Employment rates for younger adults (25-34 year-olds) slightly improved in most countries between 2016 and 2023, irrespective of their educational attainment level. However, the gap in employment rates between younger adults with below upper secondary attainment and those with tertiary attainment has widened in more than half of OECD, partner and/or accession countries with comparable data for both years.
Between 2016 and 2023, subnational regions with particularly low employment rates for 25-64 year-olds with below upper secondary attainment have shown considerable improvement, leading to a convergence in regional employment rates for some countries.
Older workers without an upper secondary education are more likely to leave the labour market early. On average across OECD countries, nearly half of 55-64 year-olds with below upper secondary attainment have exited the workforce, compared to only one in five tertiary-educated adults in that age group.
Education at a Glance 2024
Modern economies depend heavily on a supply of highly skilled workers who, in turn, reap substantial labour-market benefits. These advantages, coupled with expanded educational opportunities, are some of the motivations for individuals across the OECD to pursue higher levels of education to 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 (OECD, 2023[1]). Conversely, adults with lower levels of qualifications face more challenging labour-market prospects, including lower earnings (see Chapter A4) and a greater risk of unemployment.
Automation poses an ongoing threat to today’s labour market, with occupations at the highest risk of automation accounting for 27% of employment across OECD countries (OECD, 2023[1]). The rapid development of artificial intelligence (AI) has introduced new challenges and opportunities to the labour market. As AI expands the range of tasks that could be automated beyond routine, non-cognitive tasks, it also brings the need for new skills. Additionally, ageing has an uneven impact on older workers, particularly those lacking higher education, who are more likely to leave the workforce early, leading to pension disparities and economic insecurity (OECD, 2019[2]). Education systems at all levels must respond to these emerging challenges, ensuring that all individuals, regardless of gender, age or migration status, can benefit from economic opportunities.
Among younger adults with at least a bachelor’s or equivalent degree, the gender gap in employment rates in favour of men has fallen from 8 percentage points in 2016 to 5 percentage points in 2023 on average across OECD countries with comparable data for both years.
Foreign-born women face a dual challenge in the labour market as immigrants and as women, regardless of their level of educational attainment. For instance, the gender gap in employment rates among native-born tertiary-educated adults stands at 5 percentage points in favour of men on average across OECD countries, but is more than double that among foreign-born adults, at 13 percentage points.
Workers with below upper secondary attainment are more likely to have temporary contracts or be in involuntary part-time jobs compared to their peers with greater educational attainment. For example, on average across OECD countries with available data, 12% of 25-64 year-old employees are on temporary contracts, compared to 8% of those with higher levels of educational attainment.
Greater educational attainment is associated with higher employment rates, lower unemployment and labour-market inactivity rates. This relationship exists in nearly all OECD, partner and/or accession countries with available data, regardless of gender, age group, immigration background or subnational region. On average across OECD countries, 60% of adults (25-64 year-olds) with below upper secondary attainment are employed, compared to 77% of those with upper secondary or post-secondary non-tertiary attainment and 87% of tertiary-educated adults (Table A3.1). In parallel, 9.0% of adults with below upper secondary attainment are unemployed and 34% are inactive; 5.1% of those with upper secondary or post-secondary non-tertiary attainment are unemployed and 19% are inactive; and 3.4% of those with tertiary attainment are unemployed and 10% are inactive (OECD, 2024[3]).
The analysis in this chapter focuses on labour-market outcomes and educational attainment, which refers to the highest level of education an individual has completed. It should be noted that progression through education is not always linear. A recent study from Canada has shown that adults with a bachelor’s or equivalent degree may go on to pursue an additional qualification at the same or lower level, to complement and enhance the skills they established during their higher education (Wall, 2021[4]). Interpreting the figures on labour-market status by educational attainment takes into account the fact that an individual’s attainment level may not always reflect the latest qualification that individual has obtained.
A higher level of education attained in a country generally offers better job opportunities for young people. On average across OECD countries, 61% of 25-34 year-olds with below upper secondary attainment are employed, compared to 79% among those with upper secondary or post-secondary non-tertiary attainment. The employment rate for younger adults with tertiary attainment is even higher, at 87%. Between 2016 and 2023, employment rates have slightly improved for younger adults of all attainment levels in most countries with comparable trend data. The increases tend to be the highest for those with tertiary attainment. Greece, Hungary and Italy have experienced the highest percentage-point increase in employment rates for tertiary-educated 25-34 year-olds, of at least 10 percentage points over this period (Table A3.2).
The rapidly evolving capacity of artificial intelligence (AI) has recently created fears of job losses or less job openings for some non-routine, cognitive tasks performed by adults with higher levels of education. However, the early evidence suggests that AI-related vacancies still only represent a small share of overall vacancies in the labour market as the adoption of AI technologies is highly concentrated in those establishments that have a task structure suitable for deploying AI-powered algorithms (Acemoglu et al., 2022[5]; Borgonovi et al., 2023[6]). While the impact of AI on the labour market is currently very small because AI adoption is not widespread, the progress is so rapid that the effects in 2024 will have to be measured carefully.
Although Artificial Intelligence (AI) and other digital technologies are likely to transform the employment skill structure by creating demand for skills that are complemented by technology rather than replaced by it, adults with low educational attainment are less likely to be able to adapt to the shift in skills needed (Lassébie and Quintini, 2022[7]; Autor, 2024[8]). Between 2016 and 2023, the gap in employment rates between 25-34 year-olds with below upper secondary attainment and those with tertiary attainment has widened in more than half of OECD, partner and/or accession countries with comparable trend data. Czechia is the only exception where the gap in employment rates between younger adults with below upper secondary attainment and those with tertiary attainment has reduced by over 10 percentage points over the same period (Table A3.2).
Personal and family responsibilities, including unpaid care work, often disproportionately affect women. These traditional gender roles can prevent women not just from working but also from actively searching for employment or being available to work at short notice (Gomis et al., 2023[9]). In most OECD, partner and/or accession countries, women have lower employment rates than their male peers, regardless of educational attainment but these gender disparities narrow as educational attainment increases. On average across OECD countries, the gender difference in employment rates is 21 percentage points among 25-64 year-olds with below upper secondary attainment, but it narrows to 14 percentage points among those with upper secondary or post-secondary non-tertiary attainment. Among those with tertiary attainment the gender gap closes even further to 7 percentage points (OECD, 2024[3]).
Many countries have seen signs of the gender gap in employment falling lately. Among younger adults, although the gender gap in employment rates remains in favour of men, it has narrowed by 1 percentage point between 2016 and 2023 for those with below upper secondary attainment and by 3 percentage points for those with upper secondary or post-secondary non-tertiary attainment, or tertiary attainment across OECD countries with comparable trend data. This differential is leading to widening differences in gender outcomes across educational attainment levels (Table A3.4).
In addition to evolving cultural norms, women’s advantages in social and interpersonal skills may have played some role in the narrowing of gender gaps in employment rates, particularly among those with higher levels of educational attainment (Cortes, Jaimovich and Siu, 2018[10]; Deming, 2017[11]). Between 2016 and 2023, among 25-34 year-olds with at least a bachelor’s or equivalent degree, the gender gap in employment rates, favouring men, has fallen from 8 percentage points to 5 percentage points on average across OECD countries with comparable trend data. The gender gap fell by at least 10 percentage points in Estonia, Greece, Hungary and the Slovak Republic. In Greece and Portugal, younger women with at least a bachelor’s or equivalent degree now have similar employment rates to their male peers (Figure A3.1.). This trend is likely to continue in the age of AI, as social skills are often complementary to AI skills (Alekseeva et al., 2021[12]).
Regional disparities in employment rates tend to be smaller among adults with higher levels of educational attainment. In Spain for example, employment rates among 25-64 year-olds with below upper secondary attainment are as low as 38% in Melilla, and as high as 69% in Aragon in 2023, a difference of over 30 percentage points. Meanwhile, the employment rates among tertiary-educated adults only range from 79% in the Canary Islands to 87% in Catalonia, a difference of just 8 percentage points (OECD, 2024[13]).
Some subnational regions with relatively low employment rates for adults lacking upper secondary attainment are catching up with better-performing regions in the country, resulting in the rates converging. Türkiye is a notable example: the difference between the employment rates in the Eastern Black Sea (the region with the highest rates) and Southeastern Anatolia East (with the lowest employment rates) fell by more than 10 percentage points between 2016 and 2022. In contrast, regional differences in employment rates for adults with below upper secondary attainment has widened by 20 percentage points or more in Poland and Romania over the same period. The employment rates for adults with at least an upper secondary degree have been relatively stable between 2016 and 2022 in most regions across countries (OECD, 2024[13]).
For both native-born and foreign-born adults, the likelihood of being employed increases with higher educational attainment, but the rise is steeper for native-born adults, suggesting that labour markets tend to underutilise the potential skills of foreign-born adults. On average across OECD countries, 60% of native-born adults and 63% of foreign-born adults with below upper secondary education are employed, rising to 77% of native-born and 75% of foreign-born adults with upper secondary or post-secondary non-tertiary attainment. For those with tertiary attainment, the employment rates are 88% for native-born and 82% for foreign-born adults (Table A3.4). A key factor in explaining these values are difficulties in transferring foreign qualifications into the host-country labour market context (OECD/European Union, 2014[14]).
The differences in labour-market outcomes for foreign-born and native-born adults vary widely across OECD countries but in almost all of them, foreign-born adults with tertiary attainment tend to have lower employment rates than their native-born peers. The difference exceeds 10 percentage points in favour of native-born adults in Austria, Bulgaria, France, Germany, Italy, Latvia and the Netherlands. In contrast, the difference in employment rates is no more than 2 percentage points in Czechia, Luxembourg and the Slovak Republic. Chile stands out as the only country where foreign-born adults with tertiary attainment enjoy slightly higher employment rates than their native-born peers (Table A3.4).
In contrast, the patterns in employment rates between native- and foreign-born adults with below upper secondary attainment vary widely. These differences are largely driven by differences in the composition of migration by category (OECD/European Commission, 2023[15])). In 14 out of 34 OECD, partner and/or accession countries with available data, native-born adults with below upper secondary attainment have higher employment rates than their foreign-born peers. The most striking difference is observed in Estonia, where it is above 20 percentage points. On the other hand, in Hungary, Israel and the U, the likelihood of being employed is more than 20 percentage points higher for foreign-born adults with below upper secondary attainment than for native-born adults with the same level of educational attainment (Table A3.4).
While the overall labour market presents challenges for women, the situation is particularly daunting for foreign-born women who face a dual challenge as immigrants and women. This issue persists regardless of their level of educational attainment (Table A3.4). For instance, among tertiary-educated adults, the gender gap in employment rates among native-born adults averages 5 percentage points in favour of men on average across OECD countries, but more than doubles among foreign-born adults, reaching 13 percentage points. However, Czechia and Israel stand out as having similar gender gaps in employment rates for both foreign-born and native-born adults with tertiary attainment, and the gender gaps in Mexico and the Slovak Republic are narrower for foreign-born tertiary-educated adults than for their native-born counterparts (Figure A3.2).
Higher educational attainment does not just increase employment rates but also safeguards workers against involuntary part-time and temporary employment. Box A3.1 illustrates how adults with lower educational attainment are more susceptible to non-standard employment arrangements.
Although employment rates are a crucial indicator of labour-market outcomes, they do not fully capture the quality and stability of jobs. It is essential to consider the nature of employment, as many workers may be in non-standard forms of employment, such as involuntary part-time or temporary positions, which often lack the benefits and security of full-time, permanent jobs.
On average across OECD countries, part-time employment accounts for 20% of all employment among 25-64 year-olds with below upper secondary attainment. This share falls to 16% among those with upper secondary or post-secondary non-tertiary attainment and 13% among tertiary-educated adults (Table A3.5, available on line). Part-time employment is often associated with wage penalties, job insecurity and fewer opportunities for career progression (OECD, 2020[16]), but in most countries, part-time workers are likely to be working shorter hours by choice, especially among tertiary-educated workers. On average, around 25% of part-time workers without a tertiary degree are in involuntary part-time employment, compared to 19% among their peers with tertiary attainment. This difference is above 20 percentage points in Finland, where around 40% of part-time workers without tertiary attainment are in involuntary part-time employment compared to less than 10% among tertiary-educated ones. Denmark, Latvia, the Netherlands and Portugal are the only exceptions where 25-64 year-old workers with tertiary attainment are more likely to be in involuntary part-time employment than those with below upper secondary attainment (Figure A3.3).
Women are more likely to opt for part-time work as a primary means to achieve work-life balance or fulfil family responsibilities (OECD, 2023[17]). For instance, recent studies in the Netherlands show that women who work part time do not extend their working hours, even when childcare needs have decreased. Factors determining the decision to work more hours include income and decreasing childcare needs. But type of work, (lack of) encouragement in the work environment, or from employer or partner, informal care and personal health play an almost equal role. Taken together, these factors do not always appear to make increased labour participation necessary or attractive' (Portegijs, 2022[18]).
In most countries with available data, the share of part-time workers is higher among women than men, and women are more likely to be working part time by choice compared to men. Higher educational attainment tends to reduce the gender gap in the incidence of involuntary part-time employment in most countries. For example, in the United States, the share of men with below upper secondary education working part time involuntarily relative to all part-time workers is 24 percentage points higher than the share among women with the same level of education. Among men and women with upper secondary or post-secondary non-tertiary attainment, the difference is 19 percentage points in favour of men. Among those with tertiary attainment, the difference is 15 percentage points in favour of men. Lithuania is a notable exception where women are at more risk of working part time involuntarily than men, with the gender gap increasing among tertiary-educated adults (Table A3.5, available on line).
About one in ten employees are on temporary contracts across OECD countries with available data. Adults lacking upper secondary attainment are more likely to work on temporary contracts. On average across OECD countries with available data, 12% of 25-64 year-old employees without upper secondary education work in jobs with temporary contracts, compared to 8% for those with higher levels of attainment. The difference is particularly striking in Argentina and Hungary, where the likelihood of working in temporary jobs is 20 percentage points higher for those with below upper secondary attainment than for tertiary-educated employees. Portugal is the exception, where the probability of working on a temporary contract increases with educational attainment (Table A3.6, available on line).
Adults engaged in temporary or part-time employment are at increased risk of falling into income poverty and often lack support from unemployment benefits (OECD, 2020[16]). This risk is particularly pronounced among workers with lower levels of educational attainment, who are more likely to be in these unstable forms of employment.
In the large majority of countries, unemployment rates fall as educational attainment rises. In many OECD and partner countries, unemployment rates (i.e., the share of adults who are without work, actively seeking employment and currently available to start work, as a percentage of the labour force) are especially high among younger adults with lower educational attainment levels. Measuring unemployment rates for young people can be challenging because many of them are still in education or training programmes and may not be actively seeking employment. To address this challenge, Education at a Glance uses alternative measures such as the percentage of young people who are neither employed nor in formal education or training (NEET) in Chapter A2 in addition to the analysis of unemployment rates that follows.
On average across OECD countries, the unemployment rate among 25-34 year-olds lacking upper secondary education is 13.2%, almost twice as high as for those with upper secondary or post-secondary non-tertiary attainment (7.0%). The rate falls further among those with tertiary attainment, to 4.7%. The situation is especially severe for younger adults without upper secondary education in South Africa, where almost half of this group are unemployed. Similarly, in the Slovak Republic, more than one in three younger adults without upper secondary education face unemployment (Table A3.3).
Younger women have a higher risk of being unemployed than their male counterparts but tertiary attainment reduces the gender gap considerably. On average across OECD countries, 11.8% of younger men with below upper secondary attainment are unemployed compared with 16.4% of their female peers. The unemployment rate falls to 6.3% among younger men with upper secondary or post-secondary non-tertiary attainment and 8.3% for their female counterparts. Among tertiary-educated younger adults, the unemployment rates are roughly equal, at around 4.5% for both men and women. In fact, in about half of OECD, partner and/or accession countries with available data, the gender gap in unemployment is reversed in favour of women among younger adults with tertiary attainment (Table A3.3).
The economic inactivity rate – the share of people who are neither working nor actively looking for a job – is another important measure of labour-market participation. There are large differences among countries in the inactivity rates of tertiary-educated younger adults across OECD countries. On average, 9% of 25-34 year olds with tertiary attainment are not in the labour force, but in Hungary, Lithuania and the Netherlands the share is 5%, while in Czechia the share is 21% (Table A3.3).
Retaining older adults in the workforce is receiving increasing policy attention, as populations in OECD countries are set to become older over the coming decades. Numerous OECD countries are presently undertaking pension and labour-market reforms with the aim of postponing retirement and prolonging careers, thereby ensuring the sustainability of public pensions (OECD, 2019[2]). However, these efforts to extend working lives may carry the risk of widening pension disparities, as workers lacking upper secondary education are more prone to leave the labour market prematurely (Venti and Wise, 2015[19]). On average across OECD countries, 46% of 55-64 year-olds with below upper secondary attainment are inactive, compared to 32% of those with upper secondary or post-secondary non-tertiary and 21% of those with tertiary attainment (Figure A3.4).
Governments and policy makers across the OECD have taken steps to promote employment among older adults. For example, the United Kingdom has launched the “returnership”, targeting adults over the age of 50 who are returning to work or seeking a career change (Government, UK, 2023[20]).
Inactivity rates among older age adults have fallen across OECD countries in recent years. Between 2016 and 2023, the inactivity rates among 55-64 year-olds have decreased by an average of about 5 percentage points across OECD countries with comparable data, regardless of educational attainment. Czechia, Hungary and Slovenia have seen the most substantial falls in the inactivity rates among 55-64 year-olds with below upper secondary attainment, with drops of at least 15 percentage points (OECD, 2024[3]).
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.
Country of birth: Native-born individuals are those who were born in the country where they answered the survey, and foreign-born individuals are those who were born outside the country where they answered the survey.
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 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.
Workers in part-time employment refer to those whose usual hours of work in their main job are less than those of comparable full-time workers. The usual hours worked in the main job are based on national definitions. Workers in involuntary part-time employment refer to those working part-time who wish to work additional hours (but not necessarily full time). For more details on national definition, refer to Education at a Glance 2024 Sources, Methodologies and Technical Notes (https://doi.org/10.1787/e7d20315-en).
Employees in temporary employment refer to wage and salary workers/employees whose main job has limited duration contract.
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 more information see Source section and Education at a Glance 2024 Sources, Methodologies and Technical Notes (https://doi.org/10.1787/e7d20315-en ).
For information on sources, see Chapter A1.
Data on subnational regions for selected indicators are available in the OECD Education and Skills-Subnational education and indicators (OECD, 2024[13]).
References
[5] Acemoglu, D. et al. (2022), “Artificial intelligence and jobs: Evidence from online vacancies”, Journal of Labor Economics, Vol. 40/S1, pp. S293-S340, https://doi.org/10.1086/718327.
[12] Alekseeva, L. et al. (2021), “The demand for AI skills in the labor market”, Labour Economics, Vol. 71, p. 102002, https://doi.org/10.1016/j.labeco.2021.102002.
[8] Autor, D. (2024), “Applying AI to rebuild middle class jobs”, NBER Working Paper, No. 32140, National Bureau of Economic Research, Cambridge, MA, https://doi.org/10.3386/w32140.
[6] Borgonovi, F. et al. (2023), “Emerging trends in AI skill demand across 14 OECD countries”, OECD Artificial Intelligence Papers, No. 2, OECD Publishing, Paris, https://doi.org/10.1787/7c691b9a-en.
[10] Cortes, G., N. Jaimovich and H. Siu (2018), “The “end of men” and rise of women in the high-skilled labor market”, NBER Working Paper, No. 24274, National Bureau of Economic Research, Cambridge, MA, https://doi.org/10.3386/w24274.
[11] Deming, D. (2017), “The growing importance of social skills in the labor market*”, The Quarterly Journal of Economics, Vol. 132/4, pp. 1593-1640, https://doi.org/10.1093/qje/qjx022.
[9] Gomis, R. et al. (2023), “New data shine light on gender gaps”, Spotlight on Work Statistics, No. 12, International Labour Organization, https://www.ilo.org/publications/new-data-shine-light-gender-gaps-labour-market (accessed on 22 May 2024).
[20] Government, UK (2023), Budget 2023: What are ‘returnerships’ and who are they for?, UK.GOV blogs, https://educationhub.blog.gov.uk/2023/03/17/budget-2023-what-are-returnerships-and-who-are-they-for/.
[7] Lassébie, J. and G. Quintini (2022), “What skills and abilities can automation technologies replicate and what does it mean for workers? New evidence”, OECD Social, Employment and Migration Working Papers, No. 282, OECD Publishing, Paris, https://doi.org/10.1787/646aad77-en.
[13] OECD (2024), Education and Skills-Subnational education and indicators, http://data-explorer.oecd.org/s/3q (accessed on 31 May 2024).
[3] OECD (2024), OECD Data Explorer, http://data-explorer.oecd.org/s/4s.
[17] OECD (2023), Joining Forces for Gender Equality: What is Holding us Back?, OECD Publishing, Paris, https://doi.org/10.1787/67d48024-en.
[1] OECD (2023), OECD Employment Outlook 2023: Artificial Intelligence and the Labour Market, OECD Publishing, Paris, https://doi.org/10.1787/08785bba-en.
[16] OECD (2020), OECD Employment Outlook 2020: Worker Security and the COVID-19 Crisis, OECD Publishing, Paris, https://doi.org/10.1787/1686c758-en.
[2] OECD (2019), Working Better with Age, Ageing and Employment Policies, OECD Publishing, Paris, https://doi.org/10.1787/c4d4f66a-en.
[15] OECD/European Commission (2023), Indicators of Immigrant Integration 2023: Settling In, OECD Publishing, Paris, https://doi.org/10.1787/1d5020a6-en.
[14] OECD/European Union (2014), Matching Economic Migration with Labour Market Needs, OECD Publishing, Paris, https://doi.org/10.1787/9789264216501-en.
[18] Portegijs, W. (2022), Eens deeltijd, altijd deeltijd. Waarom vrouwen in deeltijd blijven werken als ze ’uit’ de kleine kinderen zijn, https://www.scp.nl/publicaties/publicaties/2022/09/28/eens-deeltijd-altijd-deeltijd.-waarom-vrouwen-in-deeltijd-blijven-werken-als-ze-uit-de-kleine-kinderen-zijn.
[19] Venti, S. and D. Wise (2015), “The long reach of education: Early retirement”, The Journal of the Economics of Ageing, Vol. 6, pp. 133-148, https://doi.org/10.1016/j.jeoa.2015.08.001.
[4] Wall, K. (2021), “Completion of a college certificate or diploma after a bachelor’s degree”, Insights on Canadian Society, Statistics Canada, https://www150.statcan.gc.ca/n1/pub/75-006-x/2021001/article/00001-eng.htm.
Cut-off date for the data: 14 June 2024. Any updates on data can be found on line at. Data and more breakdowns are available on the OECD Data Explorer (http://data-explorer.oecd.org/s/4s).
Percentage of employed 25-64 year-olds among all 25-64 year-olds
Note: See under Chapter A3 Tables for StatLink and Box A3.1 for the notes related to this Table.
Source: OECD (2024). See Source section for more information and Education at a Glance 2024 Sources Methodologies and Technical Notes (https://doi.org/10.1787/e7d20315-en).
Percentage of employed 25-34 year-olds among all 25-34 year-olds
Note: See under Chapter A3 Tables for StatLink and Box A3.1 for the notes related to this Table.
Source: OECD (2024). See Source section for more information and Education at a Glance 2024 Sources Methodologies and Technical Notes (https://doi.org/10.1787/e7d20315-en).
Unemployment rates measured as a percentage of 25-34 year-olds in the labour force; inactivity rates as a percentage of all 25-34 year-olds
Note: See under Chapter A3 Tables for StatLink and Box A3.1 for the notes related to this Table.
Source: OECD (2024). See Source section for more information and Education at a Glance 2024 Sources Methodologies and Technical Notes (https://doi.org/10.1787/e7d20315-en).
Percentage of employed 25-64 year-olds among all 25-64 year-olds
Note: See under Chapter A3 Tables for StatLink and Box A3.1 for the notes related to this Table.
Source: OECD (2024). See Source section for more information and Education at a Glance 2024 Sources Methodologies and Technical Notes (https://doi.org/10.1787/e7d20315-en).
Table A3.1. Employment rates of 25–64-year-olds, by educational attainment (2023)
Note: In most countries data refer to ISCED 2011. For Argentina and India data refer to ISCED-97. See Definitions and Methodology sections for more information.
1. Year of reference differs from 2023: 2022 for Chile and Indonesia.
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 (11% 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 (2016 and 2023)
Note: In most countries data refer to ISCED 2011. For Argentina and India data refer to ISCED-97. See Definitions and Methodology sections for more information. Columns showing the total for both men and women are available for consultation on line.
1. Year of reference differs from 2016: 2015 for Chile and Romania; and 2014 for Argentina.
2. Year of reference differs from 2023: 2022 for Chile and Indonesia.
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 (11% of adults aged 25-64 are in this group).
Table A3.3. Unemployment and inactivity rates of 25–34-year-olds, by educational attainment and gender (2023)
Note: In most countries data refer to ISCED 2011. For Argentina and India data refer to ISCED-97. See Definitions and Methodology sections for more information. Columns showing the total for both men and women are available for consultation on line.
1. Year of reference differs from 2023: 2022 for Chile and Indonesia.
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 (11% of adults aged 25-64 are in this group).
Table A3.4. Employment rates of native- and foreign-born adults, by age at arrival in the country, educational attainment and gender (2023)
Note: See Definitions and Methodology sections for more information. Columns showing the breakdown by gender are available for consultation on line.
1. Year of reference differs from 2023: 2022 for Chile; and 2017 for Ireland.
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 (11% of adults aged 25-64 are in this group).
Data and more breakdowns are available on the OECD Data Explorer (http://data-explorer.oecd.org/s/4s).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.