Across OECD countries, 54% of 18–24 year-olds are in education, and 19% combine work and study. This is nearly twice the share observed among 25–29 year-olds (10%), highlighting that younger adults are more likely to combine education with employment. The Netherlands stands out, with 51% of 18–24 year-olds enrolled in education and employed.
The shares of young people who are neither employed nor in education or training (NEET) are now below pre-pandemic levels in about half of OECD and partner countries with available trend data. In 8 of these 16 countries, the decline exceeds 1 percentage point. Meanwhile NEET rates have risen in almost the same number of OECD countries. Among the 17 countries where rates now exceed their pre‑pandemic benchmarks, 6 have seen increases of more than 2 percentage points.
For most youth, unemployment tends to last only a short spell of time. Across the OECD, less than 2% of 18-24 and 25-29 year-olds are unemployed and have been out of work for 12 months or more, while around 4% have been looking for work for under a year.
Education at a Glance 2025
Context
The transition from education to employment is a complex process influenced by factors such as educational attainment, economic conditions and labour-market demand. Although education plays a fundamental role in improving young people’s employment prospects, it is crucial that the skills they acquire through education are aligned with those needed in the labour market. Many young people stay in education to enhance their employability but if their skills are not in demand, they may continue to face difficulties finding employment. Economic downturns and weak labour markets can further limit opportunities, leaving even highly qualified individuals struggling to find work and increasing the risk of prolonged unemployment.
Extended periods of unemployment can have serious consequences, particularly for young people whose working lives may later be impacted by the consequences of such early joblessness. Being out of the labour market for an extended period reduces their opportunities to gain work experience and develop essential soft skills, making it increasingly difficult to secure employment. Employers may also perceive employment gaps negatively, further compounding the challenge. This cycle of limited experience and prolonged unemployment can lead to persistent labour-market and social exclusion, especially for those with lower levels of educational attainment or work qualifications (Pohlan, 2024[1]).
In addition to the economic implications, long-term unemployment can have significant psychological effects, including increased discouragement and mental health challenges such as anxiety and depression, which may further reduce motivation to seek employment (see Chapter A6). Better co-ordination between education systems and labour markets is needed to address these challenges and ensure that young people develop skills aligned with workforce needs. Policy measures should also improve employment opportunities, providing career guidance and offering mental health support. Strengthening the link between education and employment can help mitigate the risks of long-term unemployment and social disengagement of young people.
In per cent
1. Year of reference differs from 2024.
For data, see Table A2.1. For a link to download the data, see Tables and Notes section.
Other findings
Despite NEET rates largely returning to pre-pandemic levels, they remain high in several countries. On average, 14 % of 18-24 year-olds are NEET across OECD countries, but the share exceeds 25% in Colombia, the Republic of Türkiye and OECD partner country South Africa.
Although average employment and NEET rates among 18-24 year-olds have remained virtually unchanged between 2019 and 2024, several countries have seen large differences within the overall figures. In Estonia, employment ratios fell by nearly 12 percentage points for men while increasing nearly 11 percentage points for women over the period. Meanwhile, Norway saw a 13 percentage-point decrease in employment rates coupled with a 16 percentage-point increase in those in education.
Across OECD countries, the gender gap in education among 18-24 year-olds continues to favour women by more than 6 percentage points, with about 55% of women and 49% of men in education in both 2019 and 2024. In contrast, men were about 8 percentage points ahead of women in employment, with about 36% of men and 28% of women employed in both years.
Note
This chapter analyses the situation of young people in transition from education to work: those in education, those who are employed and those who are NEET. The NEET group includes not only those who have not managed to find a job (unemployed NEETs), but also those who are not actively seeking employment (NEETs outside the labour force, or inactive). The analysis distinguishes between 18-24 year-olds and 25-29 year-olds, as a significant proportion of those in the younger age group will be continuing their studies despite having completed compulsory, or in some countries even beyond compulsory, education.
Transition from education to work for 18-24 year-olds
Individuals aged 18-24 are generally engaged in either education or employment, as this age range often coincides with participation in upper secondary or tertiary education, as well as initial entry into the labour market. This stage is critical in shaping future career trajectories and developing key skills for workforce participation. Despite this, a share of young people in this age group are neither in education nor employment and are classified as NEETs, suggesting that they may face underlying barriers to labour-market entry or continued education (Table A2.1.).
NEET rates can result from limited job opportunities in difficult economic conditions or a mismatch between young people’s skills and labour-market demands. For example, dual labour markets – offering stable, well-paid‑ positions to some and precarious, low wage‑ jobs to others – exacerbate the risk of young people falling out of both work and study (Marques and Salavisa, 2017[2]). The status of being NEET also often stems not only from these structural labour market challenges or skills mismatches, but also from personal and social factors such as long term physical or mental health issues, addiction, exposure to violence and weak support networks (Rahmani and Groot, 2023[3]).
NEET rates vary considerably across OECD and partner countries, ranging from 48% of 18-24 year-olds in South Africa (about 22% unemployed and 25% outside the labour force) to as low as less than 5% in Iceland (about 1% unemployed and 3% outside the labour force). Countries vary in the proportions of those who are actively looking for employment and those who are outside the labour force. For example, in Türkiye (where 8% of 18-24 year-olds are unemployed and 24% are outside the labour force) and Mexico (3% unemployed and 16% outside the labour force, relatively large shares of youth not participating in the labour market may reflect country differences in education enrolment, family responsibilities, or cultural factors that may affect youth engagement. In contrast, there are many countries where the split is more balanced – for instance Greece and Spain, where in both cases around 9% are unemployed and 8% are outside the labour force – indicating that the youths not in education or training are more likely to be looking for jobs, even if they have not yet succeeded (Figure A2.1).
In per cent
1. Year of reference differs from 2019.
2. Year of reference differs from 2024.
3. Break in series.
For data, see Table A2.2. For a link to download the data, see Tables and Notes section.
In 2024, after several years of recovery after the COVID-19 pandemic, the average NEET rate across OECD countries was 14%, similar to the value recorded in 2019. Italy saw the most significant drop, with an 8 percentage-point decrease, followed closely by Brazil and Chile. These decreases in NEET rates might indicate that mechanisms to support youth transitions into work, education or training, such as Italy’s NEET Working Plan which was adopted in 2022, have been effective in improving individual pathways into employment or education for youth (Gaspani, Recchi and Rio, 2025[4]). Meanwhile, Lithuania experienced the largest increase (7 percentage points), followed by Estonia, Israel and Romania. These increases may point to emerging challenges such as structural shifts in the labour market, economic transitions, or areas where education and training systems are lagging behind new job market demands. Youth who become NEET repeatedly or for sustained periods face significantly greater long-term consequences than those whose NEET episodes are brief (Kleif, 2020[5]). About one-third of OECD countries saw practically no change, reflecting a return to similar levels of disengagement to those seen in 2019 (Figure A2.2).
However, stable averages at the OECD level can mask significant national shifts. For example, in Estonia, employment ratios fell by about 10 percentage points for men (from 41% in 2019 to 29% in 2024) while increasing by about 10 percentage points for women over the same period (from 28% to 38%). In Norway, the share of 18–24 year-olds in employment declined by about 13 percentage points (from 40% in 2019 to 27% in 2024), while the share in education rose by about 15 percentage points (from 51% to 67%). These examples reflect how underlying gender and country-specific trends can diverge substantially from aggregate figures (Table A2.2).
Youth and duration of unemployment
Youth unemployment, particularly among those aged 18 to 24, remains a significant concern as this age group is in a critical transition phase. Schmillen and Umkehrer (2017[6]) find that each additional day unemployed in the first 8 years on the job market leads to an extra half‑day of unemployment over the next 16 years – clear evidence of persistent scarring, especially for those with repeated or lengthy spells. Prolonged unemployment, particularly in the absence of continued education or training, can limit young people’s prospects for securing employment aligned with their skills and qualifications, while also undermining their long-term earning potential, well-being and motivation (Rahmani and Groot, 2023[3]).
In response to employment challenges, some young people opt to continue their education, specialising or developing skills that are in greater demand. Career guidance can be an effective intervention to support these decisions yet those groups that are already excluded from the labour market are less likely to seek or use these services, highlighting the need for more targeted outreach and support (OECD, 2021[7]).
Across OECD countries with available data, 1% of 18‑24 year‑olds are long-term unemployed (for 12 months or more) and 4% are in short-term unemployment (less than 12 months). The majority of young people who are unemployed across OECD countries have been so for the short term, ranging from 12% of 18-24 year-olds in Greece and 11% in Colombia to under 2% in Czechia, Israel, the Netherlands and Norway. Prolonged spells are most prevalent in Greece, Italy and the Slovak Republic, where rates exceed 3%. In contrast, less than 0.5% of youth in Canada, Costa Rica, Denmark, Estonia, Lithuania, Mexico, Norway and Poland are experiencing long‑term unemployment (Figure A2.3).
In per cent
1. Year of reference differs from 2024.
For data, see Table A2.3.. For a link to download the data, see Tables and Notes section.
Individuals who experience long-term unemployment are more likely to be perceived as less skilled, or productive than their counterparts experiencing short-term spells of unemployment, making the duration of unemployment a crucial indicator of young people’s labour market‑ engagement. Moreover, prolonged joblessness takes a serious psychological toll, raising the risk of inpatient mental health treatment, so that long-term youth unemployment becomes an indicator of distress both in economic and in health terms (Thern et al., 2017[8]). Employers may view youth who have been briefly unemployed more favourably – valuing their immediate availability – an advantage which vanishes for those experiencing extended joblessness, once again underscoring the powerful effect of longer spells of unemployment (Wachter, 2020[9]).
Gender differences are also pronounced in education and employment patterns. Across OECD countries, women aged 18–24 are over 6 percentage points more likely than men to be enrolled in education (56% versus 49%), while men are about 8 percentage points more likely to be employed (35% versus 28%). These persistent gender gaps suggest different trajectories through education and into the labour market (Table A2.2. ).
Educational and labour-market status of 18-29 year-olds
Comparing the enrolment and employment patterns of 25-29 year-olds alongside 18-24 year-olds yields further insights into labour-market transitions. Many of those in the younger age group will still be studying or just entering the labour market for the first time. Those pursuing tertiary education may still be completing a bachelor's or master's degree at the age of 24, while others are starting their professional careers. A smaller share may be engaged in doctoral studies or equivalent qualifications. In contrast, a large majority of 25-29 year-olds will have completed their initial education in most OECD countries and many will have acquired substantial labour-market experience. Among those who are in education, some might be finishing their tertiary studies, while others might have re-entered education to obtain further qualifications (see Chapter B4).
In per cent
1. Year of reference differs from 2024.
For data, see Table A2.1. For a link to download the data, see Tables and Notes section.
Some young adults combine education with employment, particularly in tertiary education, where part-time work can help cover tuition fees, accommodation and living expenses, or contribute to career development. Across OECD countries, almost one-fifth of 18-24 year-olds (19%) are combining education and employment, compared with 10% of 25-29 year-olds. The gap is widest in the Netherlands, where the education system includes many apprenticeships and a large number of students take on small, non-study-related side jobs; here over half of 18-24 year-olds (51%) are both working and studying, compared to less than one-fifth‑ of their older peers (18%). Costa Rica, Israel, Italy and Portugal are exceptions to this pattern, where the older cohort are slightly more likely to be both working and learning, reflecting the spread of part-time master’s and up-skilling programmes. Meanwhile, in Colombia, Czechia, Greece, Hungary, Italy, Portugal, Romania, the Slovak Republic and South Africa, less than 10% of either cohort combine education and employment (Figure A2.4). These differences underscore institutional and cultural contrasts in tuition regimes, labour regulations, campus job opportunities and even employers’ perspectives on hiring students. Differences between younger and older cohorts can also reflect financial necessity or even the structure of higher education programmes. For instance, high rates of study and work among 25-29 year-olds in Finland may be driven by the expansion of apprenticeship and training models and stronger support for working learners (Eurydice, 2025[10]).
Large shares of young people combining work and study can benefit the labour market as they can increase or reduce their hours on demand to cover peaks or emergencies in various sectors. Research suggests that exploiting student populations for work ultimately creates a complementary labour force that drives the development of local economies (Whittard, Drew and Ritchie, 2022[11]).For learners themselves, combining work with their studies offers valuable practical experiences that may help with transitions into full-time employment, as well as helping them build professional networks, resulting in positive labour-market outcomes especially when engaging in work related to their field of study (Geel and Backes‐Gellner, 2012[12]). In some countries like Germany, Austria and Switzerland, where dual study systems that blend academics with apprenticeships are widespread, combining education with employment may even be part of the regular qualification process. Despite these benefits, work-study arrangements may limit the time students have for academic work, potentially affecting their learning outcomes or well-being.
Subnational variation in NEET rates
Within OECD countries, the share of 18-24 year olds who are neither in employment nor in education or training (NEET) can vary dramatically from one region to another. Subnational variation in the proportion of NEETs presents 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 grid (OECD, 2024[13]).
The most pronounced regional disparities in NEET rates emerge in Canada, Italy, Mexico and Türkiye where the gaps between the best- and worst-performing regions exceed 20 percentage points. In Canada, British Columbia reports a NEET rate of 9%, while Nunavut records 41% (a 32 percentage-point difference), signalling the need for region-specific labour-market strategies and social support in remote communities. Türkiye’s gap (19% in Istanbul versus 48% percent in Eastern Anatolia – East) highlights regional disparities that may be influenced by differences in population density, infrastructure, access to employment opportunities, and access to education and training. (Table A2.4, available on line).
Conversely, Costa Rica, Ireland and Japan exhibit limited regional variation, with gaps of less than 5 percentage points between the best- and worst-performing regions. Ireland’s NEET rates range from 8% (Northern and Western) to about 10% (Eastern and Midland), suggesting broadly uniform labour-market outcomes, while Japan ranges from 2% (Hokuriku) to about 5% (Chugoku) highlighting its generally low NEET incidence. In Costa Rica, the difference between Central (24%) and Huetar Caribbean (28%) also indicates modest disparities. Although countries with larger land areas or populations often exhibit wider subnational differences – as in Türkiye and Canada – size alone does not account for all the variation. Japan is large both geographically and demographically but has one of the smallest regional differences, whereas Greece – considerably smaller by both measures – faces a 19 percentage point divide. This contrast suggests that economic structures, education systems and social policies are more influential in driving NEET differences than country size. Targeted policies for specific regions are therefore essential to narrowing these gaps and ensuring that all young people have access to education and employment opportunities (Table A2.4, available on line).
Educational attainment refers to the highest level of education successfully completed by an individual.
Employed, outside the labour force/inactive and unemployed individuals: See Definitions section in Chapter A3.
Individuals in education are those who are receiving formal education and/or training.
Levels of education: See the Reader’s Guide at the beginning of this publication for a presentation of all ISCED 2011 levels.
NEET refers to young people neither employed nor in formal education or training.
Data from the national labour force surveys usually refer to the second quarter of studies in a school year, as this is the most relevant period for knowing if the young person is really studying or has left education for the labour force. This second quarter corresponds in most countries to the first three months of the calendar year (i.e. January, February and March), but in some countries to the second three months (i.e. April, May and June).
Education or training corresponds to formal education or training; therefore, someone not working but following non-formal studies is considered NEET. However, the definition of NEET is different for subnational data collection for countries taking part in the EU-LFS, where young adults who are in non-formal education or training are not considered to be NEET. For OECD EU countries, NEET rates by subnational region are therefore not comparable to the rates at national level presented in this chapter.
For further details, refer to the OECD Handbook for Internationally Comparative Education Statistics (OECD, 2018[14]) and the Education at a Glance 2025 Sources, Methodologies and Technical Notes (https://doi.org/10.1787/fcfaf2d1-en).
For information on the sources, see Chapter A1.
Data on subnational NEET rates is from the OECD Regions and Cities databases http://oe.cd/geostats. Data on subnational NEET rates for Australia is from the Australian Bureau of statistics.
References
[10] Eurydice (2025), Finland - National reforms in vocational education and training, Eurydice, https://eurydice.eacea.ec.europa.eu/eurypedia/finland/national-reforms-vocational-education-and-training.
[4] Gaspani, F., S. Recchi and A. Rio (2025), “Young people NEET in Italy: Exploring the phenomenon and evolving policies”, in Diversity and Inclusion Research, Diversity and Inclusion in Italy, Springer Nature Switzerland, Cham, https://doi.org/10.1007/978-3-031-81938-4_29.
[12] Geel, R. and U. Backes‐Gellner (2012), “Earning while learning: When and how student employment is beneficial”, LABOUR, Vol. 26/3, pp. 313-340, https://doi.org/10.1111/j.1467-9914.2012.00548.x.
[5] Kleif, H. (2020), “The temporality of being NEET: A longitudinal study of NEET occurrences among young adults in Denmark”, YOUNG, Vol. 29/3, pp. 217-235, https://doi.org/10.1177/1103308820945098.
[2] Marques, P. and I. Salavisa (2017), “Young people and dualization in Europe: A fuzzy set analysis”, Socio-Economic Review, Vol. 15/1, pp. 135-160, https://doi.org/10.1093/ser/mww038.
[13] OECD (2024), OECD Territorial grids, https://www.bing.com/ck/a?!&&p=8fabc122880b662c83d4a17136ff8a47429fd40f0362e666a8f11e959c4206d6JmltdHM9MTc0ODkwODgwMA&ptn=3&ver=2&hsh=4&fclid=28f17106-214d-64ec-2f17-640220f965e6&psq=oecd+official+territorial+classification&u=a1aHR0cHM6Ly9zdGF0cy5vZWNkLm9.
[7] OECD (2021), Career Guidance for Adults in a Changing World of Work, Getting Skills Right, OECD Publishing, Paris, https://doi.org/10.1787/9a94bfad-en.
[14] OECD (2018), OECD Handbook for Internationally Comparative Education Statistics: Concepts, Standards, Definitions and Classifications, OECD Publishing, Paris, https://doi.org/10.1787/9789264304444-en.
[1] Pohlan, L. (2024), “Unemployment’s long shadow: The persistent impact on social exclusion”, Journal for Labour Market Research, Vol. 58/1, https://doi.org/10.1186/s12651-024-00369-8.
[3] Rahmani, H. and W. Groot (2023), “Risk factors of being a youth not in education, employment or training (NEET): A scoping review”, International Journal of Educational Research, Vol. 120, https://doi.org/10.1016/j.ijer.2023.102198.
[6] Schmillen, A. and M. Umkehrer (2017), “The scars of youth: Effects of early‐career unemployment on future unemployment experience”, International Labour Review, Vol. 156/3-4, pp. 465-494, https://doi.org/10.1111/ilr.12079.
[8] Thern, E. et al. (2017), “Long-term effects of youth unemployment on mental health: Does an economic crisis make a difference?”, Journal of Epidemiology and Community Health, Vol. 71/4, https://doi.org/10.1136/jech-2016-208012.
[9] Wachter, T. (2020), “The persistent effects of initial labor market conditions for young adults and their sources”, Journal of Economic Perspectives, Vol. 34/4, pp. 168-194, https://doi.org/10.1257/jep.34.4.168.
[11] Whittard, D., H. Drew and F. Ritchie (2022), “Not just arms and legs: Employer perspectives on student workers”, Journal of Education and Work, Vol. 35/6-7, pp. 751-765, https://doi.org/10.1080/13639080.2022.2126972.
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 A2.1. Share of young adults in education/not in education, by age group and labour-force status (2024)
Note: NEET refers to young people neither employed nor in education or training. Data usually refer to the second quarter of studies, which corresponds in most countries to the first three months of the calendar year, but in some countries, to the second three months. Columns with data for 25-29 year-olds are available for consultation on line.
1. Year of reference differs from 2024: 2022 for Chile; 2023 for Brazil, Iceland and the United States.
Table A2.2. Trends in the share of 18-24 year-olds in education/not in education, by work status and gender (2019 and 2024)
Note: NEET refers to young people who are neither employed nor in formal education or training. Data usually refer to the second quarter of studies, which corresponds in most countries to the first three months of the calendar year, but in some countries, to the second three months. Columns with data for the categories Total are available for consultation on line.
1. Year of reference differs from 2019: 2018 for Argentina; 2020 for Chile; 2022 for Bulgaria and Peru.
Year of reference differs from 2024: 2022 for Chile; 2023 for Brazil, Iceland and the United States.
Table A2.3. Share of young adults in education/not in education, by age group, labour-force status and duration of unemployment (2024)
Note: The figures on duration of unemployment may not add up to the total for all unemployed because of missing data. Columns with data for 18-24 year-olds, and for duration of unemployment of less than 12 months are available for consultation on line.
1. Year of reference for duration of unemployment differs from 2024: 2021 for Brazil, Chile, Colombia, Iceland and the United States.
2. Year of reference for all other data differs from 2024: 2022 for Chile; 2023 for Brazil, Iceland and the United States.
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)
In per cent; 18-24 year-olds
Note: For notes on this table and a link to download the data, see Tables and Notes section above.
In per cent
Note: For notes on this table and a link to download the data, see Tables and Notes section above.
In per cent; 25-29 year-olds
Note: For notes on this table and a link to download the data, see Tables and Notes section above.