Employment rates among 25-64 year-olds increase steadily with higher levels of tertiary attainment, reflecting strong labour-market returns to advanced qualifications. Individuals with a short-cycle tertiary qualification have an employment rate of 83%, compared to 86% for those with a bachelor's degree, 90% for those with a master’s and 93% for those with a doctoral or equivalent qualification.
Among unemployed adults aged 25-64, long-term unemployment is more prevalent among those with lower educational attainment: 36% of those with below upper secondary education have been unemployed for 12 months or more, compared to 30% with upper secondary or post-secondary non-tertiary education, and 25% with tertiary education.
Adults’ employment prospects depend both on educational attainment and numeracy proficiency, although the link highlighted by the second cycle of the Survey of Adult Skills is weaker than in the first cycle. Adults with tertiary education and high proficiency levels (at or above Level 4) are significantly more likely to be employed, while those with low educational attainment and weak proficiency levels (at or below Level 1) face much higher risks of unemployment or exclusion from the labour force.
Education at a Glance 2025
Context
Highly skilled workers remain vital for modern economies, and they in turn benefit from robust employment opportunities linked to their education (Box A3.2). 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 skilled 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, exacerbated by growing automation and AI-driven labour-market transformations. Concurrently, the impact of ageing populations disproportionately affects low-educated older adults, often leading to early workforce exits and economic insecurity. Education systems must adapt proactively to these changes, preparing learners for an evolving labour-market landscape.
Among tertiary-educated adults, employment rates differ depending on their field of study and resulting careers. Careers in information and communication technologies (ICT) and engineering, manufacturing and construction often exhibit higher employment rates and wages. This serves as a motivation for some individuals to pursue careers in science, technology, engineering and mathematics (STEM).
In per cent; 25-64 year-olds
1. Year of reference differs from 2024.
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).
For data, see Table A3.1. For a link to download the data, see Tables and Notes section.
Other findings
In the vast majority of OECD countries, employment rates among young women (25-34 year-olds) are lower than among young men, regardless of educational attainment. However, the difference falls as educational attainment increases. On average across OECD countries, only 46% of 25-34 year-old women with below upper secondary attainment are employed, 25 percentage points below their male peers. The gap narrows to 15 percentage points for those with upper secondary or post-secondary non-tertiary attainment and to 6 percentage points for those with a tertiary degree.
Among tertiary-educated adults, those who studied ICT have the highest average employment rate (90%) across the OECD, while the lowest rates are found among those who studied arts and humanities, social sciences, journalism and information (84%).
The unemployment rate for adults with tertiary education is as low as or lower than the unemployment rate for adults with upper secondary or post-secondary non-tertiary education in almost all OECD and partner countries except Denmark, Mexico, the Netherlands, South Africa and Switzerland.
The field of study matters more for the employment prospects of adults with lower numeracy proficiency than for those with higher skills. Employment rates vary widely, with particularly low rates for adults with a tertiary education in arts and humanities and also, in some countries, for education and for business, administration and law. In contrast, employment rates among adults with high numeracy proficiency levels tend to converge across fields.
Note
People of working age can be classified into three groups based on their labour-force status: employed, unemployed and those 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 the strong increase in attainment levels across the OECD (Table A3.2).
When analysing employment rates by educational attainment, it is clear that educational pathways are not always linear. In some cases, individuals may pursue upper secondary or post-secondary non-tertiary programmes, even if they already hold a tertiary qualification, to acquire the necessary skills for the labour market. As labour-market needs constantly evolve, individuals must continuously upskill and reskill. To do so, they may choose to pursue further education at a different level or engage in informal or non-formal learning (see Chapter A5).
Educational attainment and employment rates
Across countries, there are substantial variations in employment rates by level of education. The highest employment premiums for tertiary-educated adults over those with upper secondary or post-secondary non-tertiary education are in Lithuania and Poland, where the difference between employment rates is 16 percentage points in both countries. Conversely, in Czechia and Iceland, the average employment premium for tertiary-educated adults is 4 percentage points or less over those with upper secondary or post-secondary non-tertiary education (Table A3.1). These disparities suggest that the labour-market value of tertiary qualifications depends not only on the level of education attained but also on national economic conditions, demand for skills and the structure of secondary and post-secondary education systems.
Within tertiary education, employment rates among 25-64 year-olds rise with higher levels of tertiary attainment, from 83% for short-cycle tertiary programmes to 93% for doctoral or equivalent qualifications (Figure A3.1). This pattern reflects the increasing demand for advanced skills and qualifications in OECD and partner countries’ labour markets. Higher levels of education often signal specialised expertise, which can improve employability and access to more stable or higher-paying jobs. Although advanced degrees tend to offer better employment outcomes on average, the returns may vary depending on the match between qualifications and labour-market needs.
This overall picture must also be viewed in the context of generational shifts in educational attainment. In all OECD and partner countries, younger adults (aged 25-34) are better educated than the wider adult population (aged 25-64) (see Chapter A1). However, their employment patterns remain similar on average across OECD countries: 87% of both tertiary-educated younger adults and all adults are employed, as are 79% of younger adults with upper secondary or post-secondary non-tertiary attainment and 60% of younger adults with below upper secondary attainment (compared to 79% of all adults) (Table A3.1 and Table A3.2).
The employment gains for increasing educational attainment are particularly pronounced for women. Young women (25-34 year-olds) with an upper secondary or post-secondary non-tertiary qualification have an employment rate that is 24 percentage points higher than those with below upper secondary attainment, compared to a 14 percentage points increase among young men. The advantage for young women of attaining tertiary education is even more pronounced: their employment rate rises by a further 13 percentage points compared to those with only upper secondary attainment whereas for young men the increase is only 5 percentage points (Table A3.2).
However, young women remain disadvantaged in the labour market with lower employment rates than their male peers at all levels of educational attainment. Women aged 25-34 with below upper secondary attainment have employment rates of 46% on average across the OECD, compared with 71% for similarly educated young men. Among tertiary-educated young adults, the gap in favour of men narrows to 6 percentage points (Table A3.2). These persistent disparities underscore the importance of addressing gender-specific barriers to employment, even as progress in educational attainment continues.
Information on the quality of jobs and working conditions for Research and Innovation (R&I) professionals plays a decisive role in driving personal development decisions, career choices and informing policies oriented towards nurturing, attracting and retaining talent (Box A3.1).
Employment and fields of study
Employment rates for adults with tertiary attainment are high across all fields, but there are small differences depending on what graduates chose to study. Overall, the STEM fields have the strongest employment outcomes. Within these fields, employment rates are highest for people who studied ICT; on average 90% of adults (25-64 year-olds) with a tertiary ICT degree are in employment in OECD countries. Similarly, the average employment rate of graduates in engineering, manufacturing and construction is very high at 89%. Education has an average employment rate that is somewhat lower, but still high at 87%. Arts and humanities, social sciences, journalism and information is the broad field of study with the lowest employment rates among tertiary-educated 25-64 year-olds, at an average of 84%. To put this into perspective, this employment rate is still 7 percentage points higher than the average for those with upper secondary or post-secondary non-tertiary attainment across the OECD (Table A3.1 and Table A3.3).
Although the differences in employment rates between fields of study are small, they are very consistent across OECD countries. For example, employment rates for adults with tertiary attainment in ICT are higher than for those with tertiary attainment in arts and humanities and social sciences, journalism and information in all OECD countries. Within the STEM fields, graduates in natural sciences, mathematics and statistics tend to have lower employment rates than other STEM fields in almost all countries. The gap is especially large in Costa Rica, where the employment rate is on average approximately 11 percentage points lower for adults with a qualification in natural sciences, mathematics and statistics than for those who studied ICT (Table A3.3).
In June 2025, the OECD launched the Research and Innovation Careers Observatory (ReICO) online platform (OECD, 2025[1]). This is the first major output of a new multi-year initiative with the European Union, aiming to support evidence-based policy making to strengthen the development of research and innovation (R&I) talent, improve labour-market conditions, and promote mutually beneficial talent circulation.
ReICO provides internationally comparable statistics on research and innovation careers across interconnected themes that reflect the full working lives of R&I talent while also highlighting measurement gaps for the ReICO project to address in partnership with relevant communities.
The 2025 edition draws mainly on existing official statistics, including OECD education and training data collections, and the outcomes of a dedicated ReICO 2024 data collection on the career outcomes of doctorate holders, benchmarked against those of master’s graduates (Table A3.12, available on line). Doctoral education plays a key role in R&I talent development systems, as it explicitly prepares and accredits individuals to conduct and manage research. The platform therefore offers valuable insights into the working conditions and career paths of these individuals.
Earnings
Across the countries for which data are available, doctorate holders typically benefit from a notable earnings advantage over those with master's degrees. In the Republic of Türkiye, employed doctorate holders earn 46% more on average than those with a master’s degree, although in France and Norway the relative earnings advantage is less than 10% (Figure A3.2). Although earnings might not be the sole factor in driving individuals' decisions to pursue a doctorate and might not represent a positive rate of return on investment in all cases, this premium underscore the value attributed by the labour market to advanced research skills in some fields.
Ratio of the average gross annual earnings of employed doctorate holders to those of employed master’s degree holders; 25-64 year-olds
Note: The average includes only OECD countries, i.e. Brazil and Indonesia are excluded from the calculation.
1. Year of reference differs from 2023: 2022 for Ireland and Italy; 2021 for Brazil and Canada; 2020 for Greece and France.
For data, see Table A3.12, available on line. For a link to download the data, see Tables and Notes section.
Job Security
Employment stability can be an important factor in attracting and, especially, retaining high-level talent, particularly if remuneration is capped. The share of employed doctorate holders with indefinite contracts remains slightly below that for master’s holders in most countries (Figure A3.3).
Precarious employment has profound consequences for individuals’ career planning, well-being and the ability to undertake long-term projects. In addition, fixed-term roles often prevent individuals from finding stable housing, planning their families and pursuing sustained research agendas. Although indefinite contracts may offer different levels of job security, this gap suggests potential areas for policy improvement to enhance work conditions and thus the attractiveness of careers for doctorate holders (Auriol, 2013[2]). In response, many OECD countries are implementing structural reforms such as expanding tenure-track positions, improving access to permanent contracts and enhancing pathways to move into non-academic sectors (OECD, 2023[3]).
Share of employed doctorate and master’s degree holders who are in indefinite contracts; 25-64 year-olds
1. Year of reference differs from 2023 for doctorate holders: 2022 for Estonia, France, Lithuania, Luxembourg and Romania; 2021 for Canada, Greece and Slovenia; 2019 for Latvia, Netherlands and Poland.
2. Year of reference differs from 2023 for master's holders: 2022 for Bulgaria; 2021 for Canada; and 2020 for Latvia.
For data, see Table A3.12, available on line. For a link to download the data, see Tables and Notes section.
Working Hours
Doctorate holders generally work slightly more hours – approximately 2% more per year – than those with master’s degrees (Table A3.13, available on line). This difference might reflect increased responsibilities and more competitive working environments typically associated with doctoral-level positions. In academic research careers, this workload intensity is associated with heightened stress – and is especially pronounced in early-career positions where teaching, grant-writing and lab duties overlap (OECD, 2021[4])
The ReICO 2024 data collection highlights both the strong points and areas for further attention regarding working conditions for doctorate holders, informing policies that aim to foster sustainable and attractive research and innovation careers, as well as talent development early on in education and training systems.
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 policy makers 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 grid (OECD, 2023[5]).
On average across OECD countries, regional disparities in employment rates are markedly larger for adults with lower educational attainment. In Italy, for instance, only 37% of 25-64 year-olds with below upper secondary education are employed in Campania, compared to 75% in the Autonomous Province of Bolzano in 2024 – a difference of 39 percentage points. In contrast, among tertiary-educated adults, employment rates range from 71% in Calabria to 91% in Aosta Valley, a much narrower 20 percentage-point spread (Table A3.13, available on line).
The most pronounced regional disparities in employment rates among tertiary-educated adults are in Canada, Italy and Mexico where the gap between the best- and worst-performing regions exceeds 12 percentage points. In contrast, regional differences in employment rates for tertiary-educated adults do not exceed 1 percentage point in Lithuania, Norway and Slovenia (Table A3.13, available on line).
Among partner countries, Romania has a significant range of employment outcomes by region and education levels. In 2024, only 33% of adults with below upper secondary education were employed in Centru compared to 59% in Bucharest – Ilfov. Among tertiary-educated adults, the disparity narrows, with employment rates ranging from 89% to 93% across regions (Table A3.13, available on line).
Educational attainment, unemployment rates and duration of unemployment
Higher educational attainment continues to shield individuals from unemployment. In many OECD and partner countries, unemployment rates are especially high among younger adults with lower attainment. On average across OECD countries, the unemployment rate for younger adults with below upper secondary attainment 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 with below upper secondary attainment in the Slovak Republic and South Africa, where about 40% are unemployed. The unemployment rate is also high for this group in Finland, Greece and Spain where at least 20% 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, Bulgaria, Czechia, Hungary, Romania and the Slovak Republic, 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 attainment (Table A3.4).
Unemployment rates are often used as a proxy for labour-market health. However, this measure can be misleading if interpreted in isolation. Unemployment only measures those without a job who are actively seeking work. It excludes individuals who are out of work but not currently searching – those who are classified as inactive or outside the labour force (see next section). This distinction matters. In some countries, low unemployment rates coexist with high inactivity rates. This is often driven by discouraged workers – people who would like to work but have stopped searching due to repeated failure, lack of opportunities, or structural barriers such as poor childcare support or health issues. In such cases, a low unemployment rate can obscure significant labour-market dysfunction.
Overall, the average unemployment rate of 25–34 year-old adults in OECD countries has fluctuated significantly over the past two decades, with notable peaks in 2005, between 2010 and 2013 following the 2008/09 financial crisis, and again in 2020/21 as a consequence of the COVID-19 pandemic. This pattern was observed across most OECD countries and across all levels of education, although the magnitude of the increases and decreases varied depending on attainment level and on the specific countries. Tertiary-educated young adults, for example, were better shielded from negative labour market shocks, experiencing lower overall unemployment rates and less pronounced spikes. On average across the OECD, the unemployment rate among young adults without an upper secondary education rose by 7 percentage points between 2008 and 2010 and remained relatively elevated until 2013. In contrast, the increase among tertiary-educated 25–34 year-olds was more moderate, rising by just 3 percentage points between 2008 and 2013 (OECD, 2025[6]).
By 2023/24, unemployment rates for young adults had generally returned to pre-pandemic levels. In the most recent years for which data are available, the unemployment gap between tertiary-educated individuals and those with lower educational attainment has slightly narrowed but remains broadly in line with and does not break from long-term trends. The following paragraphs provide a cross-country overview of recent unemployment figures compared to pre-COVID-19 levels.
In per cent
1.Year of reference differs from 2024.
2.Year of reference differs from 2019.
3.Break in time series between 2019 and 2024.
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 (9% of adults aged 25-34 are in this group).
For data, see Table A3.4. For a link to download the data, see Tables and Notes section.
On average across OECD countries, unemployment rates have decreased or remained stable between 2019 and 2024 for each level of attainment. However, in a few countries, such as Finland and Romania, the unemployment rate for 25-34 year-old adults who have not attained upper secondary education has increased by at least 6 percentage points between 2019 and 2024. Argentina and Italy show the opposite pattern: the unemployment rate among 25-34 year-olds with below upper secondary attainment has fallen by at least 6 percentage points between 2019 and 2024. However, this figure should be interpreted with caution, as this country has seen the inactivity rate of those with below upper secondary attainment increase over the same period (Table A3.4).
Despite tertiary attainment rates among 25-34 year-olds increasing from 45% in 2019 to 48% in 2024 on average across OECD countries (see Chapter A1), there are few signs that the labour-market benefits of a tertiary degree are diminishing. Among 25-34 year-olds, the average gap in unemployment rates between those with tertiary attainment and those with lower levels of attainment is almost the same in 2024 as it was in 2019. In aggregate across the OECD, the labour market has absorbed a growing number of tertiary-educated workers without any noticeable effect on their unemployment rates (Figure A3.4, Table A3.4 and see Table A1.2).
Unemployment rates and fields of study
Although unemployment rates can be low for tertiary-educated adults across all fields, they still show notable variation by field of study, particularly in some countries. Within individual countries, the largest differences between unemployment rates across fields of study are in Costa Rica, where unemployment rates among tertiary-educated adults can vary by more than 35 percentage points, depending on the fields they studied. The remaining OECD countries have smaller differences between fields (Figure A3.5 and Table A3.6, available on line).
Although the differences in unemployment rates between fields of study are small, they are very consistent across OECD countries. For example, unemployment rates for adults with tertiary attainment in ICT are lower than for those with tertiary attainment in arts and humanities and social sciences, journalism and information in all but six OECD countries. STEM tertiary-educated graduates tend to have the lowest unemployment rates on average across OECD countries, compared to other fields (Table A3.6, available on line).
In per cent; 25-64 year-olds
1. Year of reference differs from 2024.
For data, see Table A3.6 (available on line). For a link to download the data, see Tables and Notes section.
Duration of unemployment
How long people remain unemployed offers a wider perspective on labour-market difficulties than overall unemployment rates. Duration of unemployment tends to decrease with higher educational attainment. On average across the OECD, 25% of unemployed adults with tertiary attainment have been unemployed for 12 months or longer, compared to 30% of those with upper secondary or post-secondary non-tertiary attainment and 36% of those with below upper secondary attainment. Tertiary-educated adults have a lower incidence of long-term unemployment than adults with lower levels of educational attainment in about two-thirds of OECD countries. However, Figure A3.6 shows only the share of long-term unemployment relative to unemployed adults. In countries with higher overall unemployment, the total number of long-term unemployed – particularly among those with lower education levels – can be significantly higher than the relative shares suggest (Figure A3.6).
In per cent; 25-64 year-olds
Note: The numbers in parentheses represent the aggregated long-term unemployment rates across all levels of education
1. Year of reference differs from 2024.
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).
For data, see Table A3.5. For a link to download the data, see Tables and Notes section.
Most unemployment is short term as the unemployed usually find new jobs within a few months. However, this pattern does not hold for unemployed adults with below upper secondary attainment. Among this group, 36% have been unemployed for more than 12 months compared to 30% who have been unemployed for 3-12 months and 34% who have been unemployed for less than 3 months. This contrasts with individuals who have completed upper secondary or tertiary education, where long-term unemployment (12 months or more) remains less common than shorter spells. Among unemployed tertiary-educated adults, the share of long-term unemployed is significantly lower (25%) compared to those unemployed for 3-12 months (35%), highlighting that individuals with higher levels of education, particularly those with tertiary qualifications, are less likely to remain unemployed for extended periods (Table A3.5).
Educational attainment and adults outside the labour force
Labour-market inactivity, or individuals who are neither employed nor seeking employment, also differs significantly by educational attainment. On average, the inactivity rate among young adults (25-34 year-olds) in 2024 was 9% for those with tertiary attainment, compared to 15% for those with upper secondary or post-secondary non-tertiary attainment and 31% for those with below upper secondary attainment (Figure A3.7). These differences underscore the persistent labour-market disadvantages faced by low-educated individuals. In particular, young adults with below upper secondary attainment are over three times more likely to be outside the labour force than their tertiary-educated peers.
Despite the relatively low average for tertiary-educated young adults, labour-market inactivity rates among this group can vary widely across OECD and partner countries – from as low as 4% in Lithuania to 32% in India (Table A3.4). High inactivity rates can indicate deep structural challenges, such as long-term exclusion from the labour market, skills mismatches, health inequities or ineffective job matching systems. These conditions may reduce economic output, worsen inequality and erode individual well-being. High inactivity rates can also reflect social norms around gender roles and caregiving responsibilities.
In per cent
1.Year of reference differs from 2024.
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 (9% of adults aged 25-34 are in this group).
1. Year of reference differs from 2019.
For data, see Table A3.4. For a link to download the data, see Tables and Notes section.
Labour-market inactivity is correlated to prolonged illnesses. Studies indicate a strong correlation between poor health and inactivity, with over one-third of economically inactive individuals in the United Kingdom experiencing long-term health issues (Crawshaw et al., 2024[7]). Those with long-term illnesses consistently exhibit lower labour-market participation and higher unemployment rates compared to their healthier counterparts. Among the economically inactive, those who are long-term sick are more likely to want to work but less likely to actively seek or secure a job, and the shift to homeworking during the pandemic has not reduced these disparities (Haskel and Martin, 2022[8]).
Before the OECD Survey of Adult Skills (a product of the Programme for the International Assessment of Adult Competencies; PIAAC), few studies had explored the labour-market returns to skills independent of formal educational attainment. Instead, qualifications were typically used as proxies for skill levels, blurring the distinction between what individuals know and what credentials they hold (OECD, 2024[9]; Barro and Lee, 2013[10]; Hanushek and Woessmann, 2011[11]). While there are sound theoretical reasons to expect a correlation – more skilled individuals are more likely to pursue further education, and education itself develops skills – this relationship is not deterministic. Education may also serve as a signal of ability or a way to navigate employers’ screening processes, rather than solely reflecting the acquisition of skills (OECD, 2024[9]) .
The Survey of Adult Skills Cycle 2 (OECD, 2024[9]) confirms that both education and skills are positively associated with employment status. Individuals with higher proficiency are more likely to be employed, and employment itself can offer further opportunities to develop skills. However, the strength of this association varies across countries, potentially reflecting differences in the “skills transparency” of qualifications – that is, how accurately formal credentials signal actual skills.
Across participating OECD countries and economies, the Survey of Adult Skills found that average proficiency in literacy, numeracy and adaptive problem solving is consistently higher among employed adults than among those who are unemployed or inactive. High-skilled individuals are also less likely to face unemployment. On average, a one standard deviation increase in numeracy proficiency (58 points) is associated with a 4 percentage point increase in the likelihood of participating in the labour market (OECD, 2024[9]). However, the link between skills, education and employment has weakened compared to ten years ago, when most countries participated in the first cycle of the Survey. The analysis shows that in countries where unemployment fell between 2012 and 2023, the association between numeracy proficiency and employment also diminished. This suggests that tighter labour markets in 2022/23 may have reduced the relative advantage of higher skills, bringing more individuals into employment regardless of their proficiency. It is worth noting, however, that not all the effects found are statistically significant at the 5% level (OECD, 2024[9]).
Data from the Survey of Adult Skills Cycle 2 confirm the link between labour-force status and both educational attainment and numeracy proficiency. Adults with tertiary education and high proficiency levels (at or above Level 4) are significantly more likely to be employed, while those with low educational attainment and low proficiency levels (at or below Level 1) face much higher risks of unemployment or exclusion from the labour force. These findings reaffirm the dual importance of formal qualifications and functional skills in ensuring employability and labour-market resilience (OECD, 2024[9]).
The positive correlation between educational attainment and employment among 25-64 year-olds is illustrated in Figure A3.8. Across the countries and economies taking part in the Survey of Adult Skills Cycle 2, employment rates rise with educational attainment even when the numeracy skills is the same at or below Level 2: 60% for those with below upper secondary education, 75% for those with upper secondary or post-secondary non-tertiary attainment and 83% for those with tertiary education.
There is also a positive correlation between numeracy proficiency and employment among 25-64 year-olds. Across the countries and economies taking part in the Survey of Adult Skills Cycle 2, employment rates rise with each proficiency and educational attainment level. This steep gradient reflects the central role of skills in enabling adults to perform effectively in the labour market. On average across the OECD, the employment rate for adults with numeracy proficiency at or below Level 1 ranges from 56% for those with below upper secondary attainment to 70% for those with upper secondary or post-secondary non-tertiary qualifications and 77% for tertiary-educated adults. For adults with numeracy proficiency at Level 2 and 3, employment rates range from 67% (Level 2) and 73% (Level 3) for those with below upper secondary attainment to 85% (Level 2) and 89% (Level 3) for those with a tertiary qualification. At the highest levels of proficiency (at or above Level 4), the employment rate reaches 88% on average for upper secondary or post-secondary non-tertiary educational attainment and 92% for tertiary attainment (Table A3.7, available on line).
Although the positive relationship between education, skills and employment prospects is observed across all participating countries, the magnitude of the difference varies considerably. In Croatia and Israel, employment rates among tertiary-educated adults are at least 30 percentage points higher than among those with below upper secondary attainment across all numeracy proficiency levels – suggesting a strong impact of educational attainment. In contrast, in Austria, Czechia and the Netherlands, adults with numeracy proficiency at or above Level 4 have employment rates that are at least 24 percentage points higher than those scoring at or below Level 1, regardless of their level of education. In these countries, proficiency appears to have a stronger association with employment outcomes than formal qualifications (Table A3.7, available on line).
Survey of Adult Skills (PIAAC); 25-64 year-olds; in per cent
Note: The numbers in parentheses represent the shares of 25-64 year-olds in employment with numeracy proficiency at or below Level 2 among those with below upper secondary attainment, with upper secondary or post-secondary non-tertiary education, and with tertiary education respectively.
For data, see Table A3.9 (available on line) and Table A3.11 (available on line). For a link to download the data, see Tables and Notes section.
Trends in employment, by educational attainment and numeracy proficiency
Table A3.8, available on line, tracks changes in employment rates between 2012 and 2023 across different levels of educational attainment and numeracy proficiency. Overall, adults with higher levels of education and proficiency were more likely to experience stable or improved labour-market outcomes. In many countries, employment rates increased for tertiary-educated adults with proficiency at or above Level 3, even amid global economic disruptions. In contrast, employment rates stagnated or declined for adults with low proficiency (at or below Level 1), particularly among those who had not completed upper secondary education.
Country-level data show important differences. In Estonia, New Zealand and Sweden, employment among low-educated adults with proficiency Level 3 remained relatively strong, reflecting more inclusive labour markets. In contrast, England (United Kingdom), Finland and France display persistently low employment rates among adults with both low educational attainment and low proficiency. These variations suggest that while skills matter universally, national education systems and labour-market structures play a key role in shaping how proficiency translates into employment opportunities (Table A3.8, available on line).
Employment, by field of study and numeracy proficiency
Among tertiary-educated adults, field of study significantly influences employment outcomes, especially when combined with numeracy proficiency. On average across OECD countries, the employment rate ranges from 80% to 94% among adults who studied in the field of education, depending on their numeracy level; from 77% to 90% for those who studied arts and humanities, social sciences, journalism and information; from 79% to 92% for business, administration and law; from 81% to 93% for STEM fields; and from 80% to 93% for those in health and welfare fields. Within each country and among adults who studied the same field, those with higher numeracy proficiency consistently achieve higher employment rates (Table A3.10, available on line).
Patterns relating to the field of study differ across countries, underscoring the importance of aligning education and skills development with local labour-market demand. The field of study seems to matter more for the employment prospects of adults with lower numeracy proficiency than for those with higher skills. Among low-proficiency adults, employment rates vary widely depending on the field, with particularly low rates for arts and humanities and also in some countries for education and for business, administration and law. In contrast, employment rates among adults with high numeracy proficiency levels tend to converge across fields, suggesting that strong numeracy skills may compensate for any mismatch between labour-market demand and fields of study. These findings highlight the role of national education and skills policies in shaping demand for qualifications and skill profiles, as well as the importance of skills-based curricula and career guidance to help graduates succeed in the labour market (Table A3.10, available on line).
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.
Fields of study are categorised according to the ISCED fields of education and training (ISCED-F 2013). See the Reader’s Guide for full listing of the ISCED fields used in this report.
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.
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).
For information on methodology, 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[12]) and the Education at a Glance 2025 Sources, Methodologies and Technical Notes (https://doi.org/10.1787/fcfaf2d1-en)
For information on sources, see Chapter A1.
Data on subnational regions for selected indicators are available in the OECD Regional Statistics Database http://oe.cd/geostats.
Data on proficiency levels and mean scores are based on the Survey of Adult Skills (PIAAC) (2012 and 2023). PIAAC is the OECD Programme for the International Assessment of Adult Competencies.
References
[2] Auriol, . (2013), “Careers of Doctorate Holders: Analysis of Labour Market and Mobility Indicators”, https://doi.org/10.1787/5k43nxgs289w-e.
[10] Barro, R. and J. Lee (2013), “A new data set of educational attainment in the world, 1950–2010”, Journal of Development Economics, Vol. 104, pp. 184-198, https://doi.org/10.1016/j.jdeveco.2012.10.001.
[7] 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.
[11] Hanushek, E. and L. Woessmann (2011), “The economics of international differences in educational achievement”, in Handbook of the Economics of Education, Elsevier, https://doi.org/10.1016/b978-0-444-53429-3.00002-8.
[8] Haskel, J. and J. Martin (2022), “Economic inactivity and the labour market experience of the long-term sick”, Imperial College.
[6] OECD (2025), OECD Data Explorer, Unemployment rates of adults, by educational attainment, age group and gender, http://data-explorer.oecd.org/s/4s.
[1] OECD (2025), Research and Innovation Careers Observatory, https://www.oecd.org/en/networks/research-and-innovation-careers-observatory.html.
[9] 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.
[5] OECD (2023), OECD Territorial Grids, OECD, Paris, https://www.oecd.org/content/dam/oecd/en/data/datasets/oecd-geographical-definitions/territorial-grid.pdf.
[3] OECD (2023), Promoting diverse career pathways for doctoral and postdoctoral researchers, https://www.oecd.org/content/dam/oecd/en/publications/reports/2023/09/promoting-diverse-career-pathways-for-doctoral-and-postdoctoral-researchers_9fdc38f5/dc21227a-en.pdf?utm_source=chatgpt.com.
[4] OECD (2021), Reducing the precarity of academic research careers, https://www.oecd.org/content/dam/oecd/en/publications/reports/2021/05/reducing-the-precarity-of-academic-research-careers_2d4e2194/0f8bd468-en.pdf?utm_source=chatgpt.com.
[12] OECD (2017), OECD Handbook for Internationally Comparative Education Statistics: Concepts, Standards, Definitions and Classifications, OECD Publishing, Paris, https://doi.org/10.1787/9789264279889-en.
To download the data for the figures and tables in this chapter, click StatLink above.
To access further data and/or other education indicators, please visit the OECD Data Explorer: https://data-explorer.oecd.org/.
Data cut-off for the print publication 13 June 2025. Please note that the Data Explorer contains the most recent data.
Table A3.1 Employment rates of adults, by educational attainment (2024)
Note: Data refer to ISCED 2011 for all countries except for Argentina and India. Data for Argentina, India, and Indonesia from the International Labour Organization (ILO).
1. Year of reference differs from 2024: 2023 for Argentina, Brazil, Iceland, India and the United States; 2022 for Chile 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 (12% of adults aged 25-64 are in this group).
Table A3.2 Trends in employment rates of 25-34 year-olds, by educational attainment and gender (2019 and 2024)
Note: Totals might not add up to 100% for the averages because of missing data for some levels for some countries. Data refer to ISCED 2011 for all countries except for Argentina and India. Data for Argentina, India, and Indonesia from the International Labour Organization (ILO). Columns showing data for category totals are available for consultation on line.
1. Year of reference differs from 2024: 2023 for Argentina, Brazil, Iceland, India and the United States; 2022 for Chile and Indonesia.
2. Year of reference differs from 2019: 2022 for Peru; 2020 for Chile.
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 (9% of adults aged 25-34 are in this group).
Table A3.3 Employment rates of tertiary-educated adults, by field of study (2024)
Note: Data on humanities (except languages), social sciences, journalism and information might refer to the broad field social sciences, journalism and information only. Data in column 14 might differ from data in Table A3.1 column 9 due to differences in country coverage and reference years.
1. Year of reference differs from 2024: 2021 for Canada, Denmark, Ireland and the United Kingdom; 2022 for Chile.
Table A3.4 Trends in the rates for 25-34 year-olds unemployed or outside the labour force, by educational attainment (2019 and 2024)
Note: Data refer to ISCED 2011 for all countries except for Argentina and India. Data for Argentina, India, and Indonesia from the International Labour Organization (ILO).
1. Year of reference differs from 2024: 2023 for Argentina, Brazil, Iceland, India and the United States; 2022 for Chile and Indonesia.
2. Year of reference differs from 2019: 2022 for Peru, 2020 for Chile.
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 (9% of adults aged 25-34 are in this group).
Table A3.5 Unemployment rates for adults and distribution of unemployment by duration, by educational attainment (2024)
Note: Data refer to ISCED 2011 for all countries except for Argentina and India. Data for Argentina, India, and Indonesia from the International Labour Organization (ILO). Columns showing data for less than 12 months and showing data for all levels of education are available for consultation on line.
1. Year of reference differs from 2024: 2021 for Argentina, Brazil, Indonesia, Japan and the United States; 2022 for Chile, 2021 for Colombia.
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).
a – category not applicable; b – break in series; c – there are too few observations to provide reliable estimates; d – contains data from another column; m – missing data; r – values are below a certain reliability threshold and should be interpreted with caution 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 2025: Sources, Methodologies and Technical Notes (https://doi.org/10.1787/fcfaf2d1-en).
Percentage of employed 25-64 year-olds among all 25-64 year-olds
Note: For notes on this table and a link to download the data, see Tables and Notes section above.
Percentage of employed 25-34 year-olds among all 25-34 year-olds
Note: For notes on this table and a link to download the data, see Tables and Notes section above.
Percentage of employed 25-64 year-olds among all 25-64 year-olds
Note: For notes on this table and a link to download the data, see Tables and Notes section above.
Rates for those outside the labour force are measured as a percentage of all 25-34 year-olds; unemployment rates as a percentage of 25-34 year-olds in the labour force
Note: For notes on this table and a link to download the data, see Tables and Notes section above.
Percentage of unemployed 25-64 year-olds among 25-64 year-olds in the labour force
Note: For notes on this table and a link to download the data, see Tables and Notes section above.