On average across the OECD, the employment rate reaches 60% among 25-64 year-olds with below upper secondary educational attainment, compared to 78% among those with upper secondary or post-secondary non-tertiary education and 87% among tertiary-educated adults.
Technological change and artificial intelligence (AI) are reshaping labour markets. Historically, tertiary-educated young adults have shown the most labour-market resilience, with lower unemployment rates than their peers with lower educational attainment during economic booms and crises. This has not changed in 2025, even as concern grows about AI's effect on entry-level hiring for tertiary graduates.
Tertiary-educated adults are more likely to work in skilled occupations, but high skills can compensate for lower attainment. Although only 34% of highly skilled adults with vocational upper secondary or post-secondary non-tertiary attainment work in skilled white-collar jobs (compared with 73% of similarly skilled tertiary-educated adults), this is nearly twice the share of low-skilled adults with the same attainment.
Education at a Glance 2026
Context
Highly skilled workers remain vital for modern economies, and they in turn benefit from robust employment opportunities linked to their education. These advantages, coupled with expanded educational opportunities, are some of the motivations for individuals across the OECD to pursue higher levels of education and acquire more skills. As demand for skills has increased, labour markets have successfully absorbed the growing number of highly educated workers, providing them with better employment prospects. Conversely, adults with lower qualifications continue to face challenging labour-market prospects, lower earnings (see Chapter A4) and a greater risk of unemployment.
Concurrently, increasing longevity is reshaping labour markets and career trajectories. As people live longer and spend a larger share of their lives in retirement, many countries face growing pressure to support longer and healthier working lives while addressing skills shortages. Educational attainment and lifelong learning play an important role in helping adults remain employable throughout longer careers, particularly as low-educated older adults continue to face higher risks of early labour-market exit and economic insecurity. Education systems must therefore adapt proactively to these demographic and technological changes, preparing learners for an evolving labour-market landscape and supporting skills development throughout adulthood.
In per cent of 25-34 year-olds in the labour force
The data for this figure can be accessed via https://stat.link/ka9j74.
Other findings
Health and education are the fields of study with the highest occupational concentration. Over half of tertiary-educated workers who studied the field of education work in the teaching profession on average, while 36% of those who studied health and welfare have become health professionals. In contrast, only 22% of those with a business, administration and law qualification work in a related field.
Young women are more likely than men to be outside the labour force. The OECD average gender gap ranges from 6 percentage points among tertiary-educated 25-34 year-olds to 26 percentage points among those with below upper secondary education.
Although part-time employment offers workers greater flexibility to balance employment with education, caregiving responsibilities or other personal commitments, it is also associated with lower earnings and career opportunities. On average among 25-64 year-olds in employment, part-time working is more prevalent among those with low numeracy skills (18% compared to 10% of those with high skills), women (21% compared to 7% of men) and those with below upper secondary attainment (18% compared to 13% of those with tertiary attainment).
Note
People of working age can be classified into three groups based on their labour-force status: employed, unemployed and outside the labour force (also referred to as inactive). The employed and unemployed together make up the labour force, which represents the total supply of labour available to contribute to economic production. Individuals who are neither employed nor actively seeking work are considered outside the labour force and are not included in the labour supply.
There continues to be a strong relationship between labour-market participation and educational attainment that holds whether participation is measured by employment, unemployment or inactivity rates. This relationship exists in nearly all OECD and partner countries with available data. It is very rare to find a country where a subpopulation with lower educational attainment has higher labour-market participation rates than a subpopulation with higher educational attainment. This positive relationship between education and the labour market holds for both men and women and has been stable over the decades, against the backdrop of a strong increase in attainment levels across the OECD (Table A3.2).
When analysing employment rates by educational attainment, it is important to recognise that educational pathways are not always linear. Adults may acquire qualifications at different levels throughout their lives as they seek to update or broaden their skills in response to changing labour-market demands. The data presented in this chapter classify individuals according to their highest level of educational attainment, not their most recent qualification. As a result, adults who complete an upper secondary or post-secondary non-tertiary programme after obtaining a tertiary qualification are recorded as tertiary-educated. The results should therefore be interpreted as reflecting the labour-market outcomes associated with individuals' highest attained qualification rather than their full educational trajectory.
Educational attainment and employment rates
Increased educational attainment improves the employment prospects of adults. On average across the OECD, 60% of 25-64 year-olds with below upper secondary educational attainment are employed, compared to 78% among those with upper secondary or post-secondary non-tertiary education. Among those, the employment rate for those who completed a vocational programme (79%) is higher than for those with general qualifications (75%). Finally, the employment rate increases to 87% among tertiary-educated adults (Table A3.1).
There are significant variations in employment rates by attainment level across countries. The Slovak Republic has the highest employment premium for adults with an upper secondary or post-secondary educational attainment, regardless of the programme orientation, at 47 percentage points (the employment rate is 81% at this level, compared to 34% for those adults with below upper secondary education). The lowest premiums at this level are observed in Colombia, Costa Rica and Mexico, and, among OECD partner countries, India and Indonesia. The highest employment premiums for tertiary-educated adults compared to those with upper secondary or post-secondary non-tertiary education are found in Lithuania and Poland, where the difference in employment rates reaches 16 percentage points, and, among OECD partner countries, in South Africa (22 percentage points). In contrast, countries such as Czechia and Iceland report a much smaller premium for tertiary attainment, at 4 percentage points or less (Table A3.1). These differences indicate that the labour-market value of a degree is shaped not only by the level of education but also by national economic conditions, specific skill demands and the structure of secondary and post-secondary education systems (OECD, 2025[1]).
These data must also be understood in the context of broader generational shifts. Although younger adults (25-34 year-olds) are more highly educated than the wider adult population, their employment patterns are remarkably consistent with OECD averages: overall, 87% of tertiary-educated younger adults are employed, the same share as for tertiary-educated adults as a whole. Similarly, 83% of younger adults with vocational upper secondary or post-secondary non-tertiary attainment are employed (compared to 79% among 25-64 year-olds), as are 73% of those with a general qualification at the same level (75% among 25-64 year-olds), and 59% of those with below upper secondary attainment (60% among 25-64 year-olds) (Table A3.2).
Adults with vocational upper secondary or post-secondary non-tertiary educational attainment typically benefit from more direct pathways into the labour market, as these programmes are specifically designed to provide occupation-specific skills that meet immediate employer needs. The slightly lower initial employment rates among their peers from general tracks may reflect the fact that these programmes are primarily oriented towards preparing students for further studies at the tertiary level. This distinction is critical, as vocational qualifications often provide a significant "safety net" against early-career unemployment, whereas the value of a general secondary qualification is frequently realised only upon the completion of a subsequent tertiary degree.
The employment benefits of higher education are particularly striking for women. The employment rate among young women (aged 25-34) with upper secondary or post-secondary non-tertiary attainment from a general programme is 21 percentage points higher than for their peers with below upper secondary attainment, rising to 30 percentage points higher if they hold a vocational qualification. In contrast, the employment advantages among similarly educated young men is 10 percentage points for a general qualification and 20 percentage points for a vocational one. The advantage to women of attaining tertiary education is even more pronounced: their employment rate is 14 percentage points higher than among those with upper secondary or post-secondary non-tertiary attainment, whereas for young men the difference is only 5 percentage points (Table A3.2).
However, young women still face persistent disadvantages in the labour market, with lower employment rates than their male peers at every level of attainment. Across the OECD, 25-34 year-old women with below upper secondary attainment have an average employment rate of 45%, compared to 69% for similarly educated men. The gender gap narrows with rising attainment: it is 15 percentage points among young adults with an upper secondary or post-secondary non-tertiary attainment and 6 percentage points among those with tertiary attainment (Table A3.2). These continued disparities highlight the importance of addressing structural barriers to employment, even as educational levels continue to improve.
Employment rates measure whether individuals are working, but not intensity of their participation in the labour market. Understanding differences in work intensity provides a more complete picture of labour-market outcomes. Box A3.1 examines how part-time employment varies by educational attainment, skills and gender using data from the 2023 cycle of the Survey of Adult Skills (PIAAC).
Part-time employment plays an important role in labour markets, offering workers greater flexibility to balance employment with education, caregiving responsibilities or other personal commitments. Although part-time work can facilitate labour-market participation for groups such as students, parents and older adults, who might otherwise be excluded from employment, it can also be associated with lower earnings, fewer opportunities for career progression and reduced access to employment-related benefits. The prevalence of part-time work varies considerably across countries and demographic groups, with women, young adults, older workers and low-skilled adults generally more likely to work part time.
The Survey of Adult Skills (PIAAC) collects information on the number of hours usually worked per week. Because national definitions of part-time employment vary across countries, the analysis here uses a harmonised definition based on hours worked rather than self-reported employment status, classifying adults who usually work less than 30 hours per week as working part time.
On average across the OECD, the share of employed 25-64 year-olds working part time ranges from 10% among those with PIAAC numeracy proficiency at Level 4 or above (i.e. those who can successfully complete complex mathematical tasks) to 18% among those performing at Level 1 or below (who typically struggle with multi-step calculations or the interpretation of more complex quantitative information). The part-time working rate is 21% among women, compared to 7% among men. Across educational attainment levels, 18% of adults with below upper secondary education work part time, compared to 14% of those with upper secondary or post-secondary non-tertiary attainment and 13% of tertiary-educated adults (Table A3.8, available online).
Employment rate trends
Between 2015 and 2025, the employment landscape for young adults (aged 25-34) has been characterised by an upward trend in employment rates, although the increase has not been linear and marked by the negative downturn due to the COVID-19 pandemic. On average across OECD countries, the employment rate for tertiary-educated young adults grew by 4 percentage points (87% in 2025). There were similar increases for young adults with upper secondary or post-secondary non-tertiary attainment: by 3 percentage points for those with a general qualification and by 4 percentage points for those with a vocational one (in 2025 at 73% and 83% respectively). In contrast, those with below upper secondary attainment remain the most vulnerable group in the labour market. Their average employment rate rose by only 1 percentage point (at 59% in 2025) in the same period (Table A3.2).
These average changes mask a wide variety of trends across different countries. Hungary, Italy and Spain have seen a sharp improvement in employment rates for young adults between 2015 and 2025, regardless of educational attainment, while in Greece, employment prospects improved at all levels except among those with below upper secondary attainment. Large increases were also recorded in other countries over this period. The employment rate rose by 12 percentage points in the Slovak Republic among tertiary-educated young adults; in Croatia, Ireland and Portugal among those with a vocational upper secondary or post-secondary non-tertiary attainment; in Germany and Slovenia among those with a general qualification at the same level; and in Czechia and Korea among those with below upper secondary education (Table A3.2).
The employment prospects of young adults sometimes diverged strongly in the same country depending on attainment and programme orientation. For example, in France and Sweden the employment rate fell for those with a general upper secondary or post-secondary non-tertiary attainment, but not for those with vocational attainment, while in Croatia the increase among this latter cohort was much larger than for those with a general qualification at the same level (Figure A3.2).
In per cent; 25-34 year-olds
1. Year of reference differs from 2025.
2. Data for upper secondary attainment include completion of intermediate upper secondary programmes.
For data, see Table A3.2. The data for this figure can be accessed via https://stat.link/ka9j74.
As well as attainment levels, different skill levels and fields of study can lead to very different career pathways and occupations. Box A3.2 analyses the distribution of the adult population across different occupations using data from the 2023 cycle of the Survey of Adult Skills (PIAAC).
Educational attainment is strongly associated with occupational outcomes. Adults with tertiary education are considerably more likely than those with lower levels of attainment to work in skilled white-collar occupations such as managers, professionals and technicians. However, skills also matter. Among adults with similar educational attainment, those with stronger numeracy skills are more likely to work in higher-skilled occupations, suggesting that strong skills can partly compensate for lower levels of formal educational attainment. These findings highlight the importance of both qualifications and skills in shaping labour-market opportunities.
Occupations in this analysis of data from the Survey of Adult Skills (PIAAC) are classified according to the International Standard Classification of Occupations (ISCO-08), which groups jobs according to the tasks and duties performed by workers. Skilled occupations include managers, professionals, and technicians and associate professionals, while semi-skilled occupations include clerical support workers, service and sales workers, skilled agricultural workers, craft and related trades workers, and plant and machine operators and assemblers (OECD, 2024[2]).
Educational attainment is a strong predictor of occupational outcomes. Adults with tertiary education are substantially more likely to work in skilled occupations than those with upper secondary or post-secondary non-tertiary attainment, regardless of their skill level. On average across the OECD, 73% of tertiary-educated adults with high numeracy skill levels work as managers, professionals or technicians, compared to 34% of similarly skilled adults with vocational upper secondary or post-secondary non-tertiary attainment (Figure A3.3).
Skills nevertheless play an important role within educational attainment levels. Adults with vocational upper secondary or post-secondary non-tertiary attainment tend to be concentrated in a range of semi-skilled occupations, and those with lower numeracy proficiency are considerably less likely to work in skilled occupations than those with higher proficiency. On average across the OECD, only 18% of adults with vocational upper secondary or post-secondary non-tertiary attainment and low numeracy skills work as managers, professionals or technicians, just over half the rate among their high-skilled peers. This suggests that strong skills can improve occupational prospects even in the absence of tertiary qualifications (Table A3.4, available online).
The relationship between fields of study and occupations varies considerably across disciplines. Some fields exhibit strong occupational concentration (i.e. graduates from these fields tend to work in a related occupation) because they prepare graduates for specific professions. Health professionals predominantly come from health and welfare programmes, reflecting the highly specialised nature of the profession: on average 36% of tertiary-educated adults who studied a health and welfare field work as a health professional (Table A3.6, available online). The education field of study has an even higher occupational concentration: on average across the OECD, 53% of those whose main field of study was education work as teaching professionals (Figure A3.4).
In comparison, tertiary graduates from science, technology, engineering and mathematics (STEM) fields or business, administration and law are distributed across a much wider range of occupations. On average, 31% of adults with a STEM degree work as a science and engineering or information and communications technology professionals, while only 22% of those with business, administration and law qualifications work as either business and administration professionals or legal, social and cultural professionals (Table A3.6, available online). The relationship also differs when examined from the perspective of occupations: Table A3.7, available online, presents the distribution by field of study for each occupation.
25-64 year-olds, numeracy proficiency of PIAAC Level 3 and above, Survey of Adult Skills (PIAAC)
Note: The percentages in parentheses represent the adults with PIAAC numeracy proficiency level 3 or above at each specific educational attainment level. Additional data breakdowns for the category of Professionals are available in Tables A3.4 and A3.5, available online. Other occupations include Skilled agricultural, forestry and fishery workers, elementary occupations and armed forces occupations.
For data see, Tables A3.4 and A3.5, available online. The data for this figure can be accessed via https://stat.link/ka9j74.
These findings should be interpreted in light of the way information collected in PIAAC. The survey records respondents’ principal field of study associated with their highest qualification rather than all qualifications obtained throughout their lifetime. As a result, some teachers may not be recorded as having studied education if they first completed a subject-specific degree and subsequently obtained a teaching qualification, entered teaching through an alternative certification pathway, or became a teacher after working in another profession. Such pathways are common in some countries and help explain why many teaching professionals report a field of study other than education.
25-64 year-olds, Survey of Adult Skills (PIAAC)
For data, see Table A3.6, available online. The data for this figure can be accessed via https://stat.link/ka9j74.
Note that the category “Teaching professionals” refers to adults whose current occupation involves teaching-related professional duties. It is therefore not directly comparable with teacher statistics reported elsewhere in Education at a Glance, which are derived from administrative data and classify teachers according to the level of education at which they are employed. Nevertheless, the analysis provides valuable insights into how educational attainment, skills and fields of study are associated with occupational outcomes across OECD countries.
Subnational variations in employment rates
Within OECD countries, employment rates among adults (25-64 year-olds) can vary dramatically from one region to another. These subnational variations present critical challenges for policymakers seeking to promote inclusive labour markets and equitable access to opportunities. The following analysis is of regions at the TL2 level, which are large subnational regions as defined by the OECD’s official regional classification (OECD, 2026[3]).
On average across OECD countries, regional disparities in employment rates are markedly larger for adults with lower educational attainment. In Italy, for instance, only 3% of 25-64 year-olds with below upper secondary education were employed in Campania in 2025, compared to 77% in the Autonomous Province of Bolzano, a difference of 38 percentage points. In contrast, among tertiary-educated adults, employment rates range from 73% in Calabria to 91% in the Autonomous Province of Bolzano, a much narrower 18 percentage-point spread (Table A3.9, available online).
The most pronounced regional disparities in employment rates among tertiary-educated adults are in Canada, Greece and Italy where the gap between the best- and worst-performing regions reaches or exceeds 12 percentage points. In contrast, regional differences in employment rates for tertiary-educated adults do not exceed 1 percentage point in Ireland and Slovenia (Table A3.9, available online).
Among partner countries, Bulgaria has a significant range of employment outcomes by region and education levels. In 2025, only 38% of adults with below upper secondary education were employed in the North West region compared to 60% in the South West – Ilfov. Among tertiary-educated adults, the disparity narrows, with employment rates ranging from 90% to 94% across regions (Table A3.9, available online).
Educational attainment and unemployment rates
Higher educational attainment continues to serve as a significant buffer against the risk of unemployment. Across many OECD and partner countries, unemployment rates are notably higher among younger adults with lower levels of education. In 2025, the average unemployment rate across OECD countries for 25-34 year-olds with below upper secondary attainment stood at 14%, nearly twice that for those with an upper secondary or post-secondary non-tertiary qualification (8% for those with a general qualification and 6% for those with vocational attainment). For tertiary-educated young adults, the unemployment rate is lower still, at just 5% (Table A3.3).
The OECD average unemployment rate for 25-34 year-olds has gone through significant fluctuations over the last two decades Figure A3.2. Notable peaks occurred between 2008 and 2013 following the global financial crisis, and again during the 2020-21 COVID-19 pandemic. Across all education levels, tertiary-educated young adults remained the most resilient during these shocks, experiencing lower overall unemployment rates and less extreme spikes. For example, during the aftermath of the 2008 crisis, the unemployment rate for those without an upper secondary education rose by 7 percentage points between 2008 and 2010, whereas the increase for tertiary-educated adults was a more moderate 3 percentage points, and it rose more gradually over a longer period (2008 to 2013) (Figure A3.2).
Recent labour-market developments do not yet suggest a widespread deterioration in employment prospects for tertiary-educated young adults. Despite growing discussion about the potential impact of artificial intelligence on highly skilled occupations (Lane, 2024[4]), the unemployment rate among tertiary-educated 25-34 year-olds remained comparatively low in 2025, at 5% on average across the OECD, and showed no marked divergence from longer-term trends. However, over the most recent two years with data available unemployment increased slightly more among tertiary-educated young adults (+0.4 percentage points on average across the OECD with available data) than among lower levels of educational attainment. The unemployment rate decreased slightly among those with upper secondary or post-secondary non-tertiary attainment (-0.2 percentage points between 2023 and 2025) and increased only slightly among those with below upper secondary education (+0.1 percentage points over the same period) (Table A3.3 and Figure A3.1).
Overall, the average unemployment rate masks wide cross-country variations. In the Slovak Republic and South Africa, the risk of unemployment is particularly acute among young adults with below upper secondary educational attainment: 40% or more are unemployed. The risk is reduced among those who completed upper secondary or post-secondary non-tertiary education: the highest rate for all programmes combined is found in South Africa (39%), while it is highest in Finland for those with general attainment at this level (14%) and in Greece for those with vocational attainment (13%). Finally, the risk is substantially lower among tertiary-educated young adults, reaching 11% in Greece, and, among partner countries, 16% in South Africa (Table A3.3).
Between 2015 and 2025, Greece and Spain experienced the largest reduction in unemployment rates for all levels of educational attainment (and Czechia for young adults with below upper secondary education). The rate increased the most among young adults without a tertiary education in South Africa (Table A3.3).
Educational attainment and adults outside the labour force
Although unemployment rates are a common indicator of a country's economic health, they can be deceptive when viewed in isolation. This measure only captures individuals who are jobless but actively seeking employment, excluding those who are outside the labour force altogether (inactive). This distinction is vital; in some nations, low unemployment rates can mask a high rate of inactivity caused by discouraged workers. These are individuals who may wish to work but have ceased their search due to structural barriers, such as a lack of childcare, health concerns, or repeated failure to find a position, potentially obscuring deeper labour-market dysfunction.
The reasons for inactivity vary across people’s lives. Among young adults, family formation and caregiving responsibilities are important drivers of labour-market withdrawal, particularly among women. As people get older, health-related limitations become increasingly important. As populations live longer and working lives extend, addressing health-related barriers to employment will become an increasingly important component of policies aimed at sustaining labour-market participation (Crawshaw et al., 2024[5]).
On average across the OECD, 32% of young adults without upper secondary are outside the labour force, falling to 21% among those with general upper secondary or post-secondary non-tertiary attainment, 11% among those with a vocational qualification at the same level and 9% among those with tertiary attainment. Across OECD and partner countries, this share ranges from 15% in Iceland and Portugal to 54% in Ireland among young adults with below upper secondary education, and from 5% in Hungary, Lithuania and the Netherlands to 32% in India among tertiary-educated ones (Table A3.3).
Across OECD and partner countries, young women are more likely than men to be outside the labour force. This pattern coincides with the life stage during which family formation and child-rearing responsibilities are most common, highlighting the continued influence of caregiving obligations on labour-market participation. However, this gender gap narrows as educational attainment increases. On average across the OECD, the gender difference ranges from 6 percentage points among tertiary-educated 25-34 year-olds to 26 percentage points among those with below upper secondary education. Across countries, differences in the share of young women and young men who are outside the labour force range from as little as 3 percentage points in Korea to 61 percentage points in the Republic of Türkiye among those with below upper secondary attainment, and from no gap at all in Portugal to 55 percentage points in India for those with tertiary attainment (Figure A3.5).
In per cent
1. Year of reference differs from 2025.
2. Data for upper secondary attainment include completion of intermediate upper secondary programmes.
For data, see Table A3.3.
The data for this figure can be accessed via https://stat.link/ka9j74.
Age groups: Adults refer to 25-64 year-olds. Younger adults refer to 25-34 year-olds. Older adults refer to 55-64 year-olds.
Educational attainment refers to the highest level of education successfully completed by an individual. See the Reader’s Guide at the beginning of this publication for a presentation of all ISCED 2011 levels.
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.
Inactive individuals/those outside the labour force are those who, during the survey reference week, were outside the labour force and classified neither as employed nor as 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 the population of the same age group).
Labour force (active population) is the total number of employed and unemployed persons, in accordance with the definition in the Labour Force Survey.
Proficiency levels: See definition in Chapter A1.
Professions: Elementary occupations are those defined in ISCO-08 as 9-Elementary Occupations. Semi-skilled blue-collar occupations include 6-Skilled Agricultural, Forestry and Fishery Workers; 7-Craft and Related Trades Workers; and 8-Plant and Machine Operators, and Assemblers. Semi-skilled white-collar occupations include 4-Clerical Support Workers and 5-Service and Sales Workers. Skilled occupations include 1-Managers, 2-Professionals, and 3-Technicians and Associate Professionals.
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).
Definitions of Skill domains and Proficiency levels related to data from Survey of Adult Skills (PIAAC) are included in Chapter A1.
For information about methodologies, see Chapter A1. Note that the employment rates do not take into account the number of hours worked.
For further details, refer to the OECD Handbook for Internationally Comparative Education Statistics ( (OECD, 2017[6])) and the Education at a Glance 2026 Sources, Methodologies and Technical Notes (https://doi.org/10.1787/dcf64a14-en).
In PIAAC data, occupations are coded using the International Standard Classification of Occupations 2008 (ISCO-08). Occupations are usually available at the 1-digit (major group), 2-digit (sub-major group), 3-digit (minor group) and sometimes 4-digit level. Only data on 1- and 2-digit categories have been analysed in this report. ISCO-08 major groups (1-digit): 1 Managers; 2 Professionals; 3 Technicians and associate professionals; 4 Clerical support workers; 5 Service and sales workers; 6 Skilled agricultural, forestry and fishery workers; 7 Craft and related trades workers; 8 Plant and machine operators and assemblers; 9 Elementary occupations; 0 Armed forces occupations
PIAAC data use respondents' highest field of study based on ISCED Fields of Education and Training 2013 (ISCED-F 2013). The broad fields are collapsed into broader categories. The share of part-time workers in PIAAC is derived from respondents' reported weekly working hours (question D2_Q11). To ensure comparability across countries, this chapter applies a harmonised definition of part-time employment, classifying workers who report working fewer than 30 hours per week as part-time.
For information on sources, see Chapter A1.
Data on subnational regions for selected indicators are available in the OECD Regional Statistics Database: https://www.oecd.org/en/topics/regions-cities-and-local-statistics.html.
Data on proficiency levels are based on the Survey of Adult Skills (PIAAC) (2023). PIAAC is the OECD Programme for the International Assessment of Adult Competencies. See About the Survey of Adult Skills at the beginning of this publication for additional information.
References
[5] Crawshaw, P. et al. (2024), “Health inequalities and health-related economic inactivity: Why good work needs good health”, Public Health in Practice, Vol. 8, https://doi.org/10.1016/j.puhip.2024.100555.
[4] Lane, M. (2024), “Who will be the workers most affected by AI?: A closer look at the impact of AI on women, low-skilled workers and other groups”, OECD Artificial Intelligence Papers, No. 26, OECD Publishing, Paris, https://doi.org/10.1787/14dc6f89-en.
[3] OECD (2026), OECD Territorial Grids, OECD, Paris, https://webfs-cfe.oecd.org/files/.Stat/region/OECD_territorial-grid_TL2024.pdf.
[1] OECD (2025), Education at a Glance 2025: OECD Indicators, OECD Publishing, Paris, https://doi.org/10.1787/1c0d9c79-en.
[2] OECD (2024), Do Adults Have the Skills They Need to Thrive in a Changing World?: Survey of Adult Skills 2023, OECD Skills Studies, OECD Publishing, Paris, https://doi.org/10.1787/b263dc5d-en.
[6] OECD (2017), OECD Handbook for Internationally Comparative Education Statistics: Concepts, Standards, Definitions and Classifications, OECD Publishing, Paris, https://doi.org/10.1787/9789264279889-en.
The data for the figures and tables in this chapter, can be downloaded via https://stat.link/ka9j74.
To access further data and/or other education indicators, please visit the OECD Data Explorer: http://data-explorer.oecd.org/s/4s.
Data cut-off for the print publication 17 June 2026. Please note that the Data Explorer contains the most recent data.
a – category not applicable; b – break in series; d – contains data from another column; m – missing data; x – contained in another column (indicated in brackets). For further control codes, see the Reader’s Guide.
For further methodological information, see Education at a Glance 2026: Sources, Methodologies and Technical Notes (https://doi.org/10.1787/dcf64a14-en).
Percentage of employed 25-64 year-olds among all 25-64 year-olds
Note: Data refer to ISCED 2011 for all countries, except Argentina and India, which use ISCED-97. Data for Argentina, India and Indonesia are from the International Labour Organization (ILO). The data for this Table can be accessed via https://stat.link/ka9j74.
1. Year of reference differs from 2025: 2024 for Brazil and Chile; 2023 for Iceland and Indonesia. 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 (10% of adults aged 25-64 are in this group).
Percentage of employed 25-34 year-olds among all 25-34 year-olds
Note: Data refer to ISCED 2011 for all countries, except Argentina and India, which use ISCED-97. Totals might not add up to 100% for the averages because of missing data for some levels for some countries. Data for Argentina, India and Indonesia are from the International Labour Organization (ILO). Columns showing data for category totals are available for consultation online.
1. Year of reference differs from 2025: 2024 for Brazil and Chile; 2023 for Iceland and Indonesia.
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 (8% of adults aged 25-34 are in this group).
3. Year of reference differs from 2015: 2016 for Brazil and Peru.
The data for this Table can be accessed via https://stat.link/ka9j74
.
Unemployment rates as a percentage of 25-34 year-olds in the labour force; shares of those outside the labour force as a percentage of all 25-34 year-olds
Note: Data refer to ISCED 2011 for all countries, except Argentina and India, which use ISCED-97. Totals might not add up to 100% for the averages because of missing data for some levels for some countries. Data for Argentina, India and Indonesia are from the International Labour Organization (ILO). Columns showing data for category totals and the breakdown for men and women are available for consultation online.
1. Year of reference differs from 2025: 2024 for Brazil and Chile; 2023 for Iceland and Indonesia.
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 (8% of adults aged 25-34 are in this group).
3. Year of reference differs from 2015: 2016 for Brazil and Peru.
The data for this Table can be accessed via https://stat.link/ka9j74.