Most young adults are in education, with many also gaining work experience besides their studies. Across OECD countries, a significant proportion (53%) of 18-24 year-olds remain in education. On average, 18% of this age group are combining education with employment.
For young people, being neither in employment nor in education or training (NEET) often stems from a combination of structural labour-market challenges, skills mismatches and personal or social factors, and the consequences of prolonged NEET status can be severe. In 2025, the OECD average share of youths who are NEET reached 14% among 18-24 year-olds and 16% among 25-29 year-olds.
In the last decade, the share of 18-24 year-old NEETs has fallen on average by 2 percentage points to 14% in 2025, but cross-country comparisons reveal a wide range of trends, from large falls in Croatia, Iceland and Ireland to increases in Germany, Latvia and South Africa.
Chapter A2. Transition from education to work: Where are today’s youth?
Copy link to Chapter A2. Transition from education to work: Where are today’s youth?Highlights
Copy link to HighlightsContext
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 on in education to enhance their employability but if their skills are not in demand, they may still 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. 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, provide career guidance and offer 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.
Figure A2.1. Distribution of 18-24 year-olds by education participation and labour-force status (2025)
Copy link to Figure A2.1. Distribution of 18-24 year-olds by education participation and labour-force status (2025)In per cent
1. Year of reference differs from 2025.
For data, see Table A2.1. The data for this figure can be accessed via https://stat.link/t764xw.
Other findings
NEET rates differ by gender only slightly on average. A greater share of 18-24 year-old women are NEET than men in about half of OECD and partner countries.
Most countries saw similar trends for young men and women, with the average NEET rate among 18-24 year-olds dropping between 2015 and 2025 by 2 percentage points to 13% for men and 4 percentage points to 15% for women. However, this is not the case in all countries: in a number of countries values increased for men and decreased for women (e.g. in Estonia where the value for men increased 2 percentage points and the one for women decreased by 8 percentage points), while the opposite was true in Finland (i.e. the value for men decreased by 3 percentage points and the one for women increased by 1 percentage point).
Among 18-29 year-olds, the average NEET rate for individuals with low literacy proficiency levels (Level 2 or below) in the OECD Survey of Adult Skills stands at 17%. This risk significantly diminishes as skill levels rise; those with moderate to high literacy proficiency levels (Level 3 or above) have an average NEET rate of 9%.
The most pronounced regional disparities in NEET rates emerge in Canada, Italy, Mexico and the Republic of Türkiye where the gaps between the regions with the highest and lowest NEET rates reach or exceed 20 percentage points.
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.
Analysis
Copy link to AnalysisEducational and labour-market status
The transition from education to employment is a complex process influenced by factors such as educational attainment, economic conditions, and labour-market demand. Most 18-24 year-olds are in a period of transition coinciding with the final years of upper secondary education, enrolment in tertiary education or initial entry into the labour market, which is critical for shaping future career trajectories. Remaining in education enhances young people’s employability, although the success of this transition depends heavily on whether the skills they acquire are aligned with those needed in the labour market (Geel and Backes‐Gellner, 2012[2]). Combining work and study is increasingly common and offers valuable practical experience, helping students build professional networks and facilitating a smoother entry into full-time employment. Young people who are neither in employment nor in education or training (NEET) face significant risks, as prolonged periods of inactivity or unemployment can lead to persistent social exclusion and a loss of essential soft skills.
Across OECD countries, a significant proportion (53%) of 18-24 year-olds remain in education as they pursue various qualifications (Figure A2.1). On average, approximately one-third of these (18% of the entire age group) are combining education with employment, particularly those in tertiary education, where part-time work can help cover tuition fees, accommodation and living expenses, or contribute to career development. The distribution of these categories varies dramatically by country. In the Netherlands, almost half of 18-24 year-olds (49%) are both working and studying, whereas this figure is 5% or less in Hungary and Italy and, among OECD partner countries, Croatia, Romania and South Africa (Table A2.1).
Considering those no longer studying, 33% of 18-24 year-olds are employed and not in education, with the highest rates observed in Israel and New Zealand (over 45%). The rest are NEET: on average, 5% of people of this age across the OECD are not studying and unemployed (i.e. actively seeking work) while 9% are not studying and outside the labour force (inactive). South Africa has the highest overall share of unemployed (22%) and inactive (26%) NEET youths while at the other end of the spectrum, Iceland reports only 1% unemployed and 3% inactive NEET youths in this age group. In countries like Colombia, Israel, Mexico and Türkiye there are relatively high shares of inactive (17% and over) NEET youth compared to those who are unemployed, while in Portugal, Spain and Sweden there are slightly more unemployed NEET youth than inactive ones (Figure A2.1).
Among 25-29 year-olds, there is a clear shift toward the labour market as the majority of this age group 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 initial tertiary studies, while others might have re-entered education to obtain further qualifications (see Chapter B4). A substantial majority of 25-29 year-olds are employed and not in education (68%). The share in education falls to 15% on average across OECD countries, but a larger proportion of these (approximately two-thirds) are combining education and work than among the younger cohort. In Israel, Italy and Portugal, 25-29 year-olds are slightly more likely than their younger peers to be both working and learning, often due to part-time master’s and up-skilling programmes (Table A2.1). In Finland, high rates of study and work among this older group are driven by the expansion of apprenticeship and training models (Eurydice, 2025[3]).
On average, in 2025 the overall NEET rate across OECD countries was 14% among 18-24 year-olds, ranging from 5% in Iceland to 31% in Türkiye, and reaching 48% in partner country South Africa. Among 25-29 year-olds, the NEET rate increases to 16% on average and ranges from 9% in the Netherlands and Norway to 33% in Türkiye and 55% in South Africa. The older age group (25-29 year-olds) has a higher NEET rate in the majority of OECD and partner countries: Czechia and Greece are the countries with the largest increase between the younger and older cohorts, while the opposite trend is observed in other countries like Colombia and Costa Rica (Figure A2.2).
Figure A2.2. Share of NEETs among 18-29 year-olds, by age group (2025)
Copy link to Figure A2.2. Share of NEETs among 18-29 year-olds, by age group (2025)In per cent
1. Year of reference differs from 2025.
For data, see Table A2.1. The data for this figure can be accessed via https://stat.link/t764xw.
The share of both unemployed and inactive NEET 25-29 year-olds are only slightly higher than among the younger cohort on average. However, Greece and South Africa have a much higher share of unemployed NEETs among the older age group, while Czechia, Italy and Latvia have higher shares of inactive NEETs (Table A2.1).
NEET rates and trends
The status of being NEET often stems from a combination of structural labour-market challenges, skills mismatches and personal or social factors (Rahmani and Groot, 2023[4]). Structural barriers, such as dual labour markets that offer stable positions to some while relegating others to precarious, low-wage work, can exacerbate the risk of young people falling out of both work and education (Marques and Salavisa, 2017[5]). Personal challenges such as long-term health issues, addiction or weak support networks can also play a significant role. The consequences of prolonged NEET status are severe, leading to a loss of opportunities to gain work experience and develop essential soft skills, which may result in persistent labour-market and social exclusion. Furthermore, long-term unemployment can cause significant psychological effects, including increased anxiety, depression and discouragement, further reducing the motivation to seek employment.
Over the last decade, the share of young people who are NEET increased during the COVID-19 pandemic to reach levels slightly lower than those recorded in 2015 (OECD, 2025[6]). Although the OECD average share of 18-24 year-old NEETs fell in the last decade by 2 percentage points to 14% in 2025, cross-country comparisons reveal a range of trends. Almost all countries saw a decline in NEET rates with the sharpest drops observed in Croatia, Ireland and Italy (by 10 percentage points or more). Germany, Israel, Latvia and South Africa are the countries where the NEET rate increased the most between 2015 and 2025 (by 2 percentage points or more, see Table A2.2).
Figure A2.3. Trends in the share of NEETs among 18-24 year-olds (2015 and 2025)
Copy link to Figure A2.3. Trends in the share of NEETs among 18-24 year-olds (2015 and 2025)In per cent
1. Year of reference differs from 2015.
2. Year of reference differs from 2025.
For data, see Table A2.2. The data for this figure can be accessed via https://stat.link/t764xw.
NEET rates diverge by gender, with the rates for young women only slightly higher on average. Across OECD and partner countries, a larger share of 18-24 year-old women are neither in employment nor in education or training than their male peers in about half the countries, with the differences reaching 17 percentage points in Colombia and 19 in Mexico. In the remaining countries, young men have higher NEET rates than women (Table A2.2), with the largest differences (4-5 percentage points) observed in Belgium, Estonia and France (Table A2.2).
In most countries, the trends were similar for young men and women between 2015 and 2025, with the average rate among 18-24 year-olds falling by 2 percentages point for men (13% in 2025) and 4 percentage points for women (15% in 2025). However, this is not the case for all the countries: in a number of countries the rate increased for men and decreased for women (e.g. in Estonia where the rate for men increased by 2 percentage points and the one for women decreased by 8 percentage points). The opposite trend was observed in Finland, with a 3 percentage-point fall for men and a 1 percentage-point rise for women. In Croatia, the rate fell for both genders but by 13 percentage points for men compared to 8 percentage points for women, closing the gender gap in NEET rates over this period (Table A2.2).
Despite these overall improvements, NEET rates remain persistently high, reinforcing the importance of comprehensive and well‑coordinated support systems for young people. Although some countries have succeeded in reducing NEET levels, others continue to struggle, highlighting that policy effectiveness varies widely and that no single approach works universally. Box A2.1 lists some of the policies implemented by across OECD countries to support those at risk of becoming NEET.
Box A2.1. Supporting NEET youth: Integrated approaches to re-engagement
Copy link to Box A2.1. Supporting NEET youth: Integrated approaches to re-engagementNEET” is a broad and heterogeneous category requiring context-specific responses. Effective NEET reduction requires integrated, multi-agency strategies that combine early intervention with personalised, holistic support. Successful systems do not rely on a single model but instead combine accessible services, tailored learning pathways, co-ordinated governance and targeted labour-market interventions to support successful transitions from school to work.
However, these policy interventions can only be effective when embedded in favourable macro-economic conditions. Strategies therefore need to reflect national circumstances, whether focusing on prevention among specific at-risk groups in countries with relatively low NEET rates or on large-scale re-engagement and activation efforts where structural challenges remain more pronounced.
Finland demonstrates the value of combining a youth guarantee with accessible one-stop guidance services, while Norway and Ireland highlight the role of personalised and second-chance learning pathways in re-engaging young people. The Netherlands shows how data-driven governance combined with a youth-centred strategy can support early identification and targeted interventions, whereas Italy combines labour-market activation with measures to prevent early school leaving. Slovenia’s PUM-O Plus illustrates the effectiveness of flexible, non-formal learning environments that promote confidence-building and gradual re-engagement.
Many countries also operate systems to identify and monitor young people who are at risk of disengaging from education or training before they become NEET. These include municipal tracking and outreach mechanisms, such as Sweden's Municipal Activity Responsibility (KAA), which require local authorities to maintain contact with young people who are no longer enrolled in education and offer support to help them re-engage. While such preventative systems play an important role in reducing future NEET rates, they are not the primary focus of the country examples presented below.
Policy interventions targeting youth in selected OECD countries
Finland: Ohjaamo One-Stop Guidance Centres
Ohjaamo centres provide free, low threshold support for all young people under 30, helping them navigate the increasingly complex transition from school to work. Developed in the context of Finland’s Youth Guarantee (Nuorisotakuu) and aligned with the objectives of the EU Youth Guarantee, they bring together employment, education, social and health services in a single, easily accessible entry point. The network has expanded (to around 70 centres nationwide by 2022), providing co-ordinated and personalised support to young people facing a wide range of educational, employment and social challenges.
Ohjaamo operates as a multi-agency service model that brings together employment services, social services, health professionals and local partners in one physical location, reducing administrative barriers and making it easier for young people to access support. Services vary by municipality, but typically include guidance on education and training, job-search support, income assistance, housing, and access to mental or physical healthcare. Young people can visit without an appointment, which is central to the “low threshold” approach aimed at reaching those who might otherwise avoid public services. The model emphasises face-to-face support, flexible service delivery, and adapting assistance to each young person’s pace and preferences (Ohjaamo, n.d.[7]).
Ireland: Youthreach and Integrated Youth Activation Services
Ireland supports young people who are NEET through a combination of second chance education programmes and integrated employment services. A central element of this approach is Youthreach, Ireland’s national programme for early school leavers aged 15-20 who have left mainstream education without qualifications. Youthreach aims to help young people develop the skills, confidence and qualifications needed to progress to further education, training, apprenticeships or employment.
Participation is voluntary and free of charge. The programme combines basic education, vocational training and personal development in a supportive learning environment designed for young people who may have struggled in traditional school settings. The flexible and learner-centred approach is intended to rebuild confidence, strengthen engagement and support successful transitions into education or work.
Youthreach operates alongside Ireland’s broader youth activation framework, which includes the EU Youth Guarantee and the Intreo public employment service. Young people who are unemployed can access personalised guidance, career counselling, training opportunities, apprenticeships and job-search support through Intreo offices. This integrated approach seeks to ensure that young people who disengage from education or employment can access appropriate support pathways and avoid long-term exclusion from the labour market (Government of Ireland, 2022[8]; Government of Ireland, 2025[9]).
Italy: Integrated pathways to support young people’s transition into education and work
Italy supports young people who are NEET through a range of policy initiatives, including Garanzia Giovani, the national implementation of the EU Youth Guarantee, the Programme Garanzia di Occupabilità dei Lavoratori (GOL), and the 2021-27 Programme Giovani, Donne e Lavoro (ANPAL, n.d.[10]; Government of Italy, n.d.[11]; Government of Italy, n.d.[12]). Together, these initiatives aim to facilitate young people’s transition into employment by providing personalised support, skills development opportunities and access to training, apprenticeships, internships and employment pathways.
A central feature of the Italian approach is its focus on reaching and engaging young people who are furthest from the labour market to prevent long-term disengagement. Young people entering these programmes typically follow an integrated pathway that begins with personalised guidance and skills assessment and leads to tailored combinations of training, mentoring, job-search assistance, work-based learning or employment opportunities. Regional authorities play a key role in delivering and adapting these services to the local labour market. The measures implemented include outreach activities targeting disadvantaged youth, specialised guidance and mentoring, training, apprenticeships, traineeships, opportunities for civic service, support for self-employment, and incentives for recruitment.
Italy also seeks to prevent young people becoming NEET through education policies aimed at reducing early school leaving. The Agenda Sud initiative, launched in 2023, supports primary and secondary schools in Southern Italy through targeted interventions designed to improve educational outcomes and address regional disparities (Government of Italy, n.d.[13]). By encouraging more young people to remain in education and attain upper secondary qualifications, the initiative contributes to improving employability and reducing the risk of becoming NEET.
Netherlands: From School to Sustainable Work Act
The Netherlands introduced the From School to Sustainable Work Act in January 2026, a national framework aimed at reducing the number of young people aged 16-27 who are NEET. The law strengthens the transition from school to work by improving early identification of young people at risk and by enhancing co-operation between education providers, municipalities, employers and youth services. Young people under the age of 16 remain covered by compulsory education legislation and are therefore expected to be in school, while the extension of support up to the age of 27 provides greater scope to assist young adults facing difficulties in their transition to employment or further education.
The Dutch approach is unique because it combines a youth-centred and data-driven strategy at regional level. Rather than applying a one-size-fits-all approach, interventions are tailored to the specific challenges, opportunities and labour market realities within each region, while always keeping the needs, talents and personal circumstances of young people at the centre. A key element of the Dutch approach is the national data infrastructure facilitated by the Ministry of Education, Culture and Science and the Education Executive Agency (DUO), using data provided by Statistics Netherlands (CBS). Data on vulnerable groups and regional trends are collected and shared with municipalities and schools, enabling them to design targeted, evidence-based interventions that respond to the actual needs of young people in their region. Across all measures, the talents, ambitions and personal circumstances of young people remain central, ensuring that support is tailored to what each individual needs to successfully complete education and build a sustainable future in work or society. The impact of these new measures will be evaluated in 2028, when the law will be reviewed (Overheid.nl, 2025[14]; Landelijk Ondersteuningsteam, n.d.[15]).
Norway: UngInvest AIB (Arbeidsinstituttet Buskerud)
UngInvest AIB is a strengths-based, practice-oriented training programme for young people aged 16-24 who are in need of an alternative path through upper secondary education. Its purpose is to help young people rebuild motivation, strengthen core skills and transition into school, apprenticeships or work. Admission is continuous throughout the year, and participants can join within two days, ensuring rapid access to support.
UngInvest supports young people who are uncertain about their educational path or who need to reinforce basic subjects such as Norwegian, mathematics and English before moving forward. The programme focuses on building trusting relationships and tailoring learning to each young person’s needs, while all teaching remains aligned with the national upper secondary curriculum. The programme aims to increase participants’ engagement by helping them stay in education or enter employment through supported or sheltered employment, labour-training courses, childcare, military service or health-related treatment programmes. UngInvest collaborates closely with schools, vocational training boards, employers and key support services such as the public employment service (the Norwegian Labour and Welfare Administration, NAV), psychological counselling and other follow-up services. This co-ordinated, multi-agency approach helps address both educational and personal barriers to progress (UngInvest, n.d.[16]).
Slovenia: Project Learning for Young Adults (PUM‑O)
PUM‑O Plus is Slovenia’s easily accessible support programme for young people aged 15-29 who have left school early or are at risk of doing so. Participation is voluntary and free of charge, and young people can join either through their employment office counsellor or directly via a local PUM‑O Plus provider. The model is designed to remove administrative barriers and provide a welcoming, youth‑friendly environment where participants can stabilise their daily routine, explore interests and receive personalised support.
Services combine creative, social and educational activities with individual mentoring. Young people work in small groups and engage in project‑based learning that helps them discover new skills, strengthen their confidence and reflect on their future plans. Activities range from practical workshops and community projects to discussions, sports, cooking and artistic expression. Mentors provide continuous one‑to‑one guidance, helping participants set goals, address personal or social challenges and prepare for a return to school or entry into employment.
PUM‑O Plus places strong emphasis on personal development and empowerment. The programme supports young people in deciding on their educational or career pathways, developing key competencies and building the motivation needed to re‑engage with formal systems. It also serves as a bridge to other employment or training programmes offered through the public employment service. Upon completion, participants receive a certificate documenting the skills, achievements and progress they made during their time in the programme (Government of Slovenia, n.d.[17]).
NEET rates by literacy skill levels
Cognitive skills are a defining factor in a young person's transition to adulthood, with literacy proficiency serving as a key predictor of their risk of becoming NEET. Individuals with lower skill levels often face significant hurdles, as their qualifications may not align with the specific demands of a modern workforce, leading to persistent difficulties in finding employment. Data from across the OECD confirm that the risk of becoming NEET are inversely related to literacy proficiency levels. Among 18-29 year-olds, the average NEET rate for individuals with literacy proficiency levels of Level 2 and below in the Survey of Adult Skills (PIAAC) stands at 17%. This risk significantly diminishes as skill levels rise; those with literacy proficiency Level 3 and above have an average NEET rate of 9% (Figure A2.4).
NEET rates for the low performing cohort range from 10% to 28% across OECD countries and economies, while those for high performers range from 4% to 16%. The countries with the highest average literacy scores for adults (OECD, 2025[6]), are also those with the smallest gap in NEET rates between low and high performers as well as some of the lowest NEET rates overall (Table A2.3).
Figure A2.4. Share of NEETs by literacy proficiency level (2023)
Copy link to Figure A2.4. Share of NEETs by literacy proficiency level (2023)In per cent; 18-29 year-olds; Survey of Adult Skills (PIAAC)
Subnational variation in NEET rates
National averages often mask significant subnational variations, as regional disparities in labour-market conditions and access to education can create very different outcomes for youth within the same country. 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 differences in NEET rates present critical challenges for policymakers seeking to promote inclusive labour markets and equitable access to opportunities. The following analysis is of regions at the TL2 level, which are large subnational regions as defined by the OECD’s regional‐classification grid (OECD, 2024[18]).
The most pronounced regional disparities in NEET rates are seen in Canada, Italy, Mexico, Romania and Türkiye, where the gaps between the regions with the highest and lowest NEET rates reach or exceed 20 percentage points. In Canada, the NEET rate in Quebec is 10%, while in Nunavut it is 38%, a 28 percentage-point difference, signalling the need for region-specific labour-market strategies and social support in remote communities. In Türkiye, regional NEET rates range from 19% in Istanbul to 48% percent in Central East Anatolia - East (Table A2.4, available online).
Conversely, Ireland, Japan, Norway and Slovenia 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% (Southern) to 9% (Eastern and Midland), suggesting broadly uniform labour-market outcomes. In Norway, the difference between Western Norway (9%) and Agder and Sør-Østlandet (11%) also indicates modest disparities, as also is the NEET rate gap in Slovenia between Western and Eastern Slovenia (8 and 10% respectively). In Japan, the NEET rate ranges from 2% (Hokuriku) to 5% (Chugoku and Kyushu-Okinawa) highlighting the country’s generally low NEET incidence. Although countries with larger land areas or populations often exhibit wider subnational differences – as in Canada and Türkiye – 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 rates in Greece – considerably smaller by both measures – differ by 19 percentage points between the highest and lowest regions. This indicates that country size alone does not explain regional variation in NEET rates and that other contextual factors, such as economic structures, education systems and social policies, are also likely to contribute. 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 online).
Definitions
Copy link to DefinitionsEducational 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.
Proficiency levels: See Definitions in Chapter A1.
Methodology
Copy link to MethodologyData 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 a 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 Labour Force Survey (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, 2017[19])and the Education at a Glance 2026 Sources, Methodologies and Technical Notes (https://doi.org/10.1787/dcf64a14-en)
Sources
Copy link to SourcesFor information on the sources, see Chapter A1.
Data on subnational NEET rates stem 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] ANPAL (n.d.), Garanzia Giovani, Agenzia Nazionale Politiche Attive del Lavoro, https://storicoanpal.politicheattive.lavoro.gov.it/garanzia-giovani.html.
[3] Eurydice (2025), Finland - National reforms in vocational education and training, https://eurydice.eacea.ec.europa.eu/eurypedia/finland/national-reforms-vocational-education-and-training.
[2] 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.
[9] Government of Ireland (2025), Intreo - the Public Employment Services, Department of Social Protection, https://www.gov.ie/en/department-of-social-protection/organisation-information/intreo-the-public-employment-services/.
[8] Government of Ireland (2022), Youthreach, https://www.gov.ie/en/department-of-further-and-higher-education-research-innovation-and-science/services/youthreach/.
[13] Government of Italy (n.d.), Agenda Sud - Programma Nazionale 2021-2027, Ministero dell’Istruzione e del Merito, https://pn20212027.istruzione.it/avvisi/agenda-sud/.
[11] Government of Italy (n.d.), Programma GOL, Ministerio del Lavoro e delle Politiche Sociali, https://www.lavoro.gov.it/temi-e-priorita/occupazione/focus/pagine/programma-gol.
[12] Government of Italy (n.d.), Programma nazionale Giovani, donne e lavoro 2021-2027, Ministero del Lavoro e delle Politiche Sociali, https://www.lavoro.gov.it/pn-giovani-donne-lavoro/programma.
[17] Government of Slovenia (n.d.), PUM-O Plus: Projektno učenje mlajših odraslih, https://www.ess.gov.si/iskalci-zaposlitve/programi-za-zaposlovanje/predstavitev-programov/pum-o-plus-projektno-ucenje-mlajsih-odraslih/.
[15] Landelijk Ondersteuningsteam (n.d.), Wet Van school naar duurzaam werk, https://www.samenvoordeklant.nl/dossier/wet-van-school-naar-duurzaam-werk.
[5] 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.
[6] OECD (2025), Education at a Glance 2025: OECD Indicators, OECD Publishing, Paris, https://doi.org/10.1787/1c0d9c79-en.
[18] OECD (2024), OECD Territorial Grids: TL2024 Classification, ECD Centre for Entrepreneurship, SMEs, Regions and Cities, https://webfs-cfe.oecd.org/files/.Stat/region/OECD_territorial-grid_TL2024.pdf.
[19] OECD (2017), OECD Handbook for Internationally Comparative Education Statistics: Concepts, Standards, Definitions and Classifications, OECD Publishing, Paris, https://doi.org/10.1787/9789264279889-en.
[7] Ohjaamo (n.d.), If you don’t know where to start, start at Ohjaamo!, https://ohjaamot.fi/en/etusivu.
[14] Overheid.nl (2025), Wet van school naar duurzaam werk, https://wetgevingskalender.overheid.nl/Regeling/WGK013026.
[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.
[4] 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.
[16] UngInvest (n.d.), UngInvest AIB er et fylkeskommunalt, praksisnært og styrke-basert læringstilbud for unge i alderen 16-24 år, https://bfk.no/unginvest/.
Chapter A2 Tables
Copy link to Chapter A2 TablesTables and notes
Copy link to Tables and notes|
Table A2.1 |
Share of young adults in education/not in education, by age group and labour-force status (2025) |
|
Table A2.2 |
Trends in the share of 18-24 year-olds in education/not in education, by work status and gender (2015 and 2025) |
|
Table A2.3 |
Distribution of 18-29 year-olds by education and labour-force status, by literacy proficiency level (2023) |
|
Table A2.4 (web only) |
Share of young people neither employed nor in formal education or training (NEET), by subnational region (2025) |
Data Download
Copy link to Data DownloadThe data for the figures and tables in this chapter can be downloaded via https://stat.link/t764xw.
To access further data and/or other education indicators, please visit the OECD Data Explorer: http://data-explorer.oecd.org/s/4s.
Data cut-off for the print publication 17 June 2026. Please note that the Data Explorer contains the most recent data.
Control codes
Copy link to Control codesa – category not applicable; b – break in series; d – contains data from another column; m – missing data; x – contained in another column (indicated in brackets). For further control codes, see the Reader’s Guide.
For further methodological information, see Education at a Glance 2026: Sources, Methodologies and Technical Notes ([https://doi.org/10.1787/dcf64a14-en.
Table A2.1. Share of young adults in education/not in education, by age group and labour-force status (2025)
Copy link to Table A2.1. Share of young adults in education/not in education, by age group and labour-force status (2025)In per cent
|
18-24 year-olds |
|||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
|
In education |
Not in education |
||||||||||
|
Employed |
Unemployed |
Outside the labour force |
Total |
Employed |
NEET |
Total |
|||||
|
Students in work-study programmes |
Other employed |
Total |
Unemployed |
Outside the labour force |
Total |
||||||
|
(1) |
(2) |
(3) |
(4) |
(5) |
(6) |
(7) |
(8) |
(9) |
(10) |
(11) |
|
|
OECD countries |
|||||||||||
|
Australia |
5 |
30 |
34 |
2 |
12 |
49 |
40 |
4 |
7 |
10 |
51 |
|
Austria |
8 |
15 |
24 |
2 |
23 |
49 |
38 |
6 |
7 |
13 |
51 |
|
Belgium |
1 |
11 |
12 |
1 |
50 |
64 |
25 |
5 |
6 |
11 |
36 |
|
Canada |
x(3) |
x(3) |
23 |
3 |
24 |
50 |
37 |
6 |
7 |
13 |
50 |
|
Chile1 |
x(3) |
x(3) |
9 |
5 |
43 |
56 |
24 |
7 |
13 |
19 |
44 |
|
Colombia |
a |
8 |
8 |
2 |
23 |
33 |
41 |
9 |
17 |
26 |
67 |
|
Costa Rica |
a |
12 |
12 |
3 |
27 |
42 |
38 |
11 |
8 |
20 |
58 |
|
Czechia |
1 |
6 |
7 |
0 |
55 |
63 |
29 |
3 |
4 |
7 |
37 |
|
Denmark |
x(3) |
x(3) |
32b |
5b |
14b |
52b |
35b |
5b |
8b |
13b |
48b |
|
Estonia |
0 |
18 |
18 |
5 |
35 |
58 |
32 |
9 |
5 |
11 |
42 |
|
Finland |
x(3) |
x(3) |
25 |
7 |
28 |
61 |
24 |
7 |
9 |
16 |
39 |
|
France |
11 |
8 |
19 |
2 |
33 |
54 |
28 |
9 |
9 |
18 |
46 |
|
Germany |
15 |
19 |
34 |
1 |
23 |
59 |
31 |
3 |
7 |
11 |
41 |
|
Greece |
a |
6 |
6 |
0 |
52 |
59 |
23 |
8 |
11 |
19 |
41 |
|
Hungary |
a |
5 |
5 |
0 |
49 |
54 |
32 |
5 |
8 |
14 |
46 |
|
Iceland1 |
a |
36 |
36 |
4 |
14 |
53 |
42 |
1 |
3 |
5 |
47 |
|
Ireland |
a |
32 |
32 |
2 |
28 |
64 |
29 |
3 |
6 |
9 |
38 |
|
Israel |
x(3) |
x(3) |
10 |
0 |
20 |
30 |
51 |
2 |
17 |
20 |
70 |
|
Italy |
m |
3 |
3 |
1 |
57 |
61 |
23 |
6 |
10 |
16 |
39 |
|
Japan |
m |
m |
m |
m |
m |
m |
m |
m |
m |
m |
m |
|
Korea |
m |
m |
m |
m |
m |
m |
m |
m |
m |
m |
m |
|
Latvia |
a |
13 |
13 |
1 |
42 |
56 |
29 |
7 |
7 |
14 |
44 |
|
Lithuania |
a |
9 |
10 |
1 |
44 |
54 |
32 |
5 |
8 |
13 |
46 |
|
Luxembourg |
a |
c |
c |
c |
46 |
59 |
30 |
c |
c |
c |
41 |
|
Mexico |
a |
10 |
10 |
0 |
29 |
39 |
42 |
3 |
17 |
19 |
61 |
|
Netherlands |
x(3) |
x(3) |
49 |
4 |
11 |
64 |
30 |
2 |
4 |
6 |
36 |
|
New Zealand |
a |
21 |
21 |
3 |
14 |
37 |
48 |
7 |
8 |
15 |
63 |
|
Norway |
5 |
32 |
38 |
4 |
23 |
64 |
29 |
2 |
4 |
7 |
36 |
|
Poland |
a |
11 |
11 |
1 |
46 |
58 |
28 |
5 |
9 |
14 |
42 |
|
Portugal |
a |
6 |
6 |
2 |
46 |
53 |
32 |
9 |
6 |
15 |
47 |
|
Slovak Republic |
c |
6 |
6 |
c |
57 |
64 |
25 |
5 |
6 |
11 |
36 |
|
Slovenia |
4 |
11 |
15 |
2 |
49 |
65 |
25 |
3 |
7 |
10 |
35 |
|
Spain |
x(3) |
x(3) |
10 |
3 |
47 |
61 |
22 |
9 |
8 |
17 |
39 |
|
Sweden |
m |
18 |
18 |
8 |
30 |
56 |
35 |
6 |
3 |
9 |
44 |
|
Switzerland |
16 |
17 |
34 |
2 |
21 |
56 |
33 |
4 |
6 |
10 |
44 |
|
Türkiye |
a |
12 |
12 |
3 |
16 |
30 |
39 |
7 |
24 |
31 |
70 |
|
United Kingdom |
6 |
14 |
19 |
2 |
22 |
44 |
41 |
6 |
10 |
16 |
56 |
|
United States |
x(3) |
20 |
20 |
1 |
25 |
46 |
39 |
4 |
10 |
14 |
54 |
|
OECD Average |
3 |
15 |
18 |
3 |
33 |
53 |
33 |
5 |
9 |
14 |
47 |
|
Partner and/or accession countries |
|||||||||||
|
Argentina |
m |
m |
m |
m |
m |
m |
m |
m |
m |
m |
m |
|
Brazil1 |
a |
19 |
19 |
3 |
15 |
38 |
40 |
6 |
16 |
22 |
62 |
|
Bulgaria |
m |
6 |
6 |
0 |
61 |
68 |
17 |
2 |
13 |
15 |
32 |
|
China |
m |
m |
m |
m |
m |
m |
m |
m |
m |
m |
m |
|
Croatia |
x(3) |
x(3) |
4 |
c |
51 |
56 |
31 |
7 |
6 |
13 |
44 |
|
India |
m |
m |
m |
m |
m |
m |
m |
m |
m |
m |
m |
|
Indonesia |
m |
m |
m |
m |
m |
m |
m |
m |
m |
m |
m |
|
Peru |
x(3) |
x(3) |
15 |
2 |
22 |
40 |
40 |
3 |
17 |
20 |
60 |
|
Romania |
x(3) |
x(3) |
1 |
c |
52 |
53 |
24 |
7 |
16 |
23 |
47 |
|
Saudi Arabia |
m |
m |
m |
m |
m |
m |
m |
m |
m |
m |
m |
|
South Africa |
a |
1 |
1 |
1 |
36 |
38 |
14 |
22 |
26 |
48 |
62 |
|
EU25 average |
6 |
11 |
15 |
2 |
41 |
56 |
28 |
6 |
8 |
13 |
41 |
|
G20 average |
m |
m |
m |
m |
m |
m |
m |
m |
m |
m |
m |
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 online.
1. Year of reference differs from 2025: 2024 for Brazil and Chile; 2023 for Iceland.
The data for this Table can be accessed via https://stat.link/t764xw.
Table A2.2. Trends in the share of 18-24 year-olds in education/not in education, by work status and gender (2015 and 2025)
Copy link to Table A2.2. Trends in the share of 18-24 year-olds in education/not in education, by work status and gender (2015 and 2025)In per cent
|
|
In education |
Not in education |
|||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
|
Employed |
NEET |
||||||||||||
|
2015 |
2025 |
2015 |
2025 |
2015 |
2025 |
||||||||
|
Men |
Women |
Men |
Women |
Men |
Women |
Men |
Women |
Men |
Women |
Men |
Women |
||
|
(1) |
(2) |
(4) |
(5) |
(7) |
(8) |
(10) |
(11) |
(13) |
(14) |
(16) |
(17) |
||
|
OECD countries |
|||||||||||||
|
Australia1 |
49 |
53 |
50 |
49 |
41 |
35 |
40 |
41 |
10 |
12 |
10 |
10 |
|
|
Austria1 |
46 |
51 |
45 |
53 |
42 |
38 |
42 |
34 |
13 |
12 |
13 |
13 |
|
|
Belgium |
52 |
59 |
58 |
70 |
34 |
27 |
29 |
21 |
14 |
14 |
13 |
9 |
|
|
Canada |
c |
c |
44 |
56 |
c |
c |
42 |
32 |
c |
c |
14 |
12 |
|
|
Chile2 |
50 |
51 |
55 |
57 |
34 |
23 |
27 |
21 |
16 |
26 |
17 |
22 |
|
|
Colombia |
32 |
34 |
31 |
34 |
54 |
30 |
52 |
32 |
14 |
35 |
17 |
34 |
|
|
Costa Rica |
46 |
47 |
42 |
100 |
38 |
22 |
38 |
m |
17 |
30 |
20 |
m |
|
|
Czechia |
m |
m |
59 |
67 |
m |
m |
35 |
24 |
m |
m |
6 |
9 |
|
|
Denmark |
61 |
68 |
51b |
53b |
27 |
20 |
36b |
35b |
13 |
12 |
13b |
13b |
|
|
Estonia |
47 |
61 |
53 |
63 |
42 |
23 |
34 |
29 |
11 |
16 |
13 |
8 |
|
|
Finland |
51 |
59 |
58 |
64 |
29 |
27 |
26 |
21 |
19 |
14 |
16 |
15 |
|
|
France |
51 |
58 |
48 |
61 |
29 |
24 |
32 |
23 |
20 |
18 |
20 |
16 |
|
|
Germany |
62 |
62 |
57 |
61 |
30 |
28 |
32 |
29 |
8 |
9 |
10 |
11 |
|
|
Greece1 |
60 |
65 |
55 |
62 |
17 |
11 |
26 |
19 |
23 |
24 |
19 |
18 |
|
|
Hungary |
51 |
55 |
52 |
56 |
34 |
28 |
36 |
28 |
15 |
17 |
12 |
16 |
|
|
Iceland2 |
53 |
64 |
48 |
60 |
38 |
30 |
46 |
37 |
8 |
6 |
6 |
3 |
|
|
Ireland |
52 |
54 |
62 |
63 |
28 |
28 |
29 |
29 |
19 |
17 |
9 |
8 |
|
|
Israel1 |
26 |
36 |
27 |
33 |
58 |
45 |
55 |
46 |
16 |
19 |
18 |
21 |
|
|
Italy |
48 |
57 |
55 |
67 |
22 |
14 |
29 |
17 |
30 |
30 |
16 |
16 |
|
|
Japan |
m |
m |
m |
m |
m |
m |
m |
m |
m |
m |
m |
m |
|
|
Korea |
m |
m |
m |
m |
m |
m |
m |
m |
m |
m |
m |
m |
|
|
Latvia |
48 |
59 |
52 |
61 |
41 |
28 |
33 |
26 |
10 |
13 |
15 |
13 |
|
|
Lithuania |
55 |
65 |
54 |
54 |
30 |
21 |
31 |
34 |
15 |
14 |
14 |
13 |
|
|
Luxembourg |
64 |
69 |
54 |
65 |
28 |
23 |
c |
c |
c |
c |
c |
c |
|
|
Mexico1 |
37 |
35 |
37 |
41 |
53 |
28 |
53 |
30 |
9 |
37 |
10 |
29 |
|
|
Netherlands |
63 |
62 |
63 |
66 |
30 |
31 |
31 |
28 |
7 |
6 |
6 |
6 |
|
|
New Zealand |
42 |
41 |
36 |
37 |
46 |
40 |
50 |
46 |
13 |
18 |
14 |
16 |
|
|
Norway1 |
44 |
55 |
59 |
70 |
46 |
35 |
34 |
24 |
10 |
9 |
7 |
6 |
|
|
Poland |
50 |
64 |
53 |
65 |
34 |
20 |
35 |
20 |
16 |
16 |
13 |
15 |
|
|
Portugal |
54 |
55 |
49 |
57 |
29 |
24 |
36 |
27 |
17 |
20 |
15 |
15 |
|
|
Slovak Republic |
47 |
62 |
56 |
72 |
37 |
21 |
33 |
17 |
16 |
17 |
12 |
11 |
|
|
Slovenia |
60 |
73 |
55 |
77 |
27 |
12 |
36 |
13 |
14 |
16 |
10 |
10 |
|
|
Spain1 |
55 |
62 |
57 |
65 |
21 |
16 |
26 |
19 |
24 |
23 |
18 |
16 |
|
|
Sweden |
41 |
51 |
51 |
61 |
47 |
38 |
40 |
30 |
12 |
11 |
9 |
10 |
|
|
Switzerland |
55b |
55b |
54 |
59 |
32b |
36b |
35 |
32 |
13b |
9b |
11 |
9 |
|
|
Türkiye1 |
44 |
35 |
30 |
31 |
36 |
19 |
50 |
26 |
20 |
46 |
20 |
43 |
|
|
United Kingdom |
43 |
43 |
42 |
46 |
44 |
40 |
43 |
39 |
13 |
17 |
16 |
15 |
|
|
United States |
46 |
49 |
44 |
49 |
39 |
33 |
42 |
37 |
15 |
17 |
15 |
14 |
|
|
OECD average |
50 |
55 |
50 |
58 |
36 |
27 |
37 |
28 |
15 |
18 |
13 |
15 |
|
|
OECD average for countries with available and comparable data for both years |
51 |
57 |
51 |
61 |
35 |
27 |
36 |
28 |
15 |
17 |
13 |
13 |
|
|
Partner and/or accession countries |
|||||||||||||
|
Argentina |
m |
m |
m |
m |
m |
m |
m |
m |
m |
m |
m |
m |
|
|
Brazil1,2 |
35 |
39 |
35 |
41 |
45 |
28 |
49 |
31 |
20 |
34 |
17 |
28 |
|
|
Bulgaria |
m |
m |
63 |
72 |
m |
m |
23 |
11 |
m |
m |
14 |
16 |
|
|
China |
m |
m |
m |
m |
m |
m |
m |
m |
m |
m |
m |
m |
|
|
Croatia |
46 |
62 |
49 |
64 |
27 |
17 |
37 |
24 |
27 |
21 |
14 |
12 |
|
|
India |
m |
m |
m |
m |
m |
m |
m |
m |
m |
m |
m |
m |
|
|
Indonesia |
m |
m |
m |
m |
m |
m |
m |
m |
m |
m |
m |
m |
|
|
Peru1 |
34 |
37 |
37 |
43 |
50 |
36 |
46 |
34 |
16 |
27 |
16 |
24 |
|
|
Romania |
42b |
46b |
52 |
55 |
35b |
25b |
30 |
17 |
23b |
29b |
18 |
28 |
|
|
Saudi Arabia |
m |
m |
m |
m |
m |
m |
m |
m |
m |
m |
m |
m |
|
|
EU25 average |
52 |
60 |
54 |
63 |
31 |
24 |
32 |
24 |
17 |
17 |
13 |
13 |
|
|
G20 average |
m |
m |
m |
m |
m |
m |
m |
m |
m |
m |
m |
m |
|
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 totals for both men and women are available for consultation online.
1. Year of reference differs from 2015: 2016 for Australia, Austria, Brazil, Greece, Israel, Mexico, Norway, Peru, Spain and Türkiye.
2. Year of reference differs from 2025: 2024 for Brazil and Chile; 2023 for Iceland.
The data for this Table can be accessed via https://stat.link/t764xw.
Table A2.3. Distribution of 18-29 year-olds by education and labour-force status, by literacy proficiency level (2023)
Copy link to Table A2.3. Distribution of 18-29 year-olds by education and labour-force status, by literacy proficiency level (2023)In per cent, Survey of Adult Skills (PIAAC)
|
|
Level 2 and below |
Level 3 and above |
||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
|
In education |
Employed and not in education |
NEET |
In education |
Employed and not in education |
NEET |
|||||||
|
% |
S.E. |
% |
S.E. |
% |
S.E. |
% |
S.E. |
% |
S.E. |
% |
S.E. |
|
|
(1) |
(2) |
(3) |
(4) |
(5) |
(6) |
|||||||
|
OECD countries |
||||||||||||
|
Austria |
28 |
(3.1) |
57 |
(3.2) |
15 |
(2.5) |
51 |
(2.6) |
42 |
(2.6) |
7 |
(1.6) |
|
Canada |
42 |
(3.1) |
41 |
(3.3) |
17 |
(2.4) |
44 |
(2.7) |
47 |
(2.9) |
9 |
(1.3) |
|
Chile |
32 |
(1.5) |
49 |
(2.2) |
19 |
(1.7) |
53 |
(3.5) |
36 |
(3.4) |
11 |
(3.3) |
|
Czechia |
27 |
(2.9) |
54 |
(3.1) |
19 |
(2.4) |
51 |
(2.5) |
41 |
(2.6) |
8 |
(1.5) |
|
Denmark |
39 |
(3.6) |
49 |
(3.8) |
12 |
(2.5) |
51 |
(2.6) |
41 |
(2.6) |
8 |
(1.5) |
|
Estonia |
36 |
(2.9) |
47 |
(3.0) |
17 |
(2.3) |
48 |
(1.6) |
46 |
(1.8) |
6 |
(0.9) |
|
Finland |
42 |
(6.1) |
40 |
(5.1) |
18 |
(4.1) |
54 |
(2.3) |
37 |
(2.2) |
9 |
(1.3) |
|
France |
30 |
(2.0) |
52 |
(2.2) |
18 |
(1.8) |
45 |
(1.7) |
46 |
(1.8) |
9 |
(1.1) |
|
Germany |
34 |
(2.7) |
47 |
(2.9) |
19 |
(2.6) |
52 |
(2.3) |
42 |
(2.1) |
6 |
(1.1) |
|
Hungary |
24 |
(2.0) |
57 |
(2.3) |
19 |
(1.8) |
51 |
(3.2) |
43 |
(3.2) |
7 |
(1.6) |
|
Ireland |
34 |
(3.9) |
52 |
(4.1) |
14 |
(2.7) |
50 |
(3.5) |
46 |
(3.6) |
4 |
(1.5) |
|
Israel |
25 |
(1.7) |
48 |
(1.6) |
27 |
(1.5) |
36 |
(2.3) |
48 |
(2.4) |
16 |
(1.8) |
|
Italy |
34 |
(2.4) |
39 |
(2.3) |
28 |
(2.2) |
54 |
(3.0) |
30 |
(2.7) |
16 |
(2.4) |
|
Japan |
27 |
(3.5) |
64 |
(4.3) |
10 |
(2.6) |
33 |
(1.5) |
57 |
(1.9) |
9 |
(1.4) |
|
Korea |
32 |
(2.8) |
50 |
(3.1) |
18 |
(2.3) |
44 |
(2.6) |
41 |
(2.7) |
16 |
(2.1) |
|
Latvia |
32 |
(3.2) |
49 |
(3.5) |
19 |
(2.9) |
44 |
(3.6) |
44 |
(3.6) |
12 |
(2.5) |
|
Lithuania |
31 |
(2.4) |
45 |
(2.6) |
24 |
(2.4) |
41 |
(4.0) |
45 |
(4.3) |
15 |
(3.0) |
|
Netherlands |
46 |
(3.8) |
43 |
(3.8) |
10 |
(2.2) |
52 |
(2.3) |
43 |
(2.3) |
5 |
(1.1) |
|
New Zealand |
28 |
(3.2) |
53 |
(3.3) |
19 |
(3.1) |
36 |
(3.8) |
55 |
(3.8) |
9 |
(2.2) |
|
Norway |
41 |
(3.6) |
48 |
(3.5) |
11 |
(2.3) |
47 |
(1.9) |
47 |
(2.2) |
6 |
(1.1) |
|
Poland |
30 |
(1.7) |
53 |
(1.8) |
17 |
(1.3) |
44 |
(3.6) |
47 |
(3.5) |
9 |
(1.8) |
|
Portugal |
28 |
(3.0) |
52 |
(3.4) |
20 |
(2.3) |
51 |
(3.6) |
38 |
(3.3) |
11 |
(1.8) |
|
Slovak Republic |
33 |
(2.2) |
54 |
(2.5) |
13 |
(1.3) |
43 |
(3.7) |
51 |
(3.8) |
6 |
(1.5) |
|
Spain |
43 |
(2.6) |
40 |
(2.5) |
16 |
(1.8) |
55 |
(3.0) |
36 |
(3.0) |
9 |
(2.1) |
|
Sweden |
47 |
(4.5) |
41 |
(4.5) |
12 |
(2.8) |
47 |
(2.6) |
42 |
(2.6) |
11 |
(2.0) |
|
Switzerland |
33 |
(3.2) |
55 |
(3.0) |
12 |
(2.1) |
56 |
(2.1) |
40 |
(1.9) |
4 |
(0.8) |
|
United States |
37 |
(3.3) |
45 |
(3.9) |
18 |
(2.5) |
44 |
(2.9) |
46 |
(2.9) |
10 |
(2.3) |
|
Other economies |
|
|
|
|
|
|
|
|
|
|
|
|
|
England (UK) |
38 |
(3.7) |
50 |
(4.1) |
12 |
(2.2) |
47 |
(2.6) |
47 |
(2.7) |
6 |
(1.1) |
|
Flemish Region (Belgium) |
26 |
(3.6) |
55 |
(3.6) |
19 |
(2.7) |
37 |
(2.8) |
56 |
(2.7) |
7 |
(1.2) |
|
OECD average |
34 |
|
49 |
|
17 |
|
47 |
|
44 |
|
9 |
|
|
Partner and/or accession countries |
||||||||||||
|
Croatia |
29 |
(2.2) |
48 |
(2.3) |
23 |
(2.1) |
48 |
(2.6) |
42 |
(2.8) |
10 |
(1.8) |
Note: Literacy proficiency refers to the PIAAC proficiency scale, which is measured on a continuous scale and grouped into levels to facilitate interpretation. Level 2 and below includes Level 1 and below as well as Level 2, while Level 3 and above includes Levels 3, 4 and 5.
The data for this Table can be accessed via https://stat.link/t764xw.