether while
also creating new ones, suggest the need for a flexible tertiary education. The development of effective pathways serves
multiple policy objectives, such as increasing the attractiveness of initial VET by meeting students’ aspirations, and removing
any perception of VET tracks as dead ends; helping to meet growing economic demands for higher level skills and
qualifications; supporting lifelong learning; removing wasteful barriers, such as requirements to repeat course material; and
improving equity by promoting access to higher level programmes among more disadvantaged groups (UNESCO-UNEVOC,
2017[6]).
Many learning pathways from initial short-cycle tertiary to higher educational level are open in principle (Figure B4.3), “but
rarely travelled” (Musset et al., 2019[7]). Graduates from this level may prefer to directly enter employment, either for financial
reasons or due to challenges in gaining recognition of their degree to advance to higher educational level. To improve the
pathways from initial short-cycle tertiary to higher education, reforms have been introduced in some countries to facilitate
credit recognition. For example, in Australia, the national qualification framework (NQF) standardises the contents of
knowledge, skills and attitudes required to observe “levels” of attainment and offers formal pathways from post-secondary
VET courses into bachelor’s programmes, whereby graduates receive credits for subject, units or years of study that they
have followed, which are taken into consideration when they apply for related degree courses in general higher education.
Nonetheless, in Australia, only 9% of bachelor’s entrants come from (vocational) technical and further education colleges
(Field and Guez, 2018[8]).
Some reforms have aimed to diversify the programmes on offer and increase the attractiveness of short-cycle tertiary
programmes. For instance, in 2016 Chile created by law (Law N° 21.910) 15 new centres for VET in tertiary education, one
per region, facilitating student access to VET throughout the country. In Sweden, higher vocational education (yrkeshögskola)
is currently going through an expansion and increasing the number of student places. The expansion began in 2018 and will
take place in stages until 2022 when the number of full-time equivalent student places will have increased by 45%. England
(United Kingdom) implemented a reform encouraging sustainable employer investment in apprenticeship training by placing
the control of apprenticeship funding in the hands of employers. Israel upgraded the status and quality of practical engineer
programmes, and improving their correspondence with market needs.

Profile of new entrants to short-cycle tertiary education
On average across OECD countries, the average age of new entrants to short-cycle tertiary programmes was 25 years old in
2018. However, there are large differences among countries. The average age varies from 22 or younger in Austria, Belgium,
Costa Rica, France, Japan, Korea, Luxembourg, Mexico and Portugal, to 28 and older in Denmark, Iceland, Ireland, Latvia,
New Zealand, Poland, Sweden, Switzerland and the United Kingdom. The average age is reflected in the share of new
entrants below the age of 25 which varies from more than 90% in Belgium, France, Japan, Korea and Mexico to below 35%
in Iceland, Poland, Sweden and Switzerland. In all countries except Belgium, France, Israel, Luxembourg and Mexico, the
share of new entrants under the age of 25 is higher at bachelor’s level than at short-cycle tertiary level (Table B4.2 and
Table B4.3).
The disparities in the average age of new entrants in short-cycle tertiary programmes depends on the profile of students
entering the programmes. In some countries, students tend to have some work experience before enrolling in these degrees.
Even in countries with direct access to this level from upper secondary education, students are typically older as they tend to
enter from upper secondary vocational programmes where completion rates are lower than for upper secondary general
programmes (see Indicator B3).

EDUCATION AT A GLANCE 2020 © OECD 2020

B4. WHO IS EXPECTED TO ENTER TERTIARY EDUCATION?  205
On average across OECD countries, 5% of new entrants into short-cycle tertiary programmes were international students in
2018, the lowest share across all tertiary levels of education. In all countries except Chile, Denmark, Iceland, Ireland and Italy,
the share of international new entrants at bachelor’s level or equivalent is greater than at short-cycle tertiary level (Table B4.2
and Table B4.3).
There are also large disparities across countries in the share of international students among new entrants, ranging from
close to zero in Colombia, Germany, Mexico, Poland, Sweden and Switzerland to 18% in New Zealand and 39% in Iceland.
As students in short-cycle tertiary programmes tend to be older than those enrolled in other tertiary programmes, they tend
to be more likely to have family or personal obligations that may hinder their international mobility (Kirsch and Beernaert,
2011[9]).
On average across OECD countries, 27% of new entrants into short-cycle tertiary programmes in 2018 enrolled in the broad
field of science, technology, engineering and mathematics (STEM); 25% in business, administration and law; 15% in health
and welfare; 13% in services; 11% in arts and humanities and the remainder in education; agriculture, forestry, fisheries and
veterinary; and social sciences, journalism and information. Promoting the study of STEM fields has become a priority in
many countries as science-related competencies, problem solving and quantitative analysis are considered essential in
today’s data-based economy and are in high demand in the labour market. In Austria, Chile, Israel, Korea, Slovenia and
Spain, where short-cycle tertiary entry rates for students under the age of 25 range from 13% (Israel) to 31% (Chile), STEM
is the largest field of study with the share of new entrants ranging from 27% (Chile) to 63% (Israel) (Table B4.2).
There are large disparities in the distribution of new entrants by fields of study across countries at short-cycle tertiary level. In
Belgium, the Czech Republic and Poland, where the short-cycle tertiary entry rate below the age of 25 is 1% or lower, all
students are enrolled in just one broad field of study: health and welfare in Belgium and Poland, and arts and humanities in
the Czech Republic. Conversely, in Germany, Iceland, Italy, the Slovak Republic and Switzerland, where the entry rate into
short-cycle tertiary education is also 1% or lower, students enter a variety of fields of study (Figure B4.1).

Figure B4.4. Entry rates into short-cycle tertiary for new entrants below the age of 25, by gender (2018)
Excluding international students
Men
Women

%
35
30
25
20
15
10

Poland

Italy

Germany

Switzerland

Czech Republic

Slovak Republic

Belgium1

Netherlands

Iceland

Norway

Ireland

Sweden

Mexico

Portugal

Hungary

Luxembourg

EU23 average

Denmark

United Kingdom

Colombia

OECD average

Slovenia

New Zealand

Spain

Latvia

Korea

Turkey

United States

Chile

0

Austria

5

1. Short-cycle tertiary: data refer to the Flemish Community of Belgium only.
Countries are ranked in descending order of the short-cycle tertiary entry rates for women below the age of 25.
Source: OECD/UIS/Eurostat (2020), Table B4.2. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2 https://doi.org/10.1787/888934163781

On average across OECD countries, 53% of new entrants into short-cycle tertiary programmes are women. In some countries,
men are particularly under-represented at this level, as in Belgium, the Czech Republic, Poland and the Slovak Republic,
EDUCATION AT A GLANCE 2020 © OECD 2020

206  B4. WHO IS EXPECTED TO ENTER TERTIARY EDUCATION?
where women make up between 65% and 86% of new entrants. Conversely, women are particulary under-represented in
Italy, Mexico, Norway, Portugal, Slovenia and Saudi Arabia where they make up between 19% and 40% of new entrants into
short-cycle tertiary programmes (Table B4.2).
The disparities in the share of women among new entrants to short-cycle tertiary programmes may depend on the prevalence
of some fields of study. Women in short-cycle tertiary programmes are under-represented in STEM fields while they tend to
dominate in the field of health and welfare (OECD, 2019[3]). Hence, the share of women among new entrants into short-cycle
tertiary across all fields of study tends to be lower when STEM fields make up a larger proportion of these programmes. In
Mexico, Norway, Portugal and Slovenia (where the entry rates vary from 4% to 23%), STEM fields make up a large share of
these programmes while the shares of women among new entrants are among the lowest, below 40% (Figure B4.1). Students’
choice of field of study is guided by a variety of factors, including career opportunities and their aspirations after education.
One explanation of the under-representation of women in some fields could be that they fear they will not have equal career
opportunities in those fields, after completing their education.
The gender distribution is more balanced at short-cycle tertiary level than across other tertiary levels in OECD countries. In
2018, on average across OECD countries, the entry rate to short-cycle tertiary programmes (excluding international students)
was the same for women as for men (10%), whereas women have a signficantly higher entry rate at bachelor's level (49% for
women versus 38% for men). However, this difference varies widely among countries. In Norway, Portugal and Slovenia, the
gender gap in short-cycle tertiary entry rates is in favour of men by 3-7 percentage points, while in Austria, Latvia, New
Zealand and Turkey, the entry rate for women is 5-6 percentage points higher than the rate for men. In countries with high
short-cycle tertiary entry rates, the entry rate for women below the age of 25 tends to be higher than for men (Figure B4.4).

Bachelor’s, master’s and doctoral education
Bachelor’s programmes are the most common route into tertiary education on average across the OECD, accounting for 77%
of first-time entrants into tertiary education. In Greece and India, it is the only route into tertiary education, as 100% of firsttime entrants enter bachelor’s programmes.
On average and excluding international students, the bachelor’s entry rate is 44% across OECD countries, the master’s entry
rate is 14% and the doctoral entry rate is just 1%. The low entry rate at doctoral level reflect the substantial investment required
from both individuals and governments to develop this level of education, as the key entry point into a career in academic
research. Furthermore, in some countries, adults with doctorates still have lower employment rates than those with a master’s
degree. Nonetheless, 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 (OECD, 2019[3]).

Profile of new entrants to bachelor’s, master’s and doctoral programmes
On average across OECD countries, 84% of new entrants into bachelor’s programmes or equivalent are below the age of 25.
The share varies from more than 96% in Belgium, Japan and Korea, to 68-69% in Israel, Sweden and Switzerland
(Table B4.3). Differences in the share of new entrants below the age of 25 reflect the possibilities of re-entry into the education
system among adults and selective entry requirements for bachelor’s programmes. Traditionally, students enter a bachelor’s
programme immediately after completing upper secondary education, and this remains true in many countries. However, in
some countries, the transition from upper secondary to tertiary education may occur at a later age, as discussed above (see
first-time entrants section).
On average across OECD countries, 74% of new entrants at master’s level and 58% at doctoral level are below the age of
30. Master’s programmes may lead directly to a labour market-relevant qualification but they are also a prerequisite to
accessing an advanced research qualification such as a doctorate in many countries. Interestingly, in Ireland and
Luxembourg, the share of new entrants below the age of 30 is greater at the doctoral level than at the master’s level
(Table B4.2).
The share of internationally mobile students increases on average with the level of education, but this pattern varies across
countries. On average across OECD countries, international students make up 9% of new entrants at bachelor’s level, 21%
at master’s level and 29% at doctoral level. New entrants at master’s level tend to be more likely to be mobile than at bachelor’s
level in all countries, except in Greece and the Slovak Republic where the share of international students entering bachelor’s
programmes is slightly higher than at master’s level. New entrants into doctoral programmes tend to be more mobile than at

EDUCATION AT A GLANCE 2020 © OECD 2020

B4. WHO IS EXPECTED TO ENTER TERTIARY EDUCATION?  207
master’s level, but this varies across countries. In Belgium, Iceland, Netherlands, New Zealand, Norway, Portugal, Sweden
and Switzerland, the share of international students among doctoral new entrants is between 20 percentage points and almost
40 percentage points higher than in master’s programmes. In contrast, the difference is negligible (less than 1 percentage
point) in Greece, Spain and the United Kingdom. In Australia, Germany, Latvia and Lithuania, the share of international
entrants to doctoral programmes ranges from around 3 percentage points to almost 20 percentage points lower than in
master’s programmes. Doctoral studies require substantial investment from both individuals and governments and some
countries may prefer to concentrate on student mobility at master’s level. Germany, Latvia and Lithuania have some of the
lowest shares of international students at doctoral level, while Australia has the second highest share of international students
among master’s new entrants (Table B4.2).
While English-speaking countries are the most attractive destinations for students overall (see Indicator B6), other non-English
speaking countries recruit from abroad more than half of new entrants at master’s level (Luxembourg) or doctoral level
(Belgium, Luxembourg, the Netherlands and Switzerland) (Table B4.3). Some countries have been developing programmes
or changing their funding policies to attract international students at these levels of education in order to help play a leading
role in research and innovation.
On average across OECD countries and excluding international students, the first-time entry rate of women to bachelor’s,
master’s and doctoral programmes is greater than among men, but the gender gap shrinks as the level of education increases.
At bachelor’s level or equivalent, 49% of women are expected to enter a bachelor programme before the typical age of 25,
compared to 38% of men. While the entry rate among women is larger than that of men in all countries at bachelor’s level,
the gender difference varies from 3 percentage points or less in Luxembourg, Mexico and Turkey to 21-22 percentage points
in Australia and Israel. At master’s level, 17% of women are expected to enter the programme before the typical age of 30,
compared to 11% of men on average across OECD countries. The entry rate of women is higher than men for all countries
with available data, except for Turkey. At doctoral level, the entry rate among women (below the typical age of 30) is almost
equal to the rate among men, at 1% on average across OECD countries. Across OECD countries, the gender difference at
doctoral level is very limited, within the range of ±0.5 percentage points (Table B4.3).

Definitions
Entry rate is the sum of age-specific entry rates up to an age threshold. The age-specific entry rate is calculated by dividing
the number of entrants by age in a certain education level by the total population of the same age. The rate can be calculated
including and 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 below an
age threshold will enter tertiary education for the first time. The rate can be calculated including and excluding international
students in the numerator of each age-specific entry rate.
Bachelor’s/master’s/doctoral level entry rate is an estimated probability, based on current entry patterns, that a young
adult below an age threshold will enter a bachelor’s/master’s/doctoral programme during his or her lifetime. The rate can be
calculated including and excluding international students in the numerator of each age-specific entry rate.
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’s programmes (ISCED 6) or master’s programmes. First-time entrants to a master’s programme in
most cases refer to entrants to a master’s long first degree (ISCED 7-LFD), but may also include entrants to a stage of a
programme at ISCED level 7 insufficient for level or partial level completion; and students authorised to enter a master’s
programme after validation of acquired experience (VAE).
Internationally mobile students or international students are those students who left their country of origin and moved to
another country for the purpose of study.
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 enrolling for the first time into a tertiary level of education but
may have previously entered and completed a degree in another tertiary level of education.

EDUCATION AT A GLANCE 2020 © OECD 2020

208  B4. WHO IS EXPECTED TO ENTER TERTIARY EDUCATION?

Methodology
Unless otherwise indicated, entry rates are calculated as net entry rates (i.e.as the sum of age-specific entry rates) up to an
age threshold. The net entry rate for a single age is obtained by dividing the number of first-time entrants of that age for each
type of tertiary education by the total population of the corresponding age. The sum of net entry rates is calculated by adding
the rates for each year of age until the age threshold. The result represents the expected probability of entering tertiary
education for the first time before the age threshold if current entry patterns are maintained. The age threshold refers to the
upper limit for entering into a tertiary degree. Age 25 is used as the upper limit for entering into a short-cycle tertiary, bachelor’s
degree and first-time tertiary education overall. At the master’s and doctoral levels, 30 is considered to be the upper age limit
for entry.
Gross entry rates are used when data by age are missing and if the average age of entry is well below the age threshold
considered for the calculation of this indicator. In this case, the number of entrants of which the age is unknown is divided by
the population at the typical entry age (see Annex 1).
The average age of students is calculated from 1 January for countries where the academic year starts in the second semester
of the calendar year and 1 July for countries where the academic year starts in the first semester of the calendar year. As a
consequence, the average age of new entrants may be overestimated by up to 6 months while that of first-time graduates
may be underestimated by the same.
Entry rates are sensitive to changes in the education system, such as the introduction of new programmes or the number of
international students. Rates could at times be very high, during periods when there are unexpectedly high numbers of
entrants. This indicator also reports the share of first-time entrants below the age threshold, alongside the entry rate, to
provide contextual information on the relevance of the age threshold for each country.
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 tertiary programmes. When international students are
included in the calculation, the percentage of expected first-time entrants into tertiary programmes can change significantly.
For more information, please see the OECD Handbook for Internationally Comparative Education Statistics 2018 (OECD,
2018[10]) and Annex 3 for country-specific notes (https://doi.org/10.1787/69096873-en).

Source
Data refer to the academic year 2017/18 and are based on the UNESCO-UIS/OECD/EUROSTAT data collection on education
statistics administered by the OECD in 2019. Data for some countries may have a different reference year. For details, see
Annex 3 at https://doi.org/10.1787/69096873-en.

References

Field, S. and A. Guez (2018), Pathways of Progression: Linking Technical and Vocational Education and Training
with Post-Secondary Education, United Nationas Educational, Scientific and Cultural Organization (UNESCO),
https://unesdoc.unesco.org/ark:/48223/pf0000265943.

[8]

Kirsch, M. and Y. Beernaert (2011), Short Cycle Higher Education in Europe, Level 5: The Missing Link, European
Association of Institutions in Higher Education (EURASHE), https://www.eurashe.eu/library/modernisingphe/L5_report_SCHE_in_Europe_full_report_Jan2011.pdf.

[9]

Musset, P. et al. (2019), Vocational Education and Training in Estonia, OECD Reviews of Vocational Education
and Training, OECD Publishing, Paris, https://dx.doi.org/10.1787/g2g9fac9-en.

[7]

OECD (2019), Education at a Glance 2019: OECD Indicators, OECD Publishing, Paris,
https://dx.doi.org/10.1787/f8d7880d-en.

[3]

EDUCATION AT A GLANCE 2020 © OECD 2020

B4. WHO IS EXPECTED TO ENTER TERTIARY EDUCATION?  209
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.

[10]

OECD (2011), Report on the Gender Initiative: Gender Equality in Education, Employment and Entrepreneurship,
OECD, Paris, https://www.oecd.org/education/48111145.pdf.

[5]

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.

[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.

[2]

OECD/Eurostat/UNESCO Institute for Statistics (2013), International Standard Classification of Education, ISCED
2011, http://uis.unesco.org/sites/default/files/documents/international-standard-classification-of-educationisced-2011-en.pdf.

[1]

UNESCO-UNEVOC (2017), Virtual Conference Report on Pathways Between TVET and Further Education,
UNESCO-UNEVOC International Centre, Bonn, https://unevoc.unesco.org/up/VC_synthesis_19_en_2.pdf.

[6]

Indicator B4 Tables
Table B4.1

Entry rate and profile of first-time entrants into tertiary education (2018)

Table B4.2

Entry rate and profile of new entrants into short-cycle tertiary level (2018)

Table B4.3

Entry rate and profile of new entrants into bachelor's, master's and doctoral levels (2018)

Cut-off date for the data: 19 July 2020. Any updates on data can be found on line at http://dx.doi.org/10.1787/eag-dataen. More breakdowns can also be found at http://stats.oecd.org/, Education at a Glance Database.

StatLink: https://doi.org/10.1787/888934163648

EDUCATION AT A GLANCE 2020 © OECD 2020

210  B4. WHO IS EXPECTED TO ENTER TERTIARY EDUCATION?
Table B4.1. Entry rate and profile of first-time entrants into tertiary education (2018)

Partners

OECD

Share
of female
first-time
entrants

Share
of first-time
entrants
Average age
below
of first-time
the age of 25
entrants

Share of first-time entrants
by level of education

Share of
international
first-time
entrants

Short-cycle
tertiary

Bachelor’s
or
equivalent

First-time tertiary entry rate
for students under 25

Master’s Excluding international students
or
equivalent
Total
Men
Women

Total

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

Countries
Australia
Austria
Belgium1
Canada
Chile
Colombia
Costa Rica
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Lithuania
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United Kingdom
United States

m
53
56
m
54
51
m
58
55
56
53
m
52
56
55
60
m
57
55
51
m
m
52
54
51
52
57
54
54
54
57
53
53
58
50
51
56
54

m
80
96
m
82
74
m
87
74
82
77
m
84
88
88
74
m
71
94
99
m
m
88
86
88
94
75
85
87
92
85
93
81
66
67
73
81
94

m
22
19
m
22
22
m
22
25
23
23
m
22
21
21
24
m
24
20
18
m
m
21
23
21
20
23
22
22
20
22
20
22
25
25
23
22
20

m
23
9
m
1
0
m
13
8
11
10
m
13
5
22
12
m
m
6
m
m
m
6
21
0
15
31
2
4
6
11
5
7
13
17
2
11
4

m
44
1
m
44
36
m
1
25
a
a
m
0
a
9
8
m
27
2
35
m
m
a
29
8
2
23
7
m
9
2
19
38
14
4
46
21
47

m
40
99
m
55
64
m
91
75
93
94
m
81
100
72
90
m
73
87
63
m
m
93
71
92
98
77
81
m
77
91
76
50
58
86
52
78
53

m
16
a
m
2
a
m
8
0
7
6
m
19
a
18
2
m
a
11
2
m
m
7
a
a
a
a
11
m
14
7
5
12
28
11
2
1
a

m
48
62
m
71
32
m
49
53
42
43
m
45
40
32
43
m
m
46
m
m
m
63
15
45
53
48
57
67
56
41
66
65
41
40
67
54
44

m
41
55
m
65
30
m
40
46
36
40
m
40
33
28
34
m
m
39
m
m
m
58
13
44
50
39
49
59
50
34
59
59
33
36
63
48
40

m
55
71
m
77
34
m
58
60
49
47
m
50
47
37
53
m
m
53
m
m
m
69
17
46
56
58
66
76
62
48
73
71
50
45
71
61
48

m
58
68
m
71
32
m
57
58
47
47
m
52
42
40
47
m
45
48
73
m
m
67
19
45
62
66
57
70
60
45
70
67
46
48
69
63
46

OECD average
EU23 average

54
54

83
85

22
22

10
10

17
13

77
79

6
8

49
48

44
43

55
54

54
53

Argentina
Brazil
China
India
Indonesia
Russian Federation
Saudi Arabia
South Africa

m
m
55
47
56
55
45
m

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

m
m
60
a
15
52
34
m

m
m
40
100
85
38
65
m

m
m
a
0
a
10
1
m

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

G20 average

52

m

m

m

28

68

5

m

m

m

m

Note: See Definitions and Methodology sections for more information. Data and more breakdowns available at http://stats.oecd.org/, Education at a Glance Database.
1. Short-cycle tertiary: data refer to the Flemish Community of Belgium only.
Source: OECD/UIS/Eurostat (2020). 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/10.1787/888934163667

EDUCATION AT A GLANCE 2020 © OECD 2020

B4. WHO IS EXPECTED TO ENTER TERTIARY EDUCATION?  211

Short-cycle tertiary entry rate
for students under 25

Average age
of first-time entrants

Share of international
first-time entrants

Generic programmes
and qualifications

Education

Health and welfare

Social sciences,
journalism and
information

Business,
administration and law

Arts and humanities

Services

Total

Men

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

(13)

(14)

(15)

(16)

(17)

Countries
Australia
Austria
Belgium1
Canada
Chile
Colombia
Costa Rica
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan 2
Korea
Latvia
Lithuania
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United Kingdom
United States

m
53
86
m
55
47
57
65
48
a
a
50
63
a
61
48
45
49
28
61
51
62
a
53
40
44
58
19
80
37
70
39
48
49
58
53
56
55

m
82
99
m
68
67
m
78
45
a
a
94
42
a
81
27
46
70
80
100
91
42
a
90
93
66
51
58
21
88
72
74
74
35
32
64
51
75

m
21
19
m
24
23
22
23
31
a
a
20
26
a
23
31
30
23
23
18
21
29
a
22
20
25
29
26
37
21
25
24
24
29
31
25
28
23

m
2
7
m
1
0
m
5
10
a
a
m
0
a
1
39
8
m
7
m
1
1
a
10
0
2
18
1
0
3
1
3
1
0
0
1
3
3

m
0
0
m
0
0
0
0
0
a
a
0
0
a
0
0
6
0
0
0d
0
0
a
0
0
0
1
0
0
0
0
0
0
0
0
0
4
m

m
11
0
m
12
0
14
0
4
a
a
0
0
a
0
8
1
35
0
11 d
5
6
a
0
0
3
4
0
0
0
10
0
8
0
2
7
4
m

m
4
100
m
21
4
1
0
4
a
a
12
0
a
1
0
12
0
0
24 d
23
28
a
19
6
9
10
0
100
9
28
2
17
4
20
16
22
m

m
1
0
m
0
1
2
0
3
a
a
2
0
a
0
0
1
0
0
4d
0
0
a
4
0
5
5
0
0
0
0
0
1
1
4
1
4
m

m
24
0
m
22
47
30
0
55
a
a
39
0
a
61
4
25
2
13
12 d
10
33
a
48
26
48
25
1
0
20
12
17
19
30
50
38
39
m

m
4
0
m
2
5
6
100
8
a
a
9
12
a
3
44
7
0
2
11 d
13
1
a
8
2
2
18
22
0
10
10
6
9
6
6
11
6
m

m
19
0
m
12
7
6
0
10
a
a
6
52
a
17
33
26
0
17
21 d
19
12
a
0
11
14
12
12
0
13
23
27
16
9
0
13
1
m

m
3
0
m
2
2
4
0
1
a
a
3
9
a
5
0
0
0
14
1d
1
1
a
0
3
2
4
0
0
6
1
3
1
2
0
3
2
m

m
34
0
m
27
33
37
0
15
a
a
29
26
a
13
11
22
63
54
16 d
28
19
a
21
52
17
20
65
0
42
16
45
29
48
17
10
18
m

m
29
1
m
30
11
m
0
10
a
a
m
0
a
3
1
4
m
1
m
28
14
a
5
4
2
12
3
0
5
1
18
27
3
1
28
8
29

m
26
0
m
29
11
m
0
11
a
a
m
0
a
3
1
4
m
1
m
27
12
a
5
5
2
9
5
0
7
1
21
28
4
1
25
8
27

m
33
1
m
32
11
m
1
9
a
a
m
0
a
4
2
3
m
0
m
30
17
a
5
3
1
14
2
0
4
1
14
25
3
1
30
8
31

m
30
1
m
31
11
m
0
12
a
a
26
0
a
3
2
4
13
1
21
28
14
a
6
4
2
15
3
0
6
1
19
27
3
1
28
8
29

OECD average
EU23 average

53
55

66
66

25
25

5
4

0
1

5
3

16
19

1
1

24
25

11
11

13
14

2
3

27
24

10
7

10
7

10
7

11
9

Argentina3
Brazil
China
India
Indonesia
Russian Federation
Saudi Arabia
South Africa

61
m
53
a
59
51
28
m

m
m
m
a
m
m
m
m

m
m
m
a
m
m
m
m

m
m
m
a
m
1
m
m

m
m
m
a
m
0
m
m

m
m
m
a
m
7
m
m

m
m
m
a
m
14
m
m

m
m
m
a
m
1
m
m

m
m
m
a
m
21
m
m

m
m
m
a
m
4
m
m

m
m
m
a
m
16
m
m

m
m
m
a
m
1
m
m

m
m
m
a
m
36
m
m

m
m
m
a
m
m
m
m

m
m
m
a
m
m
m
m

m
m
m
a
m
m
m
m

m
m
m
a
m
m
m
m

G20 average

50

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

Agriculture, forestry,
fisheries and
veterinary
Science, technology,
engineering and
mathematics

Share of first-time entrants
below the age of 25

Share of new entrants by field

Share of female
first-time entrants
Partners

OECD

Table B4.2. Entry rate and profile of new entrants into short-cycle tertiary level (2018)
Excluding
international students

Women Total

Note: See Definitions and Methodology sections for more information. Data and more breakdowns available at http://stats.oecd.org/, Education at a Glance Database.
1. Short-cycle tertiary: data refer to the Flemish Community of Belgium only.
2. All fields of study include the field Information and Communication Technologies (ICTs).
3. Year of reference 2017.
Source: OECD/UIS/Eurostat (2020). 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/10.1787/888934163686

EDUCATION AT A GLANCE 2020 © OECD 2020

212  B4. WHO IS EXPECTED TO ENTER TERTIARY EDUCATION?
Table B4.3. Entry rate and profile of new entrants into bachelor's, master's and doctoral levels (2018)
Master’s or equivalent

(4)

(5)

Total
(6)

Countries
Australia
Austria
Belgium1
Canada
Chile
Colombia
Costa Rica
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungar y
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Lithuania
Luxembourg
Mexico
Netherlands
New Zealand
Nor way
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United Kingdom
United States

80
83
96
m
82
77
m
86
76
81
75
90
83
90
88
76
89
69
94
99
98
75
87
84
87
95
74
80
87
90
85
92
91
68
69
80
87
m

21
22
9
m
0
0
m
11
8
10
6
m
7
3
9
9
5
4
6
m
2
11
5
25
0
15
31
4
m
7
9
5
2
5
10
3
16
m

60
29
66
m
50
22
m
46
47
39
42
m
38
65
26
42
61
34
39
m
56
54
59
10
41
52
41
49
m
44
38
62
43
30
40
38
50
m

50
24
59
m
47
20
m
38
39
34
39
m
36
61
24
33
58
24
35
m
53
49
56
9
39
49
34
40
m
37
33
54
37
22
36
37
43
m

71
34
74
m
53
24
m
54
56
45
46
m
41
69
29
51
64
45
45
m
59
60
63
12
42
55
50
58
m
52
44
71
50
38
44
39
56
m

OECD average
EU23 average

84
84

9
10

44
43

38
38

Argentina
Brazil
China
India
Indonesia
Russian Federation
Saudi Arabia
South Africa

m
m
m
m
m
84
m
m

m
m
m
m
m
7
m
m

m
m
m
m
m
46
m
m

G20 average

m

m

m

Share of internation al
new entrants

(3)

(7)

(8)

Total
(9)

Men
(10)

(11)

Total
(12)

77
36
72
m
50
22
m
52
51
43
45
54
41
67
29
45
64
35
41
50
57
61
62
14
41
61
56
49
63
47
41
66
44
32
46
39
60
m

75
80
94
m
48
42
m
94
86
73
49
87
90
50
88
60
57
46
90
91
57
74
80
61
58
92
61
79
86
87
88
89
79
77
81
84
75
64

61
32
17
m
2
1
m
18
23
21
20
m
28
0
24
17
27
6
9
m
12
20
12
78
2
30
38
6
m
12
8
5
21
22
31
5
43
19

8
14
27
m
6
3
m
21
23
16
5
m
20
11
11
14
14
9
22
m
6
18
17
2
3
15
4
26
m
23
27
29
15
20
14
10
11
7

6
12
24
m
4
3
m
17
20
11
4
m
18
8
9
9
12
6
18
m
5
12
12
2
3
13
3
22
m
20
20
20
11
17
13
13
8
5

9
16
29
m
7
4
m
26
26
21
6
m
23
14
13
19
16
12
27
m
7
24
23
3
4
17
5
31
m
27
34
38
18
23
14
7
14
9

49
49

49
47

74
76

21
22

14
16

11
13

m
m
m
m
m
42
m
m

m
m
m
m
m
51
m
m

m
m
m
m
m
46
m
m

m
m
m
m
m
91
m
m

m
m
m
m
m
8
m
m

m
m
m
m
m
25
m
m

m

m

m

m

m

m

Excluding
internation al
students

Doctoral entr y rate
for students under 30

Share of new entrants
below the age of 30

Men

(2)

Master’s entry rate
for students under 30

Share of internation al
new entrants

Total

(1)

Doctoral

Share of new entrants
below the age of 30

Share of internation al
new entrants

Bachelor's entr y rate
for students under 25

Share of new entrants
below the age of 25
Par tners

OECD

Bachelor’s or equivalent

(13)

(14)

Total
(15)

Men
(16)

(17)

(18)

28
20
31
m
6
3
m
27
30
20
7
39
28
11
15
17
23
10
24
8
8
24
20
8
3
22
7
28
32
26
29
30
17
25
19
10
23
9

50
65
67
m
41
17
m
76
69
65
42
76
71
46
64
36
60
37
71
57
41
48
60
73
34
85
51
47
73
37
66
59
45
57
75
53
68
61

42
39
56
m
14
5
m
23
40
35
31
m
15
0
25
41
35
8
18
16
15
14
10
89
9
51
58
29
m
35
10
10
21
43
60
8
43
25

0.8
1.3
0.3
m
0.2
0.0
m
1.9
1.1
0.9
0.7
m
2.7
1.2
0.9
0.4
1.3
0.6
1.0
m
1.2
0.9
0.8
0.1
0.2
0.6
0.5
0.8
m
1.4
1.5
1.9
1.7
0.5
1.5
0.7
1.5
0.5

0.7
1.3
0.4
m
0.2
0.0
m
1.9
1.2
0.6
0.7
m
2.9
1.2
0.9
0.3
1.2
0.5
0.9
m
1.3
0.7
0.7
0.1
0.2
0.6
0.5
0.8
m
1.2
1.4
1.7
1.6
0.5
1.5
0.7
1.5
0.6

0.9
1.2
0.3
m
0.1
0.0
m
1.9
1.0
1.2
0.7
m
2.6
1.2
1.0
0.5
1.3
0.7
1.0
m
1.0
1.1
0.9
0.1
0.2
0.6
0.6
0.8
m
1.5
1.6
2.1
1.8
0.6
1.5
0.7
1.5
0.4

1.6
2.0
0.6
m
0.2
0.0
m
2.4
2.1
1.3
1.0
1.8
2.7
1.2
1.2
1.1
2.1
0.7
1.1
0.7
1.5
1.0
0.9
1.1
0.2
1.2
1.3
1.3
1.2
1.8
1.6
2.2
2.0
1.2
3.7
0.7
2.8
0.7

17
19

19
21

57
60

29
31

1.0
1.1

0.9
1.1

1.0
1.1

1.4
1.6

m
m
m
m
m
22
m
m

m
m
m
m
m
27
m
m

m
m
m
m
m
25
m
m

m
m
m
m
m
m
m
m

m
m
m
m
m
9
m
m

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

m

m

m

m

m

m

m

m

m

Excluding
internation al
students

Excluding
internation al
students

Total

Note: 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. Doctorates: data refers to the French Community of Belgium only.
Source: OECD/UIS/Eurostat (2020). 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/10.1787/888934163705

EDUCATION AT A GLANCE 2020 © OECD 2020

214  B5. WHO IS EXPECTED TO GRADUATE FROM TERTIARY EDUCATION?

Indicator B5. Who is expected to graduate
from tertiary education?
Highlights


Bachelor’s or equivalent degrees remain the most common tertiary qualification among first-time tertiary
graduates in OECD countries. In 2018, on average across OECD countries, the majority of first-time tertiary
graduates (78%) earned a bachelor’s degree, 18% a short-cycle tertiary diploma and 10% a master’s degree.



On average across OECD countries, at short-cycle tertiary level, 24% of students graduate from the fields of
business, administration and law, whereas only 2% earn a diploma in natural sciences, mathematics and
statistics.



Based on current patterns, it is estimated that 38% of young adults across OECD countries will graduate from
tertiary education for the first time before the age of 30 (excluding international students).

Figure B5.1. Distribution of short-cycle tertiary, bachelor's, master's and doctoral graduates on average
across partners and OECD countries, by field of education (2018)
Short-cycle tertiary
Bachelor’s or equivalent
Master’s or equivalent
Doctoral or equivalent

%
30
25
20
15
10
5
0

Business,
administration
and law

Health and
welfare

Engineering,
manufacturing
and construction

Arts and
humanities

Services

Education

Information and Social sciences,
communication journalism and
technologies
information

Natural
sciences,
mathematics
and statistics

Note: Agriculture, forestry, fisheries and veterinary are not included in the chart but data are available in the education database.
Fields of study are ranked in descending order of their share of short-cycle tertiary graduates (ISCED 5).
Source: OECD/UIS/Eurostat (2020), Education at a Glance (database), http://stats.oecd.org/. See Source section for more information and Annex 3 for notes
(https://doi.org/10.1787/69096873-en).
Statlink2https://doi.org/10.1787/888934163876

EDUCATION AT A GLANCE 2020 © OECD 2020

B5. WHO IS EXPECTED TO GRADUATE FROM TERTIARY EDUCATION?  215

Context
Tertiary graduation rates illustrate a country’s capacity to provide future workers with advanced and specialised knowledge
and skills. The incentives to earn a tertiary degree, including higher salaries and better employment prospects, remain
strong across OECD countries (see Indicators A1, A3, A4 and A5 for further reading on these themes). Tertiary education
varies in structure and scope across countries, and graduation rates seem to be influenced by educational factors such
as the flexibility of programmes, the supply of spaces available by education level and fields of study, as well as other
factors during the educational year, that make students likely to complete their programme or not.
In recent decades, access to tertiary education has expanded remarkably, involving new types of institutions that offer
more choice and new modes of delivery (OECD, 2016[1]). In parallel, the student population is becoming increasingly
diverse in the study pathways they choose. Students are also becoming more likely to seek a tertiary degree outside their
country of origin. Understanding current graduation patterns helps to understand student progression throughout higher
education and anticipate the flow of new tertiary-educated workers into the labour force.
Policy makers are exploring ways to help ease the transition from tertiary education into the labour market (OECD,
2015[2]).To this end, short-cycle tertiary programmes, typically vocationally oriented, are central to preparing young people
for work, developing adults’ skills and responding to labour-market needs.

Other findings


Advanced tertiary degrees attract more international students (see Definitions section) than bachelor’s degrees.
Some 26% of students in OECD countries who graduated for the first time from a doctoral or equivalent
programme in 2018 were international students, compared to 19% of those who were awarded a master’s degree
and 8% of those who earned a bachelor’s degree for the first time.



Women’s participation in higher education has been increasing in recent years, and their share among first-time
tertiary graduates (58%) remains higher than their share among first-time tertiary entrants (54%). This is in line
with previous findings suggesting that women are more likely to complete their degree than men (OECD, 2019[3]).



Average age at graduation reflects a combination of average age at entry and the time taken to complete tertiary
educational programmes. Across OECD countries with data, people graduate for the first time from a tertiary level
programme on average at the age of 25.

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 2018 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 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. Thirty is used as the upper age limit
for completing short-cycle tertiary and bachelor’s degree, because across OECD countries, more than 95% of graduates
from upper secondary general programmes in 2018 were under 25 (see Education at a Glance Database). People who
graduate from upper secondary level at 25 or older are usually enrolled in second-chance programmes. Similarly, 35 is
used as the upper age limit for completing master’s and doctorate degrees.
In this edition of Education at a Glance, the focus is predominately on first-time graduates below the typical age (30 for
short-cycle tertiary and bachelor’s and 35 for master’s and doctoral levels). The concept of graduates (i.e. all graduates,
not only first-time graduates) is used when measuring graduation rate at each tertiary level and graduates by field of study
(see Definitions section).

EDUCATION AT A GLANCE 2020 © OECD 2020

216  B5. WHO IS EXPECTED TO GRADUATE FROM TERTIARY EDUCATION?

Analysis
Graduation patterns at tertiary level
Over the past two decades, tertiary education in OECD countries has changed significantly. The student body is more
international, more women than men are graduating and choices of fields of study have evolved. These changes might reflect
concerns about competitiveness in the global economy and the labour market, but also the interests and priorities of a growing
student population.
The first-time graduation rate from tertiary education among people under the age of 30 is an indicator of how many young
people are expected to enter the labour force for the first time with a tertiary qualification. Based on current patterns of
graduation, it is estimated that 41% of young adults will graduate from tertiary education for the first time in their life before
the age of 30 on average across OECD countries. The proportion ranges from 10% in Luxembourg (although this percentage
is negatively biased by the high percentage of secondary graduates who pursue tertiary studies abroad) to 71% in Japan
(Table B5.1).
International students (see Definitions section at the end of this indicator) can have a marked impact on graduation rates by
inflating the estimate of graduate students compared to the national population. In a country with a high proportion of
international graduates, such as Australia where they make up 46% of all first-time graduates, the difference can be significant.
Australia’s first-time tertiary graduation rate drops from 70% to 37% when international students are excluded ( Table B5.1).

Age distribution of first-time tertiary graduates
For some years now, many OECD countries have been concerned about the length of time tertiary students take to complete
their studies. They have developed policies to encourage students to graduate more quickly, so as to get more workers into
the labour market at an earlier age.
Across OECD countries, in 2018 86% of first-time tertiary graduates graduated before they turned 30, and the average age
of graduation was 25. The variation among countries is large, however, ranging from 23 in the United Kingdom, to 28 in Latvia,
Sweden and Switzerland (Table B5.1). The average age at which most students graduate reflects a combination of their
average age at entry and the length of tertiary programmes. Entrance to tertiary education can be delayed by the structure of
upper secondary education systems, processes for entry and admission into tertiary education, conscription requirements, or
diverse pathways to transition from study to work. Programme duration depends on the structure of the educational
programme and on the intensity of study, i.e. full time or part time.
In Iceland, Sweden and Switzerland, students graduate relatively later but the average age of entry is also two to three years
older than the OECD average (24-25 compared to the average of 22). These older ages for both graduation and entry in
these countries reflect students’ varied trajectories before entering higher education, the flexibility of their education systems
to accommodate transitions between educational programmes or between work and study, and adults’ lifelong learning.
Greater enrolment in part-time studies, as observed in Sweden, also tends to delay the average graduation age (see data
available on OECD.Stat at http://stats.oecd.org/).
Some education systems accommodate a wider range of ages than others. This suggests that these education systems are
more flexible about access to programmes and their duration, particularly for students outside typical student age. It may also
reflect the different policies and attitudes towards adult and lifelong learning. In Latvia, Sweden and Switzerland, the average
age of first-time graduates is more than two years higher than the OECD average.

Gender distribution of first-time tertiary graduates
Recognising the impact that education has on participation in the labour market, occupational mobility and quality of life, policy
makers and educators have emphasised the importance of reducing differences between men and women in education
opportunities and outcomes.
In 2018, more women than men graduated from tertiary education: on average 58% of first-time graduates from tertiary
education in OECD countries were women, ranging from 50% in Switzerland to 64% in Latvia ( Table B5.1). Furthermore,
the share of female first-time graduates was higher than the share of female first-time new entrants into tertiary education
(54%) in all OECD and partner countries with available data. This confirms previous findings that women are more likely to
complete tertiary education than their male counterparts (OECD, 2019[3]). On average across OECD countries, excluding
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B5. WHO IS EXPECTED TO GRADUATE FROM TERTIARY EDUCATION?  217
international students, 44% of women are expected to obtain a tertiary degree before the age of 30, compared to 29% of men.
In all countries with available data, first-time tertiary graduation rates are lower for men than for women, but the size of the
gender gap varies significantly across countries, ranging from 2 percentage points in Luxembourg to 26 percentage points in
Lithuania (Table B5.1).
Although the majority of tertiary graduates in 2018 were women, men still have better labour-market outcomes. Earnings for
tertiary-educated men are higher, on average, than those for tertiary-educated women, and tertiary-educated men tend to
have higher employment rates than women with the same level of education (see Indicators A3 and A4).

Fields studied by tertiary graduates
The distribution of graduates by field of study is related to factors such as the relative popularity of these fields among students,
the number of study spaces offered in universities and equivalent institutions, and the degree structure of the various
disciplines in each country.
Currently, in most OECD countries, the largest share of graduates across all tertiary education programmes complete degrees
in business, administration and law, with a few exceptions (Table B5.2). In 2018, on average, 25% of tertiary students
graduating in that year obtained a degree in this broad field across OECD countries, although this ranges from 15% in Korea
to 46% in Colombia. In Korea, the most popular field among tertiary graduates is engineering, manufacturing and construction;
in Belgium, Finland, Norway and Sweden it is health and welfare; in India it is social sciences, information and journalism;
and in Indonesia it is education. Some of these differences can be explained by the structure of educational systems and the
type of institutions offering qualifications in each field of study across countries. For example, degrees in fields of study such
as nursing (included under health and welfare) are more likely to be offered as a tertiary programme in countries that have
integrated most of the post-secondary vocational education into their tertiary education system.
In most countries, the broad field of natural sciences, mathematics and statistics is less popular than other fields of study. In
more than half of the OECD and partner countries with available data, the combined share of students graduating from natural
sciences, mathematics and statistics; engineering, manufacturing and construction; and information and communication
technologies is still lower than the share of students graduating from business, administration and law.

Figure B5.2. First-time short-cycle tertiary graduation rate, for students under 30 and excluding
international students (2010 and 2018)
2018
2010

%
30
25
20
15
10
5

Poland

Germany

Czech Republic 1

Italy

Netherlands

Iceland1

Slovak Republic 1

Hungary1

Luxembourg1

Norway1

Portugal

Sweden

Slovenia1

United Kingdom

Denmark

Latvia

Australia

New Zealand

Turkey

Chile

Spain

Japan

Austria

0

1. Year of reference 2013 instead of 2010.
Countries are ranked in descending order of the first-time short-cycle tertiary graduation rates for students under 30 in 2018.
Source: OECD/UIS/Eurostat (2020), Education at a Glance Database, http://stats.oecd.org/. See Source section for more information and Annex 3 for notes
(https://doi.org/10.1787/69096873-en).
Statlink2https://doi.org/10.1787/888934163895

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218  B5. WHO IS EXPECTED TO GRADUATE FROM TERTIARY EDUCATION?
Profile of first-time graduates from short-cycle tertiary levels
In 2018, the second most common tertiary qualification among first-time tertiary graduates that year remained a short-cycle
tertiary degree. On average across OECD countries 18% of those graduating earned a short-cycle tertiary qualification
ranging from 1% or less in the Czech Republic, Germany, Italy and Switzerland to 49% in Austria, where short-cycle tertiary
accounted for the largest share of first-time graduates.
Although the large majority of first-time tertiary graduates are awarded a bachelor’s degree, some OECD countries are also
encouraging participation in short-cycle tertiary programmes to improve employability and smooth transitions into work.
Generally professionally oriented, these programmes develop occupation-specific skills and most often prepare students for
direct entry into the labour market. The first-time graduation rate for students under 30 from these programmes has increased
by more than 4 percentage points in Australia and Turkey between 2010 and 2018, excluding international graduates. In
contrast, the rate has remained stable over this period in Austria, the Czech Republic, Iceland, the Netherlands and
the Slovak Republic, increasing by less than 1 percentage point over this period (Figure B5.2). In some cases, this limited
growth over time could suggest that short-cycle tertiary programmes are not an attractive option in many countries. To remedy
this situation, many countries are trying to develop future education opportunities for those entering this level, by promoting
professional or vocational programmes at bachelor’s and master’s levels.
Based on patterns of graduation prevailing in 2018 and excluding international students, on average across OECD countries,
8% are expected to graduate from a short-cycle tertiary programme before the age of 30 (Table B5.3).

Analysis by age
On average across OECD countries in 2018, 75% of first-time short-cycle tertiary graduates graduated before the age of 30,
and the median age at graduation was 25, ranging from 19 in Austria to 38 in Poland (Figure B5.3). The variation across
countries is large and older first-time graduation ages could be explained in some cases by short-cycle tertiary programmes
specifically designed for older students, as well as students taking longer to graduate.

Figure B5.3. Age distribution of first-time graduates at short-cycle tertiary level (2018)
20th percentile
Median
80th percentile

Age
55
50
45
40
35
30
25
20
15
10

France

Austria

Italy

Turkey

Portugal

Spain

Korea

Slovak Republic

Mexico

Hungary

Czech Republic

Colombia

United Kingdom

Canada

Luxembourg

Slovenia

Denmark

EU23 average

Netherlands

New Zealand

OECD average

Chile

Belgium

Norway

Brazil

Germany

Latvia

Australia

Sweden

Ireland

Iceland

Poland

0

Switzerland

5

Countries are ranked in descending order of the median graduation age of first-time graduates at short-cycle tertiary level.
Source: OECD/UIS/Eurostat (2020), Education at a Glance Database, http://stats.oecd.org/. See Source section for more information and Annex 3 for notes
(https://doi.org/10.1787/69096873-en).
Statlink2https://doi.org/10.1787/888934163914

EDUCATION AT A GLANCE 2020 © OECD 2020

B5. WHO IS EXPECTED TO GRADUATE FROM TERTIARY EDUCATION?  219
The age distribution of first-time graduates at short-cycle tertiary level provides insights into the diversity of graduates’ ages,
compared to the median value. In some countries, the age distribution is closely centred on the median, implying relatively
small age differences at this level. This is the case in Austria, France, Korea, Luxembourg, Mexico and Portugal, where no
more than 4 years separate the 80th and 20th percentile age groups. In other countries, the age distribution is much wider.
For example in Ireland, New Zealand, Poland and Switzerland, first-time short-cycle tertiary graduates in the 80th percentile
are at least 20 years older than those in the 20th percentile. However on average across 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
B5.3).

Analysis by mobility status
On average across OECD countries, 5% of first-time graduates from short-cycle tertiary programmes were international
students in 2018, the lowest share across all tertiary levels of education. The more limited share of international students in
short-cycle tertiary programmes could be due to the relative low prevalence and limited attractiveness of short-cycle tertiary
programmes, compared to the other tertiary levels. However, this pattern does not hold for every country: in Denmark, Italy,
Japan and Luxembourg, the share of international students in short-cycle tertiary level is substantially higher than in bachelor’s
programmes, by more than 2 percentage points. However, there are large disparities across countries. The share of
international students in short-cycle tertiary programmes varies from close to zero in Austria, Chile, Germany, Iceland,
the Netherlands, Poland, Sweden and Turkey to 29% in New Zealand (Table B5.3).

Analysis by field of study
On average across OECD countries, at short-cycle tertiary level, 24% of students graduate from the broad field of business,
administration and law compared to only 2% in natural sciences, mathematics and statistics (Figure B5.1). However, some
exceptions exist: Austria, Italy, Mexico, Norway, Portugal and Slovenia have the largest share of students graduating from
engineering, manufacturing and construction at short-cycle tertiary level. In Chile, Japan, Korea, Latvia, Luxembourg,
Switzerland and the United Kingdom the largest share of short-cycle tertiary graduates studied health and welfare; in Belgium
and Poland, 100% studied this broad field. The largest share of short-cycle tertiary students in Germany and Iceland graduate
from the field of services whereas the dominant field of study in the Czech Republic (with 100% of graduates),
the Slovak Republic and the United States is arts and humanities (see data available on OECD.Stat at http://stats.oecd.org/).
However, these results need to be analysed with caution as short-cycle tertiary represents less than 3% of the share of firsttime tertiary graduates in the Czech Republic, Germany, Italy, the Netherlands, Sweden and Switzerland. These differences
may result from the structure of the tertiary system, the promotion of short-cycle programmes, as well as the educational
provision of short-cycle training in certain fields of study which require more vocational skills than others.

Profile of first-time graduates from bachelor’s, master’s and doctoral levels
In 2018, the large majority of first-time tertiary graduates were awarded a bachelor’s or equivalent degree. On average across
OECD countries, 78% of first-time tertiary graduates earned a bachelor’s degree, 10% earned a master’s or equivalent degree
and 18% earned a short-cycle tertiary diploma (Table B5.1).
More young people are expected to graduate from a bachelor’s programme than from any other level of tertiary education.
Based on graduation patterns prevailing in 2018, on average across OECD countries, 33% of young people are expected to
graduate with a bachelor’s degree before they turn 30, 16% are expected to earn a master’s degree and 1% are expected to
graduate from a doctoral or equivalent programme (including international students) (Table B5.3).

Analysis by age
On average across OECD countries, 86% of first-time graduates at bachelor’s level are below the age of 30, this varies from
76% in Israel and Sweden to almost 100% in Japan. On average across OECD countries, 84% of first-time graduates from
master’s programmes and 61% from doctoral programmes are below the age of 35. Master’s programmes may lead directly
to a labour market-relevant qualification but they are also a prerequisite to accessing an advanced research qualification
(i.e. a doctorate) in many countries. In Luxembourg, the share of first-time graduates below the age of 35 is slightly higher
among doctoral graduates than among master’s (Table B5.3).

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220  B5. WHO IS EXPECTED TO GRADUATE FROM TERTIARY EDUCATION?
Analysis by mobility status
The share of first-time international graduates varies significantly across countries. The proportions are particularly high in
Australia, Luxembourg and New Zealand, which have at least 20% of international graduates in bachelor’s programmes, at
least 30% in master’s programmes, and at least 40% in doctoral programmes. In contrast, the smallest shares of international
graduates at doctoral level are found in Chile, Greece and Lithuania where they account for no more than 5% of first-time
graduates (Table B5.3).
In spite of these differences, there is a common pattern across countries with available data: advanced tertiary degrees attract
more international students than bachelor’s degrees. Some 26% of students in OECD countries who graduated for the first
time from a doctoral programme in 2018 were international students, compared to 19% of students who were awarded a
master’s degree, and 8% of students who earned a bachelor’s degree for the first time (Table B5.3). The high share of
international students in advanced tertiary degrees may be due, in part, to the emergence of knowledge-based economies
(economies directly based on the production, distribution and use of knowledge and information). This phenomenon has
contributed to the internationalisation of research. Consequently, many students are seeking opportunities to study abroad at
the master’s or doctoral level. From the point of view of host countries, attracting international students can be beneficial for
several reasons, such as the fees and other living expenses the students pay, and the social and business networks that they
help to build with their home countries.
In addition, international students, particularly at the master’s or doctoral or equivalent level, can contribute to research and
development (R&D) in the host country, initially as students and later on potentially as researchers or highly qualified
professionals. Doctoral students, in particular, form an integral part of the research staff of a country (OECD, 2016[4]).

Analysis by field of study
At tertiary level, only a small share of students graduate from the broad field of natural sciences, mathematics and statistics,
on average across OECD countries. However, there are large variations across tertiary education levels. Graduation rates
from this broad field of study increase with educational level: on average across partners and OECD countries, 6% of
bachelor’s and master’s graduates in 2018 earned a degree in natural sciences, mathematics and statistics, while this rose
to 22% of graduates at doctoral level (Figure B5.1).
The popularity of natural sciences, mathematics and statistics in doctoral programmes may be the result of policies that
encourage academic research in these fields. Recent OECD work has highlighted that while innovation draws on a wide set
of skills, excellence in scientific research is the basis of science-based innovation, and research competence is essential for
building co-operation among the scientific community, business and society. Thus, developing scientific research skills
through doctoral training has become an important aim of education policy in many countries (OECD, 2014[5]).
The broad fields of business, administration and law, and of education are among those most commonly pursued at master’s
level. On average across partners and OECD countries, business, administration and law accounted for 28% of master’s
graduates compared with 24% of bachelor’s graduates and 9% of doctoral graduates. Similarly, 12% of students graduating
at master’s level studied in the field of education, compared to 6% graduating from a bachelor’s programme and 7% earning
a doctorate (Figure B5.1). Tertiary students are more likely to graduate from the fields of social sciences, journalism and
information at bachelor’s level (12%) than from any other long-cycle tertiary level (10% at master’s and doctoral levels), on
average across partners and OECD countries (Figure B5.1).

Definitions
First-time graduates refer to students who have graduated for the first time at a given level of education during the reference
period. Therefore, if a student has graduated multiple times over the years, he or she is counted as a graduate each year, but
as a first-time graduate only once per level of education.
First-time tertiary graduates refer to students who graduate for the first time with a tertiary degree, regardless of the
education programme in which they are enrolled. This definition is applied in Tables B5.1 and B5.3.
International students are students who left their country of origin and moved to another country for the purpose of study.
In the majority of countries, international students are considered first-time graduates, regardless of their previous education
in other countries. In the calculations described here, when countries could not report the number of international students,
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B5. WHO IS EXPECTED TO GRADUATE FROM TERTIARY EDUCATION?  221
foreign students have been used as an approximation. Foreign students are students who do not have the citizenship of the
country in which they studied (for more details, please refer to Annex 3, www.oecd.org/education/education-at-a-glance19991487.htm).
Net graduation rates represent the estimated percentage of an age group who will complete a given level of education,
based on current patterns of graduation.
Typical age is the age at the beginning of the last school/academic year of the corresponding educational level and
programme when the degree is obtained.

Methodology
Unless otherwise indicated, graduation rates are calculated as net graduation rates (i.e.as the sum of age-specific graduation
rates) up to an age threshold. The net graduation rate for a single age is obtained by dividing the number of first-time graduates
of that age for each type of tertiary education by the total population of the corresponding age. The sum of net graduation
rates is calculated by adding the rates for each year of age until the age threshold. The result represents the expected
probability of graduating for the first time from tertiary education before the age threshold if current patterns are maintained.
The age threshold refers to the upper limit for completing a tertiary degree. Age 30 is used as the upper limit for completing
short-cycle tertiary, bachelor’s degrees and first-time tertiary education overall. At the master’s and doctoral levels, 35 is
considered to be the upper age limit for graduation.
Gross graduation rates are used when data by age are missing and where the average age of graduation is well below the
age threshold considered for the calculation of this indicator. In this case, the number of graduates of which the age is unknown
is divided by the population at the typical graduation age (see Annex 1).
The average age of students is calculated from 1 January for countries where the academic year starts in the second semester
of the calendar year and 1 July for countries where the academic year starts in the first semester of the calendar year. As a
consequence, the average age of new entrants may be overestimated by up to 6 months while that of first-time graduates
may be underestimated by the same.
Graduation rates are sensitive to changes in the education system, such as the introduction of new programmes or the number
of international students. Rates could at times be very high, during periods when there are unexpectedly high numbers of
graduates. This indicator also reports the share of first-time graduates below the age threshold, alongside the graduation rate,
to provide contextual information on the relevance of the age threshold for each country.
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 graduate from tertiary programmes. When international
students are included in the calculation, the percentage of expected first-time graduates from tertiary programmes can change
significantly.
For more information please see the OECD Handbook for Internationally Comparative Education Statistics (OECD, 2018[6])
and Annex 3 for country-specific notes (https://doi.org/10.1787/69096873-en).

Source
Data refer to the academic year 2017/18 and are based on the UNESCO-UIS/OECD/EUROSTAT data collection on education
statistics administered by the OECD in 2019 (for details, see Annex 3 at https://doi.org/10.1787/69096873-en).

References
OECD (2019), Education at a Glance 2019: OECD Indicators, OECD Publishing, Paris,
https://dx.doi.org/10.1787/f8d7880d-en.

EDUCATION AT A GLANCE 2020 © OECD 2020

[3]

222  B5. WHO IS EXPECTED TO GRADUATE FROM TERTIARY EDUCATION?
OECD (2018), OECD Handbook for Internationally Comparative Education Statistics 2018: Concepts, Standards,
Definitions and Classificatons, OECD Publishing, Paris, https://doi.org/10.1787/9789264304444-en (accessed
on 16 April 2020).

[6]

OECD (2016), OECD Science, Technology and Innovation Outlook 2016, OECD Publishing, Paris,
https://doi.org/10.1787/sti_in_outlook-2016-en.

[1]

OECD (2016), Trends Shaping Education 2016, OECD Publishing, Paris, http://dx.doi.org/10.1787/trends_edu2016-en.

[4]

OECD (2015), Education Policy Outlook 2015: Making Reforms Happen, OECD Publishing, Paris,
http://dx.doi.org/10.1787/9789264225442-en.

[2]

OECD (2014), OECD Science, Technology and Industry Outlook 2014, OECD Publishing, Paris,
http://dx.doi.org/10.1787/sti_outlook-2014-en.

[5]

Indicator B5 Tables
Table B5.1. Graduation rate and profile of first-time tertiary graduates (2018)
Table B5.2. Distribution of tertiary graduates by field of study (2018)
Table B5.3. Graduation rate and profile of first-time tertiary graduates at short-cycle tertiary, bachelor's, master's and doctoral
or equivalent levels (2018)
Cut-off date for the data: 19 July 2020. Any updates on data can be found on line at http://dx.doi.org/10.1787/eag-dataen. More breakdowns can also be found at http://stats.oecd.org/, Education at a Glance Database.
Statlink: https://doi.org/10.1787/888934163800

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B5. WHO IS EXPECTED TO GRADUATE FROM TERTIARY EDUCATION?  223

Table B5.1. Graduation rate and profile of first-time tertiary graduates (2018)

Par tners

OECD

Share of first-time gr aduates
by level of education
Share of
Share of
first-time
Share of
female
graduates Average age internation al
Short
Bachelor’s
Master’s
first-time
below
of first-time first-time
tertiary
or
or
graduates the age of 30 gradu ates graduates
(2-3 years) equivalent equivalent

First-time tertiar y graduation rate
for students under 30
Excluding internation al
students
Total

Men

Women

Total

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

Countries
Australia
Austria
Belgium
Canada1
Chile
Colombia
Costa Rica
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungar y
Iceland
Ireland
Israel
Italy
Japan 2
Korea
Latvia
Lithuania
Luxembourg
Mexico
Netherlands
New Zealand
Nor way
Poland
Por tugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United Kingdom
United States

56
55
61
m
57
m
m
63
56
63
57
m
53
59
59
62
m
m
58
52
m
64
61
58
53
56
57
59
m
58
63
59
55
63
50
53
57
58

84
85
93
m
78
m
m
87
85
82
79
m
87
91
84
79
m
m
91
100
m
73
92
94
90
95
78
85
m
92
86
87
85
78
77
84
89
m

25
24
24
m
27
m
m
26
26
26
27
m
25
25
26
27
m
m
24
m
m
28
24
25
25
24
26
26
m
24
25
25
25
28
28
25
23
m

46
18
14
m
0
m
m
12
8
7
10
m
4
2
7
3
m
m
4
5
m
5
3
23
m
10
30
3
m
2
7
2
7
11
7
1
12
4

8
49
m
m
47
m
m
1
21
a
a
m
0
a
8
3
m
m
1
34
m
29
a
30
8
2
29
7
m
7
4
17
37
2
1
41
21
40

68
32
95
m
51
m
m
89
79
93
91
m
85
100
80
96
m
m
81
63
m
65
93
70
92
98
71
82
m
79
89
77
49
64
99
57
78
60

24
19
5
m
2
m
m
10
a
7
9
m
15
a
12
0
m
a
17
2
m
7
7
a
a
a
a
11
m
14
7
6
14
34
0
2
1
a

37
35
32
m
44
m
m
28
45
30
37
m
32
37
23
34
m
m
34
67
m
37
50
8
m
41
36
43
m
43
30
45
52
25
36
50
41
m

30
29
26
m
37
m
m
20
38
21
31
m
28
29
18
25
m
m
27
m
m
25
38
7
m
35
28
34
m
35
21
34
45
17
33
46
35
m

44
42
39
m
52
m
m
36
52
39
44
m
37
46
28
45
m
m
40
m
m
49
64
9
m
46
45
53
m
52
38
56
59
33
39
55
47
m

70
42
37
m
44
m
m
32
50
32
41
m
33
38
25
35
m
m
35
71
m
39
52
10
28
45
52
44
m
44
31
46
55
28
39
51
48
m

OECD average
EU23 average

58
59

86
87

25
25

9
8

18
16

78
79

10
12

38
36

29
29

44
43

41
38

Argentina
Brazil
China
India
Indonesia
Russian Federation
Saudi Arabia
South Africa 1

m
m
53
53
59
56
53
61

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

G20 average

55

m

m

m

m

m

m

m

m

m

m

1. Year of reference 2017.
2. It is estimated that almost all students graduate from tertiary education before the typical graduation age.
Source: OECD/UIS/Eurostat (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2https://doi.org/10.1787/888934163819

EDUCATION AT A GLANCE 2020 © OECD 2020

224  B5. WHO IS EXPECTED TO GRADUATE FROM TERTIARY EDUCATION?
Table B5.2. Distribution of tertiary graduates by field of study (2018)

Par tners

OECD

Social
sciences,
Natural
Information
Engineering, Agriculture,
journalism
Business,
sciences,
and
manufacturing
forestry,
and
administration mathematics communication
and
fisheries and Health and
Arts and
and law
and statistics techno logies
constr uction
veterinary
welfare
Education humanities information

Services

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

Countries
Australia
Austria
Belgium
Canada 1
Chile
Colombia
Costa Rica
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungar y
Iceland
Ireland
Israel
Italy
Japan 2
Korea
Latvia
Lithuania
Luxembourg
Mexico
Netherlands
New Zealand
Nor way
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United Kingdom
United States

9
12
8
6
14
8
22
11
5
7
7
4
11
8
14
13
9
m
7
9d
7
8
6
10
11
10
10
16
21
4
14
11
17
13
10
9
8
6

12
8
10
10
3
4
3
9
12
13
10
9
11
11
9
10
12
m
17
15 d
16
7
9
10
3
9
12
8
7
10
8
9
9
6
7
11
15
19

6
7
11
15
4
7
6
11
10
8
7
7
8
14
10
16
6
m
14
7d
5
9
9
11
9
13
9
11
9
11
12
9
7
12
7
8
12
12

36
24
21
28
25
46
37
20
26
23
19
34
23
22
26
22
27
m
18
20 d
15
28
26
42
34
27
24
17
24
20
20
20
19
16
28
31
22
19

5
6
4
6
1
1
2
6
5
6
5
8
9
9
4
5
8
m
8
3d
4
3
4
6
3
6
7
5
3
6
6
7
5
4
7
2
14
8

5
4
2
3
3
5
6
5
5
7
7
4
5
3
5
5
8
m
1
x
5
5
3
6
5
3
7
4
4
2
4
4
4
4
3
2
4
4

8
21
12
13
17
17
8
15
12
15
16
14
21
16
14
9
9
m
15
18 d
20
13
19
7
18
8
9
13
15
20
12
17
13
18
16
15
9
7

1
2
2
2
2
2
1
3
1
2
2
2
2
3
4
1
1
m
3
3d
1
2
3
0
2
1
2
1
2
2
2
3
1
1
1
2
1
1

17
8
30
15
22
6
14
12
21
13
22
15
7
11
9
17
17
m
15
16 d
16
17
18
7
11
17
15
20
9
18
17
12
17
23
15
13
15
17

2
8
1
3
9
4
2
7
3
7
5
4
2
3
5
3
4
m
3
8d
10
8
3
1
3
5
5
5
7
6
6
8
8
2
5
6
0
6

OECD average
EU23 average

10
10

10
10

9
10

25
25

5
6

4
4

14
15

2
2

15
15

5
4

Argentina
Brazil
China
India
Indonesia
Russian Federation
Saudi Arabia
South Africa1

m
19
m
8
24
8
13
19

m
3
m
6
5
4
18
5

m
5
m
30
13
11
10
16

m
32
m
19
18
27
30
32

m
2
m
16
3
3
7
7

m
3
m
5
8
5
6
3

m
13
m
12
8
23
8
8

m
3
m
1
4
2
0
2

m
16
m
3
16
8
6
7

m
3
m
0
0
8
1
0

G20 average

11

10

11

25

6

4

14

2

13

4

1. Year of reference 2017.
2. Data on information and communication technologies are included in other fields.
Source: OECD/UIS/Eurostat (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2https://doi.org/10.1787/888934163838

EDUCATION AT A GLANCE 2020 © OECD 2020

B5. WHO IS EXPECTED TO GRADUATE FROM TERTIARY EDUCATION?  225

Table B5.3. Graduation rate and profile of first-time tertiary graduates at short-cycle tertiary, bachelor's, master's and doctoral
or equivalent levels (2018)
Bachelor’s or equivalent

Total

Share of first-time graduates
below the age of 30

Share of internation al
first-time gradu ates

Excluding
internation al
students

Total

Share of first-time graduates
below the age of 35

Share of internation al
first-time gradu ates

Excluding
internation al
students

Total

Share of first-time graduates
below the age of 35

Share of internation al
first-time gradu ates

Excluding
internation al
students

Total

Doctorate or equivalent

Excluding
internation al
students

Master’s or equivalent

Share of internation al
first-time gradu ates

Short-cycle
tertiary
graduation rate,
for students
under 30

Share of first-time graduates
below the age of 30
Par tners

OECD

Shor t-cycle (2-3 years)

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

(13)

(14)

(15)

(16)

Countries
Australia
Austria
Belgium
Canada 1
Chile
Colombia
Costa Rica
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan 2
Korea
Latvia
Lithuania
Luxembourg
Mexico
Netherlands
New Zealand
Nor way
Poland
Por tugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United Kingdom
United States

65
95
m
83
73
m
m
89
79
a
a
m
84
a
88
50
m
m
93
100
m
54
a
97
96
74
67
69
20
93
82
73
85
58
32
81
71
m

14
0
m
m
0
m
m
4
16
a
a
m
0
a
1
0
m
m
7
8
m
1
a
26
m
0
29
1
0
2
1
1
1
0
a
0
4
2

14
25
m
m
20
m
m
0
8
a
a
m
0
a
2
1
m
m
1
22
m
9
a
2
m
1
10
3
0
3
1
7
20
4
a
20
7
m

18
25
m
28
20
m
m
0
10
a
a
m
0
a
2
1
m
m
1
24
m
9
a
3
2
1
15
3
0
3
1
7
21
4
0
20
8
m

83
86
95
91
77
m
m
86
85
81
77
m
87
91
82
79
m
76
92
100
m
81
92
92
89
95
79
84
m
91
86
87
91
76
77
86
92
m

28
18
8
m
0
m
m
11
8
7
6
m
4
2
5
4
m
m
4
2
m
5
2
21
m
10
28
3
m
3
6
2
1
2
7
1
17
4

35
17
33
m
27
m
m
25
40
28
36
m
27
37
19
34
m
m
28
44
m
27
47
6
m
40
30
36
m
34
27
36
32
18
35
29
37
m

50
21
36
33
27
m
m
29
44
30
38
m
29
38
20
35
m
31
28
45
m
29
48
7
26
44
41
37
m
35
28
37
32
18
39
29
45
m

85
87
96
78
62
m
m
91
92
83
76
m
94
63
86
65
m
57
94
m
m
82
90
80
m
95
73
82
m
94
92
92
87
84
89
99
85
m

66
25
24
m
0
m
m
13
21
20
12
m
15
1
14
13
m
m
6
11
m
12
8
50
m
29
40
9
m
10
6
5
15
20
25
25
47
16

6
13
16
m
6
m
m
18
22
13
16
m
16
10
11
13
m
m
20
m
m
12
15
4
m
13
4
15
m
18
25
20
16
12
12
1
10
m

21
18
21
8
6
m
m
21
29
16
18
m
18
10
13
15
m
11
21
m
m
14
16
7
m
19
7
16
m
19
26
21
19
16
16
1
21
m

56
59
76
63
51
m
m
71
69
60
47
m
79
45
63
48
m
36
83
m
40
46
73
81
m
83
55
48
m
41
76
74
48
54
79
59
71
m

41
32
20
m
5
m
m
17
38
16
30
m
19
1
11
38
m
m
13
19
m
9
3
87
m
42
52
27
m
26
8
7
m
37
57
7
46
27

0.7
0.9
1.1
m
0.1
m
m
1.0
1.1
0.6
0.7
m
1.7
0.5
0.6
0.2
m
m
0.9
m
m
0.2
0.7
0.2
m
1.1
0.5
0.5
m
0.6
1.3
1.0
m
0.5
1.2
0.3
1.2
m

1.3
1.4
1.4
1
0.1
m
m
1.2
2.0
0.7
1.2
m
2.0
0.5
0.7
0.6
m
0.5
1.0
m
0.9
0.2
0.7
1.2
m
1.8
1.1
0.9
m
0.8
1.3
1.1
1.5
1.1
2.8
0.3
2.3
m

OECD average
EU23 average

75
76

5
4

8
6

9
6

86
87

8
7

31
30

33
32

84
87

19
18

13
15

16
18

62
65

26
25

0.8
0.8

1.1
1.2

Argentina
Brazil
China
India
Indonesia
Russian Federation
Saudi Arabia
South Africa

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

G20 average

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

Bachelor’s
graduation rate,
for students
under 30

Master’s
graduation rate,
for students
under 35

Doctoral
gr aduation rate,
for students
under 35

1. Year of reference 2017.
2. It is estimated that almost all students graduate from short-cycle tertiary education and bachelor's programmes before the typical graduation age.
Source: OECD/UIS/Eurostat (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2https://doi.org/10.1787/888934163857

EDUCATION AT A GLANCE 2020 © OECD 2020

226 | B6. WHAT IS THE PROFILE OF INTERNATIONALLY MOBILE STUDENTS?

Indicator B6. What is the profile of
internationally mobile students?
Highlights


The number of international and foreign tertiary students has grown on average by 4.8% per year between 1998
and 2018. Even though OECD countries host the great majority of international and foreign students, the fastest
growth has been among internationally mobile students enrolled in non-OECD countries.



In 2018, there were three international or foreign students for each national student studying abroad across OECD
countries, but this ratio exceeds 10:1 in Australia, New Zealand, the United Kingdom and the United States.



In total, women in OECD countries are about as likely as men to travel abroad for a bachelor’s or master’s degree
or equivalent, but less likely to do so to enrol in a doctoral or equivalent programme.

Figure B6.1. Growth in international or foreign enrolment in tertiary education worldwide (1998 to 2018)
Number of international or foreign students enrolled in OECD and non-OECD countries

Millions of students
6.0
5.5

Total 5.6

5.0

Non-OECD 1.7

4.5
4.0
3.5
3.0
2.5

OECD 3.9

2.0
1.5
1.0

2018

2017

2016

2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

2004

2003

2002

2001

2000

1999

1998

0.5
0.0

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 (2020). 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/10.1787/69096873-en).
Statlink2https://doi.org/10.1787/888934164009

EDUCATION AT A GLANCE 2020 © OECD 2020

B6. WHAT IS THE PROFILE OF INTERNATIONLLY MOBILE STUDENTS?  227

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 (whether international or foreign) may be an important source of income and have a
disproportionate impact on their economic and innovation systems. They 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.
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 numbers of 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. In addition, student
mobility appears to shape international scientific co-operation networks more deeply than either a common language or
geographical or scientific proximity.
In 2020, higher education institutions around the world closed down to control the spread of the COVID-19 pandemic
potentially affecting more than 3.9 million international and foreign students studying in OECD countries (UNESCO,
2020[1]). The imposed lockdown has affected the continuity of learning and the delivery of course material, as well as
students’ perceptions about the value of their degree and their host country’s capacity to look out for their safety and wellbeing. These changes could have dire consequences on international student mobility in the coming years (Box B6.1).

Other findings


Students from Asia form the largest group of international or foreign students in tertiary education at all levels,
accounting for 57% of all mobile students across the OECD in 2018. Together, the People’s Republic of China
and India contribute more than 30% of all mobile students enrolled in OECD countries.



The United States is the top OECD destination for international students. It accounts for 18% of the global
education market share, followed by Australia and the United Kingdom (8% each), and Germany (6%).



In total across OECD countries, the fields studied by mobile students share a similar pattern to those studied by
national ones, with the largest share entering the broad field of business, administration and law, followed by
engineering, manufacturing and construction.

EDUCATION AT A GLANCE 2020 © OECD 2020

228  B6. WHAT IS THE PROFILE OF INTERNATIONALLY MOBILE STUDENTS?

Analysis
Trends in international student mobility
International student mobility has been expanding quite consistently in the past twenty years. In 2018, 5.6 million tertiary
students worldwide had crossed a border to study, more than twice the number in 2005. Many factors at the individual,
institutional, national and global levels drive patterns of international student mobility. These include personal ambitions and
aspirations for better employment prospects, a lack of high-quality higher education institutions at home, the capacity of higher
education institutions abroad to attract talent, and government policies to encourage cross-border mobility for education
(Bhandari, Robles and Farrugia, 2018[2]). The needs of increasingly knowledge-based and innovation-driven economies have
spurred demand for tertiary education worldwide, while rising wealth in emerging economies has prompted the 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 enabling contacts to be maintained
across borders) and cultural factors (e.g. use of English as a common working and teaching language) have contributed to
making international study substantially more affordable and easier to access than in the past.
The number of international and foreign tertiary students grew on average by 4.8% per year between 1998 and 2018. Even
though OECD countries welcome the great majority of international and foreign students, the number of foreign students
enrolled in non-OECD countries has been rising faster: their numbers have grown by 6.2% per year on average compared to
4.3% for international and foreign students in OECD countries. In 2018, foreign students enrolled in non-OECD countries
represented about 30% of the global pool of internationally mobile students, compared to 23% in 1998 (Figure B6.1).
The growth rate of international or foreign students has fluctuated greatly in the past two decades, for both groups of students,
however it has varied more for students from non-OECD countries than from OECD ones. Between 1998 and 2018, the
annual growth rate of mobile students in non-OECD countries varied from 0.3% in 2004 to 19% in 2008. In contrast, the
annual growth in mobile students in OECD countries fluctuated between 0.7% and 8% over the same period. However, the
growth of international and foreign students in non-OECD countries has been slowing down in recent years. Since 2017, their
yearly growth rate dropped below 3%, the lowest rate since 2013, and less than half the yearly growth rate of international
and foreign students in OECD countries over this period (Figure B6.1).
Despite strong increases in the total number of international and foreign students worldwide, their relative concentration has
remained fairly stable, increasing from 5% of all tertiary students in 2014 to 6% in 2018 in total across OECD countries. While
their share increased in most OECD countries over this period, there are striking differences across countries: the share of
international or foreign students increased by 6 percentage points or more in Australia and Estonia between 2014 and 2018,
while it declined by 1 percentage point in Belgium and Greece. In about one-third of OECD countries, international students
accounted for more than 10% of enrolled tertiary students in 2018. At least 20% of tertiary students in Australia, Luxembourg
and New Zealand are international or foreign, compared to 2% or less in Chile, Colombia, Costa Rica, Mexico, and Turkey
(Table B6.1).

Mobility patterns and international student flows
The pools and flows of 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 (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
differences in the returns to or rewards for education and skills in origin and destination countries (see Indicators A3 and A4).
Economic factors include better economic performance in the host country, exchange rates, more affordable mobility (due to
lower tuition fees or higher education subsidies, for instance) and higher-quality education in the host country. In addition, the
decision to study abroad may be determined by non-economic factors, such as political stability or cultural and religious
similarities between origin and destination countries (Guha, 1977[3]; UNESCO Bangkok, 2013[4]; Weisser, 2016[5]).
The perceived quality of instruction abroad and the perceived value of host institutions are key criteria for international
students when choosing where to study (Abbott and Silles, 2016[6]). 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 for assessing the

EDUCATION AT A GLANCE 2020 © OECD 2020

B6. WHAT IS THE PROFILE OF INTERNATIONLLY MOBILE STUDENTS?  229
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 inflows of international
students in university funding formulas. In Finland, for example, the internationalisation of higher education is one of the
dimensions considered for the funding of tertiary institutions, along with quality and impact measures (Eurydice, 2020[7]).
Similarly, in Estonia and Norway, the share of foreign or international students is an indicator used to determine the level of
block grant funding allocated to tertiary institutions (OECD, 2019[8]).
Most countries have implemented reforms aiming to lower the barriers to migration of highly skilled individuals, beyond the
purposes of education, and most countries operate funding programmes to support inward, outward or return mobility. While
the conditions of migration differ (e.g. short-term versus long-term settlement), the most common target for these programmes
are pre-doctoral students and early stage researchers (both doctoral and postdoctoral). Although setting appropriate tuition fees
remains one of the most debated topics in education policy, setting higher fees for international students is less politically
controversial and often constitutes an important revenue stream for higher education institutions. In some countries, international
students in public universities pay twice as much for tuition as national students, attracted by the perceived quality of the education
and potential labour-market prospects in their host country. In contrast, some countries may seek to promote international mobility
within a region by reducing or eliminating fees. Students from the European Economic Area can study in any other country within
this area, paying the same tuition fees as national students (see Indicator C5).

Figure B6.2. Share of national tertiary students enrolled abroad (2018)
76

%
20
18
16
14
12
10
8

2
0

Luxembourg
Slovak Republic1
Iceland
Lithuania
Estonia
Ireland
Latvia
Switzerland
Norway
Austria
Greece1
Hungary
Saudi Arabia
Portugal
Italy1
Slovenia
Israel
Czech Republic1
Germany
Finland
France
Sweden
EU23 total
Canad a
Belgium
Korea1
New Zealand
China
Netherlands
Spain
Denmark
Colombi a
United Kingdom
OECD total
Poland
Costa Rica2
Chile
India
Australia
Russian Federation1
South Africa2
Japan
Brazil1
Mexico
Indonesia
Turkey1
United States
Argentina2

6
4

1. National tertiary students are calculated as total enrolment minus foreign students instead of total enrolment minus international students.
2. Year of reference 2017.
Countries are ranked in descending order of the percentage of national students enrolled abroad.
Source: OECD/UIS/Eurostat (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2https://doi.org/10.1787/888934164028

In total across OECD countries, 2% of national tertiary students were enrolled abroad in 2018. Iceland, Luxembourg and
the Slovak Republic have the highest share of national tertiary students enrolled abroad for their degree, reaching 76% in
Luxembourg (Figure B6.2). Factors such as proximity, language, historical ties, geographical distance, bilateral relationships
and political framework conditions (e.g. the European Higher Education Area) are key determinants in selecting a country in
which to study (Abbott and Silles, 2016[6]). For example, the largest share of mobile students from the Slovak Republic study
in the Czech Republic, those from Luxembourg study in Germany or Belgium, while those from Iceland are more likely to
head to Denmark (Table B6.5, available on line).
Most countries are net “importers” of students, that is, they have more students coming into the country to study than leave
to study abroad. In total across OECD countries in 2018, there were three international students for each national student

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230  B6. WHAT IS THE PROFILE OF INTERNATIONALLY MOBILE STUDENTS?
studying abroad, but this ratio exceeds ten in Australia, New Zealand, the United Kingdom and the United States. In contrast,
a number of countries are net “exporters” of students, that is, more students travel abroad to study than they receive. Chile,
Colombia, Luxembourg and Mexico are among the OECD countries with the lowest ratios of international or foreign students
to national student abroad. Among partner countries, China and India, who together are responsible for more than 30% of the
pool of international students, are also net exporters of talent (Table B6.3).

By country of destination and origin
English is the lingua franca of the globalised world, with one in four people using it worldwide (Sharifian, 2013[9]). Not
surprisingly, English-speaking countries are the most attractive student destinations overall, with four countries receiving more
than 40% of all internationally mobile students in OECD and partner countries. The United States is the top OECD destination
country for international tertiary students. Of the 3.9 million international students in OECD countries, 987 000 are enrolled in
programmes in the United States. Among the English-speaking countries, after the United States, the United Kingdom
accounts for 452 000 international students, Australia 445 000 and Canada 225 000 (Table B6.1). As a destination country,
the United States alone accounts for 18% of the global education market share. Australia and the United Kingdom each have
8% of the global market share, while Germany has 6% (Table B6.3).

Figure B6.3. Distribution of international and foreign students by region of origin (2018)

%
100

Unknown
Oceania
North America
Latin America and Carr ibean

Africa
Europe
Asia

90
80
70
60
50
40
30
20

0

Japan
Korea1
Australia
Indonesia
New Zealand
United States
Russian Federation1
Turkey1
India
Canad a
Saudi Arabia
Greece1
OECD total
United Kingdom
Ireland
Latvia
Finland
Hungary
Germany
Italy1
EU23 total
Lithuania
Norway
Sweden
Estonia
France2
Poland
Iceland
Israel
Netherlands
Czech Republic1
Switzerland
Brazil1
Luxembourg
Denmark
Austria
Slovak Republic1
Spain
Portugal
Slovenia
Belgium
South Africa3
Costa Rica3
Colombi a1
Argentina3
Mexico
Chile

10

1. Share of foreign rather than international students.
2. The share of students by country of origin is based on citizenship criteria, while their total number is based on the country of upper secondary education.
3. Year of reference 2017.
Countries are ranked in descending order of the percentage of international or foreign students from Asia.
Source: OECD/UIS/Eurostat (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2https://doi.org/10.1787/888934164047

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 and Germany, France is also a major
EU host country, accounting for 4% of global international students. The Russian Federation is another major destination
country outside of the EU, with 5% of global mobile students (Table B6.3).

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B6. WHAT IS THE PROFILE OF INTERNATIONLLY MOBILE STUDENTS?  231
Students from Asia form the largest group of international students enrolled in tertiary education programmes at all levels,
totalling 57% of all mobile students across the OECD in 2018. In total over 30% of mobile students in OECD countries come
from China and India. More than two-thirds of Chinese and Indian students are concentrated in only five countries: Australia,
Canada, Japan, the United Kingdom and the United States. Europe is the next largest region of origin, with European
international students making up 23% of all mobile students enrolled in OECD countries. European students prefer to stay in
Europe, accounting for 40% of mobile students enrolled in the EU23 countries. At least 8 out of 10 mobile students in Austria,
the Czech Republic, Denmark, the Slovak Republic and Slovenia come from other European countries (Figure B6.3 and
Table B6.4, available on line)
Among OECD and partner countries, students from African countries only make up the majority of mobile students in
South Africa, where 80% of mobile students are from other African countries, although they account for more than 3 out of
10 mobile students in Portugal and Saudi Arabia and about 5 out of 10 in France. Student flows from Latin America and the
Caribbean highlight the importance of proximity, as they make up the majority of mobile students in Argentina, Brazil, Chile,
Colombia, Costa Rica and Mexico. They also highlight the importance of the language of study: more than 40% of 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 less than 1% of mobile students in OECD destination countries
(Figure B6.3).

Box B6.1. The impact of the COVID-19 pandemic on international student mobility flows
The global spread of the coronavirus pandemic has brought tertiary education in OECD countries to a standstill as
universities have closed down their premises and countries have shut their borders in response to government lockdown
measures. While the crisis has affected all tertiary students, it has had a severe impact on the internationalisation of higher
education. In particular, the crisis has affected the safety and legal status of international students in their host country,
the continuity of learning and the delivery of course material, and students’ perception of the value of their degree, all of
which could potentially have dire consequences for international student mobility in the coming years.
International students were particularly badly hit at the start of the lockdown as they have had to sort out the implications
of university closures on their status on campus and within their host country. Students have had to decide whether to
return home (funding permitting) with limited information of when they might return, or remain in their host country with
restricted employment and education opportunities, all while sorting out their visa status. Some countries, such as Canada
or the United Kingdom, have offered leniency around visa rules, or the possibility to remain on campus (Immigration,
Refugees and Citizenship Canada, 2020[10]) (UKCISA, 2020[11]) but this has not been the case everywhere. The varying
approach across institutions and countries has captured the complexity of ensuring accountability over the well-being and
safety of international students in a globalised higher education market.
To ensure the continuity of education despite the lockdown, higher education institutions have sought to use technology
and offer online classes and learning experiences as a substitute for in-class time. Although many higher education
institutions offered online courses before the pandemic, few students considered it as a sole alternative to physical inperson learning. For example, in the United States, only 13% of first-cycle tertiary students were exclusively enrolled in
distance education courses in 2017 (NCES, 2019[12]). Now with reopening for the coming academic year severely
compromised and travel likely to remain restricted even after the confinement period, international students are being
forced to face and deal with the reality of online learning.
Beyond the transactional learning experience, students are also losing out on other benefits of international mobility such
as international exposure, access to a foreign job market, and networking. A survey of EU students studying in
the United Kingdom found that the main reasons for choosing to study abroad were to broaden their horizons/experience
other cultures, improve their labour-market prospects and improve their competence in English (West, 2000[13]). Similarly,
the opportunity to live abroad, learn or improve a foreign language and meet new people, were among the three first
reasons cited among students participating in the EU-ERASMUS programme (European Comission, 2014[14]).
A decrease in the share of international students may have severe repercussions on the funding model of some higher
education institutions, as international students often pay higher tuition fees than domestic ones. Countries, such as
Australia, Canada, the United Kingdom and the United States, that rely heavily on international students with differentiated

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232  B6. WHAT IS THE PROFILE OF INTERNATIONALLY MOBILE STUDENTS?
fees will suffer the highest losses. For instance, at the bachelor’s or equivalent level, public institutions in Australia, Canada
and the United States charged foreign students over USD 13 800 more per year on average than national ones in 2017/18
(see Indicator C5). Given the large share of international students in these countries, international student inflows provide
an important source of revenue to tertiary institutions. In Australia, the estimated revenue from foreign students’ tuition
fees exceeds one-quarter of the total expenditure on tertiary educational institutions (OECD, 2017[15]). Overall, doctoral
programmes will be particularly affected, as one in five students in these programmes are international. While the
investment in a tertiary degree still pays off over a lifetime, students may start to question the value of paying high fees to
study abroad in uncertain times, particularly if that learning is to happen on line and they are no longer able to benefit from
networking and access to a foreign labour market. Students are already demanding a partial refund of their tuition fees
and many institutions have made pro-rata refunds on room and board, or have offered fee deferrals. With the enrolment
of international students for the next academic year severely compromised, this will cut into universities’ bottom line,
affecting not only their core education services, but also the financial support they provide domestic students, as well as
research and development activities.
The financial losses are not limited to higher education institutions. Countries have traditionally relied on international
student mobility to facilitate the immigration of foreign talent and contribute to both knowledge production and innovation
nationally. Australia, New Zealand and the United Kingdom, for example, have reduced barriers to the migration of highly
qualified students, facilitating their entry into the labour market after graduation (OECD, 2019[16]) (OECD, 2016[17]). The
decline in international mobility in these countries risks affecting productivity in advanced sectors related to innovation and
research in coming years.
Higher education has often been considered a refuge in periods of low employment, enabling adults to develop their skills.
In contrast to previous economic downturns, the lockdown measures of this current crisis has affected the delivery of
learning and the experience of studying abroad in ways that extend well beyond the classroom. It has also raised
awareness on the vulnerability of international students in times of crisis. All of this is likely to influence the value students
perceive they will get from their degree in relation to the price they are willing to pay. As a result, international student
mobility is expected to decline in the coming years as students reassess their options. Faced with these challenges, higher
education institutions will need to develop a new value proposition that reassesses the quality of learning and delivery
mechanisms in the classroom, and that address the needs of an international student population that may be less willing
to cross borders for the sole purpose of study.

Profile of internationally mobile students
By level of education
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. In total across OECD
countries, international students account for 6% of total enrolment in tertiary programmes. International enrolment in
bachelor’s or equivalent 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 Australia, Austria, Luxembourg,
New Zealand and the United Kingdom, 15% or more of students at bachelor’s level are international (Figure B6.4).
International enrolment increases significantly at master’s or equivalent level. In total 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. Among countries with more than 1% international or foreign tertiary students,
the share of international students in Spain and Sweden is at least four times higher at master’s than at bachelor’s level.
Greece is the only country where the inflow of foreign students at master’s level is slightly lower than at bachelor’s level
(Figure B6.4).
At doctoral or equivalent level, international students represent 22% of enrolled students. The countries with the highest
shares are Belgium, Luxembourg, the Netherlands New Zealand, Switzerland and the United Kingdom, which all have 40% or
more of their doctoral students coming from abroad. In Luxembourg and Switzerland, there are more international students
in doctoral programmes than national students (86% in Luxembourg and 56% in Switzerland). While most countries have
higher shares of international students at doctoral than at master’s level, a number of countries show the opposite pattern.

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B6. WHAT IS THE PROFILE OF INTERNATIONLLY MOBILE STUDENTS?  233
This is particularly striking in Australia (53% at master’s level and 34% at doctoral level) and Latvia (20% at master’s and 10%
at doctoral level) (Figure B6.4 and Table B6.1).

Figure B6.4. Incoming student mobility in tertiary education, by level of study (2018)
International or foreign student enrolment as a percentage of total enrolment in tertiary education
86
78

%
60

All tertiary
Bachelor’s or equivalent
Master’s or equivalent
Doctoral or equivalent

50
40
30
20

0

Luxembourg
Australia
New Zealand
United Kingdom
Switzerland
Austria
Canada
Czech Republic
Netherlands
Hungary
Denmark
Belgium1
Germany
Ireland
Estonia
Latvia
EU23 total
France
Finland
Slovak Republic
Iceland
Portugal
Sweden
OECD total
Italy
Lithuania
United States
Japan
Saudi Arabia
Slovenia
Norway
South Africa2
Russian Federation
Poland
Spain
Greece
Israel
Argentina2
Korea
Turkey
Costa Rica2
Chile
Brazil
Colombia
Mexico
India
Indonesia

10

Note: All tertiary education includes short-cycle tertiary programmes, which are not presented separately in the figure.
1. Data on short-cycle tertiary programmes are based on nationality and refer to the Flemish community only.
2. Year of reference 2017.
Countries are ranked in descending order of the percentage of international or foreign students in tertiary education.
Source: OECD (2020), Table B6.1. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2https://doi.org/10.1787/888934164066

By field of study
Fields of study are a key consideration for students choosing to pursue a tertiary degree abroad. Some countries devote more
resources to research in certain fields and therefore benefit from strong international recognition particularly at higher levels
of tertiary education. In total across OECD countries, the distribution of fields among mobile students mirrors the distribution
among national ones, with in both cases the largest share entering the broad field of business, administration and law, followed
by engineering, manufacturing and construction. However, there are also notable exceptions. The field of social sciences,
information and journalism attracts 12% of mobile students compared to 9% of national students in total. Similarly, the field
of natural sciences, mathematics and statistics attracts 8% of mobile students compared to 5% of national ones. In contrast,
internationally mobile students are less likely to enrol in the fields of education and health and welfare than national students
in total across the OECD (Table B6.2).
There are also striking differences between countries, highlighting potential specialisations and the attractiveness in some
countries for a given field of study. More than half of foreign students in the Slovak Republic entered a health and welfare
programme, three times more than the share of national students. In Denmark, Germany and Turkey, the share of international
or foreign students entering engineering, manufacturing or construction is 10 percentage points higher than the share among
national students. Among countries with the largest share of mobile students, such as Australia, Luxembourg, New Zealand

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234  B6. WHAT IS THE PROFILE OF INTERNATIONALLY MOBILE STUDENTS?
and the United Kingdom, business, administration and law is the most attractive field for international and foreign students
(Table B6.2).

By gender
While women outnumber men among entrants and graduates from tertiary education, they are about as likely as men to travel
abroad for a bachelor’s or master’s degree on average across OECD countries. However, they are less likely to do so to enrol
in a doctoral programme: at doctoral level, the share of women among mobile students decreases to 43% on average
(Figure B6.5).
Across OECD countries, the share of women among mobile students generally decreases with higher tertiary level, and the
difference between the share of women among internationally mobile bachelor’s and doctoral students exceeds
15 percentage points in about a quarter of them. Only in Latvia is the share of women among mobile doctoral students higher
than among mobile bachelor’s students. The fall in the share of women among mobile students tends to be more pronounced
between master’s and doctoral programmes than between bachelor’s and master’s. While the share of women among mobile
students decreases by 6 percentage points between master’s and doctoral levels in total across OECD countries, the drop is
15 percentage points or more in Israel, Korea and the Slovak Republic. In contrast, the share of women among mobile
students across all three levels of education is very similar in Chile, Finland and the United States although gender parity is
only achieved at all three levels in Chile (Figure B6.5).

Figure B6.5. Share of women among international or foreign students, by level of education (2018)
Bachelor’s or equivalent
Master’s or equivalent
Doctoral or equivalent

%
80
70
60
50
40
30
20

Latvia
Russian Federation

Estonia
Turkey

Lithuania
United States

Finland
Brazil

Hungary
Japan
Germany

Poland
OECD total

Canada
Australia

Switzerland
Chile

Colombia
Greece

EU23 total
Austria
New Zealand

France
Czech Republic

Denmark
United Kingdom

Portugal
Spain

Ireland
Slovenia

Israel
Netherlands

Norway
Luxembourg
Korea

Italy
Slovak Republic

Iceland

0

Belgium
Sweden

10

Countries are ranked in descending order of the percentage of women among mobile students enrolled in bachelor's or equivalent programmes.
Source: OECD/UIS/Eurostat (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2https://doi.org/10.1787/888934164085

In most countries, the share of women tends to be greater among mobile students enrolled in bachelor’s programmes than in
any other degree. However the share of women among mobile students also displays the greatest variation across countries
at bachelor’s level. While 49% of mobile bachelor’s students are women in total across OECD countries, this varies from close
to 70% in Iceland to less than 30% in Latvia. In master’s programmes, the share varies across countries, although to a lesser
extent than in bachelor’s programmes. In Korea and Slovenia, women account for more than 60% of mobile students in
master’s programmes, the largest share across all OECD countries, but account for less than 40% in Turkey. At doctoral
level, less than half of mobile students are women in all OECD countries except Chile (Figure B6.).

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B6. WHAT IS THE PROFILE OF INTERNATIONLLY MOBILE STUDENTS?  235

Definitions
Foreign students are those who are not citizens of the country in which they are enrolled and where the data are collected.
Although they are counted as internationally mobile, they may be long-term residents or even be born in the “host” country.
While pragmatic and operational, this classification may be inappropriate for capturing student mobility because of differing
national policies regarding the naturalisation of immigrants. For instance, Australia has a greater propensity than Switzerland
to grant permanent residence to its immigrant populations. This implies that even when the proportion of foreign students in
tertiary enrolment is similar for both countries, the proportion of international students in tertiary education 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.
Mobile students are students who are either international or foreign.
National students are students who are not internationally mobile. Their number is computed as the difference between the
total number of students in each destination country and the number of international or foreign students.
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/10.1787/69096873-en).

Methodology
Defining and identifying mobile students, as well as their types of learning mobility, are a key challenge for developing
international education statistics, since current international and national statistical systems only report domestic educational
activities undertaken within national boundaries (OECD, 2018[18]).
Data on international and foreign students are therefore obtained from enrolments in their countries of destination. This is the
same method used for collecting data on total enrolments, i.e. records of regularly enrolled students in an education
programme. Students enrolled in countries that did not report to the OECD or to the UNESCO Institute for Statistics are not
included and, for their countries of origin, the total number of national students enrolled abroad may be underestimated.
The total number of students enrolled abroad refers to the count of international students, unless data are not available and
the count of foreign students is used instead. Enrolment numbers are computed using a snapshot method, i.e. counting
enrolled students at a given period of time (e.g. a specific day or period of the year).
This methodology has some limits. OECD international statistics on education tend to overlook the impact of distance and elearning, 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.

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236  B6. WHAT IS THE PROFILE OF INTERNATIONALLY MOBILE STUDENTS?
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 South-South exchanges to
global brain circulation.
For more information, please see the OECD Handbook for Internationally Comparative Education Statistics 2018: Concepts,
Standards, Definitions and Classifications (OECD, 2018[18]) and Annex 3 for country-specific notes
(https://doi.org/10.1787/69096873-en).

Source
Data refer to the academic year 2017/18 and are based on the UNESCO-UIS/OECD/EUROSTAT data collection on education
statistics administered by the OECD in 2019 (for details, see Annex 3 at https://doi.org/10.1787/69096873-en).
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 2010-18).

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[1]

UNESCO Bangkok (2013), The International Mobility of Students in Asia and the Pacific, United Nations
Educational, Scientific and Cultural Organization, http://unesdoc.unesco.org/images/0022/002262/226219E.pdf
(accessed on 3 July 2018).

[4]

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.

[5]

West, A. (2000), Reasons for Studying Abroad: A Survey of EU Students Studying in the UK, Education-line,
Edinburgh.

[13]

Indicator B6 Tables
Table B6.1

International and foreign student mobility in tertiary education (2010, 2014 and 2018)

Table B6.2

Distribution of national and international or foreign students by field of study (2018)

Table B6.3

Mobility patterns of foreign and international students (2018)

WEB Table B6.4

Distribution of international and foreign students, by country of origin (2018)

WEB Table B6.5

Distribution of international and foreign students, by country of destination (2018)

Cut-off date for the data: 19 July 2020. Any updates on data can be found on line at http://dx.doi.org/10.1787/eag-dataen. More breakdowns can also be found at http://stats.oecd.org/, Education at a Glance Database.
StatLink: https://doi.org/10.1787/888934163933

EDUCATION AT A GLANCE 2020 © OECD 2020

238  B6. WHAT IS THE PROFILE OF INTERNATIONALLY MOBILE STUDENTS?
Table B6.1. International and foreign student mobility in tertiary education (2010, 2014 and 2018)
International or foreign student enrolment as a percentage of total tertiary enrolment
Reading the sixth column of the upper section of the table (international): 27% of all students in tertiary education in Australia are international students
and 18% of all students in ter tiary education in Switzerland are international students.
Reading the sixth column of the lower section of the table (foreign): 3% of all students in tertiar y education in Greece are not Greek citizens, and 3%
of all students in tertiar y education in Kore a are not Kore an citizens.

Par tners

OECD

Number
of internation al
or foreign
students
(in thousands)

Share of international or foreign students by level of tertiar y education
Short-cycle
ter tiar y

Bachelor’s
or equivalent

Master’s
or equivalent

(1)

(2)

2018
(3)

Countries
Australia
Austria
Belgium 1
Canada
Chile
Denmark
Estonia
Finland
France 2
Germany
Hungary
Iceland
Ireland
Israel
Japan
Latvia
Lithuania
Luxembourg
Mexico
Netherlands
New Zealand
Nor way
Poland
Por tugal
Slovenia
Spain
Sweden
Switzerland
Unite d Kingdom
United States

445
75
54
225
6
33
4
24
230
312
32
1
22
11
183
8
6
3
7
105
53
12
54
28
3
71
31
54
452
987

32
1
8
13
0
13
a
a
3
0
1
28
4
m
8
1
a
10
0
3
19
1
0
3
2
1
0
0
4
2

16
19
7
12
0
6
7
5
7
7
9
5
7
3
3
8
3
23
0
10
17
3
3
5
4
1
3
10
15
5

53
22
19
17
1
20
14
12
12
16
19
11
20
5
9
20
11
78
1
17
32
7
5
10
6
11
12
29
35
13

Colombia
Costa Rica 3
Czech Republic
Greece
Italy
Korea
Slovak Republic
Turkey

5
3
45
26
107
85
12
125

0
x(6)
5
a
7
1
1
0

OECD total
Average for countries
with available data
for all reference years
EU23 total

3 939

Argentina 3
Brazil
China
India
Indonesia
Russian Federation
Saudi Arabia
South Africa 3

Doctoral
or equivalent

All ter tiar y
2018
(6)

2014
(7)

2010
(8)

34
33
42
35
12
36
17
23
38
12
19
33
30
7
19
10
7
86
2
44
49
21
2
29
10
17
36
56
41
25

27
17
10
14
0
11
10
8
9
10
11
8
10
3
5
9
5
48
0
12
20
4
4
8
4
3
7
18
18
5

18
15
11
10
0
10
4
7
10
8
7
7
7
3
3
5
3
44
0
10
19
4
2
4
3
2
6
17
18
4

22
15
7
m
m
8
2
6
m
9
5
5
m
1
m
2
1
m
m
4
15
3
1
3
2
3
7
17
16
3

0
x(6)
12
4
5
2
7
2

Foreign students
1
3
x(6)
x(6)
16
18
1
1
6
16
9
11
10
10
5
8

0
1
14
3
6
3
8
2

0
m
10
4
5
2
6
1

m
m
m
m
m
2
4
m

3

5

13

22

6

5

m

8

6

5

1 738

3

7

14

23

9

8

m

89
21
178
45
8
262
74
45

x(6)
0
m
a
x(6)
1
x(6)
x(6)

x(6)
0
m
x(6)
x(6)
5
x(6)
x(6)

Foreign students
x(6)
x(6)
1
2
m
m
x(6)
x(6)
x(6)
x(6)
6
7
x(6)
x(6)
x(6)
x(6)

3
0
m
0
0
4
5
4

m
0
m
0
m
3
5
4

m
0
m

(4)
(5)
Internation al students

m
2
m
m

1. Data on short-cycle tertiary programmes are based on nationality and refer to the Flemish community only.
2. Break in series between 2017 and 2018. See Annex 3 for more information.
3. Year of reference 2017.
Source: OECD/UIS/Eurostat (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2https://doi.org/10.1787/888934163952

EDUCATION AT A GLANCE 2020 © OECD 2020

B6. WHAT IS THE PROFILE OF INTERNATIONLLY MOBILE STUDENTS?  239

Table B6.2. Distribution of international or foreign students by field of study (2018)
All tertiary programmes

Source: OECD/UIS/Eurostat (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2https://doi.org/10.1787/888934163971

EDUCATION AT A GLANCE 2020 © OECD 2020

240  B6. WHAT IS THE PROFILE OF INTERNATIONALLY MOBILE STUDENTS?

Par tners

OECD

Table B6.3. Mobility patterns of foreign and international students (2018)
Percentage
of nation al ter tiar y
students enrolled
abroad

Number of internation al
or foreign students per
nation al student abroad

Number of internation al or
foreign students for ever y
hundred nation al students
home and abroad

Percentage of
international or foreign
students coming from
neighbouring countries

Internation al education
market shares

(1)

(2)

Total tertiar y
(3)

(4)

(5)

Countries
Australia
Austria
Belgium
Canada
Chile
Colombia
Costa Rica 3
Czech Republic 1
Denmark
Estonia
Finland
France
Germany
Greece1
Hungary
Iceland
Ireland
Israel 2
Italy 1
Japan
Korea 1
Latvia
Lithuania
Luxembourg
Mexico
Netherlands
New Zealand
Nor way
Poland
Por tugal
Slovak Republic 1
Slovenia
Spain
Sweden
Switzerland
Turkey 1
Unite d Kingdom
United States

1
6
3
3
1
2
1
4
2
8
4
4
4
5
5
17
7
4
4
1
3
7
9
76
1
2
2
6
2
4
19
4
2
4
6
1
2
0

33
4
3
5
0
0
1
4
6
1
2
2
3
1
3
0
1
1
1
6
1
1
1
0
0
6
10
1
2
2
0
1
2
2
3
3
11
12

36
20
11
16
0
0
1
15
12
10
8
9
11
3
12
7
10
3
6
5
3
10
5
22
0
13
24
4
4
8
7
4
4
7
20
2
22
5

3
58
38
4
34
59
50
52
37
43
13
14
15
60
22
7
7
5
19
54
62
17
24
54
34
28
6
20
68
4
57
27
29
20
54
47
11
5

8
1
1
4
0
0
0
1
1
0
0
4
6
0
1
0
0
0
2
3
2
0
0
0
0
2
1
0
1
1
0
0
1
1
1
2
8
18

OECD total
EU23 total

2
4

3
3

6
10

Argentina 3
Brazil 1
China
India
Indonesia
Russian Federation1
Saudi Arabia
South Africa 3

0
1
2
1
1
1
5
1

10
0
0
0
0
4
1
5

3
0
0
0
0
4
5
4

70
31
49
37
m
46
73
51
32
44

2
0
3
1
0
5
1
1

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.
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 2017.
Source: OECD/UIS/Eurostat (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2https://doi.org/10.1787/888934163990

EDUCATION AT A GLANCE 2020 © OECD 2020

242  B7. HOW DO VOCATIONAL EDUCATION SYSTEMS DIFFER AROUND THE WORLD?

Indicator B7. How do vocational education
systems differ around the world?
Highlights






About one in three students from lower secondary to short-cycle tertiary level are enrolled in a vocational
education and training (VET) programme on average across OECD countries. However, there are wide variations
between countries, ranging from less than 20% of students in Brazil, Colombia and Lithuania to more than 40%
in Australia, Austria, Belgium, Finland and Slovenia.
Upper secondary education plays a central role in VET systems and accommodate adult population increasingly.
On average, more than two-thirds of students in vocational education (from lower secondary to short-cycle tertiary)
are enrolled in upper secondary programmes, while 42% of all upper secondary students opt for VET
programmes.
On average, about two-thirds of upper secondary vocational students are in programmes that theoretically give
them the opportunity to enter tertiary education directly. Usually, this is at short-cycle tertiary level but in about
two-thirds of countries with available data, graduates from upper secondary vocational programmes can go
straight into bachelor’s or equivalent programmes.

Figure B7.1. Distribution of students enrolled in vocational education by level of education (2018)
Full- and part-time students enrolled in public and private institutions
Short-cycle tertiary education
Post-secondary non-tertiary education
Lower secondary education
Upper secondary education

%
100
90
80
70
60
50
40
30
20

Chile (28%)

Korea (27%)

Australia (43%)

Colombia (19%)

Lithuania (16%)

New Zealand (26%)

Turkey (38%)

Mexico (29%)

(8%)
Brazil

Russian Federation (25%)

Greece (25%)

Latvia (32%)

Costa Rica (22%)

Spain (28%)

Germany (27%)

France (24%)

Hungary (28%)

(31%)

OECD average (32%)

Austria (42%)

EU23 average

Israel (25%)

Belgium (47%)

Poland (35%)

Denmark (26%)

Iceland (21%)

Estonia (27%)

Sweden (24%)

Portugal (26%)

Slovenia (48%)

Slovak Republic (33%)

Netherlands (38%)

Finland (50%)

Norway (30%)

Switzerland (38%)

Luxembourg (35%)

Czech Republic (36%)

0

United Kingdom 1 (33%)

10

Note: Figures in parentheses refer to the share of students enrolled in vocational education from lower secondary to short-cycle tertiary (ISCED 2 to 5) as a percentage
of all students enrolled at these levels.
1. Short-cycle tertiary programmes include a small number of bachelor's professional programmes.
Countries are ranked in descending order of the share of students enrolled in upper secondary vocational programmes.
Source: OECD (2020), Table B7.1. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2https://doi.org/10.1787/888934164180

EDUCATION AT A GLANCE 2020 © OECD 2020

B7. HOW DO VOCATIONAL EDUCATION SYSTEMS DIFFER AROUND THE WORLD?  243

Context
Vocational education and training (VET) is formed of programmes that attracts a diverse range of students, mainly
including those seeking technical skills to enter the labour market, adults wishing to increase their employability by
developing their skills further, and students who may seek entry into higher education later on (OECD, 2019[1]). VET
programmes can also be an attractive option for students who struggle academically and are at risk of dropping out of
education. VET systems can boost economic development and help countries remain competitive in the globalised world
by adapting to evolving skill needs, through the expansion of a workforce with mid-level trade or technical and professional
skills (OECD, 2015[2]). Evidence shows that countries with well-established vocational and apprenticeship programmes
have been more effective in holding the line on youth unemployment and in providing the skills needed by the labour
market (OECD, 2010[3]). In high-quality VET systems, cooperation with employers is key. The skills taught in the
programmes are aligned with the labour-market demands, and young people also gain generic and transferable skills, and
have sufficient career guidance. Teachers have access to initial education and professional development to keep their
skills up to date and have industry experience.
VET programmes can be either mainly school-based or work-based. The combination of learning in the work environment
and in school provides numerous advantages. Learners get an education that combines practical and theoretical learning.
Firms benefit because education can be tailored to workplace needs, and students become familiar with firm-specific
procedures (OECD, 2010[3]; OECD, 2014[4]; OECD, 2018[5]). In many countries, VET has been neglected and marginalised
in policy discussions, often overshadowed by the emphasis on general academic education (OECD, 2011[6]).
Nevertheless, almost all countries have recently changed their policies and have implemented significant VET reforms
since 2013. They have often been aimed at:
1.

improving the overall quality of VET programmes by updating curricula and improving the quality of teachers

2.

supporting students' transitions after graduation from upper secondary education into post-secondary non-tertiary
or tertiary education or the labour market

3.

improving access to VET and its attractiveness to students and employers

4.

strengthening apprenticeship systems by increasing the number of places available, enhancing workplace training
and encouraging employer engagement ( (OECD, 2018[5]) and (OECD, 2018[7])).

Other findings


Although they provide labour-market advantages, about one-third of all students in upper secondary vocational
education are enrolled in combined school- and work-based programmes on average across the OECD.



The typical actual duration of work-based learning in combined school- and work-based programmes differ widely
across countries and programmes. The work-based component forms less than 30% of such programmes’
duration in Estonia and Israel, compared to 80% in Finland and Switzerland.



On average across OECD countries, the average age of enrolment in upper secondary education is higher for
students in vocational education (21 years) than for students enrolled in general education (17 years).



On average across OECD countries, women make up 45% of vocational upper secondary students, with wide
variations across sectors and occupations. In contrast, at post-secondary non-tertiary level, more than 55% of
students enrolled in vocational programmes are women.

Note
VET programmes are classified as school-based or combined school- and work-based in this indicator. In school-based
programmes, at least 75% of the curriculum is presented in the school environment. In combined school- and work-based
programmes, at least 10% (but less than 75%) of the curriculum is presented in the school environment, with the remainder
is organised as work-based learning in enterprises. Entirely work-based programmes (i.e. over 90% of the curriculum is
presented in a work-based environment) are not included in the scope of this indicator.
The ISCED 2011 classification does not define academic and professional programmes for bachelor’s, master’s, doctoral
or equivalent degrees (ISCED 6 to 8) (OECD/Eurostat/UNESCO Institute for Statistics, 2015[8]). In the absence of
internationally agreed definitions for these categories of tertiary education, no analysis of vocational programmes at these
ISCED levels can be carried out. For this reason, this indicator focuses on vocational programmes from lower secondary
to short-cycle tertiary education (ISCED levels 2 to 5), where vocational programmes are clearly defined. Work is being
undertaken to address this limitation in the future.

EDUCATION AT A GLANCE 2020 © OECD 2020

244  B7. HOW DO VOCATIONAL EDUCATION SYSTEMS DIFFER AROUND THE WORLD?

Analysis
Overview of vocational education from lower secondary to tertiary level
The organisation and structure of vocational education varies considerably from one country to another, both in terms of the
opportunities available to students to enrol in it, the content of the programmes and the possibilities for further study and
employment. On average across OECD countries, about one in three students from lower secondary to short-cycle tertiary
level are enrolled in a VET programme. However, there are wide variations between countries, ranging from less than 20%
of students in Brazil, Colombia and Lithuania to more than 40% in Australia, Austria, Belgium, Finland and Slovenia
(Figure B7.1).
These relatively low figures are largely explained by the fact that lower secondary vocational programmes exist in only half of
the countries with available data, which explains why only 6% of lower secondary students enrol in vocational programmes
on average across OECD countries. VET programmes at this level are often designed for adults and are not part of initial
education. The share of students enrolled in VET at lower secondary level exceeds 10% only in Australia, Belgium,
Costa Rica, Ireland, Mexico and the United Kingdom. Most VET students enrolled in lower secondary vocational education
can directly access upper secondary vocational programmes except in Estonia, Mexico and the Slovak Republic. The other
exceptions include the few students enrolled in special education in Belgium and students in the Netherlands enrolled in
practical training designed for students who do not have the skills needed to go on into further education. Vocational lower
secondary programmes generally offer options for young people wishing to prepare for direct entry to the labour market in
low- or semi-skilled jobs, or provide adults and students with special educational needs with the basic skills necessary for
further learning (Table B7.1, Figure B7.1 and (OECD/Eurostat/UNESCO Institute for Statistics, 2015[8])).
Upper secondary education is the most common level at which VET programmes are provided across countries. All countries
except the United States have some students enrolled in vocational upper secondary education. In the United States, there
is no distinct vocational path at upper secondary level, although optional vocational courses are offered within the general
track and VET programmes start at the post-secondary level. On average across OECD countries, more than two-thirds of
all VET students are enrolled in upper secondary education and 42% of all upper secondary students are in vocational
programmes. However, the importance of VET systems within the educational landscape varies widely across countries. In
some, VET plays a central role in the initial education of young people whereas in other systems most students follow a
general education programme. In more than one-quarter of countries with available data, more than half of upper secondary
students participate in vocational programmes. In Austria, the Czech Republic, Finland, the Netherlands, the Slovak Republic
and Slovenia, more than 65% of upper secondary students follow this track. In Finland, the high proportion of students enrolled
in vocational education at this level is partly explained by the large number of adults participating in VET. In contrast, over
80% of upper secondary students are enrolled in general programmes in Brazil, Canada, Chile, Korea and Saudi Arabia. In
Canada, the proportion of young people expected to enrol in an upper secondary vocational programme is considerably
smaller because vocational programmes are often provided within the post-secondary system, and in Quebec (Canada),
vocational training at the secondary level is largely through second-chance programmes for older students (Table B7.1).
For students looking to continue their vocational education, the two most common options after upper secondary are postsecondary non-tertiary and short-cycle tertiary programmes. But these programmes are also for students who come from the
general education path. Just over one-quarter of all students in any kind of VET programme are enrolled in one of these two
levels. Specifically, 10% of these students are enrolled in post-secondary non-tertiary level programmes and 17% in shortcycle tertiary programmes. Two observations can be made. First, the countries with the most students enrolled in vocational
short-cycle tertiary programmes – Chile, Colombia, Korea, Spain, the Russian Federation and Turkey – either have no postsecondary non-tertiary options, or, for example in the Russian Federation and Spain, have few students enrolled at this level.
In these countries, short-cycle tertiary programmes are the best option for further education. Similarly, those with the most
students in post-secondary non-tertiary programmes are those with no or few short-cycle tertiary programmes (e.g. Brazil,
Greece and Lithuania). Second, there are some countries – Chile, Colombia, Korea and Turkey – where a larger share of
VET students are enrolled at short-cycle tertiary level than at upper secondary level (Table B7.1 and Figure B7.1). This might
be explained by the fact that even though short-cycle tertiary programmes are often vocational, they also enrol students from
upper secondary general programmes, which may create a shortage of places for students graduating from vocational tracks.
As a result, some countries have recently implemented reforms to improve upper secondary vocational graduates’ access to
short-cycle tertiary programmes. For example, Chile and Portugal have strengthened networking and co-ordination with higher
education institutions to help students with the transition from upper secondary VET to tertiary education. Similarly, Chile,
Italy and Japan have opened new technical institutes to increase the opportunities for vocational upper secondary graduates

EDUCATION AT A GLANCE 2020 © OECD 2020

B7. HOW DO VOCATIONAL EDUCATION SYSTEMS DIFFER AROUND THE WORLD?  245
to undertake further studies in short-cycle tertiary education while France has introduced quotas to ensure graduates from
upper secondary vocational education have more places in short-cycle tertiary programmes (OECD, 2018[5]).
Short-cycle tertiary programmes are often designed to prepare students to enter the labour market. However, these
programmes may also provide a pathway to other tertiary education programmes (see Indicator B4). The absence of or very
low enrolment levels in vocational short-cycle tertiary programmes, as seen for instance in Estonia, Finland and Germany,
does not mean that these countries’ VET systems do not offer students the opportunity to continue their studies at other
tertiary levels. On the contrary, in about two-thirds of OECD member and partner countries with data, students who have
completed upper secondary vocational education have the opportunity to enrol directly in bachelor's (or equivalent)
programmes (ISCED 6). However, the lack of internationally agreed definitions to distinguish between "academic" and
"professional" programmes at the bachelor's (or equivalent) level make it impossible to measure the importance of
professional programmes at this level in OECD countries to date (Table B7.2 and Figure B7.1).

Transition from upper secondary vocational education
Upper secondary education builds on students’ basic skills and knowledge to prepare them for tertiary education or the labour
market. In many countries, this level of education is not compulsory and it can last from two to five years. Most education
systems provide different types of programmes at this level to cater to students’ different interests and competencies, which
will prepare them to contribute fully to society. Developing and strengthening both general and vocational programmes in
upper secondary education can make education more inclusive, and strengthen the transition from school to work (OECD,
2019[1]; OECD/Eurostat/UNESCO Institute for Statistics, 2015[8]).
Pathways to higher levels of learning are likely to be particularly important in the near future. VET students may be particularly
at risk here. The OECD predicts that 14% of jobs are at high risk of automation and a further 32% are likely to change radically
in the coming years (OECD, 2019[9]). Recognising the importance of creating opportunities for further learning, many countries
have created (or are in the process to create) pathways to higher levels of education for VET graduates. For instance, as part
of the Portuguese Higher Education Admission Process 2020/2021, a new special competition for the admission to higher
education of graduates of specialised vocational and artistic education will be introduced. Pathways between upper secondary
VET, post-secondary non-tertiary and tertiary education can be either through direct access or through bridging programmes.

Transition to tertiary education
The number of students enrolled in upper secondary vocational education varies widely across countries. The type of upper
secondary vocational programmes also differs greatly, as do the opportunities they offer young people to continue their studies
in tertiary education. Even if upper secondary VET programmes are not academically oriented, they still provide eligibility to
tertiary education for many students in most countries. On average, about two-thirds of students enrolled in upper secondary
vocational education are receiving an education that theoretically provides them with the opportunity to directly enter a higher
education level, often short-cycle tertiary but also at bachelor’s or equivalent level (Table B7.2 and Figure B7.2).
Despite these opportunities, they are more limited than those offered to general upper secondary students in more than twothirds of the countries with available data. On average across countries, more than 90% of students in general upper
secondary education are enrolled in programmes that provide, in theory, eligibility to tertiary education. Only Austria, Israel,
Switzerland and the United Kingdom have a larger share of vocational upper secondary students enrolled in a programme
leading directly to tertiary education than the share of general upper secondary students. Among these countries, Austria,
Israel and the United Kingdom offer many opportunities for young upper secondary vocational graduates to continue their
studies in vocational programmes at the short-cycle tertiary level. Switzerland is one of the few countries with Germany where
a large proportion of upper secondary vocational students directly go on to enter tertiary institutions that award qualifications
equivalent to bachelor's level (Table B7.2).
However, starting tertiary education does not guarantee completion, particularly for upper secondary vocational graduates.
Students with a general upper secondary qualification have higher completion rates (within the theoretical duration of the
programme plus three years) at bachelor’s or equivalent level (70%) than students with a vocational upper secondary
qualification (58%). 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 (OECD, 2019[10]).

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246  B7. HOW DO VOCATIONAL EDUCATION SYSTEMS DIFFER AROUND THE WORLD?

Figure B7.2. Distribution of students enrolled in upper secondary vocational education by type of
vocational programme (2018)
Full- and part-time students enrolled in public and private institutions
Full level completion with eligibility to tertiary education (ISCED 354)
Full level completion without direct access to tertiary education (ISCED 353)
Insufficient (or partial level completion) without access to tertiary education (ISCED 351 and 352)

%
100
90
80
70
60
50
40
30
20

Norway (49%)

Sweden (35%)

Ireland (36%)

New Zealand (30%)

Iceland (28%)

Hungary (38%)

Belgium (57%)

Netherlands (68%)

Luxembourg (62%)

Spain (36%)

United Kingdom (44%)

France (39%)

Estonia (40%)

EU23 average (47%)

Czech Republic (71%)

Slovenia (71%)

OECD average (42%)

Poland (52%)

Denmark (38%)

Latvia (39%)

Slovak Republic (68%)

Italy (54%)

Greece (29%)

Germany (46%)

Israel (41%)

Switzerland (64%)

Austria (68%)

Mexico (35%)

Lithuania (27%)

Turkey (46%)

Japan1 (22%)

Korea (18%)

Portugal (40%)

Finland (72%)

Colombia (27%)

Costa Rica (32%)

(9%)

Brazil (11%)

Canada

0

Chile (16%)

10

Note: Figures in parentheses refer to the share of students enrolled in upper secondary vocational education as a percentage of all students enrolled at this level.
1. Vocational programmes sufficient for level completion, with eligibility to tertiary (ISCED 354) include all vocational programmes insufficient for level completion, without
direct access to tertiary education (ISCED 351).
Countries are ranked in descending order of the share of students enrolment in upper secondary vocational programmes sufficient for level completion, with eligibility to
tertiary education (ISCED 354).
Source: OECD (2020), Table B7.2. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2https://doi.org/10.1787/888934164199

Transition to post-secondary non-tertiary education or the labour market
Supporting students' transitions after graduation from upper secondary education into post-secondary education is an
important challenge for countries. A small group of countries including Belgium, Hungary, Iceland, Ireland, New Zealand,
Norway and Sweden present a different pattern for the transition between upper secondary and post-secondary education
(Figure B7.2). In these countries, upper secondary vocational programmes are not designed to provide to students eligibility
to tertiary education, but rather to offer them either direct entry to the labour market, or the option to pursue their studies in
post-secondary non-tertiary education before entering tertiary education or the labour market (Figure B7.3 and Table B7.2).
Among these countries, Norway has recently changed its policy and most of the upper secondary vocational programmes
provide access to tertiary education from 2018. Sweden is also a special case. The country abolished certain mandatory
academic content in VET programmes and the automatic eligibility of VET students for tertiary education through the 2011
reforms. However, despite this change, students enrolled in upper secondary vocational programmes have the right to
choose, if they wish, to add more academic courses to their timetable in order to access higher education.
Interestingly, these countries have common characteristics. Young adults with upper secondary vocational attainment have
excellent employment and earnings prospects in all of them, significantly higher than those with general qualifications, but
also higher than OECD average employment rates. For example, three of these countries (Iceland, Norway and Sweden)
have the highest employment rates for young adults with an upper secondary vocational qualification, all over 90% (see
Indicator A3). Another common feature of all these countries, with the exception of Hungary, is that upper secondary VET
programmes offer their graduates opportunities to continue their education at the post-secondary non-tertiary level (ISCED 4),

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B7. HOW DO VOCATIONAL EDUCATION SYSTEMS DIFFER AROUND THE WORLD?  247
often in the form of one-year training courses that allow them to deepen their technical skills to specialise in occupations in
fields as diverse as health and welfare, agriculture, crafts, and building and construction (Figure B7.2, Table B7.2 and
(OECD/Eurostat/UNESCO Institute for Statistics, 2015[8])).
Well-established VET systems can aid in the transition to the labour market by giving young people opportunities to gain
professional experience, and by providing them with a combination of specific and general skills that will help them to evolve
professionally as their own interests and labour-market requirements change. Italy, New Zealand and Slovenia reported
examples of policies aiming to strengthen these synergies. Italy has implemented a major labour-market reform which
includes measures to support more effective transitions and support the labour market. New Zealand introduced in 2020 a
major Reform of Vocational Education legislation designed to bring together industry and educators into a single vocational
education system for developing the skills of the current and future workforce. In Slovenia, following the reform of vocational
education (2008-11), 20% of the curriculum can now be designed in co-operation with social partners, particularly local
companies. More globally, more than one-third of the 31 countries with available data – Belgium, Chile, Estonia, Finland,
France, Germany, Israel, Italy, Latvia, Korea, the Netherlands, Slovenia, Spain, and the United Kingdom – declared that their
curricula have been reviewed and improved since 2013 (often in co-operation with enterprises) to align the skills and
certification of VET systems with labour-market demands (INES ad-hoc survey on VET and (OECD, 2018[5])).
Not all countries offer students a choice between attending a post-secondary non-tertiary education programme or entering
tertiary education after they complete upper secondary vocational education. For example, post-secondary non-tertiary
programmes do not exist in about one-third of OECD and partner countries with data, preventing students in these countries
from accessing programmes that could build on their upper secondary education. This also limits their choices to entering the
labour market or continuing their studies at the tertiary level. The other 24 countries with available data do have such
programmes. They are mainly vocationally oriented: on average, 92% of all post-secondary non-tertiary students enrol in
vocational programmes (Table B7.1). However, in a few countries there are general programmes at post-secondary nontertiary level which are aimed at students who completed a vocational upper secondary programme 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. In the same vein, a large proportion of students enrolled at this level in the Czech Republic take one-year general
courses that help them prepare for university entrance. These courses are also delivered by universities
(OECD/Eurostat/UNESCO Institute for Statistics, 2015[8]).
Although post-secondary non-tertiary vocational education is designed to prepare students for entry into the labour market, it
should not lock participants out of further learning options. Thus, in half of the 24 countries with data on this level, all or most
students are enrolled in post-secondary non-tertiary vocational education that theoretically gives them the opportunity to
access tertiary education if they wish or if the requirement for accessing tertiary education is completion of upper-secondary
education. In nine other countries, a majority of students are enrolled in post-secondary non-tertiary programmes that are
theoretically designed for direct entry into the labour market by taking advantage of one or two years training courses that
allow them to deepen their technical skills. Among these countries, Germany is an interesting case. The majority of students
are enrolled in programmes that are theoretically designed for direct entry into the labour market. However, students have
eligibility to tertiary academic programmes by the given university entrance qualification obtained at upper secondary level of
education. The few remaining countries offer a more mixed profile of programmes, some of which are designed to lead to
further study and some of which do not (Figure B7.3).
Analysis of the transition between upper secondary, post-secondary non-tertiary and tertiary education shows large
differences between countries. In Hungary, for example, non-tertiary post-secondary education is a stepping stone to tertiary
education and there is in general no direct access to tertiary education for graduates of upper secondary education.
Conversely, in countries such as Ireland, Norway and Sweden, vocational programmes at the post-secondary non-tertiary
level offer no more opportunities for further study at tertiary level than those at the upper secondary level (Figure B7.2 and
Figure B7.3).

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248  B7. HOW DO VOCATIONAL EDUCATION SYSTEMS DIFFER AROUND THE WORLD?

Figure B7.3. Distribution of students enrolled in post-secondary non-tertiary vocational education by
type of vocational programme (2018)
Full- and part-time students enrolled in public and private institutions
Sufficient for level completion, with eligibility to tertiary education (ISCED 454)
Sufficient for level completion, without direct access to tertiary education (ISCED 453)

%
100
90
80
70
60
50
40
30
20

Spain (100%)

Poland (100%)

Norway (100%)

Luxembourg (100%)

Latvia (100%)

Ireland (100%)

Greece (100%)

(99%)

(93%)
Belgium

Iceland

(36%)
Czech Republic

(76%)

(95%)
EU23 average

Sweden

(92%)
OECD average

(93%)
Germany1

Austria (100%)

(84%)
New Zealand

United States (100%)

(77%)
Switzerland

Slovak Republic (100%)

Portugal (100%)

Lithuania (100%)

Hungary (100%)

(55%)
France

Finland (100%)

Estonia (100%)

0

Brazil (100%)

10

Note: Figures in parentheses refer to the share of students enrolled in post-secondary non-tertiary vocational education as a percentage of all students enrolled at this level.
1. The majority of students enrolled in ISCED 453 have eligibility to tertiary academic programmes by the given university entrance qualification obtained at upper secondary
level of education (ISCED 344).
Countries are ranked in descending order of the share of students enrolment in post-secondary non-tertiary vocational programmes sufficient for level completion, with
eligibility to tertiary education (ISCED 454).
Source: OECD (2020), Table B7.2. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2https://doi.org/10.1787/888934164218

Box B7.1. Upper secondary graduates from vocational programmes, by field of study and gender
Participating in a vocational education and training (VET) programme has both personal and societal 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[11]).
VET is an important part of upper secondary education in many OECD countries. However, certain fields of study are more
common at this level. On average across OECD countries, 33% of those graduating from upper secondary vocational
programmes in 2018 earned a qualification in the broad field of engineering, manufacturing and construction. The share
falls to 18% for business, administration and law; 17% for services; 13% for health and welfare; and 4% for information
and communication technologies (ICT). However, this pattern does not hold for every country. In Estonia, Hungary and
Iceland, 50% or more of students graduate with a specialisation in engineering, manufacturing and construction. In contrast,
business, administration and law is the most popular field in at this level for Brazil, Luxembourg and Switzerland. In Ireland,
the Netherlands, Spain and the United Kingdom, the field of health and welfare is the most popular out of the selected
fields in Figure B7.4.
The cost of VET programmes varies greatly depending on the fields of study followed by the students. For example, some
VET programmes require expensive equipment or sophisticated infrastructure to train students. This is particularly the case
for programmes in science or technology. Countries where a large share of VET students graduate with a specialisation in

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B7. HOW DO VOCATIONAL EDUCATION SYSTEMS DIFFER AROUND THE WORLD?  249
engineering, manufacturing and construction, such as Chile, Estonia, Iceland and Sweden tend to spend more per student
in vocational programmes than in general ones. The differences are also significant in countries where the field of health
and welfare is the most popular, such as Greece, the Netherlands and Spain (see Figure C1.2 and Box C1.1).
Upper secondary graduation patterns by field of study also reveal a strong gender bias. The share of women pursuing an
upper secondary vocational qualification in engineering, manufacturing and construction is low: only 13% 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
81% of graduates on average. In fact, in health and welfare, the share of female graduates exceeds 75% in all countries
except Latvia (where it is 71%) and Sweden (73%). Between these two extremes, there is more gender balance: in the
field of services, on average, 57% of graduates are women, and in business, administration and law, 64% of graduates
are women (OECD, 2019[12]).

Figure B7.4. Share of upper secondary vocational graduates, by selected field of study (2018)
Information, Communication and Technologies
Health and welfare
Services
Business, administration and law
Engineering, manufacturing and construction

%
100
90
80
70
60
50
40
30
20

Ireland (36%)

Portugal (40%)
Brazil (11%)
New Zealand (30%)
United Kingdom (44%)

Finland (72%)
Colombia (27%)
Luxembourg (62%)
Netherlands (68%)
Spain (36%)

Australia1 (49%)
Turkey (46%)
Denmark (38%)
Italy (54%)

France (39%)
OECD average (42%)
Switzerland (64%)
EU23 average (47%)

Belgium (57%)
Slovenia (71%)
Austria (68%)
Germany (46%)

Poland (52%)
Russian Federation (51%)
Slovak Republic (68%)
Latvia (39%)

Japan (22%)
Norway (49%)
Czech Republic (71%)
Greece (29%)

Lithuania (27%)
Chile (16%)
Sweden (35%)
Korea (18%)

0

Hungary (38%)
Iceland (28%)
Estonia (40%)

10

Note: Figures in parentheses refer to the share of students enrolled in upper secondary vocational education as a percentage of all students enrolled at this level.
1. Year of reference 2018.
Countries are ranked in descending order of the share of graduates in engineering, manufacturing and construction field.
Source: OECD/UIS/Eurostat (2020) See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2https://doi.org/10.1787/888934164237

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[13]). In contrast, their over-representation in health-related fields seems to mirror their
supposed aptitude for caring positions, as women make up a large share of frontline healthcare workers. In the context of
the current sanitary crisis, their exposure to infectious diseases is exacerbated, which in turn represents a high
psychological burden on women healthcare workers.

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250  B7. HOW DO VOCATIONAL EDUCATION SYSTEMS DIFFER AROUND THE WORLD?
Share of students beyond the typical enrolment age in vocational education, by education level
The proportion of students who are older than the typical enrolment age for their level of education tends to be higher in
vocational education than in general education from lower secondary to post-secondary non-tertiary levels. In 10 of the 37
countries for which data are available, less than 10% of vocational upper secondary students are over 20 years old. However,
in Australia, Denmark, Ireland and New Zealand, 70% or more are over the typical enrolment age, i.e. older than 20. Overall,
the average age of enrolment is 21 years old for vocational upper secondary programmes and 17 years old for general
programmes. The average age of enrolment in upper secondary vocational programmes is 25-29 years old in Denmark,
Finland, Iceland and Spain while in Australia, Ireland and New Zealand it is over 30 years. In contrast, the country with the
highest average age of enrolment in general education is Sweden, where it is 21 years of age (Table B7.2 and Figure B7.5).

Figure B7.5. Share of students beyond the typical enrolment age in vocational education, by education
level (2018)
Full- and part-time students enrolled in public and private institutions
% of 16 years and older enrolled in lower secondary vocational education
% of 20 years and older enrolled in upper secondary vocational education
% of 25 years and older enrolled in post-secondary non-tertiary vocational education

%
100
90
80
70
60
50
40
30
20

Israel

Korea

Colombia

Poland

Chile

Mexico

Indonesia

Italy2

Turkey

Slovak Republic

France

Russian Federation

Austria

Latvia

Czech Republic

Portugal

Hungary

Lithuania

Costa Rica

Switzerland

Brazil

Slovenia

Norway

Luxembourg

EU23 average

OECD average

Estonia

Sweden

Germany

Saudi Arabia

United Kingdom 1

Spain

Netherlands

Finland

Iceland

New Zealand

Ireland

Denmark

0

Australia

10

Note: The absence of a symbol for a level of education means that there are no VET programmes at that level in the country concerned.
1. Short-cycle tertiary programmes include a small number of bachelor's professional programmes.
2. Upper secondary vocational programmes include post-secondary non-tertiary programmes.
Countries are ranked in descending order of the share of students beyond the typical enrolment age in upper secondary vocational education.
Source: OECD (2020), Table B7.1. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2https://doi.org/10.1787/888934164256

There are two main reasons that might explain the higher average age of students in vocational programmes. First, vocational
systems are often flexible enough to allow students who left the education system early to re-enter later on. Thus, VET
systems from lower secondary to post-secondary non-tertiary education often have programmes designed to offer a second
chance for some students to acquire basic skills and for others to re-enter a learning environment, developing skills that will
subsequently increase their employability. This trend is particularly pronounced in lower secondary education where, except
in Costa Rica and, to a lesser extent, Greece and the Netherlands, the majority of students enrolled in lower secondary VET
programmes are over 16 years old, which is over the typical enrolment age at this level (Table B7.1 and Figure B7.5). VET
systems in these countries are flexible and able to satisfy different needs at different stages of people’s lives, whether they
are preparing for a first career, seeking additional skills to assist in their work or catching up on educational attainment
(OECD/Eurostat/UNESCO Institute for Statistics, 2015[8]).

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B7. HOW DO VOCATIONAL EDUCATION SYSTEMS DIFFER AROUND THE WORLD?  251
A second reason for these differences is that VET programmes also tend to cater for students with greater difficulties who
also graduate from earlier levels of education at a later age. Moreover, the completion rate of upper secondary education
(within the theoretical duration of the programme) is lower among students enrolled in vocational education (62%) than among
those in general education (76%). In this context, male students and/or those enrolled in upper secondary vocational
programmes that do not give direct access to tertiary education are less likely to complete upper secondary education, even
three years after the typical duration, than others (see Indicator B3 and Box B7.1).

Share of women enrolled in vocational education, by education level
Women have historically been under-represented in certain fields of study at upper secondary level such as engineering,
manufacturing and construction or ICT, and continue to be so despite undeniable political efforts to reduce gender gaps
(Box B7.1). Women's under-representation is not just limited to particular fields of study at upper secondary level; they are
also clearly under-represented in vocational education overall. This may be a cause for concern in view of the Sustainable
Development Goal (SDG) of ensuring equal access for all women and men to high-quality and affordable technical and
vocational education by 2030 (see SDG chapter). On average across OECD countries, women make up 45% of enrolment
into upper secondary vocational programmes. Only in about one-quarter of the 40 countries for which data are available is
the proportion of women above 50%. There is, however, significant variations among countries: the share of women ranges
from less than 37% in Germany, Greece, Iceland and Lithuania to over 55% in Brazil, Costa Rica, Ireland and New Zealand
(Table B7.1).
The pattern changes when focusing on post-secondary non-tertiary education. At that level, more than 55% of students are
women. They account for more than half of enrolments in most of the countries for which data are available. The only
exceptions are the Czech Republic, Ireland, Luxembourg, Portugal and the Russian Federation. The same applies to the
short-cycle tertiary level, but the trend towards the over-representation of women is less pronounced. On average in OECD
countries, women account for 52% of all students enrolled at this level and make up more than 50% in about two-thirds of
countries for which data are available. However, there are wide variations between countries, with the share of female
students ranging from less than 30% in Italy and Norway to 65% or more in Brazil, Germany, Poland and the Slovak Republic
(Table B7.1). The proportion of women in VET programmes is closely related to differences between countries in the
predominant fields of study at this level (Box B7.1). The number of students enrolled in the different levels of education must
also be taken into account in the analysis of these results. For example, the proportion of women is very high in short-cycle
tertiary programmes in Germany, but the level itself only enrols a minority of students.
There are two main reasons for the under-representation of women in upper secondary vocational education but not in postsecondary education. First, women have a higher completion rate for upper secondary vocational education than men and
therefore are more likely to continue their studies in post-secondary education (Indicator B3). Second, women are more
strongly represented in certain broad fields of study such as health and social welfare, and business, administration and law,
fields which are very prevalent in short-cycle tertiary vocational education at tertiary level, but especially in post-secondary
non-tertiary education (OECD, 2019[12]). In contrast, the share of women in short-cycle tertiary education tends to be lower in
countries where science, technology, engineering and mathematics (STEM) fields are prominent at this level (Indicator B4).

School-based and combined school- and work-based vocational programmes
The content of VET programmes and the way they are organised and delivered in upper secondary education varies
considerably from country to country. In general, VET programmes are divided into school-based programmes and combined
school- and work-based programmes, and countries often have VET systems that offer several types of programmes in
parallel. In school-based programmes, at least 75% of the curriculum is presented in the school environment. This includes
special training centres run by public or private authorities, or enterprise-based special training centres if they qualify as
educational institutions. In combined school- and work-based programmes, at least 10%, but less than 75%, of the curriculum
is presented in the school environment or through distance learning, with the remainder is organised as work-based learning
in enterprises. Such programmes are in some national context called “apprenticeships”. These programmes can be organised
in conjunction with education authorities or institutions. They include apprenticeship programmes that involve concurrent
school-based and work-based training (e.g. in Denmark and Norway), and programmes that involve alternating periods of
attendance at educational institutions and participation in work-based training, as in the dual systems in Austria, Germany
and Switzerland (see Definitions section and Table B7.3).

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252  B7. HOW DO VOCATIONAL EDUCATION SYSTEMS DIFFER AROUND THE WORLD?
Through work-based learning, students acquire the skills that are valued in the workplace. Work-based learning is also a way
to develop public-private partnerships and to involve social partners and employers in the development of VET programmes,
often including the definition of curricular frameworks (OECD, 2018[7]). The combination of learning in school and in the work
environment through combined school- and work-based programmes offers numerous advantages. Learners get an education
that combines practical and theoretical learning, and gain soft skills from engaging in actual workplaces. Employers benefit
because students’ education can be tailored to workplace needs and students become familiar with firm-specific procedures.
Combined school- and work-based programmes therefore reduce skill mismatches and provide hiring opportunities for firms,
which also provides a smooth transition into working life for students (see Indicator A3 and Box B7.2).
For all these reasons, apprenticeships and other forms of work-based learning have received much attention from policy
makers, and about two-thirds of countries with available data have implemented recent reforms to strengthen the quality of
their combined school- and work-based programmes. The nature of these reforms differ across countries. Some have
strengthened their apprenticeship training and other forms of work-based learning. For some countries (Australia, Belgium,
Chile, Finland, Ireland, Israel, Italy, Korea, Norway and the United Kingdom) this meant creating new places in apprenticeship
programmes. For others, sometimes the same countries (e.g. Australia, Belgium, Canada, Hungary and Korea), additional
attention has focused on public support for students to access VET and on the provision of tax reductions to enterprises taking
part (OECD, 2018[7]).
The governance of VET programs has also been an important focus of recent reforms. In Canada, for instance, Federal,
provincial and territorial governments in most jurisdictions reconfirmed their commitment to harmonise apprenticeship training
across regions for key trades. Finally, some countries have recently reformed their combined school- and work-based
programmes in greater depth and created a new model of apprenticeship, as in the Flemish Community of Belgium, Estonia,
France, Latvia, Mexico, the Slovak Republic, Slovenia and Spain. In France, for example, the 2018 law for the "freedom to
choose one's professional future" reinforces the weight of professional branches in the governance of apprenticeship. It also
strengthens apprenticeship training opportunities by improving financial assistance to students and companies, increasing
the number of apprenticeship training centres and developing bridges between school education and apprenticeship (INES
ad-hoc survey and (OECD, 2018[7]).
Although programmes combining learning in both the school and work environment provide numerous labour-market
advantages and received a surge of policy attention over the last decade, about one-third of all students in upper secondary
vocational education are enrolled in these programmes on average across OECD countries. The rest are enrolled in schoolbased programmes. Overall, school-based VET programmes account for more than 90% of students in 14 out of the
35 countries for which data are available. There are only school-based VET programmes in countries as diverse as Brazil,
Costa Rica, the Czech Republic, Greece, Italy, Japan, Korea, Lithuania and Mexico. The rest of these countries have a largely
school-based system alongside some apprenticeships. Even where school-based programmes predominate, however, that
does not mean that vocational education does not have a work-based component. For instance, vocational school-based
programmes in France have a work-based component that accounts for 17-23% of the programmes’ duration (Table B7.3 and
Figure B7.6). Some countries have well-developed combined school- and work-based upper secondary VET systems,
although the form that the work-based component may take differs between them. Overall, more than 44% of upper secondary
VET students are enrolled in combined school- and work-based programmes in 12 out of the 35 countries with available data.
Of these countries, the proportion of students enrolled in these programmes exceeds 89% in Denmark, Germany, Hungary,
Ireland, Latvia, the Netherlands and Switzerland. Interestingly, among the 26 countries with at least some students enrolled
in combined school- and work-based programmes, the work-based component is mandatory in all of them except Latvia,
where it depends on training contracts among the VET schools and enterprises. Combined school- and work-based
programmes can also differ in cost models. For instance, only the French Community of Belgium, Chile, Estonia,
the Netherlands, Portugal, Slovenia, Spain and Sweden declared that “some” or “most” students enrolled in these
programmes do not receive remuneration on the work-based component, which is common in all other countries (Table B7.3
and Figure B7.6).
There are other major differences among combined school- and work-based programmes. First, combined school- and workbased programmes can be quite different in terms of their practical arrangements. Work and study periods alternate
continually over the course of the programmes, with varying proportions of study and work across countries. For example,
the work-based component is less than 30% of the programme’s duration in Estonia and Israel, while it is 80% or more in
Finland and Switzerland. In some VET systems, school-based study and work-based study may be consecutive instead of
parallel. The Norwegian 2+2 Model, for instance, divides a four-year vocational training course into a two-year school-based
learning period and a two-year work-based learning period (Table B7.3 and (OECD, 2016[14])).

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B7. HOW DO VOCATIONAL EDUCATION SYSTEMS DIFFER AROUND THE WORLD?  253

Figure B7.6. Distribution of upper secondary vocational students by type of vocational programme (2018)
Full- and part-time students enrolled in public and private institutions
Combined school- and work-based programmes
School-based programmes

%
100
90
80
70
60
50
40
30
20
10

Latvia

Ireland 3

Hungary 3

Denmark 3

Switzerland

Netherlands

Turkey4

Germany

Iceland

Norway

United Kingdom

Austria

EU23 average 3

OECD average3

Slovenia4

Australia3

France

Poland

Luxembourg 3

Finland

Portugal 4

Chile3

Slovak Republic3

Israel

Estonia

Belgium2

Spain

Sweden

Brazil1

Mexico1

Lithuania1

Korea 1

Japan1

Italy1

Greece1

Czech Republic 1

Costa Rica1

0

Note: Figures in parentheses refer to the most typical duration of the work-based component as a percentage of the total programme duration for combined school- and
work-based programmes. For example, in Germany, more than 98% of students in combined school- and work-based programmes are enrolled in a programme where the
duration of the work component accounts for about 60% of the total programme duration. See Table B7.3 for more information.
1. Data on typical duration of the work-based component are not applicable because the category does not apply.
2. The most typical duration of the work-based component is at least 46% for the Flemish Community of Belgium and 60% for the French Community of Belgium.
3. Data on the most typical duration of the work-based component are missing.
4. The share of students enrolled in combined school- and work-based programmes as a percentage of all student enrolled in upper secondary vocational education is
estimated based on the results of the INES ad-hoc survey on VET.
Countries are ranked in descending order of the share of students enrolled in school-based vocational programmes.
Source: OECD (2020), Table B7.3. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2https://doi.org/10.1787/888934164275

Second, the duration of upper secondary VET programmes also varies widely across countries. For example, in Germany,
more than 95% of students in upper secondary combined school- and work-based are enrolled programmes which last three
years, with the work component accounting for about 60% of the total duration of the programme. In contrast, the main upper
secondary VET programme in Ireland lasts only one year, which means that number of months worked is much smaller than
in Germany. This is an important parameter to take into account when analysing the results (Table B7.3 and Figure B7.6).

Box B7.2. Vocational education during the COVID-19 lockdown
The unprecedented health crisis that we are experiencing, linked to the rapid spread of COVID-19 throughout the world,
has strong consequences for the economy and consequently on education systems, which are themselves vectors of
economic growth. Schools have had to close for several months in most countries, resulting in the loss of about 14 weeks
(though it may include school and public holidays) in the first half of 2020 on average across countries (see Box D1.2).
Firms also suffered during this period, as the crisis led to an almost general lockdown of companies and a slowdown in
economic activity. Governments have reacted to ensure pedagogical continuity over this period, and distance learning
has taken over rather effectively. In many cases, this had to be done immediately and without specific preparation, which
also challenged teachers to use new techniques and methods. However, it is not necessarily the most appropriate

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254  B7. HOW DO VOCATIONAL EDUCATION SYSTEMS DIFFER AROUND THE WORLD?
response for the most disadvantaged students who need more individualised support, nor for the less well-off families
who do not necessarily have sufficient equipment or material comfort to provide their children with the conditions they
need to follow their courses and not drop out. In contrast to the more academic streams which have been able to offer
more flexible learning options and, therefore, distance learning, vocational education and training (VET) programmes face
challenges in the search for new forms of e-learning that will allow their students to continue to develop their skills.
VET programmes suffer from a double disadvantage compared to general ones. First, whether they are school-based or
combined school- and work-based programmes, practical teaching forms an important part of their curricula, which is
difficult to do at a distance. Some fields such as agriculture, health, engineering, construction or crafts, require specific
equipment, learning in small groups for practical demonstrations, and careful attention from teachers to ensure that the
actions performed by the students are the right ones. This type of learning does not correspond to what distance education
offers, or does so only in a limited way, which raises questions about educational loss. Another problem faced by VET
education, particularly work-study programmes, is the size of the work-based component, which accounts for more than
60% of total learning time in some countries (Table B7.3). The consequences of the lockdown for these programmes are
therefore serious, even though they are normally the most sought-after by companies and offer better employability. The
situation is less clear today. For example, apprentices who were placed in companies and sectors that have come to a
standstill as a result of border closures and the confinement of populations, such as catering or tourism, have largely
stopped their working activities. With an economic crisis looming, it is also an open question whether companies will wish
to continue to take on apprentices when their priorities will be to relaunch their businesses.
This situation raises doubts about what will happen in the coming months, but some initiatives have already been
announced and governments seem to have grasped how much is at stake. For example, according to the OECD/Harvard
study published in June 2020 (OECD/Harvard, 2020[15]), in 70% of countries for which data are available, plans to reopen
schools generally include provisions and remedial measures, particularly for students in vocationally oriented
programmes. The measures do not stop at the early reopening of schools for VET students; in many countries there is a
genuine understanding that apprenticeship streams should not be the first victims of the current situation. For example,
according to a policy brief produced by the VET team of the OECD Centre for Skills (OECD, 2020[16]), many measures
have already been taken in OECD countries. These include:


increasing the use of online and virtual platforms more appropriate to VET to ensure continuity of learning



financing training breaks or extensions to avoid breaks in learning resulting in fees, repayments or other penalties
for both learners and providers



providing wage support for apprentice retention to allow apprentices to maintain contact with employers and if
possible continue working through remote working or virtual meetings



leveraging links between work-based and school-based VET to provide alternative school-based VET in cases
where upper secondary VET students are unable to secure an apprenticeship, including work-based components



offering flexible skills assessment and awarding of qualifications as, in many sectors, particularly healthcare, a
direct route to qualification may need to be established quickly in response to the COVID-19 crisis



informing, engaging and communicating with learners, providers and social partners about new guidance on the
delivery of assessment, or to ensure apprentices are informed of changes to regulations and practices



investing in VET to mitigate future skills shortages and minimise the shock of the crisis.

All these actions confirm the importance that decision makers attach to VET, and the coming months will be crucial in
assessing the effectiveness of these measures.

Definitions
General education programmes are designed to develop learners’ general knowledge, skills and competencies, as well as
literacy and numeracy skills, often to prepare participants for more advanced education programmes at the same or a higher
ISCED level and to lay the foundation for lifelong learning. These programmes are typically school- or college-based. General
education includes education programmes that are designed to prepare participants for entry into vocational education but
do not prepare for employment in a particular occupation, trade or class of occupations or trades, nor lead directly to a labour
market-relevant qualification.

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B7. HOW DO VOCATIONAL EDUCATION SYSTEMS DIFFER AROUND THE WORLD?  255
Vocational education programmes are designed for learners to acquire the knowledge, skills and competencies specific to
a particular occupation, trade, or class of occupations or trades. Such programmes may have work-based components
(e.g. apprenticeships or 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.
Both general and vocational programmes can contain some courses or subjects that are common to both programmes. For
example, a vocational programme may contain courses on mathematics or the national language which are also taught to
students in general programmes. When reporting data on certain statistical units, in particular educational personnel, by
programme orientation it is the classification of the programme that determines the orientation and not the subject being
studied or taught.
The data in this chapter cover formal education programmes that represent at least the equivalent of one semester (or onehalf of a school/academic year) of full-time study and take place entirely in educational institutions or are delivered as a
combined school- and work-based programme. At the upper secondary level and the non-tertiary post-secondary level,
vocational programmes are further divided into school-based programmes and combined school- and work-based
programmes on the basis of the amount of training that is provided in school as opposed to the workplace.
In school-based programmes instruction takes place (either partly or exclusively) in educational institutions. These include
special training centres for vocational education run by public or private authorities or enterprise-based special training centres
if these qualify as educational institutions. These programmes can have an on-the-job training component, i.e. a component
of some practical experience at the workplace. Programmes should be classified as school-based if at least 75% of the
curriculum is presented in the school environment (covering the whole educational programme) or through distance education.
Programmes are classified as combined school- and work-based programmes if less than 75% of the curriculum is
presented in the school environment or through distance education. The 75% cut-off point should be regarded as a general
guideline that may need to be operationalised differently across countries. These programmes include:
- apprenticeship programmes organised in conjunction with educational authorities or educational institutions that involve
concurrent school-based and work-based training
- dual-system programmes organised in conjunction with educational authorities or educational institutions that involve
alternating intervals of attendance at educational institutions and participation in work-based training (programmes of
training in alternation, sometimes referred to as sandwich programmes).
Note that programmes of dual-system apprenticeships are usually considered part of upper secondary (ISCED 3) education,
but other programmes under this heading may be classifiable not just as ISCED 3 but also ISCED levels 4-6.
The amount of instruction provided in school should be counted over the whole duration of the programme. An institution
providing school- and work-based programmes is classified as either public or private according only to the school-based
component.

Source
Data refer to the academic year 2017/18 and are based on the UNESCO-UIS/OECD/EUROSTAT data collection on education
statistics administered by the OECD in 2019. Data for some countries may have a different reference year. For details, see
Annex 3 at https://doi.org/10.1787/69096873-en.
Data on main characteristics of combined school- and work-based programmes in upper secondary education (Table B7.3)
are based on a special survey on VET administered by the OECD in 2020 and on UNESCO-UIS/OECD/EUROSTAT
ISCED 2011 mappings at http://uis.unesco.org/en/isced-mappings.
Data from Argentina, the People’s Republic of China, India, Indonesia, Saudi Arabia and South Africa are from the UNESCO
Institute of Statistics (UIS).

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256  B7. HOW DO VOCATIONAL EDUCATION SYSTEMS DIFFER AROUND THE WORLD?

References

Cedefop (2011), “The benefits of vocational education and training”, Research Paper, No. 10, European Centre for
the Development of Vocational Training, Publication Office of the European Union, Luxembourg,
http://dx.doi.org/10.2801/43027.

[11]

OECD (2020), “VET in a time of crisis: Building foundations for resilient vocational education and training
systems”, Policy Brief, OECD, Paris, https://read.oecd-ilibrary.org/view/?ref=132_132718fdwmrqsgmy&title=VET-in-a-time-of-crisis-Building-foundations-for-resilient-vocational-education-and-trainingsystems.

[16]

OECD (2020), Education at a Glance Database, https://stats.oecd.org/ (accessed on 6 July 2018).

[12]

OECD (2019), Education at a Glance 2019: OECD Indicators, OECD Publishing, Paris,
https://doi.org/10.1787/f8d7880d-en.

[10]

OECD (2019), OECD Employment Outlook 2019: The Future of Work, OECD Publishing, Paris,
https://doi.org/10.1787/9ee00155-en.

[9]

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 Policy Outlook 2018: Putting Student Learning at the Centre, OECD Publishing, Paris,
http://dx.doi.org/10.1787/9789264301528-en.

[5]

OECD (2018), Seven Questions about Apprenticeships: Answers from International Experience, OECD Reviews of
Vocational Education and Training, OECD Publishing, Paris, https://dx.doi.org/10.1787/9789264306486-en.

[7]

OECD (2016), Education at a Glance 2016 : OECD Indicators, OECD Publishing, Paris,
http://dx.doi.org/10.1787/eag-2016-en.

[14]

OECD (2015), Education Policy Outlook 2015: Making Reforms Happen, OECD Publishing, Paris,
https://dx.doi.org/10.1787/9789264225442-en.

[2]

OECD (2015), The ABC of Gender Equality in Education: Aptitude, Behaviour, Confidence, PISA, OECD
Publishing, https://dx.doi.org/10.1787/9789264229945-en.

[13]

OECD (2014), Skills beyond School: Synthesis Report, OECD Reviews of Vocational Education and Training,
OECD Publishing, Paris, http//dx.doi.org/10.1787/9789264214682-en.

[4]

OECD (2011), Learning for Jobs: Pointers for Policy Development, OECD Reviews of Vocational Education and
Training, OECD Publishing, Paris, http://www.oecd.org/education/skills-beyondschool/LearningForJobsPointersfor%20PolicyDevelopment.pdf.

[6]

OECD (2010), Learning for Jobs, OECD Reviews of Vocational Education and Training, OECD Publishing, Paris,
http://dx.doi.org/10.1787/9789264087460-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,
https://dx.doi.org/10.1787/9789264228368-en.

[8]

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B7. HOW DO VOCATIONAL EDUCATION SYSTEMS DIFFER AROUND THE WORLD?  257
OECD/Harvard (2020), Schooling disrupted, schooling rethought - How the Covid-19 pandemic is changing
education, https://read.oecd-ilibrary.org/view/?ref=133_133390-1rtuknc0hi&title=Schooling-disruptedschooling-rethought-How-the-Covid-19-pandemic-is-changing-education.

[15]

Indicator B7 Tables
Table B7.1

Profile of students enrolled in vocational education from lower secondary to short-cycle tertiary, by type
of programme, age and gender (2018)

Table B7.2

Pathways between upper secondary or post-secondary non-tertiary education and higher levels of
education, by type of programme and programme orientation (2018)

Table B7.3

Main characteristics of combined school- and work-based programmes in upper secondary education
(2018)

Cut-off date for the data: 19 July 2020. Any updates on data can be found on line at http://dx.doi.org/10.1787/eag-dataen. More breakdowns can also be found at http://stats.oecd.org/, Education at a Glance Database.
StatLink: https://doi.org/10.1787/888934164104

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258  B7. HOW DO VOCATIONAL EDUCATION SYSTEMS DIFFER AROUND THE WORLD?
Table B7.1. Profile of students enrolled in vocational education from lower secondary to short-cycle tertiary, by type of
programme, age and gender (2018)
Full- and part-time students enrolled in public and private institutions

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B7. HOW DO VOCATIONAL EDUCATION SYSTEMS DIFFER AROUND THE WORLD?  259

1. Upper secondary vocational programmes include post-secondary non-tertiary programmes.
2. Short-cycle tertiary programmes include a small number of bachelor's professional programmes.
Source: OECD/UIS/Eurostat (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2https://doi.org/10.1787/888934164123

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260  B7. HOW DO VOCATIONAL EDUCATION SYSTEMS DIFFER AROUND THE WORLD?
Table B7.2. Pathways between upper secondary or post-secondary non-tertiary education and higher levels of education, by
type of programme and programme orientation (2018)
Full- and part-time students enrolled in public and private institutions

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B7. HOW DO VOCATIONAL EDUCATION SYSTEMS DIFFER AROUND THE WORLD?  261

1. ISCED 7 in column 12 includes only Master's long first degree programmes.
Source: OECD/UIS/Eurostat (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2https://doi.org/10.1787/888934164142

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262  B7. HOW DO VOCATIONAL EDUCATION SYSTEMS DIFFER AROUND THE WORLD?
Table B7.3. Main characteristics of combined school- and work-based programmes in upper secondary education (2018)
Full- and part-time students enrolled in public and private institutions

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B7. HOW DO VOCATIONAL EDUCATION SYSTEMS DIFFER AROUND THE WORLD?  263

Note: This table includes only combined school- and work-based programmes. In these programmes, at least 10%, but less than 75%, of the curriculum is presented in the
school environment or through distance learning, with the remainder organised as work-based learning.
1. ISCED 351 includes all vocational programmes insufficient for level completion. ISCED 352 includes all vocational programmes sufficient for partial level completion,
without access to tertiary education. ISCED 353 includes all vocational programmes sufficient for level completion, without direct access to tertiary education. ISCED 354
includes all vocational programmes sufficient for level completion, with direct access to tertiary education. See Definitions section for more information.
2. The share of students enrolled in combined school- and work-based programmes as a percentage of all student enrolled in vocational education is estimated based on
the results of the INES ad-hoc survey on VET.
3. Additional combined school- and work-based programmes exist but they represent only a small proportion of total enrolment in combined school- and work-based programmes.
4. The share of students enrolled in combined school- and work-based programmes as a percentage of all student enrolled in vocational education is for public institutions only.
Source: 2020 INES ad-hoc survey on vocational education and training (VET). See Source section for more information and Annex 3 for notes
(https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2https://doi.org/10.1787/888934164161

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| 265

Chapter C. Financial
resources invested in
education

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266  CHAPTER C. INTRODUCTION

Introduction
Educational expenditure indicators help to show what, how and where financial resources are directed to education. Every
year, governments, private companies, students and their families make decisions about the financial resources invested in
education. These investments are made with the well-established idea that expenditure on education enhances labour
productivity by improving the skills of the workforce (Mallick, Das and Pradhan, 2016[1]) which might affect economic growth
and social development. Therefore, analysing various aspects of educational finance helps clarify the efforts made by
countries in education as well as its possible impact on future national economic and social perspectives.

The framework for international educational finance indicators
At the national level, educational institutions are the most common defining unit of analysis for analysing expenditure on
education. This approach reflects the traditional interest in knowing how much schools, colleges and universities cost, and
how much of that is paid by the government or by students, for instance. However, this does not take into account that
educational systems around the world might spend their resources differently. For instance, the goods and services provided
by educational institutions in one country may be provided outside educational institutions in another. Another example arises
when comparing the educational goods and services associated with educational institutions. There are some goods and
services they provide that are not associated with education or instruction, so considering them might affect comparability
across countries. Finally, educational systems are funded differently; in some countries public sources might be more relevant,
in others private sources might be an important source of funding. Therefore, a framework for international educational
expenditure is needed to make comparisons across countries.
The framework for international educational expenditure is built around three dimensions:


The location of service providers (within or outside of educational institutions). 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 covers student living costs and the cost of
student transport not provided by educational institutions.



The type of goods and services provided or purchased (core or peripheral goods and services). 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 and housing – 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.
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.



The source of funds that finance the provision or purchase of these goods and services (from public, private
and international sources). Considering 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. Public expenditure
refers to spending by public authorities (central, regional and local governments). Private expenditure refers to

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CHAPTER C. INTRODUCTION  267
expenditure by households and other private entities. International funds consist of funds from public multilateral
organisations for development aid to education. These sources of funds can be analysed from the perspective of
either the initial or the final payer, depending on when the transaction is made. The initial source of funds is the
original source of the funds before transfers have taken place, while the final source of funds is after transfers have
taken place. Public transfers of funds to private entities fall into two distinct categories: public subsidies to households
(e.g. scholarships and grants), and public subsidies to other private entities (e.g. subsidies to private companies for
the provision of training at the workplace as part of combined school and work-based programmes, including
apprenticeship programmes). Other type of transactions are the intergovernmental transfers of funds.

International classification of educational expenditure in this chapter

Classification of educational expenditure
According to the international framework for educational expenditure presented above, educational expenditure in this chapter
is also classified into three dimensions:


The first dimension – represented by the horizontal axis in the diagram below – relates to the location where spending
occurs (within or outside educational institutions).



The second dimension – represented by the vertical axis in the diagram below – classifies the type of goods and
services that are purchased (core or peripheral goods and services).

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268  CHAPTER C. INTRODUCTION


The third dimension – represented by the colours in the diagram below – distinguishes the sources from which funding
originates. These include the funds from the public sector and international agencies (indicated by light blue), and
the private funds such as funds from households and other private entities (indicated by medium blue). Where private
expenditure on education is subsidised by public funds, this is indicated by grey cells. The uncoloured cells indicate
the parts of the framework that are excluded from the coverage of the finance indicators in Education at a Glance.

Accounting principle
In keeping with the system used by many countries to record government expenditures and revenues, educational
expenditure data are compiled on a cash accounting rather than an accrual accounting basis. That is to say that expenditure
(both capital and current) is recorded in the year in which the payments occurred. This means in particular that:


Capital acquisitions are counted fully in the year in which the expenditure occurs.



Depreciation of capital assets is not recorded as expenditure, although expenditure on repairs and maintenance is
recorded in the year it occurs. This can result in sharp fluctuations in expenditure from year to year owing to the onset
or completion of school building projects which, by their nature, are sporadic.



Expenditure on student loans is recorded as the gross loan outlay in the year in which the loans are made, without
subtracting repayments or interest payments from existing borrowers.

A notable exception to the cash accounting rules is the treatment of the retirement costs of educational personnel in situations
where there are no (or only partial) ongoing employer contributions towards the future retirement benefits of the personnel.
In these cases, countries are asked to impute these expenditures in order to arrive at a more internationally comparable cost
of employing the personnel.

International educational finance indicators
This chapter provides a comprehensive and comparative analysis on education expenditure across OECD and partner
countries, focusing on five aspects of educational spending:


Financial resources invested in educational institutions, relative to the number of students (Indicator C1), and relative
to national wealth (Indicator C2).



The source of funds devoted to educational institutions (Indicator C3).



Total public resources invested in education, both inside and outside educational institutions, relative to total
government spending (Indicator C4).



Students' costs and the financial support for tertiary studies (Indicator C5).



The distribution of educational expenditure across resource categories (Indicator C6).

Reference

Mallick, L., P. Das and K. Pradhan (2016), “Impact of educational expenditure on economic growth in major Asian
countries: Evidence from econometric analysis”, Theoretical and Applied Economics, Vol. XXIII/2, pp. 173-186.

[1]

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270  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 USD 11 200 per student on primary to tertiary educational institutions. This
represents about USD 10 000 per student at primary, secondary and post-secondary non-tertiary level, and
USD 16 300 at tertiary level.
Excluding activities peripheral to instruction (research and development and ancillary services such as student
welfare services), OECD countries spend an average of USD 10 000 per student per year from primary to tertiary
education.
The orientation of secondary school programmes influences expenditure on educational institutions per student
in most countries. On average, across the 27 OECD countries with available data, the expenditure per student in
a vocational programme was almost USD 1 500 more than in a general programme in 2017.

Figure C1.1. Total expenditure on educational institutions per full-time equivalent student, by source
of funds (2017)
From primary to tertiary education, in equivalent USD converted using PPPs, direct expenditure within educational
institutions (final source of funds)

Equivalent USD
(in thousands)
25

Private expenditure on all educational institutions
Public expenditure on all educational institutions
Public expenditure on public institutions

20
15
10

0

Luxembourg
United States
Norway
Austria
Sweden
Canada1
Belgium
United Kingdom
Iceland
Netherlands
Germany
Denmark
Australia
France
Korea
Japan
Finland
EU23 average
OECD average
New Zealand
Ireland
Italy
Portugal
Spain
Slovenia
Israel
Estonia
Czech Republic
Poland
Hungary
Slovak Republic
Latvia
Lithuania
Chile
Russian Federation
Turkey
Colombia2
Mexico
Argentina3
Brazil3
Costa Rica2
Greece3
Switzerland

5

Note: International expenditure is aggregated with public expenditure for display purposes.
1. Primary education includes pre-primary programmes.
2. Year of reference 2018.
3. Data only available for government expenditure on public educational institutions.
Countries are ranked in descending order of total expenditure on educational institutions per full-time equivalent student.
Source: OECD/UIS/Eurostat (2020), Table C1.5 and C1.6 (web tables). See Source section for more information and Annex 3 for notes
(https://doi.org/10.1787/69096873-en).
Statlink2 https://doi.org/10.1787/888934164370

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C1. HOW MUCH IS SPENT PER STUDENT ON EDUCATIONAL INSTITUTIONS?  271

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 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.
This indicator provides an assessment of the investment in each student. Expenditure per student on educational
institutions is influenced by teachers’ salaries (see Indicator D3), pension systems, instructional and teaching hours (see
Indicators 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 perstudent expenditure. Ancillary services and research and development (R&D) activities also influence the level of
expenditure per student.
In general, 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
on public institutions amounts to just over USD 11 000 per student from primary to tertiary level, compared to
USD 11 200 in private ones.



Public expenditure on public institutions averaged about USD 10 100 per student from primary to tertiary
education across OECD countries. The public expenditure per student in primary, secondary and post-secondary
non-tertiary programmes was almost USD 3 800 lower than at the tertiary level.



From 2012 to 2017, expenditure on non-tertiary educational institutions grew at a rate of 1.6% a year on average
across OECD countries, while the number of students remained fairly stable. This resulted in an average annual
growth rate of 1.4% in expenditure per student over this period.



On average, OECD countries spent the equivalent of 23% of gross domestic product (GDP) per capita per student
on primary, secondary and post-secondary non-tertiary educational institutions in 2017. The figure is much higher
at tertiary level, where countries spent, on average, 36% of GDP per capita on funding each short-cycle tertiary,
bachelor’s, master’s and doctoral student.

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272  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 from primary to tertiary level provides an assessment of the
investment made in each student. In 2017, the average annual spending per student from primary to tertiary education in
OECD countries as a whole was USD 11 200. But this average masks a broad range of figures across OECD and partner
countries. Annual spending per student at these levels ranged from around USD 3 300 in Mexico, to more than USD 16 000
in Austria, Norway and the United States, and to more than USD 23 000 in Luxembourg (Table C1.1 and Figure C1.1). The
drivers of expenditure per student vary across countries and by level of education: the countries with the highest expenditure
per student enrolled in primary through tertiary education (e.g. Austria, Luxembourg and the United States) are also among
those that tend to pay their teachers at secondary level the most (see Indicator D3), whereas Mexico has one of the highest
ratios of students to teaching staff (see Indicator D2).
The way resources are allocated across the different levels of education varies widely from level to level and largely reflects
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. OECD countries as a whole spend on average around USD 9 100
per student at the primary level, and USD 10 500 per student at secondary level. At secondary level, and particularly at upper
secondary, the level of expenditure is strongly influenced by the programme orientation. Vocational education and training
(VET) programmes, which may require specific equipment and infrastructure, typically cost more per student than general
ones. The size of the work-based component of VET programmes also influences their cost through expenditure on training
and wages (Box C1.1).

Box C1.1. The cost of vocational education and training
Vocational education and training (VET) programmes form an important part of the curriculum in OECD countries. Their structure
varies across countries (see Indicator B7), but in general, they are two or three year programmes (Kuczera, 2017[1]) that develop
skills targeted at specific trades and occupations, and which can take place from lower secondary to tertiary level.
In most OECD countries, expenditure per student at upper secondary level varies according to programme orientation. In
the 28 countries for which data are available, VET programmes are often more expensive than general educational
programmes across OECD countries: expenditure per student in upper secondary vocational programmes in 2017 was,
on average, USD 1 500 higher than in general programmes (Figure C1.2).
Various factors such as the size or structure of VET systems, the programmes offered, and also recent investments to
upgrade the programmes, can influence the cost of vocational programmes:


The share of students enrolled: countries with a smaller share of students enrolled in vocational programmes
(see Figure B7.2a in Indicator B7) tend to spend more per student in VET programmes than on general
programmes. In contrast, in Finland and Slovenia, where more than 70% of students are in VET programmes,
these programmes are less expensive than general ones (Figure C1.2).



The structure of the programmes: VET programmes with work-based components require additional
expenditure related to training in the workplace. This could be direct expenditure by private companies or the
private sector could be subsidised by the government. Countries where all or most VET students are enrolled in
school-based programmes, such as Lithuania, tend to show small differences in expenditure per student between
VET and general programmes. But in Iceland and Germany, where more than half of upper secondary VET
students are enrolled in combined school- and work-based programmes, the differences are larger (Figure C1.2
and Figure B7.6 in Indicator B7).



The field of study: some VET programmes require expensive equipment or sophisticated infrastructure to train
students (Hoeckel, 2008[2]). This is particularly the case for programmes in science or technology. Countries
where a large share of VET students graduate with a specialisation in engineering, manufacturing and
construction, such as Chile, Estonia, Iceland and Sweden (above 40%, see Box B7.1 in Indicator B7) tend to
spend more per student in vocational programmes than in general ones. The differences are also significant in
countries where the field of health and welfare is the most popular, such as Greece, the Netherlands and Spain.

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C1. HOW MUCH IS SPENT PER STUDENT ON EDUCATIONAL INSTITUTIONS?  273
In contrast, differences are smaller in countries such as Luxembourg where business, administration and law is
the most popular field in upper secondary vocational programmes (Figure C1.2 and Box B7.1).


Recent investment in VET programmes and curricula: while digitalisation might impact the future of VET, the
evidence is that demand for VET graduates remains significant and that salaries of VET graduates are rising
(Meer, 2007[3]). Therefore, the cost and the resources invested in VET programmes might be affected by the
increasing demand, and the need to adapt VET programmes to the evolving skills needed in the labour market.
For example, the Netherlands has engaged in initiatives to strengthen the link between the content of VET
curricula and the job market. Consortia of vocational schools and business received additional funding from the
business community, the education sector and the government in 2018 to invest in innovative VET training in
regions (Eurydice, 2020[4]).

Figure C1.2. Total expenditure on educational institutions per full-time equivalent student, in
vocational and general upper secondary education programmes (2017)
In equivalent USD converted using PPPs
Equivalent USD
(in thousands)
25

General

Vocational

20
15
10

Russian Federation

Mexico

Turkey

Lithuania

Australia

Slovak Republic

Slovenia

Finland

Estonia

Chile

Latvia

Poland

Greece

United Kingdom

Hungary

Czech Republic

OECD average

EU23 average

Spain

Iceland

Sweden

New Zealand

Belgium

Netherlands

France

Norway

Israel

Germany

Austria

0

Luxembourg

5

Countries are ranked in descending order of the total expenditure per full-time equivalent student in vocational programmes.
Source: OECD/UIS/Eurostat (2020), Table C1.1. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2 https://doi.org/10.1787/888934164389

The greater reliance on private funding in tertiary education has led to higher expenditure at this level than in lower ones (see
Indicator C3, and Table C1.5, available on line). In 2017, while OECD countries spent on average around USD 10 000 per
student at the primary, secondary and post-secondary non-tertiary levels, expenditure per student reached USD 16 300 at
the tertiary level. However, the average expenditure at this level is driven up by high values in a few countries, most notably
Canada, Luxembourg, Norway, Sweden, the United Kingdom and the United States (Table C1.1). Significant differences are
also observed at the subnational level (Box C1.2).
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 16% more per secondary student than
they do per primary student. This percentage is near 50% or more in the Czech Republic, France and the Netherlands.
However, Chile, Denmark, Estonia, Iceland, Israel, Lithuania, Poland, the Slovak Republic and the United Kingdom all invest
more per primary student than on each secondary student, despite the fact that teacher’s salaries, a strong driver of total
expenditure, tend to increase with higher levels of education. Similarly, educational institutions in OECD countries spend an
average of 24% more on each tertiary student (excluding R&D) than on each primary student. Hungary, Ireland, Turkey,
the United Kingdom and the United States spend about twice as much on a tertiary student (excluding R&D) than on a primary
student (Table C1.1).
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274  C1. HOW MUCH IS SPENT PER STUDENT ON EDUCATIONAL INSTITUTIONS?

Box C1.2. Subnational variation in annual expenditure per student on educational institutions
Annual expenditure per student can be quite heterogeneous across countries with large differences between regions, due
to their economic circumstances and geographic challenges. Among the six countries with available data at subnational
level, Canada and the United States have the highest variation in annual expenditure per student on educational
institutions at primary and secondary levels combined: in Canada, the region with the highest value (USD 24 000) spends
almost three times as much per student as the region with the lowest value (almost USD 9 000). Smaller regional
differences are found in Germany and Switzerland, while in Belgium and Lithuania expenditure per student on primary
and secondary educational institutions is almost identical across the regions.
There are also regional differences in spending on education personnel in Switzerland. While expenditure on teaching
and non-teaching staff per student at primary and lower secondary is over USD 20 000 in Zürich, it is USD 13 000 in
Ticino.
Note: 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.

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 89% of total expenditure per student from primary to tertiary educational institutions and it
exceeds 90% in Chile, Latvia and Poland. In about one-third of OECD and partner countries with available data, annual
expenditure on R&D and ancillary services per student accounts for around 14% or more of the total annual expenditure per
student on primary to tertiary institutions. In the Slovak Republic and Sweden, this reaches 23% (Table C1.2).
However, this overall picture masks large variations across levels of education (Table C1.2 and Figure C1.3). At non-tertiary
levels (primary, secondary and post-secondary non-tertiary education), expenditure is dominated by spending on core
education services. On average, OECD countries spend 95% of their total per-student expenditure (about USD 9 500) on
core educational services at these levels. However, in Finland, France, Hungary, 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 widely at tertiary
level, as R&D expenditure can account for a significant proportion of educational spending (Table C1.2). On average across
OECD countries, 69% of total expenditure on educational institutions at tertiary level goes to core services. Excluding R&D
activities, expenditure per student across OECD countries averages aboutr USD 11 200, ranging from about USD 2 000 in
Colombia and Greece to USD 29 000 or more in Luxembourg and the United States (Table C1.2).
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 (Table C1.2).
On average across OECD countries, expenditure on R&D and ancillary services at the tertiary level represents 31% of all
tertiary expenditure on educational institutions per student. In eight 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 Denmark and Sweden recording the highest shares, at around 52% (Table C1.2).
The share of expenditure on ancillary services tends to be lower in tertiary education than at lower levels of education
(Table C1.2). On average, only 5% of expenditure on tertiary institutions goes towards ancillary services, and the amount is
negligible (below USD 100 per student) in the Czech Republic, Denmark, Finland, Israel, Sweden. Luxembourg,
the Slovak Republic and the United States spend the most in ancillary services per student at tertiary level among OECD
countries, over USD 2 000 per student (Table C1.2).

Expenditure per student on educational institutions relative to per capita GDP
Expenditure on educational institutions per student relative to 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

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C1. HOW MUCH IS SPENT PER STUDENT ON EDUCATIONAL INSTITUTIONS?  275
relatively high on this measure, even when a large proportion of their wealth is spent on educating a relatively small number
of students.

Figure C1.3. Total expenditure on educational institutions per full-time equivalent student, by type of
service (2017)
In equivalent USD converted using PPPs
Total
R&D
Ancillary services
Core services

Equivalent USD
(in thousands)
25

Primary, secondary and post-secondary non-tertiary education

20
15
10

Chile

Turkey

Colombia2

Mexico

Latvia

Mexico

Greece

Colombia 2

Lithuania

Russian Federation
Lithuania

Chile

Russian Federation

Latvia

Hungary

Poland

Estonia

Israel

Czech Republic

Spain

Ireland

Portugal

Slovenia

Japan

New Zealand

OECD average

Italy

Slovak Republic

Equivalent USD
(in thousands)
60

Finland

France

EU23 average

Australia

Canada1

United Kingdom

Denmark

Netherlands

Germany

Korea

Sweden

Iceland

Belgium

United States

Austria

Norway

0

Luxembourg

5

Tertiary education

50
40
30
20
10

Turkey

Korea

Poland

Czech Republic

Slovak Republic

Portugal

Italy

Israel

Slovenia

Hungary

Spain

Estonia

New Zealand

Iceland

EU23 average

OECD average

Ireland

France

Finland

Denmark

Germany

Japan

Austria

Belgium

Australia

Netherlands

Norway

Canada

Sweden

United Kingdom

Luxembourg

United States

0

1. Primary, secondary and post-secondary non-tertiary education includes pre-primary programmes.
2. Year of reference 2018.
Countries are ranked in descending order of total expenditure on educational institutions per full-time equivalent student.
Source: OECD/UIS/Eurostat (2020), Table C1.2. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2 https://doi.org/10.1787/888934164408

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
36% 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, Portugal’s expenditure per student for most
educational levels and its per capita GDP are both below the OECD average and it spends an above-average share of its per
capita GDP per student at most educational levels (Table C1.4, available on line).

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276  C1. HOW MUCH IS SPENT PER STUDENT ON EDUCATIONAL INSTITUTIONS?
The relationship between per capita GDP and expenditure per student on educational institutions is difficult to interpret. 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 40 000;
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. Canada, the United Kingdom and the United States spend more than 50% of per capita GDP on each
student in tertiary institutions (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-fifth of total expenditure per student at this level (Table C1.2).

Change in expenditure per student on educational institutions between 2012 and 2017
Changes in expenditure on educational institutions largely reflect changes in the size of the school-age population and the
expenditure allocated to teachers’ compensation, which is a function of the number of teachers and teachers’ salaries.
Teachers’ salaries, the main component of educational costs, have increased in the majority of countries over the past decade
(see Indicator D3). The size of the school-age population influences both enrolment levels and the amount of resources and
organisational effort a country must invest in its education system. The larger this population, the greater the potential demand
for education services. Changes in expenditure per student over the years may also vary between levels of education within
countries, as both enrolment and expenditure may follow different trends at different levels of education.
Between 2012 and 2017, expenditure per student on primary to tertiary educational institutions grew by an average rate of
1.3% per year in OECD countries while the number of students remained stable (Table C1.3 and Figure C1.4). Over this
period, the average annual growth in spending per student was positive in all countries with data, with the exception of
Canada, Finland, Mexico and Slovenia. The decrease in expenditure per student observed in these countries (between 0.2%
and 2.0%) is either the combined effect of a reduction on spending on educational institutions and a slight increase in the
number of students or, as in the case in Canada, the result of lower expenditure than student growth over this period. In some
countries within the European Union, such as Estonia, Hungary, Latvia, Poland and the Slovak Republic, the strong annual
growth rates in expenditure per student (around or above 2%) are explained by significant increases in expenditure
accompanied by significant decreases in the growth of the number of students over the period under analysis. Outside the
European Union, Chile, Iceland, Norway and Turkey have also reported increases in spending per student of around 2% per
year in real terms since 2012 (Table C1.3).
At non-tertiary levels, the number of students remained fairly stable on average across OECD countries between 2012 and
2017. During the same period, expenditure on non-tertiary educational institutions increased by an annual average growth
rate of 1.6% (Table C1.3). As a result, expenditure per student at these levels increased by 1.4% per year on average between
2012 and 2017. Most OECD countries spent more per student in 2017 than they did in 2012, with the exception of Denmark,
Finland, Luxembourg, Mexico and Slovenia. Expenditure per student increased by more than 4% per year in Colombia,
Hungary, Iceland and the Slovak Republic. This resulted from stable or slight annual reductions in student enrolments
combined with significant annual increases (above 3%) in total spending on non-tertiary institutions between 2012 and 2017.
In contrast, the increase in number of students enrolled was accompanied by a reduction in spending on educational
institutions per student in Finland, Mexico and Slovenia (Table C1.3).
Expenditure at tertiary level increased at a slightly smaller rate than at lower levels of education, rising on average by 0.9%
annually between 2012 and 2017. It also increased faster than the number of students enrolled over this period (annual
average growth rate of 0.5%). As a result, OECD countries recorded an average increase in expenditure per student of 0.4%
per year over this period. However, there are stark differences across countries. Among OECD and partner countries with
available data, Canada, Colombia, the Czech Republic, Finland, France, Germany, Greece, Israel, Lithuania, Mexico,
the Netherlands, Spain and Turkey 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 by more than 4% in Estonia, Hungary, Iceland and the Slovak Republic due to an increase in total
expenditure and a reduction in the number of students (Table C1.3).

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C1. HOW MUCH IS SPENT PER STUDENT ON EDUCATIONAL INSTITUTIONS?  277

Figure C1.4. Average annual growth in total expenditure on primary to tertiary educational institutions
per full-time equivalent student (2012 to 2017)
Students

%
8

Total expenditure

Total expenditure per student

6
4
2
0

Mexico

Finland

Slovenia

Canada

Czech Republic

Russian Federation

Spain

France

Italy

Lithuania

New Zealand

Belgium

Austria

Sweden

Netherlands

Portugal

Israel

Germany

United Kingdom

EU23 average

United States

OECD average

Colombi a

Turkey

Chile

Norway

Latvia

Estonia

Poland

Slovak Republic

Iceland

-4

Hungary

-2

Countries are ranked in descending order of annual growth in total expenditure on primary to tertiary educational institutions per full-time equivalent student.
Source: OECD/UIS/Eurostat (2020), Table C1.3. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2 https://doi.org/10.1787/888934164427

Public expenditure on educational institutions per student, by type of institution
The resources devoted to private educational institutions are higher than the ones devoted to public institutions. On average
across OECD countries, total expenditure on primary to tertiary public institutions amounts to just over USD 11 000 per
student, compared to USD 11 200 in private ones (Table C1.6, available on line). The differences are significant in countries
such as Israel, the Netherlands, Turkey and the United States where expenditure per student in private institutions is at least
USD 5 000 higher than in public ones. In contrast, in countries such as Austria, Canada, Luxembourg, and Iceland, more
resources are invested per student in public institutions than in private ones (above USD 4 000) (Table C1.6, available on
line).
Focusing on public sources of expenditure goes some way to show how much governments value education (see
Indicator C4). Naturally, public funds go to public institutions; but in some cases a significant part of the public budget may be
spent on private educational institutions. On average among OECD countries, public expenditure per student on primary to
tertiary public educational instructions (USD 10 100) is nearly twice the public expenditure per student on private institutions
(USD 5 500). However, the difference varies at different levels of education (Table C1.6, available on line). At non-tertiary
level, average public expenditure per student on public institutions is USD 9 500, about 50% more than the expenditure on
private institutions (USD 6 100), whereas at tertiary level it averages USD 13 300 on public institutions, more than three times
the expenditure on private institutions (USD 4 400) (Table C1.6, available on line).

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.

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278  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
The annual average growth rate is calculated using the compound annual growth rate which shows the geometric progression
ratio that provides a constant rate of return over the time period under analysis.
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 would be required to fully adjust the 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 part-time 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.
Vocational education and training expenditure: Expenditure on workplace training provided by private companies is only
included when it is part of combined school- and work-based programmes, provided that the school-based component
represents at least 10% of the study over the whole programme duration. Other types of employer-provided workplace training
(e.g. entirely work-based training or employee training that takes place 95% at work) are excluded. Expenditure on VET
programmes include the expenditure on training (e.g. salaries and other compensation of instructors and other personnel, as
well as the cost of instructional materials and equipment). However, it excludes apprentices’ wages and other compensations
to students or apprentices.
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/10.1787/69096873-en).

Source
Data refer to the financial year 2017 (unless otherwise specified) and are based on the UNESCO, OECD and Eurostat (UOE)
data collection on education statistics administered by the OECD in 2019 (for details see Annex 3 at
https://doi.org/10.1787/69096873-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).

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C1. HOW MUCH IS SPENT PER STUDENT ON EDUCATIONAL INSTITUTIONS?  279
The data on expenditure for 2012 to 2017 were updated based on a survey in 2019-20, and expenditure figures for 2012 to
2017 were adjusted to the methods and definitions used in the current UOE data collection.
Data on subnational regions are currently available for six countries: Belgium, Canada, Germany, Lithuania, Switzerland and
the United States. Subnational estimates were provided by countries using national data sources. Subnational data are based
on a special survey administrated by the OECD in 2020.

References

Eurydice (2020), National Reforms in Vocational Education and Training and Adult Learning | Eurydice,
https://eacea.ec.europa.eu/national-policies/eurydice/content/national-reforms-vocational-education-andtraining-and-adult-learning-47_en (accessed on 30 June 2020).

[4]

Hoeckel, K. (2008), Costs and Benefits in Vocational Education and Training, OECD, Paris,
https://www.oecd.org/education/skills-beyond-school/41538706.pdf (accessed on 21 February 2020).

[2]

Kuczera, M. (2017), “Striking the right balance: Costs and benefits of apprenticeship”, OECD Education Working
Papers, No. 153, OECD Publishing, Paris, https://dx.doi.org/10.1787/995fff01-en.

[1]

Meer, J. (2007), “Evidence on the returns to secondary vocational education”, Economics of Education Review,
Vol. 26/5, pp. 559-573, http://dx.doi.org/10.1016/j.econedurev.2006.04.002.

[3]

OECD (2018), OECD Handbook for Internationally Comparative Education Statistics 2018, OECD Publishing,
Paris, https://doi.org/10.1787/9789264304444-en (accessed on 16 April 2020).

[5]

Indicator C1 Tables
Table C1.1

Total expenditure on educational institutions per full-time equivalent student (2017)

Table C1.2

Total expenditure on educational institutions per full-time equivalent student for core educational
services, ancillary services and R&D (2017)

Table C1.3

Average annual growth in total expenditure on educational institutions per full-time equivalent student
(2012 to 2017)

WEB Table C1.4

Total expenditure on educational institutions per full-time equivalent student relative to GDP per capita
(2017)

WEB Table C1.5

Total expenditure on educational institutions per full-time equivalent student, by source of funds (2017)

WEB Table C1.6

Public and total expenditure on educational institutions per full-time equivalent student, by type of
institution (2017)

Cut-off date for the data: 19 July 2020. Any updates on data can be found on line at http://dx.doi.org/10.1787/eag-dataen. More breakdowns can also be found at http://stats.oecd.org/, Education at a Glance Database.
StatLink: https://doi.org/10.1787/888934164294

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280  C1. HOW MUCH IS SPENT PER STUDENT ON EDUCATIONAL INSTITUTIONS?
Table C1.1. Total expenditure on educational institutions per full-time equivalent student (2017)
In equivalent USD converted using PPPs for GDP, direct expenditure within educational institutions, by level of education

Lower secondar y

General
programmes

Vocation al
programmes

All prog rammes

All secondar y

Post-secon dar y nontertiar y

Primar y, secondary and
post-secondary nontertiar y

Short-cycle ter tiar y

Long-cycle tertiar y

All tertiar y

All tertiar y
(excluding R&D)

Primar y to ter tiar y

Primar y to ter tiar y
(excluding R&D)

Tertiar y

Primar y

Secondar y

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

(13)

(14)

Countries
Australia
Austria
Belgium
Canada 1, 2
Chile
Colombia 2 , 3
Costa Rica 3
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungar y
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Lithuania
Luxembourg
Mexico
Netherlands
New Zealand
Nor way
Poland
Por tugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
Unite d Kingdom
United States

10 238
12 754
11 106
10 238 d
5 259
3 494
m
5 971
13 278
7 481
9 633
8 319
9 572
6 085
5 491
13 333
8 215
9 155
9 160
8 824
11 702
6 379
6 340
19 690
2 782
9 301
8 533
13 906
7 806
8 766
6 836
9 062
8 161
12 189
m
4 002
11 604
12 592

13 181
16 794
14 524
x(1)
5 440
4 468
m
10 081
13 127
7 622
15 400
11 252
11 975
6 951
5 259
15 620
10 054
x(3, 4, 5)
10 073
10 511
12 597
6 492
5 994
23 073
2 438
13 527
10 059
13 906
7 286
10 993
6 121
11 336
9 567
12 894
m
3 912
11 749
13 654

14 019
14 425
14 210 d
x(5)
4 393
x(5)
m
8 174
x(5)
6 878
8 719
13 944
12 963
5 834
7 961
10 785
x(5)
6 940 d
x(5)
x(5)
x(5)
7 048
6 066
22 236
3 115
11 365
12 004
17 398
6 798
x(5)
7 217
9 199
9 732
11 078
x(5)
5 448
13 429
x(5)

7 371
18 054
14 896 d
x(5)
8 342
x(5)
m
9 645
x(5)
7 670
7 985 d
16 227
17 960
8 756
9 494
13 426
x(5)
17 258 d
x(5)
x(5)
x(5)
8 628
5 832
22 546
3 980
15 776
13 859
16 982
8 639
x(5)
7 441
7 599
12 851 d
14 723
x(5)
6 159
8 978
x(5)

11 825
16 593
14 606 d
13 891
5 033
3 436
m
9 246
9 526
7 208
8 180 d
14 743
15 466
6 638
8 465
11 503
8 890
9 079 d
10 883 d
11 510 d
14 394
7 680
6 002
22 427
3 418
14 274
12 401
17 191
7 838
10 463 d
7 370
8 110
10 711 d
12 427
18 966 d
5 776
11 480
15 202

12 640
16 705
14 578 d
13 891
5 167
4 177
m
9 666
11 164
7 404
10 454 d
12 748
13 283
6 789
6 867
13 122
9 445
9 079
10 574 d
11 024 d
13 579
7 102
5 997
22 724
2 823
13 889
11 117
15 735
7 577
10 721 d
6 652
9 370
10 134 d
12 634
m
4 859
11 592
14 411

8 504
5 700
x(3, 4, 5, 6)
m
a
m
a
2 763
a
8 053
x(4, 5, 6)
9 897
12 403
m
13 642
15 532
35 312
1 205
x(5, 6)
x(5, 6, 9, 10, 11)
a
8 585
5 857
1 951
a
a
10 059
21 168
3 742
x(5, 6)
6 383
a
x(4, 5, 6)
5 883
x(5)
a
a
15 908

11 270
15 097
13 054
11 380 d
5 213
3 855
m
8 052
12 163
7 462
10 133
10 867
12 195
m
6 780
13 254
9 218
9 064
10 036
9 963
12 704
6 766
6 094
21 244
2 803
11 931
9 937
14 848
7 597
9 836
6 711
9 223
9 166
12 339
m
4 594
11 597
13 511

10 943
18 457
12 965
18 820
4 821
x(11)
m
18 866
17 623
a
a
15 359
11 284
a
4 675
9 682
x(11)
5 584
4 240
13 617 d
5 791
8 141
a
27 920
x(11)
11 467
11 279
20 615
27 938
7 451
8 345
3 757
9 795
6 874
m
x(11)
19 093
x(11)

23 261
19 206
19 649
27 948
11 503
x(11)
m
11 462
18 116
14 580
17 730
17 442
18 487
3 294
13 256
16 497
x(11)
15 795
12 277
20 209 d
11 948
8 381
8 428
55 433
x(11)
20 493
17 096
23 522
10 041
11 941
11 776
14 100
14 387
27 167
m
x(11)
29 131
x(11)

20 436
19 089
19 422
24 671
9 610
2 335
m
11 484
18 062
14 580
17 730
16 952
18 486
3 294
12 878
16 270
16 794
12 310
12 226
18 839 d
10 633
8 346
8 428
52 089
6 586
20 445
16 068
23 439
10 044
11 788
11 715
12 787
13 446
25 584
m
9 708
28 144
33 063

14 314
13 711
12 539
m
9 079
1 331
m
7 217
8 778
9 618
9 874
11 638
10 436
2 137
10 838
m
16 185
8 382
8 131
m
8 400
6 379
6 353
32 325
5 263
13 104
12 755
13 414
7 843
9 126
9 075
10 302
10 052
11 928
m
7 857
22 291
29 153

13 272
16 319
14 287
14 428 d
6 487
3 538
m
8 732
13 499
8 946
11 637
12 080
13 529
m
7 797
13 819
10 489
9 671
10 473
11 896
11 981
7 121
6 652
23 324
3 320
13 809
11 098
16 644
8 144
10 220
7 562
9 897
10 105
14 505
m
5 586
14 209
17 993

11 935
14 672
12 954
m
6 333
3 328
m
7 887
11 396
7 912
10 082
11 020
11 822
m
7 457
m
10 386
8 936
9 655
m
11 202
6 679
6 156
22 053
3 139
12 190
10 471
14 548
7 652
9 696
7 113
9 427
9 360
12 271
m
5 227
13 226
17 096

OECD average
EU23 average

9 090
9 269

10 527
10 963

10 051
10 383

11 521
11 774

10 888
10 836

10 547
10 786

m
m

9 999
10 344

12 422
13 014

17 566
17 126

16 327
16 688

11 234
11 339

11 231
11 515

10 103
10 503

m
m
m
m
m
m
m
m
m
m
x(3, 4, 5, 6) x(3, 4, 5, 6)
m
m
m
m

m
m
m
m
m
5 651 d
m
m

a
m
m
m
m
2 582 d
m
m

m
m
m
m
m
5 382 d
m
m

m
m
m
m
m
5 382 d
m
m

a
m
m
m
a
x(3, 4, 5, 6)
m
m

m
m
m
m
m
5 382
m
m

m
m
m
m
m
5 379
m
m

m
m
m
m
m
9 776
m
m

m
m
m
m
m
8 629
m
m

m
m
m
m
m
7 750
m
m

m
m
m
m
m
6 090
m
m

m
m
m
m
m
5 898
m
m

m

m

m

m

m

m

m

m

m

m

m

m

Par tners

OECD

Upper secondar y

Argentina
Brazil
China
India
Indonesia 3
Russian Federation
Saudi Arabia
South Africa
G20 average

m

m

Note: See Definitions and Methodology sections for more information. Data and more breakdowns available at http://stats.oecd.org/, Education at a Glance Database.
1. Primary education includes pre-primary programmes.
2. Post-secondary non-tertiary figures are treated as negligible.
3. Year of reference 2018.
Source: OECD/UIS/Eurostat (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888934164313

EDUCATION AT A GLANCE 2020 © OECD 2020

C1. HOW MUCH IS SPENT PER STUDENT ON EDUCATIONAL INSTITUTIONS?  281

Table C1.2. Total expenditure on educational institutions per full-time equivalent student for core educational services,
ancillary services and R&D (2017)
In equivalent USD converted using PPPs for GDP, direct expenditure within educational institutions, by level of education
Primary, secondary
and post-secondary non-tertiary

Tertiary

Partners

OECD

Core
Ancillary
All
Core
Ancillary
services services services services services

R&D

Primary to tertiary
All
services
excluding Core
Ancillary
All
R&D
services services
services

R&D

All
services
excluding
All
R&D
services

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

(13)

Countries
Australia
Austria
Belgium
Canada1
Chile
Colombia 2
Costa Rica 2
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Lithuania
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United Kingdom
United States

11 120
14 429
12 587
x(3)
4 800
3 683
m
7 542
12 029
7 365
9 086
9 513
11 878
m
5 905
x(3)
x(3)
8 623
9 550
x(3, 7)
11 636
6 651
5 804
19 845
x(3)
11 931
x(3)
14 351
7 343
9 207
5 621
x(3)
8 489
11 064
m
4 354
10 456
12 440

150
668
467
x(3)
413
172
m
510
133
97
1 047
1 353
316
m
875
x(3)
x(3)
441
486
x(3, 7)
1 068
115
290
1 399
x(3)
a
x(3)
497
254
629
1 090
x(3)
677
1 275
m
240
1 071
1 071

11 270
15 097
13 054
11 380 d
5 213
3 855
m
8 052
12 163
7 462
10 133
10 867
12 195
m
6 780
13 254
9 218
9 064
10 036
9 963
12 704
6 766
6 094
21 244
2 803
11 931
9 937
14 848
7 597
9 836
6 711
9 223
9 166
12 339
m
4 594
11 597
13 511

13 568
13 528
11 480
x(7)
8 766
x(7)
m
7 130
8 682
8 949
9 874
10 831
9 421
x(7)
9 787
x(7)
x(7)
8 338
7 675
x(7)
x(7)
6 245
5 537
31 232
x(7)
13 104
x(7)
13 072
7 572
8 714
6 979
x(7)
9 506
11 928
m
6 755
20 637
24 839

746
183
1 059
x(7)
313
x(7)
m
87
96
669
0
807
1 015
x(7)
1 051
x(7)
x(7)
44
456
x(7)
x(7)
134
816
2 001
x(7)
a
x(7)
343
271
412
2 096
x(7)
546
0
m
1 102
1 654
4 314

6 121
5 378
6 883
x(7)
531
1 004
m
4 268
9 284
4 962
7 856
5 313
8 051
1 157
2 041
x(7)
609
3 929
4 096
x(7)
2 233
1 968
2 075
18 855
1 323
7 341
3 313
10 024
2 201
2 663
2 640
2 485
3 394
13 657
17 444
1 851
5 853
3 911

20 436
19 089
19 422
24 671
9 610
2 335
m
11 484
18 062
14 580
17 730
16 952
18 486
3 294
12 878
16 270
16 794
12 310
12 226
18 839 d
10 633
8 346
8 428
52 089
6 586
20 445
16 068
23 439
10 044
11 788
11 715
12 787
13 446
25 584
m
9 708
28 144
33 063

14 314
13 711
12 539
m
9 079
1 331
m
7 217
8 778
9 618
9 874
11 638
10 436
2 137
10 838
m
16 185
8 382
8 131
m
8 400
6 379
6 353
33 234
5 263
13 104
12 755
13 414
7 843
9 126
9 075
10 302
10 052
11 928
m
7 857
22 291
29 153

11 655
14 153
12 372
x(12)
5 950
x(12)
m
7 460
11 271
7 695
9 242
9 776
11 357
m
6 553
x(12)
x(12)
8 569
9 175
x(12)
x(12)
6 560
5 740
20 613
x(12)
12 190
x(12)
14 083
7 394
9 110
5 852
x(12)
8 712
11 205
m
4 820
12 063
15 282

280
520
582
x(12)
384
x(12)
m
427
125
217
839
1 244
464
m
904
x(12)
x(12)
367
480
x(12)
x(12)
119
416
1 440
x(12)
a
x(12)
465
258
586
1 261
x(12)
648
1 066
m
407
1 163
1 814

1 337
1 646
1 332
x(12)
154
210
m
845
2 104
1 034
1 555
1 059
1 707
409
340
x(12)
103
735
818
x(12)
780
443
496
1 271
181
1 619
627
2 096
492
524
449
470
745
2 234
3 319
359
983
896

13 272
16 319
14 287
14 428 d
6 487
3 538
m
8 732
13 499
8 946
11 637
12 080
13 529
m
7 797
13 819
10 489
9 671
10 473
11 896
11 981
7 121
6 652
23 324
3 320
13 809
11 098
16 644
8 144
10 220
7 562
9 897
10 105
14 505
m
5 586
14 209
17 993

11 935
14 672
12 954
m
6 333
3 328
m
7 887
11 396
7 912
10 082
11 020
11 822
m
7 457
m
10 386
8 936
9 655
m
11 202
6 679
6 156
22 053
3 139
12 190
10 471
14 548
7 652
9 696
7 113
9 427
9 360
12 271
m
5 227
13 226
17 096

OECD average
EU23 average

9 547
9 815

452
529

9 999
10 344

11 313
10 940

809
703

4 205
5 044

16 327
16 688

11 234
11 339

9 956
9 925

659
671

616
919

11 231
11 515

10 103
10 503

Argentina
Brazil
China
India
Indonesia 2
Russian Federation
Saudi Arabia
South Africa

m
m
m
m
m
x(3)
m
m

m
m
m
m
m
x(3)
m
m

m
m
m
m
m
5 382
m
m

m
m
m
m
m
x(7)
m
m

m
m
m
m
m
x(7)
m
m

m
m
m
m
m
879
m
m

m
m
m
m
m
8 629
m
m

m
m
m
m
m
7 750
m
m

m
m
m
m
m
x(12)
m
m

m
m
m
m
m
x(12)
m
m

m
m
m
m
m
192
m
m

m
m
m
m
m
6 090
m
m

m
m
m
m
m
5 898
m
m

G20 average

m

m

m

m

m

m

m

m

m

m

m

m

m

Note: Some levels of education are included with others. Refer to "x" code in Table C1.1 for details. See Definitions and Methodology sections for more information. Data
and more breakdowns available at http://stats.oecd.org/, Education at a Glance Database.
1. Primary, secondary and post-secondary non-tertiary education includes pre-primary programmes.
2. Year of reference 2018.
Source: OECD/UIS/Eurostat (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888934164332

EDUCATION AT A GLANCE 2020 © OECD 2020

282  C1. HOW MUCH IS SPENT PER STUDENT ON EDUCATIONAL INSTITUTIONS?
Table C1.3. Average annual growth in total expenditure on educational institutions per full-time equivalent student (2012 to 2017)
GDP deflator 2015 = 100, constant prices and constant PPPs, by level of education
Prima ry, secondar y
and post-secondar y non-tertiar y

Ter tiar y

Primar y to tertiar y

(4)

(5)

2012
(6)

2017
(7)

Countries
Australia
Austria
Belgium
Canada 1
Chile
Colombia
Costa Rica
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungar y
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Lithuania
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
Unite d Kingdom
United States

m
13 508
12 017
10 408 d
4 560
2 417
m
7 008
12 168
6 861
10 023
9 969
10 521
6 451
4 613
9 974
m
7 572
8 980
m
m
5 367
4 994
21 485
2 907
10 769
8 999
13 212
6 577
8 953
5 531
9 290
8 387
11 142
18 255
3 764
10 540
12 284

10 611
14 164
12 189
10 642 d
4 994
3 045
m
7 501
11 254
7 029
9 553
10 201
11 355
m
6 565
12 514
8 935
8 538
9 161
m
12 390
6 342
5 703
19 866
2 657
11 277
9 280
14 288
7 320
9 366
6 818
8 595
8 544
11 719
m
4 526
10 979
13 126

m
-0.1
0.4
0.9 d
-0.3
-1.1
0.4
1.0
-0.3
0.6
0.4
0.5
-0.7
0.6
-1.7
0.1
2.2
1.9
0.0
m
-3.1
0.0
-2.7
1.6
0.8
-0.6
0.6
0.5
-0.9
-1.9
-1.1
1.1
1.0
2.7
1.4
2.1
0.8
0.5

m
0.9
0.7
1.4 d
1.5
3.6
m
2.3
-1.9
1.1
-0.6
1.0
0.8
m
5.4
4.7
m
4.4
0.4
m
m
3.4
0.0
0.0
-1.0
0.4
1.2
2.1
1.3
-1.0
3.1
-0.4
1.3
3.8
m
5.9
1.6
1.8

m
1.0
0.3
0.4 d
1.8
4.7
m
1.4
-1.6
0.5
-1.0
0.5
1.5
m
7.3
4.6
m
2.4
0.4
m
m
3.4
2.7
-1.6
-1.8
0.9
0.6
1.6
2.2
0.9
4.3
-1.5
0.4
1.0
m
3.8
0.8
1.3

m
17 831
16 995
24 378
8 402
5 616
m
11 267
m
8 915
19 143
16 478
18 334
4 094
9 366
11 763
m
13 468
11 129
m
m
7 802
9 320
m
8 422
19 540
14 641
19 613
7 993
10 656
9 539
10 526
12 727
23 744
26 901
12 127
25 500
28 825

OECD average
EU23 average

9 076
9 325

9 442
9 747

0.2
0.1

1.6
1.1

1.4
1.1

Argentina
Brazil
China
India
Indonesia
Russian Federation
Saudi Arabia
South Africa

m
m
m
m
m
4 984
m
m

m
m
m
m
m
5 048
m
m

0.3
m
m
m
0.5
2.8
m
m

m
m
m
m
m
3.1
m
m

m

m

m

m

Total
expenditure
per student

(3)

Total
expenditure

(2)

Number of
students

Total
expenditure
per student

Total
expenditure
per student

Total
expenditure

Total
expenditure

2017

(1)

G20 average

Number of
students

2012

Number of
students

Par tners

OECD

Total expenditure
Total expenditur e
Total expenditure
per student in
per student in
per student in
constant prices
constant prices
con stant prices
and constant
Average annual growth
and constant
Average annual growth
and con stant
Average annual grow th
PPPs
between 2012 and 2017 (%)
PPPs
between 2012 and 2017 (%)
PPPs
between 2012 and 2017 (%)

(8)

(9)

(10)

2012
(11)

(13)

(14)

(15)

19 242
17 909
18 135
23 071
9 207
5 535
m
10 698
16 713
13 734
16 714
15 914
17 214
3 106
12 470
15 362
16 279
11 596
11 161
m
10 370
7 824
7 887
48 708
6 244
19 323
15 006
22 554
9 678
11 225
11 902
11 916
12 535
24 299
m
9 562
26 643
32 120

m
0.7
1.4
0.7
2.5
0.9
1.7
-4.4
1.0
-6.7
0.5
2.1
3.1
2.7
-4.9
-1.3
1.9
4.1
-0.5
m
-1.4
-2.6
-3.9
m
6.9
2.2
0.7
3.2
-2.7
-2.3
-2.9
-3.2
1.9
0.9
2.9
8.9
3.3
-1.2

m
0.8
2.8
-0.4
4.4
0.6
m
-5.4
m
1.7
-2.2
1.4
1.8
-2.8
0.7
4.1
m
1.0
-0.5
m
m
-2.5
-7.0
6.9
0.7
1.9
1.2
6.2
1.1
-1.3
1.5
-0.8
1.6
1.4
m
3.9
4.2
0.9

m
0.1
1.3
-1.1
1.8
-0.3
m
-1.0
m
9.0
-2.7
-0.7
-1.3
-5.4
5.9
5.5
m
-2.9
0.1
m
m
0.1
-3.3
m
-5.8
-0.2
0.5
2.8
3.9
1.0
4.5
2.5
-0.3
0.5
m
-4.6
0.9
2.2

m 12 496
14 794 15 310
12 942 13 340
13 640 d 13 492 d
5 568
6 215
948
1 015
m
m
8 053
8 135
m 12 491
7 432
8 427
11 820 10 970
11 188 11 340
11 946 12 597
5 674
m
5 521
7 550
10 329 13 048
m 10 167
8 583
9 110
9 418
9 561
m
m
m 11 685
5 973
6 676
6 079
6 225
m 21 810
3 490
3 148
12 508 13 051
10 062 10 365
14 413
16 016
6 917
7 847
9 294
9 731
6 266
7 682
9 568
9 223
9 304
9 420
13 359 13 777
19 803
m
5 003
5 502
12 664 13 451
16 336 17 479

m
0.2
0.6
0.9 d
0.4
-0.7
0.6
-0.3
0.0
-1.2
0.4
0.8
0.0
1.3
-2.3
-0.2
2.2
2.3
-0.1
m
-2.6
-0.6
-3.0
m
1.5
0.0
0.6
1.0
-1.3
-2.0
-1.4
0.2
1.2
2.4
1.7
3.2
1.1
0.1

m
0.8
1.2
0.6 d
2.7
0.6
m
-0.1
m
1.3
-1.1
1.1
1.1
m
4.0
4.6
m
3.5
0.2
m
m
1.6
-2.5
0.9
-0.6
0.9
1.2
3.2
1.2
-1.1
2.7
-0.5
1.4
3.0
m
5.2
2.4
1.5

m
0.7
0.6
-0.2 d
2.2
1.4
m
0.2
m
2.5
-1.5
0.3
1.1
m
6.5
4.8
m
1.2
0.3
m
m
2.3
0.5
m
-2.0
0.9
0.6
2.1
2.6
0.9
4.2
-0.7
0.2
0.6
m
1.9
1.2
1.4

14 357
13 545

15 482
15 739

0.5
-0.6

0.9
0.2

0.4
0.7

9 642
9 536

10 540
10 854

0.2
-0.1

1.4
0.9

1.3
1.2

m
m
m
m
m
0.3
m
m

m
m
m
m
m
7 799
m
m

m
m
m
m
m
8 094
m
m

2.9
m
m
3.2
5.0
-3.8
m
m

m
m
m
m
m
-3.1
m
m

m
m
m
m
m
0.7
m
m

m
m
m
m
m
5 772
m
m

m
m
m
m
m
5 712
m
m

0.9
m
m
m
1.1
1.2
m
m

m
m
m
m
m
0.9
m
m

m
m
m
m
m
-0.2
m
m

m

m

m

2.2

m

m

m

m

m

m

m

2017
(12)

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, secondary and post-secondary non-tertiary education includes pre-primary programmes.
Source: OECD/UIS/Eurostat (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888934164351

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284  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 2017, OECD countries spent an average of 4.9% 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 non-tertiary education (primary, secondary and post-secondary nontertiary levels) was 3.5% of GDP, much larger than the share devoted to tertiary education (1.4% 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 0.4% of GDP, after transfers between government and the private
sector. At non-tertiary levels, private spending on education represents only one-tenth of the total expenditure on
institutions, or 0.3% of GDP.



Between 2012 and 2017, 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 total expenditure on educational
institutions increasing more slowly than GDP.

Figure C2.1. Total expenditure on educational institutions as a percentage of GDP (2017)
From public, private and international sources, by level of education
All tertiary
Primary, secondary, and post-secondary non-tertiary

%
7
6
5
4
3
2

Luxembourg

Ireland

Lithuania

Czech Republic

Russian Federation

Italy

Slovak Republic

Latvia

Hungary

Japan

Germany

Spain

Slovenia

Poland

Mexico

Estonia

Austria

EU23 average

OECD average

Korea

Turkey

Portugal

Netherlands

France

Finland

Sweden

Denmark

Colombia2

Iceland

Belgium

Canada1

Australia

Israel

United States

United Kingdom

Chile

Norway

0

New Zealand

1

1. Primary, secondary and post-secondary non-tertiary education includes pre-primary programmes.
2. Year of reference 2018.
Countries are ranked in descending order of total expenditure on educational institutions as a percentage of GDP.
Source: OECD/UIS/Eurostat (2020), Table C2.1. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2 https://doi.org/10.1787/888934164522

EDUCATION AT A GLANCE 2020 © OECD 2020

C2. WHAT PROPORTION OF NATIONAL WEALTH IS PENT ON EDUCATIONAL INSTITUTIONS?  285

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 the proportion of a nation’s wealth that is invested in
educational institutions. This measure demonstrates the priority given to educational institutions 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 0.8% of GDP on average
across OECD countries, after transfers between government and the private sector.



Between 2015 and 2017, public expenditure on educational institutions as a share of GDP decreased slightly at
non-tertiary levels (1.2% on average across OECD countries). However, at the tertiary level the reduction has
been more significant, at just over 5.1% on average across OECD countries.

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286  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 2017,
OECD countries spent on average 4.9% 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 Australia, Chile,
Israel, New Zealand, Norway, the United Kingdom and the United States, to 3-4% in the Czech Republic, Hungary, Ireland,
Italy, Japan, Latvia, 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 investment 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, 71% 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 at 4.5% or more of GDP in Colombia, Iceland, Israel,
New Zealand and Norway while it accounts for 2.4% of GDP in Lithuania and the Russian Federation (Table C2.1).
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, as well as the duration of each level of education. Countries with relatively low
fertility rates are more likely to spend a smaller share of their wealth on primary and lower secondary education. Indeed, the
countries where investment in primary education is 1% of GDP or lower also tend to be those with low birth rates (e.g. Austria,
the Czech Republic, Germany, Hungary, Italy, 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. Around one-third 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 percentage points) (Table C2.1).
Tertiary education accounts for 1.4% 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. In 2017, Australia, Canada, Chile, Norway, the United Kingdom 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 organised as well as the infrastructure and facilities available.
Expenditure levels tend to be higher in Australia, Finland, the Netherlands, Norway, Sweden and other OECD countries where
most publicly funded R&D is performed by tertiary educational institutions than in 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, although the difference is at least 0.7 percentage
points in Denmark, Finland, Norway and Sweden (Table C2.1).

Expenditure on educational institutions by source of funds
Public 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 4.1% of
GDP. However, large differences are observed across countries with available data. In the Czech Republic, Greece, Ireland,
Japan, Lithuania, Luxembourg, the Slovak Republic and the Russian Federation, public investment represents around 2.8-

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C2. WHAT PROPORTION OF NATIONAL WEALTH IS PENT ON EDUCATIONAL INSTITUTIONS?  287
3.2% of GDP, while Belgium, Brazil, Costa Rica, Denmark, Finland, Iceland, Israel, Norway and Sweden devote around 5.06.4% of their GDP to direct public expenditure on educational institutions (Table C2.2).

Figure C2.2. Total expenditure on educational institutions as a percentage of GDP, by source of funds
(2017)
After transfers; from public, private and international sources
Private expenditure
Public expenditure
%
5.0

Primary, secondary and post-secondary non-tertiary education

4.5
4.0
3.5
3.0
2.5
2.0
1.5
1.0

Ireland

Lithuania
Luxembourg

Italy

Russian Federation

Japan

Ireland

Greece

Czech Republic

Czech Republic

Colombia1

Luxembourg

Slovak Republic

Slovak Republic

Estonia

Hungary

Slovenia

Lithuania

Italy

Latvia
Latvia

Hungary

Russian Federation

Spain

Austria

Poland

Mexico

Slovenia

EU23 average

Korea

Turkey

Netherlands

Germany

%
3.0

OECD average

United States3

Chile

Canada2

Finland

France

Sweden

Denmark

Australia

Belgium

Portugal

United Kingdom

Iceland

Norway

New Zealand

Israel

0

Colombia1

0.5

Tertiary education

2.5
2.0
1.5
1.0
0.5
Portugal

Poland

Mexico

Germany

EU23 average

Spain

Iceland

Japan

OECD average

France

Israel

Estonia

Belgium

Korea

Finland

Sweden

Denmark

Turkey

Netherlands

Austria

New Zealand

Norway

United Kingdom

Canada

Australia

Chile

United States3

0

Note: International expenditure is aggregated with public expenditure for display purposes.
1. Year of reference 2018.
2. Primary, secondary and post-secondary non-tertiary education includes pre-primary programmes.
3. Figures are for net student loans rather than gross, thereby underestimating public transfers.
Countries are ranked in descending order of total expenditure on educational institutions as a percentage of GDP.
Source: OECD/UIS/Eurostat (2020), Table C2.2. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2 https://doi.org/10.1787/888934164541

Public transfers to households (such as scholarships and loans to students for tuition and other fees) and subsidies to other
private entities for education (e.g. to firms or labour organisations operating apprenticeship programmes) comprise 0.2% of
GDP on average across OECD countries from primary to tertiary level. They account for 0.3% of GDP or more in Australia,
Chile, Korea and New Zealand and reach 0.6% in the United Kingdom, mainly driven by public transfers at tertiary level
(Table C2.2).
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288  C2. WHAT PROPORTION OF NATIONAL WEALTH IS SPENT ON EDUCATIONAL INSTITUTIONS?
With public budgets tightening, many educational systems are turning increasingly towards the private sector for additional
investment, particularly at tertiary level. After transfers, private sector expenditure on primary to tertiary educational institutions
accounts for 0.8% of GDP on average. Countries nevertheless differ considerably in the contribution of private expenditure
on educational institutions, ranging from 0.1% of GDP or less in Denmark, Finland and Luxembourg, to 2% 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 0.3% of GDP on average across OECD countries
after public-to-private transfers. However, it amounts to at least 0.7% of GDP in Australia, Colombia, 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 for 0.4% of GDP after transfers on average. In some
countries, private sources contribute a larger share of the GDP even before public transfers to households are taken into
account. Countries such as Australia, Chile, Korea, New Zealand and the United Kingdom devote 0.6% of GDP or more in
private spending before transfers. After public transfers are taken into account, private investment represents more than 1%
of the GDP in these countries. In Chile and the United States, it amounts to 1.7% 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
(2012 and 2017)
Final source of funds, by level of education, (reference year 2012 = 100)
Primary, secondary, and post-secondary non-tertiary

Index
180

All tertiary

Total

160
140
120
100
80

Lithuania

Luxembourg

Slovenia

United Kingdom

Mexico

Finland

Czech Republic

Japan

Poland

Greece

New Zealand

Spain

EU23 average

Latvia

Netherlands

United States

OECD average

Austria

Colombi a

Canad a1

Turkey

Belgium

Germany

Switzerland

Italy

France

Portugal

Israel

Sweden

Iceland

Slovak Republic

Brazil

Norway

Hungary

Russian Federation

40

Chile

60

1. Primary, secondary and post-secondary non-tertiary 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 (2020), Table C2.4, available on line. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2 https://doi.org/10.1787/888934164560

Changes in educational expenditure between 2012 and 2017
Between 2012 and 2017, OECD countries have increased public expenditure on educational institutions across all levels of
education, but at a slower pace than average GDP growth (Table C2.4, available on line, and Figure C2.3). This pattern also
holds when private sources are included in the equation. On average, total expenditure from all sources on primary to tertiary
educational institutions increased by 6.6% between 2012 and 2017, but since GDP grew at a higher pace (13.1%) total
expenditure as a percentage of GDP fell by 5.2% (Table C2.3). More than two-thirds of OECD and partner countries with
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C2. WHAT PROPORTION OF NATIONAL WEALTH IS PENT ON EDUCATIONAL INSTITUTIONS?  289
available data experienced a reduction in the total expenditure on educational institutions as a share of GDP. Colombia,
the Czech Republic, Ireland, Lithuania, Luxembourg, Mexico and Slovenia were among the countries with the largest negative
adjustments; all them saw increases in GDP of over 10% over that period combined with reductions in total expenditure on
educational institutions. In contrast, Norway was the major exception, with an increase of 17% in total expenditure on
educational institutions outstripping its significant increase in GDP (Table C2.3)
Spending on the various levels of education evolved similarly between 2012 and 2017. Expenditure on educational institutions
at the non-tertiary levels decreased by 3.9% relative to GDP. However, this average masks significant changes in some
countries. In Sweden and the Russian Federation, for example, expenditure on non-tertiary education as a share of GDP
increased by at least 6% over this period. Over the same period, Lithuania, Luxembourg, Mexico, Portugal and Slovenia
experienced some of the largest decreases in the share of expenditure on these educational levels (over 11%), mainly
explained by a decrease in public expenditure (Table C2.3).
At the tertiary level, about one-fifth of countries with available data increased their investment in tertiary education relative to
GDP between 2012 and 2017, even though their spending at non-tertiary levels declined or remained fairly stable. Clear
examples of this trend are Chile, Luxembourg and the United Kingdom, which increased the share of GDP invested in tertiary
educational institutions by over 10% but reduced the share invested in non-tertiary educational institutions by at least 2%
during this period (Table C2.3).

Definitions
Expenditure on educational institutions refers to public, private and international expenditure on entities that provide
instructional services to individuals or education-related services to individuals and other educational institutions (schools,
universities and other public and private institutions).
Initial public spending includes both direct public expenditure on 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 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 institutions such as research grants or other
funds from international sources paid directly to educational institutions.
Public subsidies to households and other private entities for educational institutions include public and international
transfers, such as scholarships and other financial aid to students, plus certain subsidies to other private entities. Therefore,
they are composed of government transfers and certain other payments to households, insofar as these translate into
payments to educational institutions for educational services (for example, fellowships, financial aid or student loans for
tuition). They also include government transfers and some other payments (mainly subsidies) to other private entities,
including subsidies to firms or labour organisations that operate apprenticeship programmes and interest subsidies to private
financial institutions that provide student loans, etc.
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.

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290  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 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/10.1787/69096873-en).

Source
Data refer to the financial year 2017 (unless otherwise specified) and are based on the UNESCO, OECD and Eurostat (UOE)
data collection on education statistics administered by the OECD in 2019 (for details see Annex 3 at
https://doi.org/10.1787/69096873-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 2012 to 2017 were updated based on a survey in 2019-20, and expenditure figures for
2005 to 2017 were adjusted to the methods and definitions used in the current UOE data collection.

References

OECD (2018), OECD Handbook for Internationally Comparative Education Statistics 2018, OECD Publishing,
Paris, https://doi.org/10.1787/9789264304444-en (accessed on 16 April 2020).

[1]

EDUCATION AT A GLANCE 2020 © OECD 2020

C2. WHAT PROPORTION OF NATIONAL WEALTH IS PENT ON EDUCATIONAL INSTITUTIONS?  291

Indicator C2 Tables
Table C2.1

Total expenditure on educational institutions as a percentage of GDP (2017)

Table C2.2

Total expenditure on educational institutions as a percentage of GDP, by source of funds (2017)

Table C2.3

Index of change in total expenditure on educational institutions as a percentage of GDP (2005, 2012
and 2017)

WEB Table C2.4

Index of change in public expenditure on educational institutions as a percentage of GDP (2005, 2012
and 2017)

Cut-off date for the data: 19 July 2020. Any updates on data can be found on line at http://dx.doi.org/10.1787/eag-dataen. More breakdowns can also be found at http://stats.oecd.org/, Education at a Glance Database.
StatLink: https://doi.org/10.1787/888934164446

EDUCATION AT A GLANCE 2020 © OECD 2020

292  C2. WHAT PROPORTION OF NATIONAL WEALTH IS SPENT ON EDUCATIONAL INSTITUTIONS?
Table C2.1. Total expenditure on educational institutions as a percentage of GDP (2017)
Direct expenditure within educational institutions, by level of education

Lower secondar y

General
programmes

Vocation al
programmes

All programmes

All secondar y

Post-secondar y nonter tiar y

Primary, secondar y and
post-secon dar y nonter tiar y

Shor t-cycle tertiary

Long-cycle ter tiar y

All ter tiar y

All ter tiar y
(excluding R&D)

Primary to ter tiary

Primary to ter tiary
(excluding R&D)

Tertiar y

Primary

Secondar y

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

(13)

(14)

1.8
0.9
1.6
2.2 d
1.8
2.0
m
0.8
2.0
1.5
1.3
1.2
0.7
1.3
0.7
2.2
1.2
2.5
1.0
1.1
1.5
1.4
0.8
1.1
1.6
1.2
1.8
2.2
1.6
1.6
0.9
1.5
1.3
1.9
m
0.9
1.9
1.7

1.3
1.2
0.9
x(1)
0.6
2.1
m
1.0
1.0
0.7
1.1
1.3
1.2
0.7
0.7
1.0
0.6
x(3, 4, 5)
0.7
0.7
0.8
0.7
1.0
0.8
0.8
1.2
1.3
1.0
0.7
1.2
0.9
0.8
0.8
0.9
m
1.0
1.0
0.9

0.6
0.3
0.7 d
x(5)
0.9
x(5)
m
0.2
x(5)
0.4
0.3
0.8
0.4
0.5
0.7
0.8
x(5)
1.4 d
x(5)
x(5)
x(5)
0.5
0.3
0.3
0.5
0.3
1.0
0.8
0.3
x(5)
0.3
0.3
0.6
0.6
x(5)
0.7
0.9
x(5)

0.2
0.6
1.0 d
x(5)
0.3
x(5)
m
0.7
x(5)
0.3
0.9 d
0.5
0.5
0.3
0.4
0.4
x(5)
0.9 d
x(5)
x(5)
x(5)
0.4
0.1
0.5
0.3
0.8
0.3
0.7
0.5
x(5)
0.6
0.6
0.3 d
0.5
x(5)
0.7
0.5
x(5)

0.8
0.9
1.7 d
1.4
1.2
0.6
m
0.9
0.9
0.7
1.2 d
1.2
0.9
0.7
1.1
1.2
0.5
2.2 d
1.2 d
0.8 d
1.1
0.8
0.4
0.9
0.8
1.2
1.4
1.5
0.8
1.2 d
0.8
0.9
0.9 d
1.1
1.3 d
1.5
1.4
1.0

2.0
2.1
2.6 d
1.4
1.8
2.7
m
1.8
1.8
1.3
2.3 d
2.5
2.1
1.4
1.8
2.2
1.1
2.2
1.9 d
1.5 d
2.0
1.5
1.5
1.6
1.6
2.3
2.7
2.4
1.5
2.4 d
1.7
1.7
1.7 d
2.0
m
2.4
2.4
1.9

0.1
0.0
x(3, 4, 5, 6)
m
a
m
a
0.0
a
0.1
x(4, 5, 6)
0.0
0.2
m
0.3
0.1
0.2
0.0
x(5, 6)
x(5, 6, 9, 10, 11)
a
0.1
0.1
0.0
a
a
0.1
0.0
0.0
x(5, 6)
0.0
a
x(4, 5, 6)
0.0
x(5)
a
a
0.0

4.0
3.1
4.2
3.6 d
3.6
4.7
m
2.7
3.8
2.9
3.6
3.7
3.0
m
2.9
4.5
2.5
4.7
3.0
2.6
3.5
2.9
2.4
2.7
3.2
3.5
4.6
4.7
3.1
4.0
2.7
3.2
3.0
3.9
m
3.3
4.3
3.6

0.2
0.3
0.0
0.6
0.4
x(11)
m
0.0
0.2
a
a
0.3
0.0
a
0.0
0.0
x(11)
0.2
0.0
0.2 d
0.2
0.1
a
0.0
x(11)
0.0
0.2
0.0
0.0
0.0
0.0
0.0
0.2
0.0
m
x(11)
0.1
x(11)

1.8
1.5
1.5
1.7
2.3
x(11)
m
0.9
1.5
1.5
1.6
1.1
1.2
0.8
1.1
1.3
x(11)
1.3
0.9
1.2 d
1.4
0.9
1.0
0.5
x(11)
1.7
1.5
1.9
1.2
1.1
0.9
1.0
1.1
1.5
m
x(11)
1.8
x(11)

2.0
1.7
1.5
2.3
2.7
0.8
m
0.9
1.7
1.5
1.6
1.5
1.2
0.8
1.1
1.3
0.9
1.5
0.9
1.4 d
1.6
1.1
1.0
0.5
1.2
1.7
1.7
2.0
1.2
1.2
1.0
1.0
1.3
1.6
m
1.7
2.0
2.6

1.4
1.2
1.0
m
2.6
0.4
m
0.6
0.8
1.0
0.9
1.0
0.7
0.5
0.9
m
0.9
1.0
0.6
m
1.2
0.8
0.8
0.3
1.0
1.1
1.4
1.1
0.9
0.9
0.7
0.8
0.9
0.7
m
1.4
1.6
2.3

6.0
4.8
5.7
5.9 d
6.3
5.5
m
3.6
5.5
4.4
5.2
5.2
4.2
m
3.9
5.8
3.4
6.2
3.9
4.0
5.0
4.0
3.4
3.2
4.4
5.2
6.3
6.6
4.3
5.2
3.6
4.2
4.3
5.4
m
5.0
6.3
6.1

5.4
4.3
5.1
m
6.2
5.1
m
3.3
4.6
3.9
4.5
4.7
3.7
m
3.8
m
3.4
5.7
3.6
m
4.7
3.8
3.2
3.1
4.2
4.6
6.0
5.8
4.0
4.9
3.4
4.0
4.0
4.6
m
4.7
5.8
5.8

1.5
1.3

1.0
0.9

0.6
0.5

0.5
0.5

1.1
1.0

1.9
1.9

m
m

3.5
3.2

0.1
0.1

1.3
1.2

1.4
1.2

1.0
0.9

4.9
4.5

4.5
4.1

m
m
m
m
m
m
m
m
m
m
x(3, 4, 5, 6) x(3, 4, 5, 6)
m
m
m
m

m
m
m
m
m
2.3 d
m
m

m
m
m
m
m
0.1 d
m
m

m
m
m
m
m
2.4 d
m
m

m
m
m
m
m
2.4 d
m
m

a
m
m
m
a
x(3, 4, 5, 6)
m
m

m
m
m
m
m
2.4
m
m

m
m
m
m
m
0.2
m
m

m
m
m
m
m
0.9
m
m

m
m
m
m
m
1.1
m
m

m
m
m
m
m
1.0
m
m

m
m
m
m
m
3.4
m
m

m
m
m
m
m
3.3
m
m

m

m

m

m

m

m

m

m

m

m

m

m

Par tners

OECD

Upper secondary

Countries
Australia
Austria
Belgium
Canada 1, 2
Chile
Colombia 2, 3
Costa Rica 3
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungar y
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Lithuania
Luxembourg
Mexico
Netherlands
New Zealand
Nor way
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
Unite d Kingdom
United States
OECD average
EU23 average
Argentina
Brazil
China
India
Indonesia 3
Russian Federation
Saudi Arabia
South Africa
G20 average

m

m

Note: See Definitions and Methodology sections for more information. Data and more breakdowns available at http://stats.oecd.org/, Education at a Glance Database.
1. Primary education includes pre-primary programmes.
2. Post-secondary non-tertiary figures are treated as negligible.
3. Year of reference 2018.
Source: OECD/UIS/Eurostat (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888934164465
EDUCATION AT A GLANCE 2020 © OECD 2020

C2. WHAT PROPORTION OF NATIONAL WEALTH IS PENT ON EDUCATIONAL INSTITUTIONS?  293

Table C2.2. Total expenditure on educational institutions as a percentage of GDP, by source of funds (2017)
Direct expenditure within educational institutions, by level of education
Primary, secondary
and post-secondary non-tertiary

International

Public

Private

International

Public

Private

International

Public

Private

International

Public

Private

International

Final funds
(after transfers
between public and
private sectors)

Private

Initial funds
(before transfers
between public and
private sectors)

Public

Final funds
(after transfers
between public and
private sectors)

International

Initial funds
(before transfers
between public and
private sectors)

Private

Final funds
(after transfers
between public and
private sectors)

Primary to tertiary

Public
Partners

OECD

Initial funds
(before transfers
between public and
private sectors)

Tertiary

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

(13)

(14)

(15)

(16)

(17)

(18)

Countries
Australia
Austria
Belgium
Canada 1
Chile
Colombia 2
Costa Rica 2
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Lithuania
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United Kingdom
United States 3

3.3
3.0
4.1
m
3.0
m
m
2.5
3.7
2.5
3.6
3.5
m
m
m
4.4
2.2
4.3
2.8
m
3.1
m
2.2
2.6
2.9
m
3.9
4.7
2.7
3.5
2.5
2.9
2.6
3.9
3.2
2.4
3.7
m

0.7
0.1
0.1
m
0.6
m
m
0.2
0.1
0.1
0.0
0.3
m
m
m
0.2
0.3
0.5
0.2
m
0.4 d
m
0.1
0.1
0.3
m
0.7
0.0
0.3
0.4
0.1
0.3
0.4
a
m
0.9
0.6
m

0.0
a
0.0
m
a
0.0
m
0.0
0.0
0.2
0.0
0.0
m
0.0
0.0
0.0
0.0
0.0
0.0
0.0
x(2)
0.1
0.0
0.1
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
a
0.0
0.0
0.0
a

3.2
2.9
4.0
3.3 d
3.0
3.1
4.0
2.5
3.7
2.8
3.6
3.4
2.6
2.5
2.6
4.4
2.2
4.2
2.8
2.4
3.0
2.8
2.3
2.6
2.8
3.0
3.8
4.7
2.8
3.5
2.5
2.9
2.6
3.9
3.2
2.4
3.6
3.2

0.7
0.1
0.1
0.3 d
0.6
1.6
m
0.2
0.1
0.1
0.0
0.3
0.4
m
0.2
0.2
0.3
0.5
0.2
0.2
0.4 d
0.1
0.1
0.1
0.4
0.4
0.8
0.0
0.3
0.4
0.2
0.3
0.4
a
m
0.9
0.7
0.3

0.0
a
0.0
x(5)
a
0.0
m
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
x(5)
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
a
0.0
0.0
0.0
a

1.1
1.6
1.3
m
1.2
m
m
0.7
1.6
0.9
1.4
1.2
m
0.6
m
1.2
0.8
m
0.7
m
0.8
m
0.6
0.4
0.9
m
1.1
1.8
1.1
0.7
0.6
0.8
0.9
1.3
1.3
1.3
1.0
m

0.9 d
0.1
0.2
m
1.5
m
m
0.2
0.0
0.2
0.1
0.3
m
0.1
m
0.1
0.1
m
0.2
m
0.7 d
m
0.3
0.0
0.3
m
0.6
0.1
0.1
0.4
0.2
0.1
0.4
0.2
m
0.3
0.9
m

x(8)
a
0.1
m
a
0.0
m
0.0
0.0
0.3
0.1
0.0
m
0.1
0.0
0.0
0.0
0.0
0.0
0.0 d
x(8)
0.1
0.1
0.0
0.0
0.1
0.0
0.0
0.0
0.1
0.1
0.1
0.0
0.1
0.0
0.0
0.1
a

0.7
1.6
1.2
1.2
1.0
0.8
1.6
0.7
1.6
1.1
1.4
1.1
1.0
0.6
0.7
1.2
0.6
0.8
0.6
0.4 d
0.6
0.6
0.7
0.4
0.8
1.1
0.9
1.8
1.0
0.7
0.7
0.9
0.8
1.3
1.3
1.3
0.5
0.9

1.3 d
0.2
0.2
1.1 d
1.7
0.0
m
0.2
0.0
0.2
0.1
0.3
0.2
0.1
0.4
0.1
0.3
0.7
0.3
1.0 d
1.0 d
0.3
0.3
0.0
0.4
0.5
0.9
0.1
0.2
0.4
0.3
0.1
0.4
0.2
m
0.3
1.4
1.7

x(11)
a
0.0
x(11)
a
0.0
m
0.0
0.0
0.2
0.1
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0 d
x(11)
0.1
0.1
0.0
0.0
0.1
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.1
0.0
0.0
0.1
a

4.4
4.5
5.4
m
4.2
m
m
3.2
5.4
3.5
5.0
4.6
m
m
m
5.5
3.0
m
3.4
m
3.9
m
2.8
3.0
3.7
m
5.0
6.5
3.8
4.2
3.1
3.7
3.5
5.2
4.6
3.8
4.7
m

1.6 d
0.2
0.2
m
2.1
m
m
0.4
0.1
0.3
0.1
0.5
m
m
m
0.3
0.3
m
0.4
m
1.1 d
m
0.4
0.1
0.7
m
1.3
0.1
0.4
0.8
0.4
0.4
0.8
0.2
m
1.2
1.5
m

x(14)
a
0.1
m
a
0.0
m
0.0
0.0
0.6
0.1
0.0
m
0.1
0.0
0.0
0.0
0.0
0.1
0.0
x(14)
0.2
0.2
0.1
0.0
0.1
0.0
0.0
0.1
0.1
0.1
0.1
0.0
0.1
0.0
0.0
0.1
a

3.9
4.5
5.2
4.5 d
4.0
3.8
5.6
3.2
5.4
3.8
5.0
4.5
3.6
3.1
3.3
5.5
2.8
5.0
3.3
2.9
3.6
3.4
2.9
3.0
3.7
4.2
4.7
6.4
3.7
4.2
3.1
3.8
3.5
5.2
4.5
3.8
4.1
4.2

2.0 d
0.3
0.4
1.4 d
2.4
1.6
m
0.4
0.1
0.3
0.1
0.7
0.6
m
0.6
0.3
0.5
1.2
0.5
1.2
1.4 d
0.5
0.4
0.1
0.7
0.9
1.6
0.2
0.5
0.8
0.5
0.4
0.8
0.2
m
1.2
2.1
2.0

x(17)
a
0.1
x(17)
a
0.0
m
0.0
0.0
0.2
0.1
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.1
0.0
x(17)
0.1
0.1
0.1
0.0
0.1
0.0
0.0
0.1
0.1
0.0
0.1
0.0
0.1
0.0
0.0
0.1
a

OECD average
EU23 average

3.2
3.0

0.3
0.2

0.0
0.0

3.1
3.0

0.3
0.3

0.0
0.0

1.0
1.0

0.3
0.2

0.1
0.1

1.0
0.9

0.4
0.3

0.0
0.1

4.2
4.0

0.6
0.4

0.1
0.1

4.1
3.9

0.8
0.6

0.0
0.1

Argentina
Brazil
China
India
Indonesia 2
Russian Federation
Saudi Arabia
South Africa

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

3.7
4.0
m
m
m
2.3
m
4.1

m
m
m
m
m
0.1
m
m

a
m
m
m
m
0.0
m
m

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

1.2
1.1
m
m
m
0.7
m
0.6

m
m
m
m
m
0.3
m
m

a
m
m
m
m
0.0
m
m

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

4.9
5.1
m
m
m
3.0
m
4.7

m
m
m
m
m
0.4
m
m

a
m
m
m
m
0.0
m
m

G20 average

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

Note: Some levels of education are included with others. Refer to "x" code in Table 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, secondary and post-secondary non-tertiary education includes pre-primary programmes.
2. Year of reference 2018.
3. Figures are for net student loans rather than gross, thereby underestimating public transfers.
Source: OECD/UIS/Eurostat (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888934164484

EDUCATION AT A GLANCE 2020 © OECD 2020

294  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, 2012 and 2017)
GDP deflator 2015 = 100, constant prices, by level of education
Primar y, secondar y
and post-secondary
non-tertiar y

Tertiar y

Primar y to tertiar y

GDP

Par tners

OECD

Change in total expenditure Change in total expenditure
Change in total expenditure
on educational institutions on educational institutions Change in total expenditure on educational institutions
as a percentage of GDP
as a percentage of GDP on educational institutions as a percentage of GDP
(2015 = 100)
(2015 = 100)
(2015 = 100)
(2015 = 100)

Change in GDP
(2015 = 100)

2005

2012

2017

2005

2012

2017

2005

2012

2017

2005

2012

2017

2005

2012

2017

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

(13)

(14)

(15)

Countries
Australia
Austria
Belgium
Canada1
Chile
Colombia
Costa Rica
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungar y
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Lithuania
Luxembourg
Mexico
Netherlands
New Zealand
Nor way
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
Unite d Kingdom
United States

m
m
97.3
98.1 d
114.2
m
m
104.4
m
117.9
93.1
103.9
109.5
96.3
118.5
117.3
m
83.5
99.9
99.0
m
99.1
m
m
99.2
98.6
m
105.2
114.8
90.6
99.0
125.9
92.4
110.7
m
m
93.4
108.3

m
100.0
103.4
103.0 d
118.4
97.2
m
104.0
m
109.1
98.7
101.4
104.5
101.5
90.7
100.7
m
101.5
98.4
103.0
m
85.3
114.0
112.0
99.0
103.2
104.2
99.2
106.3
114.4
92.9
112.3
101.4
101.5
m
101.1
99.5
103.6

101.4
98.1
99.4
101.8 d
114.3
99.3
m
101.4
m
100.0
91.5
100.3
99.4
m
100.6
102.3
96.8
105.6
98.3
95.0
m
88.6
97.3
93.3
83.1
96.7
97.1
100.7
96.3
101.3
94.9
97.7
98.5
107.3
m
100.4
97.1
101.6

m
m
84.6
99.1
95.3
m
m
82.5
m
65.4
96.6
88.7
83.9
148.3
124.2
95.8
m
110.2
91.3
100.0 d
m
93.7
89.3
m
81.2
84.3
m
m
114.4
98.5 d
57.3
122.3
85.1
96.3
m
m
m
95.0

m
100.2
96.8
104.0
121.5
108.2
m
124.4
m
91.0
107.4
98.7
99.7
91.5
141.9
104.2
m
116.3
101.7
103.6 d
m
91.1
115.7
79.5
92.3
97.4
102.1
90.6
96.0
104.3 d
65.4
116.8
98.9
104.0
m
104.5
93.0
107.6

99.0
98.1
102.9
94.0
134.8
95.7
m
81.8
m
85.8
91.6
99.6
99.5
80.8
124.7
102.7
90.4
102.7
97.4
96.8 d
91.0
70.4
68.7
92.5
84.4
98.7
94.9
112.0
86.2
91.0 d
61.7
99.9
97.6
98.0
m
94.1
103.1
100.9

m
m
81.9
79.7 d
73.4
m
m
79.7
m
84.7
89.6
90.9
88.3
136.4
109.4
92.7
m
61.2
102.8
96.0
m
83.8
m
m
75.8
84.5
m
m
78.3
93.7
58.4
111.7
86.1
87.2
m
m
m
86.9

m
98.4
97.6
95.3 d
110.4
96.0
m
102.4
m
96.3
102.1
98.0
98.7
101.9
93.1
91.1
m
94.9
100.3
101.5
m
80.9
104.8
95.0
90.3
98.1
96.2
91.3
94.9
110.1
76.6
109.1
97.0
94.3
m
84.5
90.8
97.9

104.7
102.6
103.8
98.4 d
125.9
99.0
m
102.1
m
102.7
96.8
103.4
104.2
m
113.3
114.0
106.5
112.9
101.1
99.3
m
87.6
92.4
99.2
87.7
102.4
102.1
106.8
100.9
104.3
87.4
106.2
104.1
109.5
m
108.9
102.0
105.2

m
m
94.1
98.5 d
106.8
m
m
97.7
m
98.2
94.2
99.6
102.1
109.7
119.8
112.6
m
90.0
97.9
99.4
m
97.4
m
m
94.4
94.0
m
m
114.7
92.6
84.2
125.1
90.2
106.3
m
m
m
102.7

m
100.1
101.7
103.4 d
119.6
108.2
m
110.2
m
102.4
101.3
100.6
103.1
98.9
102.7
101.4
m
105.1
99.2
103.2
m
87.1
114.6
107.1
97.2
101.3
103.6
96.8
103.2
111.9
83.1
113.4
100.7
102.3
m
102.3
97.6
105.3

100.6
98.1
100.3
98.6 d
122.3
95.7
m
95.5
m
94.7
91.5
100.1
99.5
m
106.2
102.4
95.0
104.9
98.1
95.6
m
82.9
86.4
93.1
83.4
97.4
96.5
103.8
93.3
98.7
83.1
98.2
98.2
104.4
m
98.2
98.9
101.3

73.7
88.9
87.1
80.9
68.7
63.9
66.1
81.6
92.8
86.3
95.1
91.2
86.5
124.4
91.3
82.3
70.7
68.0
105.0
96.7
69.7
86.1
78.5
76.9
80.3
90.0
79.8
78.9
68.3
101.3
69.3
89.3
95.5
82.0
82.7
60.5
86.5
84.6

92.6
98.3
96.0
92.2
92.3
88.7
91.2
92.9
95.3
94.1
100.7
97.4
95.7
103.0
90.6
89.8
72.6
90.3
101.1
98.4
91.4
92.9
91.4
88.7
92.9
96.8
92.8
94.3
91.9
98.4
92.2
96.2
96.4
92.2
94.6
82.6
93.1
93.0

104.1
104.6
103.5
99.8
103.0
103.5
107.8
106.9
105.3
108.5
105.8
103.4
104.8
101.3
106.6
111.3
112.1
107.7
103.0
103.8
106.2
105.6
106.9
106.5
105.1
105.2
105.9
102.9
108.2
105.6
105.2
108.1
106.0
104.9
103.6
110.9
103.2
103.9

OECD average
EU23 average

103.5
103.6

102.7
102.6

98.7
97.8

95.3
94.8

102.2
100.7

94.9
91.8

88.1
91.0

96.6
97.2

102.9
101.5

100.9
101.0

102.8
102.0

97.5
95.9

83.2
88.0

93.3
94.3

105.5
105.7

Argentina
Brazil
China
India
Indonesia
Russian Federation
Saudi Arabia
South Africa

m
m
m
m
m
90.0
m
m

m
m
m
m
m
107.5
m
m

m
m
m
m
m
122.7
m
m

m
m
m
m
m
64.2
m
m

m
m
m
m
m
110.5
m
m

m
m
m
m
m
92.6
m
m

m
m
m
m
m
62.4
m
m

m
m
m
m
m
108.4
m
m

m
m
m
m
m
113.7
m
m

m
m
m
m
m
80.4
m
m

m
m
m
m
m
108.6
m
m

m
m
m
m
m
111.5
m
m

73.2
75.9
40.1
48.3
57.7
77.6
58.6
77.0

97.5
100.1
80.9
80.9
86.0
99.8
90.2
94.7

100.5
98.2
113.9
113.8
110.4
102.0
100.9
101.8

m

m

m

m

m

m

m

m

m

m

m

m

74.9

92.7

104.7

G20 average

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, secondary and post-secondary non-tertiary education includes pre-primary programmes.
Source: OECD/UIS/Eurostat (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888934164503

EDUCATION AT A GLANCE 2020 © OECD 2020

296  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 (68%).



The share of private spending 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 8%
of total spending on tertiary institutions on average across OECD countries. However, they reach or exceed 15%
of spending in Australia, Ireland, Korea, New Zealand and the United Kingdom.

Figure C3.1. Distribution of transfers and public and private expenditure on educational institutions (2017)
Tertiary educational levels
Private expenditure
Public expenditure
Public-to-private transfers

%
100
90
80
70
60
50
40
30
20

Turkey

Portugal

Iceland

Greece

Estonia

Denmark

Czech Republic

Finland

Lithuania

Sweden

Slovenia

Luxembourg

Austria

Mexico

Norway

Spain

France

Slovak Republic

Belgium

EU23 average

OECD average

Chile

Poland

Italy

New Zealand

Korea

Australia

Ireland

0

United Kingdom

10

Note: International expenditure is aggregated with public expenditure for display purposes.
Countries are ranked in descending order of the proportion of public-to-private transfers.
Source: OECD/UIS/Eurostat (2020), Table C3.2. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2 https://doi.org/10.1787/888934164655

EDUCATION AT A GLANCE 2020 © OECD 2020

C3. HOW MUCH PUBLIC AND PRIVATE INVESTMENT IN EDUCATIONAL INSTITUTIONS IS THERE?  297

Context
Today, more people than ever before are participating in a wide range of educational programmes offered by an increasing
number of providers. 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 most at the 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, raising concerns about equity in access to education. The debate is particularly intense
over funding for tertiary education. Some stakeholders are concerned that the balance between public and private funding
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 the need for direct private spending and reduce 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 2012 and 2017, the share of expenditure coming from private sources on educational institutions from
primary to tertiary level increased by 0.5 percentage point, while the share from public sources decreased by
almost 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 7-9% of expenditure on educational institutions comes from private
sources. This share reaches 13% at upper secondary level.

EDUCATION AT A GLANCE 2020 © OECD 2020

298  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 primary to tertiary 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.
In 2017, on average across OECD countries, 83% of the funding for primary to tertiary educational institutions came directly
from public sources and 16% from private sources, being the remaining 1% from international sources (Table C3.1). However,
there are many disparities across countries. In Denmark, 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
small share of total expenditure on educational institutions. On average across OECD countries, they account for 1% of total
expenditure, reaching around 2% or more in Estonia, Latvia, Lithuania, Luxembourg, Poland and Portugal (Table C3.1).

Non-tertiary educational institutions
Public funding dominates non-tertiary education (primary, secondary and post-secondary non-tertiary) in all countries. In
2017, 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. In most countries, the largest share of private expenditure at these levels
comes from households and goes mainly towards tuition fees (Table C3.1 and Figure C3.2).
The share of private expenditure on educational institutions varies across countries and according to the level of education.
At the primary level, 7% of expenditure on educational institutions comes from private sources on average across OECD
countries. However in Norway and Sweden, all educational funding of primary institutions is public, while in Chile, Colombia,
Spain and Turkey, more than 15% of funds come from private sources (OECD, 2019[1]).
The share of private funding at the lower secondary level is similar to the share at primary level. Around 9% of educational
expenditure on lower secondary institutions is privately sourced on average across OECD countries. In around 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, Ireland and Turkey (OECD, 2019[1]).
Upper secondary education relies more on private funding than the primary and lower secondary levels, reaching an average
of 13% across OECD countries. Private sources contribute a similar share to the spending on vocational and general
programmes, at around 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
28 percentage points higher than in general education. In Germany, private companies have a long tradition of involvement
in the provision of dual training (combined work- and school-based programmes), helping to improve the availability of the
skilled individuals needed in the labour market. 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 at least 10 percentage points (OECD,
2019[1]). In several countries, the share of public funds they currently devote to vocational programmes is the result of various
national policy developments on vocational education designed to improve the transition from school to work. For example,
in the 1990s, France, the Netherlands, Norway and Spain introduced financial incentives to employers offering
apprenticenships to secondary students. As a result of these policies, programmes combining work and learning were
introduced more widely in a number of OECD countries (OECD, 1999[2])
The level of public funding in post-secondary non-tertiary education stands at only 69% on average across OECD countries.
Unlike the three lower levels presented above, post-secondary non-tertiary education in Germany, Ireland, New Zealand,
Poland and the United States relies more heavily on private than public sources of funding (OECD, 2019[1]).

EDUCATION AT A GLANCE 2020 © OECD 2020

C3. HOW MUCH PUBLIC AND PRIVATE INVESTMENT IN EDUCATIONAL INSTITUTIONS IS THERE?  299

Figure C3.2. Distribution of public and private expenditure on educational institutions (2017)
Final source of funds
All private sources
Expenditure from other private entities
Household expenditure
Public expenditure
%
100

Primary, secondary and post-secondary non-tertiary education

90
80
70
60
50
40
30
20

Turkey

Colombia3

United States1

Japan

Chile

Australia

Chile

United Kingdom

New Zealand

Korea

Spain
New Zealand

Australia

Germany

Israel

Canada

United Kingdom

Kore a

Netherlands

Italy

Mexico

Portugal

Israel

Ireland

France

OECD average

Slovenia

Poland

Canad a2

United States1

Czech Republic

Portugal

%
100

Slovak Republic

Japan

Hungary

Italy

EU23 average

Latvia

Lithuania

Austria

Estonia

Iceland

Russian Federation

Belgium

Luxembourg

Finland

Denmark

Norway

0

Sweden

10

Tertiary education

90
80
70
60
50
40
30
20

Latvia

Russian Federation

Spain

Hungary

Mexico

Netherlands
Lithuania

Slovak Republic

Ireland

OECD average

EU23 average
Czech Republic

Turkey

France

Poland

Germany

Greece

Estonia

Belgium

Slovenia

Sweden

Austria

Iceland

Norway

Luxembourg

Denmark
Finland

0

Colombia3

10

Note: International expenditure is aggregated with public expenditure for display purposes.
1. Figures are for net student loans rather than gross, thereby underestimating public transfers.
2. Primary, secondary and post-secondary non-tertiary education includes pre-primary programmes.
3. Year of reference 2018.
Countries are ranked in descending order of the proportion of public and international expenditure on educational institutions.
Source: OECD/UIS/Eurostat (2020), Table C3.1. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2 https://doi.org/10.1787/888934164674

EDUCATION AT A GLANCE 2020 © OECD 2020

300  C3. HOW MUCH PUBLIC AND PRIVATE INVESTMENT IN EDUCATIONAL INSTITUTIONS IS THERE?
Tertiary educational institutions
The high private returns to tertiary education (see Indicator A5) have led a number of countries to expect individuals to make
a greater financial contribution to their education 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 after public-toprivate transfers is far higher at tertiary level than at lower levels of education. In 2017, on average across OECD countries,
nearly 29% of total expenditure on tertiary institutions was sourced from the private sector after transfers (Table C3.1 and
Figure C3.2).
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, Denmark, 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 the relative share of public, private and international expenditure on educational
institutions (2012 and 2017)
Final source of funds; primary to tertiary education
Percentage
points
10

Public sources

Private sources

International sources

8
6
4
2
0
-2
-4
-6

United Kingdom

Spain

Lithuania

Norway

Belgium

Austria

Luxembourg

Japan

France

Netherlands

United States

Slovenia

OECD average

Italy

New Zealand

Finland

Sweden

Germany

EU23 average

Latvia

Turkey

Poland

Canada1

Israel

Iceland

Estonia

Slovak Republic

Hungary

Russian Federation

Colombia

Czech Republic

Chile

Portugal

-10

Mexico

-8

1. Primary to tertiary education includes pre-primary programmes.
Countries are ranked in descending order of the percentage-point change in the share of public expenditure on educational institutions.
Source: OECD/UIS/Eurostat (2020), Table C3.3. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2 https://doi.org/10.1787/888934164693

EDUCATION AT A GLANCE 2020 © OECD 2020

C3. HOW MUCH PUBLIC AND PRIVATE INVESTMENT IN EDUCATIONAL INSTITUTIONS IS THERE?  301

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 2012 and 2017, the share of private spending after transfers on primary to tertiary
educational institutions increased by 0.5 percentage points on average across OECD countries, while the share of public
spending fell by about the same amount. Increases in the share of private funding were observed in more than half of OECD
and partner countries, with the United Kingdom showing the largest increase (10 percentage points). In contrast, Chile
experienced the largest decrease in the share of private spending (at least 6 percentage points), balanced by an equivalent
increase from public sources (Figure C3.3).
In many OECD countries, the increase in the share of funding from private sources between 2012 and 2017 was moderate
at non-tertiary level (0.4 percentage points), the share from public sources remained stable. There are, however, some
variations across countries: in Estonia, Hungary, Latvia, Lithuania, Spain and Turkey, the share of private funding for nontertiary education increased by approximately 2 percentage points between 2012 and 2017. In other countries, large increases
were observed during the same period in the share of public funds, notably in Chile, Mexico, Portugal and the Slovak Republic,
where the increases were over 4 percentage points (Table C3.3).
At tertiary level, although the share of public funding on institutions increased in some countries between 2012 and 2017,
they have fallen below their 2012 levels in others. In many cases, these reductions have been matched by an equivalent
increase in the share of private funding. This is the case for example for Belgium, Greece, Lithuania, Norway, Spain and
the United Kingdom, where the share of public funds decreased by at least 5 percentage points in 2017 compared to 2012
but the share of private funds increased by the same amount. On the other hand, countries such as Chile, the Czech Republic,
Estonia, Hungary, Iceland, Poland, Portugal and Turkey have seen increases in the share of public funds of at least
5 percentage points (Table C3.3).

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 are not a significant feature at non-tertiary educational levels. In 2017, on average across
OECD countries, 1% of the total funds devoted to these educational levels are transfers from the public to the private sector.
France and the Slovak Republic are the only countries where this share exceeds 1% (Table C3.2). Upper secondary
education accounts for a larger share of public transfers to the private sector, reaching an average of 2% across OECD
countries, mainly driven by public-to-private transfers in vocational programmes (4%) (Table C3.2).
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 lower-income students. However,
there is no single allocation model across OECD countries (OECD, 2017[3]). 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 othersprivate 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 (Table C3.2).
In 2017, on average across OECD countries, 8% of the total funds devoted to tertiary institutions were 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 18% in Australia and the United Kingdom, both of which have high tuition fees. In contrast, public transfers
were below 1% in countries with no or lower fees, such as Austria, Denmark, Estonia, Finland, Greece, Norway, Slovenia and
Sweden. However, some countries, such as Lithuania, Portugal and Spain, have high levels of private spending (above 30%)
EDUCATION AT A GLANCE 2020 © OECD 2020

302  C3. HOW MUCH PUBLIC AND PRIVATE INVESTMENT IN EDUCATIONAL INSTITUTIONS IS THERE?
without high levels of support from the government in forms of public transfers to the private sector (below 3%) (Figure C3.1
and Table C3.2).

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 have been taken into account.
Initial public spending includes both direct public expenditure on 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.

EDUCATION AT A GLANCE 2020 © OECD 2020

C3. HOW MUCH PUBLIC AND PRIVATE INVESTMENT IN EDUCATIONAL INSTITUTIONS IS THERE?  303
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/10.1787/69096873-en).

Source
Data refer to the financial year 2017 (unless otherwise specified) and are based on the UNESCO, OECD and Eurostat (UOE)
data collection on education statistics administered by the OECD in 2019 (for details see Annex 3 at
https://doi.org/10.1787/69096873-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, 2012 to 2017 were updated based on a survey in 2019-20, and expenditure figures for
2005 to 2017 were adjusted to the methods and definitions used in the current UOE data collection.

References

OECD (2019), 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, OECD Publishing,
Paris, https://doi.org/10.1787/9789264304444-en (accessed on 16 April 2020).

[4]

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,
https://dx.doi.org/10.1787/4c4f545b-en.

[3]

OECD (1999), Implementing the OECD Jobs Strategy: Assessing Performance and Policy, The OECD Jobs
Strategy, OECD Publishing, Paris, https://dx.doi.org/10.1787/9789264173682-en.

[2]

Indicator C3 Tables
Table C3.1

Relative share of public, private and international expenditure on educational institutions, by final source
of funds (2017)

Table C3.2

Relative share of public, private and international expenditure on educational institutions, by source of
funds and public-to-private transfers (2017)

Table C3.3

Trends in the share of public, private and international expenditure on educational institutions (2005,
2012 and 2017)

Cut-off date for the data: 19 July 2020. Any updates on data can be found on line at http://dx.doi.org/10.1787/eag-dataen. More breakdowns can also be found at http://stats.oecd.org/, Education at a Glance Database.
StatLink: https://doi.org/10.1787/888934164579

EDUCATION AT A GLANCE 2020 © OECD 2020

304  C3. HOW MUCH PUBLIC AND PRIVATE INVESTMENT IN EDUCATIONAL INSTITUTIONS IS THERE?

Household
expenditure

Expenditure
by other private
entiti es

All private
sources

International sources

Expenditure
by other private
entiti es

Public sources

Household
expenditure

International sources

Public sources

All private
sources

International sources

Private sources

All private
sources

Primary to tertiary

Private sources

Expenditure
by other private
entities

Tertiary

Private sources

Household
expenditure

Primary, secondary
and post-secondary non-tertiary

Public sources
Partners

OECD

Table C3.1. Relative share of public, private and international expenditure on educational institutions, by final source of funds (2017)
After transfers between public and private sectors, by level of education

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

Countries
Australia
Austria
Belgium
Canada 1
Chile
Colombia 2
Costa Rica 2
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Lithuania
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United Kingdom
United States

(9)

(10)

(11)

(12)

(13)

(14)

(15)

81
96
96
91 d
83
65
m
92
98
95
99
91
87
m
92
96
89
89
94
92
87
95
95
94
89
87
83
99
89
89
92
91
87
100
m
73
84
91

17
3
3
4d
16
35
m
6
2
3
1
8
x(4)
m
x(4)
3
7
8
5
6
11
3
3
2
11
5
12
1
9
11
6
9
12
a
m
14
11
9

2
1
0
6d
2
0
m
2
0
1
0
1
x(4)
m
x(4)
0
4
3
0
2
2d
2
2
0
0
8
5
0
0
0
2
0
1
a
m
13
4
0

19
4
3
9d
17
35
m
8
2
4
1
9
13
m
8
4
11
11
5
8
13 d
5
5
3
11
13
17
1
9
11
8
9
13
a
m
27
15
9

0
a
1
x(3, 4)
a
0
m
0
0
0
0
0
0
m
0
0
0
0
1
0
x(3, 4)
0
0
3
0
0
0
0
2
0
0
0
0
a
m
0
0
a

36
91
82
54
36
100
m
73
99
72
92
77
83
77
65
90
67
54
62
31 d
38
60
64
89
70
67
51
92
81
60
68
83
66
84
m
80
25
35

49
3
8
22
58
0
m
9
0
7
0
11
x(9)
15
x(9)
7
26
28
29
53 d
43
28
22
3
30
17
33
4
15
29
15
11
29
1
m
11
52
45

15
6
6
24 d
7
0
m
14
1
8
3
10
x(9)
a
x(9)
1
2
17
6
16 d
19 d
5
8
3
0
13
16
3
4
4
14
2
3
11
m
9
19
19

64
9
14
46 d
64
0
m
23
1
15
4
21
15
15
33
8
29
46
35
69 d
62 d
33
30
6
30
30
49
7
19
33
29
13
32
12
m
20
71
65

x(8, 9)
a
3
x(8, 9)
a
0
m
4
0
13
5
2
2
8
2
2
4
0
3
0d
x(8, 9)
8
6
5
0
3
0
1
1
7
3
4
2
4
m
1
4
a

66
94
92
76 d
63
70
m
87
98
88
97
87
86
m
85
95
83
81
86
71
72
85
86
94
84
80
74
97
87
82
86
89
81
95
m
75
66
68

28
3
4
11 d
34
30
m
7
2
5
1
9
x(14)
m
x(14)
4
12
13
11
22
21
10
9
3
16
9
18
2
10
15
8
9
17
0
m
13
24
24

6
3
2
13 d
4
0
m
5
0
3
1
4
x(14)
m
x(14)
0
3
7
2
7
7d
3
4
0
0
10
8
1
1
1
6
1
2
3
m
11
9
8

34
6
6
24 d
37
30
m
12
2
8
2
13
14
m
15
5
16
19
12
29
28 d
12
12
3
16
18
26
2
12
16
14
10
19
3
m
24
33
32

x(13, 14)
a
1
x(13, 14)
a
0
m
1
0
5
1
1
1
m
1
0
1
0
1
0
x(13, 14)
2
2
3
0
1
0
0
2
2
1
1
0
1
m
0
1
a

OECD average
EU23 average

90
92

8
6

2
2

10
7

0
0

68
73

21
16

9
7

29
22

3
4

83
87

12
8

4
3

16
12

1
1

Argentina
Brazil
China
India
Indonesia 2
Russian Federation
Saudi Arabia
South Africa

m
m
m
m
m
96
m
m

m
m
m
m
m
3
m
m

m
m
m
m
m
1
m
m

m
m
m
m
m
4
m
m

a
m
m
m
m
0
m
m

m
m
m
m
m
66
m
m

m
m
m
m
m
21
m
m

m
m
m
m
m
12
m
m

m
m
m
m
m
33
m
m

a
m
m
m
m
1
m
m

m
m
m
m
m
87
m
m

m
m
m
m
m
8
m
m

m
m
m
m
m
4
m
m

m
m
m
m
m
13
m
m

a
m
m
m
m
0
m
m

G20 average

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

d

d

d

d

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, secondary and post-secondary non-tertiary education includes pre-primary programmes.
2. Year of reference 2018.
3. Figures are for net student loans rather than gross, thereby underestimating public transfers.
Source: OECD/UIS/Eurostat (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888934164598

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C3. HOW MUCH PUBLIC AND PRIVATE INVESTMENT IN EDUCATIONAL INSTITUTIONS IS THERE?  305

Table C3.2. Relative share of public, private and international expenditure on educational institutions, by source of funds and
public-to-private transfers (2017)
By level of education and source of funding
Primary, secondary and post-secondary
non-tertiary

Tertiary

Public-to-private
transfers

Public

Private

(5)

(6)

(7)

(8)

(9)

82
97
97
m
83
m
m
92
98
88
99
93
m
m
m
96
89
90
94
m
88
m
94
95
90
m
84
100
87
89
93
90
87
100
m
73
86
m

18
3
2
m
17
m
m
8
2
4
1
7
m
m
m
4
11
10
5
m
12 d
m
4
3
10
m
16
0
9
11
5
9
13
a
m
27
14
m

0
a
1
m
a
0
m
0
0
8
0
0
m
m
0
0
0
0
1
0
x(2)
2
1
3
0
0
0
0
4
0
2
1
0
a
m
0
0
a

81
96
96
91 d
83
65
m
92
98
95
99
91
87
m
92
96
89
89
94
92
87
95
95
94
89
87
83
99
89
89
92
91
87
100
m
73
84
91

19
4
3
9d
17
35
m
8
2
4
1
9
13
m
8
4
11
11
5
8
13 d
5
5
3
11
13
17
1
9
11
8
9
13
a
m
27
15
9

0
a
1
x(5)
a
0
m
0
0
0
0
0
0
m
0
0
0
0
1
0
x(5)
0
0
3
0
0
0
0
2
0
0
0
0
a
m
0
0
a

1
1
1
m
0
m
m
0
0
0
0
2
m
m
m
0
0
1
0
m
1
m
0
0
1
m
1
0
0
0
3
0
0
a
m
0
1
m

55
92
87
m
46
m
m
73
99
64
92
80
m
76
m
90
89
m
73
m
54
m
58
89
71
m
66
94
91
58
67
80
69
84
m
80
51
m

OECD average
EU23 average

91
93

8
6

1
1

90
92

10
7

0
0

1
1

Argentina
Brazil
China
India
Indonesia 2
Russian Federation
Saudi Arabia
South Africa

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

m
m
m
m
m
96
m
m

m
m
m
m
m
4
m
m

a
m
m
m
m
0
m
m

G20 average

m

m

m

m

m

m

Public-to-private
transfers

International

(4)

International

Private

(3)

(13)

(14)

64
9
14
46 d
64
0
m
23
1
15
4
21
15
15
33
8
29
46
35
69 d
62 d
33
30
6
30
30
49
7
19
33
29
13
32
12
m
20
71
65

x(12)
a
3
x(12)
a
0
m
4
0
13
5
2
2
8
2
2
4
0
3
0d
x(12)
8
6
5
0
3
0
1
1
7
3
4
2
4
m
1
4
a

19
1
4
m
10
m
m
0
0
0
0
3
m
0
m
0
23
m
11
m
16
m
0
1
2
m
15
2
10
0
4
0
2
0
m
0
26
m

68
73

29
22

3
4

8
6

m
m
m
m
m
m
m
m

m
m
m
m
m
66
m
m

m
m
m
m
m
33
m
m

a
m
m
m
m
1
m
m

m
m
m
m
m
m
m
m

m

m

m

m

m

Private

Public

(2)

Public

International

(1)
Countries
Australia
Austria
Belgium
Canada 1
Chile
Colombia 2
Costa Rica 2
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Lithuania
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United Kingdom
United States3

International

Private

Initial funds
Final funds
(before transfers between (after transfers between public
public and private sectors)
and private sectors)

Public
Partners

OECD

Initial funds
Final funds
(before transfers between (after transfers between public
public and private sectors)
and private sectors)

(10)

(11)

(12)

45
8
10
m
54
m
m
23
1
15
3
18
m
15
m
8
6
m
24
m
46 d
m
30
5
28
m
34
5
8
33
25
13
30
11
m
20
45
m

9
a
3
m
a
0
m
4
0
22
5
2
m
10
2
2
4
0
3
0d
x(9)
14
12
5
0
3
0
1
1
9
8
7
2
4
m
1
4
a

36
91
82
54
36
100
m
73
99
72
92
77
83
77
65
90
67
54
62
31 d
38
60
64
89
70
67
51
92
81
60
68
83
66
84
m
80
25
35

75
77

21
17

4
6

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

m
m
m
m
m
m
m
m

m

m

m

d

d

Note: See Definitions and Methodology sections for more information. Relative share of public, private and international expenditure on primary to tertiary education (i.e.
Columns 15 to 21) are available for consultation on line (see StatLink below). Data and more breakdowns available at http://stats.oecd.org/, Education at a Glance Database.
1. Primary to tertiary education includes pre-primary programmes (Columns 15 to 21, available on line).
2. Year of reference 2018.
3. Figures are for net student loans rather than gross, thereby underestimating public transfers.
Source: OECD/UIS/Eurostat (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888934164617

EDUCATION AT A GLANCE 2020 © OECD 2020

306  C3. HOW MUCH PUBLIC AND PRIVATE INVESTMENT IN EDUCATIONAL INSTITUTIONS IS THERE?
Table C3.3. Trends in the share of public, private and international expenditure on educational institutions (2005, 2012 and 2017)
Final source of funds
Primary to tertiary

Partners

OECD

2017
(3)

(4)

2005
(5)

2012
(6)

2017
(7)

Countries
Australia
Austria
Belgium
Canada 1
Chile
Colombia
Costa Rica
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Lithuania
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United Kingdom
United States 2

m
m
93
75 d
50
m
m
88
98
91
98
89
86
94
91
95
m
82
94
70
m
83
m
m
80
83
m
m
91
m
83
87
89
96
m
m
m
72

m
96
94
75 d
57
45
m
83
m
85
97
88
86
89
81
94
m
79
87
72
m
85
88
95
79
81
74
99
86
72
84
89
84
96
91
75
76
68

66
94
92
76 d
63
49
m
87
98
88
97
87
86
m
85
95
83
81
86
71
72
85
86
94
84
80
74
97
87
82
86
89
81
95
m
75
66
68

m
-2
-2
1d
6
4
m
4
m
2
0
-1
0
m
4
1
m
1
0
-1
m
0
-2
-1
4
-1
0
-2
1
10
2
0
-3
0
m
0
-10
0

m
m
6
24 d
50
m
m
12 d
2d
8d
2d
11
14
6d
9
5d
m
18
9d
30
m
15
m
m
20
17
m
m
9d
m
16 d
12
11
3
m
m
m
28

m
4
5
24 d
43
55
m
12
m
6
2
12
14
9
19
5
m
21
11
28
m
13
11
3
21
18
26
1
12
20
16
10
16
3
m
25
23
32

OECD average
EU23 average

86
90

83
87

82
87

0
0

14
10

Argentina
Brazil
China
India
Indonesia
Russian Federation
Saudi Arabia
South Africa

m
m
m
73
m
m
m
m

m
m
m
m
m
84
m
m

m
m
m
m
m
87
m
m

m
m
m
m
m
3
m
m

G20 average

m

m

m

m

Percentagepoint difference
between 2012
and 2017

2012
(2)

Share of international expenditure
on educational institutions (%)

Percentagepoint difference
between 2012
and 2017

2005
(1)

Share of private expenditure
on educational institutions (%)

Percentagepoint difference
between 2012
and 2017

Share of public expenditure
on educational institutions (%)

(8)

2005
(9)

2012
(10)

2017
(11)

34
6
6
24 d
37
51
m
12
2
8
2
13
14
m
15
5
16
19
12
29
28 d
12
12
3
16
18
26
2
12
16
14
10
19
3
m
24
33
32

m
2
1
-1 d
-6
-4
m
0
m
2
0
1
0
m
-4
0
m
-1
1
1
m
0
1
1
-4
0
0
1
0
-4
-2
0
3
0
m
0
10
0

m
a
1
x(5)
a
m
m
x(5)
x(5)
x(5)
x(5)
0
0
x(5)
0
x(5)
m
0
x(5)
0
m
2
m
m
0
0
m
m
x(5)
m
x(5)
1
m
1
m
m
m
a

m
a
1
x(6)
a
0
m
5
m
9
1
0
1
2
0
2
m
0
2
0
m
2
1
3
0
1
0
0
2
8
1
1
0
1
m
0
1
a

x(7)
a
1
x(7)
a
0
m
1
0
5
1
1
1
m
1
0
1
0
1
0
x(7)
2
2
3
0
1
0
0
2
2
1
1
0
1
m
0
1
a

m
m
1
x(8)
a
0
m
-4
m
-4
0
0
0
m
1
-1
m
0
-1
0
m
0
1
1
0
0
0
0
-1
-6
0
0
0
0
m
0
0
a

16
11

17
12

1
0

m
m

2
2

1
1

0
-1

m
m
m
27
m
m
m
m

m
m
m
m
m
16
m
m

m
m
m
m
m
13
m
m

m
m
m
m
m
-3
m
m

m
m
m
0
m
m
m
m

m
m
m
m
m
0
m
m

a
m
m
m
m
0
m
m

m
m
m
m
m
0
m
m

m

m

m

m

m

m

m

m

d

(12)

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 to tertiary education includes pre-primary programmes.
2. Figures are for net student loans rather than gross, thereby underestimating public transfers.
Source: OECD/UIS/Eurostat (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888934164636

EDUCATION AT A GLANCE 2020 © OECD 2020

308  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 2017, 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% consisting of direct public expenditure on education.



Spending on non-tertiary education (primary, secondary and post-secondary non-tertiary levels) is mostly
decentralised, with 56% 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 13% 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 (2017)
Primary to tertiary education

%
18

Public transfers and payments to the non-educational private sector
Direct public expenditure on educational institutions
Total public expenditure on education as a percentage of total government expenditure

16
14
12
10
8
6
4
0

Chile
South Africa
Mexico
Brazil
Switzerland
New Zealand
Iceland
Costa Rica1
Israel
Korea
Ireland
Denmark
Australia
Norway
United Kingdom
Argentina
United States
Turkey
Sweden
Netherlands
Canada2
Belgium
OECD average
Estonia
Finland
Portugal
Austria
EU23 average
Colombia1
Poland
Latvia
Lithuania
Germany
Slovenia
Russian Federation
Spain
France
Czech Republic
Slovak Republic
Japan
Hungary
Luxembourg
Italy
Greece

2

1. Year of reference 2018.
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 (2020), Table C4.1. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2 https://doi.org/10.1787/888934164788

EDUCATION AT A GLANCE 2020 © OECD 2020

C4. WHAT IS THE TOTAL PUBLIC SPENDING ON EDUCATION?  309

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.
Government funding on education can also be affected by an external shock. In this respect, the COVID-19 pandemic
could also influence the public funds available for education. Past economic crises have put pressure on public budgets
with a 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 learning adquisition and economic growth.
This indicator compares total public spending on education with total government expenditure across OECD and partner
countries. This indicates the priority placed on education relative to other public areas of investment, such as health care,
social security, defence and security. 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. Finally it also covers how
public expenditure has changed over time.

Other findings


Governments in 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 nearuniversal enrolment at lower levels.



Between 2012 and 2017, the proportion of government expenditure devoted to public expenditure on primary to
tertiary education slightly increased across OECD countries (0.3%). However, in 56% of the OECD and partner
countries with available data for both years this share increased over the same period, most notably in Greece
and Spain, where the increases were over 9%, but in many countries increases in educational expenditure did
not keep pace with the growth in government expenditure overall.



There are greater levels of transfers of public funds from central to regional and local levels of government at
primary, secondary and post-secondary non-tertiary level than there are at tertiary level. At non-tertiary levels,
42% of public funds come from local sources after transfers between levels of government, compared to 26%
before transfers. At the tertiary level, local sources represent around 1% of public funds, before and after transfers
between levels of government.

EDUCATION AT A GLANCE 2020 © OECD 2020

310  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 2017, 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 Greece to around 17% in Chile
(Table C4.1and Figure C4.1).
Overall, significant government funding was devoted to non-tertiary levels of education in 2017. 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 depends more on
private funding sources than non-tertiary levels (primary, secondary and post-secondary non-tertiary levels).
In 2017, the share of total public expenditure devoted to tertiary education varied widely among countries. On average across
OECD countries, total public expenditure on tertiary education amounted to 27% of the total public expenditure on primary to
tertiary education. The share ranges from 15-20% in Greece, Israel, Latvia, Luxembourg and Portugal to over 35% in Austria,
Denmark 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 noneducational 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 2017, on average across OECD countries, this public
expenditure represented less than 1% of total government expenditure and 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 non-educational private sector represent 1.5-2.4% of total government expenditure in Australia,
Chile, Denmark, Ireland, the Netherlands, New Zealand, Norway and the United Kingdom, and less than 0.3% in Argentina,
the Czech Republic, Estonia, Greece, Luxembourg and the Russian Federation (Figure C4.1).
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 gross domestic product (GDP)
varies greatly among countries (Table C4.1 – web columns). In 2017, around 11% of countries with available data reported
that total government expenditure on all services accounted for 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 relative to a country’s
GDP. For example, Korea allocates 13% of its total government expenditure on primary to tertiary education (more than the
OECD average of 11%), but total public expenditure on education as a share of GDP is relatively low (3.9% compared to the
OECD average of 4.4%). This can be explained by Korea’s relatively low total government expenditure as a share of GDP
(30%) (Table C4.1 – web columns).
The economic crisis associated with the spread of the COVID-19 pandemic is likely to affect the availability of public funding
for education in OECD and partner countries, as emergency funds have been funnelled to support increasing healthcare and
welfare costs. While the longer-term impact on education funding is still uncertain, some countries have implemented
immediate financial measures to support students and education systems cope with the disruptions and economic impact of
school and university closures (Box C4.1).

Box C4.1. Impact of COVID-19 on the financing of education in OECD countries
The global COVID-19 pandemic has triggered one of the most significant economic and financial crises of the century
(OECD, 2020[1]). This crisis, as with the financial crisis in 2008, is expected to significantly impact our societies and
education might be one of the sectors affected.

EDUCATION AT A GLANCE 2020 © OECD 2020

C4. WHAT IS THE TOTAL PUBLIC SPENDING ON EDUCATION?  311
While the 2008 financial crisis severely impacted public budgets, cuts to education budgets were delayed in many
countries (OECD, 2013[2]). Between 2008 and 2009, despite severe budget cuts in all OECD countries, public spending
on education continued to increase in the majority of them. The first signs of slowdown appeared in 2010 following austerity
measures that imposed cuts in the education budgets of about one-third of OECD countries (OECD, 2013[2]).
However, the current crisis is expected to affect education budgets more quickly as public revenues decline and
governments review the prioritisation of education in national budgets (IIEP-UNESCO, 2020[3]). Forecasts predict that the
pandemic will lead to slower growth in government spending in the coming year. If the share of government spending
devoted to education were to remain unchanged, education spending would continue to grow but at significantly lower
rates than before the pandemic(Al-Samarrai, Gangwar and Gala, 2020[4]).
Some countries are also putting in place immediate financial measures to support their education systems during the
COVID-19 crisis. Examples include:


In April 2020, the Australian Government announced the Higher Education Relief Package which provided funding
to Australians who have been displaced as a result of the COVID-19 crisis and who were looking to upskill or
retrain. This package reduced the cost of studying short online courses, provided exemptions from loan fees for
domestic students for a period of six months starting in May and guaranteed funding for domestic students, even
if enrolments dropped. (Australian Government, 2020[5]).



The launch of the Canada Emergency Student Benefit announced in April 2020 which seeks to provide financial
support to post-secondary students and recent high school graduates who are unable to find work due to COVID19 over the summer months. The Canada Student Service Grant will also provide financial support to students
who do national service and serve their communities during the pandemic crisis. Finally, the government has also
announced plans to double student grants and broaden the eligibility for financial assistance (Trudeau, 2020[6]),
as well as additional support in the form of scholarship funding extensions for students and postdoctoral
researchers impacted by the COVID-19 pandemic (Ministry of Education, 2020[7]).



Distance learning support measures announced by the Italian government in March 2020 to equip schools with
digital platforms and tools for distance learning, lend digital devices to less well-off students, and train school staff
in methodologies and techniques for distance learning (Republic of Italy, 2020[8]). In May 2020 new measures
were announced which seek to provide extra funding to cover costs derived from responses to the pandemic
crisis at the school and university level (Republic of Italy, 2020[9]). This extra funding will cover among others the
costs associated to special services, safety equipment and cleaning material needed in schools and universities
for the next academic year. Additional financial resources were approved to recruit new teachers for primary to
secondary level for the next school year. Emergency financial grants to cover partial or total course-related costs
were announced for less well-off tertiary students.



Support packages for tertiary students announced by the New Zealand government in April 2020 to help students
continue their studies after the crisis. Measures include increasing the amount of student loans and providing
additional support to students to cover extra course-related costs (Ministry of Education, 2020[10]).



England’s (The United Kingdom) financial support for schools launched in April 2020, which provides additional
funding to schools to support them with costs associated with coronavirus. The additional costs covered by the
fund include utilities and resources needed to keep the school open during holidays for priority groups of children,
support for free school meals for eligible children not attending school, as well as additional cleaning costs, where
schools had suspected or confirmed cases of the virus (Department for Education, 2020[11]).



The announcement of the CARES Act Higher Education Emergency Relief Fund by the education authorities in
the United States which provides funding to institutions to provide emergency financial aid grants to students
whose lives have been disrupted (U.S. Department of Education, 2020[12]). The CARES Act Elementary and
Secondary School Emergency Relief Fund aims to provide financial support to school districts impacted by the
disruption and closure of schools from COVID-19 (New Jersey Department of Education, 2020[13]).

Trends in public expenditure on education as a percentage of total government expenditure,
2012-17
Total public spending on primary to tertiary education increased by 7.5% across OECD countries between 2012 and 2017
(Table C4.3), however this increase was less than the increase in total government expenditure (8.4%) over the same period.

EDUCATION AT A GLANCE 2020 © OECD 2020

312  C4. WHAT IS THE TOTAL PUBLIC SPENDING ON EDUCATION?
As a result, over this period, total government expenditure on primary to tertiary education as a share of total government
expenditure increased by 0.1% on average across OECD countries (Table C4.3).
A similar trend is observed at country level (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, there were also large increases in total
government expenditure. Over this five-year period, about 56% of countries with available data increased their public
expenditure on education as a share of total government expenditure, with Greece and Spain showing the greatest increase
(over 9%) while 81% of countries increased total government expenditure on all goods and services. However, in about half
of OECD and partner countries, the increase in public expenditure on education was smaller than the increase in government
spending overall. The most notable examples are Estonia and Latvia, where the relative increase in total government
expenditure was more than 8 percentage points higher than the increase in public expenditure on education (Table C4.3).

Figure C4.2. Index of change in total public expenditure on education as a share of total government
expenditure (2012 and 2017)
Primary to tertiary education (2012 = 100); 2015 constant prices
Change in public expenditure
on education

Index
140

Change in total government
expenditure for all services

Change in total public expenditure on education
as a percentage of total government expenditure

130
120
110
100

Lithuania

Finland

Argentina

Estonia

Latvia

Norway

Poland

Japan

Switzerland

New Zealand

Turkey

Slovenia

Germany

Austria

Mexico

Slovak Republic

EU23 average

OECD average

France

Chile

Iceland

Italy

Canad a1

Czech Republic

United States

Israel

Sweden

Belgium

Brazil

Netherlands

United Kingdom

Portugal

Russian Federation

Greece

Spain

80

Hungary

90

1. 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 (2020), Table C4.3. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2 https://doi.org/10.1787/888934164807

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 initial level of
government, where the funds originate, and the final level of government, where they are ultimately spent. At the initial level,
decisions are made about how much funding should be allocated and any restrictions on how that money can be spent. At
the final level of government, additional restrictions may be attached to the funds, or this level of government may even pay
directly for educational resources (e.g. teachers’ salaries).
In some countries, education funding is centralised, while in others it is decentralised but with funds transferred between
levels of government. Complete centralisation can cause delays in decision making. Decisions that are far removed from
those affected can also 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, either due to differences
in priorities related to education, or to differences in their ability to raise funding for education. Wide variations in education

EDUCATION AT A GLANCE 2020 © OECD 2020

C4. WHAT IS THE TOTAL PUBLIC SPENDING ON EDUCATION?  313
standards and resources can also lead to inequality of educational opportunities and insufficient attention being paid to longterm 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[14]).
The levels of government responsible for funding education differ at different levels of education. Typically, public funding is
more centralised at the tertiary level than at lower levels of education. In 2017, on average across OECD countries, 59% of
the public funds for non-tertiary education came from the central government before transfers to the various levels of
government, compared to 88% of the funds for tertiary education (Table C4.2).
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 Costa Rica, Ireland and New Zealand. In countries such as Chile, Colombia, France, Greece, Hungary,
Israel, Italy, Luxembourg, the Netherlands, Portugal, Slovenia, Turkey and the United Kingdom, the 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, the 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, the Czech Republic, Germany, the Russian Federation, 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 Denmark, Finland, Iceland, Norway and Sweden, 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 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 59% to 44% after transfers to other levels of government have been accounted for, while the share of
local funds rises as a result from 26% 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, Lithuania, 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 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 88% of funds before transfers and this barely changes once
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 32 countries, the central government is
the main source of initial funding and there are no or small transfers to regional or local governments. In contrast, countries
such as Belgium, Germany and Spain 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
representing around 1% of public funds, with the exception of the United States, where it generates and spends 11% of the
funds.

EDUCATION AT A GLANCE 2020 © OECD 2020

314  C4. WHAT IS THE TOTAL PUBLIC SPENDING ON EDUCATION?

Figure C4.3. Distribution of initial sources of public funds for education and change in government
levels' share of funds after intergovernmental transfers (2017)
Primary, secondary and post-secondary non-tertiary education
Distribution of initial sources of public funds for education, by level of government
Initial funds from the local level of government
Initial funds from the regional level of governmnet
Initial funds from the central level of government

%
100
90
80
70
60
50
40
30
20
0

Costa Rica1
Ireland
New Zealand
Greece
Turkey
Chile
Netherlands
Hungary
Slovenia
Italy
Luxembourg
Colombia1
Israel
Portugal
Korea
Slovak Republic
Mexico
Lithuania
Austria
France
Poland
Latvia
EU23 average
United Kingdom
OECD average
Estonia
Australia
Finland
Denmark
Iceland
Belgium
Japan
Brazil
Czech Republic
Spain
United States
Norway
Germany
Sweden
Canada 2
Switzerland
Russian Federation

10

Change in government levels’ share of funds after intergovernmental transfers
Percentage
points
100

Change in local governments’ share of funds after intergovernmental transfers
Change in regional governments’ share of funds after intergovernmental transfers
Change in central governments’ share of funds after intergovernmental transfers

80
60
40
20
0
-20
-40
-60

Costa Rica1
Ireland
New Zealand
Greece
Turkey
Chile
Netherlands
Hungary
Slovenia
Italy
Luxembourg
Colombia1
Israel
Portugal
Korea
Slovak Republic
Mexico
Lithuania
Austria
France
Poland
Latvia
EU23 average
United Kingdom
OECD average
Estonia
Australia
Finland
Denmark
Iceland
Belgium
Japan
Brazil
Czech Republic
Spain
United States
Norway
Germany
Sweden
Canada2
Switzerland
Russian Federation

-80
-100

1. Year of reference 2018.
2. Primary, secondary and post-secondary non-tertiary 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 (2020), Table C4.2. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2 https://doi.org/10.1787/888934164826

EDUCATION AT A GLANCE 2020 © OECD 2020

C4. WHAT IS THE TOTAL PUBLIC SPENDING ON EDUCATION?  315

Definitions
Intergovernmental transfers are transfers of funds designated for education from one level of government to another. They
are defined as net transfers from a higher to a lower level of government. Initial funds refer to the funds before transfers
between levels of government, while final funds refer to the funds after such transfers.
Public expenditure on education covers expenditure on educational institutions and expenditure outside educational
institutions such as support for students’ living costs and other private expenditure outside institutions, 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[15]).
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[16]) and Annex 3 for country-specific notes (https://doi.org/10.1787/69096873-en).

Source
Data refer to the financial year 2017 (unless otherwise specified) and are based on the UNESCO, OECD and Eurostat (UOE)
data collection on education statistics administered by the OECD in 2019 (for details see Annex 3 at
https://doi.org/10.1787/69096873-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 2020 © OECD 2020

316  C4. WHAT IS THE TOTAL PUBLIC SPENDING ON EDUCATION?
The data on expenditure for 2005, 2012 to 2017 were updated based on a survey in 2019-20, and expenditure figures for
2005 to 2017 were adjusted to the methods and definitions used in the current UOE data collection.

References

Al-Samarrai, S., M. Gangwar and P. Gala (2020), The Impact of the COVID-19 Pandemic on Education Financing,
World Bank, Washington, DC, https://openknowledge.worldbank.org/handle/10986/33739 (accessed on
27 May 2020).

[4]

Australian Government (2020), Higher Education Relief Package | Ministers’ Media Centre,
https://ministers.dese.gov.au/tehan/higher-education-relief-package (accessed on 24 June 2020).

[5]

Department for Education (2020), School funding: Exceptional costs associated with coronavirus (COVID-19) for
the period March to July 2020 - GOV.UK, GOV.UK website,
https://www.gov.uk/government/publications/coronavirus-covid-19-financial-support-for-schools/school-fundingexceptional-costs-associated-with-coronavirus-covid-19-for-the-period-march-to-july-2020 (accessed on
28 May 2020).

[11]

Eurostat (European Commission) (2011), “Manual on sources and methods for the compilation of COFOG
Statistics”, Methodologies and Working papers, Eurostat, Luxembourg, http://dx.doi.org/10.2785/16355.

[15]

IIEP-UNESCO (2020), What price will education pay for COVID-19?, International Institute for Educational
Planning, http://www.iiep.unesco.org/en/what-price-will-education-pay-covid-19-13366 (accessed on
27 May 2020).

[3]

Ministry of Education (2020), COVID-19: Tertiary student support package, New Zealand Government website,
https://www.beehive.govt.nz/release/covid-19-tertiary-student-support-package (accessed on 28 May 2020).

[10]

Ministry of Education (2020), Extension of Tri-agency scholarships and fellowships (Canada Graduate
Scholarships - Master’s, Canada Graduate Scholarships - Doctoral, agency-specific doctoral awards,
Postdoctoral Fellowships, Vanier Canada Graduate Scholarships and Banting Postdoctoral Fellowships),
https://www.sshrc-crsh.gc.ca/news_room-salle_de_presse/latest_news-nouvelles_recentes/2020/triagency_extension-prolongation_trois_organismes-eng.aspx (accessed on 19 June 2020).

[7]

New Jersey Department of Education (2020), CARES Act Education Stabilization Fund, State of New Jersey
website, https://www.nj.gov/education/covid19/boardops/caresact.shtml (accessed on 28 May 2020).

[13]

OECD (2020), Coronavirus (COVID-19): Joint actions to win the war, OECD website,
https://www.oecd.org/about/secretary-general/Coronavirus-COVID-19-Joint-actions-to-win-the-war.pdf
(accessed on 27 May 2020).

[1]

OECD (2018), OECD Handbook for Internationally Comparative Education Statistics 2018, OECD Publishing,
Paris, https://doi.org/10.1787/9789264304444-en (accessed on 16 April 2020).

[16]

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.

[14]

OECD (2013), “What is the impact of the economic crisis on public education spending?”, Education Indicators in
Focus, No. 18, OECD Publishing, Paris, https://doi.org/10.1787/5jzbb2sprz20-en (accessed on 27 May 2020).

[2]

EDUCATION AT A GLANCE 2020 © OECD 2020

C4. WHAT IS THE TOTAL PUBLIC SPENDING ON EDUCATION?  317
Republic of Italy (2020), Misure di potenziamento del Servizio sanitario nazionale e di sostegno economico per
famiglie, lavoratori e imprese connesse all’emergenza epidemiologica da COVID-19 (Law decree 17th March
2020 number 18), GAZZETTA UFFICIALE DELLA REPUBBLICA ITALIANA,
https://www.gazzettaufficiale.it/eli/gu/2020/03/17/70/sg/pdf (accessed on 28 May 2020).

[8]

Republic of Italy (2020), Misure urgenti in materia di salute, sostegno al lavoro e all’economia, nonché di politiche
sociali connesse all’emergenza epidemiologica da COVID-19 (Law decree 19th May 2020 number 34 , Articles
230,231,232,233,234,235,236)., Gazzetta Ufficiale della Repubblica Italiana, No. 34,
https://www.gazzettaufficiale.it/static/20200519_128_SO_021.pdf (accessed on 12 June 2020).

[9]

Trudeau, J. (2020), Support for students and new grads affected by COVID-19 | Prime Minister of Canada, Prime
Minister of Canada, https://pm.gc.ca/en/news/news-releases/2020/04/22/support-students-and-new-gradsaffected-covid-19 (accessed on 28 May 2020).

[6]

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Education website, https://www2.ed.gov/about/offices/list/ope/caresact.html (accessed on 28 May 2020).

[12]

Indicator C4 Tables
Table C4.1

Total public expenditure on education as a percentage of total government expenditure (2017)

Table C4.2

Distribution of sources of total public funds devoted to education, by level of government (2017)

Table C4.3

Index of change in total public expenditure on education as a percentage of total government
expenditure (2005, 2012 and 2017)

Cut-off date for the data: 19 July 2020. Any updates on data can be found on line at http://dx.doi.org/10.1787/eag-dataen. More breakdowns can also be found at http://stats.oecd.org/, Education at a Glance Database.
StatLink: https://doi.org/10.1787/888934164712

EDUCATION AT A GLANCE 2020 © OECD 2020

318  C4. WHAT IS THE TOTAL PUBLIC SPENDING ON EDUCATION?
Table C4.1. Total public expenditure on education as a percentage of total government expenditure (2017)
Initial sources of funds, by level of education

Primary

Lower secondary

General
programmes

Vocational
programmes

All programmes

All secondary

Post-secondary non-tertiary

Primary, secondary
and post-secondary non-tertiary

Short-cycle tertiary

Long-cycle tertiary

All tertiary

All tertiary
(excluding R&D)

Total

Of which: public transfers
and payments to
the non-educational
private sector

Primary to tertiary
(excluding R&D)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

(13)

(14)

(15)

4.4
1.8
2.9
4.7 d
5.9
3.3
4.7
2.1
3.8
3.5
2.5
2.1
1.4
2.5
1.4
5.2
4.7
6.0
2.0
2.8
4.6
3.5
2.2
2.5
5.7
2.7
4.0
3.7
3.5
3.3
2.1
3.1
2.7
3.8
4.4
2.1
4.1
4.0

2.7
2.4
1.7
x(1)
2.2
2.8
3.1
2.4
2.0
1.6
2.0
2.1
2.6
1.4
1.4
2.4
1.8
x(3, 4, 5)
1.4
1.7
2.6
1.7
3.1
1.8
3.1
2.6
2.8
1.6
1.6
2.5
2.2
1.7
1.8
1.8
2.6
2.2
2.0
2.1

1.2
0.6
1.3 d
x(5)
2.7
x(5)
0.7
0.5
x(5)
0.9
0.7
1.3
0.9
0.9
1.5
1.7
x(5)
3.0 d
x(5)
x(5)
x(5)
1.2
1.0
0.7
1.7
0.7
2.1
1.4
0.6
x(5)
0.6
x(5)
1.2
1.4
1.0 d
1.2
1.6
x(5)

0.4
1.3
2.0 d
x(5)
1.2
x(5)
0.9
1.6
x(5)
0.8
1.7 d
0.7
0.9
0.6
0.8
0.8
x(5)
1.7 d
x(5)
x(5)
x(5)
1.0
0.3
1.3
1.0
1.6
0.7
1.4
1.1
x(5)
1.3
x(5)
0.8 d
1.1
1.6 d
1.9
1.0
x(5)

1.6
1.9
3.4 d
2.9
3.9
1.0
1.6
2.1
2.1
1.7
2.4 d
2.0
1.9
1.4
2.3
2.5
2.3
4.7 d
2.4 d
1.7 d
3.0
2.2
1.3
2.0
2.7
2.3
2.8
2.8
1.7
2.4 d
1.9
2.1
2.0 d
2.5
2.6 d
3.1
2.7
2.3

4.3
4.3
5.1 d
2.9
6.1
3.8
4.7
4.4
4.1
3.3
4.4 d
4.2
4.5
2.8
3.7
4.9
4.2
4.7
3.8 d
3.4 d
5.6
3.9
4.3
3.8
5.8
4.9
5.6
4.4
3.3
4.9 d
4.1
3.7
3.8 d
4.3
5.2 d
5.3
4.7
4.4

0.3
0.0
x(3, 4, 5, 6)
m
a
m
a
0.0
a
0.3
x(4, 5, 6)
0,0
0,3
0,0
0,6
0,1
0,4
0,0
x(5, 6)
x(5, 6, 9, 10, 11)
a
0.2
0.4
0.0
a
0.0
0.3
0.1
0.0
x(5, 6)
0.1
a
x(4, 5, 6)
0.1
x(3, 4, 5, 6)
a
a
0.0

9.0
6.2
8.0
7.6 d
12.0
7.1
9.4
6.5
7.9
7.1
6.9
6.3
6.3
5.4
5.7
10.2
9.2
10.8
5.8
6.2
10.2
7.6
6.9
6.3
11.5
7.6
9.8
8.1
6.8
8.2
6.3
6.8
6.5
8.2
9.6
7.4
8.7
8.4

0.6
0.6
0.1
1.2
0.7
x(11)
x(11)
0.0
0.5
a
a
0.5
0.0
a
0.0
0.1
x(11)
0.5
0.0
0.2 d
0.3
0.3
a
0.1
x(11)
0.0
0.4
0.1
0.0
0.0
0.0
0.1
0.4
0.2
x(11)
x(11)
0.3
x(11)

2.7
2.9
2.7
2.6
4.7
x(11)
x(11)
1.8
4.3
2.9
3.1
1.7
2.8
1.3
1.7
3.1
x(11)
1.8
1.5
1.4 d
2.5
1.5
2.3
1.0
x(11)
3.7
3.2
4.1
2.6
1.7
1.9
2.1
1.9
3.5
x(11)
x(11)
3.1
x(11)

3.3
3.5
2.8
3.8
5.4
2.3
3.7
1.8
4.8
2.9
3.1
2.2
2.8
1.3
1.7
3.2
3.7
2.3
1.5
1.6 d
2.8
1.8
2.3
1.1
3.5
3.7
3.7
4.2
2.6
1.8
1.9
2.1
2.3
3.6
4.0
4.6
3.4
3.7

1.9
2.6
2.0
m
5.0
m
m
1.0
3.1
2.0
2.0
1.5
1.8
0.9
1.4
m
m
m
1.0
m
2.0
1.4
1.7
0.7
2.6
2.7
3.1
2.9
2.1
1.3
1.4
1.8
1.6
2.4
2.0
3.8
2.8
3.2

12.3
9.7
10.8
11.3 d
17.4
9.4
13.1
8.3
12.7
10.0
9.9
8.4
9.1
6.7
7.4
13.4
12.9
13.1
7.3
7.8
13.0
9.4
9.2
7.4
15.0
11.4
13.5
12.3
9.4
9.9
8.2
9.0
8.8
11.9
13.6
12.0
12.1
12.1

1.8
0.5
0.7
0.9 d
1.8
0.9
a
0.2
2.2
0.2
0.6
0.4
0.9
0.0
0.3
0.6
2.0
0.4
0.5
0.5
1.1
0.4
0.4
0.1
0.9
1.6
1.9
1.5
0.4
0.6
0.7
0.5
0.4
1.4
0.3
1.0
2.4
1.4

10.9
8.8
10.0
m
17.0
m
m
7.5
11.0
9.1
8.9
7.8
8.1
6.3
7.1
m
m
m
6.8
m
12.2
9.0
8.6
7.0
14.1
10.3
13.0
11.1
8.9
9.5
7.7
8.7
8.1
10.6
11.6
11.2
11.5
11.6

3.4
2.8

2,1
2.0

1,2
1.0

1,1
1.1

2,3
2.1

4,4
4.1

m
0.2

7.9
7.0

0.3
0.2

2.5
2.4

2.9
2.6

2.1
1.8

10.8
9.6

0.9
0.8

9.8
8.7

3.9
3.1
4.1
3.4
m
m
m
m
m
m
x(3, 4, 5, 6) x(3, 4, 5, 6)
m
m
6.8
2.1

x(5)
x(5)
m
m
m
6.4 d
m
x(5)

x(5)
x(5)
m
m
m
0.3 d
m
x(5)

2.2
3.1 d
m
m
m
6.6 d
m
3.0

5.2
6.5 d
m
m
m
6.6 d
m
5.2

a
x(5, 6)
m
m
a
x(3, 4, 5, 6)
m
0.6

9.2
10.6
m
m
m
6.6
m
12.6

x(11)
x(11)
m
m
m
0.5
m
x(11)

x(11)
x(11)
m
m
m
1.8
m
x(11)

2.9
4.0
m
m
m
2.2
m
2.5

m
3.6
m
m
m
2.1
m
m

12.1
14.6
m
m
m
8.9
m
15.1

0.2
1.3
m
m
m
0.2
m
m

m
14.2
m
m
m
8.7
m
m

m

m

m

m

m

m

m

m

m

m

m

m

m

Par tners

OECD

Upper secondary

Countries
Australia
Austria
Belgium
Cana da 1, 2
Chile
Colombia 2 , 3
Costa Rica 3
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungar y
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Lithuania
Luxembourg
Mexico
Netherlands
New Zealand
Nor way
Poland
Por tugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United Kingdom
United States
OECD average
EU23 average
Argentina
Brazil
China
India
Indonesia 3
Russian Federation
Saudi Arabia
South Africa
G20 average

Primary
to tertiary
(including R&D)

(1)

Secondary

m

m

Tertiary

Note: Public expenditure presented in this table includes both public transfers and 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. Post-secondary non-tertiary figures are treated as negligible.
3. Year of reference 2018.
Source: OECD/UIS/Eurostat (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888934164731
EDUCATION AT A GLANCE 2020 © OECD 2020

C4. WHAT IS THE TOTAL PUBLIC SPENDING ON EDUCATION?  319

Table C4.2. Distribution of sources of total public funds devoted to education, by level of government (2017)
Before and after transfers, by level of education
Primar y, secondar y
and post-secondary non-tertiar y

15
13

26
25

44
48

13
14

42
38

Argentina
Brazil
China
Ind ia
Indonesia 2
Russian Federation
Saudi Arabia
South Africa

m
14
m
m
m
1
m
m

m
42
m
m
m
52
m
m

m
44
m
m
m
46
m
m

m
7
m
m
m
1
m
m

m
43
m
m
m
52
m
m

G20 average

m

m

m

m

m

Local

59
61

Region al

90
96
15
m
100
97
100
97
92
100
99
86
30
100
100
100
100
97
86
91 d
96
100
99
100
82
100
100
98
100
100
100
99
18
98
35
100
100
53

Central

x(5)
13
3
86 d
39
6
a
26
66
72
92
12
22
6
9
74
a
32
4
70
63
82
78
9
0
8
a
95
95
11
76
9
6
95
39
1
40
98

Local

97
50
73
10 d
a
4
a
62
0
a
a
15
72
a
a
a
a
a
6
30
36
a
a
a
73
0
a
a
2
6
a
a
82
a
60
a
a
2

Region al

3
37
24
3d
61
90
100
12
34
28
8
73
6
94
91
26
100
68
91
1
1
18
22
91
27
92
100
5
4
83
24
91
12
5
0
99
60
1

(9)

(10)

(11)

10
4
84
m
a
3
a
2
0
a
a
10
68
a
a
a
a
a
14
9d
2
a
a
a
18
0
a
a
0
0
a
a
81
2
65
a
a
36

x(8)
1
1
m
0
0
a
2
8
0
1
5
2
a
0
a
a
3
0
0d
2
0
1
0
0
a
a
2
0
0
0
1
1
1
0
0
0
11

87
96
14
m
100
97
100
97
92
100
99
86
20
100
100
100
100
97
84
90 d
96
100
99
100
80
100
100
98
100
100
99
99
18
98
18
100
100
53

88
87

11
11

1
1

m
50
m
m
m
46
m
m

m
75
m
m
m
79
m
m

m
24
m
m
a
21
m
m

m

m

m

d

Final funds
(after transfers
between levels
of government)

Central

(8)

Initial funds
(before transfers
between levels
of government)

Local

x(2)
12
3
23 d
3
6
a
26
71
44
66
11
18
0
9
74
a
12
2
28
2
38
25
9
0
6
a
92
36
11
20
9
6
95
35
1
40
49

Region al

(7)

Final funds
(after transfers
between levels
of government)
Central

66
14
73
73 d
a
4
a
60
0
a
a
16
75
a
a
a
a
a
7
55
17
a
a
a
22
0
a
a
1
6
a
a
82
a
62
a
a
42

OECD average
EU23 average

(6)
d

Primar y to ter tiar y

Local

(5)

34
74
24
4d
97
90
100
14
29
56
34
74
6
100
91
26
100
88
91
17
80
62
75
91
78
94
100
8
63
83
80
91
12
5
3
99
60
9

Region al

(4)

d

Central

Region al

(3)

(1)
Countries
Australia
Austria
Belgium
Canada 1
Chile
Colombia 2
Costa Rica 2
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungar y
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Lithuania
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Por tugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
Unite d Kingdom
United States

Initial funds
(before transfers
between levels
of government)

Local

Central

(2)

Central

Local

Final funds
(after transfers
between levels
of government)

Region al

Par tners

OECD

Initial funds
(before transfers
between levels
of government)

Tertiar y

(12)

(13)

(14)

(15)

(16)

(17)

(18)

13
3
85
m
a
3
a
2
0
a
a
10
78
a
a
a
a
a
16
9d
2
a
a
a
20
0
a
a
0
0
a
a
81
2
82
a
a
36

x(13)
1
1
m
0
0
a
2
8
0
1
5
2
a
0
a
a
3
0
0d
2
0
1
0
0
a
a
2
0
0
1
1
1
1
0
0
0
11

49
82
21
m
98
92
100
32
53
69
54
77
14
100
93
44
100
89
90
33
84
69
81
92
79
96
100
39
73
86
84
93
14
34
13
99
71
23

51
10
76
m
a
4
a
48
0
a
a
14
73
a
a
a
a
a
8
45
14
a
a
a
21
0
a
a
0
5
a
a
82
1
62
a
a
40

x(14)
8
2
m
2
4
a
21
47
31
46
9
13
0
7
56
a
11
2
22
2
31
19
8
0
4
a
61
26
9
16
7
4
66
25
1
29
37

26
58
21
m
73
92
100
30
56
48
36
76
10
95
93
43
100
73
89
19
21
34
41
92
39
94
100
37
30
86
41
93
14
34
6
99
71
17

74
33
76
m
a
4
a
49
0
a
a
14
74
a
a
a
a
a
8
25
29
a
a
a
61
0
a
a
1
5
a
a
82
1
67
a
a
12

x(17)
8
2
m
27
4
a
21
44
52
64
10
16
5
7
57
a
27
3
55
50
66
59
8
0
5
a
63
69
9
59
7
4
66
28
1
29
71

87
87

12
12

1
1

68
69

13
13

19
18

56
58

13
14

30
28

m
1
m
m
a
0
m
m

m
75
m
m
m
79
m
m

m
24
m
m
a
21
m
m

m
1
m
m
a
0
m
m

m
31
m
m
m
21
m
m

m
37
m
m
m
44
m
m

m
32
m
m
m
35
m
m

m
26
m
m
m
21
m
m

m
38
m
m
m
44
m
m

m
36
m
m
m
35
m
m

m

m

m

m

m

m

m

m

m

m

d

d

d

Note: Some levels of education are included with others. Refer to "x" code on 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, secondary and post-secondary non-tertiary education includes pre-primary programmes.
2. Year of reference 2018.
Source: OECD/UIS/Eurostat (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888934164750

EDUCATION AT A GLANCE 2020 © OECD 2020

320  C4. WHAT IS THE TOTAL PUBLIC SPENDING ON EDUCATION?
Table C4.3. Index of change in total public expenditure on education as a percentage of total government expenditure (2005,
2012 and 2017)
Initial sources of funds, by level of education and year

Par tners

OECD

Primar y, secondar y
and post-secon dar y
non-ter tiar y

Ter tiar y

Primar y to ter tiar y

Change in public
Change in public
Change in public
expenditure on education
expenditure on education expenditure on education
as a percentage of total
Change in public
as a percentage of total
as a percentage of total
government expenditure government expenditure expenditure on education government expenditure
(2015 = 100)
(2015 = 100)
(2015 = 100)
(2015 = 100)

Change in total
government expenditur e
(2015 = 100)

2005

2012

2017

2005

2012

2017

2005

2012

2017

2005

2012

2017

2005

2012

2017

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

(13)

(14)

(15)

Countries
Australia
Austria
Belgium
Canada1
Chile
Colombia
Costa Rica
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungar y
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Lithuania
Luxembourg
Mexico
Netherlands
New Zealand
Nor way
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
Unite d Kingdom
United States

m
m
98.0
x(10)
114.9
m
m
m
m
x(10)
107.3
110.9
100.6
x(10)
125.5
x(10)
m
76.1
x(10)
109.3
m
111.9
141.3
m
132.0
105.1
m
x(10)
117.0
x(10)
x(10)
134.8
113.4
104.6
108.3
m
m
109.9

m
100.9
98.0
100.0 d
118.4
m
101.7
97.1
m
118.8
101.1
100.8
102.9
95.6
94.2
95.1
m
94.8
99.2
102.4
m
86.3
112.7
m
98.3
98.2
99.5
107.0
103.3
102.3
101.8
110.5
93.5
98.9
107.9
95.9
92.8
97.6

m
102.1
101.9
96.7 d
111.4
103.7
m
108.7
m
102.3
95.5
100.8
98.2
107.9
105.3
97.9
106.3
101.9
102.7
98.1
m
86.2
102.3
92.1
95.5
100.9
96.7
99.1
95.3
112.6
108.2
108.2
105.6
107.1
99.8
90.8
95.7
101.4

m
m
93.1
x(10)
44.9
m
m
m
m
x(10)
117.7
99.7
82.7
x(10)
159.3
x(10)
m
87.0
x(10)
92.3 d
m
78.9
89.5
m
100.2
90.9
m
x(10)
91.4
x(10)
x(10)
132.9
110.3
91.1
103.8
m
m
100.0

m
102.3
95.8
94.3
82.5
m
87.9
121.0
m
74.5
107.0
98.7
100.4
99.6
125.9
98.0
m
95.9
102.6
105.3 d
m
81.7
113.7
m
87.4
92.2
98.1
112.7
89.9
92.2
75.3
120.8
95.7
99.6
101.2
99.5
93.1
101.3

m
99.8
105.1
112.4
106.9
110.0
m
97.8
m
82.1
92.7
99.3
98.9
96.8
133.3
93.3
97.3
92.5
102.6
97.7 d
95.3
59.1
67.6
89.0
87.6
103.6
89.4
105.1
89.4
95.2
63.0
107.2
103.9
97.0
101.0
97.5
108.7
106.0

m
m
81.4
83.2 d
51.5
37.2
m
85.3
m
93.0
91.3
92.4
87.5
145.8
117.6
92.7
m
61.5
110.9
90.5
m
80.1
94.5
m
74.8
85.6
m
91.5
79.4
104.7
56.1
114.2
94.2
87.3
87.9
m
m
89.3

m
99.9
98.4
94.8 d
91.7
89.2
85.3
101.8
m
97.1
101.9
98.1
99.7
103.6
88.5
91.2
m
91.8
101.5
102.7
m
78.9
106.6
96.3
89.8
97.7
97.3
98.0
94.0
99.9
76.6
110.1
100.5
94.3
97.9
84.2
93.3
97.4

m
101.7
102.7
107.0 d
115.4
110.5
m
106.0
m
104.0
95.3
103.0
104.0
94.7
109.4
112.0
104.7
110.8
102.3
99.0
m
83.7
91.7
98.3
90.9
101.8
100.2
105.6
100.1
108.3
88.6
105.6
104.6
108.4
104.1
110.6
100.0
107.1

m
m
96.7
101.7 d
92.6
m
m
103.2
m
125.4
110.5
108.0
95.1
137.8
132.0
112.8
m
78.2
112.6
105.8
m
103.3
124.1
m
124.1
100.5
m
122.0
109.6
106.7
93.2
134.3
112.6
100.2
107.0
m
m
107.0

m
101.4
97.4
98.3 d
107.0
m
98.4
102.7
m
103.9
103.0
100.2
102.1
96.5
100.2
95.8
m
95.0
99.9
103.0
m
85.1
113.0
m
95.6
96.3
99.1
108.9
99.4
100.2
92.8
113.0
94.1
99.2
105.9
97.2
92.9
98.7

m
101.2
102.7
101.5 d
110.0
110.0
m
106.2
m
95.5
94.6
100.4
98.4
105.5
110.6
96.8
103.5
100.1
102.7
98.0
m
79.1
90.8
91.6
93.6
101.7
94.6
101.0
93.6
109.1
92.8
108.0
105.1
103.8
100.1
93.3
99.0
102.8

70.7
89.0
84.1
81.8
55.6
m
66.1
82.7
87.2
74.2
82.6
85.6
92.0
105.8
89.1
82.2
81.6
78.7
98.6
85.5
63.9
77.6
76.1
m
60.3
85.2
77.4
75.5
72.4
98.2
60.2
85.0
83.7
87.2
82.1
m
86.0
83.5

89.9
98.5
101.0
96.4
85.7
m
86.7
99.1
101.3
93.4
98.9
97.9
97.6
107.3
88.4
95.1
105.7
96.6
101.6
99.6
92.6
92.7
94.3
m
93.9
101.5
98.2
83.7
94.5
99.7
82.6
97.5
106.8
95.1
92.4
86.7
100.4
98.7

103.2
100.5
100.0
105.5
105.0
100.4
142.4
99.8
99.0
108.8
100.7
102.6
105.6
89.7
98.9
115.7
101.1
110.7
99.6
101.0
105.8
105.8
101.0
107.3
97.2
100.1
105.9
105.9
107.0
99.3
95.5
97.8
99.5
104.4
104.0
118.6
101.0
104.2

OECD average
EU23 average

m
m

100.9
100.4

101.1
102.1

m
m

98.3
99.1

96.7
95.0

87.9
94.5

95.6
97.1

102.7
100.9

109.5
111.4

99.9
99.7

99.9
99.8

80.8
84.7

95.9
98.0

104.0
101.1

120.3
75.8
m
m
m
m
m
m

105.2
105.7
m
m
86.0
113.1
m
m

92.0
98.4
m
m
m
126.4
m
m

89.5
61.7
m
m
m
m
m
m

101.0
66.1
m
m
95.9
102.6
m
m

102.2
114.0
m
m
m
97.1
m
m

49.0
56.6
m
m
m
m
m
m

90.5
92.7
m
m
81.4
105.9
m
m

94.4
99.9
m
m
m
117.9
m
m

113.4
72.4
m
m
m
m
m
m

104.3
96.1
m
m
87.8
109.9
m
m

94.3
102.2
m
m
m
117.5
m
m

43.2
78.2
23.0
48.6
57.2
64.6
40.4
65.9

86.8
96.5
71.4
81.8
92.7
96.4
73.5
90.2

100.1
97.7
114.1
115.0
104.6
100.4
82.4
100.9

m

m

m

m

m

m

m

m

m

m

m

m

68.3

91.8

103.1

Argentina
Brazil
China
India
Indonesia
Russian Federation
Saudi Arabia
South Africa
G20 average

Note: Public expenditure presented in this table includes both public transfers and 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 figures 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, secondary and post-secondary non-tertiary education includes pre-primary programmes.
Source: OECD/UIS/Eurostat (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888934164769

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322  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


Public institutions charge no tuition fees for bachelor’s or equivalent programmes in nearly one-third of OECD
countries and economies with data. In a similar number of countries, annual tuition fees are below USD 2 000,
while in the remaining countries, tuition fees range from about USD 2 600 to over USD 8 000 per year.



Short-cycle tertiary programmes often represent a cheaper alternative to bachelor’s programmes and tend to be
more oriented towards specific professions.



In Australia, Denmark, New Zealand, Norway and Sweden, at least 80% of national students receive public
financial support in the form of student loans, scholarships or grants. In the last decade, the share of students
receiving public financial support increased by at least 14 percentage points in Chile, Denmark and Italy, while
the share remained stable in all other OECD countries and economies with available data.

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 the salaries
of teachers and researchers, development of digital learning and non-teaching services, changes in demand for tertiary
education, investments to support internationalisation, and the 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. Support for students comes in many forms,
including means-based subsidies, family allowances for students, tax allowances for students or their parents and other
household transfers. Governments strive to strike the right balance among these different subsidies, especially in periods
of financial crisis. For a given amount of subsidies, public support such as tax reductions may provide less support for lowincome 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.

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C5. HOW MUCH DO TERTIARY STUDENTS PAY AND WHAT PUBLIC SUPPORT DO THEY RECEIVE?  323

Figure C5.1. Annual average (or most common) tuition fees charged by tertiary public educational
institutions to national students, by level of education (2017/18)
Master’s
Bachelor’s
Short-cycle tertiary

In USD converted
using PPPs
14 000
12 000
10 000
8 000
6 000
4 000
2 000

Sweden

Slovenia

Norway

Slovak Republic

Finland

Greece

Denmark

France

Germany1,10

French Comm. (Belgium)

Flemish Comm. (Belgium)

Austria1

Portugal

Switzerland9

Italy

Spain1

Israel

Netherlands

Ireland8

Latvia2

New Zealand6, 7

Korea5

Japan

Australia4

Canada

Chile

United States1, 3

England (UK)1, 2

0

1. Year of reference 2016/17.
2. Government-dependent private instead of public institutions.
3. Figures for master's and doctoral programmes combined.
4. Year of reference 2017.
5. Year of reference 2018.
6. Bachelor's programmes refer to both short-cycle tertiary and bachelor's programmes combined.
7. Estimates include universities only and exclude postgraduate certificates and diplomas.
8. Tuition fees paid by students instead of fees charged by institutions. Figures cover universities only.
9. Figures refer to both public and government-dependent private institutions combined.
10. Bachelor's programmes refer to bachelor's, master's and doctoral academic programmes combined.
Countries and economies are ranked in descending order of the annual tuition fees charged by public institutions for bachelor's or equivalent programmes.
Source: OECD (2020), Table C5.1. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2https://doi.org/10.1787/888934164921

Other findings


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.



In recent years, OECD countries and economies have passed several reforms to improve access to tertiary
education. Chile, Italy, Greece, Korea and Portugal implemented measures to expand access to tertiary education
to students from disadvantaged backgrounds, while New Zealand increased public subsidies to make the first
year of tertiary education free of tuition fees for new students or trainees. England (United Kingdom) has
expanded its income-contingent loan programmes.



Among countries with data available, the average amount that students borrow ranges from USD 2 400 a year in
Latvia to over USD 10 000 in England (United Kingdom) and Norway (where tuition is free of charge and loans
finance students’ living costs). Scholarships or grants received by students range from less than USD 1 000 a
year in Estonia and the Slovak Republic to over USD 7 000 in Australia, Austria, Denmark, Switzerland and
the United States.



In over half of the countries with available data, tuition fees for bachelor’s degrees in public institutions have
increased by at least 15% over the past decade. In Canada, Italy, Spain and the United States, tuition fees for the
academic year 2016/17 (2017/18 for Canada and Italy) were between 25% and 46% higher than in 2007/08 while
the largest increase was observed in England (United Kingdom), where tuition fees tripled over this period.

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324  C5. HOW MUCH DO TERTIARY STUDENTS PAY AND WHAT PUBLIC SUPPORT DO THEY RECEIVE?

Analysis
Differentiation of tuition fees
Differentiation by type of degree
Entry into tertiary education often means costs for students and their families, both in terms of tuition fees and living expenses,
although they may also receive financial support to help them afford it. Most national students entering tertiary programmes
enrol at bachelor’s or equivalent level in OECD countries (see Indicator B4). Public institutions charge no tuition fees to
national students in nearly one-third of countries, including Denmark, Finland, Greece, Norway, the Slovak Republic, Slovenia
and Sweden (Figure C5.1). In a similar number of countries, tuition fees are moderate, with the average cost for students
below USD 2 000. In the remaining countries, tuition fees range from about USD 2 600 to over USD 8 000 per year. They
exceed USD 10 000 in England (United Kingdom), where the majority of students enrol in government-dependent private
institutions (Figure C5.1).
In many OECD countries, short-cycle tertiary programmes are expanding, with higher first-time graduation rates at this level
in 2018 than in 2010 (see Indicator B5). These programmes consist mostly of tertiary-level vocational education and training
and therefore prepare students for specific occupations. Short-cycle tertiary programmes offer slightly less positive
employment prospects and earnings than other tertiary qualifications (see Indicators A3 and A4), but they provide a shorter
and cheaper tertiary education and, in a number of countries, a better benefit-to-cost ratio than long-cycle tertiary programmes
such as bachelor’s and master’s (OECD, 2019[1]). Tuition fees for short-cycle tertiary programmes in public institutions are
generally much lower than for bachelor’s programmes. Generally, they are free of charge in Denmark, France,
the Slovak Republic, Slovenia, Spain and Sweden and they amount to less than half the tuition fees for bachelor’s
programmes in Chile and the United States, where they are below USD 3 500. In contrast, tuition fees for short-cycle tertiary
programmes in public institutions are the same as for bachelor’s programmes in the Netherlands and Portugal. In Norway,
short-cycle tertiary is the only tertiary programme that is not free of charge (Figure C5.1).
Higher tertiary education after a bachelor’s degree leads to better labour-market outcomes. Graduates with a master’s or
doctoral or equivalent degree have better employment opportunities and earnings prospects (see Indicator A4). However,
despite the earnings advantage from completing a master’s programme or a doctorate, tuition fees in public institutions for
full-time national students in these programmes are similar to those for bachelor’s programmes in the majority of OECD
countries (Table C5.1). The additional expenses that master’s and doctoral students face are limited to the additional years
of education and the foregone earnings due to the delayed entry into the labour market. In most countries where tuition is free
of charge at bachelor’s level, there are also no fees at master’s and doctoral levels. In other countries, similar tuition fees are
charged on average across the different levels of tertiary education, as in Austria, Canada, the Flemish Community of Belgium,
Italy, Japan, the Netherlands, Portugal and Switzerland (Table C5.1).
In contrast, tuition fees for master’s programmes in public institutions are about 30% higher than for bachelor’s programmes
in Chile, France, Korea and the United States, while in Australia, the French Community of Belgium and Spain they are over
50% higher (Table C5.1). These higher fees may limit participation at this level, if they are not paired with financial support to
students. In a few countries (e.g. Australia, Italy and Switzerland), public institutions charge lower fees for doctoral
programmes than for bachelor’s and master’s programmes to promote enrolment in doctoral programmes and attract talent
for research and innovation. In Australia, for example, the annual average tuition fees in public institutions for doctoral
programmes are about 15 times lower than for bachelor’s programmes (less than USD 300 compared to about USD 5 000).
In fact, very few national doctoral students are charged any fees in Australia (less than 5% of doctoral students in public
institutions). However, public institutions in Chile, France, Korea, New Zealand and the United States charge higher tuition
fees for doctoral programmes than for bachelor’s programmes (data for the United States refer to master’s and doctoral
programmes combined) (Table C5.1).
Differentiation by type of institution
Some institutions may struggle to strike a balance between offering an affordable education and their need for financial
resources, leading to different levels of tuition fees in different types of institutions (see Definitions section). 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
charge higher annual tuition fees than public institutions for bachelor's programmes in all OECD countries with available data
(Table C5.1). In addition, countries may differentiate tuition fees by field of study in order to attract students to certain fields
or to reflect differences in labour-market opportunities (see Box C5.1).

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C5. HOW MUCH DO TERTIARY STUDENTS PAY AND WHAT PUBLIC SUPPORT DO THEY RECEIVE?  325
In most OECD countries and economies with available data, over 80% of all students in bachelor’s programmes enrol in
public institutions. In only about one-fifth of OECD countries and economies are the majority of students enrolled in private
institutions. The share exceeds 85% in England (United Kingdom), Israel and Latvia, where the majority of students at this
level are enrolled in government-dependent private institutions (Table C5.1).
In over one-third of countries with available data, tuition fees for bachelor’s or equivalent programmes are at least twice as
high in independent private institutions as in public institutions (Figure C5.2). 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, average annual tuition
fees at this level are between USD 8 500 and USD 8 600 in independent private institutions, while they are 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 and Switzerland. In
the Slovak Republic, tuition fees for bachelor’s or equivalent programmes are around USD 2 100 in independent private
institutions, while public institutions do not charge tuition fees. Similarly, in Norway, the annual average tuition fees for
bachelor’s and master’s degrees combined are around USD 5 800 in independent private institutions, while there are no
tuition fees in public institutions (Table C5.1).
In contrast, the difference in average annual tuition fees at the bachelor’s or equivalent level between public institutions and
government-dependent private institutions is relatively small in most countries with available data. Neither type of institution
charges fees in Finland, Slovenia and Sweden, and government-dependent private and public institutions charge very similar
average tuition fees in Austria, Chile, the Flemish Community of Belgium and Israel (Table C5.1).

Figure C5.2. Tuition fees charged by tertiary educational institutions to national students for bachelor's
or equivalent programmes, by type of institution (2017/18)
Annual average (or most common) tuition fees charged to full-time national students
Public
Government-dependent private
Independent private

In USD converted
using PPPs
12 000

29 478

10 000
8 000
6 000
4 000
2 000

England (UK)1, 5

Latvia

Sweden

Slovenia

Slovak Republic

Greece

Norway

Finland

Denmark

Germany1, 9

France

French Comm. (Belgium)

Flemish Comm. (Belgium)

Austria1

Switzerland8

Portugal

Italy

Spain1

Israel

Netherlands

Ireland7

New Zealand5, 6

Korea4

Japan

Australia3

Canada

Chile

United States1, 2

0

1. Year of reference 2016/17.
2. Figures typically refer to tuition fees for out-of-state national students. However, in a minority of institutions, tuition fees can be lower for out-of-state national students.
3. Year of reference 2017.
4. Year of reference 2018.
5. Figures refer to short-cycle tertiary and bachelor's programmes combined.
6. Estimates include universities only and exclude postgraduate certificates and diplomas.
7. Tuition fees paid by students instead of fees charged by institutions. Figures cover universities only.
8. Figures for public institutions refer to both public and government-dependent private institutions combined.
9. Figures refer to bachelor's, master's and doctoral academic programmes combined.
Countries and economies are ranked in descending order of the annual tuition fees charged by public institutions for bachelor's or equivalent programmes.
Source: OECD (2020), Table C5.1. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2https://doi.org/10.1787/888934164940

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326  C5. HOW MUCH DO TERTIARY STUDENTS PAY AND WHAT PUBLIC SUPPORT DO THEY RECEIVE?

Box C5.1. Tuition fees by fields of study
OECD countries often differentiate tuition fees by field of study in order to attract students to fields that are less in demand
and to account for differences in costs and labour-market opportunities. The latter is one of the main reasons for
introducing differentiated fees, although in some countries differences in tuition fees between fields of study may result
from differences in tuition fees and enrolment between institutions rather than differences within institutions.

Figure C5.3. Tuition fees charged by tertiary public educational institutions to national students for
first-cycle tertiary programmes, by field of study (2017/18)
Annual average (or most common) tuition fees charged to full-time national students
F01 - Education
F02 - Arts and humanities
F03 - Social sciences, journalism and information
F04 - Business, administration and law
F05 - Natural sciences, mathem atics and statistics

In USD
converted
using PPPs
10 000

F09

F08

F06 - Information and Communication Technologies
F07 - Engineering, manufacturing and construction
F08 - Agriculture, forestry, fisheries and veterinary
F09 - Health and welfare
F10 - Services

F08

8 000
F10
F07
F09

6 000

F04

F01

F01
4 000

F03

F01

F08

F06

2 000
F01

F08
F06

Germany5, 6

Spain5

Israel

New Zealand3, 4

Canada

Chile

Australia2

Ireland1

0

1. Tuition fees charged by institutions differ significantly from those paid by students. See Figure C5.6 for more information.
2. Year of reference 2017.
3. Figures refer to both short-cycle tertiary and bachelor's programmes combined.
4. Estimates include universities only and exclude postgraduate certificates and diplomas.
5. Year of reference 2016/17.
6. Figures refer to bachelor's, master's and doctoral academic programmes combined.
Countries are ranked in descending order of the fields in which the highest average annual tuition fees are charged.
Source: OECD (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2https://doi.org/10.1787/888934164959

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C5. HOW MUCH DO TERTIARY STUDENTS PAY AND WHAT PUBLIC SUPPORT DO THEY RECEIVE?  327

The differences in fees charged by public institutions for different fields of study are limited for first-cycle degree
programmes (bachelor’s and long first master’s degrees) in Germany and Spain, while Australia, Canada, Chile and
Ireland have the largest range of tuition fees across fields of study. Australia has the greatest variation: public institutions
charge over USD 9 000 per year on average for first-cycle tertiary programmes in the two broad fields of engineering,
manufacturing and construction, and agriculture, forestry, fisheries and veterinary compared with just over USD 4 000 per
year for programmes in the field of education (Figure C5.3).
The fees charged by public institutions for programmes in the field of education are among the lowest in four out of the
seven countries with data available (Australia, Canada, Chile and Israel). Fields such as engineering, manufacturing and
construction; agriculture, forestry, fisheries and veterinary; and health and welfare are among the most expensive, as
some of them often have the highest market returns (Figure C5.3).

Differentiation for foreign students
Tuition fee policies 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 in fees for national and
foreign students can have an impact on the international flows of students (see Indicator B6), among other factors such as
public support from their home countries (OECD, 2017[2]). An increasing number of OECD countries charge higher tuition
fees to foreign students than to national ones.
National and foreign students are generally charged similar tuition fees in Chile, the Flemish Community of Belgium, France,
Israel, Italy, Japan, Korea and Spain. This is also the case in Greece, Norway and the Slovak Republic, where tuition is free
of charge for both national and foreign students. In the 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, in Australia, Canada, and
the United States, public institutions charge on average over USD 13 500 more per year for foreign students than for national
students at the bachelor’s level (Table C5.1). In the United States, national students who study outside their state also pay
higher tuition fees than in-state students. In Austria, although 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 programmes), these fees remain relatively moderate. In Sweden, tuition fees for non-EU bachelor’s students reach
USD 14 900 per year, while tuition is free for national students and citizens of EU countries. In Finland, as of the 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 (Table C5.1).
Higher tuition fees do not necessarily discourage foreign students from studying abroad, 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. For instance, in Australia, Austria and
Canada, international or foreign students make up at least 12% of students enrolled at the bachelor’s level, compared to only
5% across OECD countries (see Indicator B6).

Public reforms to tuition fees and public financial support to students
Reforms related to the level of tuition fees and the availability of scholarships, grants and loans are intensely debated in
national education policy. They are often discussed in tandem, 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 academic years
2007/08 and 2017/18, 12 out of 20 countries and economies with available information have undertaken tuition fee reforms.
In eight of them, reforms to tuition fees were accompanied by changes in the level of public subsidies available to students
(Table C5.2).
In over half of the countries with available data, tuition fees for bachelor’s degrees in public institutions have increased by at
least 15% over the past decade, in real terms. This is the case for countries like Canada, Italy, Spain and the United States,
where tuition fees in the academic year 2016/17 (2017/18 for Canada) were between 25% and 46% higher than in 2007/08.
The largest increase was in England (United Kingdom), where tuition fees tripled in the same period. The only two countries
that registered a decrease were Austria and Germany. In contrast, there was no change over this period among the countries

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328  C5. HOW MUCH DO TERTIARY STUDENTS PAY AND WHAT PUBLIC SUPPORT DO THEY RECEIVE?
charging no tuition fees in 2007/08 (Denmark, Finland, Greece, Norway, the Slovak Republic and Slovenia). In Australia,
Chile, France and Ireland, tuition fees remained fairly stable and did not increase by more than 10% (Table C5.2).
OECD countries have different approaches to providing financial support to students enrolled in tertiary education. Regardless
of the level of tuition fees, countries and economies can be categorised according to the level of public financial support
available to tertiary students. In Australia, Denmark, New Zealand, Norway and Sweden, at least 80% of national students
receive public financial support in the form of student loans, scholarships or grants, but no more than 20% of students do so
in Austria, the French Community of Belgium, Portugal and Switzerland (Figure B1.3). In these countries, public financial
support instead targets selected groups of students such as those from disadvantaged backgrounds or low-income families.
In recent years, OECD countries and economies have passed several reforms to improve access to tertiary education
(Table C5.2). In Chile, Greece, Korea and Portugal, measures were implemented to expand access to tertiary education to
students from disadvantaged backgrounds, while New Zealand increased public subsidies to make the first year of tertiary
education free of tuition fees for new students or trainees. From the academic year 2016/17, Norway started a reform to
gradually increase the State Educational Loan Fund’s financial support from ten to eleven months per year. In England
(United Kingdom), the threshold for the repayment of income-contingent loans for graduates from short-cycle tertiary and
bachelor's programmes was increased from the financial year 2018/19, and grants for living costs were replaced with larger
loans for new eligible national students from the academic year 2016/17. It also introduced the postgraduate master's loan
scheme in 2016 to improve access to master's programmes. In Australia, measures were taken to improve the sustainability
of the subsidy system for public institutions’ students enrolled in bachelor’s programmes (Table C5.2).
In the last decade, the share of students receiving public financial support increased by at least 14 percentage points in Chile
(from 17% in 2007/08 to 58% in 2017/18), Denmark (from 69% in 2007/08 to 83% in 2016/17) and Italy (from 17% in 2007/08
to 39% in 2017/18). This share remained stable in all other OECD countries and economies with available data (Figure B1.3).

Figure C5.4. Share of tertiary national students receiving public financial support (2007/08 and 2017/18)
Share of national tertiary students receiving public financial support in the form of public or government-guaranteed private
loans and/or grants/scholarships
2017/18
2007/08

%
100
90
80
70
60
50
40
30
20

Switzerland1

Austria1

Portugal

French Comm. (Belgium)

Italy

Spain1

Chile

Finland

Australia

Denmark1

New Zealand

Sweden

0

Norway

10

1. Year of reference 2016/17 instead of 2017/18.
Countries and economies are ranked in descending order of the share of tertiary students receiving public financial support in 2017/18.
Source: OECD (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2https://doi.org/10.1787/888934164978

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C5. HOW MUCH DO TERTIARY STUDENTS PAY AND WHAT PUBLIC SUPPORT DO THEY RECEIVE?  329

Forms of public financial support to tertiary national students
A key question that many educational systems face is whether to primarily use loans or to use grants or scholarships to
provide financial support for tertiary students. On the one hand, advocates of student loans argue that they allow a larger
number of students to benefit from the available resources (OECD, 2014[3]). If funding spent on scholarships and grants was
used to guarantee and subsidise loans, the same public resources could support a larger number of students, and overall
access to higher education would increase. Loans also shift some of the cost of higher education onto those who benefit from
it the most, 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 at 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 indebted
graduates could be a problem if their employment prospects are not sufficient to guarantee student loan repayments.
OECD governments support students’ living and education costs through different combinations of these two types of support
– and these combinations vary even among countries with similar levels of tuition fees. Among countries with data available,
the average amount of public or government-guaranteed private loans that students borrow each year ranges from USD 2 400
per student in Latvia to over USD 10 000 in England (United Kingdom) and Norway (where tuition is free of charge and loans
finance students’ living costs). Scholarships or grants received by students range from less than USD 1 000 per year in
Estonia and the Slovak Republic to over USD 7 000 in Australia, Austria, Denmark, Switzerland and the United States
(Figure B1.4). Among countries and economies with data on both forms of financial support, the total annual amounts received
by students are highest in England (United Kingdom) (where the system is largely based on loans), and Norway and the
United States (both Norway and the United States offer a combination of both loans and scholarships/grants). In Australia,
Denmark, Switzerland and the United States, the average amount of grants or scholarships received by students is more than
the average amount they borrow each year, but the proportion of beneficiaries of loans and grants/scholarships differs
between countries – for example, in Switzerland only a minority of students receive public financial support (OECD, 2019[1]).

Loans

Grants/scholarships

Australia

In USD converted
using PPPs
20 00 0

Switzerland1

Figure C5.5. Average annual amounts of public grants/scholarships and loans received by national
tertiary students (2017/18)

18 00 0
16 00 0
14 00 0
12 00 0
10 00 0
8 00 0
6 00 0
4 00 0

Estonia

French Comm. (Belgium)

Flemish Comm. (Belgium)

Portugal

Italy4

Austria1

Latvia

Denmark1

Slovak Republic

Chile

Korea3

Finland2

Canada1

United States1

Sweden

Japan

New Zealand

Netherlands

Norway

0

England (UK)1

2 00 0

1. Year of reference 2016/17 instead of 2017/18.
2. Government-guaranteed private loans instead of public loans.3. Year of reference 2018 instead of 2017/18.
3. Year of reference 2018 instead of 2017/18.
4. First- and second-cycle degrees only.
Countries and economies are ranked in descending order of loans' average annual amount borrowed by student loan beneficiaries.
Source: OECD (2020), Table C5.3. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
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330  C5. HOW MUCH DO TERTIARY STUDENTS PAY AND WHAT PUBLIC SUPPORT DO THEY RECEIVE?
In all countries with data available, loans can be used for tuition fees, study materials and living costs, except in Chile where
loans cover only tuition fees. Not all students are eligible to apply for student loans. The most common eligibility criteria for
loans are a low-income background and the need to report progress in studies (the extent of this varies by country), together
with citizenship or long-term residence and age (being at least 18 years old and below certain age thresholds that vary by
country). Outstanding academic performance is a requirement in Chile, Japan and Korea, and study performance is one of
the criteria required in Canada and Norway, while several OECD countries use means-tested financial assessments of
students’ households to determine their eligibility for loans (Table C5.3).
In half of the OECD countries and economies with data available, public grants and scholarships are extended on the basis
of both need and merit. Many countries prioritise public financial support for socio-economically disadvantaged students:
grants are referred to as needs-based if they take into account various socio-economic criteria (most frequently family
income). On the other hand, merit-based grants refer to grants awarded to the best-performing students, based on higher
education performance, on secondary school results or on admission tests scores. In the Flemish and French Communities
of Belgium, the Netherlands, Norway, and Switzerland, public grants and scholarships are needs-based only, while in Latvia
they are only awarded on the basis of students’ academic merit (Table C5.3). In France, merit-based grants were modified in
2015 and reserved for students who graduated from upper secondary education with a very good grade and who meet
scholarships’ socio-economic criteria for three years. As with loans, low income, disability, full-time enrolment and academic
progress are among the most common eligibility criteria for grants and scholarships. In Denmark, all full-time students are
entitled to a number of monthly grants and the maximum number of grants changes from one course to another. In Norway,
financial support is initially extended as a loan and, if students progress through their studies and do not live with their parents
(among other requirements), up to 40% of the amount may be converted to a grant. In the French Community of Belgium,
students’ residence is also taken into consideration for the allocation of grants (Table C5.3).
In addition to direct financial support to students in the form of public loans, guarantees on students’ private loans, grants and
scholarships, countries may also decide to provide indirect subsidies to tertiary education by fully or partially waiving tuition
fees charged by education institutions or by covering eventual additional charges applied to students. For this reason, in
addition to measuring direct public financial support, it is important to analyse the level of tuition fees ultimately paid by
students rather than those charged by tertiary educational institutions (see Box C5.2).

Box C5.2. Tuition fees paid by students
Tertiary education policies do not only depend on the overall amount of public financial resources but also on the
allocation of public funding (see Indicator C4). Some countries have decided to regulate tuition fees or not apply tuition
fees at all, while others may give education institutions autonomy to set the level of tuition fees. This may lead to high
tuition fees, which may be offset by direct financial support to students in the form of public loans, guarantees on student
private loans, grants and scholarships. This type of financial support is directly extended to the beneficiaries, provided
that they meet certain requirements.
Countries may also decide to provide indirect subsidies to tertiary education by fully or partially covering the tuition fees
charged by education institutions. This is the case in Ireland, where the tuition fees charged by public institutions for
bachelor’s programmes may exceed USD 8 700 but the majority of first-cycle tertiary students benefit from the Free Fees
Scheme and pay only an annual student contribution charge of USD 3 800 (EUR 3 000) towards the cost of their
programme of study (reference academic year 2017/18). Italy also reported that students pay slightly lower tuition fees
than those charged by institutions, while in the French Community of Belgium students are offered other fee reductions
and waivers based on their socio-economic status (Figure C5.6).
The fees actually paid by students are not necessarily always lower than those charged by institutions. In some countries
(e.g. Chile), students face additional fees on top of tuition (Figure C5.6). Austria, Chile, Finland, Italy, the Slovak Republic
and Slovenia reported additional charges, mostly related to administration, registration and student union membership.

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C5. HOW MUCH DO TERTIARY STUDENTS PAY AND WHAT PUBLIC SUPPORT DO THEY RECEIVE?  331

Figure C5.6. Tuition fees charged by educational institutions compared to those paid by students
(2017/18)
Tuition fees for bachelor's programmes in public tertiary educational institutions
Fees charged by institutions
Additional fees

In USD converted
using PPPs

Fees paid by students
Fees reductions/waivers

10 000
8 000
6 000
4 000
2 000

Ireland3

French Comm. (Belgium)

Slovenia2

Austria1

Slovak Republic

Finland

Italy

-2 000

Chile

0

Note: This figure plots only countries that reported additional fees or reductions or a difference between tuition fees charged by institutions and those paid by students.
1. Year of reference 2016/17.
2. Year of reference 2018.
3. Year of reference 2018/19.
Countries and economies are ranked in descending order of the additional fees that students pay and in ascending order of the fees' reductions they benefit of.
Source: OECD (2020), Table C5.2. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2https://doi.org/10.1787/888934165016

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 who are citizens of countries outside
the European Union. Further details on these definitions are available in Indicator B6.
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.

Methodology
Tuition fees and loan amounts in national currencies 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

EDUCATION AT A GLANCE 2020 © OECD 2020

332  C5. HOW MUCH DO TERTIARY STUDENTS PAY AND WHAT PUBLIC SUPPORT DO THEY RECEIVE?
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[4]) and Annex 3 for country-specific notes (https://doi.org/10.1787/69096873-en).

Source
Data refer to the academic 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/10.1787/69096873-en).

References

OECD (2019), Education at a Glance 2019: OECD Indicators, OECD Publishing, Paris,
https://dx.doi.org/10.1787/f8d7880d-en.

[1]

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.

[4]

OECD (2017), “Tuition fee reforms and international mobility”, Education Indicators in Focus, No. 51, OECD
Publishing, Paris, https://dx.doi.org/10.1787/2dbe470a-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

Trends and reforms in tuition fees and public financial support to tertiary education (2007/08 to 2017/18)

Table C5.3

Public financial support to national students enrolled in tertiary programmes (2017/18)

WEB Table C5.4

Interest subsidies, repayment and remission of public loans to students in tertiary education (2017/18)

Cut-off date for the data: 19 July 2020. Any updates on data can be found on line at http://dx.doi.org/10.1787/eag-dataen.
StatLink: https://doi.org/10.1787/888934164845
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C5. HOW MUCH DO TERTIARY STUDENTS PAY AND WHAT PUBLIC SUPPORT DO THEY RECEIVE?  333

Bachelor’s

Master’s

Short-cycle tertiary

Bachelor’s

Master’s

Short-cycle tertiary

Bachelor’s

Master’s

(6)

(7)

(8)

(9)

(10)

(11)

(12)

(13)

(14)

(15)

4 340

4 961

8 799

x(10)

x(11)

x(12)

6 544 d

m

18 751

m

936

936

m

936

936

m

m

m

m

1 870

1 870

m

5 493

5 744

m

a

a

m

a

a

m

21 207

13 552

22

3 312

7 361

10
220 3 729

8 383

9 935

3 570

6 577

10 495

99 100

0

0

m

0

a

a

a

Master’s

(5)

Bachelor’s

Short-cycle tertiary

Public institutions

Master’s

Foreign students

Bachelor’s

National students
Independent private
institutions

(4)

(2)

(3)

18

92

90

82

77

85

Canada

m 100 100

Chile

4

20

Denmark

98

Austria 2

Government-dependent
private institutions

Short-cycle tertiary

Public institutions

(1)
Countries
Australia 1

National students

Share of
enrolment
in public
institutions
Short-cycle tertiary
OECD

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, for full-time students, by type of institutions and level of education

0

0

9 223 d 11 847 d

18 051

No differentiation for foreign students
m
a

m

m

Tuition fees may apply for students
outside EU/EEA area

Finland

a

38

82

a

0

0

a

0

0

a

a

a

France

65

85

71

0

240

334

m

m

m

m

m

m

Germany 2, 3

78

86

95

m

136 d

x(5)

m

x(11)

x(11)

m

5 011 d

x(11)

Greece

a 100 100

a

0

4 187

a

a

a

a

a

a

No differentiation for foreign students

Ireland 4

89

97

87

m

8 708 10 428

m

m

m

m

m

m

m

Israel

45

12

12

m

3 141

m

m

3 138

m

m

6 890

m

No differentiation for foreign students

No differentiation for foreign students
m

x(5)
m

Italy

0

86

89

a

1 953

2 179

a

a

a

m

6 802

8 164

No differentiation for foreign students

Japan

7

20

47

3 681

5 090

5 087

a

a

a

6 642

8 541

7 433

No differentiation for foreign students

x(5)
21 965

Korea5

2

23

31

2 717

4 785

6 281

a

a

a

6 918

8 578

11 511

No differentiation for foreign students

Latvia

45

a

a

m

a

a

3 046

4 348

4 565

3 898

4 714

5 550

m

a

a

Netherlands

36

90

65

2 577

2 577

2 577

a

a

a

m

m

m

m

m

m

New Zealand 6, 7

55

94

97

x(5) 4 541 d

m

m

m

m

m

m

m

m

m

m

Nor way

72

82

93

2 469

0

0 5 342

1 018 d

x(8)

0

5 765 d

x(11)

Por tugal 8

81

79

87

1 529

1 529

1 529

m

m

m

m

m

m

Slovak Republic

64

88

86

0

0

0

a

a

a

a

2 059

2 464

No differentiation for foreign students
m

m

m

No differentiation for foreign students

Slovenia

72

84

91

0

0

0

0

0

0

0

0

0

Spain 2

75

83

71

0

1 782

2 930

m

a

a

m

7 926

12 270

Sweden

42

94

92

0

0

0

0

0

0

a

a

a

0

14 909

14 909

Switzerland 9

11

80

95

m 1 305 d 1 305 d

m

x(5)

x(6)

m

3 238

3 238

m

m

m

United States 2 , 10

91

68

48

a

a

a

14 587

24 854

m

3 156

8 804 11 617 d

29 478 24 712 d

m

m

m

No differentiation for foreign students

7 668

Economies
Flemish Comm. (Belgium)

39

42

47

French Comm. (Belgium)

m

m

m

a

England (UK) 2 , 6

a

a

a

a

8

388

655

655

542 d 1 004 d
a

a

m

m

No differentiation
m
for foreign
students

No differentiation for foreign
students, but institutions have
the autonomy to determine tuition
fees for students from outside
the EEA.

388

655

655

a

x(5)

x(6)

a

a

a

a

m

m

x(8) 12 038 d

m

a

a

a

a

a

a

Note: No tuition fees charged by educational institutions are reported as zero.
1. Year of reference 2017 for tuition fees.
2. Year of reference 2016/17.
3. Master's and doctoral programmes included with bachelor's programmes. Only academic programmes are included.
4. Universities only. The majority of undergraduate students in Ireland avail of the Free Fees Scheme and would pay USD 3 806 towards the cost of their programme of study.
5. Year of reference 2018.
6. Short-cycle tertiary programmes are included in bachelor's or equivalent programmes
7. Estimates include universities only and exclude postgraduate certificates and diplomas.
8. Average between minimum and maximum tuition fees charged.
9. Government-dependent private institutions are included in public institutions.
10. Master's and doctoral levels are combined. 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-of-state national students.
Source: OECD (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2https://doi.org/10.1787/888934164864
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334  C5. HOW MUCH DO TERTIARY STUDENTS PAY AND WHAT PUBLIC SUPPORT DO THEY RECEIVE?
Table C5.2. Trends and reforms in tuition fees and public financial support to tertiary education (2007/08 to 2017/18)
Students enrolled in full-time and part-time programmes in both public and private institutions

1. Year of reference 2016/17 instead of 2017/18.
2. Year of reference 2008 instead of 2007/08.
3. Year of reference 2018/19 instead of 2017/18.
4. Year of reference 2018 instead of 2017/18.
5. Year of reference 2009/10 instead of 2007/08. Includes government-dependent private institutions.
6. Year of reference 2006/07 instead of 2007/08.
Source: OECD (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2https://doi.org/10.1787/888934164883
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C5. HOW MUCH DO TERTIARY STUDENTS PAY AND WHAT PUBLIC SUPPORT DO THEY RECEIVE?  335

Table C5.3. Public financial support to national students enrolled in tertiary programmes (2017/18)
Students enrolled in full-time and part-time programmes in both public and private institutions

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336  C5. HOW MUCH DO TERTIARY STUDENTS PAY AND WHAT PUBLIC SUPPORT DO THEY RECEIVE?

1. Year of reference 2016/17.
2. Government-guaranteed private loans instead of public loans.
3. First- and second-cycle degree programmes only.
4. Year of reference 2018.
5. Year of reference 2015/16.
Source: OECD (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2https://doi.org/10.1787/888934164902

EDUCATION AT A GLANCE 2020 © OECD 2020

338  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, most of the spending in educational institutions – 92% on average across OECD
countries – is devoted to current expenditure.



On average across OECD countries, staff compensation comprises the largest share of current expenditure at all
levels of education (74%), accounting for a larger share in non-tertiary (primary, secondary and post-secondary
non-tertiary) education (77%) than in tertiary education (67%).



Staff compensation constitutes a higher share of current expenditure in public institutions than in private ones
across OECD countries, both at non-tertiary level (79% in public institutions and 72% in private ones) and at
tertiary level (67% in public institutions and 63% in private ones).

Figure C6.1. Share of capital expenditure, by type of institution (2017)
Primary to tertiary education
Private institutions

%
20

Public institutions

15
10

Italy

Brazil

Portugal
United Kingdom
Mexico

Iceland
Sweden
Costa Rica2

Belgium

Spain
Chile
Ireland
Slovak Republic

Poland
Austria
Denmark
Lithuania

Slovenia
EU23 average
Germany

OECD average

Czech Republic
France

Estonia
Russian Federation

United States
Canada1
Australia
Luxembourg
Hungary

Argentina
Finland

Israel
Netherlands

Japan

Turkey
Greece
Latvia

0

Korea
Norway

5

1. Primary education includes pre-primary programmes.
2. Year of reference 2018.
Countries are ranked in descending order of the share of capital expenditure in public institutions.
Source: OECD/UIS/Eurostat (2020), Education at a Glance Database, http://stats.oecd.org/.See Source section for more information and Annex 3 for notes
(https://doi.org/10.1787/69096873-en ).
Statlink2 https://doi.org/10.1787/888934165111

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C6. ON WHAT RESOURCES AND SERVICES IS EDUCATION FUNDING SPENT?  339

Context
How education spending is allocated between current and capital expenditure affects the provision of services such as
meals, transport, housing and research activities; the level of staff salaries; the material conditions under which instruction
takes place (via the expenditure on school buildings and maintenance); and the ability of the education system to adjust
to changing demographic and enrolment trends.
Decisions about the resources devoted to educational institutions and their allocation between short-term and long-term
goods and services can thus influence the quality of instruction and, by extension, student learning outcomes. Striking a
proper balance that reflects their country’s educational priorities, is a challenge all governments and institutions face,
especially in times of crisis and competing priorities. Comparing the amount and distribution of educational expenditure
across resource categories, and over time, can shed some light on the various organisational and operational
arrangements developed by countries.
This indicator describes how money for educational institutions from all funding sources (governments, international
sources and the private sector) is spent on educational goods and services, both overall and by type of institution (public
or private). It also analyses how spending has varied over time, covering the five-year period from 2012 to 2017.

Other findings


OECD countries allocate on average 8% of their total education spending to capital expenditure from primary to
tertiary level. Overall, the share of capital expenditure is higher at tertiary level (10%) than at non-tertiary level
(7%). Large variations in the share of capital expenditure are observed across countries, with higher values in
Korea, Norway and Turkey.



In absolute terms, from primary to tertiary level the average current expenditure per full-time equivalent student
in OECD countries was about USD 10 900 in 2017, while the average capital expenditure was about USD 900
per student. These amounts vary widely across OECD countries, however: current expenditure ranges from about
USD 4 600 per student in Turkey to about USD 22 000 in Luxembourg, while capital expenditure ranges from
almost USD 250 per student in Italy to around USD 2 200 in Norway.



On average across OECD countries, expenditure on staff compensation per full-time equivalent student is higher
at the tertiary level (USD 10 100) than at the non-tertiary level (USD 7 100).



Between 2012 and 2017, current expenditure per student on primary to tertiary education in public institutions
slightly increased on average across OECD countries, with an average annual growth rate of more than 1% in
real terms.

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340  C6. ON WHAT RESOURCES AND SERVICES IS EDUCATION FUNDING SPENT?

Analysis
Distribution of educational institutions’ current and capital expenditure by education level
Expenditure on education is composed of current and capital expenditure. Current expenditure includes staff compensation
and spending on the goods and services needed each year to operate schools and universities, while capital expenditure
refers to spending on the acquisition or maintenance of assets which last longer than one year (see Definitions section).
Differences in current and capital expenditure allocation across countries reflect the degree to which countries have invested
in the construction of new buildings – for example as a response to increases in enrolment rates – or in the restoration of
existing school premises, due to obsolescence and ageing of existing structure, or the need to adapt to new educational,
societal or safety needs. Unlike current expenditure, capital expenditure can show large fluctuations over time, with peaks in
years when investment plans are implemented, followed by years of lows.
Given the labour-intensive nature of education, current expenditure represents the largest proportion of total expenditure on
education in OECD countries. In 2017, current expenditure accounted for 92% of total expenditure on primary to tertiary
educational institutions in OECD countries, with the remainder devoted to capital expenditure. On average, the overall share
of current expenditure does not differ by more than 3 percentage points across education levels but there are larger
differences across countries. The share of current expenditure on institutions from primary to tertiary level ranges from 87%
in Turkey, Norway and Korea to 98% in Italy (Table C6.1). Broken down by educational level, the share ranges from 85% in
Korea to 99% in Italy at primary, secondary and post-secondary non-tertiary level, and from 57% in Greece to 98% in Chile
and Iceland at the tertiary level (Table C6.1).
Capital expenditure represents 8% of expenditure on primary to tertiary educational institutions on average across OECD
countries, but reaches 10% or more in Australia, Japan, Korea, Latvia, Netherlands, Norway, and Turkey (Table C6.1). The
share of capital expenditure is higher at tertiary level (10%) than at non-tertiary – i.e. primary, secondary and post-secondary
non-tertiary – level (7%). Some OECD and partner countries have massively invested in infrastructure at the tertiary level: in
2017, capital expenditure on tertiary education reached 20% in Turkey and 43% in Greece. At non-tertiary level, Korea
allocates 15% of its education budget to capital expenditure, the highest share across countries with available data
(Table C6.1 and Figure C6.1).
In 2017, the average current expenditure per full-time equivalent student across OECD countries was almost USD 11 000,
with higher values at tertiary level (USD 16 000) than at non-tertiary level (USD 9 300). Across all education level, current
expenditure per student varies widely across OECD countries, ranging from about USD 4 600 in Turkey to about USD 22 000
in Luxembourg. The average capital expenditure is less than USD 1 000 per student; the countries that invested more in longterm assets in 2017 were Korea, Luxembourg, Norway and the United States (over USD 1 500 per student), while Chile,
Colombia, Italy, Lithuania and the Russian Federation invested the least (below or around USD 500) (Table C6.1).

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 (including teaching materials
and supplies, ordinary maintenance of school buildings, provision of meals and dormitories to students, and rental of school
facilities). Current and projected changes in enrolment, changes to the salaries of education personnel, and the different costs
of maintaining education facilities over time and across education levels can affect not only the amounts, but also the shares
allocated to each category.
In 2017, compensation of teachers and other staff employed in educational institutions comprised the largest share of current
expenditure from primary to tertiary education (74% on average across OECD countries) but this varies significantly across
countries and within education levels (Table C6.2 and Figure C6.2). On average across OECD countries, the share of staff
compensation on total current expenditure is higher in non-tertiary education (77%) than in tertiary education (67%), due to
the higher costs of facilities and equipment in tertiary education. Belgium, France, Greece and Poland report the greatest
share of current expenditure allocated to staff compensation at tertiary level (above or around 75%). At non-tertiary levels,
Belgium, Colombia and Portugal devoted 85% or more of educational expenditure on staff compensation, the highest across
OECD and partner countries, meaning they devoted less to other contracted and purchased services, such as support
services (e.g. building maintenance), ancillary services (e.g. meal programmes) and rent for school buildings and other
facilities (Table C6.2 and Figure C6.2).

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C6. ON WHAT RESOURCES AND SERVICES IS EDUCATION FUNDING SPENT?  341
In countries with available data, compensation of teachers represents a higher share of current expenditure than other nonteaching staff, especially in non-tertiary education. The difference in spending between teaching and non-teaching staff
reflects the degree to which educational institutions count non-teaching personnel (such as principals, guidance counsellors,
bus drivers, school nurses, janitors and maintenance workers) among their staff members. At tertiary level, compensation of
staff involved in research and development may also explain some of the differences between the share of expenditure
allocated to teaching and non-teaching staff across countries and different levels of education (see Indicator C1).

Figure C6.2. Distribution of current expenditure in public and private educational institutions (2017)
Other current expenditure
Compensation of non-teaching staff
Compensation of teachers
Compensation of all staff (if bre akdowns not available)
%
100

Primary, secondary and post-secondary non-tertiary education

90
80
70
60
50
40
30
20

Finland

Czech Republic

Chile

Italy

Chile

United Kingdom

Japan3

Estonia

Sweden

Australia

Turkey

Iceland
Korea

Poland

Estonia

Austria

Latvia

Hungary

Hungary

United States

Korea

EU23 average

Sweden

Slovak Republic

Italy

Australia

Latvia

OECD average

Slovenia

United Kingdom

Austria

%
100

Lithuania

Netherlands

Spain

France

United States

Russian Federation

Israel

Norway

Canada2

Germany

Japan

Luxembourg

Portugal

Colombia1

0

Belgium

10

Tertiary education

90
80
70
60
50
40
30
20

Finland

Canada

Germany

Luxembourg

Turkey

OECD average

Norway

EU23 average

Israel

Russian Federation

Slovenia

Portugal

Lithuania

Iceland

Netherlands

Spain

Poland

Belgium

France

0

Greece

10

1. Year of reference 2018.
2. Primary, secondary and post-secondary non-tertiary education includes pre-primary programmes.
3. Tertiary education includes post-secondary non-tertiary education.
Countries are ranked in descending order of the share of all staff compensation.
Source: OECD/UIS/Eurostat (2020), Table C6.2. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en ).
Statlink2 https://doi.org/10.1787/888934165130
EDUCATION AT A GLANCE 2020 © OECD 2020

342  C6. ON WHAT RESOURCES AND SERVICES IS EDUCATION FUNDING SPENT?
In 2017, OECD countries spent on average about USD 7 900 per full-time equivalent student on staff compensation from
primary to tertiary levels, with higher values at tertiary level (USD 10 100 per student) than at non-tertiary level (USD 7 100).
However, there were substantial variations across countries and educational levels. At primary, secondary and postsecondary non-tertiary level, expenditure per student on staff compensation ranges from less than USD 3 000 in Chile,
Colombia, Costa Rica and Turkey to more than USD 10 000 in Austria, Belgium, Luxembourg and Norway. At tertiary level,
spending on staff compensation per student exceeds USD 15 000 in Canada, Luxembourg, Sweden and the United States
(Table C6.2).
Variations in the share of current expenditure for expenses other than staff compensation (such as equipment available to
staff, contracted services and rent) reflects the different cost structures of educational institutions across countries. Facilities
and equipment costs are 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. Chile
devotes the largest share to other current expenditure at both tertiary (52% of total current expenditure), and non-tertiary level
(43%) (Table C6.2 and Figure C6.2).

Distribution of current and capital expenditure by type of educational institution
On average across OECD countries, public and private institutions divide their spending between current and capital
expenditure in a similar way. There is wide variation across countries, however. The share of current expenditure is at least
10 percentage points higher in public institutions than in private ones at non-tertiary level in Poland, and Portugal, and at
tertiary level in Australia. Capital expenditure accounts for 10% among public institutions and 9% among private ones at
tertiary level, while at non-tertiary level accounts for 7% among public institutions and 6% among private ones. However, the
proportions vary across countries (Table C6.3). At non-tertiary level, capital expenditure accounts for more than 15% of total
expenditure in public institutions in Korea, while the share is over 15% in private institutions in Poland. Costa Rica and Italy
record the lowest share of capital expenditure in public institutions at this level (1%), while in the Czech Republic, Norway
and Slovenia, private institutions recorded no capital expenditure in 2017. At tertiary level, public institutions in Greece,
Hungary and Turkey have the highest shares of capital expenditure, at over 15%, while the highest shares for private
institutions are observed in Australia, Hungary and Turkey, also over 15% (Table C6.3 and Figure C6.1).
Public and private institutions differ in how current expenditure is distributed. Staff compensation accounts for a larger share
of current expenditure in public institutions across OECD countries: 79% compared to 72% in private ones at non-tertiary
level, and 67% compared to 63% at tertiary level. Private institutions may be more likely to contract services from external
providers, or to rent school buildings and other facilities (as opposed to public institutions operating in state-owned properties),
or to be at a disadvantage when purchasing teaching materials, as they cannot benefit from the same economies of scale in
procurement as the public sector. In a number of countries, however, the share of current expenditure allocated to staff
compensation is higher in private institutions, with differences of over 5 percentage points in the Netherlands and Norway at
non-tertiary level, and Finland, Israel, Japan, Korea and the Netherlands at tertiary level (Table C6.3).
Expenditure per student on compensation of teachers in non-tertiary public institutions is generally higher than in private
institutions for countries with available data, and amounts to USD 5 900 on average. The biggest differences (over
USD 3 000) are found in Canada, Italy and Luxembourg. In contrast, in Colombia, Estonia, Korea, Lithuania,
the Slovak Republic and the United Kingdom, expenditure on staff compensation per student is higher in private institutions.
At tertiary level, the largest difference between staff compensation per student in public and private institutions among
countries with available data is observed in Austria and Finland (above USD 4 000). However, France, the Slovak Republic
and the United States spend more on staff compensation per student in private tertiary institutions than in public ones
(Table C6.3).

Trends in current and research expenditure per student
The share of resources devoted to a given category of expenditure highlights how they are allocated compared to other costs,
but provides no information about whether that funding is sufficient to cover students’ educational needs or the teaching
requirements of teachers. Although the shares devoted to current and capital expenditure do not show much variation on
average over time – with current expenditure at about 90% of total expenditure – the amount of current and capital expenditure
per full-time equivalent student shows greater variability across countries and over time. These changes are due to the
combination of changes in the resources devoted to education and in the student population.

EDUCATION AT A GLANCE 2020 © OECD 2020

C6. ON WHAT RESOURCES AND SERVICES IS EDUCATION FUNDING SPENT?  343
In the five-year period between 2012 and 2017, the average annual growth rate of current expenditure per student in public
institutions from primary to tertiary education has been higher than 1% across OECD countries. The greatest increase (over
4%) has been observed in Hungary, Iceland, the Slovak Republic and Turkey, with Iceland and the Slovak Republic also
experiencing the biggest increases in staff compensation per student. In Finland, Greece, Mexico and Slovenia, on the other
hand, current expenditure per student decreased, driven by a reduction in staff compensation per student. Among private
institutions, current expenditure per student at primary to tertiary level remained generally stable between 2012 and 2017 in
countries with available data, although there were increases of over 1% per year in Hungary, Iceland, Norway, Sweden and
the United States (Table C6.4, available on line).
Teachers’ compensation per student in public institutions slightly increased between 2012 and 2017 in countries with available
data, with larger increases at tertiary level than at lower levels of education. At tertiary level it increased the most in
the Czech Republic, Iceland and the Slovak Republic (between 7% and 11% on average per year), while the biggest annual
decreases have been recorded in Greece and Mexico (around or greater than 5%). At non-tertiary level, Colombia, Iceland,
Portugal and the Slovak Republic experienced the biggest increases (greater than 4%), while the biggest fall was observed
in Finland (2%) (Table C6.4, available on line).
The average annual growth rate in expenditure on research and development (R&D) per student in public tertiary institutions
between 2012 and 2017 shows wide variation across countries. Average increases exceeded 5% per year in Brazil, Finland
and Luxembourg. The latter two are also, along with Denmark, Germany, Norway and Sweden, the OECD countries with the
highest expenditure on R&D as a share of total tertiary expenditure (see Table C1.2). While in Luxembourg and Norway the
expenditure on R&D increased in parallel with increases in total expenditure on tertiary education, in Finland total expenditure
on tertiary education was falling over the same period. In contrast, spending on R&D per student in public institutions fell by
more than 1% in France, Greece, Lithuania, Mexico, Portugal and Turkey, with the largest fall observed in Portugal and
Turkey. While in most of these countries the negative trend is partly explained by an increase in the number of students
without any proportional increase in funds devoted to R&D, in Portugal the number of students in public universities actually
decreased over the reference period, meaning that expenditure on R&D fell faster than the number of students (Table C6.4,
available on line).
Comparing trends in R&D spending per student in public and private institutions in countries with available data, the picture
is somewhat mixed. In Belgium, both trends are positive, but R&D in public institutions grew faster than in private ones; in
Chile, Hungary, Norway and the United States both trends are also positive, but R&D in private institutions grew faster, while
in Finland, and Sweden spending on R&D rose in public institutions but fell in private institutions. In Italy, Lithuania, Spain
and Turkey, spending on R&D fell in both public and private institutions, but more in private institutions. Finally, in
the Czech Republic and Portugal, spending on R&D decreased in public institutions while it increased in private institutions
(Table C6.4, available on line).

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 capital nor current expenditure
includes debt servicing.
Current expenditure refers to spending on staff compensation and on “Other current expenditure”, i.e. on goods and services
consumed within the current year, which require recurrent production in order to sustain educational services (expenditure on
support services, ancillary services like preparation of meals for students, rental of school buildings and other facilities, etc.).
These services are obtained from outside providers, unlike the services provided by education authorities or by educational
institutions using their own personnel.
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.
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
EDUCATION AT A GLANCE 2020 © OECD 2020

344  C6. ON WHAT RESOURCES AND SERVICES IS EDUCATION FUNDING SPENT?
or third parties to finance retirement benefits for current educational personnel); and 3) expenditure on other non-salary
compensation (healthcare or health insurance, disability insurance, unemployment compensation, maternity and childcare
benefits and other forms of social insurance). The “teachers” category includes only personnel who participate directly in the
instruction of students. The “non-teaching staff” category includes other pedagogical, administrative and professional
personnel as well as support personnel (e.g. head teachers, other school administrators, supervisors, counsellors, school
psychologists and health personnel, librarians, and building operations and maintenance staff). At tertiary levels, "teaching
staff" includes personnel whose primary assignment is instruction or research. This cathegory excludes student teachers,
teachers’ aides and paraprofessionals.

Methodology
The annual average growth rate is calculated using the compound annual growth rate, which is the “common ratio” of a
geometric progression over the time period under analysis. A geometric progression, in turn, is a sequence of numbers where
each term after the first one is obtained by multiplying the previous one by a fixed, non-zero number (the common ratio).
Assuming a linear trend, the compound growth rate hence represents the constant percentage change between one year’s
value and the previous year’s.
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).
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 part-time enrolment have higher apparent expenditure per full-time equivalent student on educational institutions
than those that cannot differentiate between the different types of attendance.
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/10.1787/69096873-en ).

Source
Data refer to the financial year 2017 (unless otherwise specified) and are based on the UNESCO, the OECD and Eurostat
(UOE) data collection on education statistics administered by the OECD in 2019 (for details see Annex 3 at
https://doi.org/10.1787/69096873-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 2012 to 2017 were updated based on a survey in 2019-20, and expenditure figures for 2012 to
2017 were adjusted to the methods and definitions used in the current UOE data collection.

EDUCATION AT A GLANCE 2020 © OECD 2020

C6. ON WHAT RESOURCES AND SERVICES IS EDUCATION FUNDING SPENT?  345

References

OECD (2019), Education at a Glance 2019: OECD indicators, OECD Publishing, Paris,
https://dx.doi.org/10.1787/eag-2019-en.

[2]

OECD (2018), OECD Handbook for Internationally Comparative Education Statistics 2018: Concepts, Standards,
Definitions and Classificatons, OECD Publishing, Paris, https://doi.org/10.1787/9789264304444-en (accessed
on 16 April 2020).

[1]

Indicator C6 Tables
Table C6.1

Share of current and capital expenditure, by education level (2017)

Table C6.2

Current expenditure, by resource category (2017)

Table C6.3

Share of current expenditure, by resource category and type of institution (2017)

WEB Table C6.4

Average annual growth rate of current and R&D expenditure per full-time equivalent student, by type of
institution (2012-17)

Cut-off date for the data: 19 July 2020. Any updates on data can be found on line at http://dx.doi.org/10.1787/eag-dataen. More breakdowns can also be found at http://stats.oecd.org/, Education at a Glance Database.
StatLink: https://doi.org/10.1787/888934165035

EDUCATION AT A GLANCE 2020 © OECD 2020

346  C6. ON WHAT RESOURCES AND SERVICES IS EDUCATION FUNDING SPENT?
Table C6.1. Share of current and capital expenditure, by education level (2017)
Distribution of current and capital expenditure from public and private sources
Secondary
Lower secondary Upper secondary

Primary

All secondary

Par tners

OECD

Current Capital Current Capital Current Capital Current Capital
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
Countries
Australia
Austria
Belgium
Canada 1, 2
Chile
Colombia 2, 3
Costa Rica3
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungar y
Iceland 4
Ireland
Israel
Italy
Japan
Korea
Latvia
Lithuania
Luxembourg
Mexico
Netherlands
New Zealand
Nor way
Poland
Por tugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
Unite d Kingdom
United States

91
92
95
92 d
94
94
m
90
m
90
88
93
94
98
97
94
m
88
99
87
83
88
95
91
m
89
m
86
93
97
96
94
97
96
m
91
97
91

9
8
5
8d
6
6
m
10
m
10
12
7
6
2
3
6
m
12
1
13
17
12
5
9
m
11
m
14
7
3
4
6
3
4
m
9
3
9

90
96
97
x(1)
94
95
m
90
m
91
88
93
94
99
97
94
95
x(5)
99
88
86
88
95
91
m
90
m
86
94
97
98
94
97
96
m
91
96
91

10
4
3
x(2)
6
5
m
10
m
9
12
7
6
1
3
6
5
x(6)
1
12
14
12
5
9
m
10
m
14
6
3
2
6
3
4
m
9
4
9

90
98
97 d
92
93
93
m
95
98
95
91 d
92
91
97
95
99
m
93 d
99 d
91 d
89
89
95
92
m
91
m
87
92
89 d
94
92
97 d
95
m
88
96
91

10
2
3d
8
7
7
m
5
2
5
9d
8
9
3
5
1
m
7d
1d
9d
11
11
5
8
m
9
m
13
8
11 d
6
8
3d
5
m
12
4
9

90
97
97 d
92
93
95
m
93
m
93
90 d
92
93
98
96
97
m
93
99 d
89 d
88
89
95
92
m
90
m
87
93
93 d
96
93
97 d
95
m
89
96
91

10
3
3d
8
7
5
m
7
m
7
10 d
8
7
2
4
3
m
7
1d
11 d
12
11
5
8
m
10
m
13
7
7d
4
7
3d
5
m
11
4
9

Primary,
secondary and
Post-secondary non- post-secondary
tertiary
non-tertiary
Current
(9)

Primary
to tertiary

Tertiary

Capital Current Capital Current Capital Current Capital
(10)
(11)
(12)
(13)
(14)
(15)
(16)

91
9
99
1
x(5, 7)
x(6, 8)
m
m
a
a
m
m
a
a
95
5
a
a
98
2
x(5, 7)
x(6, 8)
92
8
94
6
m
m
90
10
98
2
m
m
100
0
x(5, 7)
x(6, 8)
x(5, 7, 13) x(6, 8, 14)
a
a
92
8
95
5
100
0
a
a
a
a
m
m
87
13
91
9
x(5, 7)
x(6, 8)
95
5
a
a
x(5, 7)
x(6, 8)
94
6
m
m
a
a
a
a
89
11

90
95
96
92 d
94
94
m
92
m
92
89
93
93
m
95
95
m
90
99
89
85
88
95
91
m
90
m
86
93
95
96
93
97
96
m
90
96
91

10
5
4
8d
6
6
m
8
m
8
11
7
7
m
5
5
m
10
1
11
15
12
5
9
m
10
m
14
7
5
4
7
3
4
m
10
4
9

84
92
95
90
98
m
m
m
97
91
95
92
92
57
81
98
m
93
93
88 d
90
90
93
93
m
90
m
89
91
95
m
93
89
96
m
80
87
90

16
8
5
10
2
m
m
m
3
9
5
8
8
43
19
2
m
7
7
12 d
10
10
7
7
m
10
m
11
9
5
m
7
11
4
m
20
13
10

88
94
96
91 d
95
m
m
m
m
92
91
92
93
m
92
96
m
91
98
88
87
89
94
92
m
90
m
87
92
95
m
93
95
96
m
87
93
90

12
6
4
9d
5
m
m
m
m
8
9
8
7
m
8
4
m
9
2
12
13
11
6
8
m
10
m
13
8
5
m
7
5
4
m
13
7
10

OECD average

93

7

93

7

93

7

93

7

m

m

93

7

90

10

92

8

EU23 average

94

6

94

6

94

6

94

6

m

m

94

6

90

10

93

7

m
m
m
m
m
x(5, 7)
m
m

m
m
m
m
m
x(6, 8)
m
m

m
m
m
m
m
x(5, 7)
m
m

m
m
m
m
m
x(6, 8)
m
m

m
m
m
m
m
93 d
m
m

m
m
m
m
m
7d
m
m

m
m
m
m
m
93 d
m
m

m
m
m
m
m
7d
m
m

m
m
m
m
a
x(5, 7)
m
m

m
m
m
m
a
x(6, 8)
m
m

m
m
m
m
m
93
m
m

m
m
m
m
m
7
m
m

m
m
m
m
m
90
m
m

m
m
m
m
m
10
m
m

m
m
m
m
m
92
m
m

m
m
m
m
m
8
m
m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

Argentina
Brazil
China
India
Indonesia3
Russian Federation
Saudi Arabia
South Africa
G20 average

Note: Data on expenditure per student for primary to tertiary education (Columns 17 to 22) are available for consultation on line (see StatLink below). The figures for current
and capital expenditure reported on line might not correspond to the total expenditure on educational institutions reported in Table C1.1. This is because the institutions
have either increased or reduced their fund balances during the period in question. 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. Post-secondary non-tertiary figures are treated as negligible.
3. Year of reference 2018.
4. Total current expenditure includes capital expenditure in private institutions. Capital expenditure only includes expenditure in public institutions.
Source: OECD/UIS/Eurostat (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en ).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888934165054

EDUCATION AT A GLANCE 2020 © OECD 2020

C6. ON WHAT RESOURCES AND SERVICES IS EDUCATION FUNDING SPENT?  347

Table C6.2. Current expenditure, by resource category (2017)
Distribution of current expenditure from public and private sources as a percentage of total current expenditure
Primar y, secondar y
and post-secondar y non-ter tiar y

Par tners

Total

(1)

(2)

(3)

59
66
70
67 d
36
82
m
43
m
47
50
59
x(3)
m
x(3)
53
m
x(3)
60
x(3)
58
x(3)
56
78
m
x(3)
m
x(3)
x(3)
76
60
x(3)
71
53
m
x(3)
68
54

17
8
19
15 d
22
7
m
18
m
25
12
22
x(3)
m
x(3)
20
m
x(3)
16
x(3)
17
x(3)
24
6
m
x(3)
m
x(3)
x(3)
9
16
x(3)
10
14
m
x(3)
10
27

76
74
89
82 d
57
89
m
61
m
72
62
80
82
m
76
74
m
81
76
83
76
77
80
84
m
80
m
81
74
85
76
78
81
68
m
74
78
81

Teachers

Other
staff

Total

(4)

(5)

(6)

(7)

24
26
11
18 d
43
11
m
39
m
28
38
20
18
m
24
26
m
19
24
17
24
23
20
16
m
20
m
19
26
15
24
22
19
32
m
26
22
19

32
61
45
35
23
m
m
m
m
25
34
42
x(7)
66
x(7)
44
m
x(7)
34
x(7)
37
x(7)
34
15
m
x(7)
m
x(7)
x(7)
x(7)
m
x(7)
53
x(7)
m
x(7)
32
30

29
6
30
29
25
m
m
m
m
37
29
37
x(7)
23
x(7)
29
m
x(7)
21
x(7)
24
x(7)
37
52
m
x(7)
m
x(7)
x(7)
x(7)
m
x(7)
21
x(7)
m
x(7)
27
35

Teachers

Other
staff

Total

Other current
expenditure

Other
staff

Prima ry to ter tiary
Staff compensation

Other current
expenditure

Countries
Australia
Austria
Belgium
Canada 1
Chile
Colombia 2
Costa Rica 2
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungar y
Iceland 3
Ireland
Israel
Italy
Japan
Korea
Latvia
Lithuania
Luxembourg
Mexico
Netherlands
New Zealand
Nor way
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
Unite d Kingdom
United States

Teachers

Tertiar y
Staff compensation

Other current
expenditure

OECD

Staff compensation

(8)

(9)

(10)

(11)

(12)

60
66
75
64
48
m
m
m
m
62
63
80
67
89
62
73
m
69
55
58 d
61
65
72
67
m
73
m
68
75
72
m
71
74
65
m
68
59
65

40
34
25
36
52
m
m
m
m
38
37
20
33
11
38
27
m
31
45
42 d
39
35
28
33
m
27
m
32
25
28
m
29
26
35
m
32
41
35

50
64
63
54 d
30
m
m
m
m
39
45
54
x(11)
m
x(11)
51
m
x(11)
54
x(11)
51
x(11)
50
69
m
x(11)
m
x(11)
x(11)
x(11)
m
x(11)
66
x(11)
m
x(11)
57
44

21
7
22
20 d
23
m
m
m
m
29
17
26
x(11)
m
x(11)
22
m
x(11)
17
x(11)
20
x(11)
28
12
m
x(11)
m
x(11)
x(11)
x(11)
m
x(11)
13
x(11)
m
x(11)
15
30

71
72
86
74 d
53
m
m
m
m
69
63
80
78
m
73
73
m
78
72
75
71
74
78
81
m
78
m
78
75
82
m
76
79
67
m
72
72
74

29
28
14
26 d
47
m
m
m
m
31
37
20
22
m
27
27
m
22
28
25
29
26
22
19
m
22
m
22
25
18
m
24
21
33
m
28
28
26

OECD average

m

m

77

23

m

m

67

33

m

m

74

26

EU23 average

61

15

77

23

m

m

69

31

m

m

75

25

Argentina
Brazil
China
Ind ia
Indonesia 2
Russian Federation
Saudi Arabia
South Africa

m
m
m
m
m
x(3)
m
m

m
m
m
m
m
x(3)
m
m

m
m
m
m
m
81
m
m

m
m
m
m
m
19
m
m

m
m
m
m
m
x(7)
m
m

m
m
m
m
m
x(7)
m
m

m
m
m
m
m
70
m
m

m
m
m
m
m
30
m
m

m
m
m
m
m
x(11)
m
m

m
m
m
m
m
x(11)
m
m

m
m
m
m
m
77
m
m

m
m
m
m
m
23
m
m

G20 average

m

m

m

m

m

m

m

m

m

m

m

m

Note: Some levels of education are included with others. Refer to "x" in Table C6.1 for details. Data on expenditure on staff compensation per student for primary to tertiary
education (Columns 13 to 15) are available for consultation on line (see StatLink below). "Tertiary staff" and "Total staff" at tertiary level include personnel employed whose
primary assignment is instruction or research (column 14, available on line). 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, secondary and post-secondary non-tertiary education includes pre-primary programmes.
2. Year of reference 2018.
3. Total current expenditure includes capital expenditure in private institutions.
4. At Tertiary level of education, "Teaching Staff" and "Total Staff" include personnel employed whose primary assignment is instruction or research.
Source: OECD/UIS/Eurostat (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en ).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888934165073

EDUCATION AT A GLANCE 2020 © OECD 2020

348  C6. ON WHAT RESOURCES AND SERVICES IS EDUCATION FUNDING SPENT?
Table C6.3. Share of current expenditure, by resource category and type of institution (2017)
Distribution of current expenditure by educational institutions
Primary, secondary and post-secondary non-tertiary

Tertiary

Compensation of staff as a percentage
Compensation of staff as a percentage
of current expenditure
of current expenditure
Share of current
Share of current
expenditure in Compensation Compensation
Total
expenditure in Compensation Compensation
Total
total expenditure
of teachers
of other staff
compensation total expenditure
of teachers
of other staff
compensation

Par tners

OECD

Public Private Public Private Public Private Public Private Public Private Public Private Public Private Public Private
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
(9)
(10)
(11)
(12)
(13)
(14)
(15)
(16)
Countries
Australia
Austria
Belgium
Canada 1
Chile
Colombia 2
Costa Rica 2
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungar y
Iceland 3
Ireland
Israel
Italy
Japan
Korea
Latvia
Lithuania
Luxembourg
Mexico
Netherlands
New Zealand
Nor way
Poland
Por tugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
Unite d Kingdom
United States

93
95
95
92 d
94
97
99
91
m
92
89
92
94
98
95
95
93
89
99
89
84
88
95
91
98
89
m
85
94
97
96
93
97
96
m
90
97
91

85
99
97
94 d
93
88
m
100
m
95
95
93
89
m
96
100
m
95
98
88
92
87
96
97
m
98
m
100
73
85
100
100
96
95
m
89
95
91

61
66
68
68 d
37
85
70
43
m
46
51
60
x(7)
92
x(7)
53
58
x(7)
61
x(7)
58
x(7)
56
79
79
x(7)
m
x(7)
x(7)
81
59
x(7)
73
53
m
x(7)
67
54

OECD average

93

94

EU23 average

94

94

Argentina
Brazil
China
India
Indonesia 2
Russian Federation
Saudi Arabia
South Africa

87
98
m
m
m
93
m
m

G20 average

m

57
68
72
52 d
35
77
m
45
m
52
47
53
x(8)
m
x(8)
55
m
x(8)
47
x(8)
59
x(8)
55
71
m
x(8)
m
x(8)
x(8)
49
61
x(8)
64
54
m
x(8)
68
53

15
9
21
14 d
26
8
3
18
m
26
11
22
x(7)
2
x(7)
20
10
x(7)
17
x(7)
18
x(7)
24
5
12
x(7)
m
x(7)
x(7)
9
16
x(7)
9
14
m
x(7)
12
27

19
4
18
19 d
19
4
m
20
m
14
17
20
x(8)
m
x(8)
18
m
x(8)
0
x(8)
14
x(8)
19
14
m
x(8)
m
x(8)
x(8)
12
14
x(8)
11
12
m
x(8)
8
26

76
75
89
82 d
63
93
73
61
m
72
62
82
84
94
76
74
67
84
78
84
76
77
80
84
91
80
m
80
74
90
76
78
82
68
m
86
79
81

76
71
89
71 d
53
81
m
65
m
66
64
73
76
m
76
72
m
72
47
73
73
78
74
84
m
87
m
100
75
61
75
65
75
67
m
35
77
78

89
91
95
90
96
m
89
93
m
91
94
92
91
57
81
98
98
87
94
90 d
87
94
93
93
96
89
m
88
91
95
93
93
88
96
m
82
a
90

63

m

63

57

m
m
m
m
m
96
m
m

70
x(7)
m
m
m
x(7)
m
77

m

m

57
93
95
a
98
m
m
m
m
95
97
91
94
a
81
100
m
93
91
87 d
91
89
95
a
m
94
m
98
95
93
m
100
95
97
m
74
87
89

33
61
48
35
27
m
x(15)
46
m
25
31
40
x(15)
66
x(15)
44
34
x(15)
34
x(15)
29
x(15)
35
15
57
x(15)
m
x(15)
x(15)
x(15)
34
x(15)
57
x(15)
m
x(15)
a
32

23
58
43
a
22
m
m
m
m
29
43
52
x(16)
a
x(16)
44
m
x(16)
33
x(16)
40
x(16)
27
a
m
x(16)
m
x(16)
x(16)
x(16)
m
x(16)
35
x(16)
m
x(16)
32
28

15

m

79

72

90

91

m

m

14

13

78

72

91

93

m

m

m
m
m
m
m
x(8)
m
m

23
x(7)
m
m
m
x(7)
m
7

m
m
m
m
m
x(8)
m
m

93
78
m
m
m
81
m
83

m
m
m
m
m
61
m
m

95
97
m
m
m
90
m
m

m
m
m
m
m
96
m
m

60
x(15)
m
m
m
x(15)
m
56

m
m
m
m
m
x(16)
m
m

m

m

m

m

m

m

m

m

m

27
6
29
29
32
m
x(15)
18
m
37
30
40
x(15)
23
x(15)
29
1
x(15)
21
x(15)
26
x(15)
37
52
15
x(15)
m
x(15)
x(15)
x(15)
24
x(15)
21
x(15)
m
x(15)
a
36

40
3
31
a
22
m
m
m
m
30
26
22
x(16)
a
x(16)
29
m
x(16)
19
x(16)
23
x(16)
39
a
m
x(16)
m
x(16)
x(16)
x(16)
m
x(16)
21
x(16)
m
x(16)
27
33

60
67
77
64
59
m
75
64
m
62
61
81
67
89
62
73
35
46
55
52 d
55
80
72
67
72
72
m
68
76
75
58
73
78
66
m
69
a
68

63
62
74
a
45
m
m
m
m
59
69
74
61
a
62
73
m
70
53
62 d
63
63
66
a
m
79
m
64
69
56
m
40
56
64
m
61
59
61

m

m

67

63

m

m

68

63

30
x(15)
m
m
m
x(15)
m
0

m
m
m
m
m
x(16)
m
m

90
71
m
m
m
70
m
56

m
m
m
m
m
63
m
m

m

m

m

m

Note: Some levels of education are included with others. Refer to "x" in Table C6.1 for details. Data on expenditure on compensation of teachers per student for primary to
tertiary education (Columns 17 to 20) are available for consultation on line (see StatLink below). "Tertiary staff" at tertiary level include personnel employed whose primary
assignment is instruction or research (columns 19 and 20, available on line). 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, secondary and post-secondary non-tertiary education includes pre-primary programmes. Post-secondary non-tertiary figures are treated as negligible.
2. Year of reference 2018.
3. Total current expenditure includes capital expenditure in private institutions.
Source: OECD/UIS/Eurostat (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en ).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888934165092

EDUCATION AT A GLANCE 2020 © OECD 2020

| 349

Chapter D. Teachers, the
learning environment and
the organisation of schools

EDUCATION AT A GLANCE 2020 © OECD 2020

350  D1. HOW DOES TIME SPENT BY STUDENTS IN THE CLASSROOM VARY OVER THE YEARS?

Indicator D1. How does time spent by
students in the classroom vary over the
years?
Highlights


In most OECD and partner countries, the number of hours of instruction in compulsory primary and lower
secondary education does not change much from year to year. However, between 2014 and 2019 the instruction
time regulations have changed at least once in a majority of the countries with available data.



The total number of compulsory instruction hours in primary and general lower secondary education changed in
three-quarters of the countries with available data between 2014 and 2019. The changes exceeded 5% in
Australia, Denmark, Hungary, Lithuania, Portugal and Spain.



Changes in instruction time regulations could influence one or more aspects of students’ compulsory instruction
time: the number of grades in different levels of compulsory education, the length of school year and the
distribution of compulsory instruction time by subject and/or by grade.

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. These priorities and preferences may change over time to adapt to the changes in the society or
education policy. Changes may also be implemented further to specific crisis, such as the pandemic due to COVID-19
(Box D1.2). 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 Box D2.3 in Indicator D2 on 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


On average across OECD countries in 2019, the compulsory primary and lower secondary curriculum is defined
over six grades at primary level and three grades at lower secondary level. Between 2014 and 2019, the number
of grades changed only in Australia at primary level and in Spain at general lower secondary level.



Between 2014 and 2019, most of the countries with available information changed the distribution of compulsory
instruction time devoted to individual subjects in primary and general lower secondary education. However, only
about one-third of them had significant changes (of 5 percentage points or more) in the share of instruction time
devoted to some subjects: Australia, Canada (primary), Denmark, Greece (lower secondary), Hungary, Ireland,

EDUCATION AT A GLANCE 2020 © OECD 2020

D1. HOW DOES TIME SPENT BY STUDENTS IN THE CLASSROOM VARY OVER THE YEARS?  351

Poland, Portugal, the Slovak Republic and Spain. In many of these countries, the share of compulsory instruction
time devoted to the flexible curriculum changed by more than 5 percentage points between 2014 and 2019.

Figure D1.1. Compulsory instruction time in general education (2014 and 2019)
Primary and lower secondary education, in public institutions
Number of
compulsory
instruction hours
8 000

Primary (2019)
Primary (2014)

Lower secondary (2019)
Lower secondary (2014)

Difference in hours of compulsory primary and general lower secondary instruction (2019 2014)
8 000

6 000

6 000

4 000

4 000

2 000

2 000

0

0

2 000

-2 000

4 000

-4 000

6 000

-6 000

Note: Light-coloured circles indicate no change in instruction time (primary and general lower secondary education) between the two reference years. Values next to
country names refer to the duration (in years) of primary and lower secondary education in 2019.
1. Reference year differs from indicated year. Refer to the sources table for details.
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. 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 descending order of the difference between the total number of compulsory instruction hours in 2019 and in 2014.
Source: OECD (2020), Tables D1.1 and D1.2. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2https://doi.org/10.1787/888934165244

EDUCATION AT A GLANCE 2020 © OECD 2020

352  D1. HOW DOES TIME SPENT BY STUDENTS IN THE CLASSROOM VARY OVER THE YEARS?

Analysis
Changes in number of grades in compulsory primary and lower secondary 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 face a heavier
annual workload based on statutory requirements. In other countries, the workload is distributed evenly over more years. This
indicator focuses on changes in 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 below the
age at which primary education starts (see Annex 3 for more details on the length of compulsory education). Moreover, in
around three-fifths of countries and economies with available data, compulsory full-time education includes at least one year
of upper secondary education (see Figure X3.D1.1 in Annex 3 for more details).
On average across OECD countries the compulsory curriculum in primary and lower secondary education was defined over
six grades at primary level and three grades at lower secondary level in 2019 (Table D1.1 and Table D1.2). Even though
there may be differences among countries, the number of grades in primary and lower secondary levels does not change
much from year to year. Between 2014 and 2019, only a few countries with available information changed the total number
of years of compulsory primary and lower secondary education. Only Australia and Spain changed the total number of grades
in compulsory primary or lower secondary general education (Tables D1.5 and D1.6, available on line).
In Australia, the number of grades in primary education changed from six grades in 2014 and 2015 to seven grades from
2016, which contributed to an increase in total instruction time in primary education of more than 15% between 2014 and
2019 (Table D1.1). However, the number of grades in primary and lower secondary education that are part of the 10 years of
compulsory education varies across jurisdictions in the country (6-7 years for primary and 3-4 years for lower secondary) and
the figures reported for 2014 and 2015 referred to the minimum number of years of primary education, whereas they referred
to typical values for other reference years. In Spain, the total length of compulsory lower secondary instruction time fell by
26% between 2014 and 2019 (Table D1.2). Most of this reduction resulted from the fact that Spain had four lower secondary
grades until 2015 (Grades 7 to 10) and only three from 2016 when the final grade was moved to upper secondary level,
although it remains compulsory.
Poland has also decided to change the distribution of grades across compulsory education. A major reform of the country’s
national education system was begun since 2016/17 and is still ongoing as it is implemented in a process covering several
years. This transition will entail a major change in the number of grades in each ISCED level.

Changes in compulsory instruction time
In most countries, official documents define compulsory and non-compulsory instruction time either by level of education or
by grade in each level of education. Neither the curriculum nor the number of instruction hours is expected to change each
year in any given country. As a consequence, only few countries show changes in compulsory instruction hours between two
reference years. However, the pattern changes when a longer period is considered, as more countries are likely to have
changed their regulations at least once over this time.
Between 2014 and 2019, the total number of instruction hours in compulsory primary and general lower secondary education
has changed in three-quarters of the countries with available data (28 out of 38 countries and economies). Six of these
countries showed significant changes in instruction time (more than 5%) during this period: Australia, Denmark, Hungary,
Lithuania, Portugal and Spain (Figure D1.1).
In Australia and Spain, the significant changes in the total number of instruction hours in compulsory primary and general
lower secondary education resulted mainly from the changes to their grade structures discussed above. However, the number
of hours of compulsory instruction time per year also changed slightly (by less than 5%) between the years when the number
of grades changed.
In the other four countries, new regulations implemented between 2014 and 2019 resulted in a significant increase (10-36%)
in total number of compulsory instruction hours in primary and general lower secondary education.
The increase in compulsory instruction time resulted from an increase in the number of instruction days in a school year in
Lithuania (by 15 days at primary level and 17 days at lower secondary level between 2016 and 2019) and in Portugal (by
5 days in Grade 6 at primary level only between 2014 and 2019). Since the compulsory instruction time is defined weekly in

EDUCATION AT A GLANCE 2020 © OECD 2020

D1. HOW DOES TIME SPENT BY STUDENTS IN THE CLASSROOM VARY OVER THE YEARS?  353
these two countries, increasing the number of instruction days directly translated into an increase of the total annual instruction
time (Tables D1.5 and D1.6, available on line).
An increase in compulsory instruction time can also result from increasing the number of hours of compulsory instruction,
without any change in the number of instruction days per school year. This implies longer instruction days on average. In
Denmark, a reform of its Folkeskolen (integrated primary and general lower secondary school) implemented for 2014/15 and
2015/16 extended the average length of a school day. Although instruction time increased by 36% between 2014 and 2019
in total across these levels, the typical number of instruction days remained at 200 days per year. In Hungary, during the fouryear phased transition to the new Framework Curricula, compulsory instruction time increased by about 13% in both primary
and lower secondary education although the number of instruction days remained at about 180 days per year (Table D1.1,
Table D1.2, and Tables D1.5 and D1.6, available on line).

Box D1.1. Comparability of data on instruction time across countries and over time
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. Moreover, changes and revisions in the data collection on instruction time
over years may hinder comparability issues on instruction time trend data.

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 the number of hours of
instruction. In some countries, the data can be 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.
Intended instruction time is usually similar across schools throughout the whole country. However, in some countries it is
a weighted average based on various regulations. This is the case when intended instruction time varies 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). In these countries small variations in instruction time over time may result from changes
in the weights used to compute the average for the whole country, rather than from changes in the minimum or
recommended instruction in the subnational entities.

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 the 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 where the length
of the school day does not change over the week or year.

Number of hours of instruction
Instruction time is given 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 half of 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

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354  D1. HOW DOES TIME SPENT BY STUDENTS IN THE CLASSROOM VARY OVER THE YEARS?
time per week or day rather than per school year, so the weekly or daily values are multiplied by the defined or estimated
number of weeks or days 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 at the national level,
although they are excluded from reported intended instruction time to comply with the international definition. For example
in Denmark, breaks have been a part of regulated compulsory instruction time in both primary and lower secondary
education since 2014/15, although they are not included in the reported data. Similarly, in Spain, primary education
legislations in autonomous communities includes breaks in compulsory instruction time (87.5 hours per year), which has
been excluded from the reported data since 2014.

Distribution of instruction time by subject
Instruction time is devoted to various subjects and the distribution of instruction time by subject is displayed by level of
education for the different countries. To improve comparability across countries, definitions of some subjects have been
clarified over time. For example, “reading, writing and literature” has been further clarified to only include reading, writing
and literature in another national language when it is also a language of instruction in almost every public school. The
definition “foreign languages” was revised to “second and other languages” to include time spent on other national
languages. These clarifications resulted in changes in the proportion of instruction time devoted to these subjects in Ireland
and Luxembourg, although the statutory regulations on the number of hours devoted to these subjects did not change.
Several countries also revised subject categories over time to better reflect the curriculum contents of these subjects. In
lower secondary general education in Finland, home economics, once classified under “other subjects”, is now classified
as “practical and vocational skills”. In Greece, geography (at primary level) and geology-geography (at lower secondary
level) have been moved from “social studies” to “natural sciences”. In primary education in Japan, instruction time spent
on living environment studies, which was previously included in both “social studies” and “natural sciences”, is now
included in “other subjects”.
For more information on comparability issues, see notes for specific countries and/or specific years in Annex 3 in the
relevant editions of Education at a Glance.

Changes in 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. Most of the OECD countries and economies only have compulsory
instruction subjects and so did not have non-compulsory subjects over the period 2014-19. In these countries, all the changes
in total intended instruction time between 2014 and 2019 can be explained by the change in compulsory instruction time
between these years.
However, one-fifth of the OECD countries and economies include non-compulsory subjects in their intended instruction time,
which is another factor that could explain the change in total intended instruction time between 2014 and 2019. Among these
countries, instruction time devoted to non-compulsory subjects increased by 10% or more in five countries between 2014 and
2019: Canada (lower secondary but non-compulsory instruction time amounts to less than 10 hours per year), Finland, France
(lower secondary), Greece (primary) and Slovenia. Non-compulsory curriculum hours have been increased for various
purposes, from remedial/supplementary classes (Greece) to optional subjects such as second and other languages (Finland,
France and Slovenia), or for classes working on projects (lower secondary education in Greece). Only Portugal recorded a
large decrease in non-compulsory instruction time of 32% (359 hours) in primary education (Table D1.1 and Table D1.2).

Changes in the distribution of instruction time by subject
Changes in the compulsory instruction time devoted to some subjects may affect the total number of hours of instruction, but
also the distribution of instruction time by subject. Countries can also make changes in the distribution of instruction time by
subject without changing the number of hours of compulsory instruction time.
The distribution of compulsory instruction time by subject may change over time due to the combination of multiple instruction
time regulations (see Box D1.1). This combination of different regulations may result from the existence of different levels of
governance responsible for education as in federal countries like Canada, Germany and Spain. Different regulations may also
apply to different types of schools. This is the case in Austria (at lower secondary level), Chile, Greece (in primary education

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D1. HOW DOES TIME SPENT BY STUDENTS IN THE CLASSROOM VARY OVER THE YEARS?  355
before 2017), Israel, Latvia and Turkey (lower secondary). Similar issues can also arise in countries undergoing transition
between two sets of regulations, as in Poland (for more information, see Annex 3).
Other than the instruction time on specific subjects set at central level, instruction time can be allocated in ways that allow
local authorities, schools, teachers and/or students to have freedom in organising instruction time or in choosing subjects.
Changes in the proportion of compulsory flexible curriculum (compulsory instruction time set for subjects within a flexible
timetable, or subjects chosen by schools and/or students) signal how much freedom schools or students are allowed in
organising instruction time or choosing subjects. Between 2014 and 2019, this change was notable (exceeding 5 percentage
points) in Australia, Denmark (lower secondary), Hungary, Ireland (lower secondary), Poland, Portugal, the Slovak Republic
and Spain (lower secondary) (Table D1.3 and Table D1.4).

Primary education
At primary level, most of the 31 countries with available information made changes to the distribution of compulsory instruction
time devoted to different subjects between 2014 and 2019 (Table D1.3). However, only in nine countries did the changes in
the proportion of instruction time devoted to any specific subject exceed 5 percentage points (Figure D1.2).
In four of these countries (Australia, Denmark, Hungary and Portugal), the number of hours of instruction devoted to some
compulsory subjects increased (together with an increase of total compulsory instruction time) with some impact on the
distribution of compulsory instruction time by subject. In these countries, the changes led to an increase in total compulsory
instruction time of 12-39% (Table D1.3).
The number of compulsory instruction hours in primary education increased the most in Denmark (by 39% or 2 080 hours) as
a result of an additional 510 hours of instruction devoted to a number of compulsory subjects (reading, writing and literature;
mathematics; natural sciences; second and other languages etc.) and 1 570 hours to various compulsory learning activities
(included in the “other subjects” category). This led to a large change in the distribution of instruction time by subject, with a
reduction of 13 percentage points in the proportion of time devoted to reading, writing and literature; mathematics; natural
sciences; and the compulsory flexible curriculum, counterbalanced by an increase in the proportion of compulsory instruction
time devoted to other compulsory curriculum subjects (Table D1.1, Table D1.3 and Figure D1.2).
In Australia and Portugal, there were also large changes in the distribution of instruction time among subjects in parallel to
the significant increase of instruction time between 2014 and 2019 (Table D1.3). However, while the proportion of instruction
time devoted to the compulsory flexible curriculum increased by more than 50 percentage points in Portugal, it decreased by
more than 70 percentage points in Australia. In Australia, the change resulted from the introduction of a national curriculum
that provides guidelines on the time to be spent on specific compulsory subjects. Previously individual schools had full
autonomy over how to organise the instruction time for a set of compulsory subjects. In Portugal, a decree-law in 2018
provided more autonomy to individual schools: compulsory instruction time is no longer allocated to specific subjects (except
reading, writing and literature; mathematics; and physical education and health in some grades), and the majority of
compulsory instruction time is allocated to flexible arrangements such as subjects with flexible timetables and compulsory
subjects chosen by schools.
In Hungary, the implementation of the new Framework Curricula increased the proportion of compulsory instruction time
devoted to physical education and health, arts, and compulsory flexible subjects chosen by schools. As a result, the proportion
of compulsory instruction time devoted to the flexible curriculum and to other subjects increased by more than 5 percentage
points, balanced by a decrease in other subjects, mostly in reading, writing and literature (Table D1.3).
In three countries (Ireland, Poland and the Slovak Republic), there were changes in the proportion of instruction time devoted to
a specific subject which exceeded 5 percentage points and total compulsory instruction time decreased slightly (by 1-5%). In
both Poland and the Slovak Republic, the main changes in the distribution of compulsory instruction time by subject relate to the
reduction in time devoted to the flexible curriculum (by 9-13 percentage points). This was balanced by increases in all other
subjects except natural sciences in Poland and all other subjects except second and other languages in the Slovak Republic.
Unlike in Hungary and Portugal, schools in Poland and the Slovak Republic have seen a reduced degree of autonomy in
choosing subjects. However, for Poland, comparing the distribution of instruction time between these two reference years should
be done with caution, due to the gradual implementation of its ongoing reform, as discussed above. The instruction time allocated
to compulsory flexible subjects chosen by schools fell by nearly 9 percentage points as of 2019, with minor changes (less than
2 percentage points) in various compulsory subjects. In addition, the reform accounted for about a 5% decrease in the number
of hours of compulsory instruction in primary education (Table D1.1 and Table D1.3).

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356  D1. HOW DOES TIME SPENT BY STUDENTS IN THE CLASSROOM VARY OVER THE YEARS?

Figure D1.2. Instruction time per subject in primary education in 2019 and change in the distribution by
subject between 2014 and 2019
As a percentage of total compulsory instruction time, in public institutions
Instruction time per subject in 2019
Difference in compulsory instruction time in percentage points (2019 2014)
Compulsory flex ible curriculum
Natural sciences
Other compulsory curriculum
Mathematics
Second and other languages
Reading, writing and literature
%
100

Instruction time per subject in 2019

90
80
70
60
50
40
30
20
10

England (UK)

Poland3

Chile

Greece

Slovak Republic

Ireland 2

Turkey

French Comm. (Belgium)

52

Flemish Comm. (Belgium)

Mexico

Netherlands

Italy

Luxembourg 2

France

Iceland

Austria

Estonia

Canada

Israel

Spain

Norway

EU23 average1

Korea

Japan

Latvia

Czech Republic

Slovenia

Germany

Finland

Hungary

Portugal

OECD average1

Percentage
points
50

Australia

Denmark

0

40
30
20
10
0
-10
-20
-30
-40
-50

-71 -52

Change in the distribution by subject between 2014 and 2019

Note: No marker for a country indicates that there are no data on the total number of compulsory instruction hours for one of the two corresponding reference years.
1. Excludes Australia, England (United Kingdom), the Flemish Community of Belgium, the French Community of Belgium, Italy, the Netherlands and Portugal.
2. The second language of instruction includes other national languages taught in 2019.
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 percentage-point change in total compulsory instruction hours since 2014.
Source: OECD (2020), Tables D1.1 and D1.3. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2https://doi.org/10.1787/888934165263

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D1. HOW DOES TIME SPENT BY STUDENTS IN THE CLASSROOM VARY OVER THE YEARS?  357

In the two remaining countries, Canada and Spain, the total number of hours of compulsory instruction time stayed generally
constant between 2014 and 2019, but the distribution of instruction time by subject changed significantly, especially in some
compulsory subjects. In these two federal countries, the changes arise from varying proportions of subnational-level
regulations on instruction time being taken into account, as discussed above (Table D1.1 and Table D1.3).
Other than these large changes between 2014 and 2019, there were also small changes in the number of instruction hours
devoted to new or existing subjects (in the Czech Republic, Finland, France, Japan, Latvia, Norway, Portugal and Slovenia)
and changes in the distribution of instruction time by subjects resulting from changes in the combination of multiple instruction
time regulations over time (in Chile, Germany, Greece, Israel, and Latvia) (Table D1.3). Changes were also implemented in
how some subjects are classified in the subject categories in Greece, Ireland, Japan and Luxembourg (see Box D1.1).

General lower secondary education
In lower secondary general education, changes to the distribution of compulsory instruction time by subject occurred in the
majority of the 31 countries with available information (Table D1.4). However, the proportion of instruction time devoted to a
specific subject category changed by more than or equal to 5 percentage points in 9 of these 31 countries (Figure D1.3).
In Denmark, Hungary, Poland and Portugal, new regulations on instruction time implemented in lower secondary education
increased the total number of instruction hours (by 2-29%) as a result of significant changes in the number of instruction hours
devoted to many subjects. The distribution of instruction time by subject changed significantly in these four countries. The
variation in the proportion of instruction time devoted to a specific subject only reached or exceeded 5 percentage points for
a few subjects, but in all four countries there was a significant change in the time devoted to compulsory flexible curriculum.
In Denmark and Poland, the share of the compulsory curriculum devoted to the compulsory flexible curriculum fell by 911 percentage points, whereas the proportion increased by 7 percentage points in Hungary and 58 percentage points in
Portugal. As a result, Portugal has the fourth largest proportion of instruction time devoted to compulsory flexible curriculum
among OECD countries and economies in 2019, while the proportion does not exceed 10% in the three other countries
(Table D1.2 and Table D1.4).
Spain is the only country combining a significant decrease in the total number of hours of compulsory instruction (by more
than 2%) and significant changes (by over 5 percentage points) in the distribution of instruction time devoted to specific
subjects. The distribution of instruction time by subject in Spain has mainly changed following the move of one grade from
lower secondary level to upper secondary level (as indicated by the 26% reduction in total compulsory instruction time at
lower secondary level). As this grade had a very different distribution of instruction time by subject compared to the other
grades that are still part of the lower secondary level, moving it into upper secondary level had a significant impact on the
distribution of instruction time by subject. Changes in regulations regarding compulsory curriculum chosen by students and
compulsory flexible curriculum chosen by schools have also had an impact (Table D1.2 and Table D1.4).
In Australia, Greece, Ireland, and the Slovak Republic, the total number of hours of compulsory instruction did not change by
more than 2% between 2014 and 2019, but the distribution of compulsory instruction time by subject changed significantly,
and by at least 5 percentage points in a few subjects. The changes in the distribution are especially large in Australia and
Ireland. In Ireland, subject selection and the competence to decide instruction time has been significantly delegated to
individual schools at lower secondary level since the school year 2014/15 (from 12% of compulsory instruction time in 2014
to 60% in 2019). Thus, similar to Portugal, the level of autonomy of individual schools on the organisation of instruction time
and on the choices of subject increased between 2014 and 2019, leading to an increase of 48 percentage points in the share
of the compulsory curriculum devoted to compulsory flexible subjects. The changes in the distribution of instruction time by
subject were in the opposite direction in Australia. As for primary education, the share devoted to compulsory flexible
curriculum decreased by more than 60 percentage points. However, in 2019 Australia and Ireland remain among the few
countries devoting at least 40% of the compulsory curriculum to compulsory flexible curriculum at the lower secondary level
(Table D1.4).
In Greece and the Slovak Republic, the changes in the share of compulsory curriculum devoted to specific subjects changed
to a lesser extent. The largest changes (by 5 percentage points or more) occurred in one or two categories: compulsory
flexible curriculum and other compulsory curriculum for the Slovak Republic, and other compulsory curriculum for Greece
(Figure D1.3). In Greece, a reform rearranged compulsory instruction time for numerous compulsory subjects in order to
reduce students’ weekly study load by 9% since 2016/17 (Table D1.4). However, this change did not reduce total compulsory

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358  D1. HOW DOES TIME SPENT BY STUDENTS IN THE CLASSROOM VARY OVER THE YEARS?
instruction as this reduction was offset by 9% increase (13 days) in the number of instruction days in the school year at lower
secondary level (Table D1.6, available on line).

Figure D1.3. Instruction time per subject in general lower secondary education in 2019 and change in the
distribution by subject between 2014 and 2019
As a percentage of total compulsory instruction time, in public institutions
Difference in compulsory instruction time in percentage points (2019 2014)
Compulsory flex ible curriculum
Natural sciences
Other compulsory curriculum
Mathematics
Second and other languages
Reading, writing and literature
%
100

Instruction time per subject in 2019

90
80
70
60
50
40
30
20
10

Spain

England (UK)

France

Finland

Israel

French Comm. (Belgium)

Australia
61

Slovak Republic

Ireland 4

Chile

Japan

Slovenia

Germany

Mexico

Netherlands

Latvia

Luxembourg 4

Korea 3

Italy2

Iceland

Austria

Estonia

Turkey

Canada

Greece

Norway

Czech Republic

Flemish Comm. (Belgium)

OECD average1

Poland

Portugal
58

EU23 average1

Percentage
points
50

Hungary

Denmark

0

40
30
20
10
0
-10
-20
-30
-40
-50

-58

Change in the distribution by subject between 2014 and 2019

-61

Note: No marker for a country indicates that there are no data on the total number of compulsory instruction hours for one of the two corresponding reference years.
1. Excludes Australia (in 2014 only), England (United Kingdom), the Flemish Community of Belgium, Ireland (in 2019 only), the Netherlands and Portugal (in 2019 only).
2. Reading, writing and literature includes social studies. Mathematics includes natural sciences.
3. Natural sciences includes information and communication technologies and practical and vocational skills.
4. The second language of instruction includes other national languages taught in 2019.
Countries and economies are ranked in descending order of the percentage-point change in total compulsory instruction hours since 2014.
Source: OECD (2020), Tables D1.2 and D1.4. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2 https://doi.org/10.1787/888934165282

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D1. HOW DOES TIME SPENT BY STUDENTS IN THE CLASSROOM VARY OVER THE YEARS?  359
In addition to the significant changes above, four countries had small changes in the categories other compulsory curriculum
and compulsory flexible curriculum: France, the French Community of Belgium, Korea and Mexico (Figure D1.3 and
Table D1.4). Combinations of multiple instruction time regulations resulted in small changes over time in the distribution of
instruction time in Austria, Canada, Chile, Germany, Israel, Latvia, Spain and Turkey (Table D1.4). In Greece, Ireland and
Luxembourg, there were changes in how some subjects are classified into subject categories (see Box D1.1).

Changes in flexible allocation of instruction time across multiple grades
In one-quarter of countries with available data in 2019, the allocation of instruction time across grades is flexible, i.e. the
instruction time for a specific subject is defined across a certain number of grades or even the whole of compulsory education,
without specifying the time to be allocated within each grade. Between 2014 and 2019, only four countries have made changes
in the flexibility of the allocation of subjects over multiple grades (Luxembourg (primary only), Poland, Portugal and the Slovak
Republic). For example, in the Slovak Republic, since 2015/16, instruction time on compulsory subjects is no longer allocated
across multiple grades in primary and lower secondary general education (Tables D1.5 and D1.6, available on line).
In Finland and Sweden, although instruction time for most subjects continues to be flexibly allocated in primary and lower
secondary education, new regulations changed the grouping of grades in which instruction time of a specific subject can be
flexibly arranged at the discretion of individual schools. For example, in Sweden, instruction time for most subjects was once
allowed to be flexibly allocated across all grades in primary and lower secondary education, but now is allocated within two
3-year stages in primary education and one 3-year stage in lower secondary education (Table D1.1 and Table D1.2).
In these countries, it is not possible to estimate the impact of these changes on the flexibility of the curriculum on the number
of annual hours of compulsory education, because individual schools/local authorities decide how to allocate instruction hours
across multiple grades.

Box D1.2. Impact of COVID19 on instruction time
Out of the 38 OECD countries and 8 partner countries covered in this edition of Education at a Glance,
the People’s Republic of China was the first to impose a school closure in response to the COVID19 pandemic. School
closures were imposed on 16 February 2020 in some parts of China, where the scheduled spring semester starts earlier,
and extended nationwide about a week later. Other countries also began to close schools (closure of school premises,
without necessarily a complete cessation of teaching/learning) as the pandemic expanded. Preliminary information from
various sources (see below) provides a snapshot of responses during this ongoing and evolving global pandemic.
By the end of March, school closures had been implemented to some extent in all 46 countries covered here, but to a
different extent: countrywide in 41 countries and at a subnational or local level in 5 (Australia, Iceland,
the Russian Federation, Sweden and the United States). However, not all countries hit by the pandemic closed all of their
schools. For example, primary schools in Iceland remained open if class sizes were below 20 students. In Sweden, most
primary and lower secondary schools remained open, while upper secondary schools switched to mainly distance learning
from mid-March (UNESCO, 2020[1]).

Impact on the number of instruction weeks at school
It is difficult to estimate accurately the number of instruction weeks affected in all countries as in some countries individual
schools or local authorities have autonomy over the organisation of the school year schedule and the re-opening of schools.
However, by the end of June 2020, out of these 46 countries, some degree of school closure was effective for at least
7 weeks in 2 countries (4%), 8-12 weeks in 6 countries (13%), 12-16 weeks in 24 countries (52%), 16-19 weeks in
13 countries (28%) and more than 19 weeks in China (UNESCO, 2020[1]).
However, the actual impact may have been less severe as some of these periods included scheduled school breaks. In
many European and Southern Hemisphere countries, Easter holidays scheduled in mid-April and/or spring vacation
between April and early May mitigated the impact of school closure by up to 2 weeks. In Japan for example, there is a twoweek spring vacation in late March (see Figure X3.D1.2 in Annex 3 for more information) (UNESCO, 2020[1]; European
Commission/EACEA/Eurydice, 2019[2]).

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360  D1. HOW DOES TIME SPENT BY STUDENTS IN THE CLASSROOM VARY OVER THE YEARS?
Moreover, some countries have reorganised their school years to minimise the impact on the number of instruction weeks.
For example, in Australia (in some jurisdictions) and Chile the winter school holidays were brought forward; in Korea the
school year started in April (about one month later than the typical start) by shortening the summer vacation, and in
Lithuania two-week compulsory school holidays were introduced in the last two weeks of March (OECD, 2020[3]).

Figure D1.4. Number of countries with school closures due to COVID19
Data covers the period between 17 February 2020 and 30 June 2020
Nationwide (OECD country)
Localised (OECD country)

Number
of countries
40

Nationwide (Partner country)
Localised (Partner country)

35
30
25
20
15
10
5
0
5

29 June

22 June

15 June

08 June

01 June

25 May

18 May

11 May

04 May

27 April

20 April

13 April

06 April

30 March

23 March

16 March

09 March

02 March

24 February

17 February

10

Note: This figure covers educational institutions from early childhood education to tertiary education. Localised school closure refers to school closures of some levels
of education only and/or for some subnational entities.
Source: UNESCO (2020[1]).
Statlink2 https://doi.org/10.1787/888934165301

Measures to continue students’ learning during school closure
Countries used different instructional resources to support students’ learning while they were unable to come to school,
including instructional packages (textbooks, worksheets and printouts), radio education, educational television and online
instructional resources. Countries usually used several tools, to reach the largest proportion of students possible. In the
OECD and partner countries, online platforms were the most popular tool used during school closures (Schleicher and
Reimers, 2020[4]).
Online platforms were used in nearly all the OECD and partner countries, through various online learning tools, ranging
from educational content which students can explore at their own discretion and formalised learning programmes
conducted at their own pace, to real-time lessons led by their teachers through virtual meeting platforms. For example,
Estonia has collaborated with private services to provide a wealth of educational content free to students during school
closure. In France, already-existing distance learning programme Ma classes à la maison (My classes at home) became
available for all students in primary and secondary schools (Ministère de l'Éducation nationale et de la Jeunesse, 2020 [5]).

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D1. HOW DOES TIME SPENT BY STUDENTS IN THE CLASSROOM VARY OVER THE YEARS?  361
In Greece, virtual real-time classes with teachers were conducted in conjunction with other online learning tools (Ministry
of Education and Religious Affairs, 2020[6]; Schleicher and Reimers, 2020[4]).
Another popular learning arrangements in many OECD countries were television broadcasts providing educational content
to continue students’ learning. In some countries, TV programmes mostly catered for younger children in primary schools
(for example, in Greece, Korea and Portugal), who may have difficulty using online learning platforms or conducting selfdirected learning. TV broadcasts are also another way to reach students who do not have adequate resources for online
instruction. Despite their advantages, broadcasts can be limited to covering only a few subjects due to short time
designated for these TV programmes. For example, two channels in Spain covered one of the five subjects (Spanish,
mathematics, social science, natural sciences and arts and/or physical education) per day during a one-hour slot (Ministry
of Education and Vocational Training, 2020 [7]; Schleicher and Reimers, 2020[4]).
Other measures were also taken to help students in their learning at home. For example in Luxembourg, the government
set up a new support system for students and parents to support home schooling. In Mexico, a telephone line “Your Teacher
Online” has been activated to offer mentoring to students (OECD, 2020[3]).
In the majority of the OECD and partner countries, these measures were conducted by the government with active
involvement from individual schools. However, in Estonia, Finland, Japan and the Netherlands, individual schools had more
autonomy in organising these alternative education arrangements (Schleicher and Reimers, 2020[4]).

Re-opening of schools
After mid-April, some OECD countries gradually started to re-open schools for some levels of education. By the end of
May, more than two months after the school closures began in most OECD countries, schools were re-opened (at least
partially) in two-thirds of the OECD countries (UNESCO, 2020[1]; Schleicher and Reimers, 2020[4]).
In most countries, where schools have re-opened, attendance is not compulsory for all students, to take into account
students who are sick or have at-risk family members, or because schools could not welcome all students with the new
sanitary measures to maintain sufficient distance between students and teachers in classrooms (see Box D2.2). For
example, in the Czech Republic, lower secondary schools re-opened for students in Grade 9, organised in small groups of
up to 15 people with voluntary attendance. Neither students nor their teachers have to wear face masks if a two-metre
social distance is kept (Schleicher and Reimers, 2020[4]).
Many countries re-opened schools gradually, setting out a process with a number of phases by grade or level of education.
For example, younger students were the first to return to school in Denmark (childcare and primary schools with additional
measures such as reduced class sizes and physical distancing), France (primary schools in most regions with limitations
on the number of children in a classroom), the Netherlands (primary schools) and Norway (kindergarten and grades 1 to 4
primary schools with additional measures such as reduced class sizes and physical distancing).In contrast, schools reopened first for older students in Greece and Korea, especially for final year students who were sitting for secondary school
qualification examinations or entrance examinations for tertiary education (OECD, 2020[3]; Schleicher and Reimers, 2020[4];
UNESCO, 2020[1]).
While schools in many countries began to re-open in April and May, the plans are for primary and secondary schools in
Ireland, Italy, Lithuania, Portugal (except grades 11 and 12) and Spain (schools re-open for grades 10 and 12 with voluntary
attendance) to be closed until June (inclusive), that is to say the end of the school year 2019/20 (UNESCO, 2020[1];
Schleicher and Reimers, 2020[4]; OECD, 2020[3]).

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

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362  D1. HOW DOES TIME SPENT BY STUDENTS IN THE CLASSROOM VARY OVER THE YEARS?
subjects they chose from a list defined by central education authorities). It is compulsory for the school to offer one of these
subjects, and students must attend.
Compulsory options chosen by the students refers to the total amount of instruction time in one or more subjects that
pupils have to select (from a set of subjects that are compulsory for schools to offer) in order to cover part of their compulsory
instruction time.
Compulsory subjects with a flexible timetable refers to the total amount of instruction time indicated by the central
authorities for a given group of subjects, which regional authorities, local authorities, schools or teachers allocate to individual
subjects. There is flexibility in the time spent on a subject, but not in the subjects to be taught.
Flexible allocation of instruction time across multiple grades refers to the case where the curriculum only indicates the
total instruction time for a specific subject for a certain number of grades, or even the whole of compulsory education, without
specifying the time to be allocated to each grade. In such cases, schools/local authorities are free to decide how much time
should be assigned for each grade.
Instruction time refers to the time a public school is expected to provide instruction to students on all the subjects integrated
into the compulsory and non-compulsory curriculum, on school premises or in before-school/after-school activities that are
formal parts of the compulsory programme. Instruction time excludes breaks between classes or 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 (OECD, 2007[8])).
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 full-time general education.
Although the data are difficult to compare among countries because of different curricular policies, they nevertheless provide
an indication of how much formal instruction time is considered necessary for students to achieve the desired educational
goals.
When the allocation of instruction time across grades is flexible (i.e. instruction time for a specific subject is defined for a
certain number of grades, or even the whole of compulsory education, without specifying the time to be allocated to each
grade), instruction time per age or level of education was estimated by 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[9])
and Annex 3 for country-specific notes (https://doi.org/10.1787/69096873-en).

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D1. HOW DOES TIME SPENT BY STUDENTS IN THE CLASSROOM VARY OVER THE YEARS?  363

Source
Data on instruction time are from:


the 2012 OECD-INES Survey on Teachers and the Curriculum and refer to the school year 2010/11.



the 2013 to 2018 Joint Eurydice-OECD Instruction time data collection and refer to instruction time during compulsory
primary and full-time lower secondary general education for the school years 2013/14 to 2018/19.

References

European Commission/EACEA/Eurydice (2019), The Organisation of School Time in Europe, Primary and General
Secondary Education - 2019/20, Publications Office of the European Union.

[2]

Ministère de l’Éducation nationale et de la Jeunesse (2020), Ma classe à la maison : mise en œuvre de la
continuité pédagogique [My class at home: implementing educational continuity], Ministère de l’Éducation
nationale et de la Jeunesse, France, https://www.education.gouv.fr/ma-classe-la-maison-mise-en-oeuvre-de-lacontinuite-pedagogique-289680 (accessed on 20 April 2020).

[5]

Ministry of Education and Religious Affairs (2020), Mathainoume sto spiti [We learn at home], Ministry of Education
and Religious Affairs, Greece, https://mathainoumestospiti.gov.gr/ (accessed on 20 April 2020).

[6]

Ministry of Education and Vocational Training (2020), El Ministerio de Educación y FP y RTVE lanzan
’Aprendemos en casa’ para facilitar el aprendizaje de todo el alumnado durante la suspensión de clases
presenciales [Ministry of Education and FP and RTVE launch ’learn at home’ during school closure], Ministry of
Education and Vocational Training, Spain,
https://www.educacionyfp.gob.es/prensa/actualidad/2020/03/20200321-mefprtve.html (accessed on
20 April 2020).

[7]

OECD (2020), Key country policy responses, https://oecd.github.io/OECD-covid-actionmap/data/CoronavirusUpdate_AllCountries_Public.xlsx (accessed on 25 June 2020).

[3]

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 (2007), Education at a Glance 2007: OECD Indicators, OECD Publishing, Paris,
https://dx.doi.org/10.1787/eag-2007-en.

[8]

Schleicher, A. and F. Reimers (2020), Schooling disrupted, schooling rethought: How the COVID-19 pandemic is
changing education, OECD, https://read.oecd-ilibrary.org/view/?ref=133_133390-1rtuknc0hi&title=Schoolingdisrupted-schooling-rethought-How-the-Covid-19-pandemic-is-changing-education (accessed on 3 June 2020).

[4]

UNESCO (2020), COVID-19 Educational Disruption and Response,
https://en.unesco.org/covid19/educationresponse (accessed on 25 June 2020).

[1]

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364  D1. HOW DOES TIME SPENT BY STUDENTS IN THE CLASSROOM VARY OVER THE YEARS?

Indicator D1 Tables
Table D1.1

Instruction time in compulsory primary education (2011, 2014 to 2019)

Table D1.2

Instruction time in compulsory general lower secondary education (2011, 2014 to 2019)

Table D1.3

Instruction time per subject in compulsory primary education (2014 and 2019)

Table D1.4

Instruction time per subject in compulsory general lower secondary education (2014 and 2019)

WEB Table D1.5

Organisation of compulsory primary education (2011, 2014 to 2019)

WEB Table D1.6

Organisation of compulsory general lower secondary education (2011, 2014 to 2019)

Cut-off date for the data: 19 July 2020. Any updates on data can be found on line at http://dx.doi.org/10.1787/eag-dataen. More breakdowns can also be found at http://stats.oecd.org/, Education at a Glance Database.

StatLink: https://doi.org/10.1787/888934165149

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D1. HOW DOES TIME SPENT BY STUDENTS IN THE CLASSROOM VARY OVER THE YEARS?  365

Table D1.1. Instruction time in compulsory primary education1 (2011, 2014 to 2019)
In public institutions

Note: Columns showing the data for 2014 and 2016 to 2018 and non-compulsory instruction time 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. The number of grades that are part of compulsory primary education have changed: in 2016 in Australia, in 2014 in Ireland and in 2014 in Turkey following the split of a
single structure between primary and lower secondary levels. For more information, see Table D1.5.
3. 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.
Source: OECD (2013 to 2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888934165168

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366  D1. HOW DOES TIME SPENT BY STUDENTS IN THE CLASSROOM VARY OVER THE YEARS?
Table D1.2. Instruction time in compulsory general lower secondary education 1 (2011, 2014 to 2019)
In public institutions

Note: Columns showing the data for 2014 and 2016 to 2018 and non-compulsory instruction time 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.
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. Excludes the last year of compulsory education, which can be classified as either lower secondary or upper secondary level.
4. The number of grades that are part of compulsory lower secondary education have changed: in 2014 in Luxembourg and in 2016 in Spain and Scotland (United Kingdom).
For more information, see Table D1.6.
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 (2013 to 2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888934165187

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D1. HOW DOES TIME SPENT BY STUDENTS IN THE CLASSROOM VARY OVER THE YEARS?  367

Table D1.3. Instruction time per subject in compulsory primary education (2014 and 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. Columns showing other subjects areas and noncompulsory instruction time 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. Australia, England (United Kingdom), the Flemish Community of Belgium, the French Community of Belgium, Italy, the Netherlands, Portugal and Scotland
(United Kingdom) are not included in the averages.
2. For some subjects, allocation of instruction time across multiple levels of education is flexible.
3. The second language of instruction includes other national languages taught in 2019. In Ireland, the second language is included in “Other subjects” in 2014.
4. Excludes the first three years of primary education for which a large proportion of the time allocated to compulsory subjects is flexible.
Source: OECD (2014 and 2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888934165206
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368  D1. HOW DOES TIME SPENT BY STUDENTS IN THE CLASSROOM VARY OVER THE YEARS?
Table D1.4. Instruction time per subject in compulsory general lower secondary education (2014 and 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. Columns showing other subjects areas and noncompulsory instruction time 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. Australia (2014 only), England (United Kingdom), the Flemish Community of Belgium, Ireland (2019 only), the Netherlands, Portugal (2019 only) and Scotland (United
Kingdom) are not included in the averages.
2. 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.
3. For some subjects, allocation of instruction time across multiple levels of education is flexible.
4. The second language of instruction includes other national languages taught in 2019.
5. Actual instruction time in 2014.
6. Instruction time for other languages is included in instruction time for the second language for grade 9 in 2019.
Source: OECD (2014 and 2019). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888934165225

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370  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


At upper secondary level, the programme orientation can strongly influence the student-teacher ratio. In about
40% of OECD countries with data, the ratio is greater in vocational programmes than in general ones.



On average across OECD countries with available data, the student-teacher ratio is slightly higher in public
institutions than in private ones at both lower and upper secondary level.



Between 2005 and 2018, class sizes have fallen by 2% at primary level and 7% at lower secondary level on
average across OECD countries.

Figure D2.1. Ratio of students to teaching staff in upper secondary education, by programme
orientation (2018)
General programmes
Vocational programmes

Ratio
30
25
20
15
10

Luxembourg

Latvia

Lithuania

Austria

Denmark

Greece

Poland

Belgium

Norway

Switzerland1, 2

Czech Republic

Italy1

Spain

Hungary

New Zealand

EU23 average

Australia1

Turkey

Germany

Korea

Ireland

OECD average

France

Slovak Republic

Estonia1

Finland

Costa Rica

Slovenia

United States

United Kingdom1

Chile

Netherlands

Brazil

0

Mexico

5

1. Upper secondary includes programmes outside upper secondary level - see Annex 3 for further details.
2. Public institutions only.
Countries are ranked in descending order of the ratio of students to teaching staff in upper secondary general programmes.
Source: OECD/UIS/Eurostat (2020), Table D2.1. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2 https://doi.org/10.1787/888934165396

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D2. WHAT IS THE STUDENT-TEACHER RATIO AND HOW BIG ARE CLASSES?  371

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), teachers’ working time and the division of
teachers’ time between teaching and other duties (see Indicator D4). Together with teachers’ salaries (see Indicator D3)
and instruction time (see Indicator D1), class size and student-teacher ratios also have a considerable impact on the level
of current expenditure on education through teacher salary costs (Box D2.3).
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, investment in their professional
development, greater investment in teaching technology, or more widespread use of assistant teachers whose salaries
are often considerably lower than those of teachers.
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
Valenaire, 2006[1]), overall evidence of the effect of class size on student performance is mixed (Fredriksson, Öckert and
Oosterbeek, 2013[2]; OECD, 2016[3]). Changes in class size over periods of time may also reveal potential imbalances in
the supply of teachers compared to student demand. Some countries face difficulties in recruiting new teachers to respond
to a growing student base, while others face the opposite problem of adjusting the overall number of teachers to declining
enrolments (OECD, 2019[4]).
In the context of the 2020 global COVID-19 crisis, class size will be a critical parameter that will determine if and how
schools reopen after the lockdown measures imposed in most OECD and partner countries. Guidelines on social
distancing have imposed a minimum safety distance between students that will need to be accommodated in current
classrooms. Countries with larger classes will face more challenges in reorganising student groups to minimise the risks
of viral transmission (Box D2.2).

Other findings


On average across OECD countries, there are 15 students for every teacher at primary level but the ratio ranges
from 9 to 1 in Greece and Luxembourg to 26 to 1 in Mexico.



At primary level, the average class in OECD countries has 21 students. There are fewer than 25 students per
class in nearly all of the countries with available data, with the exception of Chile, Israel, Japan, and the United
Kingdom.



On average across OECD countries, average class sizes do not differ between public and private institutions by
more than one student per class in either primary or lower secondary education.

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372  D2. WHAT IS THE STUDENT-TEACHER RATIO AND HOW BIG ARE CLASSES?

Analysis
Student-teacher ratios
By level of education
The ratio of students to teaching staff compares the number of students (full-time equivalents) to the number of teachers (fulltime 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 relative to the length of teachers’ working days, nor how much time teachers spend
teaching. Therefore, it cannot be interpreted in terms of class sizes (Box D2.1).
On average across OECD countries, there are 15 students for every teacher at primary level but the ratio ranges from 9 to 1
in Greece and Luxembourg to 26 to 1 in Mexico. 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 between primary and 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). Only Chile, Colombia, Costa Rica, Hungary, Mexico, and the Netherlands, have a larger
student to teacher ratio at secondary level than at primary level (Table D2.1).
On average, the student-teacher ratio is about the same in lower 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 over twice
as many students per teacher at the upper secondary level than at the lower secondary level. In Mexico, it is the opposite
case, with 33 students per teacher at lower secondary level compared to 22 at upper secondary level (Table D2.1).
At the upper secondary level, the programme orientation can strongly influence the student-teacher ratio although on average
the ratios of students to teaching staff in upper secondary vocational and general programmes are similar (13 to 1). In about
40% of OECD countries with data, the ratio is greater in vocational programmes than in general ones. In Latvia, New Zealand
and the United Kingdom, there are about 9 students more per teacher in vocational programmes than in general ones. In
other countries such as Brazil and Mexico, the difference is reversed: there are over ten students more per teacher in general
programmes (Figure D2.1).
A combination of several factors may influence the variation in student-teacher ratios between vocational and general upper
secondary programmes. In some countries, vocational programmes are significantly work-based, so vocational students
spend considerable time outside the school resulting in fewer teachers (OECD, 2017[5]). Countries where more than half of
upper secondary vocational students are enrolled in combined school- and work-based programmes tend to have an equal
or higher number of students per teacher in vocational than in general programmes. In contrast, in most countries where all
upper secondary vocational students are enrolled in school-based programmes, the student-teacher ratio in general
programmes tends to be the same or higher than in vocational ones.
However, programme type alone does not explain all differences between student-teacher ratio in vocational and general
upper secondary education. Other factors, such as field of study, also influence the student-teacher ratio in vocational
programmes. Some fields require greater instructor attention and supervision, particularly those where students have access
to more sophisticated equipment (Hoeckel, 2008[6]). This may be particularly the case in technical fields such as engineering,
manufacturing and construction, or some specialties in health and welfare. For example, Latvia and the United Kingdom have
among the lowest shares of upper secondary vocational students graduating from the combined fields of engineering,
manufacturing and construction and health and welfare across OECD countries (see Box B7.1). In both countries, there are
nine more students per teacher in vocational than in general programmes, the highest difference across OECD countries. In
contrast, the fields of study of upper secondary vocational graduates in Austria, Germany and Switzerland are more
diversified, which may explain the similar student-teacher ratios across programme orientations in these countries. These
differences have important implications for the cost of vocational instruction, as advanced vocational training in specialised
fields of study requires both complex machinery and a greater level of human resources (Klein, 2001[7]). In most countries
with available data, the cost per student in upper secondary vocational programmes is higher than in general ones (see
Box C1.1).
At tertiary level, there are on average 15 students per teaching staff member. The student-teacher ratio ranges from 4 to 1 in
Luxembourg to over 25 to 1 in Colombia and Indonesia. The difference in student-teaching staff ratios across short-cycle
tertiary and bachelor’s, masters and doctoral or equivalent level varies across countries with available data. These results

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D2. WHAT IS THE STUDENT-TEACHER RATIO AND HOW BIG ARE CLASSES?  373
should be interpreted with caution, however, as the student-teacher ratio remains a limited measure of the level of teaching
resources at tertiary level, where research staff may make up a significant share of academic personnel. Moreover, the
relatively low enrolment in short-cycle tertiary in some countries limits comparability across tertiary levels (see Indicator B1).

By type of institution
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 lower and upper secondary level (Table D2.2). However, this can differ significantly
across countries. At lower secondary level, about 40% of OECD and partner countries with available data have more students
per teacher in private institutions than in public ones. Among those countries, the largest difference between private and public
institutions is found in Chile, Portugal and Spain -where there are at least 5 more students per teacher in private institutions than
in public ones- and particularly in Luxembourg with 17 more students. In contrast, in Mexico and the Russian Federation, the
ratios of students to teaching staff is over two times higher in public institutions. At upper secondary level, the student-teacher
ratio is larger in public institutions than in private institutions in 18 countries, smaller in public institutions in 13 countries, and
similar for both sectors in 8 countries. Mexico displays the largest variation among OECD countries with 10 students more per
teacher in public than in private institutions at this level. Among partner countries, the highest difference is observed in South
Africa, with 14 more students per teacher in public than in private upper secondary institutions (Figure D2.2).

Figure D2.2. Ratio of students to teaching staff in upper secondary education, by type of institution (2018)
Ratio

Public institutions
Private institutions

35
30
25
20
15
10

0

South Africa
Colombia
Brazil
Mexico
Finland
Chile
United Kingdom1
United States
Estonia1
Indonesia
China
Slovak Republic
Costa Rica
Slovenia
Sweden
Turkey
Canada
New Zealand
OECD average
Ireland
Germany
Australia1
Denmark
Switzerland1
EU23 average
Hungary
Korea
Saudi Arabia
France
Czech Republic
Japan1
Latvia
Italy1
Austria
Norway
Israel
Belgium
Poland
Spain
Greece
Luxembourg
Portugal1
Lithuania

5

1. Upper secondary includes programmes outside upper secondary level - see Annex 3 for further details.
Countries are ranked in descending order of the ratio of students to teaching staff in public institutions.
Source: OECD/UIS/Eurostat (2020), Table D2.2. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2 https://doi.org/10.1787/888934165415

Although on average across OECD countries the difference between the student-teacher ratio in public and private institutions
tends be the same at lower and upper secondary level, the range of variation differs across countries. In about 40% of OECD
countries with data, there are larger variations in the student-teacher ratio between public and private institutions at upper
secondary level than at lower secondary. For example, although the student-teacher ratio at lower secondary level is the
same for public and private institutions in both Denmark and Italy, at upper secondary level, Denmark has seven more
students per teacher in public institutions than in private ones and Italy has four more. In other countries, the difference
narrows at upper secondary level: while Mexico has 22 more students per teacher in public institutions than in private ones
at lower secondary level, the difference falls to 9 at upper secondary level. Finally, in some countries, the situation is reversed.
In Japan, the student-teacher ratio is larger in public institutions than private ones at lower secondary level, but it is the other
way around at upper secondary. 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

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374  D2. WHAT IS THE STUDENT-TEACHER RATIO AND HOW BIG ARE CLASSES?
programmes, which have a slightly lower student-teacher ratio than general programmes. In addition, in a number of countries,
the provision of private education increases in upper secondary education, which may also influence the student-teacher ratio
at this level (Table D2.2and Figure D2.2).

Box D2.1. What is the relationship between class size and the student-teacher ratio?
Class size, as presented in Table D2.3, 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 Table D2.1 and Table D2.2, is calculated by dividing the number of full-time equivalent students by the number of fulltime equivalent teachers at a given level of education.
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 relative to its student population, whereas
class sizes measure the average number of students that are grouped together in a classroom.
Given the difference between student-teacher ratios and average class sizes, 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), but the average class size differs substantially
(21 students per class in the United States and 26 in Israel). This may be explained by the fact that teaching hours in
the United States are considerably longer 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 D4).

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 25 pupils per class in all the
countries with available data, with the exception of Chile, Israel, Japan, and the United Kingdom. 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, the Russian Federation and the Slovak Republic to
30 students or more per class in Chile, Colombia, Costa Rica and Japan (Table D2.3).
The number of students per class tends to increase between primary and lower secondary education, although to a varying
extent across countries. In Costa Rica, this increase corresponds to 18 students, the highest difference across OECD
countries. On the other hand, in the United Kingdom and, to a lesser extent, Australia, Chile, Finland, Hungary, Latvia and
the Russian Federation, the number of students per class falls between these two levels of education (Table D2.3).

Box D2.2. Class size, a critical parameter for the reopening of schools during the COVID-19 pandemic
The COVID-19 global crisis has led to full school closures in most OECD countries. When and how to reopen is one of
the toughest and most sensitive decisions now on political agendas. Unquestionably, the largest factor driving the decision
is the stage and spread of the disease, and the likelihood of a second wave of infections, all of which vary significantly
across countries. Some countries, such as Ireland, Italy, Lithuania, and Spain, have been reluctant to allow students to
go back to school before the start of the 2020-2021 academic year, preferring to ensure pedagogical continuity through
online learning. While some countries have decided to keep schools closed for the remainder of the 2019-2020 academic
year, other countries have progressively started reopening their classroom doors. However, reopening in the midst of a
health crisis will require a careful assessment of the hygiene and sanitary measures in place to protect students and staff
from the risks of transmission.

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D2. WHAT IS THE STUDENT-TEACHER RATIO AND HOW BIG ARE CLASSES?  375
The response to school reopening has been evaluated based on the scientific evidence regarding the spread of the disease
and its containment. Most countries have engaged in a gradual and phased reopening of schools to allow preventive
measures to be effectively implemented. Many, such as Denmark, France, the Netherlands, and Norway, have prioritised
lower levels of education, due to their importance in the cognitive development of children, and to the difficulty in engaging
with young children in an online format. In contrast, countries such as Greece, Iceland, Korea or Portugal have prioritised
upper secondary over primary levels (see Box D1.2) (Schleicher and Remiers, 2020[8]) (OECD, 2020[9]).
However, school reopening is contingent on a number of preventive measures which schools have been instructed to
implement to contain the spread of the disease. Among others, social distancing has proven to be one of the most effective.
Within a school context, this means reducing contact between groups of children and maintaining a safe distance of 12 metres between pupils and staff. In some countries, the safety distance depends on the level of containment of the virus
achieved. For example, schools in less-affected areas in Japan (Level 1) are required to maintain a distance of 1 metre
while those in more-affected ones (Levels 2 or 3) maintain a distance of 1-2 metres (MEXT, 2020[10]). Guidance in many
countries has been to reduce or halve the size of the classes in order to maintain the required safety distance between
students. Some countries have specified the maximum number of students allowed in the classroom at any given time.
For example, France and the United Kingdom have recommended a limit of 15 students in primary classes, provided the
safety distances are maintained (Ministère de l’Education Nationale et de la Jeunesse, 2020[11]; Department for Education,
2020[12]).
Countries with smaller class sizes will find it easier to comply with new restrictions on social distancing. Although France
and the United Kingdom recommend the same limit on the number of children per primary class, public institutions in
France have a smaller class size with 23 students, than the United Kingdom with 27 students per class. As class size
tends to increase with education level, social distancing in the classroom will be more challenging at secondary level. With
more than 30 students per class in lower secondary level, countries such as Chile, Colombia and Japan will face more
difficulties in reorganising classes into smaller groups of students in order to maintain a safe distance between desks.
However, reducing class size will also depend on other factors such as classroom size, room availability, staff availability
and personal decisions from pupils and staff on when to return to schools.
While returning to school is compulsory in most OECD countries for students in permitted age groups or specific levels of
education (except for sick students or those with a vulnerable or sick family member), attendance is optional in countries
such as Canada, the Czech Republic, France, and Spain, with remote and online learning for students who wish to stay
at home. These hybrid measures aim to secure support for the reopening of schools while optimising their capacity for
social distancing (Schleicher and Remiers, 2020[8]).
To ensure all students have the opportunity to benefit from face-to-face teaching in a context of reduced class sizes,
schools in about 60% of OECD member and partner countries are organising shifts to alternate students throughout the
day when they cannot accommodate them all on site (Schleicher and Remiers, 2020[8]). The direct consequence of this
measure will be reduced classroom instruction time compared to before school closures (see Box D1.2). Distance learning
has therefore remained in place until the end of the academic year to continue to support students, including for those
who have opted not to or cannot attend class for sanitary or personal health reasons.

Class size in public and private institutions
Class size is one factor that parents may consider when deciding on a school for their children, particularly at lower levels of
education. Hence, the difference in average class size between public and private schools (and between different types of
private institutions) could influence enrolment in different types of institutions.
Differences in class sizes between public and private institutions are similar to those observed for student-teacher ratios. On
average across OECD countries, class sizes do not differ between public and private institutions by more than one student
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
six additional students compared to the average class in private schools (Table D2.3). However, with the exception of Brazil
and Colombia, the private sector is relatively small in all of these countries, representing at most 6% of students at the primary
level (OECD, 2019[13]). In contrast, in Chile, Greece and Korea, the average primary class in private institutions is larger than
in public institutions by at least four students (Figure D2.3).

EDUCATION AT A GLANCE 2020 © OECD 2020

376  D2. WHAT IS THE STUDENT-TEACHER RATIO AND HOW BIG ARE CLASSES?
At the lower secondary level, where private institutions are more prevalent, the comparison of class size between public and
private institutions shows even larger variations. For example, in Costa Rica, there are on average 15 students less per class
in private institutions than in public ones. The average class in private lower secondary institutions is larger than in public
institutions in 8 countries, smaller in 17 countries and the same in 7 countries (Figure D2.3).

Trends in average class size
Between 2005 and 2018, class sizes have fallen at primary level and lower secondary level on average across OECD
countries. At primary level, while class size decreased by 2% on average, there are strong differences among countries.
About half of countries experienced an increase between 2005 and 2018, with Mexico and the Russian Federation displaying
the most notable increases of 21% and 29% respectively. In contrast, primary class sizes in Korea decreased by almost 30%
over the same period, the highest decline over the same period across countries with data. At the lower secondary level, the
average class size fell by 7% between 2005 and 2018. This average masks considerably larger changes in individual
countries. In Greece and Korea, for example, the average class size in lower secondary education has decreased by about
20-25% over the past decade whereas it increased by 3% or more in France, and Spain (Table D2.3).
Changes in class size may reflect efforts to balance the supply of teachers with changes in the student population. Countries
with lower than average class sizes may see an increasing trend. For example, small class sizes in Lithuania results from both
a high concentration of teachers in the active population and a declining student base (Shewbridge et al., 2016[14]). As a result,
primary class size has increased by 17% between 2005 and 2018 as new recruits to the teaching profession are limited. In 2018,
only 5% of primary teachers were under the age of 30, one of the lowest across OECD countries. In contrast, countries such as
Chile and Korea with higher than average primary class sizes have both seen a notable decline between 2005 and 2018 (Table
D2.3). In Chile, this is likely due to a rise in primary teacher numbers, which increased by more than 10% since 2014. In contrast,
in Korea, declining student numbers has likely contributed to the fall in class size (OECD, 2019[13]).

Class size, along with instruction time and teaching time, determines the number of teachers an education system
requires. It is therefore an important parameter in understanding the level of expenditure allocated to staff
compensation in education. Countries make different choices when investing their resources which affect the
salary cost of teachers per student (Box D2.3).

Figure D2.3. Average class size, by level of education (2018)
Number of students
per class

Primary
Lower secondary

40

30

20

Costa Rica

Latvia

Lithuania

Poland

Greece

Austria

Slovak Republic

Iceland

Slovenia

Italy

Estonia

Finland

Sweden

Denmark

EU23 average

Russian Federation

Germany

United States

OECD average

Czech Republic

Portugal

Hungary

Spain

Turkey

Brazil

Korea

Colombia

France

Australia

Mexico

United Kingdom

Israel

Japan

0

Chile

10

Countries are ranked in descending order of the average class size at the primary level.
Source: OECD/UIS/Eurostat (2020), Table D2.3. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2 https://doi.org/10.1787/888934165434

EDUCATION AT A GLANCE 2020 © OECD 2020

D2. WHAT IS THE STUDENT-TEACHER RATIO AND HOW BIG ARE CLASSES?  377

Box D2.3. Theoretical class size, one of the drivers of teachers’ salary cost
The salary cost of teachers per student is determined by four factors: teachers’ salaries, instruction time, teaching time and
theoretical class sizes. The impact of the first factor 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 must be hired in order to reduce class sizes while keeping everything else constant.

Figure D2.4. Contribution of various factors to salary cost of teachers per student in public institutions,
primary education (2018)
USD converted using PPPs for private consumption

USD converted
using PPPs
4 000

Contribution of teachers’ salary
Contribution of instruction time
Contribution of teaching time
Contribution of theoretical class size
Difference of salary cost of teachers per student from OECD average

3 000
2 000
1 000
0
-1 000
-2 000
-3 000
-4 000

How to read this figure: This figure shows the contribution (in USD) of the factors influencing the difference between salary cost of teachers per
studentin the country and the OECD average. For example, in Poland,the salary cost of teachers per studentis USD 192 lower than the OECD average.
Poland has a smaller theoretical class size (+ USD 975) and less teaching time (+ USD 953) than the OECD average, both of which push the salary
cost of teachers up. However, this is more than compensated for by below-average teachers' salaries (- USD 1 357) and below-average
instruction time (- USD 762), which push the cost down.
Notes: See Table D2.5, available on line, for notes on each factor.
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 (2020), Table D2.4, available on line. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2 https://doi.org/10.1787/888934165453

EDUCATION AT A GLANCE 2020 © OECD 2020

378  D2. WHAT IS THE STUDENT-TEACHER RATIO AND HOW BIG ARE CLASSES?
When comparing a country’s salary cost to the OECD average, it is possible to determine the contribution of each of the four
factors. For instance, it is possible to assess whether a given salary cost is above average because of higher salaries, higher
instruction time, lower teaching time, smaller class sizes or a combination of these four factors. Changes to one of these
factors may require compensating trade-offs among the other factors in order to keep the total salary cost constant.
Figure D2.4 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 compared to the OECD average depends on the difference
between the factor itself and the relevant OECD average. The sum of each factor’s contribution equals the difference in salary
cost between that country and the OECD average. For example, in Poland, the salary cost of primary teachers per student is
USD 192 below the OECD average. Poland has smaller estimated class sizes (+ USD 975) and shorter teaching time (+
USD 953) than the OECD average, both of which push the salary cost of teachers up. However, this is more than
compensated for by below-average teachers' salaries (- USD 1 357) and below-average instruction time (- USD 762), which
push the cost down (Figure D2.4).
The analysis highlights different policies at primary level across countries with similar spending. For example, the teacher
salary costs per student in Greece and Japan are very similar (about 3 000 USD), but how they allocate their resources differ
substantially. Japan spends more than OECD countries on average on primary teachers’ salaries and primary teachers have
slightly shorter teaching hours than on average across countries. It compensates for these costs with larger than average
class sizes, and shorter students’ instruction time. In contrast, class sizes in Greece are significantly smaller than the average.
Greece compensates for the higher cost of smaller classes with below-average teachers’ salaries at this level (Figure D2.4).

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.

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 (OECD,
2018[15]) and Annex 3 for country-specific notes (https://doi.org/10.1787/69096873-en).

EDUCATION AT A GLANCE 2020 © OECD 2020

D2. WHAT IS THE STUDENT-TEACHER RATIO AND HOW BIG ARE CLASSES?  379

Source
Data refer to the academic year 2017/18 and are based on the UNESCO-UIS/OECD/EUROSTAT data collection on education
statistics administered by the OECD in 2019 (for details, see Annex 3 at https://doi.org/10.1787/69096873-en).

References

Department for Education (2020), Coronavirus (COVID-19): Implementing protective measures in education and
childcare settings, GOV.UK website, https://www.gov.uk/government/publications/coronavirus-covid-19implementing-protective-measures-in-education-and-childcare-settings (accessed on 20 May 2020).

[12]

Fredriksson, P., B. Öckert and H. Oosterbeek (2013), “Long-term effects of class size”, Quarterly Journal of
Economics, Vol. 128/1, pp. 249-285, https://doi.org/10.1093/qje/qjs048.

[2]

Hoeckel, K. (2008), Costs and Benefits in Vocational Education and Training, OECD, Paris,
https://www.oecd.org/education/skills-beyond-school/41538706.pdf (accessed on 26 May 2020).

[6]

Klein, S. (2001), Financing Vocational Education: A State Policymaker’s Guide, RTI International,
http://www.rti.org/sites/default/files/resources/financing_vocational_education.pdf.

[7]

MEXT (2020), Gakkou niokeru shingata coronavirus kansenshou nikansuru eiseikanri manual - Gakkou no
atarashii seikatsu youshiki [COVID-19 hygiene management at schools - New lifestyle at schools], Ministry of
Education, Culture, Sports, Science and Technology, Japan,
https://www.mext.go.jp/content/20200522_mxt_kouhou02_mext_00029_01.pdf (accessed on 25 May 2020).

[10]

Ministère de l’Education Nationale et de la Jeunesse (2020), Réouverture des écoles et des établissements
scolaires [Reopening of schools and educational establishments], Ministère de l’Education Nationale et de la
Jeunesse, France, https://www.education.gouv.fr/bo/20/Hebdo19/MENE2011220C.htm (accessed on
20 May 2020).

[11]

OECD (2020), Key country policy responses, https://oecd.github.io/OECD-covid-actionmap/data/CoronavirusUpdate_AllCountries_Public.xlsx (accessed on 30 June 2020).

[9]

OECD (2019), Education at a Glance Database, https://stats.oecd.org/ (accessed on 6 July 2018).

[13]

OECD (2019), Working and Learning Together: Rethinking Human Resource Policies for Schools, OECD Reviews
of School Resources, OECD Publishing, Paris, https://dx.doi.org/10.1787/b7aaf050-en.

[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.

[15]

OECD (2017), Education at a Glance 2017: OECD Indicators, OECD Publishing, Paris,
http://dx.doi.org/10.1787/eag-2017-en.

[5]

OECD (2016), PISA 2015 Results (Volume II): Policies and Practices for Successful Schools, PISA, OECD
Publishing, Paris, https://doi.org/10.1787/9789264267510-en.

[3]

Piketty, T. and M. Valenaire (2006), “L’impact de la taille des classes sur la réussite scolaire dans les écoles,
collèges et lycées français”, Les Dossiers: Enseignement scolaire, Vol. 173.

[1]

EDUCATION AT A GLANCE 2020 © OECD 2020

380  D2. WHAT IS THE STUDENT-TEACHER RATIO AND HOW BIG ARE CLASSES?
Schleicher, A. and F. Remiers (2020), Schooling disrupted schooling rethought :How the Covid-19 pandemic is
changing education, https://read.oecd-ilibrary.org/view/?ref=133_133390-1rtuknc0hi&title=Schooling-disruptedschooling-rethought-How-the-Covid-19-pandemic-is-changing-education (accessed on 3 June 2020).

[8]

Shewbridge, C. et al. (2016), OECD Reviews of School Resources: Lithuania 2016, OECD Reviews of School
Resources, OECD Publishing, Paris, https://dx.doi.org/10.1787/9789264252547-en.

[14]

Indicator D2 Tables
Table D2.1

Ratio of students to teaching staff in educational institutions, by level of education (2018)

Table D2.2

Ratio of students to teaching staff, by type of institution (2018)

Table D2.3

Average class size, by type of institution (2018) and index of change between 2005 and 2018

WEB Table D2.4

Contribution of various factors to salary cost of teachers per student in primary education (2018)

WEB Table D2.5

Factors used to compute the salary cost of teachers per student in public institutions, in primary
education (2018)

Cut-off date for the data: 19 July 2020. Any updates on data can be found on line at http://dx.doi.org/10.1787/eag-dataen. More breakdowns can also be found at http://stats.oecd.org/, Education at a Glance Database.
StatLink: https://doi.org/10.1787/888934165320

EDUCATION AT A GLANCE 2020 © OECD 2020

D2. WHAT IS THE STUDENT-TEACHER RATIO AND HOW BIG ARE CLASSES?  381

Table D2.1. Ratio of students to teaching staff in educational institutions, by level of education (2018)
Calculations based on full-time equivalents

Partners

OECD

Upper secondary

Tertiary

General
Vocational
All
programmes programmes programmes

All
secondary

Postsecondary
non-tertiary

Short-cycle
tertiary

Bachelor’s,
master’s
and doctoral

All tertiary

Primary

Lower
secondary

Countries
Australia
Austria
Belgium
Canada 1
Chile
Colombia
Costa Rica
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland 2
Israel 2
Italy
Japan 3
Korea
Latvia
Lithuania
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland 2
Turkey
United Kingdom
United States

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

15
12
13
17 d
19
23
12
19
12
13
14
19
15
9
10
11
15
15
12
16
17
12
11
9
26
16
17
10
10
12
18
10 d
14
14
15
17
20
15

x(3)
8
9
x(1)
20
26
13
12
11
10
9
14
13
8
11
10
m
11
11
13
13
9
8
11
33
16
16
9
11
9
13
x(1)
12
11
12
16
16
15

12 d
10
11
x(5)
21
x(5)
14
11
10
14
14
13
12
10
12
m
13 d
x(5)
12
x(5)
13
9
8
8
27
16
12
11
11
x(5)
14
15
12
x(5)
11
12
15
15

m
10
9
x(5)
19
x(5)
11
11
17
18 d
22
8
14
8
12
a
a
x(5)
9d
x(5)
10
17
10
9
16
18
20
10
9
x(5)
13
13
9
x(5)
13 d
12
25 d
a

m
10
10
13
21
25
13
11
12
16 d
19
11
13
9
12
m
13 d
10
10 d
12 d
12
11
8
9
22
18
13
10
10
9d
13
14
11
14
12 d
12
18
15

m
9
9
m
20
26
13
12
11
13
14
13
13
9
11
m
13
10
11 d
12 d
13
10
8
9
28
17
15
10
10
9d
13
m
11
12
12 d
14
17
15

m
11
16
m
a
54
a
14
a
x(4)
22
18
13
m
8
m
m
m
x(4)
x(5)
a
25
15
12
a
a
24
12
14
x(5)
14
a
a
10
x(4)
a
a
x(10)

m
8
x(10)
m
m
25
m
11
19
a
a
12
12
a
x(10)
m
x(10)
m
a
m
m
13
a
9
20
12
19
11
10
x(10)
7
22
11
7
a
57
x(4, 10)
x(10)

16
16
x(10)
m
m
29
m
15
15
13
15
18
12
m
x(10)
m
x(10)
16
20
m
m
18
14
4
18
15
18
9
14
x(10)
12
14
13
10
13
21
x(4, 10)
x(10)

m
14
21
m
m
28
m
15
16
13
15
17
12
m
12
m
20
m
20
m
m
16
14
4
18
15
18
9
14
14
11
14
12
10
13
25
15
14

OECD average
EU23 average

15
13

13
11

13
12

13
13

13
12

13
12

18
15

16
12

15
14

15
14

Argentina
Brazil
China
India
Indonesia
Russian Federation
Saudi Arabia
South Africa

m
24
16
m
17
23
14
m

m
25
12
25
15
12 d
12
m

m
26
x(5)
x(5)
x(5)
x(2)
x(5)
m

m
14
x(5)
x(5)
x(5)
x(8)
x(5)
m

m
24
14
33
15
x(2, 8)
11
28

m
24
13
29
15
12
12
28

a
25
m
m
a
x(8)
2
42

m
3
m
m
m
13 d
m
m

m
25
m
m
m
12
17
m

m
25
m
25
27
13 d
19
m

G20 average

17

16

m

m

16

16

m

m

m

19

1. Primary includes pre-primary education.
2. For Ireland and Switzerland, public institutions only for all levels. For Israel, public institutions only for lower secondary, upper secondary education and all secondary.
3. Upper secondary education includes a part of post-secondary non-tertiary education.
Source: OECD/UIS/Eurostat (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888934165339

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382  D2. WHAT IS THE STUDENT-TEACHER RATIO AND HOW BIG ARE CLASSES?
Table D2.2. Ratio of students to teaching staff, by type of institution (2018)
By level of education, calculations based on full-time equivalents
Lower secondar y

Upper secondary

All secondar y programmes

Governmentdependent
private
institutions

Independent
private
institutions

Total private
institutions

Total private
institutions

Public
insti tution s

Public
insti tution s

Independent
private
institutions

Independent
private
institutions

Governmentdependent
private
institutions

(1)

(2)

(3)

(4)

(5)

(6)

Countries
Australia 1
Austria
Belgium
Canada
Chile
Colombia
Costa Rica
Czech Republic
Denmark
Estonia 2
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy 2
Japan 2
Korea
Latvia
Lithuania
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Por tugal 2
Slovak Republic
Slovenia
Spain
Sweden
Switzerland 2
Turkey
Unite d Kingdom 2
United States

x(5)
8
9
m
16
28
14
13
11
10
9
14
13
8
11
10
x(5)
11
11
13
13
9
8
9
38
16
17
9
12
9
13
m
11
11
12
17
16
16

x(6)
9
9
m
24
21
8
11
11
8
10
16
13
8
12
6
m
m
11
11
14
5
8
26
16
m
13
9
9
14
12
m
15
12
m
9
16
10

x(7)
x(2)
9
m
25
a
14
11
11
8
10
16
x(2)
a
13
6
a
m
a
a
14
a
a
10
a
a
a
9
11
12
12
m
16
12
m
a
18
a

a
x(2)
5
m
20
21
7
a
4
4
a
m
x(2)
8
11
m
m
a
11
11
a
5
8
m
16
m
13
10
9
15
a
a
14
a
m
9
8
10

12
10
10
13
18
26
14
11
12
16
18
11
13
9
12
m
13 d
10
11
11 d
12
11
8
9
25
18
13
10
10
9
14
14
10
14
12
13
16
16

11
10
10
15
23
23
9
12
5
13
21
12
11
9
12
m
m
m
7
14 d
13
10
7
7
15
m
12
11
10
10
12
16
14
14
m
9
19
10

OECD average
EU23 average

13
11

12
12

12
12

11
9

13
12

Argentina
Brazil
China
Ind ia
Indonesia
Russian Federation
Saudi Arabia
South Africa

m
26
12
m
16
12 d
12
27

m
20
17
m
14
5d
10
m

m
a
x(2)
m
x(2)
a
x(2)
m

m
20
x(2)
m
x(2)
5d
x(2)
m

G20 average

17

13

m

m

Private insti tution s

Governmentdependent
private
institutions

Total private
institutions

Private insti tution s

Public
insti tution s
Par tners

OECD

Private insti tution s

(7)

(8)

(9)

(10)

(11)

(12)

11
x(6)
10
x(6)
24
a
13
12
5
12
21
12
x(6)
a
11
m
a
m
a
a
13
a
a
10
a
a
13
11
10
11
12
29
15
14
m
a
21
a

m
x(6)
10
x(6)
16
23
8
a
12
19
a
m
x(6)
9
14
m
m
a
7
14 d
a
10
7
5
15
m
11
a
10
9
a
12
13
a
m
9
8
10

m
9
9
m
17
27
14
12
12
13
13
13
13
9
11
m
13
10
11
12 d
12
10
8
9
32
17
15
10
10
9
13
m
10
12
12
15
16
16

m
10
9
m
23
22
8
11
9
10
18
14
12
8
12
m
m
m
8
13 d
14
8
8
10
16
m
12
11
10
11
12
m
15
13
m
9
17
10

m
x(10)
9
m
25
a
13
11
10
10
18
14
x(10)
a
12
m
a
m
a
a
14
a
a
10
a
a
13
11
11
12
12
m
15
13
m
a
20
a

m
x(10)
8
m
17
22
7
a
5
15
a
m
x(10)
8
13
m
m

12
11

14
14

11
10

13
11

12
11

13
13

11
10

m
25
14
m
15
x(1)
11
29

m
19
18
m
15
x(2)
11
15

m
a
x(6)
m
x(6)
a
x(6)
m

m
19
x(6)
m
x(6)
x(4)
x(6)
m

m
26
13
m
16
12
12
28

m
19
17
m
15
5
11
19

m
a
x(10)
m
x(10)
a
x(10)
m

m
19
x(10)
m
x(10)
5
x(10)
m

15

13

m

m

16

13

m

m

d

d

d

8
13 d
a
8
8
11
16
m
12
10
9
11
a
12
13
a
m
9
8
10

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.
Source: OECD/UIS/Eurostat (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888934165358

EDUCATION AT A GLANCE 2020 © OECD 2020

D2. WHAT IS THE STUDENT-TEACHER RATIO AND HOW BIG ARE CLASSES?  383

Index of change between 2005 and 2018 (2005 = 100)

All private
institutions

Governmentdependent private
institutions

Independent
private
institutions

All lower secondary
institutions

Public institutions

All private
institutions

Total
public and private
institutions

Public institutions

All private
institutions

All lower
secondary
institutions

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

(13)

(14)

(15)

(16)

23
18
m
m
28
25
16
21
20
19
20
23
21
17
22
19
m
27
19
27
23
17
17
15
25
23
m
a
18
21
18
19
21
20
19
23
27
21

24
19
m
m
32
18
16
15
17
15
18
25
22
21
21
15
m
25
19
28
27
10
16
m
20
m
m
a
12
20
18
20
24
18
m
18
23
18

24
x(2)
m
m
34
a
25
15
17
16
18
25
x(2)
a
21
15
m
25
a
a
a
a
a
19
a
m
m
a
11
22
18
20
25
18
m
a
28
a

a
x(2)
m
m
25
18
16
a
a
6
a
a
x(2)
21
17
a
m
a
19
28
27
10
16
m
20
m
m
a
12
20
a
a
21
a
m
18
12
18

23
18
m
m
31
23
16
21
20
19
20
23
21
17
22
19
m
26
19
27
23
16
17
m
24
m
m
a
18
21
18
19
22
20
m
22
26
21

21
21
m
m
29
31
35
22
21
19
19
25
24
20
21
20
m
29
21
32
27
16
19
18
27
m
m
a
21
22
19
20
25
22
19
26
24
27

24
21
m
m
31
24
20
18
19
15
19
26
24
22
21
14
m
24
21
33
26
13
20
m
23
m
m
a
16
23
18
20
26
22
m
18
22
20

24
x(7)
m
m
33
a
29
18
19
16
19
27
x(7)
a
22
14
m
24
a
a
26
a
a
19
a
m
m
a
17
25
18
20
27
22
m
a
25
a

a
x(7)
m
m
25
24
18
a
a
8
a
12
x(7)
22
17
a
m
a
21
33
a
13
20
m
23
m
m
a
16
23
a
a
20
a
m
18
12
20

22
21
m
m
30
30
33
22
20
19
19
25
24
20
21
20
m
28
21
32
27
16
19
m
27
m
m
a
21
22
19
20
25
22
m
25
23
26

97
92
m
m
86
m
m
103
102
97
m
m
95
88
110
103
m
97
104
96
71
99
117
97
125
104
m
a
91
116
92
102
107
m
m
83 d
105
102

m
92
m
m
102
m
m
m
m
m
m
m
93
m
108
111
m
m
99
83
83
120
156
m
91
m
m
a
99
94
m
119
101
m
m
m
a
99

98
92
m
m
96
m
m
102
101
96
m
m
95
88
109
103
m
95
104
96
71
98
117
m
121
m
m
a
89
114
92
102
105
m
m
82 d
108
102

87
88
m
m
82
m
m
93
103
82
m
104
97
81
97
100
m
95
100
96
75
82
87
95
91
m
m
a
86
97
85
97
105
m
m
x(11)
100
101

m
85
m
m
95
m
m
m
m
m
m
105
93
m
97
118
m
m
99
92
74
151
131
m
87
m
m
a
97
100
m
95
99
m
m
m
a
95

89
87
m
m
89
m
m
93
102
82
m
104
97
81
97
99
m
92
100
96
75
82
87
m
91
m
m
a
85
98
84
97
103
m
m
x(13)
105
100

OECD average

21

20

21

18

21

23

22

22

19

23

99

m

99

93

m

93

99

m

98

93

m

93

Governmentdependent private
institutions
Independent
private
institutions

Public institutions

Lower secondary

Countries
Australia
Austria
Belgium
Canada
Chile
Colombia
Costa Rica
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungar y
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Lithuania
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United Kingdom
United States
Average for countries
with available data
for both reference years

Par tners

Primary

All primary
institutions

Lower secondary
Private institutions

All private
institutions

Primary
Private institutions
Public institutions
OECD

Table D2.3. Average class size, by type of institution (2018) and index of change between 2005 and 2018
By level of education, calculations based on number of students and number of classes

EU23 average

20

19

20

15

20

21

21

21

17

21

101

m

101

93

m

93

Argentina
Brazil
China
India
Indonesia
Russian Federation
Saudi Arabia
South Africa

m
24
m
m
m
20
m
m

m
18
m
m
m
13
m
m

m
a
m
m
m
a
m
m

m
18
m
m
m
13
m
m

m
23
m
m
m
20
m
m

m
28
m
m
m
19
m
m

m
24
m
m
m
12
m
m

m
a
m
m
m
a
m
m

m
24
m
m
m
12
m
m

m
27
m
m
m
19
m
m

m
96
m
m
m
129
m
m

m
93
m
m
m
m
m
m

m
92
m
m
m
129
m
m

m
86
m
m
m
101
m
m

m
92
m
m
m
m
m
m

m
86
m
m
m
101
m
m

G20 average

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

m

Source: OECD/UIS/Eurostat (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888934165377

EDUCATION AT A GLANCE 2020 © OECD 2020

384  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. School heads’ actual salaries are over 53% higher on average than those
of teachers across primary and secondary education in OECD countries and economies.



Teachers’ actual salaries at pre-primary, primary and general secondary levels of education are 80-94% of the
earnings of tertiary-educated workers on average across OECD countries and economies.



On average across OECD countries and economies, primary and secondary school heads’ actual salaries are at
least 26% higher than the earnings of tertiary-educated workers.

Context
The 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 whether to remain a teacher – in general, the higher teachers’ salaries, the fewer people choose
to leave the profession (OECD, 2005[1]). 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. The recent global pandemic creates new
challenges for the economy and education systems, and will also put further pressure on public expenditure. 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 D2).
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. of Education at a Glance 2019 (OECD, 2019[2]), Box D3.3
and Annex 3) and the fact that data collected only cover public educational institutions, should be kept in mind when
analysing teachers’ salaries and comparing them across countries.

Other findings


In most OECD countries and economies, 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 among teachers.



The statutory salaries of teachers with maximum qualifications at the top of their salary scales are on average 7880% higher than those of teachers with the minimum qualifications at the start of their career.

EDUCATION AT A GLANCE 2020 © OECD 2020

D3. HOW MUCH ARE TEACHERS AND SCHOOL HEADS PAID?  385



Between 2005 and 2019, on average across OECD countries and economies with available data, the statutory
salaries of teachers with 15 years of experience and the most prevalent qualifications increased by 7% at primary
level, 7% at lower secondary level (general programmes) and 5% at upper secondary level (general programmes).



The statutory salaries of primary, lower secondary and upper secondary teachers with 15 years of experience
and minimum qualifications now exceed the levels prior to the 2008 crisis.



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 disadvantaged or remote areas 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’ actual salaries relative to earnings for
tertiary-educated workers (2019)
Ratio of salary, using annual average salaries (including bonuses and allowances) of teachers and school heads in
public institutions relative to the earnings of workers with similar educational attainment (weighted average) and to the
earnings of full-time, full-year workers with tertiary education
Teachers’ actual salaries relative to earnings
for tertiary-educated workers

School heads’ actual salaries relative to earnings 
for tertiary-educated workers

Teachers’ actual salaries relative to earnings
for similarly educated workers (weighted averages)

School heads’ actual salaries relative to earnings 
for similarly educated workers (weighted averages)
Costa Rica
Lithuania
Portugal
Germany
Finland
England (UK) 1
Israel
France
Australia
Estonia
OECD aver age
EU23 aver age
Slovenia
Netherlands
Sweden
New Zealand
Ireland
Flemish Comm. (Belgium) 2
Austria
Denmark
French Comm. (Belgium) 2
Chile
Greece
Poland
Norway
Slovak Republic
Italy
Hungary
Czech Republic
United States

2.5
Ratio

2.0

1.5

1.0

0.5

0.0

0.0

0.5

1.0

1.5

2.0

2.5
Ratio

1. Data on earnings for full-time, full-year workers with tertiary education refer to the United Kingdom.
2. Data on earnings for full-time, full-year workers with tertiary education refer to Belgium.
Countries and economies are ranked in descending order of the ratio of teachers' salaries to earnings for full-time, full-year tertiary-educated workers aged 25-64.
Source: OECD (2020), Table D3.2. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2https://doi.org/10.1787/888934165567

EDUCATION AT A GLANCE 2020 © OECD 2020

386  D3. HOW MUCH ARE TEACHERS AND SCHOOL HEADS PAID?

Analysis
Statutory salaries of teachers
Teachers’ statutory salaries can vary according to a number of factors, including the level of education taught, their
qualification level and their level of experience or the stage of their career (for variation between general and vocational
programmes see Box D3.2).

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 Hungary
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 D3.1).
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, Denmark, Lithuania 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 Finland and the Slovak Republic they earn 36-50% more, and in Mexico, 88% 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 D3.1).
The difference in salaries between teachers at pre-primary and upper secondary levels is less than 5% in Australia, Chile,
Costa Rica, France, Slovenia and the United States, and teachers earn the same salary irrespective of the level of education
taught in Colombia, England (United Kingdom), Greece, Poland, Portugal, Scotland (United Kingdom) and Turkey
(Table D3.1).
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 different levels of education. To become a teacher,
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 to explain the higher salaries
observed at these levels in those countries (Table X3.D3.2, available on line).
Differences in salaries for teachers with the minimum and most prevalent qualifications are by no means the general rule: in
countries where a large proportion of teachers have the minimum qualifications, they may also be the most prevalent
qualifications. 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, meaning there is no difference in statutory salaries between teachers with the minimum and most prevalent
qualifications throughout a teacher’s career.
In the remaining countries and economies, the most prevalent qualification is higher than the minimum qualification required
at a given level of education, and this is recognised by the compensation system. Among the 15 countries and economies
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 at all stages of their careers in Colombia (pre-primary and primary levels), the
Flemish Community of Belgium (upper secondary level), Norway (upper secondary level), Poland (pre-primary and primary
levels) and the United States (primary, lower and upper secondary levels). The difference exceeds 75% in Costa Rica,
EDUCATION AT A GLANCE 2020 © OECD 2020

D3. HOW MUCH ARE TEACHERS AND SCHOOL HEADS PAID?  387
although the salaries of teachers with the most prevalent qualifications are still at least 20% lower than the OECD average
(at all stages of their 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 qualifications (Tables D3.5 and
D3.6, available on line).
The most prevalent qualifications 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 might apply at one or more of the four career stages considered (starting point, 10 years of experience, 15 years
of experience and top of the range) in one or more levels of education. Such variation 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 career stage). In Norway, the most prevalent qualification when entering the teaching profession at the primary and lower
secondary level is the minimum qualification, but then the most prevalent qualification differs from the minimum among more
experienced teachers at these levels of education (Table D3.1 and Table D3.5, 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. Qualification levels can also influence starting and maximum salaries and lead to wage increases in
some countries.
In OECD countries, teachers’ salaries for a given qualification level rise during the course of their career, although the rate of
change differs across countries. For lower secondary teachers with the most prevalent qualifications, average statutory
salaries are 28% higher than average starting salaries after 10 years of experience, and 36% higher after 15 years of
experience. Average salaries at the top of the scale (reached after an average of 26 years) are 66% higher than the average
starting salaries. In Greece, Hungary, Israel, Italy, Japan, Korea, the Slovak Republic and Spain, lower secondary school
teachers only reach the top of the salary scale after at least 35 years of service. In contrast, lower secondary teachers in
Australia, New Zealand and Scotland (United Kingdom) reach the highest step on the salary scale after 6-8 years
(Tables D3.5 and D3.10, available on line).
In addition to pay scales, the number of years needed to reach the top of scale is an indication of the speed of career
progression and prospects. In general, the wider the range between minimum and maximum salaries, the more years it takes
for teachers to reach the top of the scale. For example, although it only takes 6-8 years to start earning the maximum salary
in Australia, New Zealand and Scotland (United Kingdom), the top of the scale is only about 33-53% higher than starting
salaries, compared to 66% on average across OECD countries and economies with data on salaries at both points of the
scale. However, this is not true of all countries. For example, while teachers with the most prevalent qualifications in both
the Czech Republic and Israel will reach the top of their scale within approximately 32-36 years, maximum statutory salaries
in the Czech Republic are only 32% higher than starting statutory salaries, compared to 104% higher in Israel (Table D3.10,
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 teachers’ statutory salaries may also translate into different levels of salary per teaching hour. The average statutory salary
per teaching hour for teachers with 15 years of experience and the most prevalent qualifications is USD 59 for primary
teachers, USD 69 for lower secondary teachers and USD 76 for upper secondary teachers in general education (Table D3.10,
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 Chile, the salary per teaching hour for an upper secondary teacher is 3% higher than that

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388  D3. HOW MUCH ARE TEACHERS AND SCHOOL HEADS PAID?
of a primary teacher while in Mexico it is 72% higher. In Costa Rica and Lithuania, the salary per teaching hour is higher at
the primary level (Table D3.10, 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 best-qualified teachers. 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 with smaller differences in salaries among employees may enjoy more trust, freer flows of information and more
collegiality among co-workers.
At the lower secondary level, the average statutory salary of a teacher with the most prevalent qualifications and 15 years of
experience is 38% higher than that of a teacher starting out 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
qualifications (Figure D3.2).

Figure D3.2. Lower secondary teachers’ statutory salaries at different points in teachers’ careers (2019)
Annual statutory salaries of teachers in public institutions, in equivalent USD converted using PPPs

Equivalent USD converted
using PPPs

Starting salary/minimum qualifications
Salary after 15 years of ex perience/most prevalent qualifications
Salary at top of scale/max imum qualifications

160 000
140 000
120 000
100 000
80 000
60 000
40 000

0

Luxembourg
Germany
Switzerland
Denmark
Spain
Australia
Austria
Netherlands
Sweden 1, 2
United States 1
Iceland
Norway
Flemish Comm. (Belgium)3
Finland
Canada
French Comm. (Belgium)
Ireland
EU23 average
Scotland (UK)
OECD average
Portugal
Italy
France4
New Zealand
Korea
England (UK)
Japan
Turkey
Slovenia
Mexico
Lithuania
Estonia
Czech Republic
Chile
Israel
Colombia
Greece
Hungary
Latvia
Slovak Republic
Costa Rica
Brazil

20 000

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 (2020), Table D3.1, Tables D3.6 and D3.16, available on line. See Source section for more information and Annex 3 for notes
(https://doi.org/10.1787/69096873-en).
Statlink2https://doi.org/10.1787/888934165586

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D3. HOW MUCH ARE TEACHERS AND SCHOOL HEADS PAID?  389
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 22-39% higher. These differences may reflect 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 8% and 44% higher than the OECD average, while maximum salaries are lower than the OECD average
(9-26% lower). This results from relatively flat/compressed salary scales in a number of these countries (Tables D3.6 and
D3.16, available on line, and Figure D3.2).
In contrast, for lower secondary teachers, maximum salaries (at the top of the scale, with maximum qualifications) are at least
double the starting salaries (for teachers with minimum qualifications) in Chile, Colombia, Costa Rica, England
(United Kingdom), France, the French Community of Belgium, Hungary, Ireland, Israel, Japan, Korea, Mexico,
the Netherlands and Portugal (Figure D3.2).
The salary premium for teachers with maximum qualifications at the top of the pay scales, and those with the most prevalent
qualifications and 15 years of experience, also varies across countries. At lower secondary level, the pay gap is less than
10% in seven OECD countries and economies, while it exceeds 60% in Chile, Colombia, France, Hungary, Israel, Mexico
and Portugal (Table D3.16, 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, as noted above, the minimum qualifications
are the most prevalent in the majority of countries. Additionally, 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 X2.11, available on line).

Salary trends since 2000
Teachers’ salaries increased overall in real terms in most countries for which data are available between 2000 and 2019.
Around two-thirds of countries show an increase over this period and one-third show a decrease. However, only two in five
OECD countries have the relevant data available (the statutory salaries of teachers with the most prevalent qualifications and
15 years of experience) for the whole of this period with no break in the time series.
The biggest reductions in salaries in real terms between 2000 and 2019 were in France, where salaries fell by up to 10% (at
secondary levels), and Greece, where salaries fell by 20%. There were also smaller declines in teachers’ salaries in real
terms in England (United Kingdom) (2%), and Italy (less than 1%). Salaries increased by more than 30% for primary and
secondary teachers in Ireland and Israel. However, in some countries, an overall increase in teachers’ salaries between 2000
and 2019 includes periods when salaries fell in real terms, particularly from 2010 to 2013 (Table D3.14, available on line).
Over the period 2005 to 2019, 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 the most prevalent qualifications. On average across OECD countries and economies with available data for
the reference years of 2005 and 2019, statutory salaries increased by 7% at primary level, 7% at lower secondary level and
5% at upper secondary level. The increase exceeded 20% in Poland at pre-primary, primary and secondary levels (the result
of a 2007 government programme that aimed to increase teachers’ salaries successively between 2008 and 2013, and also
since 2017, and to improve the quality of education by providing financial incentives to attract high-quality teachers) and also
in Iceland (pre-primary), Israel, and Sweden (Table D3.14, available on line).
In most countries, the salary increases were similar across primary, lower secondary and upper secondary levels between
2005 and 2019. However, this is not the case in Israel, where salaries increased by more than 50% at pre-primary level, 31%
at primary level, 43% at lower secondary level and 44% at upper secondary level. This is largely the result of the gradual
implementation of the “New Horizon” reform in primary and lower secondary schools, which began in 2008 following an
agreement between the education authorities and the Israeli Teachers Union (for primary and lower secondary education).
This reform included raising teachers’ pay in exchange for longer working hours (see Indicator D4).
In contrast, salaries have decreased slightly since 2005 in a few countries and economies including Denmark (pre-primary),
France, Hungary (upper secondary), Italy, Portugal, Scotland (United Kingdom), Spain and the United States (primary). They
decreased by 8% in Japan, and by more than 29% in Greece as the result of reductions in remuneration, the implementation
of new wage grids and salary freezes since 2011 (Table D3.14, available on line).

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390  D3. HOW MUCH ARE TEACHERS AND SCHOOL HEADS PAID?
However, these overall changes in teachers’ salaries in OECD countries between 2005 and 2019 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. Statutory salaries for primary, lower and upper secondary teachers with 15 years of
experience and minimum qualifications now exceed pre-crisis levels, on average across OECD countries with data for all
reference years (Figure D3.3).

Figure D3.3. Change in teachers’ salaries in OECD countries (2005 to 2019)
Average index of change, among OECD countries with data on statutory salaries for all reference years, for teachers with
15 years of experience and minimum qualifications (2005 = 100, constant prices)
Primary
Lower secondary, general programmes
Upper secondar y, general programmes

Index of change
(2005 = 100)
110
108
106
104
102
100
98
96
94
92
90
2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

2018

2019

Source: OECD (2020), Table D3.14, available on line. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2https://doi.org/10.1787/888934165605

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 (see Indicator D4 for more details).
Differences in the nature of the work carried out and the hours worked by school heads (compared to teachers) are reflected
in the systems of compensation used within countries (see Tables D4.2 and D4.5 for the working time of teachers and school
heads). School heads may be paid according to a specific salary range and may or may not receive a school-head allowance
on top of their statutory salaries. 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 and economies with available information, and according
to a specific salary range in the other 20 countries and economies. Of these, 13 countries and economies have no specific
school-head allowance and 7 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, or the number of teachers

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D3. HOW MUCH ARE TEACHERS AND SCHOOL HEADS PAID?  391
supervised). 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 D3.21, available on line).
Considering the large number of criteria involved in the calculation of school heads’ statutory salaries, the statutory salary
data for school heads focuses on the minimum qualification requirements to become a school head, and Table D3.4 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 for school heads is USD 52 077 on average across OECD countries and
economies, ranging from USD 20 124 in Latvia to USD 110 128 in Luxembourg. The maximum salary is USD 86 974 on
average across OECD countries and economies, ranging from USD 32 337 in Poland to USD 152 305 in Luxembourg. These
values should be interpreted with caution, as minimum and maximum statutory salaries refer to school heads in different types
of schools. About half of OECD countries and economies have similar pay ranges for primary and lower secondary school
heads, while upper secondary school heads benefit from higher statutory salaries on average.

Figure D3.4. Minimum and maximum statutory salaries for lower secondary teachers and school heads (2019)
Based on teachers with most prevalent qualifications at a given level of education and school heads with minimum
qualifications
Salary range of teachers (most prevalent qualification)
School head – minimum
School head – max imum

Equivalent USD converted
using PPPs
160 000
140 000
120 000
100 000
80 000
60 000
40 000

Poland

Czech Republic

Turkey

Slovak Republic

Greece

Lithuania

Japan

Hungary

Slovenia

Denmark

Finland

Sweden 1

Colombia

Costa Rica

French Comm. (Belgium)

Israel

France

EU23 average

Portugal

Flemish Comm. (Belgium)

Spain

OECD average

Italy

Chile

Austria

Korea

Iceland

New Zealand

United States 1

Ireland

Scotland (UK)

Australia

Netherlands

Mexico

Luxembourg

0

England (UK)

20 000

1. Actual base salaries.
Countries and economies are ranked in descending order of maximum salaries of school heads.
Source: OECD (2020), Table D3.4 and Table D3.5 available on line. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2https://doi.org/10.1787/888934165624

On average across OECD countries and economies, the maximum statutory salary of a school head with minimum
qualifications is 66% higher than the minimum statutory salary at primary level, 67% higher than the minimum in lower
secondary and 63% higher in upper secondary. There are only 12 countries or economies where school heads at 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.
The minimum statutory salaries for school heads with minimum qualifications are higher than the starting salaries of teachers,
except in Costa Rica. The difference between minimum salaries for school heads (with minimum qualifications) and starting

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392  D3. HOW MUCH ARE TEACHERS AND SCHOOL HEADS PAID?
salaries for teachers with the most prevalent qualifications increases with level of education: they are 28% higher on average
across OECD countries and economies at pre-primary level, 40% at primary level, 48% at lower secondary level and 47% at
upper secondary level. In a number of countries, the minimum statutory salary for school heads is higher even than the
maximum salary for teachers. This is the case at lower secondary level in Australia, Denmark, England (United Kingdom),
Finland, Iceland, Israel, Italy, Japan, Mexico, New Zealand, Scotland (United Kingdom), Slovenia, Sweden, Turkey and
the United States (Figure D3.4).
Similarly, the maximum statutory salaries for school heads are higher than the maximum salaries for teachers for all OECD
countries and economies with available data. At lower secondary level, the maximum statutory salary of a school head is 49%
higher than the salary of teachers at the top of the scale (with most prevalent qualifications), on average across OECD
countries and economies. The maximum statutory salaries of school heads in Chile, England (United Kingdom), Iceland,
Mexico, New Zealand and Scotland (United Kingdom) are more than twice statutory teachers’ salaries at the top of the scale
(Figure D3.4).

Average actual 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. Actual average salaries are
influenced by the prevalence of bonuses and allowances in the compensation system. 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 their salary levels.

Figure D3.5. Actual salaries of lower secondary teachers and school heads (2019)
Annual actual salaries of teachers and school heads in public institutions, in equivalent USD converted using PPPs
Equivalent USD converted
using PPPs

Actual salaries of school heads

Actual salaries of teachers

140 000
120 000
100 000
80 000
60 000
40 000

Latvia

Estonia1

Greece

Poland1

Czech Republic 1

Chile1

Slovenia1

Portugal 1

Costa Rica

Sweden 1

Iceland

Norway

Israel

France1

EU23 average

OECD average

New Zealand 1

Finland

French Comm. (Belgium)

Flemish Comm. (Belgium)

Denmark

Austria

United States

Netherlands

Ireland

Italy

England (UK)

0

Australia

20 000

1. Year of reference differs from 2019. See Table D3.3 for more information.
Countries and economies are ranked in descending order of actual salaries of school heads.
Source: OECD (2020), Table D3.3. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2https://doi.org/10.1787/888934165643

Across OECD countries and economies, in 2019 the average actual salaries of teachers aged 25-64 were USD 38 677 at
pre-primary level, USD 43 942 at primary level, USD 46 225 at lower secondary level and USD 49 778 at upper secondary
level. Average actual salaries for school heads aged 25-64 ranged from USD 67 365 at primary level to USD 73 404 at lower
secondary level and USD 79 531 at upper secondary level (Table D3.3, see Box D3.1 for variations at subnational level).
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D3. HOW MUCH ARE TEACHERS AND SCHOOL HEADS PAID?  393
There are 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 seven of these countries and economies at
pre-primary level and 11 of these countries and economies at upper secondary level (Table D3.3).
The 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, school heads’ actual salaries in 2019 were 53% higher than those of teachers
at primary level. The premium is 59% at lower secondary level and 60% at upper secondary level. The difference between the
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 over teachers are England (United Kingdom) (secondary levels) and
Italy (primary and secondary levels), where school heads’ actual salaries are more than twice those of teachers. The lowest
premiums, of less than 25%, are in Estonia (at primary and secondary) and Latvia (lower secondary). 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 school heads’ actual salaries are 29% higher than teachers’ at pre-primary level but the
difference is 42% at lower secondary and 60% at upper secondary level. In Costa Rica, Latvia and Slovenia, the difference is
much larger at pre-primary level than at primary and lower secondary levels (Table D3.3).

Box D3.1. Subnational variations in teachers' and school heads’ salaries at pre-primary, primary and
secondary levels
In each country, teachers’ statutory salaries can vary according to the level of education and their level of experience.
Salaries can also vary significantly across 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 2019 in Belgium, for example, the starting salary of a primary school teacher
varied by only 3% (USD 1 256), from USD 37 630 in the French Community to USD 38 885 in the Flemish Community. In
comparison, subnational variation was largest in the United States, where the starting salary of a primary school teacher
varied by 81% (USD 27 016) across subnational entities, ranging from USD 33 445 in Oklahoma to USD 60 461 in
New York. Starting salaries for lower secondary and upper secondary teachers varied the least in Belgium (by 3-4%, and
the most in Canada (by 77%).
In Belgium, the variation in statutory salaries between subnational entities remains relatively consistent across all levels
of education and stages of teachers’ careers. In contrast, in both Canada and the United Kingdom, the variation across
subnational entities is similar at different levels of education, but 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 22% (USD 6 433)
between subnational entities (from USD 29 488 to USD 35 921), while salaries at the top of the salary scale varied by only
8% (USD 3 759, from USD 47 761 to USD 51 520). 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 34 789 to USD 58 203
(a difference of 67%, or USD 23 414) and the largest for salaries at top of the salary scale, ranging from USD 43 654 to
USD 109 709 (a difference of 151%, or USD 66 055).
There are also large subnational variations in actual salaries of teachers and school heads across the three countries
(Belgium, the United Kingdom and the United States) with available data in 2019. In the United Kingdom, the subnational
variation in actual salaries was greater for school heads than for teachers. For example, at the upper secondary level,
teachers’ salaries in the United Kingdom (for the two subnational entities with available data) ranged from USD 49 312 in
England to USD 51 569 in Northern Ireland, a difference of 5% or USD 2 257 In comparison, school heads’ salaries ranged
from USD 91 873 in Northern Ireland to USD 116 592 in England, a difference of 27% or USD 24 720. Subnational
variation in actual salaries was much smaller for both teachers and school heads in Belgium. For example, the salaries of
upper secondary school heads ranged from USD 94 331 in the French Community to USD 101 480 in the Flemish
Community, a difference of 8% or USD 7 149. In the United States, subnational variation in actual salaries are similar for
both teachers and school heads, but much larger than in Belgium. For example, the salaries of upper secondary school
heads ranged from USD 75 354 in South Dakota to USD 145 482 in New Jersey, a difference of 93% or USD 70 128.

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394  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. In the United Kingdom (for subnational entities with available data) the subnational variation in teachers’
salaries is largest at the pre-primary and primary levels, while subnational variation in school heads’ salaries is largest at
lower and upper secondary levels. In the United States, subnational variation in the actual salaries of teachers and school
heads was greater at the primary level than at lower and upper secondary levels.
Source: Education at a Glance Database, http://stats.oecd.org.

Box D3.2. Teachers’ salaries in vocational programmes
In this indicator, the information on the salaries of secondary teachers relates to those in general programmes. However,
a specific survey carried out by the OECD in 2019 collected data on the salaries of teachers in vocational programmes.
Vocational programmes are much more common at upper secondary level than at lower secondary. Among the
29 countries and economies that participated in the survey, 28 have vocational programmes at upper secondary level,
compared with only 10 at the lower secondary level, Hence, the following analysis focuses on teachers in upper secondary
vocational programmes.

Figure D3.6. Comparison of the statutory salaries of upper secondary teachers in general and
vocational programmes (2019)
Salaries of teachers with 15 years of experience and the minimum qualification, in equivalent USD converted using PPPs
Teachers in general programmes
All teachers in vocational programmes
Teachers of general subjects in vocational programmes
Teachers of vocational theory
Teachers of vocational practice

Equivalent USD converted
using PPPs
90 000
80 000
70 000
60 000
50 000
40 000
30 000
20 000

Costa Rica 1

Slovak Republic

Poland

Turkey 1

Chile2

Israel

Colombia2

France

Slovenia

Portugal 2

Norway

Iceland

Finland

Korea

Spain1

Mexico

French Comm. (Belgium)

Austria

0

Germany

10 000

1. All teachers of vocational theory and practice are included in the category “teachers of vocational theory”.
2. Year of reference is 2018
Countries and economies are ranked in descending order of salaries of upper secondary teachers in general programmes.
Source: OECD (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2https://doi.org/10.1787/888934165662

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D3. HOW MUCH ARE TEACHERS AND SCHOOL HEADS PAID?  395

In many countries with available information, different types of teachers within vocational programmes can be
distinguished based on the types of subjects they teach: teachers of general subjects, vocational theory and vocational
practice may require different qualifications and/or have different working conditions. In several countries, however, it is
not possible to distinguish between teachers of vocational theory and teachers of vocational practice. In 21 of the
countries and economies that responded to the survey, teachers of general subjects can teach in both general and
vocational programmes without changes to their terms and conditions. However, only 11 countries allow teachers of
vocational practice and/or vocational theory to teach in general programmes.
Differences in categories of teachers within vocational programmes are associated with substantial variations between
countries in the extent of the differences in the pay and conditions of teachers in general and vocational programmes.
For instance, in seven countries the qualification requirements are the same for all teachers, whatever the orientation of
the programmes they teach. Meanwhile in four countries, teachers in vocational programmes have different qualification
requirements from teachers in general programmes. In the remaining 17 countries and economies, some of the teachers
in vocational programmes have the same qualification requirements and others do not.
Similar variations exist between teachers in general and vocational programmes for working time, teaching time and
salaries. It is possible to quantify the extent of the differences in salaries from the data provided in the survey. Figure D3.6
shows the statutory salaries of upper secondary teachers with 15 years of experience by programme orientation. For
these 19 OECD countries and economies, statutory salaries of teachers in vocational programmes are similar to those in
general programmes. However, it cannot be assumed that this finding applies more generally to all OECD countries
because the countries with available data in this survey may be those where the remuneration regimes are the same for
both types of programmes and therefore they may find it easier to provide data on a consistent basis.
Data on the actual salaries paid to teachers tell a similar story. Among the countries with available actual salaries by
orientation of programmes, the actual salaries of teachers in vocational programmes are similar to those of teachers in
general programmes but tend to be slightly lower. For example, the average pay of teachers aged 25-64 in vocational
programmes is slightly lower than their peers in general programmes in Sweden (1%), Norway (2%) and France (6%).
Meanwhile the actual salaries of teachers in vocational and general programmes are equal in Iceland, Israel and Portugal.
Where there are lower actual salaries, this may reflect differences in the distribution of teachers by age, level of
qualification and experience as well as differences in the allowances available and tasks undertaken.
Source: INES VET Survey 2019

Teachers’ and school heads’ actual salaries relative to earnings of 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[3]). Teachers’ salaries relative to other occupations with similar education requirements, and their likely growth
in earnings may have a huge influence on a graduate’s decision to become a teacher and stay in the profession (see Box D3.3
for information on satisfaction of teachers with their pay). 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.
In most OECD countries and economies, a tertiary degree is required to become a teacher and then a school head, at all levels
of education, meaning that 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 of teachers are compared to
the earnings of other tertiary-educated professionals: 25-64 year-old full-time, full-year workers with a similar tertiary education
(ISCED levels 5 to 8). Moreover, to ensure that comparisons between countries are not biased by differences in the distribution
of tertiary attainment level among teachers and tertiary-educated workers more generally, teachers’ actual salaries are also
compared to a weighted average of earnings of similarly educated workers (the earnings of similarly educated workers are
weighted by the proportion of teachers with similar tertiary attainment – see Tables X2.9 and X2.10 in Annex 2 for the proportion
of teachers and school heads by attainment level; and the Methodology section for more details).
Among the 22 countries and economies with available data (for at least one level), teachers’ actual salaries amount to 65%
or less of the earnings of similarly educated workers in Chile (pre-primary, primary and lower secondary) the Czech Republic
(primary and lower secondary), Hungary (upper secondary), Poland (pre-primary) and the United States. Very few countries

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396  D3. HOW MUCH ARE TEACHERS AND SCHOOL HEADS PAID?
and economies have teachers’ actual salaries that reach or exceed those of similarly educated workers. However, in
Germany, the actual salaries of upper secondary teachers are the same as those of similarly educated workers (Table D3.2).
Considering how few countries have 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). Against this benchmark, actual teachers’ salaries relative to other tertiary-educated workers increase with higher
education levels. On average, pre-primary teachers’ salaries amount to 80% of the full-time, full-year earnings of tertiaryeducated 25-64 year-olds. Primary teachers earn 85% of this benchmark salary, lower secondary teachers 89% and upper
secondary teachers 94% (Table D3.2).
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 lowest relative salaries are at pre-primary level: in the Czech Republic
pre-primary teachers’ salaries are 55% of those of tertiary-educated workers, in the Slovak Republic they are 58%, and in
the United States they are 61%. However in some countries, teachers earn more than tertiary-educated adults, either at all
levels of education (Costa Rica, Lithuania and Portugal), or only at some levels (at upper secondary level in Finland, France
and the French Community of Belgium, at lower and upper secondary levels in Germany). In Lithuania and Portugal, teachers
earn at least 30% more than tertiary-educated workers (Table D3.2 and Figure D3.1).

Box D3.3. Comparability issues related to relative 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 teacher compensation
systems, adhering to these guidelines and methodology is not always straightforward. Some caution is therefore required
when interpreting these data.
The relative salaries measure divides the salaries of teachers or school heads (numerator) by the earnings of comparable
workers (denominator). Two different versions of the measure are presented in Table D3.2. The first simply divides
teachers’ or school heads’ salaries by the earnings of tertiary-educated workers; the second weights the earnings of
workers so that they reflect the distribution of educational attainment among teachers or school heads. This avoids
potential comparability issues related to different distributions of attainment among teachers or school heads compared
with tertiary-educated workers.
Both versions of the relative salaries measure are still subject to biases due to differences in the characteristics, working
patterns and remuneration systems of teachers and other workers. Five potential sources of bias in the comparison of
teachers' salaries to tertiary-educated workers are described below.

Part-time working
The relative measures of salaries are based on the salaries of full-time teachers and the earnings of full-time workers.
However, a share of teachers, and workers more generally, work on a part-time basis during the year. Differences in the
frequency of part-time working between teachers and workers could introduce a bias into the measure of relative salaries
as it will impact in a different way on the average salaries of teachers and the average earnings of tertiary-educated
workers. It is worth noting that part-time work might be more common in education than in the rest of the labour market
not least because women make up a large proportion of teachers in most OECD countries and they are more likely to
work part time.
The wage penalty associated with part-time work is a well-established phenomenon and is often one of the reasons for
women’s lower salaries (Matteazzi, Pailhé and Solaz, 2017[4]). However, it might be limited or even non-existent in
education in some countries. For example, this is the case in the Netherlands in primary education and, to a lesser extent,
in secondary education. Hourly salaries are identical for part-time and full-time teachers, due to the collective labour
agreements in those sectors. This is not only true for the statutory salaries (based on collective labour agreements), but
also for the actual salaries.

Part-year working
Not only is the measure of relative salaries of teachers based on a comparison with full-time workers, but also with fullyear workers. This measure aims to compare full-time, full-year teachers to full-time, full-year tertiary-educated workers.

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D3. HOW MUCH ARE TEACHERS AND SCHOOL HEADS PAID?  397
However, there may be a bias in the comparison due to the fact that a proportion of teachers in a few countries (such as
the United States) are paid for a contract that spans less than a 12-month year, reflecting only the months of the school
year. Therefore, teachers’ salaries may not be a true reflection of teachers’ earnings over a full year. In some countries,
teachers may have other earnings from non-teaching jobs that are excluded from the calculation. The potential
underestimation of teachers’ earnings over the year may bias the comparison with earnings of tertiary-educated workers.

Including teachers in the earnings of tertiary-educated workers
The earnings of tertiary-educated workers also include the earnings of teachers. The relative size of the teaching workforce
in the labour market as a whole, as well as the level of teachers’ earnings compared to those of other tertiary-educated
workers, has an impact on the level of earnings of tertiary-educated workers used to compute relative salaries. As a
consequence, this also affects the measure of relative salaries of teachers.

Different sources of data for teachers’ salaries and workers’ earnings
The sources of data used to report teachers’ salaries and the earnings of workers may differ, at least partly. This may
result in differences in the type of data and the methodology used to report them: statutory and actual salaries for teachers,
compared with actual earnings for workers. For example, in several countries including the Netherlands and the United
States, the earnings data are at least partially based on the Labour Force Survey (LFS) of that country. However, the
teachers’ salary data often comes from regulations, collective agreements, administrative sources or sample surveys.

Differences in pensions systems between teachers and other workers
In many countries, teachers in public institutions have substantial pension contributions paid by their employer, but a
relatively low salary compared to the private sector. In contrast, private sector employees may get higher salaries, but
they may also have to make their own pension arrangements. Differences in pensions systems between the public and
private sector, and between countries, may affect the comparability of salary and earnings data, and therefore the
comparability of the measure of relative salaries of teachers.
Pensions are only taken into account in data on salaries of teachers through the social contributions that are
included/excluded from the amounts reported. Some countries may report data on salaries in a different way due to data
limitations.
For more information on comparability issues, see Box D3.1 of Education at a Glance 2019 (OECD, 2019[2]) and the notes
for specific countries in Annex 3.
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 18 OECD countries
and economies with available data (for at least one level), it is only school heads in the United States and pre-primary school
heads in Denmark, Estonia, Finland and Poland 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
England (United Kingdom), the Flemish Community of Belgium (pre-primary, primary and lower secondary) and New Zealand
(primary and secondary) (Table D3.2).
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 26%
more than tertiary-educated adults at primary level, 38% more at lower secondary level and 46% more at upper secondary
level. School heads earn less than tertiary‑educated adults only in the Czech Republic (pre-primary), Denmark (pre-primary),
Estonia (pre-primary), Finland (pre-primary), Norway (pre‑primary), and Poland (pre-primary) (Table D3.2).

Box D3.4. Teachers’ satisfaction with their pay
The OECD Teaching and Learning International Survey (TALIS) asks teachers and school leaders about their working
conditions and the learning environment in their schools. It includes questions on the reasons teachers had for joining the
profession.

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398  D3. HOW MUCH ARE TEACHERS AND SCHOOL HEADS PAID?
A large proportion of lower secondary teachers in the OECD countries which took part in the 2018 round of TALIS cited
the opportunity to influence the development of children and young people (92%) and the opportunity to provide a
contribution to society (88%) as important reasons for deciding to become a teacher.
Working conditions and salaries can also be part of the reasons for joining the teaching profession. Among the OECD
countries taking part in the survey, two-thirds of lower secondary teachers said that the fact that teaching provides a
reliable income was an important factor for them in becoming a teacher. However, the satisfaction they now express with
their pay varies widely across countries. Fewer than 10% of lower secondary teachers in publicly managed schools in
Iceland and Portugal say that they are satisfied with the salary they receive for their work. This compares to over 70% in
Alberta (Canada), Austria, the Flemish Community of Belgium, Chinese Taipei, Denmark, and Singapore.

Figure D3.7. Lower secondary teachers’ actual salaries and satisfaction with their salaries (2018)
Annual actual salaries of teachers in public institutions (in equivalent USD converted using PPPs) compared to
percentage of teachers in publicly managed schools who are satisfied with the salary they receive for their work

OECD average

Percentage of teachers
who are satisfied with the salary
they receive for their work
80
70
60

Flemish Comm.
(Belgium)

Denmark

Austria

Australia1
England (UK)
French Comm. (Belgium)

50

Norway

Chile

Finland

Estonia

40

United States
New Zealand
Sweden

Slovenia

30

Hungary

Czech Republic

OECD aver age

France1

Latvia
20

Slovak Republic
Lithuania

10

Italy
Brazil1
Portugal
Iceland

0
0

10 000

20 000

30 000

40 000

50 000

60 000
70 000
80 000
Actual salaries of teachers in equivalent USD
converted using PPPs

1. Year of reference for actual salaries is 2017.
Source: OECD (2020), Table X2.5 and TALIS 2018 Volume 2 Table 3.57. See Source section for more information and Annex 3 for notes
(https://doi.org/10.1787/69096873-en).
Statlink2https://doi.org/10.1787/888934165681

Satisfaction with pay is lower for more experienced teachers. Those with more than five years of experience tend to be
less satisfied with their pay than those with fewer than five years of experience. Among the OECD countries that took part
in TALIS, more experienced teachers were less satisfied with their pay then their less experienced colleagues in
13 countries. The opposite was true in only 4 countries while the remaining 12 showed no significant difference.
There is some evidence that male teachers tend to be less satisfied with their salaries than female teachers. On average
among the OECD members that took part in TALIS, 2.5% fewer male teachers were satisfied with their pay than female
teachers were but only six countries show significantly lower satisfaction for male teachers. There is no significant
difference in most countries.

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D3. HOW MUCH ARE TEACHERS AND SCHOOL HEADS PAID?  399
It may be presumed that teachers’ satisfaction with their pay is related to the earnings of tertiary workers in their country
but there is no evidence of this relationship at the aggregate national level. There is no correlation between the salaries
of teachers relative to the earnings of tertiary-educated workers and teachers’ satisfaction with their pay.
However, there is a relationship between absolute levels of pay and the satisfaction teachers express. Figure D3.7 shows
this relationship, there is a correlation between the actual salaries teachers receive (converted into USD using PPPs) and
the percentage of teachers who agree that they are satisfied with the salary they receive for their work (r 2=0.49). Countries
with higher rates of pay have more teachers who are satisfied with their pay.
Source: TALIS 2018 Results (Volume II) - Teachers and School Leaders as Valued Professionals (OECD, 2020[5])

Formation of base salary and additional payments: Incentives and allowances
Statutory salaries, based on pay scales, are only one component of the total compensation of teachers and school heads.
School systems also offer additional payments to teachers and school heads, such as allowances, bonuses or other rewards.
These may take the form of financial remuneration and/or 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 D3.19 and D3.20,
available on line).
Criteria for additional payments vary across countries. In the large majority of countries and economies, 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 compensated through specific bonuses or additional payments
(Table D3.17, available on line). Teachers may also be required to have some responsibilities or perform some tasks without
additional compensation (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 three-fifths 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 D3.17, 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 to 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 D3.17, 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: Australia, Austria, the French Community of Belgium and Portugal (Table D3.18, available on line).
Among the 31 countries and economies with available data, around one-quarter provide additional compensation to school
heads for participating in management tasks over and above their usual responsibilities as school heads or for working
overtime. About half of the countries and economies (Australia, Austria, Chile, England [United Kingdom], Finland, France,
the French Community of Belgium, 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 (Tables D3.17 and D3.18, available on line). The extent to which teachers receive additional compensation for taking
on extra responsibilities and the activities for which teachers are compensated vary 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 school
heads’ duties and so they are not compensated with any extra allowances.
At lower secondary level, school heads are awarded additional compensation for outstanding performance in more than onethird of the countries and economies with available data, just as teachers are. However, Austria, Chile, England
(United Kingdom), Israel, Portugal and Turkey award teachers additional compensation for outstanding performance, but not
school heads. The opposite is observed in Colombia, France and Spain, where school heads are rewarded for high

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400  D3. HOW MUCH ARE TEACHERS AND SCHOOL HEADS PAID?
performance, but not teachers. In France, part of the school-head allowance is awarded according to the results of a
professional interview and is paid every three years (Tables D3.17 and D3.18, 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 and economies, with the exception of Australia, where such incentives are only provided to
teachers (Tables D3.17 and D3.18, available on line).

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 full-time
teachers/school heads aged 25 to 64, before taxes. It is the gross salary from the employee’s point of view, since it includes
the part of social security contributions and pension-scheme contributions that are paid by the employees (even if deducted
automatically from the employees’ gross salary by the employer). However, the employers’ premium for social security and
pension is excluded. Actual salaries also include work-related payments, such as school-head allowance, annual bonuses,
results-related bonuses, extra pay for holidays and sick-leave pay. Income from other sources, such as government social
transfers, investment income and any other income that is not directly related to their profession are not included.
Earnings for workers with tertiary education are average earnings for full-time, full-year workers aged 25-64 with an
education at ISCED level 5, 6, 7 or 8.
Salary at the top of the scale refers to the maximum scheduled annual salary (top of the salary range) for a full-time
classroom teacher (for a given level of qualification of teachers recognised by the compensation system).
Salary after 15 years of experience refers to the scheduled annual salary of a full-time classroom teacher. Statutory salaries
may refer to the salaries of teachers with a given level of qualification recognised by the compensation 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’ salaries 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 2018 to 30 June 2019. The reference date for PPPs is
2018/19, 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. 2019). Tables with salaries in
national currency are included in Annex 2. To calculate changes in teachers’ salaries (Table D3.14 and Table D3.15, 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).

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D3. HOW MUCH ARE TEACHERS AND SCHOOL HEADS PAID?  401
In Table D3.2, 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 2 to 5 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 X2.9 and X2.10 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 2019
reference year used for salaries of teachers or school heads, a deflator has been used to adjust earnings data to 2019). For
all other ratios in Table D3.2 and those in Table D3.8 (available on line), information on all tertiary-educated workers was
used instead of weighted averages. Data on the 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 D3.7 (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[6]) and Annex 3 for country-specific notes (https://doi.org/10.1787/69096873-en).

Source
Data on salaries and bonuses for teachers and school heads are derived from the 2019 joint OECD/Eurydice data collection
on salaries of teachers and school heads. Data refer to the school year 2018/19 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.

References

Johnes, G. and J. Johnes (2004), International Handbook on the Economics of Education, Edward Elgar,
Cheltenham, UK; Northampton, MA.

[3]

Matteazzi, E., A. Pailhé and A. Solaz (2017), “Part-time employment, the gender wage gap and the role of wagesetting institutions: Evidence from 11 European countries”, European Journal of Industrial Relations, Vol. 24/3,
pp. 221-241, http://dx.doi.org/10.1177/0959680117738857.

[4]

OECD (2020), TALIS 2018 Results (Volume II): Teachers and School Leaders as Valued Professionals, TALIS,
OECD Publishing, Paris, https://dx.doi.org/10.1787/19cf08df-en.

[5]

OECD (2019), Education at a Glance 2019: OECD Indicators, OECD Publishing, Paris,
https://dx.doi.org/10.1787/f8d7880d-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 (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]

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402  D3. HOW MUCH ARE TEACHERS AND SCHOOL HEADS PAID?

Indicator D3 Tables
Table D3.1. Teachers' statutory salaries, based on the most prevalent qualifications at different points in teachers' careers
(2019)
Table D3.2. Teachers’ and school heads’ actual salaries relative to earnings of tertiary-educated workers (2019)
Table D3.3. Teachers’ and school heads’ average actual salaries (2019)
Table D3.4. School heads’ minimum and maximum statutory salaries, based on minimum qualifications (2019)
WEB Table D3.5 Teachers' statutory salaries, based on the most prevalent qualification at a given level of education (2019)
WEB Table D3.6 Teachers' statutory salaries, based on the minimum qualifications to enter the teaching profession (2019)
WEB Table D3.7. Teachers’ and school heads’ statutory salaries relative to earnings of tertiary-educated workers (2019)
WEB Table D3.8. Teachers’ actual salaries relative to earnings of tertiary-educated workers, by age group and gender (2019)
WEB Table D3.9. School heads’ actual salaries relative to earnings of tertiary-educated workers, by age group and gender
(2019)
WEB Table D3.10. Comparison of teachers' statutory salaries, based on the most prevalent qualification of teachers at a
given level of education, by level of education (2019)
WEB Table D3.11. Comparison of teachers' statutory salaries, based on the minimum qualifications required to enter the
teaching profession in the reference year (2019)
WEB Table D3.12. Teachers’ average actual salaries, by age group and gender (2019)
WEB Table D3.13. School heads’ average actual salaries, by age group and gender (2019)
WEB Table D3.14. Trends in teachers’ statutory salaries, based on most prevalent qualifications at different points in teachers'
careers (2000 and 2019)
WEB Table D3.15. Trends in teachers’ statutory salaries, based on minimum qualifications to enter the teaching profession
(2000 and 2019)
WEB Table D3.16. Teachers’ starting and maximum statutory salaries, based on minimum/maximum qualifications (2019)
WEB Table D3.17. Criteria used for base salaries and additional payments awarded to teachers in public institutions, by level
of education (2019)
WEB Table D3.18. Criteria used for base salaries and additional payments awarded to school heads in public institutions, by
level of education (2019)
WEB Table D3.19. Decision-making level for criteria used for determining teachers' base salaries and additional payments,
by level of education (2019)
WEB Table D3.20. Decision-making level for criteria used for determining school heads' base salaries and additional
payments, by level of education (2019)
WEB Table D3.21. Structure of compensation system for school heads (2019)
Cut-off date for the data: 19 July 2020. Any updates on data can be found on line at http://dx.doi.org/10.1787/eag-dataen. More breakdowns can also be found at http://stats.oecd.org/, Education at a Glance Database.
StatLink: https://doi.org/10.1787/888934165472

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D3. HOW MUCH ARE TEACHERS AND SCHOOL HEADS PAID?  403

Table D3.1. Teachers' statutory salaries, based on the most prevalent qualifications at different points in teachers' careers (2019)
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 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. 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. 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 (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2https://doi.org/10.1787/888934165491

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404  D3. HOW MUCH ARE TEACHERS AND SCHOOL HEADS PAID?
Table D3.2. Teachers’ and school heads’ actual salaries relative to earnings of tertiary-educated workers (2019)
Ratio of salary, using annual average salaries (including bonuses and allowances) of full-time teachers and school heads in public
institutions relative to the earnings of workers with similar educational attainment (weighted average) and to the earnings of full-time,
full-year workers with tertiary education

Note: Where the year of reference for the earnings of tertiary-educated workers and the salaries of teachers differ, the earnings of tertiary-educated workers have been
adjusted to the reference year used for salaries of teachers using deflators for private final consumption expenditure. See Definitions and Methodology sections for more
information. Data available at http://stats.oecd.org/, Education at a Glance Database.
1. Year of reference is 2018 for salaries of teachers and school heads.
2. Year of reference is 2017 for salaries of teachers and school heads.
3. At pre-primary and primary levels, actual salaries refer to all teachers/school heads in those levels of education combined including special needs education. At lower
and upper secondary levels, actual salaries refer to all teachers/school heads in those levels of education combined including vocational and special needs education.
Source: OECD (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2https://doi.org/10.1787/888934165510
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D3. HOW MUCH ARE TEACHERS AND SCHOOL HEADS PAID?  405

Table D3.3. Teachers’ and school heads’ average actual salaries (2019)
Annual average salaries (including bonuses and allowances) of teachers and school heads in public institutions, in equivalent USD
converted using PPPs for private consumption, by age group and gender

Note: Where the year of reference for the earnings of tertiary-educated workers and the salaries of teacher differ the earnings of tertiary-educated workers have been
adjusted using deflators for private final consumption expenditure. See Definitions and Methodology sections for more information. Data available at http://stats.oecd.org/,
Education at a Glance Database.
1. Includes teachers working in vocational programmes at the upper secondary level (in Sweden, includes only those teachers teaching general subjects within vocational
programmes).
2. Year of reference 2018.
3. Includes data on the majority, i.e. kindergarten teachers only for pre-primary education.
4. Year of reference 2017.
5. At pre-primary and primary levels actual salaries refer to all teachers/school heads in those levels of education combined including special needs education. At lower and
upper secondary levels, actual salaries refer to all teachers/school heads in those levels of education combined including vocational and special needs education.
6. Includes unqualified teachers.
7. Includes salaries of school heads and teachers.
Source: OECD (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2https://doi.org/10.1787/888934165529
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406  D3. HOW MUCH ARE TEACHERS AND SCHOOL HEADS PAID?
Table D3.4. School heads’ minimum and maximum school heads' statutory salaries, based on minimum qualifications (2019)
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. 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. For 2018/2019, methodology has been revised, The new data apply to school heads (ISCED 02 and 1) in charge of schools with 10 classes or more, i.e. with teaching
responsibilities accounting for 50 per cent or less of their working time, in line with the international guidelines.
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).
5. Excludes countries for which either the starting salary (with minimum qualifications) or the salary at top of scale (with maximum qualifications) is not available.
Source: OECD (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2https://doi.org/10.1787/888934165548

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408  D4. HOW MUCH TIME DO TEACHERS AND SCHOOL HEADS SPEND TEACHING AND WORKING?

Indicator D4. How much time do teachers and
school heads spend teaching and working?
Highlights


According to official regulations or agreements, teachers in public schools in OECD countries and economies are
required to teach on average 993 hours per year at pre-primary level, 778 hours at primary level, 712 hours at
lower secondary level (general programmes) and 680 hours at upper secondary level (general programmes).



Annual teaching hours are similar in general and vocational programmes in most countries. However, at the upper
secondary level, there are five countries where teaching time in vocational programmes is 10 to 30% higher than
in general programmes, while in Mexico, it is about 20% lower.



Most countries regulate the number of hours teachers and school heads are required to work per year. The way
teachers’ total working time is divided between teaching and non-teaching activities, and the distribution of
working hours taking place within the school or elsewhere, varies greatly across countries.

Figure D4.1. Teaching hours per year of teachers in upper secondary education, by type of
programmes (2019)
Net statutory contact time in public institutions
Upper secondar y, general programmes
Upper secondar y, vocational programmes

Hours per year
1300
1200
1100
1000
900
800
700
600

Iceland

Poland

Turkey

Japan3

Norway

Korea

Finland

Slovenia

Slovak Republic

French Comm. (Belgium)

Czech Republic

Greece

Portugal

Flemish Comm. (Belgium)

Switzerland 1, 2

Germany

Italy

Israel

EU23 average

Hungary

Spain

France

OECD average

Luxembourg

Colombia

Mexico

Chile

Lithuania

100
0

Costa Rica

500
400
300
200

1. Actual teaching time.
2. Reference year differs from 2019. Refer to the source table for details.
3. Average planned teaching time in each school at the beginning of the school year.
Countries and economies are ranked in descending order of the number of teaching hours per year in general upper secondary education.
Source: OECD (2020), Table D4.1. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2 https://doi.org/10.1787/888934165814

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D4. HOW MUCH TIME DO TEACHERS AND SCHOOL HEADS SPEND TEACHING AND WORKING?  409

Context
Although statutory working and teaching hours only partly determine the actual workload of teachers and school heads,
they do offer valuable insights into the demands placed on teachers and school heads in different countries. Teaching
hours and the extent of non-teaching duties may also affect the attractiveness of the teaching profession. Together with
salaries (see Indicator D3) and average class sizes (see Indicator D2), this indicator presents some key measures of the
working lives of teachers and school heads.
For teachers, the proportion of their 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 could also indicate that teachers have to
perform these tasks in their own time and hence work more hours than required by their statutory working hours.
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 Box D2.3 in Indicator D2).

Other findings


The number of teaching hours per year required of the average teacher in pre-primary, primary and secondary
public schools varies considerably across OECD 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 993 hours per year across
OECD countries and economies, ranging from 519 hours in Mexico to 1 755 hours in Germany.



Between 2000 and 2019, average statutory teaching hours remained stable in OECD countries and economies
with available data, falling by 2% in primary education and by less than 1% in general lower secondary education.



At the lower secondary level, teachers spend 44% of their working time on teaching on average, ranging from
35% or less in Austria, Iceland, Korea, Poland and Turkey to 63% in Scotland (United Kingdom). During their
working time, teachers in most countries are required to perform various non-teaching tasks such as lesson
planning/preparation, marking students’ work and communicating or co-operating with parents or guardians.



School heads in OECD countries and economies work an average of 43-45 weeks per year, according to the level
of education. Their annual statutory working time averages to 1 658 hours at pre-primary level, 1 630 hours at
primary level, 1 628 hours at lower secondary level and 1 632 hours at upper secondary level. In about two-thirds
of the OECD countries, school heads are required to work during students’ school holidays.



In more than half of the OECD countries, official documents explicitly state that school heads have additional
tasks and responsibilities (e.g. teaching students, communication with parents) on top of their managerial and
leadership roles.

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410  D4. HOW MUCH TIME DO TEACHERS AND SCHOOL HEADS SPEND TEACHING AND WORKING?

Analysis
Teaching time of teachers
At the pre-primary, primary and secondary levels, countries vary considerably in their annual statutory teaching time – the
number of teaching hours per year required of a full-time teacher in a public school. Variations in how teaching time is
regulated and/or reported across countries may explain some of the differences in statutory teaching time between countries
(Box D4.1). In some countries, teaching time also varies at the subnational level (Box D4.2).

Box D4.1. Comparability of statutory teaching and working time data
Teaching time of teachers
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 the 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.
Moreover, official documents might regulate teaching time as a minimum, typical or maximum time, and these differences
may explain some of the differences reported between countries. While most data refer to typical teaching time, about
one-third of countries report maximum or minimum values for teaching time.
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 of teachers, such as professional development days (including attending conferences) and student
examination days, are also requested to be excluded from the teaching hours reported in this indicator. At each level of
general education, more than half of the countries and economies with available information are able to exclude the
number of days spent on these activities from statutory teaching time (for vocational programmes, 40% of countries are
able to exclude these activities at the lower secondary level and 67% of countries at the upper secondary level). However,
in the rest of the countries, the regulations do not always specify the number of days devoted to some of these activities
and/or whether teachers are required to conduct these activities outside of scheduled teaching times, making it difficult to
estimate and exclude them from teaching time.
Less than one-third of the countries cannot exclude professional development days from teaching time at all levels of
education (general and vocational programmes). In these countries, the regulations specify some days of professional
development activities for all teachers, but the impact on reported teaching time is difficult to estimate as the number of
days and how they are organised during the school year may vary across schools or subnational entities. Similarly, less
than one-third of countries with available information cannot exclude student examination days from teaching time at each
level of education. In many of these countries, regulations include some guidelines on the number of student examination
days, but they are not clear about whether scheduled teaching time is reduced by the time devoted to examinations, or
by how much. Overall, not excluding the time devoted to professional development and student examinations may result
in annual teaching time being overestimated by approximately one to five days in these countries.
Other forms of professional development activities and student examinations may result in the overestimation of teaching
time. Examples include professional development activities required for specific groups of teachers only (when regulations
do not explicitly forbid them from participating during their scheduled teaching time) and compulsory standardised student
assessments conducted for only a few hours of the school day. The time spent on these activities should also be excluded
from teaching time but they are not due to the complexity of estimation and the fact that only some teachers participate in
these activities.

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D4. HOW MUCH TIME DO TEACHERS AND SCHOOL HEADS SPEND TEACHING AND WORKING?  411

Working time for teachers and school heads
The working hours of teachers and school heads are usually defined in the regulations. However, some calculation may
be required to estimate the annual working time when working time is defined based on units other than annual hours. In
21 out of 28 countries (75%), teachers’ total working time has been converted from daily or weekly values to annual hours
by using the number of teaching weeks and days for at least one level of education. However, in few of these countries
the regulations may also specify working time during students’ school holidays on top of working time during students’
school year ─ for example, teachers in Colombia are required to work five additional weeks during the students’ school
holidays. In 22 out of 29 countries (76%), school heads’ total working time has been converted from daily or weekly values
to annual hours by using the number of working weeks and days for at least one level of education. The statutory working
time for school heads extend beyond the students’ school year, except in Ireland, New Zealand, Scotland
(United Kingdom) and the Slovak Republic.
More detailed information on the reporting practices on teaching time and working time for all participating countries and
economies is available in Annex 3.
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 per year ranges from 158 days in the Flemish Community of
Belgium to 225 days in Germany and Norway. Annual teaching hours range from 519 hours 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
993 hours per year, spread over 40 weeks or 194 days of teaching (Table D4.1 and Figure D4.2).
Primary school teachers are required to teach 778 hours per year in public institutions on average. 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
Mexico must teach 780 hours per year, over 62 hours more than in Turkey. However as teachers teach more days in Mexico
than in Turkey (195 days compared to 180 days), teachers in both countries teach four hours a day on average (Table D4.1).
Lower secondary school teachers in general programmes in public institutions are required to teach an average of 712 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 Costa Rica and Mexico. However, the reported hours for Finland and Korea refer to the minimum time teachers
are required to teach (Box D4.1) 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.
A teacher in general upper secondary education in public institutions has an average teaching load of 680 hours per year.
Teaching time ranges from fewer than 500 hours per year in Iceland, Poland and the Russian Federation to more than
1 000 hours in Costa Rica. Teachers in Finland, Iceland, Japan, Korea, Norway, Poland, the Slovak Republic, Slovenia,
Turkey and the Russian Federation teach for three hours or less per day, on average, compared to six hours or more in
Costa Rica (Table D4.1).

Box D4.2. Teaching and working time at the subnational level
There are regional differences in teachers’ statutory teaching and working time in the four countries (Belgium, Canada,
Korea and the United Kingdom) reporting subnational data. Only in Canada did the number of weeks of teaching (at preprimary, primary, and lower and upper secondary levels) vary between regions (from 36 to 38 weeks) in 2019 ─ in Belgium,
Korea and the United Kingdom, the number of weeks of teaching is the same across subnational regions. However, overall
figures for the number of weeks of teaching can mask differences in teaching time in terms of days or hours of teaching
at the subnational level.
The four 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 Flemish and French 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 11% higher in the French Community than in the Flemish Community (177 days compared to
160 days) due to differences in how a school day is defined in the regulations. However, teaching hours vary by only 5%
between the two communities (620 hours in the Flemish Community compared to 589 hours in the French Community).

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412  D4. HOW MUCH TIME DO TEACHERS AND SCHOOL HEADS SPEND TEACHING AND WORKING?
In contrast, the number of days teaching at primary and secondary levels varies by 6% across the different provinces and
territories in Canada (between from 180 days and 190 days), but teaching hours vary much more. 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). For lower and upper secondary general programmes, the difference
reaches 54% (947 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 9% at upper secondary level (from 514 to
561 hours) and by 29% at lower secondary level (from 442 to 570 hours). They also vary by 12% at the primary level (from
634 to 708 hours) and by 21% at the pre-primary level (from 729 to 883 hours).
However, caution is necessary when comparing information at the subnational level due to the following considerations:
potential differences in the regulations between countries and between subnational regions within countries, how data are
reported for the different subnational regions, and varying data availability for subnational regions within countries. For
example typical teaching time is reported for the subnational regions of Belgium, but mandated 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 D4.1).
Source: Education at a Glance Database. http://stats.oecd.org.

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 preprimary level is more than at the upper secondary level (general programmes). The exceptions are Chile and Scotland
(United Kingdom), where teachers are required to teach same hours at all levels of education, and Australia, Colombia,
Costa Rica, Lithuania and Mexico, where upper secondary school teachers are required to teach more hours than pre-primary
school teachers (Table D4.1 and Figure D4.2).
The largest difference in teaching time requirements is between the pre-primary and primary levels of education. On average,
pre-primary school teachers are required to spend about 28% more time in the classroom than primary school teachers. In
the Czech Republic, Estonia, Germany, Hungary, Iceland, Latvia and Slovenia, pre-primary school teachers are required to
teach at least twice the number of hours per year as primary school teachers (Table D4.1).
In Austria, France, Ireland, Korea, the Netherlands, Portugal, Spain and Turkey, primary school teachers have at least 25%
more annual teaching hours than lower secondary school teachers, while there is no difference in Chile, the Czech Republic,
Hungary, Iceland, 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, Latvia and Lithuania, and much lighter in Mexico
(Table D4.1).
Teaching time at lower and upper secondary levels is similar across most countries. However, in Iceland, Japan, Norway and
Switzerland, annual required teaching time at the lower secondary level is at least 20% more than at the upper secondary
level (Table D4.1).

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, the level for which most countries have both general and vocational programmes, teaching hours are similar
in both programmes in nearly two-thirds of the 27 countries and economies with available information. However, teaching
times are at least 12% higher in vocational programmes than in general programmes in the Flemish Community of Belgium,
Finland, Lithuania, Norway and Switzerland, and 18% lower in vocational programmes in Mexico (Figure D4.1).
Within vocational programmes, the statutory teaching time may vary according to the type of subjects being taught, as some
countries and economies set different teaching requirements (and working conditions, see Box D3.3) for teachers of
vocational and general subjects. For example, in the Flemish Community of Belgium, teachers of vocational practice courses
in upper secondary vocational programmes are required to teach up to 50% more hours per week compared to those teaching
general subject courses and vocational theory courses.

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D4. HOW MUCH TIME DO TEACHERS AND SCHOOL HEADS SPEND TEACHING AND WORKING?  413

Figure D4.2. Teaching hours per year of teachers, by level of education (2019)
Net statutory contact time in public institutions

Hours per year
1800

Upper secondar y, general programmes
Lower secondary, general programmes
Primary
Pre-primary

1600
1400
1200
1000
800
600
400

0

Costa Rica
Chile
United States 1, 2
Lithuania
Scotland (UK)
Mexico
Colombia
Australia
New Zealand
Luxembourg
Netherlands
Ireland
Latvia1, 2
France
OECD average
Spain
Hungary
EU23 average
Italy
Israel
Germany
Switzerland 1, 2
Flemish Comm. (Belgium)
Portugal
Austria
Greece
Czech Republic
French Comm. (Belgium)
Estonia
Slovak Republic
Slovenia
Finland
Korea
Norway
Japan3
Turkey
Russian Federation 1, 2
Poland
Iceland
Denmark

200

1. Actual teaching time (in Latvia except for pre-primary level).
2. Reference year differs from 2019. Refer to the source table for details.
3. Average planned teaching time in each school at the beginning of the school year.
Countries and economies are ranked in descending order of the number of teaching hours per year in general upper secondary education.
Source: OECD (2020), Table D4.1. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2 https://doi.org/10.1787/888934165833

Trends in teaching time
While there has been little change in average teaching hours between 2000 and 2019, one in five countries with available
data (and no break in the time series) reported change of 10% or more in teaching time in one or more educational levels
over these 19 years (Table D4.6, available on line).
At the primary level, teaching time increased by at least 14% (more than 100 hours) between 2000 and 2019 in Israel and
Japan. In Israel, this increase in teaching (and working) time is part of the “New Horizon” reform that has been gradually
implemented since 2008. One of the key measures of this reform was to lengthen teachers’ working week to accommodate
small-group teaching in exchange for more generous compensation. Teachers’ working time was increased from 30 to
36 hours per week and now includes 5 hours of small-group teaching in primary schools. To compensate, salaries have been
raised substantially (see Indicator D3). Teaching time for lower secondary school teachers also increased in Israel, by nearly
20% (115 hours), and in Japan, albeit to a lesser extent (10% or 58 hours) during this period. At the upper secondary level,
the largest increase in teaching time was also in Israel, where teachers had to teach nearly 19% more hours (99 additional
hours) in 2019 than they did in 2000 (Table D4.6, available on line).
In contrast, net teaching time fell between 2000 and 2019 in some countries and economies. At the pre-primary level, among
the few countries and economies with available data for 2000 and 2019, teaching time decreased by 10% or more in Portugal
(by 190 hours) and Scotland (United Kingdom) (by 95 hours). At other levels of education, teaching time decreased by 10%
or more in Mexico at lower secondary level (by 168 hours), in the Netherlands at both lower and upper secondary levels (by
147 hours), in Scotland (United Kingdom) at primary level (by 95 hours) and in Turkey at upper secondary level (by 64 hours).

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414  D4. HOW MUCH TIME DO TEACHERS AND SCHOOL HEADS SPEND TEACHING AND WORKING?
The reduction was 22% in Korea at primary level (by 189 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 hours to 22.5 hours per week for primary,
secondary and special school teachers in 2001. In Chile, the fall has also been significant as the regulations have gradually
decreased teaching time since 2016 by 14% (159 hours) in pre-primary, primary and secondary school teachers. However,
even with this decrease in net contact time, the maximum time teachers at these levels in Chile and Scotland
(United Kingdom) can be required to teach is still longer than the OECD average (Table D4.6, available on line).

Actual teaching time
Statutory teaching time, as reported by most of the countries in this indicator, refers to teaching 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 (actual time spent in the
classroom) includes 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 selfreported that they spent 78% of classroom time on teaching and learning in 2018 (OECD, 2019[1]).
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 New Zealand, Poland and Slovenia, for example, lower
secondary teachers actually teach 6 to 15% more hours than their statutory teaching time (Figure D4.6, 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.

Teaching time of school heads
Whereas teaching is the primary or main responsibility of teachers, it can also be part of the responsibilities of school heads
in some countries.
Among the 28 countries with available information, school heads in pre-primary institutions are required to take some teaching
responsibility in 14 countries (50%), can voluntarily teach in 3 countries (11%) and are not required to teach in 11 countries
(39%). In primary education, teaching is required from school heads in more than half of the countries with available data
(19 out of 34 countries). Teaching responsibilities become less common for school heads at the secondary level. In general
lower secondary education, school heads are required to teach in 15 out of 34 countries (44%), are free to teach at their own
discretion in 5 countries (15%), and are not required to teach in 14 countries (41%). Similarly, in general upper secondary
education: teaching is a requirement in 14 out of 34 countries (41%), a voluntary task in 5 countries (15%) and is not part of
the responsibilities of the school heads in 15 countries (44%). In all the countries with available data, the teaching
responsibilities of school heads in secondary education are similar in general and vocational programmes (Table D4.7,
available on line).
Most of the countries where teaching is one of the responsibilities of school heads, do not set a specific number of teaching
hours for them, but rather define minimum and/or maximum teaching hours. In lower secondary general programmes, for
example, the minimum statutory teaching time for school heads (converted into hours per year) ranges from 0 hours
(i.e. exempt from teaching) to 194 hours, and the maximum statutory teaching time from 148 hours to 594 hours. In most of
these countries, teaching represents less than 30% of school heads’ statutory working time, but the proportion reaches 36%
in the Slovak Republic and exceeds 73% in Ireland (in the Education and Training Board sector) (Table D4.7, available on
line). The maximum teaching time is usually only required for school heads in specific circumstances. For example, in Ireland
almost all school heads actually have either no or minimal teaching hours (for more information on minimum and/or maximum
teaching time requirements, refer to Table X3.D4.9 in Annex 3).
Although teaching may be required for school heads at all levels of education in a given country, their minimum and maximum
teaching requirements could vary across levels of education. In a majority of the countries with teaching requirements, the
number of teaching hours required from school heads decreases as the level of education increases. The exceptions are

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D4. HOW MUCH TIME DO TEACHERS AND SCHOOL HEADS SPEND TEACHING AND WORKING?  415
Australia, where teaching requirements increase between the pre-primary and primary education, and Turkey, where teaching
requirements for school heads are the same at all levels of education (Table D4.7, available on line).
In almost all countries, the teaching requirements for school heads do not vary between general and vocational programmes.
At upper secondary level, Finland is the only country where the teaching requirements vary significantly ─ maximum teaching
time requirements for school heads are 30% higher in general programmes than in vocational programmes (Table D4.7,
available on line).
In all countries where school heads have teaching responsibilities, except Turkey, the requirements vary based on specific
criteria related to school heads. In a large majority of these countries, the characteristics of the school such as its size (number
of students, teachers and/or classes) and/or the level of education it covers are important determinants of the teaching
requirements. Geographical location or the socioeconomic status of the region may also be considered (in Australia and
Ireland).

Working time of teachers
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.
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 one-third 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 half of these countries (Hungary, Iceland, Latvia, Luxembourg, New Zealand, Portugal,
Sweden and Turkey), pre-primary teachers are required to be available at school for at least 20% more hours than upper
secondary school teachers and the difference even exceeds 40% in Latvia and New Zealand (although total statutory working
time is the same for both levels in Hungary, Iceland, Sweden and Turkey) (Table D4.2).
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, 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,
the Netherlands, Poland, the Slovak Republic and Switzerland (Table D4.2). Of these, teachers in France, Germany (in some
Länder), Japan, Korea, Portugal and Turkey are subject to the same statutory working time as civil servants (for more
information on the definition of teachers’ working time, see Table X3.D4.7 in Annex 3).
In addition, workloads 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 based on their age, number of years in the profession or for
doing extracurricular activities at school. Iceland reduces the teaching time of primary and lower secondary teachers
according to their age: teachers aged 55 or over receive a reduction of teaching time (from 46 hours, or 8% of the statutory
teaching time, for 55-59 year-olds to 162 hours, or 27% of teaching time, 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 (Figure D4.3).
Even though teaching is a core activity for teachers, in a large number of countries, they spend most of their working time on
activities other than teaching. In the 25 countries and economies with data for both teaching and total working time for lower
secondary teachers, 44% of teachers’ working time is spent on teaching on average, with the proportion ranging from 35% or
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416  D4. HOW MUCH TIME DO TEACHERS AND SCHOOL HEADS SPEND TEACHING AND WORKING?
less in Austria, Iceland, Korea, Poland and Turkey to at least 50% in Chile, Colombia, Israel, Lithuania, Luxembourg and
Scotland (United Kingdom) (Figure D4.3).
While the proportion of working time spent teaching increases with the number of teaching hours per year, there are some
variations between countries. For example, Germany and Spain have a similar number of teaching hours (651 hours in
Germany and 669 hours in Spain), but 37% of teachers’ working time is spent on teaching in Germany, compared to 47% in
Spain. In some countries, teachers devote similar proportions of their working time to teaching, despite having considerably
different teaching hours. For example, in Estonia and Switzerland, lower secondary teachers spend about 39% of their working
time teaching, but teachers teach 606 hours in Estonia, compared to 748 hours in Switzerland (Figure D4.3).

Figure D4.3. Percentage of lower secondary teachers' working time spent teaching (2019)
Net teaching time (typical annual number of hours) as a percentage of total statutory working time in general programmes
in public institutions
Percentage of total statutory
working time spent teaching
Country average

65

60

Scotland (UK)

Luxembour g

Lithuania
Isr ael

55

Colombia
Chile

50
Por tugal

Spain

Latvia 1

45

Countr y aver age
Nether lands

Slovak Republic
Czec h Republic
40

Estonia
Hungar y
Kor ea

35

Poland

Japan2
Ic eland

Fr ance

Denmar k

Nor way
Switzer land1

Ger many
Austr ia

Tur key
30
400

500

600

700

800

900
1000
Number of teaching hours per year

Note: For better interpretation, please refer to the notes on the nature of the data in Table D4.1.
1. Reference year of actual teaching time data differs from 2019. Refer to the source table for details.
2. Average planned teaching time in each school at the beginning of the school year.
Source: OECD (2020), Tables D4.1 and D4.2. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2 https://doi.org/10.1787/888934165852

In some countries, such as Austria (upper secondary level), Costa Rica, the Flemish and French communities of Belgium
(lower and upper secondary levels), Italy and Mexico (upper secondary level), there are no formal requirements for time spent
on non-teaching activities. However, this does not mean that teachers are given total freedom to carry out other tasks. In
the Flemish Community of Belgium, although there are no regulations regarding the time devoted to preparing lessons,
correcting tests, marking students’ papers and other non-teaching tasks, additional non-teaching hours at school are set at

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D4. HOW MUCH TIME DO TEACHERS AND SCHOOL HEADS SPEND TEACHING AND WORKING?  417
the school level. In Italy, teachers are required to perform up to 80 hours of scheduled non-teaching collegial work at school
per year. Of these 80 hours, up to 40 hours are dedicated to meetings of the teachers’ assembly, staff planning meetings and
meetings with parents, with the remaining 40 compulsory hours dedicated to class councils (Table D4.2).

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.
Individual teachers often do not have the authority to choose whether to perform certain tasks related to teaching. According
to regulations in more than 35 out of the 42 countries and economies with available data for general lower secondary
education, individual planning or preparing lessons, marking and correcting student work, and communicating and cooperating with parents are mandatory non-teaching tasks for teachers during their statutory working time. General
administrative work and teamwork, and dialogue with colleagues are also required in at least 30 countries, and can be decided
at the school level in at least 5 other countries with available data. For such mandatory tasks, incentives such as reductions
in teaching time and financial compensation are rare (Table D4.3).
Responsibilities such as being class/form teacher, participating in mentoring programmes and/or supporting new teachers in
induction programmes or participating in school or other management in addition to teaching duties are largely distributed
among general lower secondary teachers in more than two out of five countries. In over half of these countries, participation
in school or other management activities can result in specific compensation for teachers. In some countries, their teaching
time might be reduced to balance the workload between teaching and other responsibilities, in addition to financial
compensation (Table D4.4).
Of the various tasks teachers might perform, full-time classroom teachers (in general lower secondary education) are either
required or asked to perform student counselling in more than half of countries and economies with available information.
However, in some countries, not all teachers can perform student counselling. For example, in Israel, only teachers with
master’s degree or higher can perform this duty. In Iceland, this duty is not performed by teachers, but by special student
counsellors (Table D4.4).
Teachers do not only perform the tasks that are required by regulations or school heads; they also often perform tasks
voluntarily. In about half of the countries with available data at the general lower secondary level, individual teachers decide
themselves whether to engage in extracurricular activities or whether to train student teachers. Teaching more classes or
hours than their full-time contract requires is also a voluntary decision by teachers in about two-fifths of the countries and
more than two-thirds of these countries offer financial compensation for this additional teaching (Table D4.4).
Participation in professional development activities is considered an important responsibility of teachers at all levels of
education, as it is mandatory for teachers at all levels in 24 countries. Participation is required at the discretion of individual
schools in 10 countries for at least one level of education. Only seven countries allow teachers to participate in professional
development activities at their own discretion. Regardless of the requirement, a large majority of teachers in OECD countries
participate in professional development activities (OECD, 2019[1]). For more information on requirements related to teachers’
compulsory professional development activities, see Box D4.3.
In general, requirements to perform certain tasks and responsibilities do not vary much across levels of education. However,
there can be some differences reflecting the changing needs of students at different levels of education. For example, lower
secondary teachers are required to supervise students during breaks in 17 countries, but this is much more widespread at
pre-primary (23 countries) and primary (22 countries) level (Table D4.3).

Box D4.3. Professional development activities of teachers (2019)
Teaching students is the primary function of teachers, but they are involved in a larger number of activities than teaching.
Among many other activities, they engage in learning to develop their skills to provide students with a better quality of
education. A recent OECD survey gathered information on the requirements of teachers in public schools related to

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418  D4. HOW MUCH TIME DO TEACHERS AND SCHOOL HEADS SPEND TEACHING AND WORKING?
continuing professional development (CPD) activities. The findings from this survey shows the diversity of requirements on
CPD across the OECD and partner countries.
Among the 38 countries and economies participating in this survey, 24 countries have compulsory CPD requirements for
all teachers in at least one level of education, and then 20 countries have compulsory CPD requirements for teachers in
all levels of education (from pre-primary to upper secondary). At all levels of education, more than half of these countries
have minimum requirements for the duration of these CPD activities, either each year or over a period of several years.
Though not fully comparable due to differences in the units used, the duration ranges from 16 hours per three-year period
(about 5 hours per year) in Luxembourg (at pre-primary and primary levels) to 5 days per year in Slovenia. Even though a
large number of countries have no minimum duration requirements, they can use other ways to ensure all teachers
participate in CPDs. For example, in the Czech Republic, schools are legally obliged to organise CPD for teachers, and
the relevant government body checks that schools are implementing this rule. In about one-third of the countries with
compulsory CPD for teachers, teachers are required to participate in these activities during non-teaching working time.
In addition to compulsory CPD throughout their teaching career, teachers can be required to participate in compulsory CPD
activities at specific points in their careers. Ten out of the 38 countries have such CPD requirements, with four countries
requiring that teachers participate in these activities at the beginning of their teaching career. However, for many of these
countries, more details on the requirements related to the duration and period of these activities are not available.

Figure D4.4. Participation in professional development activities1
For teachers in lower secondary general programmes
Compulsor y CPDs Requir ed for :
A All teachers
B All teachers at specific point(s) of teaching career
C All teachers under individual circumstances

Percentage of lower secondary
teachers who participated in
professional development activities

Ex ists

Does not ex ist

Missing

France

Chile

Brazil

Portugal

Japan

Colombia

Spain

Denmark

Finland

Italy

Turkey

Norway

Hungary

Sweden

Israel

England (UK)

Flemish Comm. (Belgium)

Czech Republic

Estonia

Korea

United States

Netherlands

Slovenia

New Zealand

Latvia

Austria

Australia

Lithuania

A
B
C

Note: This figure only includes countries and economies with information in both TALIS and the NESLI Survey. The NESLI Survey reflects information on full-time, fully
qualified teachers in public institutions for the school year 2018/19, whereas TALIS 2018 was also conducted with teachers in government-dependent and/or private
schools for the school year 2017/18. Please refer to TALIS Technical Report (OECD, 2019) for more information on sampling.
1. The scope of professional development activities in the NESLI Survey is limited to formal and compulsory professional development activities, whereas the scope of
professional development activities in TALIS 2018 was broader, including non-formal activities such as reading professional literature.
Countries and economies are ranked in descending order of the percentage of lower secondary teachers who participated in professional development activities in the
12 months prior to the survey.
Source: OECD (2019) and OECD-INES NESLI 2019 Survey on requirements related to examination days and professional development.
Statlink2 https://doi.org/10.1787/888934165871

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D4. HOW MUCH TIME DO TEACHERS AND SCHOOL HEADS SPEND TEACHING AND WORKING?  419
Moreover, there could be also CPD requirements on teachers based on their individual circumstances. Fifteen of the
38 countries surveyed indicated the existence of such requirements. Among these countries, Chile, Colombia, Israel and
Lithuania do not have compulsory CPDs required for all teachers or required at some points of teaching career
(Figure D4.4). These compulsory CPD activities are often the minimum requirement (or part of the minimum requirement)
for salary increases, promotions, obtaining higher-level teaching credentials or teaching specific subjects/group of students.
In some countries, the majority of teachers could be participating in these forms of CPD in any given year because they
could be required continuously throughout a teaching career (for instance, for salary increases). In only 6 of the
15 countries, teachers are required to participate in these activities outside of their scheduled teaching hours.
Though no CPD is compulsory for any teachers in England (United Kingdom), New Zealand, Norway and Sweden,
teachers in these countries and economies can participate in CPD activities at the discretion of their schools during some
of their regulated working time (Table D4.4 and Figure D4.4). In Denmark, CPD requirements for upper secondary teachers
exist at a local level.
The findings of the survey could complement the result of TALIS 2018 which found that 94% of general lower secondary
teachers in (a different set of) 31 OECD countries and economies participated in at least one type of professional
development during the last 12 months prior to the survey (OECD, 2019[1]). Although TALIS asks about participation in
both compulsory and non-compulsory CPD and includes teachers in schools other than public institutions, the countries
and economies with compulsory CPD requirements for all teachers in public schools generally have a higher proportion of
teachers participating in CPD than those which do not (Figure D4.4).

Working time of school heads
As with teachers’ working time, many OECD and partner countries define school heads’ statutory working time under relevant
regulations or collective or individual contracts. In France, Japan, Korea, Mexico (upper secondary education) and Turkey,
civil servants’ regulations apply for school heads’ working time (as for teachers, except in Mexico). Only in
the Flemish Community of Belgium, Germany (in most Länder), Greece, Italy and Luxembourg, are there no official
documents specifying quantitative information on the working time for school heads (Table X3.D4.8 in Annex 3).
According to levels of education, on average across OECD countries and economies school heads work 43-45 weeks, or
more than 210 days, per year. On average, the school heads’ annual statutory working hours do not vary much between
levels of education: they average 1 658 hours at the pre-primary level, 1 630 hours at primary level, 1 628 hours at lower
secondary level and 1 632 hours at upper secondary level. There is no difference in the number of statutory working hours
between general and vocational programmes in the countries with both programmes in lower and/or upper secondary
education. Across all levels of education, school heads in Chile have the longest hours (1 971 hours per year). In contrast,
school heads’ statutory working hours are lowest in Mexico (at pre-primary level) and Ireland (for primary and lower and upper
secondary general programmes) where statutory working hours are below 1 300 hours per year (Error! Not a valid
bookmark self-reference. and Table D4.5).
In 21 out of 29 OECD and partner countries and economies with available data (72%), school heads’ annual working hours
do not vary much across levels of education. In the remaining eight countries where their statutory working time do vary,
school heads in pre-primary education generally work more hours per year than those in secondary education. For example,
school heads’ statutory hours in pre-primary schools are 2-8% higher than in primary and secondary schools in Estonia,
Finland and New Zealand. Mexico is the only country where school heads have shorter working hours at pre-primary and
primary levels than at lower secondary level (by 14%) and at upper secondary level (by 26%) (Table D4.5).
In about two-thirds of the OECD countries and economies with available data, the statutory working time of school heads
includes working during students’ (seasonal) school holidays. The amount worked during students’ school holidays could
range from about 1 week in Austria and the Netherlands (at the request of the school heads’ employers) to 11 weeks in
Turkey. During students’ school holidays, school heads in some of these countries are required to prepare for the new school
semester and arrange professional development programmes etc. In the other one-third of countries, the regulations do not
require school heads to work during students’ school holidays. Nevertheless, the actual practice could be different. For
example, school heads in Ireland may work during at least a part of students’ school holidays although it is not included in
their statutory working time (Table X3.D4.8 in Annex 3).

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420  D4. HOW MUCH TIME DO TEACHERS AND SCHOOL HEADS SPEND TEACHING AND WORKING?

Figure D4.5. Working and teaching hours per year of school heads in general lower secondary education (2019)
Statutory working time and teaching time in public institutions
Total working time
Minimum teaching requirement
Max imum teaching requirement

Hours per year
2000
1800
1600
1400
1200
1000
800
600
400

Flemish Comm. (Belgium)

Greece

Ireland 1

Australia

Scotland (UK)

Mexico

New Zealand

Israel

Finland

Portugal

Slovak Republic

Spain

France

EU23 average

Denmark

OECD average

Hungary

Netherlands

Lithuania

Czech Republic

Norway

Slovenia

Poland

Colombia

Japan

Estonia

Iceland

Sweden

Korea

Austria

Turkey

Chile

0

Latvia

200

1. Maximum teaching requirement for school heads in the Education and Training Board Sector.
Countries and economies are ranked in descending order of the number of total working hours per year in general lower secondary education.
Source: OECD (2020), Table D4.5 and Table D4.7 (available on line). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2 https://doi.org/10.1787/888934165890

Tasks and responsibilities of school heads
In more than half of the OECD and partner countries with available data, regulations explicitly state that school heads are
expected to play managerial and leadership roles. In addition, school heads can be required to perform other tasks and
responsibilities, such as management of human/financial resources, organising professional development activities,
organising students’ educational activities and teaching students as well as facilitating good relations with parents, education
inspectorates, and/or the government. In a majority of countries, the tasks and responsibilities required from school heads do
not vary across levels of education and educational programmes (for more details, refer to Table X3.D4.8 in Annex 3).
However, in about one-quarter of countries with available information (Denmark, Estonia, Finland, Italy, Mexico,
the Netherlands, New Zealand, Norway, Scotland [United Kingdom] and Sweden), official documents on the working
conditions of school heads do not detail their responsibilities and tasks. School heads in these countries may have more
autonomy in organising their work and responsibilities (Table X3.D4.8 in Annex 3).

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.
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D4. HOW MUCH TIME DO TEACHERS AND SCHOOL HEADS SPEND TEACHING AND WORKING?  421
Statutory teaching time is defined as the scheduled number of 60-minute hours per year that a full-time teacher (or a school
head) teaches a group or class of students, as set by policy, their 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 or school head 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 (of teachers) 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/10.1787/69096873-en).

Source
Data are from the 2019 OECD-INES-NESLI Survey on Working Time of Teachers and School Heads and refer to the school
year 2018/19 (statutory information) or school year 2017/18 (actual data).

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]

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422  D4. HOW MUCH TIME DO TEACHERS AND SCHOOL HEADS SPEND TEACHING AND WORKING?

Indicator D4 Tables
Table D4.1

Organisation of teachers’ teaching time (2019)

Table D4.2

Organisation of teachers’ working time (2019)

Table D4.3

Tasks of teachers, by level of education (2019)

Table D4.4

Other responsibilities of teachers, by level of education (2019)

Table D4.5

Organisation of school heads’ working time (2019)

WEB Table D4.6

Number of teaching hours per year (2000, 2005 to 2019)

WEB Table D4.7

Teaching requirements of school heads (2019)

Cut-off date for the data: 19 July 2020. Any updates on data can be found on line at http://dx.doi.org/10.1787/eag-dataen. More breakdowns can also be found at http://stats.oecd.org/, Education at a Glance Database.
StatLink: https://doi.org/10.1787/888934165700

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D4. HOW MUCH TIME DO TEACHERS AND SCHOOL HEADS SPEND TEACHING AND WORKING?  423

Table D4.1. Organisation of teachers’ teaching time (2019)
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. Minimum teaching time.
4. Average planned teaching time in each school at the beginning of the school year.
5. Actual teaching time (in Latvia except for pre-primary level).
6. Year of reference 2018 for Latvia and Switzerland, 2017 for the Russian Federation and 2016 for the United States.
Source: OECD (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888934165719

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424  D4. HOW MUCH TIME DO TEACHERS AND SCHOOL HEADS SPEND TEACHING AND WORKING?
Table D4.2. Organisation of teachers’ working time (2019)
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 (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888934165738

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D4. HOW MUCH TIME DO TEACHERS AND SCHOOL HEADS SPEND TEACHING AND WORKING?  425

Table D4.3. Tasks of teachers, by level of education (2019)
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 3, 4, 5, 7, 8, 9, 11, 12, 13, 15, 16, 17, 19, 20, 21, 23, 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 (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888934165757

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426  D4. HOW MUCH TIME DO TEACHERS AND SCHOOL HEADS SPEND TEACHING AND WORKING?
Table D4.4. Other responsibilities of teachers, by level of education (2019)
Teachers' responsibilities 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 2, 3, 4, 6, 7, 8, 10, 11, 12, 14, 15, 16, 18, 19, 20, 22, 23, 24, 26 27, 28, 30, 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 (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888934165776
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D4. HOW MUCH TIME DO TEACHERS AND SCHOOL HEADS SPEND TEACHING AND WORKING?  427

Table D4.5. Organisation of school heads’ working time (2019)
Number of statutory working weeks, working days and total working hours in public institutions over the reference 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. Includes working time during students' school holidays.
2. Actual data.
3. Year of reference 2016.
Source: OECD (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888934165795

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428  D5. WHO ARE THE TEACHERS

Indicator D5. Who are the teachers?
Highlights


Although women make up the majority of the teaching profession in upper secondary education, the share of
female teachers is significantly higher in general programmes than in vocational ones.



There are relatively few young teachers (under the age of 30), and the proportion decreases with the level of
education. Young teachers make up 12% of the teaching population in primary education, 10% in lower secondary
education and 8% in upper secondary education, on average across OECD countries.



At upper secondary level, the share of teachers below the age of 30 fell by 4 percentage points between 2005
and 2018, on average across OECD countries with available data.

Figure D5.1. Gender distribution of teachers in upper secondary education, by programme orientation
(2018)
Percentage of women among teaching staff in public and private institutions
General programmes
Vocational programmes

%
100
90
80
70
60
50
40
30
20

Mexico

Switzerland1

Turkey

Denmark

Korea

Netherlands

Norway

Costa Rica

Greece

Luxembourg

Chile

Spain

Germany

United States

Brazil

Czech Republic

France

New Zealand

United Kingdom1

Belgium

OECD average

Austria

EU23 average

Hungary

Slovenia

Italy1

Finland

Poland

Ireland1, 2

Slovak Republic

Estonia1

Latvia

0

Lithuania

10

1. Upper secondary includes programmes outside upper secondary level.
2. Public institutions only.
Countries are ranked in descending order of the share of women in general programmes.
Source: OECD/UIS/Eurostat (2020), Table D5.1. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2 https://doi.org/10.1787/888934165985

Context
The demand for teachers depends on a range of factors, including average class sizes, 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 many OECD
countries set to reach retirement age in the next decade and the size of the school-age population projected to increase

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D5. WHO ARE THE TEACHERS  429

in some countries, governments will be under pressure to recruit and train new teachers. There is compelling evidence
that the calibre of teachers is the most significant in-school determinant of student achievement, so concerted efforts are
needed to attract top talent to the teaching profession and provide them with high-quality training (OECD, 2019[1]).
Teacher retention policies need to promote work environments that encourage effective teachers to continue teaching. In
addition, teaching at the pre-primary, primary and lower secondary levels remains largely dominated by women so the
gender imbalance in the teaching profession, and its possible effect on students’ learning, warrant detailed study (OECD,
2017[2]).

Other findings


Women make up the majority of teachers in primary and secondary education, while they are under-represented
in tertiary education. At all education levels, the largest share of women is found among the new generation of
teachers (below the age of 30).



Between 2005 and 2018, on average across OECD countries, there was a gradual increase in the gender gap in
favour of women from primary level to upper secondary level, but a decrease in the gap in favour of men at the
tertiary level.



The share of older teachers (aged 50 and over) increases with the education level, from 32% in primary education
to 36% in lower secondary and 39% in upper secondary education.



On average across OECD countries participating in the Teaching and Learning International Survey (TALIS),
around 90% of teachers say they were motivated to join the profession by the opportunity to influence children’s
development and contribute to society. On average, 76% of teachers report that, if they could decide again, they
would still choose to work as a teacher.

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430  D5. WHO ARE THE TEACHERS

Analysis
Gender profile of teachers
Share of female teachers, by level of education
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 with each successive level of
education. While women represent 96% of the teaching staff at pre‑primary level and 82% at primary level, they make up
60% at upper secondary and only 44% at tertiary level on average across OECD countries (Table D5.1).
Women account for over 85% of pre-primary teachers in all OECD and partner countries with available data, and over 65%
of primary teachers in all countries except Japan (64%), Turkey (62%) and Saudi Arabia (52%). In secondary education,
although female teachers continue to dominate, the proportion of female teachers is smaller than at lower levels. Women
make up 67% of lower secondary teachers on average across OECD countries, with values ranging from 43% in Japan to
85% in Latvia. At upper secondary level the share of female teachers’ drops to 60% on average across OECD countries, with
significant variations across countries (from 31% in Japan to 80% in Latvia) (Table D5.1).
At the tertiary level, the gender profile of teachers is reversed, with men making up the majority across OECD countries and
female teachers accounting for 44% of the teaching staff on average. In fact, among countries with available data, only in
Finland, Latvia, Lithuania and the Russian Federation do women make up more than 50% of teachers in tertiary education.
The smallest share of female tertiary teachers among OECD countries is found in Japan (28%) (Table D5.1).

Share of female upper secondary teachers, by programme orientation
The share of women among upper secondary teachers tends to be higher in general than in vocational programmes, although
women are over-represented in both types of programmes. In general education, women account for 62% of teachers on
average across OECD countries, and there are more female than male teachers in all countries except Switzerland (48%).
The share of female teachers is particularly high in countries such as Latvia and Lithuania, where over 80% are women. In
contrast, in vocational programmes, women account for a smaller share of teachers: 56% on average across OECD countries.
The share of female teachers in vocational education ranges from 44% in Switzerland to 73% in Latvia (Figure D5.1).
In some countries, the share of female teachers differs significantly between general and vocational programmes. For
instance, in Austria, Brazil, Finland, Hungary, Latvia and Lithuania, the share of female teachers in general programmes is at
least 10 percentage points higher than in vocational programmes, even though women still make up the majority of vocational
teachers in these countries. In contrast, the share of female teachers is the same in general and vocational programmes in
the Czech Republic (at 60%), the Netherlands (54%), Norway (55%) and Slovenia (67%) (Figure D5.1).

Box D5.1. Potential sources and implications of gender imbalances in the teaching profession
Several factors may contribute to gender imbalances in the teaching profession across levels of education and programme
types. One explanation may be cultural: social perceptions of the links between gender and choice of profession may
influence both 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[5]). 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[6]; 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 (see
Indicator B4 and (OECD, 2014[6])).
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 tertiary-educated
counterparts in other professions, while female teachers in primary and lower secondary education earn virtually the same

EDUCATION AT A GLANCE 2020 © OECD 2020

D5. WHO ARE THE TEACHERS  431
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[7];
OECD, 2005[8]; OECD, 2009[9]). While there is little evidence that a teacher’s gender has an effect on student performance
(Antecol, Eren and Ozbeklik, 2012[10]; Holmlund and Sund, 2008[11]), 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[12]). 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[13]; OECD, 2014[14]).

Share of female teachers, by age group and level of education
The higher proportion of women among young teachers, together with the predominance of female tertiary graduates in the
field of education (see Education at a Glance Database), may raise concerns about future gender imbalances at the primary
to upper secondary levels, where women already dominate the profession.
In most countries, the share of women is higher among young teachers (under the age of 30) than among older teachers
(aged 50 or older). At primary level, the difference between the two age groups is rather small, with women making up 83% of
the younger group, compared to 82% of the older group, on average across OECD countries. At lower secondary level, the
difference is also small on average: women make up 68% of teachers under the age of 30, and 66% of those of aged 50 or
older. The difference grows larger at upper secondary level: on average across OECD countries, 63% of young teachers are
women at this level, compared to 56% in the older group (Table D5.2).
However, at tertiary level, where female teachers are in the minority on average, the higher share of women among the
younger generation of teachers suggests there will be an increase in gender parity. On average across OECD countries, the
share of women is closer to 50% among younger tertiary teachers, accounting for 52% of teachers under the age of 30,
compared to 39% among those aged 50 or older (Table D5.2).
These indicators are consistent with the gender distribution dynamics observed over the decade, which point to a gradual
increase in the gender gap in the teaching profession at the primary and secondary level, but a decrease at the tertiary level.
On average, for all OECD countries with data for both years, the rise in the share of female teachers between 2005 and 2018
has widened the gender gap by 3 percentage points for the primary and secondary levels combined, while it has narrowed
the gap by 5 percentage points at the tertiary level. At the primary and secondary levels, the increase exceeds 5 percentage
points in countries such as the Czech Republic, Germany, Greece, Ireland, Korea and Slovenia. At the tertiary level, the
gender gap has decreased considerably in many countries, with a change of at least 7 percentage points in Belgium,
Germany, Japan, the Netherlands and Slovenia (Table D5.2).
The persistent gender imbalances in the teaching profession, together with imbalances in school leadership, have raised a
number of concerns, and countries such as the United Kingdom have implemented policies encouraging the recruitment and
retention of a diverse and inclusive teacher workforce, including in terms of gender (OECD, 2014[6]; OECD, 2017[2]).

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 more time spent in
tertiary education can delay the entrance of teachers into the labour market. Competitive salaries, good working conditions
and career development opportunities may have attracted young people to teaching in some countries or helped to retain
effective teachers in others.
Young teachers (below the age of 30) only account for a small proportion of the teaching population: 12% in primary education,
10% in lower secondary and 8% in upper secondary, on average across OECD countries. The pattern is particularly striking
at the upper secondary level, where young teachers make up less than 10% of the teaching population in most countries. In
fact, they account for less than 5% of upper secondary teachers in the Czech Republic, Denmark, Finland, Greece, Hungary,
Italy, Lithuania, Poland, Portugal, Slovenia and Spain (Figure D5.2).
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432  D5. WHO ARE THE TEACHERS
On average across OECD countries, more than half of primary, lower secondary and upper secondary teachers are aged
between 30 and 49, and a high share of teachers are at least 50 years old. The share of older teachers (aged 50 and over)
increases with the education level, from 32% in primary education to 36% in lower secondary and 39% in upper secondary
education. In most countries, at least one teacher in every three at upper secondary level is aged 50 or over. There is,
however, a high level of variation across countries, with the share at upper secondary level ranging from 15% in Turkey to
63% in Italy (Table D5.3).
The ageing of the teaching force has a number of implications for countries’ education systems. In addition to prompting
recruitment and training efforts to replace retiring teachers, it may also affect budgetary decisions. In most school systems,
teachers’ salaries increase with years of teaching experience. Thus, the ageing of teachers increases school costs, which
can in turn limit the resources available for other initiatives (see Box D2.3 in Indicator D2). In addition, during the current
COVID-19 crisis, the high share of teachers over the age of 50 may raise health concerns, as older individuals are more at
risk of developing severe forms of the disease (Jordan, Adab and Cheng, 2020[15]).

Figure D5.2. Share of teachers below the age of 30, by level of education (2018)
Primary
Lower secondary
Upper secondary

%
35
30
25
20
15
10

Italy1

Portugal1

Iceland

Lithuania

Hungary

Slovak Republic

Slovenia5
Poland

Spain

Costa Rica

Finland

Greece

Germany

Czech Republic

Sweden

Canada4

Brazil

Estonia1

Latvia

EU23 average

Colombi a

France

OECD average

Israel3

New Zealand

Ireland1, 2

Denmark

Netherlands

Korea

United States
Turkey

Austria

Norway

Chile

Switzerland1

Japan1

Belgium

Luxembourg

0

United Kingdom1

5

1. Upper secondary includes programmes outside upper secondary level.
2. Public institutions only.
3. Public institutions only for upper secondary level.
4. Primary includes pre-primary education.
5. Primary includes lower secondary education.
Countries are ranked in descending order of the share of teachers below the age of 30 in primary education.
Source: OECD/UIS/Eurostat (2020), Table D5.3. See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Statlink2 https://doi.org/10.1787/888934166004

Trends in the share of young upper secondary teachers between 2005 and 2018
As discussed above, upper secondary education is the level with the smallest share of young teachers on average across
OECD countries, and this share has been decreasing in recent years. While on average 12% of upper secondary teachers
were below the age of 30 in 2005, this proportion had fallen by 4 percentage points in 2018. The largest decreases were
observed in Luxembourg (8 percentage points) and Poland (10 percentage points). In Luxembourg, the share of young
teachers still remains above the OECD average at 10%, although in Poland it is now below average, at 4% (Figure D5.3).
However, a few countries have experienced an increase in the share of young upper secondary teachers between 2005 and
2018. The largest increases were observed in Chile (6 percentage points), Japan (4 percentage points) and
the United Kingdom (4 percentage points) (Figure D5.3). This may partly reflect efforts to implement teacher recruitment
EDUCATION AT A GLANCE 2020 © OECD 2020

D5. WHO ARE THE TEACHERS  433
policies. For instance, the United Kingdom launched an ambitious recruitment campaign in the early 2000s, aiming at
improving the status of the teaching profession. The campaign used slogans such as “Use your head: teach” or “Turn your
talent to teaching”, in order to appeal to young people who were considering teaching but were put off by a number of barriers,
including the financial burden of the training. The United Kingdom combined this with financial support for teacher trainees
(OECD, 2011[16]). 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 (Santiago et al., 2017[17]).

Figure D5.3. Share of upper secondary teachers below the age of 30 (2005 and 2018)
2005
2018

%
25
20
15
10

Greece

Portugal1

Italy1

Lithuania

Finland

Hungary

Spain3

Czech Republic

Poland

Slovenia

Denmark

Germany

Switzerland1

Sweden

EU23 average

Latvia

Austria

Estonia1

OECD average

Norway

Slovak Republic

France

Colombia

Korea

Luxembourg

Canada

Brazil

Israel2

Costa Rica

Netherlands

Turkey

Ireland1, 2

United States

Japan1

Belgium

Chile

0

United Kingdom1

5

1. Upper secondary includes programmes outside upper secondary level.
2. Public institutions only.
3. Upper secondary includes lower secondary programmes.
Countries are ranked in descending order of the share of teachers below the age of 30 in 2018.
Source: OECD/UIS/Eurostat (2020), Table D5.3 and Education at a Glance Database, http://stats.oecd.org. See Source section for more information and Annex 3 for notes
(https://doi.org/10.1787/69096873-en).
Statlink2 https://doi.org/10.1787/888934166023

Box D5.2. Attracting and retaining teachers: Insights from TALIS 2018
The Teaching and Learning International Survey (TALIS) covers about 260 000 teachers across 48 countries and
economies, and provides data on topics such as teachers’ and school leaders’ working environment, their motivations
and their job satisfaction. This box focuses on teachers’ motivations to enter the profession and on their job satisfaction,
as both factors can influence the attractiveness of the profession and teacher retention.
Looking at individuals’ motivations to become teachers helps understand what aspects of the job make it attractive. A
large share of lower secondary teachers affirm that one of their main motivations in becoming a teacher was serving a
larger social purpose. In fact, around 90% of teachers across OECD countries mention a sense of self-fulfilment through
the opportunity to influence children’s development and contribute to society. Factors related to the teaching schedule,
job security and reliability of income are reported as important motivations by around 60-70% of teachers (OECD,
2019[1]).1
The Teaching and Learning international Survey (TALIS) also offers insights into teachers’ job satisfaction, which can be
key to ensuring teacher retention. On average across OECD countries, although only 39% of lower secondary teachers
report being satisfied with their salaries, the great majority of them (90%) declare that they are, all in all, satisfied with
their job, and that they enjoy working at their current school. In addition, 76% of teachers on average report that, if they

EDUCATION AT A GLANCE 2020 © OECD 2020

434  D5. WHO ARE THE TEACHERS
could decide again, they would still choose to work as a teacher. This proportion varies significantly across countries,
however. While less than 65% of teachers would still decide to teach in Iceland, Japan, Lithuania, South Africa and
Sweden, this share rises to over 90% in Argentina (Ciudad Autónoma de Buenos Aires), Colombia and Mexico
(Figure D5.4 and (OECD, 2020[18])).
Several factors may help predict teachers’ job satisfaction. These include selecting motivated candidates who are eager
to become lifelong learners, putting an emphasis on induction and mentoring throughout teachers’ careers, and providing
opportunities for meaningful and impactful professional learning. Working conditions and school climate (e.g. a
collaborative environment), as well as factors related to trust and respect for teachers’ work, can also be key to ensuring
teachers’ satisfaction and the attractiveness of the profession (Schleicher, 2018[19]).

Figure D5.4. Lower secondary teachers' job satisfaction (2018)
Percentage of lower secondary teachers who would still choose to work as a teacher, if they could decide again1
%
100
90
80
70
60
50
40
30
20

Japan

Iceland

South Africa
Sweden

Portugal

Lithuania

Latvia

Saudi Arabia

Denmark

England (UK)
Korea

Hungary

New Zealand

Czech Republic

Turkey

France
Estonia

Norway

OECD average-31

Brazil

Slovak Republic

Belgium

Slovenia
Shanghai (China)

Israel

Finland

United States

Chile
Netherlands

Austria

Australia

Italy

Alberta (Canad a)

Spain

Mexico

0

CABA (Argentina)
Colombia

10

1. Includes teachers who “agree” or “strongly agree” with the statement: “If I could decide again, I would still decide to work as a teacher”.
Countries and economies are ranked in descending order of the percentage of teachers who would still decide to work as a teacher, if they could decide again.
Source: OECD, TALIS 2018 Database, Table II.2.10. For more information (including standard errors), see https://www.oecd.org/education/talis/talis2018tables.htm.

Statlink2 https://doi.org/10.1787/888934166042
1. The measures presented in this paragraph correspond to the percentage of lower secondary teachers who report that these elements were of “moderate” or “high”

importance in deciding to become a teacher, on average across the 31 OECD countries participating in TALIS.

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

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D5. WHO ARE THE TEACHERS  435
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. below the age of
30) among the total population of the same age group.
For more information, please see the OECD Handbook for Internationally Comparative Education Statistics 2018 (OECD,
2018[20]) and Annex 3 for country-specific notes (https://doi.org/10.1787/69096873-en).

Source
Data refer to the academic year 2017/18 and are based on the UNESCO-UIS/OECD/EUROSTAT data collection on education
statistics administered by the OECD in 2019 (for details, see Annex 3 at https://doi.org/10.1787/69096873-en).

References

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school: Evidence from a randomized experiment”, IZA Discussion Paper Series, No. 6453, Forschungsinstitut
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[10]

Beilock, S. et al. (2010), “Female teachers’ math anxiety affects girls’ math achievement”, Proceedings of the
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[13]

Croft, A. et al. (2014), “The second shift reflected in the second generation: Do parents’ gender roles at home
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[3]

Drudy, S. (2008), “Gender balance/gender bias: The teaching profession and the impact of feminisation”, Gender
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[7]

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[11]

Hutchings, M. et al. (2008), “Nice and kind, smart and funny: What children like and want to emulate in their
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[12]

Jordan, R., P. Adab and K. Cheng (2020), “Covid-19: Risk factors for severe disease and death”, BMJ, p. m1198,
http://dx.doi.org/10.1136/bmj.m1198.

[15]

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American Mathematical Society, Vol. 59/1, http://dx.doi.org/10.1090/noti790.

[4]

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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.

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OECD (2017), “Gender imbalances in the teaching profession”, Education Indicators in Focus, No. 49, OECD
Publishing, Paris, https://dx.doi.org/10.1787/54f0ef95-en.

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OECD (2015), “What lies behind gender inequality in education?”, PISA in Focus, No. 49, OECD Publishing, Paris,
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[19]

Indicator D5 Tables
Table D5.1

Gender distribution of teachers (2018)

Table D5.2

Gender distribution of teachers by age group (2018) and percentage of female teachers for all ages
(2005 and 2018)

Table D5.3

Age distribution of teachers (2018)

Cut-off date for the data: 19 July 2020. Any updates on data can be found on line at http://dx.doi.org/10.1787/eag-dataen. More breakdowns can also be found at http://stats.oecd.org/, Education at a Glance Database.

StatLink: https://doi.org/10.1787/888934165909

EDUCATION AT A GLANCE 2020 © OECD 2020

D5. WHO ARE THE TEACHERS  437

Par tners

OECD

Table D5.1. Gender distribution of teachers (2018)
Percentage of female teachers in public and private institutions by level of education, based on head counts
Upper secondary

Tertiary

Postsecondary
General
Vocational
All
nonLower
secondary programmes programmes programmes tertiary

Shortcycle
tertiary

Bachelor’s,
master’s
and
doctoral

Pre-primary

Primary

All tertiary

All levels
of
education

Countries
Australia
Austria
Belgium
Canada 1
Chile
Colombia
Costa Rica
Czech Republic
Denmark
Estonia 2
Finland
France
Germany
Greece
Hungar y
Iceland
Ireland 1, 2
Israel 1
Italy
Japan
Korea
Latvia
Lithuania
Luxembourg
Mexico
Netherlands
New Zealand
Nor way
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United Kingdom
United States

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

m
99
97
x(2)
99
97
94
100
89
99
97
91
95
99
100
94
99
99 d
99
97
99
99
99
96
96
88
97
92
98
99
100
97
93
96
97
95
96
94

m
92
83
75 d
81
77
79
94
68
90
80
83
87
72
96
83
85
86
96
64
78
92
97
76
69
87
84
74
83
81
90
89 d
77
82
83
62
86
87

m
72
64
x(2)
68
51
57
78
62
83
75
61
66
67
77
82
x(4,6)
79
77
43
71
85
82
54
54
54
67
74
75
72
76
x(2)
60
65
56
57
63
67

m
64
63
x(6)
58
x(6)
56
60
53
77
69
60
59
56
67
m
70 d
x(6)
68
x(6)
54
83
82
56
50
54
61
55
70
x(6)
74
67
58
x(6)
48
51
62
58

m
50
63
x(6)
52
x(6)
59
60
46
60 d
55
59
50
50
57
m
a
x(6)
60 d
x(6)
46
73
71
53
47
54
59
55
63
x(6)
71
67
52
x(6)
44 d
50
57 d
a

m
56
63
75
56
49
57
60
51
70 d
61
60
56
54
63
m
70 d
70
64 d
31 d
53
80
79
55
49
54
61
55
66
69 d
72
67
56
54
45 d
50
60 d
58

m
69
45
m
a
65
a
43
a
x(5, 6)
55
41
55
55
61
m
m
m
x(5, 6)
x(6, 8, 9)
a
67
65
28
a
a
54
55
69
x(6)
68
a
a
44
x(5)
a
a
x(10)

m
52
x(10)
54
m
38
52
60
40
a
a
52
45
a
x(10)
m
x(10)
90
a
50 d
45
68
a
54
m
46
49
55
70
x(10)
57
45
51
44
a
41
x(10)
x(10)

47
41
x(10)
44
m
38
44
38
44
49
52
42
40
35
x(10)
m
x(10)
46
37
23 d
33
54
56
34
m
46
50
46
45
x(10)
46
42
42
45
35
45
x(10)
x(10)

m
43
48
49
m
38
44
38
44
49
52
44
40
35
41
m
45
49
37
28 d
36
56
56
36
m
46
50
46
45
45
46
42
44
45
35
44
45
50 d

m
67
71
m
m
59
68
76
65
83
74
68
67
65
75
m
m
m
77
48
62
84
82
65
m
66
72
66
75
71
77
80
65
75
62
57
68
70

OECD average
EU23 average

96
97

82
86

67
70

62
65

56
59

60
63

55
55

53
53

43
44

44
44

70
72

Argentina
Brazil
China
India
Indonesia
Russian Federation 2
Saudi Arabia
South Africa

m
95
97
m
96
99
100
m

m
88
67
m
68
99
52
m

m
67
56
45
57
83
51
m

m
60
m
m
m
x(3)
m
m

m
50
m
m
m
x(8)
m
m

m
58
53
41
56
x(3,8)
51
58

a
47
m
m
a
x(8)
50
55

m
45
m
a
m
72 d
25
m

m
46
m
m
m
54
41
m

m
46
m
42
43
62 d
41
m

m
70
m
m
m
86
m
m

G20 average

96

78

61

m

m

55

m

m

m

43

m

Note: The data for "All levels of education" do not include early childhood educational development (ISCED 01).
1. For Canada, public institutions only at tertiary level. For Ireland, public institutions only for all levels except pre-primary. For Israel, private institutions are only included
at primary and bachelor's, master's and doctoral levels.
2. Pre-primary includes early childhood education.
Source: OECD/UIS/Eurostat (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888934165928

EDUCATION AT A GLANCE 2020 © OECD 2020

438  D5. WHO ARE THE TEACHERS
Table D5.2. Gender distribution of teachers by age group (2018) and percentage of female teachers for all ages (2005 and 2018)
Percentage of female teachers, by age group and level of education
Primar y

Lower secondar y

Upper secondary

All ter tiar y

2018

2018

2018

2018

OECD

< 30 years >= 50 years < 30 years >= 50 years < 30 years >= 50 years < 30 years >= 50 years
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)

All ter tiary

2005

2018

2005

2018

(9)

(10)

(11)

(12)

All ages

Countries
Australia
Austria
Belgium
Canada 1, 2
Chile
Colombia
Costa Rica
Czech Republic
Denmark
Estonia3
Finland
France
Germany
Greece
Hungar y
Iceland
Ireland 2
Israel 2
Italy 3
Japan 3
Korea
Latvia
Lithuania
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Por tugal3
Slovak Republic
Slovenia
Spain
Sweden
Switzerland3
Turkey
United Kingdom
United States 4

m
94
85
83 d
80
76
66
92
58
84
82
88
91
88
92
76
80
91
94
65
74
85
92
78
m
88
87
69
80
88
86
91 d
79
75
88
75
84
88

m
92
79
70 d
81
78
81
95
71
92
76
76
86
60
96
84
86
84
97
68
88
93
97
74
m
85
86
78
85
79
93
89 d
77
83
80
43
89
88

m
76
70
x(1)
70
50
56
73
53
75
77
62
79
76
69
75
x(5)
87
67
45
72
69
73
63
m
62
74
69
69
65
76
x(1)
64
56
68
67
66
69

m
73
59
x(2)
65
52
57
81
64
85
73
58
66
63
76
84
x(6)
75
77
40
60
86
82
48
m
46
67
78
75
72
78
x(2)
58
66
51
36
59
68

m
72
68
83
60
47
56
52
54
59 d
67
61
73
80
61
m
65 d
83
57 d
38 d
68
61
68
64
m
65
64
58
59
55 d
78
65
59
52
58 d
66
64 d
62

m
53
58
70
50
50
57
58
46
73 d
57
57
52
49
59
m
69 d
65
63 d
23 d
32
82
79
50
m
47
61
50
63
70 d
72
63
53
51
41 d
34
55 d
56

m
53
67
60
m
47
46
m
44
54
47
55
45
45
46
m
m
53
50
49 d
66
56
55
36
m
50
50
44
m
46
57
86
49
48
54
54
48
m

m
38
44
44
m
30
38
m
40
45
52
38
31
32
36
m
m
45
34
25 d
23
55
53
30
m
36
48
44
m
40
43
38
38
43
30
31
42
m

m
m
65 d
73
70
m
m
71 d
m
m
69
m
65
59
79
m
72
79
78
46 d
61
m
84 d
m
56
66 d
69
m
76
74 d
77
78
62
m
m
m
68
74

m
74
70
75
71
64
69
77
62
83 d
73
68
70
66
79
m
79
80
78 d
49 d
68
87
85
64
58
70
72
69
77
74 d
79
89
66
70
65 d
56
72 d
75

m
m
41
48
m
m
m
40
m
48
47
m
32
36
39
m
39
m
34
18 d
31
m
53
m
m
35
50
m
41
42 d
42
33
39
m
m
38
40
44 d

m
43
48
49
m
38
44
38
44
49
52
44
40
35
41
m
45
49
37
28 d
36
56
56
36
m
46
50
46
45
45
46
42
44
45
35
44
45
50 d

OECD average

83

82

68

66

63

56

52

39

70

72

40

44

69

72

39

44

Average for countries
with available data
for both reference years

Par tners

Total primar y
to upper secondary

EU23 average

85

85

69

69

63

60

52

40

71

74

40

44

Argentina
Brazil
China
Ind ia
Indonesia
Russian Federation 4, 5
Saudi Arabia
South Africa

m
82
m
m
m
m
m
m

m
92
m
m
m
m
m
m

m
60
m
m
m
m
m
m

m
70
m
m
m
m
m
m

m
54
m
m
m
x(7)
m
m

m
59
m
m
m
x(8)
m
m

m
50
m
m
m
64 d
m
m

m
42
m
m
m
55 d
m
m

m
m
m
m
m
86
m
m

m
72
m
m
m
87
m
m

m
m
m
m
m
51 d
m
m

m
46
m
42
43
62 d
41
m

G20 average

m

m

m

m

m

m

m

m

m

m

m

43

1. Primary includes pre-primary education.
2. For Canada, public institutions only at tertiary level. For Ireland, public institutions only. For Ireland, public institutions only. For Israel, private institutions are only included
at primary and bachelor's, master's and doctoral levels.
3. Upper secondary includes programmes outside upper secondary level. For Japan, tertiary includes programmes outside tertiary level - see Annex 3 for further details.
4. Tertiary includes programmes outside tertiary level - see Annex 3 for further details.
5. Upper secondary is included partly in lower secondary education and partly in tertiary education. Total primary to upper secondary excludes part of upper secondary
education.
Source: OECD/UIS/Eurostat (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888934165947

EDUCATION AT A GLANCE 2020 © OECD 2020

D5. WHO ARE THE TEACHERS  439

Table D5.3. Age distribution of teachers (2018)
Percentage of teachers in public and private institutions, by level of education and age group, based on head counts
Primary

Lower secondary

Upper secondary

Primary to upper secondary

Par tners

OECD

< 30 years 30-49 years >= 50 years < 30 years 30-49 years >= 50 years < 30 years 30-49 years >= 50 years < 30 years 30-49 years >= 50 years
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
(9)
(10)
(11)
(12)
Countries
Australia
Austria
Belgium
Canada1, 2
Chile
Colombia
Costa Rica
Czech Republic
Denmark
Estonia 3
Finland
France
Germany
Greece
Hungar y
Iceland
Ireland 2
Israel 2
Italy 3
Japan 3
Korea
Latvia
Lithuania
Luxembourg
Mexico
Netherlands
New Zealand
Nor way
Poland
Portugal 3
Slovak Republic
Slovenia
Spain
Sweden
Switzerland3
Turkey
Unite d Kingdom3
United States

m
18
21
10 d
19
12
8
9
15
10
8
12
9
9
6
6
14
13
1
19
18
12
5
21
m
15
13
19
7
1
7
7d
8
10
19
16
29
16

m
46
55
63 d
57
50
65
48
51
45
59
65
55
49
50
55
67
65
41
51
67
50
47
61
m
50
50
53
58
57
63
58 d
59
54
49
68
55
55

m
36
24
27 d
24
38
27
43
33
45
33
23
37
42
43
39
19
21
58
29
15
39
48
17
m
34
37
28
34
42
30
35 d
33
36
32
16
16
29

m
13
16
x(1)
19
10
11
9
15
7
8
10
6
1
4
6
x(7)
10
2
18
11
8
4
11
m
15
12
19
6
1
9
x(1)
4
8
10
26
22
16

m
40
56
x(2)
55
53
70
54
53
38
60
59
49
45
49
55
x(8)
62
44
51
59
42
44
63
m
46
48
53
63
52
53
x(2)
58
55
56
68
60
55

m
47
28
x(3)
26
37
19
37
32
55
32
32
44
54
47
39
x(9)
28
54
31
29
50
52
27
m
39
40
28
31
47
38
x(3)
38
37
35
6
18
29

m
7
14
10
19
9
11
4
4
8d
3
10
6
0
3
m
11 d
10
2d
13 d
10
8
3
10
m
11
m
8
4
2d
8
4
3
6
5d
12
17 d
12

m
46
55
63
54
53
71
43
52
40 d
48
59
55
41
56
m
63 d
57
35 d
48 d
59
41
41
63
m
43
m
49
61
57 d
49
51
58
50
52 d
73
55 d
54

m
47
31
27
27
37
19
53
43
52 d
49
32
40
59
41
m
26 d
33
63 d
39 d
31
51
56
28
m
46
m
42
35
41 d
42
45
38
44
43 d
15
28 d
34

m
13
17
10
19
11
9
7
12
9d
7
11
7
4
5
m
13
12
2d
17 d
13
9
4
15
m
14
12
16
6
1d
8
7
6
8
13 d
18
23 d
15

m
43
55
63
55
51
67
48
52
42 d
56
61
52
46
52
m
65
62
39 d
50 d
63
45
44
62
m
47
48
52
60
56 d
55
58
58
53
52 d
70
56 d
55

m
44
28
27
25
37
23
44
36
49 d
37
29
41
49
44
m
22
26
59 d
32 d
24
45
52
23
m
39
40
32
34
43 d
37
35
36
38
36 d
12
20 d
30

OECD average
EU23 average

12
11

55
54

32
35

10
9

54
52

36
40

8
6

53
50

39
43

11
9

54
52

35
38

Argentina
Brazil
China
Ind ia
Indonesia
Russian Federation
Saudi Arabia
South Africa

m
11
m
m
m
m
m
m

m
67
m
m
m
m
m
m

m
22
m
m
m
m
m
m

m
11
m
m
m
m
m
m

m
65
m
m
m
m
m
m

m
24
m
m
m
m
m
m

m
10
m
m
m
x
m
m

m
65
m
m
m
x
m
m

m
25
m
m
m
x
m
m

m
11
m
m
m
m
m
m

m
66
m
m
m
m
m
m

m
23
m
m
m
m
m
m

G20 average

m

m

m

m

m

m

m

m

m

m

m

m

1. Primary includes pre-primary education.
2. For Canada, public institutions only at tertiary level. For Ireland, public institutions only. For Israel, private institutions are included for all levels except for pre-primary and
upper secondary levels.
3. Upper secondary includes programmes outside upper secondary level - see Annex 3 for further details.
Source: OECD/UIS/Eurostat (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888934165966

EDUCATION AT A GLANCE 2020 © OECD 2020

ANNEX 1. CHARACTERISTICS OF EDUCATION SYSTEMS  441

Annex 1. Characteristics of education systems

All tables in Annex 1 are available on line at:
StatLink: https://doi.org/10.1787/888934166061

EDUCATION AT A GLANCE 2020 © OECD 2020

442  ANNEX 1. CHARACTERISTICS OF EDUCATION SYSTEMS
Table X1.1. Typical graduation ages, by level of education (2018)
The typical age refers to the age of the students at the beginning of the school year; students will generally be one year older than the
age indicated when they graduate at the end of the school year. The typical age is used for the gross graduation rate calculation.
Upper secondar y

Post secondar y
non-tertiar y

Tertiary

General programmes

Vocationa l programmes

General programmes

Vocationa l programmes

General programmes

Vocationa l programmes

First degree (3-4 years)

Long first degree
(more than 4 years)

Second or further
degree, (fo llowing a
bachelor's

Long first degree
(at least 5 years)

Second or further
degree, (fo llowing a
bachelor's

Second or further
degree, (fo llowing a
master's or equivalent
prog ramme)

Doctoral or equivalent

Master’s or equivalent

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

(13)

OECD

Bachelor’s or equivalent

Countries
Australia
Austria
Belgium
Canada
Chile
Colombia
Costa Rica
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungar y
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Lithuania
Luxembourg
Mexico
Netherlands
New Zealand
Nor way
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
Unite d Kingdom
United States

17-18
17-18
18-19
17-18
17-17
16-17
16-18
m
18-19
18-19
19-20
17-18
18-19
17-18
17-19
18-19
17-18
17-18
18-19
17-17
18-19
18-19
17-18
17-19
17-18
16-18
17-18
18-19
19-19
17-17
18-19
18-19
17-17
18-19
18-22
17-17
15-17
17-18

18-32
16-18
18-19
19-34
17-17
16-17
17-18
m
19-25
18-20
19-26
16-19
19-22
17-18
17-19
19-26
18-25
17-18
18-19
17-17
18-19
20-21
19-24
17-20
17-18
18-21
16-31
18-22
19-20
17-18
18-19
17-19
17-21
18-19
18-24
17-17
16-19
a

a
a
a
m
a
18-21
a
m
a
a
a
m
20-23
a
a
24-35
a
m
a
18-18
a
a
a
a
a
a
17-23
a
a
a
a
a
a
19-23
21-23
a
a
a

18-37
19-30
20-22
m
a
a
a
m
22-38
20-28
32-46
m
21-24
20-22
19-21
22-36
20-26
m
18-19
18-18
a
20-24
19-26
21-28
a
a
16-27
19-32
21-25
19-26
19-27
a
25- 45
19-32
a
a
a
19-22

19-24
a
a
a
a
a
20-25
m
a
a
a
m
a
a
a
a
m
m
a
19-19
a
a
a
a
a
a
18- 46
22-28
a
a
a
a
a
21-28
a
a
19-25
20-21

18-30
18-19
21-25
20-24
21-27
19-24
20-25
m
20-24
a
a
m
22-26
a
20-22
22-34
m
m
20-22
19-19
20-22
21-26
a
21-23
20-22
21-27
18-26
21-27
23-38
20-21
20-23
21-25
20-23
22-30
22-36
19-22
18-30
20-21

20-23
21-24
21-23
22-24
22-27
m
22-27
m
22-25
21-25
23-26
m
22-25
m
21-24
22-25
21-23
24-28
21-24
21-21
23-25
22-24
21-22
22-24
20-24
21-23
20-23
21-24
22-24
21-22
21-22
21-23
21-23
22-26
23-28
22-24
20-22
21-23

22-25
a
a
22-24
22-28
m
22-30
m
a
a
a
m
a
m
a
a
23-25
27-29
m
a
m
23-25
a
a
m
a
22-24
a
a
a
a
a
a
a
a
a
22-24
a

22-34
a
22-24
22-29
23-26
m
a
m
37- 48
a
a
m
24-30
m
27- 41
26-41
23-33
24-33
m
a
a
24-35
23-30
a
a
a
21-28
26-32
22-34
33-39
a
a
a
a
30-39
a
20-27
a

a
24-27
a
22-24
24-26
a
24-37
m
35-39
24-26
26-28
m
24-27
a
23-26
25 -26
m
m
24-26
23-23
a
25-29
23-24
a
a
a
a
24-26
24-25
23-24
23-24
24-25
22-25
24-28
24-29
23-24
a
a

22-30
24-28
22-24
24-29
26-35
25-34
a
m
24-27
23-28
25-30
m
24-27
m
23-26
24-33
m
27-36
24-26
23-23
25 -31
24-27
24-26
24-28
23-26
23-26
23-30
24-29
24-25
23-26
23-24
24-26
22-26
24-30
25-32
25-30
23-28
24-31

29- 44
a
23-32
24-29
m
27-39
a
m
a
a
30-41
m
24-27
m
a
a
m
m
m
m
a
a
27-29
25-31
a
24-27
a
25-29
a
a
24-30
a
28-32
a
26-32
a
22-33
24-31

26-35
28-34
27-31
29-34
29-36
31-42
27-49
m
27-32
28-34
29-37
26-30
28-32
m
27-32
28-37
27-32
31-37
27-33
26-26
29-38
28-36
28-31
28-32
24-28
28-31
27-35
28-35
29-32
28-37
26-29
27-32
28-38
28-34
28-34
30-35
25-32
26-32

Par tners

Shor t-cycle ter tiar y

Argentina 1
Brazil
China
India
Indonesia
Russian Federation
Saudi Arabia
South Africa1

18-20
16-17
18-20
16-18
19-21
17-18
18-20
19-21

18-20
16-18
18-20
16-18
19-21
17-18
18-20
19-21

m
a
m
m
m
a
m
m

m
18-26
m
m
m
18-22
m
m

22-24
m
20-22
21-23
20-22
a
20-22
21-23

22-24
19-28
20-22
21-23
20-22
19-20
20-22
21-23

22-24
20-27
22-24
21-23
23-25
21-23
22-24
22-24

22-24
a
22-24
21-23
23-25
a
22-24
22-24

m
m
m
m
m
a
m
m

a
a
a
23-25
a
22-25
24-26
a

24-26
25-31
24-26
23-25
25-27
22-25
24-26
24-26

m
a
m
m
m
a
m
m

27-29
29-37
27-29
28-30
28-30
25-27
28-30
27-29

Note: The range of typical age contain at least 50% of the share of graduation rates.
1. Year of reference 2017.
Source: OECD (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888934166080

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ANNEX 1. CHARACTERISTICS OF EDUCATION SYSTEMS  443

Short-cycle ter tiary
(1)

Bachelor’s or equivalent
(2)

Master’s or equivalent
(3)

Doctoral or equivalent
(4)

OECD

Countries
Australia
Austria
Belgium
Canada
Chile
Colombia
Costa Rica
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Lithuania
Luxembourg
Mexico
Netherlands
New Zealand
Nor way
Poland
Por tugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
Unite d Kingdom
United States

m
17-18
18-20
m
18-21
17-21
17-18
19-21
19-26
a
a
18-20
22-26
a
19-21
20-28
18-30
18-24
19-20
18-18
18-18
19-23
a
19-22
18-19
19-23
17-25
20-24
19-33
18-20
19-21
19-21
18-20
19-27
22-26
18-22
17-29
18-22

18-20
19-21
18-20
m
18-19
17-21
17-18
19-20
20-22
19-20
19-21
18-20
18-21
18-19
19-20
20-22
18-19
20-24
19-19
18-18
18-18
19-22
19-19
19-21
18-19
18-20
18-20
19-20
19-20
18-19
19-20
19-19
18-18
19-21
18-25
18-20
18-21
18-19

21-25
19-25
21-23
m
18-31
23-33
24-31
22-24
23-25
22-27
22-30
21-23
19-24
22-28
19-23
23-29
21-27
24-32
19-23
22-23
22-27
22-25
23-25
22-27
21-34
22-24
21-28
20-25
19-23
18-22
22-23
22-24
18-24
19-24
22-26
23-27
21-30
22-28

22-30
25-29
23-27
m
24-32
25-36
28-39
24-28
25-28
24-28
26-32
23-26
25-28
23-32
24-27
25-32
22-27
26-33
24-27
24-28
23-32
24-30
25-28
24-28
25-39
24-28
22-30
25-31
24-26
23-33
24-26
24-28
23-30
24-30
24-30
26-30
21-30
22-27

Par tners

Table X1.2. Typical age of entry, by level of education (2018)
The typical age refers to the age of the students at the beginning of the school year.

Argentina 1
Brazil
China
India
Indonesia
Russian Federation
Saudi Arabia
South Africa1

m
m
18-20
18-20
19-21
17-18
18-20
m

m
m
18-20
18-20
19-21
17-20
18-20
m

22-24
m
22-24
21-23
23-25
21-24
22-24
m

24-26
m
24-26
23-25
25-27
17-20
25-27
m

Note: The range of typical age contain at least 50% of the share of entry rates.
1. Year of reference 2017.
Source: OECD (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888934166099

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444  ANNEX 1. CHARACTERISTICS OF EDUCATION SYSTEMS
Table X1.3. School year and financial year used for the calculation of indicators, OECD countries
Financial year

School year

OECD

2016
2017
2018
2019
Month 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6
Australia
Austria
Belgium
Canada
Chile
Colombia
Costa Rica
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Lithuania
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Por tugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
Unite d Kingdom
United States
Month 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6
2016
2017
2018
2019

Source: OECD (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888934166118

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ANNEX 1. CHARACTERISTICS OF EDUCATION SYSTEMS  445

Table X1.4. School year and financial year used for the calculation of indicators, partner countries
Financial year

School year

Partners

2016
2017
2018
2019
Month 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6
Argentina
Brazil
China
India
Indonesia
Russian Federation
Saudi Arabia
South Africa
Month 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6
2016
2017
2018
2019

Source: OECD (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888934166137

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446  ANNEX 1. CHARACTERISTICS OF EDUCATION SYSTEMS
Table X1.5. Starting and ending age for students in compulsory education and by level of education (2018)
The age refers to the age of the students at the beginning of the school year

OECD
Par tners

Compulsor y education

Countries
Australia
Austria
Belgium
Canada
Chile
Colombia
Costa Rica
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungar y
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Lithuania
Luxembourg
Mexico
Netherlands
New Zealand
Nor way
Poland
Por tugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
Unite d Kingdom
United States
Argentina
Brazil
China
India
Indonesia
Russian Federation
Saudi Arabia
South Africa

Lower secondar y education

Upper secondar y education

Starting age
(1)

End ing age
(2)

Star ting age
(3)

Primary education
Ending age
(4)

Star ting age
(5)

Ending age
(6)

Star ting age
(7)

Ending age
(8)

6
6
6
6
6
5
4
6
6
7
7
6
6
5
3
6
6
3
6
6
6
5
7
4
3
5
5
6
6
6
6
6
6
6
4-5
5-6
4-5
4-6

17
15
18
16-18
18
16
16
15
16
16
16
16
18
14-15
16
16
16
17
16
15
14
16
16
16
17
18
16
16
16
18
16
14
16
15
15
17
16
17

5
6
6
6
6
6
6
6
6
7
7
6
6
6
7
6
5
6
6
6
6
7
7
6
6
6
5
6
7
6
6
6
6
7
7
6
4-5
6

11
9
11
11
11
10
11
10
12
12
12
10
9
11
10
12
12
11
10
11
11
12
10
11
11
11
10
12
12
11
9
11
11
12
12
9
10
11

12
10
12
12
12
11
12
11
13
13
13
11
10
12
11
13
13
12
11
12
12
13
11
12
12
12
11
13
13
12
10
12
12
13
13
10
11
12

15
13
13
14
13
14
14
14
15
15
15
14
15
14
14
15
15
14
13
14
14
15
16
14
14
14
14
15
15
14
14
14
14
15
15
13
13
14

16
14
14
15
14
15
15
15
16
16
16
15
16
15
15
16
16
15
14
15
15
16
17
15
15
15
15
16
16
15
15
15
15
16
16
14
14
15

17
17
17
17
17
16
16
18
18
18
18
17
18
17
18
19
17
17
18
17
17
18
18
18
17
17
17
18
18
17
18
18
17
18
19
17
17
17

4
4
6
6
7
7
6
7

17
17
14
13
15
17
14
15

6
6
6
6
7
7
6
7

11
10
11
10
12
10
11
13

12
11
12
11
13
11
12
14

14
14
14
13
15
15
14
15

15
15
15
14
16
16
15
16

17
17
17
17
18
17
17
18

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 (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888934166156

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ANNEX 2. REFERENCE STATISTICS  447

Annex 2. Reference statistics

All tables in Annex 2 are available on line at:
StatLink: https://doi.org/10.1787/888934166175

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448  ANNEX 2. REFERENCE STATISTICS
Table X2.1. Basic reference statistics in current prices (reference period: calendar year, 2005, 2012, 2015, 2017)

Countries
Australia
Austria
Belgium
Canada
Chile
Colombia
Costa Rica
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungar y
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Lithuania
Luxembourg
Mexico
Netherlands
New Zealand
Nor way1
Poland
Por tugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United Kingdom
United States

2005
(1)

2012
(2)

2015
(3)

2017
(4)

2005
(5)

2012
(6)

2015
(7)

2017
(8)

OECD

Total government expenditure
(in millions of local currency, current prices)

959 401
254 075
310 038
1 357 196
68 831 705
336 940 938
9 532 875
3 264 931
1 585 984
11 336
164 687
1 765 905
2 288 310
199 242
22 549 020
1 058 882
170 187
639 627
1 493 635
521 757 250
957 447 800
13 587
21 002
30 031
9 562 648
550 883
156 652
1 515 409
990 463
158 553
50 486
29 114
927 357
2 912 659
508 900
673 703
1 339 165
12 625 184

1 517 883
318 653
386 175
1 787 348
129 947 342
665 883 659
23 371 406
4 059 912
1 895 002
18 051
201 037
2 088 804
2 745 310
191 204
28 847 930
1 841 729
175 116
991 667
1 624 359
492 295 675
1 440 111 400
21 925
33 332
44 112
15 817 755
652 966
214 299
2 294 240
1 629 425
168 296
73 484
36 253
1 031 099
3 732 539
626 414
1 569 672
1 672 918
15 869 795

1 643 365
344 269
416 701
1 993 784
159 553 348
804 692 000
29 281 373
4 595 783
2 036 356
20 782
211 516
2 198 432
3 030 070
177 258
34 785 204
2 293 948
262 833
1 165 324
1 655 355
518 236 950
1 658 020 400
24 426
37 322
52 066
18 551 459
690 008
245 097
2 614 085
1 800 243
179 713
79 758
38 853
1 077 590
4 248 213
654 258
2 338 647
1 875 697
17 876 019

1 806 094
370 296
446 365
2 054 428
180 211 290
920 194 000
33 014 819
5 047 267
2 175 106
23 776
225 785
2 295 063
3 244 990
180 218
38 835 221
2 612 973
297 131
1 271 555
1 736 602
538 270 275
1 835 698 200
26 798
42 269
56 814
21 911 894
738 146
273 675
2 792 035
1 989 351
195 947
84 517
42 987
1 161 878
4 621 046
669 542
3 110 650
2 014 526
19 117 232

348 130
129 973
160 792
559 532
13 864 133
m
3 146 730
1 380 188
812 682
3 825
80 729
941 123
1 071 405
90 778
11 143 538
437 351
56 795
284 482
705 620
186 153 000
267 103 300
4 647
7 157
m
2 025 092
232 712
61 359
845 493
438 106
74 145
20 056
13 507
356 857
1 531 961
171 949
m
575 464
4 818 229

558 195
163 192
218 102
762 378
30 008 083
m
7 341 900
1 805 836
1 098 247
7 032
111 456
1 192 859
1 233 138
106 669
14 239 130
807 229
73 686
407 867
821 764
201 021 600
443 590 700
8 309
12 072
m
4 512 044
305 275
91 618
1 283 758
698 362
82 278
30 103
17 893
501 688
1 904 437
208 135
525 252
780 641
6 515 902

622 118
176 030
223 851
812 749
39 699 373
362 163 000
9 670 579
1 916 390
1 110 377
8 155
119 415
1 248 656
1 334 518
94 936
17 612 176
949 126
76 007
448 036
832 927
208 973 200
504 008 400
9 270
13 105
21 606
5 235 052
307 826
99 029
1 533 194
750 292
86 707
36 492
18 925
472 962
2 102 206
222 506
746 115
811 057
6 913 742

678 312
181 844
231 707
885 266
45 703 653
401 948 000
14 409 969
1 965 604
1 114 524
9 352
121 319
1 293 953
1 441 419
85 492
18 241 747
1 124 114
77 481
502 504
845 054
211 180 600
555 679 000
10 186
14 020
23 757
5 718 430
313 333
110 660
1 663 422
820 043
88 904
35 083
18 941
478 669
2 276 875
228 665
1 061 533
852 489
7 414 715

Par tners

Gross domestic product (GDP)
(adjusted to financial year, in millions of local currency, current prices)

Argentina
Brazil
China
Ind ia
Indonesia
Russian Federation
Saudi Arabia
South Africa

582 538
2 170 585
18 731 890
35 812 963
3 035 611 121
23 234 482
1 230 771
1 639 254

2 637 914
4 814 760
53 858 000
99 440 131
8 615 704 500
68 042 380
2 759 906
3 253 852

5 954 511
5 995 787
68 599 290
137 640 373
11 526 332 800
83 094 305
2 453 512
4 049 884

10 644 779
6 583 319
82 075 430
167 731 450
13 589 825 700
92 101 348
2 582 198
4 653 579

142 284
863 633
3 427 928
9 761 839
526 114 278
6 820 645
346 471
461 829

971 294
1 792 444
15 178 679
27 210 645
1 622 837 246
23 174 718
917 198
1 020 652

2 463 143
2 317 135
21 896 915
37 262 268
2 014 591 077
29 307 781
1 001 292
1 333 492

4 382 860
2 533 368
26 234 659
45 868 618
2 250 751 426
31 989 128
860000
1 518 601

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 (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888934166194

EDUCATION AT A GLANCE 2020 © OECD 2020

ANNEX 2. REFERENCE STATISTICS  449

Table X2.2. Basic reference statistics (reference period: calendar year, 2005, 2012, 2015, 2017)
GDP deflator (2015 = 100)

2012
(2)

2015
(3)

2017
(4)

2005
(5)

2012
(6)

2015
(7)

2017
(8)

2005
(9)

2012
(10)

2017
(11)

OECD

Population in thousands on 1st January

2005
(1)
Countries
Australia
Austria
Belgium
Canada
Chile
Colombia
Costa Rica
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Latvia
Lithuania
Luxembourg
Mexico
Netherlands
New Zealand
Nor way 1
Poland
Por tugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
Unite d Kingdom
United States

1.4
0.9
0.9
1.2
333.7
949.5
228.5
14.6
8.6
0.5
1.0
0.9
0.9
0.7
130.9
95.8
1.0
3.7
0.9
129.6
788.9
0.4
0.4
0.9
7.1
0.9
1.5
9.0
1.9
0.7
0.6
0.6
0.8
9.5
1.7
0.8
0.7
1.0

1.5
0.8
0.8
1.2
347.2
1 182.0
355.0
13.3
7.6
0.5
0.9
0.8
0.8
0.7
125.6
137.0
0.8
4.0
0.7
104.3
854.9
0.5
0.5
0.9
7.9
0.8
1.5
9.0
1.8
0.6
0.5
0.6
0.7
8.7
1.4
1.0
0.7
1.0

1.5
0.8
0.8
1.2
391.4
1 209.0
386.9
12.9
7.3
0.5
0.9
0.8
0.8
0.6
132.5
141.9
0.8
3.9
0.7
103.4
857.4
0.5
0.4
0.9
8.3
0.8
1.5
9.9
1.8
0.6
0.5
0.6
0.7
8.9
1.2
1.2
0.7
1.0

1.5
0.8
0.8
1.2
411.3
1 297.1
392.9
12.4
6.9
0.5
0.9
0.8
0.7
0.6
134.4
137.1
0.8
3.7
0.7
105.4
871.7
0.5
0.4
0.8
8.9
0.8
1.5
9.9
1.7
0.6
0.5
0.6
0.6
8.7
1.2
1.4
0.7
1.0

20 177
8 225
10 479
32 242
16 283
42 889
4 214
10 234
5 419
1 359
5 246
63 168
81 337
10 987
10 087
296
4 160
6 961
58 191
127 755
48 185
2 239
3 323
466
107 000
16 320
4 148
4 623
38 161
10 503
5 387
2 001
43 663
9 030
7 482
68 435
60 413
295 993

22 734
8 426
11 107
34 751
17 450
46 582
4 651
10 509
5 591
1 325
5 414
65 651
80 426
11 045
9 920
321
4 597
7 907
60 339
127 552
50 200
2 034
2 988
532
116 885
16 755
4 418
5 019
38 534
10 515
5 406
2 057
46 766
9 519
7 997
75 176
63 705
314 255

23 816
8 630
11 274
35 703
18 045
48 203
4 830
10 543
5 682
1 313
5 481
66 581
81 687
10 821
9 843
331
4 696
8 377
60 731
127 110
51 015
1 977
2 905
569
120 846
16 940
4 635
5 191
38 455
10 358
5 422
2 063
46 410
9 799
8 282
78 218
65 110
321 026

24 602
8 795
11 375
36 540
18 522
49 292
4 945
10 590
5 767
1 316
5 508
67 063
82 657
10 755
9 788
343
4 802
8 710
60 537
126 706
51 362
1 941
2 828
597
123 364
17 131
4 832
5 277
38 422
10 300
5 438
2 066
46 533
10 058
8 452
80 313
66 040
325 410

79.2
83.0
85.4
84.1
62.8
65.5
49.3
87.1
83.9
63.2
81.9
88.1
87.3
90.4
71.0
56.1
91.6
80.7
86.0
104.1
82.9
64.6
71.7
75.0
64.2
88.7
80.1
73.5
80.6
87.1
91.3
83.9
90.1
83.6
94.1
47.6
82.5
83.5

99.8
94.1
96.5
97.3
88.2
93.3
87.6
95.1
97.7
92.3
94.4
97.5
94.6
104.7
91.5
89.4
91.8
94.2
97.1
96.5
95.1
96.7
97.7
95.5
91.8
97.7
94.2
93.0
98.5
95.2
99.9
97.0
99.3
95.3
101.2
81.2
95.8
95.5

105.6
102.8
103.5
103.2
109.7
110.5
104.6
102.7
101.4
105.4
100.9
101.0
102.2
100.4
104.7
102.3
100.8
101.3
101.8
100.0
104.3
103.9
105.9
102.5
112.4
101.7
105.5
103.8
102.2
103.3
100.7
102.3
101.7
103.7
98.8
119.9
104.1
102.9

Par tners

Purchasing power parity for GDP (PPP) (USD = 1)

Argentina
Brazil
China
Ind ia
Indonesia
Russian Federation
Saudi Arabia
South Africa

1.1
1.1
2.8
10.4
2 012.5
12.7
1.3
3.5

3.2
1.6
3.5
16.0
3 671.5
18.5
1.9
4.9

6.7
1.9
3.5
17.1
4 032.3
23.6
1.4
5.5

11.6
2.0
3.5
17.8
4 181.1
24.1
1.5
6.1

38 592
184 991
1 307 560
1 114 238
221 204
143 519
23 906
47 602

41 733
198 315
1 354 040
1 235 000
245 425
143 202
29 086
52 325

43 132
203 476
1 374 620
1 283 000
255 462
146 406
31 557
54 750

44 045
206 805
1 390 080
1 316 896
261 891
146 842
32 613
56 522

13.4
47.7
68.2
53.9
45.7
36.0
85.6
52.6

45.4
80.2
97.1
89.3
86.9
82.0
124.7
84.9

177.8
111.9
105.0
107.1
106.8
108.7
104.3
112.9

1. The GDP Mainland market value is used for Norway.
Source: OECD (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888934166213

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450  ANNEX 2. REFERENCE STATISTICS
Table X2.3. 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 (2019)

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. Data on pre-primary teachers include the salaries of kindergarten teachers who are the majority.
2. Excludes the social security contributions and pension-scheme contributions paid by the employees.
3. Actual base salaries.
Source: OECD (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888934166232

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ANNEX 2. REFERENCE STATISTICS  451

Table X2.4. Secondary teachers' statutory salaries at different points in their careers, for teachers with the most prevalent
qualifications defined at different points in teachers' careers (2019)

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. 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).
3. Excludes the social security contributions and pension-scheme contributions paid by the employees.
4. Actual base salaries.
Source: OECD (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888934166251
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452  ANNEX 2. REFERENCE STATISTICS
Table X2.5. Trends in average teachers' actual salaries, in national currency (2000, 2005, 2010 to 2019)

Average annual salary (including bonuses and allowances) of teachers aged 25-64

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ANNEX 2. REFERENCE STATISTICS  453

Note: Years 2011 to 2017 (i.e. Columns 4 to 10, 16 to 22, 28 to 34 and 40 to 46) 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. At pre-primary and primary levels actual salaries refer to all teachers/school heads in those levels of education combined, including special needs education. At lower
and upper secondary levels, actual salaries refer to all teachers/school heads in those levels of education combined, including vocational and special needs education.
5. Also includes data on actual salaries of preschool teachers' assistants for pre-primary education for 2011-2015.
6. Average actual teachers’ salaries.
7. Includes all teachers, irrespective of their age.
8. Average actual teachers' salaries for all teachers, irrespective of the level of education they teach.
Source: OECD (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888934166270

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454  ANNEX 2. REFERENCE STATISTICS
Table X2.6. Reference statistics used in calculating teachers' salaries (2000, 2005 to 2019)

Note: Private consumption deflators for years 2006 to 2009, 2011 to 2014 and 2016 to 2018 (i.e. Columns 8 to 11, 13 to 16 and 18 to 20) 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. 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 (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888934166289

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ANNEX 2. REFERENCE STATISTICS  455

Table X2.7. Distribution of teachers by minimum or most prevalent qualifications and level of education (2019)
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.
1. Year of reference is 2018
Source: OECD (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888934166308

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456  ANNEX 2. REFERENCE STATISTICS
Table X2.8. Distribution of teachers aged 25-64 by educational attainment and level of education (2019)

Note: See Definitions and Methodology sections for more information. Data available at http://stats.oecd.org/, Education at a Glance Database.
1. Year of reference 2018.
2. Data for pre-primary level refer to pre-primary and primary combined. Data for lower secondary level refer to lower secondary and upper secondary combined.
3. Year of reference 2017.
Source: OECD (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888934166327

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ANNEX 2. REFERENCE STATISTICS  457

Table X2.9. Distribution of school heads aged 25-64 by educational attainment and level of education (2019)

Note: See Definitions and Methodology sections for more information. Data available at http://stats.oecd.org/, Education at a Glance Database.
1. Year of reference 2018.
2. Year of reference 2017.
Source: OECD (2020). See Source section for more information and Annex 3 for notes (https://doi.org/10.1787/69096873-en).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Statlink2 https://doi.org/10.1787/888934166346

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ANNEX 3. SOURCES, METHODS AND TECHNICAL NOTES  459

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/10.1787/69096873-en

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CONTRIBUTORS TO THIS PUBLICATION  461

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 2020: OECD Indicators.
The OECD wishes to thank them all for their valuable efforts.

INES Working Party
Ms Ana COPES (Argentina)

Ms Amanda HODGKINSON (Canada)

Mr Juan Manuel CORVALAN ESPINA (Argentina)

Ms Robin Liu HOPSON (Canada)

Ms Inés CRUZALEGUI (Argentina)

Mr David McBRIDE (Canada)

Mr Karl BAIGENT (Australia)

Ms Klarka ZEMAN (Acting Chair INES Working Party,
Canada)

Mr Stuart FAUNT (Australia)
Mr. Edward HARVEY (Australia)
Ms Kee HIAUJOO (Australia)
Ms Rebecca SMEDLEY (Australia)
Ms Sabine MARTINSCHITZ (Austria)
Mr Mark NÉMET (Austria)
Mr Wolfgang PAULI (Austria)
Ms Helga POSSET (Austria)
Ms Natascha RIHA (Austria)
Mr Philippe DIEU (Belgium)
Ms Isabelle ERAUW (Belgium)
Ms Nathalie JAUNIAUX (Belgium)
Mr Guy STOFFELEN (Belgium)
Mr Raymond VAN DE SIJPE (Belgium)
Ms Ann VAN DRIESSCHE (Belgium)
Mr Pieter VOS (Belgium)
Mr Daniel Jaime CAPISTRANO DE OLIVEIRA (Brazil)
Ms Juliana MARQUES DA SILVA (Brazil)
Ms.Rachel RABELO (Brazil)
Mr Patric BLOUIN (Canada)
Mr. Gregory BYLINSKI (Canada)
Ms Jennifer CHEW LEUNG (Canada)

Ms Rosario DEL VILLAR (Chile)
Ms Javiera IBACACHE (Chile)
Mr Ignacio LARRAGUIBEL (Chile)
Ms Paola LEIVA (Chile)
Ms.Francisca MULLER (Chile)
Mr Fabián RAMÍREZ (Chile)
Mr Juan SALAMANCA (Chile)
Ms Claudia DÍAZ (Colombia)
Ms Helga Milena HERNÁNDEZ (Colombia)
Mr Javier Andrés RUBIO (Colombia)
Mr Wilfer VALERO (Colombia)
Ms Azucena Paola VALLEJO (Colombia)
Ms Elsa Nelly VELASCO (Colombia)
Ms Erika VILLAMIL (Colombia)
Ms Carolina CHAVES (Costa Rica)
Mr Andrés FERNÁNDEZ (Costa Rica)
Ms Eliecer RAMIREZ (Costa Rica)
Ms Paula VILLALTA (Costa Rica)
Mr Vladimír HULÍK (Czech Republic)
Ms Michaela MARŠÍKOVÁ (Czech Republic)
Mr Lubomír MARTINEC (Czech Republic)
Mr Jens BJERRE (Denmark)

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462  CONTRIBUTORS TO THIS PUBLICATION
Mr Thomas LARSEN (Denmark)

Ms Hedvig SZABÓ (Hungary)

Ms Susanne Irvang NIELSEN (Denmark)

Mr Gunnar J. ÁRNASON (Iceland)

Mr Frederik SMITH (Denmark)

Ms Ásta M. URBANCIC (Iceland)

Ms Ken THOMASSEN (Denmark)

Ms Swapna BHATTACHARYA (India)

Ms Tiina ANNUS (Estonia)

Mr Tayyab MOHAMMAD (India)

Ms Katrin REIN (Estonia)

Mr Pádraig BROCK (Ireland)

Ms Kadi SERBAK (Estonia)

Ms Deirdre CULLEN (Ireland)

Mr Arnaud DESURMONT (Eurostat, European
Commission)

Ms Mary GILBRIDE (Ireland)

Ms Malgorzata STADNIK (Eurostat, European
Commission)
Mr Jukka HAAPAMÄKI (Finland)
Mr Mika TUONONEN (Finland)
Ms Kristiina VOLMARI (Finland)
Ms Nathalie CARON (France)
Ms Alexandra FARRUGIA (France)
Ms Pascaline FEUILLET (France)
Ms Isaure LEFEUVRE (France)
Ms Valérie LIOGIER (France)
Ms Clotilde LIXI (France)
Mr. Michael ORAND (France)
Ms Pascale POULET-COULIBANDO (France)
Mr Robert RAKOCEVIC (France)
Ms Sylvie ROUSSEAU (France)
Ms Julie SOLARD (France)
Mr Boubou TRAORE (France)
Mr Frédéric BLAESCHKE (Germany)
Ms Pia BRUGGER (Germany)
Mr Hans-Werner FREITAG (Germany)
Mr Michael LENZEN (Germany)
Mr Benny SCHNEIDER (Germany)
Mr Martin SCHULZE (Germany)
Ms Susanne ZIEMEK (Germany)
Ms Dimitra FARMAKIOTOU (Greece)
Ms Maria FASSARI (Greece)
Mr Antonios KRITIKOS (Greece)
Ms Vassiliki MAKRI (Greece)
Mr Athanasios STAVROPOULOS (Greece)
Mr István BUCSI SZABÓ (Hungary)
Ms Sára HATONY (Hungary)

Ms Violeta MOLONEY (Ireland)
Ms Sophie ARTSEV (Israel)
Mr Yoav AZULAY (Israel)
Ms Orit BARANY (Israel)
Mr Matan CHOCRON (Israel)
Ms Hana COHEN (Israel)
Ms Merav KATZ (Israel)
Mr Daniel LEVI-MAZLOUM (Israel)
Ms Orit LEVIN (Israel)
Ms Iris Avigail MATATYAHU (Israel)
Mr Dov NATAN (Israel)
Mr Haim PORTNOY (Israel)
Ms Michal SALANSKI (Israel)
Mr Dan SCHEINBERG (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)
Mr Takashi FURUDATE (Japan)
Mr Yu KAMEOKA (Japan)
Mr Tetsuya KASHIHARA (Japan)
Ms Saki KISHIDA (Japan)
Mr Mutsuhisa KISHIMOTO (Japan)
Mr Tetsuya KISHIMOTO (Japan)
Ms Rumiko MORI (Japan)
Mr Hongbo CHOI (Korea)
Ms Yukyung HA (Korea)

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CONTRIBUTORS TO THIS PUBLICATION  463
Ms Hyojin HAN (Korea)

Mr.Thijs NOORDZIJ (Netherlands)

Ms Hyojung HAN (Korea)

Mr Joost SCHAACKE (Netherlands)

Ms Seongkyeong JEONG (Korea)

Ms Priscilla TEDJAWIRJA (Netherlands)

Mr Sunghun KANG (Korea)

Ms Anouschka VAN DER MEULEN (Netherlands)

Ms Hannah KIM (Korea)

Mr. Gregory KEEBLE (New Zealand)

Ms Jiyoung KIM (Korea)

Ms.Rebecca PARISH (New Zealand)

Ms Solhwi KIM (Korea)

Ms. Fernanda PIRAUD (New Zealand)

Ms Youngok KIM (Korea)

Mr David SCOTT (New Zealand)

Ms Eunji LEE (Korea)

Ms. Debra TAYLOR (New Zealand)

Ms Wonhee NA (Korea)

Mr Sadiq Kwesi BOATENG (Norway)

Mr Jaehyoung OH (Korea)

Ms Kristin Mathilde DRAHUS (Norway)

Ms Jongeun PARK (Korea)

Mr Øyvind KLUBBEN LEKNESSUND (Norway)

Mr Sungho PARK (Korea)

Mr Geir NYGÅRD (Norway)

Ms Taeyeon SHIN (Korea)

Ms Anne Marie RUSTAD HOLSETER (Norway)

Ms Youngho SON (Korea)

Ms Alette SCHREINER (Norway)

Mr Min SUNG (Korea)

Mr Piotr JAWORSKI (Poland)

Ms Ieva ERVALDE (Latvia)

Ms Renata KORZENIOWSKA-PUCUŁEK (Poland)

Ms Inta JAUNZEME (Latvia)

Mr Andrzej KURKIEWICZ (Poland)

Mr Viktors KRAVČENKO (Latvia)

Ms Anna NOWOŻYŃSKA (Poland)

Ms Brigita KUKJALKO (Latvia)

Ms Magdalena WIKTOR (Poland)

Mr Rolands ŅIKITINS (Latvia)

Ms Hanna ZIELIŃSKA (Poland)

Ms Anita ŠVARCKOPFA (Latvia)

Ms Mónica LUENGO (Portugal)

Mr Ričardas ALIŠAUSKAS (Lithuania)

Mr Carlos Alberto MALACA (Portugal)

Ms Salvinija CHOMIČIENĖ (Lithuania)

Ms Rute NUNES (Portugal)

Ms Ugnė CIBULSKAITĖ (Lithuania)

Mr Marco PIMENTA (Portugal)

Ms Rita DUKYNAITĖ (Lithuania)

Ms Dora PEREIRA (Portugal)

Ms Daiva MARCINKEVIČIENĖ (Lithuania)

Mr José RAFAEL (Portugal)

Ms Elisa MAZZUCATO (Luxembourg)

Mr Nuno Miguel RODRIGUES (Portugal)

Mr Marco CALDERÓN ARGOMEDO (Mexico)

Mr Joaquim SANTOS (Portugal)

Mr Luis DEGANTE MÉNDEZ (Mexico)

Mr Amaro VIEIRA (Portugal)

Mr René GÓMORA CASTILLO (Mexico)

Mr Mark AGRANOVICH (Russian Federation)

Mr Alberto MAYORGA RÍOS (Mexico)

Ms Julia ERMACHKOVA (Russian Federation)

Ms. Alicia del Rosario NAVA CARDONA (Mexico)

Ms Irina SELIVERSTOVA (Russian Federation)

Mr Tomás RAMÍREZ REYNOSO (Mexico)

Mr Abdulrahman S. AL-ANGARI (Saudi Arabia)

Ms María del Carmen REYES GUERRERO (Mexico)

Mr Saad ALBAIZ (Saudi Arabia)

Mr Gerardo H. TERRAZAS GONZÁLEZ (Mexico)

Mr Peter BRODNIANSKY (Slovak Republic)

Mr Lorenzo VERGARA LÓPEZ (Mexico)

Ms Eva HLADIKOVA (Slovak Republic)

Ms Danielle ANDARABI (Netherlands)

Ms Danica OMASTOVA (Slovak Republic)

Mr Maarten BALVERS (Netherlands)

Mr Roman SAJBIDOR (Slovak Republic)

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464  CONTRIBUTORS TO THIS PUBLICATION
Ms Gabriela SLODICKOVA (Slovak Republic)

Mr Jaime VAQUERO JIMÉNEZ (Spain)

Ms Tanja DOMIJAN (Slovenia)

MS Isabel YUN MORENO (Spain)

Ms Andreja KOZMELJ (Slovenia)

Mr Mattias FRITZ (Sweden)

Ms Barbara KRESAL STERNIŠA (Slovenia)

Ms Maria GÖTHERSTRÖM (Sweden)

Ms Duša MARJETIČ (Slovenia)

Ms Marie KAHLROTH (Sweden)

Ms Tatjana ŠKRBEC (Slovenia)

Mr Alexander GERLINGS (Switzerland)

Ms Jadranka TUŠ (Slovenia)

Ms Katrin HOLENSTEIN (Switzerland)

Ms Rirhandzu BALOYI (South Africa)

Ms Nicole SCHÖBI (Switzerland)

Ms Mamphokhu KHULUVHE (South Africa)

Mr Emanuel VON ERLACH (Switzerland)

Ms Letho MAPASEKA (South Africa)

Ms Hatice Gülşah AYGÖRMEZ (Turkey)

Ms Bheki MPANZA (South Africa)

Ms Fatma Filiz ÇİÇEK (Turkey)

Ms Hersheela NARSEE (South Africa)

Ms Hatice Nihan ERDAL (Turkey)

Ms Matome SEKGOTA (South Africa)

Ms Gülçin ÖZ (Turkey)

Ms Nthabiseng TEMA (South Africa)

Mr Friedrich HUEBLER (UNESCO)

Mr Miguel Ángel ÁLVAREZ ESPINOSA (Spain)

Ms Anuja SINGH (UNESCO)

Ms Elena BANDA LÓPEZ (Spain)

Ms Aliki PAREAS (United Kingdom)

Mr. José María GALLEGO ALONSO-COLMENARES
(Spain)

Ms Mary COLEMAN (United States)

Ms. Laura GUERRERO GÓMEZ (Spain)
Mr Jesús IBAÑEZ MILLA (Spain)
Mr. Ricardo MARTÍNEZ ZAMORANO (Spain)

Mr Cristobal DE BREY (United States)
Ms Rachel DINKES (United States)
Ms Jana KEMP (United States)
Ms Ashley ROBERTS (United States)

Ms Ana REVILLA TRUJILLO (Spain)
Ms Carmen TOVAR SÁNCHEZ (Spain)

Network on Labour Market, Economic and Social Outcomes of Learning (LSO)
Mr Karl BAIGENT (Australia)

Mr Marco SERAFINI (CEDEFOP)

Mr Stuart FAUNT (Australia)

Mr Daniel SCHEUREGGER (CEDEFOP)

Ms Kee HIAUJOO (Australia)

Mr Ignacio LARRAGUIBEL (Chile)

Ms Rebecca SMEDLEY (Australia)

Ms Paola LEIVA (Chile)

Mr Mark NÉMET (Austria)

Mr Fabián RAMÍREZ (Chile)

Ms Isabelle ERAUW (Belgium)

Mr Roberto SCHURCH (Chile)

Ms Geneviève HINDRYCKX (Belgium)

Ms Constanza VIELMA (Chile)

Mr Kasper OSSENBLOK (Belgium)

Mr Vladimír HULÍK (Czech Republic)

Ms Naomi WAUTERICKX (Belgium)

Ms Michaela MARŠÍKOVÁ (Czech Republic)

Ms Christyne CARVALHO DA SILVA (Brazil)

Ms Lidia GONZÁLEZ (Costa Rica)

Mr Carlos Augusto DOS SANTOS ALMEIDA (Brazil)

Ms Dianny HERNÁNDEZ RUÍZ (Costa Rica)

Mr Patric BLOUIN (Canada)

Ms María Luz SANARRUSIA SOLANO (Costa Rica)

Mr Gregory BYLINSKI (Canada)

Mr Jens ANDERSEN (Denmark)

Ms Annik FOREMAN (Canada)

Ms Tiina ANNUS (Estonia)

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CONTRIBUTORS TO THIS PUBLICATION  465
Ms Kristel BANKIER (Estonia)

Ms Liana VERZICCO (Italy)

Ms Ingrid JAGGO (Estonia)

Ms Yukyung HA (Korea)

Mr Priit LAANOJA (Estonia)

Ms Jongeun PARK (Korea)

Ms Marianne LEPPIK (Estonia)

Mr Min SUNG (Korea)

Mr Marti Lillemägi (Estonia)

Ms Heekyung CHO (Korea)

Ms Kaire Raasik (Estonia)

Mr Jungseung YANG (Korea)

Ms Aune VALK (Estonia)

Mr Sungho PARK (Korea)

Mr Jens FISHER-KOTTENSTEDE (European
Commission)

Ms Hyeja KIM (Korea)

Mr Mantas SEKMOKAS (European Commission)
Ms Elodie CAYOTTE (Eurostat, European Commission)
Ms Sabine GAGEL (Eurostat, European Commission)
Ms Irja BLOMQVIST (Finland)
Mr Mika WITTING (Finland)
Mr Michael ORAND (France)
Ms Pascale POULET-COULIBANDO (France)
Mr Hans-Werner FREITAG (Germany)
Ms Sylvia SCHILL (Germany)
Ms Susanne ZIEMEK (Germany)
Ms Maria FASSARI (Greece)
Ms Vassilliki MAKRI (Greece)
Mr Georgios NTOUROS (Greece)
Mr Dimitrios VATIKIOTIS (Greece)
Mr László LIMBACHER (Hungary)
Mr István BUCSI SZABÓ (Hungary)
Ms Ásta M. URBANCIC (Iceland)
Ms Deirdre CULLEN (Ireland)
Ms Helen MAXWELL (Ireland)
Ms Violeta MOLONEY (Ireland)
Ms Tracey SHANKS (Ireland)
Ms Sarah Crilly (Ireland)
Mr Steven Lucas (Ireland)
Ms Sophie ARTSEV (Israel)
Ms Hana COHEN (Israel)
Ms Lior DUPAZ (Israel)
Mr Mark FELDMAN (Israel)
Ms Hagit SARID (Israel)
Ms Raffaella CASCIOLI (Italy)
Mr Gaetano PROTO (Italy)

EDUCATION AT A GLANCE 2020 © OECD 2020

Mr Yeoncheon KIM (Korea)
Ms Ruta BEINĀRE (Latvia)
Ms Sandra CERIŅA (Latvia)
Mr Jānis KLIĢIS (Latvia)
Mr Viktors Kravčenko (Latvia)
Ms Zaiga PRIEDE (Latvia)
Mr Eduardas DAUJOTIS (Lithuania)
Mr Gintautas JAKŠTAS (Lithuania)
Ms Vaida KOSTYGOVA (Lithuania)
Mr Dalius POŽĖLA (Lithuania)
Ms Karin MEYER (Luxembourg)
Mr Gerardo H. TERRAZAS GONZÁLEZ (Mexico)
Mr Ted REININGA (Netherlands)
Ms Francis VAN DER MOOREN (Netherlands)
Ms Antoinette VAN WANROIJ (Netherlands)
Ms Megan CHAMBERLAIN (New Zealand)
Ms Jessica FORKERT (New Zealand)
Mr David JAGGER (New Zealand)
Ms Nicola MARSHALL (New Zealand)
Mr Aaron NORGROVE (New Zealand)
Ms Beth RUST (New Zealand)
Mr David SCOTT (New Zealand)
Mr Zane VERRAN (New Zealand)
Ms Hild Marte BJØRNSEN (Norway)
Mr Sadiq-Kwesi BOATENG (Norway)
Mr Nawid FAZLI (Norway)
Mr Jacek MAŚLANKOWSKI (Poland)
Ms Anna NOWOŻYŃSKA (Poland)
Mr Carlos Alberto MALACA (Portugal)
Mr Joaquim SANTOS (Portugal)
Mr Mark AGRANOVICH (Russian Federation)

466  CONTRIBUTORS TO THIS PUBLICATION
Ms Elena SABELNIKOVA (Russian Federation)

Ms Wayra CABALLERO LIARDET (Switzerland)

Mr Frantisek BLANAR (Slovak Republic)

Mr Emanuel VON ERLACH (Chair LSO Network,
Switzerland)

Mr Matej DIVJAK (Slovenia)
Ms Melita SELJAK (Slovenia)
Mr Miguel Ángel ÁLVAREZ ESPINOSA (Spain)
Mr Jesús IBAÑEZ MILLA (Spain)
Mr Raúl SAN SEGUNDO (Spain)
Ms Ann-Charlott LARSSON (Sweden)
Mr Mattias FRITZ (Sweden)

Mr Davut OLGUN (Turkey)
Mr Cengiz SARAÇOĞLU (Turkey)
Mr Thomas LOCKHART (United Kingdom)
Ms Rachel DINKES (United States)
Ms Ashley ROBERTS (United States)
Mr Cristobal DE BREY (United States)

Ms Anna BENGTSSON (Sweden)

Network for the Collection and Adjudication of System-level descriptive Information
on Educational Structures, Policies and Practices (NESLI)
Mr Karl BAIGENT (Australia)

Mr Jelen VÁCLAV (Czech Republic)

Mr Stuart FAUNT (Australia)

Mr Thomas LARSEN (Denmark)

Ms Antonella SALPIETRO (Australia)

Mr Jorgen Balling RASMUSSEN (Denmark)

Ms Rebecca SMEDLEY (Australia)

Mr Frederik SMITH (Denmark)

Mr Stefan POLZER (Austria)

Ms Tiina ANNUS (Chair of NESLI Network, Estonia)

Mr Philippe DIEU (Belgium)

Ms Hanna KANEP (Estonia)

Ms Nathalie JAUNIAUX (Belgium)

Ms Kristel VAHER (Estonia)

Ms Bernadette SCHREUER (Belgium)

Ms Hille Vares (Estonia)

Mr Raymond VAN DE SIJPE (Belgium)

Ms Nathalie BAIDAK (Eurydice)

Ms Ann VAN DRIESSCHE (Belgium)

Ms Sonia PIEDRAFITA-TREMOSA (Eurydice)

Ms Christyne CARVALHO DA SILVA (Brazil)

Ms Petra PACKALEN (Finland)

Ms Camila NEVES SOUTO (Brazil)

Ms Kristiina VOLMARI (Finland)

Ms Rachel PEREIRA RABELO (Brazil)

Ms. Marion DEFRESNE (France)

Ms Jennifer CHEW LEUNG (Canada)

Ms Alexandra FARRUGIA (France)

Mr Brett WILMER (Canada)

Ms Anne GAUDRY-LACHET (France)

Mr Gregory BYLINSKI (Canada)

Mr Louis MEURIC (France)

Mr Ignacio LARRAGUIBEL (Chile)

Mr Robert RAKOCEVIC (France)

Ms Paola LEIVA (Chile)

Ms. Julie SOLARD (France)

Mr Fabián RAMÍREZ (Chile)

Mr Thomas ECKHARDT (Germany)

Mr Roberto SCHURCH (Chile)

Mr Benny SCHNEIDER (Germany)

Ms Constanza VIELMA (Chile)

Mr Marco MUNDELIUS (Germany)

Mr Andrés FERNÁNDEZ (Costa Rica)

Ms Dimitra FARMAKIOUTOU (Greece)

Ms Carolina CHAVES (Costa Rica)

Ms Maria FASSARI (Greece)

Mr Vladimír HULÍK (Czech Republic)

Ms Vassilliki MAKRI (Greece)

Ms Michaela MARŠÍKOVÁ (Czech Republic)

Mr Panagiotis PASSAS (Greece)

Mr Lubomír MARTINEC (Czech Republic)

Ms Sára HATONY (Hungary)
EDUCATION AT A GLANCE 2020 © OECD 2020

CONTRIBUTORS TO THIS PUBLICATION  467
Mr István BUCSI SZABÓ (Hungary)

Ms Elisa MAZZUCATO (Luxembourg)

Mr Gunnar J. ÁRNASON (Iceland)

Mr Alberto MAYORGA RÍOS (Mexico)

Ms Asta URBANCIC (Iceland)

Mr Marco CALDERÓN ARGOMEDO (Mexico)

Ms Deirdre CULLEN (Ireland)

Mr Thijs NOORDZIJ (Netherlands)

Ms. Mary GILBRIDE (Ireland)

Mr Hans RUESINK (Netherlands)

Ms Violeta MOLONEY (Ireland)

Mr Jerry STRATEN (Netherlands)

Mr Steven LUCAS (Ireland)

Mr Dick VAN VLIET (Netherlands)

Mr Yoav AZULAY (Israel)

Ms Rebecca PARISH (New Zealand)

Ms Hana COHEN (Israel)

Ms Kirsti RAWSTRON (New Zealand)

Mr Pinhas KLEIN (Israel)

Mr David SCOTT (New Zealand)

Mr Aviel KRENTZLER (Israel)

Ms Alexandra MCGREGOR (New Zealand)

Mr Daniel LEVI-MAZLOUM (Israel)

Mr Gregory KEBBLE (New Zealand)

Mr David MAAGAN (Israel)

Mr Øyvind Klubben LEKNESSUND (Norway)

Ms Gianna BARBIERI (Italy)

Ms Barbara ANTOSIEWICZ (Poland)

Ms Lucia DE FABRIZIO (Italy)

Ms Renata KARNAS (Poland)

Ms Annarita Lina MARZULLO (Italy)

Ms Renata KORZENIOWSKA-PUCUŁEK (Poland)

Mr Michele SCALISI (Italy)

Ms Anna NOWOŻYŃSKA (Poland)

Mr Takashi FURUDATE (Japan)

Mr Joaquim SANTOS (Portugal)

Mr Yu KAMEOKA (Japan)

Mr Mark AGRANOVICH (Russian Federation)

Ms Saki KISHIDA (Japan)

Ms Julia ERMACHKOVA (Russian Federation)

Ms Yukyung HA (Korea)

Ms Eva HLADIKOVA (Slovak Republic)

Ms Jongeun PARK (Korea)

Ms Gabriela SLODICKOVA (Slovak Republic)

Mr Min SUNG (Korea)

Ms Barbara KRESAL-STERNIŠA (Slovenia)

Mr Sungho PARK (Korea)

Ms Duša MARJETIČ (Slovenia)

Ms Hyojung HAN (Korea)

Ms Karmen SVETLIK (Slovenia)

Ms Nayoung KIM (Korea)

Ms Tanja TAŠTANOSKA (Slovenia)

Ms Hannah KIM (Korea)

Mr Juan Carlos GIRÓN ORTEGA (Spain)

Ms Youngho SON (Korea)

Mr Jaime VAQUERO JIMÉNEZ (Spain)

Ms Jiyoung KIM (Korea)

Mr David VARAS DEL PESO (Spain)

Ms Modra JANSONE (Latvia)

Ms Karin Zetterberg GRÜNEWALD (Sweden)

Mr Viktors KRAVČENKO (Latvia)

Mr Tomas GUSTAVSSON (Sweden)

Mr Evaldas BAKONIS (Lithuania)

Ms Katrin MÜHLEMANN (Switzerland)

Ms Daiva JAKAVONYTĖ-STAŠKUVIENĖ (Lithuania)

Ms Fatma Filiz ÇİÇEK (Turkey)

Mr Linas JAŠINAUSKAS (Lithuania)

Ms Gülçin ÖZ (Turkey)

Ms Vitalija NAUDŽIUVIENĖ (Lithuania)

Mr Osman Yıldırım UĞUR (Turkey)

Ms Rima ZABLACKĖ (Lithuania)

Ms Sarah CROSS (United Kingdom)

Mr Gilles HIRT (Luxembourg)

Mr James DEATON (United States)

Ms Charlotte MAHON (Luxembourg)

Ms Jana KEMP (United States)

EDUCATION AT A GLANCE 2020 © OECD 2020

468  CONTRIBUTORS TO THIS PUBLICATION

Other contributors to this publication
BRANTRA SPRL (Translation)

Ms Fung Kwan TAM (Layout)

Ms Sally Caroline HINCHCLIFFE (Edition)

EDUCATION AT A GLANCE 2020 © OECD 2020

EDUCATION INDICATORS IN FOCUS  469

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
“What role might the social outcomes of education play during the COVID-19 lockdown?”, Education
Indicators in Focus, No. 75 (2020)
https://doi.org/10.1787/8aa53421-en
“How have women’s participation and fields of study choice in higher education evolved over time?”,
Education Indicators in Focus, No. 74 (2020)
https://doi.org/10.1787/731d5f4a-en
“What are the choices facing first-time entrants to tertiary education?”, Education Indicators in Focus, No.
73 (2020)

https://doi.org/10.1787/487f588e-en
“How has private expenditure on tertiary education evolved over time and how does it affect participation in
education?”, Education Indicators in Focus, No. 72 (2020)

https://doi.org/10.1787/6b7ded53-en
“How do young people’s educational attainment and labour-market outcomes differ across regions?”,
Education Indicators in Focus, No. 71 (2019)
https://doi.org/10.1787/c9fcfd45-en
“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

EDUCATION AT A GLANCE 2020 © OECD 2020

470  EDUCATION INDICATORS IN FOCUS
“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
“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

EDUCATION AT A GLANCE 2020 © OECD 2020

EDUCATION INDICATORS IN FOCUS  471
“Educational attainment: A snapshot of 50 years of trends in expanding education”, Education Indicators in
Focus, No. 48 (2017)
http://dx.doi.org/10.1787/409ceb2b-en
“How are health and life satisfaction related to education?”, Education Indicators in Focus, No. 47 (2016)
http://dx.doi.org/10.1787/6b8ca4c5-en
“What influences spending on education?”, Education Indicators in Focus, No. 46 (2016)
http://dx.doi.org/10.1787/5jln041965kg-en
“Fields of education, gender and the labour market”, Education Indicators in Focus, No. 45 (2016)
http://dx.doi.org/10.1787/5jlpgh1ppm30-en
“Attainment and labour market outcomes among young tertiary graduates”, Education Indicators in Focus,
No. 44 (2016)
http://dx.doi.org/10.1787/5jlsmkvp0slq-en
“Subnational variations in educational attainment and labour market outcomes”, Education Indicators in
Focus, No. 43 (2016)
http://dx.doi.org/10.1787/5jlvc7mddlkl-en
“What are the benefits from early childhood education?”, Education Indicators in Focus, No. 42 (2016)
http://dx.doi.org/10.1787/5jlwqvr76dbq-en
“How much do tertiary students pay and what public support do they receive?”, Education Indicators in
Focus, No. 41 (2016)
http://dx.doi.org/10.1787/5jlz9zk830hf-en
“Teachers' ICT and problem-solving skills”, Education Indicators in Focus, No. 40 (2016)
http://dx.doi.org/10.1787/5jm0q1mvzqmq-en
“The internationalisation of doctoral and master's studies”, Education Indicators in Focus, No. 39 (2016)
http://dx.doi.org/10.1787/5jm2f77d5wkg-en
“How is learning time organised in primary and secondary education?”, Education Indicators in Focus,
No. 38 (2015)
http://dx.doi.org/10.1787/5jm3tqsm1kq5-en
“Who are the bachelor's and master's graduates?”, Education Indicators in Focus, No. 37 (2016)
http://dx.doi.org/10.1787/5jm5hl10rbtj-en
“What are the benefits of ISCED 2011 classification for indicators on education?”, Education Indicators in
Focus, No. 36 (2015)
http://dx.doi.org/10.1787/5jrqgdw9k1lr-en
“How do differences in social and cultural background influence access to higher education and the
completion of studies?”, Education Indicators in Focus, No. 35 (2015)
http://dx.doi.org/10.1787/5jrs703c47s1-en
“What are the advantages today of having an upper secondary qualification?”, Education Indicators in
Focus, No. 34 (2015)
http://dx.doi.org/10.1787/5jrw5p4jn426-en
“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
EDUCATION AT A GLANCE 2020 © OECD 2020

472  EDUCATION INDICATORS IN FOCUS
“How much time do teachers spend on teaching and non-teaching activities?”, Education Indicators in
Focus, No. 29 (2015)
http://dx.doi.org/10.1787/5js64kndz1f3-en
“Are young people attaining higher levels of education than their parents?”, Education Indicators in Focus,
No. 28 (2015)
http://dx.doi.org/10.1787/5js7lx8zx90r-en
“What are the earnings advantages from education?”, Education Indicators in Focus, No. 27 (2014)
http://dx.doi.org/10.1787/5jxrcllj8pwl-en
“Learning Begets Learning: Adult Participation in Lifelong Education”, Education Indicators in Focus,
No. 26 (2014)
http://dx.doi.org/10.1787/5jxsvvmr9z8n-en
“Who are the doctorate holders and where do their qualifications lead them?”, Education Indicators in
Focus, No. 25 (2014)
http://dx.doi.org/10.1787/5jxv8xsvp1g2-en
“How innovative is the education sector?”, Education Indicators in Focus, No. 24 (2014)
http://dx.doi.org/10.1787/5jz1157b915d-en
“At what age do university students earn their first degree?”, Education Indicators in Focus, No. 23 (2014)
http://dx.doi.org/10.1787/5jz3wl5rvjtk-en
“How much time do primary and lower secondary students spend in the classroom?”, Education Indicators
in Focus, No. 22 (2014)
http://dx.doi.org/10.1787/5jz44fnl1t6k-en
“How much are teachers paid and how much does it matter?”, Education Indicators in Focus, No. 21 (2014)
http://dx.doi.org/10.1787/5jz6wn8xjvvh-en
“How old are the teachers?”, Education Indicators in Focus, No. 20 (2014)
http://dx.doi.org/10.1787/5jz76b5dhsnx-en
“What are tertiary students choosing to study?”, Education Indicators in Focus, No. 19 (2014)
http://dx.doi.org/10.1787/5jz8ssmzg5q4-en
“What is the impact of the economic crisis on public education spending?”, Education Indicators in Focus,
No. 18 (2013)
http://dx.doi.org/10.1787/5jzbb2sprz20-en
“Does upper secondary vocational education and training improve the prospects of young adults?”,
Education Indicators in Focus, No. 17 (2013)
http://dx.doi.org/10.1787/5jzbb2st885l-en
“How can countries best produce a highly-qualified young labour force?”, Education Indicators in Focus,
No. 16 (2013)
http://dx.doi.org/10.1787/5k3wb8khp3zn-en
“How are university students changing?”, Education Indicators in Focus, No. 15 (2015)
http://dx.doi.org/10.1787/5k3z04ch3d5c-en
“How is international student mobility shaping up?”, Education Indicators in Focus, No. 14 (2013)
http://dx.doi.org/10.1787/5k43k8r4k821-en
“How difficult is it to move from school to work?”, Education Indicators in Focus, No. 13 (2013)
http://dx.doi.org/10.1787/5k44zcplv70q-en
“Which factors determine the level of expenditure on teaching staff?”, Education Indicators in Focus, No. 12
(2013)
http://dx.doi.org/10.1787/5k4818h3l242-en
“How do early childhood education and care (ECEC) policies, systems and quality vary across OECD
countries?”, Education Indicators in Focus, No. 11 (2013)
http://dx.doi.org/10.1787/5k49czkz4bq2-en

EDUCATION AT A GLANCE 2020 © OECD 2020

EDUCATION INDICATORS IN FOCUS  473
“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 2020 © OECD 2020

Education at a Glance 2020
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 – provide 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 2020 edition includes a focus on vocational education and training, investigating participation in vocational
education and training at various levels of education, the labour market and social outcomes of vocational
graduates as well as the human and financial resources invested in vocational institutions. Two new indicators
on how vocational education and training systems differ around the world and on upper secondary completion
rate complement this topic. A specific chapter is dedicated to the Sustainable Development Goal 4,
and investigates the quality and participation in secondary education.

PRINT ISBN 978-92-64-50078-5
PDF ISBN 978-92-64-38261-9

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