Peter Jarrett
Pierre-Alain Pionnier
OECD Economic Surveys: Hungary 2026
Abstract
As Hungary’s population is shrinking and ageing, it is essential that women actively participate in the labour market to mitigate the drag on labour supply and that young people are increasingly well educated to foster productivity developments. While the gender employment gap has declined over time, a substantial wage gap remains because mothers with young children stay away from the labour market for a long time, which is costly for their career. Aligning family leave entitlements with international practices for both men and women and accelerating the construction of early childcare facilities would improve the situation. While young people entering the labour market are largely employed under permanent contracts and earn wages that are close to those of older age groups, they are not better educated on average than the previous generation, and the share of tertiary-educated workers in Hungary is now one of the lowest in the OECD. The social background of students has a strong influence on educational attainments. Leaving no one behind at school will be key to improve overall education. Reducing class sizes in disadvantaged primary schools, using financial and non-financial incentives to facilitate recruitments and attract teachers with specific qualifications to those schools, and providing additional tutoring to avoid grade repetition would be especially helpful.
Many developed countries face ongoing or foreseeable downturns in their available labour force in the coming years, and Hungary is no exception. Its population peaked at around 10.7 million in the early 1980s. It is currently just over 9.5 million, and the 2024 UN projections expect it to fall below 9 million by 2050 and below 7.5 million in 2100, despite government efforts to boost fertility and activity rates. However, activity rates will inevitably plateau, resulting in contracting available labour resources if the fertility rate does not recover: the labour force could fall by 0.5% per year over the next 25 years, about six times as fast as in the OECD overall (OECD, 2022[1]).
The labour market is an important determinant of economic growth, prosperity and distributive justice in OECD countries. Its inclusivity has been shown to boost economic growth (Hsieh et al., 2019). Previous OECD Economic Surveys of Hungary concluded that outcomes suffer from the lack of affordable childcare, insufficient recourse to flexible working arrangements and poor skills development, notably from the compulsory education system. A review of the recommendations made and actions taken in response is given in Table 3.1.
This chapter focuses on women and young adults and the challenges they face in the Hungarian labour market. The main justification for looking at these two groups in the case of Hungary is that they could help mitigate the drag on labour supply from ongoing population ageing. If labour-market inequality between men and women could be totally overcome, Hungary’s per capita GDP growth would rise by an estimated average of 0.16 percentage point (pp) per year, which cumulates to 6.1% more output by 2060 (Fluchtmann, Keese and Adema, 2024[2]). This is less than the corresponding OECD averages of 0.22pp and 8.8%, respectively, but considerable. As is the case in other OECD countries, young people’s labour-market outcomes are worse than those of their older peers. Their unemployment rate is about 10pp higher than those of their prime-age counterparts, and various education outcomes are unsatisfactory, especially when it comes to overall education achievements and gaps between students with different socio-economic backgrounds.
3.1.1. The gender employment gap has declined over time, contrary to the wage gap
Following progress over the last 15 years, activity and employment rates in Hungary now exceed the OECD average for both women and men, and the gender gap for both measures is below the OECD average. The gender gap in activity has dwindled to 7.8% in 2024, below the OECD average of 9.8%. With no meaningful gender gap in unemployment, the difference in employment rates between women and men was close to 7% in 2024, down from almost 10% in 2018 (Figure 3.1, Panel A). One important explanatory factor behind the narrowing gender employment gap is the shift in Hungary’s economic structure away from industry and construction (where men represent 71% of employed persons) to services (where women have 57% of all jobs). Nevertheless, there are significant differences across age groups. While gender activity and employment gaps are below 3% for people aged less than 55, these gaps exceed 28% for 60–64-year-olds: female employment rates fall much more with age than in most other countries. This is related to the continuing difference in the pension age between men and women, a feature that is increasingly rare across OECD countries, as well as the Women40 Programme, allowing women to retire after 40 years of work, including up to eight years of child rearing (Chapter 1). Moreover, official employment statistics hide the fact that women in paid parental leave are absent from the labour market for a long time, even though they are formally counted as employed (see below).
In 2024, Hungarian women faced a wage gap of 14.2% compared to men, around 4pp above the OECD average (Figure 3.1, Panel B). This wage gap has risen continuously since 2006, when it was only 6.4%. Nevertheless, social transfers keep poverty for men and women nearly equally low around 12%, the second lowest rate in the OECD. The gender gap in poverty only becomes significant at retirement age, when it reaches 10%, albeit much below the OECD average of 24%.
3.1.2. Women tend to study and work in less remunerative sectors
The fact that Hungarian women are on average better educated than men limits the overall employment gap. Indeed, the gender employment gap declines from 16pp for those with primary education or less, to 10pp for those with secondary attainment and 4pp for those with tertiary education. Early school leaving is slightly lower for girls than for boys, and women outnumber men as tertiary students at both bachelor and master levels and have reached parity at the doctoral level.
Note: In Panel A, employees who are temporarily away from work but continue to receive a remuneration from their employer or the government, which includes women receiving maternity or parental-leave allowances, are counted as employed. In Panel B, the gender wage gap is calculated as the difference between the median average incomes of male and female full-time employees, without controlling for any composition effect such as those related to differences in education, experience and economic sector. The OECD aggregate is the unweighted average of 38 countries in both Panels.
Source: OECD Employment and Labour Market Statistics.
Nevertheless, young Hungarian women in particular are more likely than men not to be in employment, education or training (NEET), possibly in part because of young motherhood. In 2024, the gap was 4.5pp, compared to around 2pp in the European Union as a whole. According to the Hungarian authorities, female NEETs are also less likely to register at the public employment service than their male counterparts. This calls for policy action, e.g. in the form of official communication campaigns directed at young women.
While being more educated on average, Hungarian women are less likely to study in more remunerative STEM fields, in particular ICT (Figure 3.2). Hungary’s gap of 10pp between women whose PISA outcomes are predicted to be sufficient to successfully complete a STEM degree (30% in 2012-15) and those who actually do so (20%) is large in international comparison (Mostafa, 2019[3]). This helps explain why the returns to tertiary education are smaller for women than for men, with Hungary’s gender gap in those returns bigger than anywhere else in the OECD (OECD, 2024[4]).
The low proportion of STEM tertiary students in Hungary is mainly related to the fact that women opt for different studies (Figure 3.2). Increasing the representation of women in STEM would facilitate their access to scientific careers where they can enhance their productivity and earn higher wages. This would reduce income inequality between men and women and ultimately boost long-term growth (Einiö, Feng and Jaravel, 2025[5]). Efforts should start from the first year of primary school and continue throughout schooling by promoting scientific careers through regular exposure to positive female role models (Breda et al., 2023[6]).
Share of STEM in all entrants in tertiary education programmes, 2023 or latest available year
Note: The OECD aggregate refers to the unweighted average of 37 countries. Data for Czechia, Germany, Ireland and the UK refer to 2022.
Source: OECD Education at a Glance 2025, Distribution of enrolled students, new entrants and graduates by field of education.
Different fields of study naturally translate into differences between sectors where men and women work. For example, women are under-represented in high-paying ICT occupations and over-represented in low-paying industries such as education and health care. Moreover, women tend to make fewer job transitions in general, especially early in their careers (Gonne and Trincão, 2024[7]). This could be especially harmful in Hungary where between-firm wage dispersion is one of the largest in the OECD (OECD, 2021[8]). Beyond initial education, Hungarian women aged 25-64 are less likely than men to participate in adult training, and increasingly so as the gap in favour of men has widened from 3.6pp in 2011 to 7.8pp in 2022, contrary to the evidence for the EU as a whole, where women are more likely than men to participate in adult training (Eurostat, Adult Education Surveys). This is likely to hamper job transitions and career progression for Hungarian women.
Hungarian women are also less likely to be in entrepreneurial roles than men. While Hungarians are less confident about starting a business than other Europeans in general, which could be ascribed to a lack of entrepreneurship education at school (Global Entrepreneurship Monitor, 2025[9]), this is especially the case for women. Despite a limited gender gap in financial knowledge (OECD, 2023, p. 137[10]), the long-term survival rates for female-led firms are lower (Csákné Filep, Szennay and Timár, 2024[11]). Gender-sensitive public procurement (mainstreaming gender considerations throughout the public procurement process) may be an option to encourage female entrepreneurship and empowerment (OECD, 2021[12]). It is used in a number of EU countries (EIGE, 2022[13]).
3.1.3. Mothers with young children stay away from the labour market for a long time
Official statistics show only small and declining differences in the employment rates of mothers with up to two children and women aged 15-49 with no children. It is only after the birth of a third child that the employment rate of Hungarian mothers falls significantly. Nevertheless, following EU-wide statistical practice, those statistics count as employed all employees who are temporarily away from work but continue to receive a remuneration from their employer or the government, which includes women receiving maternity or parental-leave allowances. In Hungary where those benefits can be received for an extended period, this statistical treatment increases the number of women counted as employed by 7% (Köllö, 2022[14]).
The Hungarian legislation grants more generous family leave benefits than in most other OECD countries. Women who have worked at least 12 months in the last two years and give birth to a child are entitled to a maternity leave of six months at full pay with no ceiling and no social contributions payable, which is called the infant-care benefit (CSED). Fathers are entitled to a paternity leave of two weeks. Either mothers or fathers are then entitled to 18 months of childcare benefit at 70% of previous pay with a ceiling of around EUR 1,000 per month under the GYED scheme, and a further year under the childcare allowance (GYES) with a fixed amount of around EUR 70 per month. The total is 160 weeks, with up to 79 weeks at full-rate equivalent for mothers. Such lengthy paid family leaves are matched only in Estonia and Slovenia among OECD countries (Figure 3.3, Panel A).
While combining childcare benefits with work is allowed, in practice Hungarian mothers with young children stay away from the labour market for a long time. If they return to work when their child reaches three months, they are entitled to keep 70% of the infant care allowance (CSED Extra) in addition to their salary. The childcare allowance GYED can also be cumulated with work and taken by either mothers or fathers. Nevertheless, only 12% of Hungarian mothers with their youngest child aged less than two are actually at work, compared with 38% on average in the EU (Figure 3.3, Panel B). In the worst-case scenario, the GYED allowance may even be formally taken by fathers (usually the higher earners) while mothers stay at home, leaving them with fewer years of pension contributions. It would be more equitable and cost-efficient to require the benefit to be taken by the parent who actually stops working.
The effects on mothers’ labour-market outcomes of being out of the labour force for such a long time are significant, especially for those with the highest education, as it leads to a depreciation of their human capital and lower chances of promotion and career progression (Canaan et al., 2022[15]). Indeed, the available evidence shows that pure labour-market discrimination between men and women does not play a significant role in explaining the gender wage gap in Hungary, as gaps are negligible early in professional life. The wage gap that Hungarian women face is mostly related to childbearing and then tends to persist until the end of their professional life (Ciminelli, Schwellnus and Stadler, 2021[16]).
Major changes benefitting women with children have been recently introduced in the Personal Income Tax (PIT) schedule to encourage fertility while reinforcing work incentives for women (Chapter 1). Women with four or more children have been exempt from PIT since 2020. This measure was extended to mothers with three or more children in 2025 and will be progressively extended to those with two or more children over 2026-29. Since 2023, all mothers below the age of 30 have also been exempted from PIT, whatever their number of children so as to encourage maternity at a younger age. Altogether, the government estimates that mothers with two or more children and all mothers under 30 will enjoy an increase of EUR 270 in their average monthly disposable income, which is more than their current average wage disadvantage compared to men.
The impact of these tax incentives should be carefully evaluated, as they will be costly for public finances and probably entail large deadweight costs (Chapter 1). In order to increase fertility, as well as the labour supply and career prospects of women with children, it would be more cost effective to try to change social norms, align family leave entitlements with international practices for both men and women, and use the corresponding savings to accelerate the construction of childcare facilities for children under three (see below).
Note: In Panel A, family leave comprises maternity-, paternity-, home care- and parental leave. Entitlements are reported in full-rate equivalent Weeks of shareable leave refer to parental- and home care leave entitlements that can be freely shared between parents. The OECD aggregate refers to the unweighted average of 38 countries. In Panel B, the “at-work” rate includes only those who did at least one hour of work for pay or profit during the survey reference week. It differs from the employment rate in that it excludes those who are employed but absent from work. For Canada and the United States, data refer to mothers with children aged 0 to 17. For Canada, the child age groups are 0 to 5 and 6 to 17, and for the United States 0 to 2, 3 to 5 and 6 to 17.
Source: OECD Family Database, PF2.1 Key characteristics of parental leave systems; and (OECD, 2022[1]).
3.1.4. Social norms play a large role in determining women’s labour-market outcomes
According to qualitative surveys, social norms about gender roles in Hungary are among Europe’s most conservative (Fodor and Balogh, 2010[17]). For example, only 28% of the Hungarian respondents to the 2023 European Social Survey consider it very good for family life if equal numbers of men and women are in paid work, compared to an EU average of 40%. Similarly, only 14% of Hungarians strongly support the idea that men and women should take equal periods of paid leave for childcare, half the sample average. Perceptions are aligned with these opinions, as 34% of respondents believe that women are never or only rarely paid less for the same work, double the average, and only 20% think that women are less fairly treated in hiring, pay or promotions, well below the cross-country average of 52%.
Anecdotal evidence suggests that such social norms likely incentivise women to take the full length of parental leave benefits to which they are entitled and, when they return to work, to seek out positions with better job security for which they are often over-qualified. While Hungarian women make up a reasonable share of managerial jobs (over 40% according to Eurostat), they are severely under-represented on the boards of publicly listed companies, where they are only 10% of directors, slightly less than in 2013, compared to a growing OECD average share of nearly 30% (Figure 3.4). Moreover, only 15% of Members of Parliament are women, up from 9% in 2012 but much below the OECD average of 34%. The public sector has a key role to play to change perceptions and induce progress. A 2024 EU directive calls for at least a third of all directors to be women by mid-2026. Most of the best-performing countries by this measure have implemented quotas, which have been achieved or even surpassed. Financial incentives could be used as well, and the same could be done for election candidates.
Share of women on boards of largest listed companies according to implemented quotas and targets
Note: Israel and Korea have introduced a quota mandating “at least one” woman on boards of listed companies, which is indicated at 20% in this figure, but may differ across companies depending on the size of the board. For countries with higher indicated shares of women on boards in 2013 than in 2021, this might be explained by the composition of the samples, which may vary over time to reflect changes in the market capitalisation of companies and/or volumes of shares traded. The OECD aggregate is the unweighted average of 37 countries. See the source for more specific notes.
Source: OECD (2023), Joining Forces for Gender Equality: What is Holding us Back?
Granting fathers a non-transferable paternity leave is another way to change perceptions and social norms regarding the role of men in parenting (OECD, 2023[10]). Such leaves have been shown to rebalance childcare roles between parents (Canaan et al., 2022[15]) and enhance women’s careers (Cools, Fiva and Kirkebøen, 2015[18]). Hungarian men have been eligible for a non-transferable paternity leave of two weeks since 2023, half at full salary and the rest at 40%, but take-up is only around a quarter. Other countries are more generous with paternity leave, most notably Spain with 16 weeks. Hungary should consider further extending non-transferable paternity leave and either making it partly mandatory or at least putting in place communication campaigns to encourage uptake.
3.1.5. The availability of childcare places for young children should be further expanded
While kindergarten is mandatory from the age of three, a large majority of children below that age is not enrolled in formal childcare in Hungary (Figure 3.5, Panel A). Empirical estimates show that if the availability of early childhood education and care (ECEC) was as complete as that of kindergartens, maternal employment in Hungary would rise significantly (Szabo et al., 2022[19]). Formal childcare also provides cognitive, social development and well-being advantages to children themselves, at least once they are a year old and the benefits of breast-feeding are largely exhausted (Heckman, 2008[20]) (Eros, Smoter and Kreko, 2022[21]).
Because they are income-related, net childcare costs are relatively low in Hungary. For example, a couple with two children, one parent earning 67% of the average wage and the other earning the minimum wage, pays 6% of disposable income for full-time childcare, below the OECD average of 9% (OECD, 2023[22]). This accounts for costs net of any benefits such as childcare allowances, tax and fee rebates calculated based on income. While social norms may contribute to low enrolment, limited supply is an issue in many locations. Nursery coverage has improved in recent years following a capacity-building programme launched in 2017, but the number of available places compared to the population of young children remains low. In the best equipped districts (in Budapest), there are places for 45% of the children under three, but half of Hungarian children under three live in districts where there are nursery places for less than a fourth of them. This proportion falls to 5% in some districts (Figure 3.5, Panel B).
Note: Panel A: According to the Hungarian Central Statistical Office (HCSO), the proportion of children aged less than three not enrolled in formal childcare was 78% in 2024, slightly above the 76.3% estimated by Eurostat based on EU-SILC survey. Panel B shows that 50% of Hungarian children under 3 live in districts where the ratio of nursery places to the number of children under 3 is below 25%.
Source: Panel A: Eurostat; Panel B: Hungarian Central Statistical Office (KSH), OECD calculations.
Beyond expanding the number of existing places, their availability may also be improved. Formal childcare centres typically close around 5pm, forcing parents (usually mothers) to leave the workplace in time to pick up their children. Lengthening childcare hours and expanding out-of-school-hours could be used to help more parents take up at least part-time employment, as has been done in Chile (Contreras and Sepulveda, 2017[23]), Switzerland (Felfe, Lechner and Thiemann, 2016[24]) and Germany (Shure, 2019[25]). While parents have recently been offered the possibility to ask for extended childcare hours for professional reasons, the ability of nurseries to respond to this additional demand is unclear. The planned development of official statistics on the supply and demand of early childcare is welcome.
Developing teleworking and other flexible working arrangements may also help parents to accommodate constraints related to work, family and childcare schedules. Only around 8% of all Hungarian employees worked from home in 2024, for an average of 1.4 days per week (Aksoy et al., 2025[26]), up from 5% in 2015, but below the EU average of 14% (Eros, Smoter and Kreko, 2022[21]). While teleworking may have adverse effects on the productivity of workers when it is used too intensively (Cappelli and Nehmen, 2025[27]), this risk seems slight in the case of Hungary, because of its limited use. As in Europe women tend to work more than men in jobs where teleworking is feasible (Touzet, 2023[28]), they may benefit even more than men from such developments.
3.1.6. With little formal long-term care, population ageing may further raise the burden on women
Hungary allocates comparatively few resources to long-term care (European Commission, 2024). In 2023, the sector had only 1.8 workers per 100 people aged 65+, just a third of the OECD average (Figure 3.6). Hungary is one of the OECD countries spending the least on formal elderly care (0.25% of GDP), well below North European countries such as Sweden (2.8% of GDP) (OECD, 2024[29]). Only 21% of the elderly with long-term care needs receive any formal care, compared to an OECD average of 27% (OECD, 2024, p. 114[29]). Data for Hungary on accessibility are not available, but in 2019, the number of elderly people registered on a waiting list for a place in a nursing home represented around 45% of existing places, thus pointing to capacity constraints (Gyarmati, 2019[30]).
Number of long-term care workers, 2024 or latest available year
Note: The OECD aggregate refers to the unweighted average of 25 countries.
Source: OECD Health Statistics, "Long-term care resources and utilisation - workers" (database).
European women spend 20% more time than men on informal care activities (Cattaneo et al., 2025[31]), but Hungarian women are especially exposed to this burden. Hungary’s gender gap is the third largest in the EU, surpassed by only Czechia and Lithuania (EIGE, 2019[32]), and it has not declined since the early 2010s, contrary to what happened elsewhere in Europe. This has been shown to reduce women’s labour market activity. As the population ages, this situation risks further increasing the burden on women and restricting their labour supply, especially for those in their 50s and older. In this context, expanding social expenditure on long-term care in line with demographic developments will be key.
3.2.1. Youth labour market outcomes could improve further
In 2024, the unemployment rate of Hungarian youth (aged 15-24) was 15.2%, 11.3pp higher than for the prime-age group (25-54). This gap has narrowed over time but remained above the OECD average of 6.4pp in 2024, which shows that further progress is possible. In the wake of the financial crisis of 2008-09 and the subsequent economic crisis in Europe, the youth unemployment rate was 19pp higher than for the prime-age group, and the youth employment rate 60pp lower. The subsequent recovery brought the unemployment-rate gap to around 10pp in 2016, and it has hovered around this level since then (Figure 3.7), but with significant differences between regions. The gap is lowest in Budapest and Central Transdanubia and three times as high in Southern Transdanubia. It is also higher in rural areas and for less educated workers.
Even more important is the number of such people who are neither in employment, education or training (NEET), since spending a considerable period as NEET can lead to a variety of adverse social conditions, such as poverty and social exclusion, insecurity, criminal activity and physical and mental health problems (Kyriakopoulou, 2021[33]). Hungary’s overall NEET rate for 15–29-year-olds was 10.9% in 2024, close to the EU average (Figure 3.8). Nevertheless, it is three times higher in rural areas (around 16%, the fifth highest in the EU) than in urban areas (just over 5%, among the lowest in the EU) (Figure 3.8). While this Chapter assesses youth employment globally, it should be noted that Roma youth face a particularly unfavourable situation in the labour-market, with a NEET rate around four times higher than non-Roma youth, which deserves specific policies for this target group (ERGO Network, 2024[34]).
Labour market outcomes for people aged 15-24
Note: Youth employment and unemployment rates are expressed at 3-month moving average rate and they are compared to employment and unemployment rates for prime-age people (25-54) by indicating differences of percentage points between them.
Source: Hungarian Central Statistical Office.
Young people neither in employment nor in education and training (NEETs), 15-29 years, 2024
Note: Data are based on a combination of two datasets where data on breakdowns by degree of urbanisation and its total come from Eurostat. The OECD aggregate refers to the unweighted average of countries included in this figure.
Source: OECD Youth not in employment, education or training (NEET) dataset; Eurostat.
The government offers various programmes to support labour-market entry by young people (Table 3.2). Over 2024-25, EUR 84 million has been spent on the largest one (Youth Guarantee Plus) to support about 27,000 young people. It will be important to assess its cost-effectiveness. Some young people with less than primary education can also be beneficiaries of public work schemes, created in 2011 and covering about 2% of total employees. Participants are paid half the minimum wage to work for municipalities, churches and NGOs. Six months after completion, only 9% are employed in the primary labour market, 14% are unemployed, and the majority are in public employment, according to the Hungarian authorities. Young people entering the labour market are also partly exempted from employer social contributions for one year.
Source: Government of Hungary.
Only a limited share of Hungarian workers is employed under temporary contracts, and young people are no exception. The proportion of such contracts has declined over time, even more so among women than men, to reach 5% for all workers and 12% for those aged 15-24 in 2023, well below the EU averages of 13% and 48%, respectively.
Even though many young people in Hungary start their careers at the minimum wage, their wages are on average relatively close to those earned by older age groups, in contrast to what happens in other countries. In 2022, Hungarians aged less than 30 earned on average 87% of national average earnings, significantly above the EU-country average of 75% (Eurostat, Structure of Earnings Survey). This could be related to the prohibition of age discrimination in wage determination, the lack of age-based differentiation in minimum wages, and the rarity of collective agreements linking wages to age/service time, as well as a lower proportion of part-time jobs in Hungary than elsewhere, including for young people.
In line with earnings, the poverty rate of young people in Hungary (9%) is close to the average for all age groups (10%). The fact that they leave the parental home relatively late (at an average age of 27, according to Eurostat), and that they finish schooling and get their first regular job at a slightly earlier age than the EU average also contributes to this outcome.
More could be done to protect young people from labour-market risks. They are especially exposed to the strict eligibility conditions for accessing unemployment insurance. As in other OECD countries, the unemployment rate of young people is more sensitive to business cycle fluctuations than that of older workers. However, unemployment insurance is only available for three months in Hungary, which is shorter than in any other OECD country, and eligibility requires a minimum of 12 months of contributions, above the OECD average of 10 months. When jobs are harder to find during an economic downturn, jobseekers may be left without resources or forced to take a low-paying job, risking a feedback loop ending in poverty. During the first COVID-19 pandemic wave for example, 20% of jobseekers registered at the National Employment Service did not receive any benefits, and half of those initially eligible for unemployment benefits lost them after three months, in a context where it was difficult to find a new job due to lockdowns and depressed economic activity (Boza and Krekó, 2022[35]). Easing access to unemployment insurance and/or extending its duration during economic downturns, as done in France since 2023, would disproportionately benefit young people. Another idea would be to have a permanent short-time working scheme in place that could be mobilised rapidly in times of economic distress, to avoid repeating the initial failure in the spring of 2020 when overly strict access conditions resulted in low take-up (OECD, 2024[36]).
Training and targeted job-search assistance, favouring disadvantaged groups and regions, should also be further developed. This should complement a more flexible access to unemployment insurance to facilitate return to employment. Indeed, 38% of unemployed Hungarians aged 15-24 in 2024 were in this situation for more than six months (OECD: 21%), and 21% for more than a year (OECD: 10%), thus showing structural difficulties in finding a job. In 2022, Hungary’s budget for labour-market spending had fallen to only around 0.4% of GDP (0.2% on active measures), compared to the OECD average of 1.0% (0.4% on active measures). Better funding would allow the Public Employment Service (PES) to support more jobseekers. In 2020, only 60% of Hungary’s jobless were in contact with the PES, well below corresponding levels for Lithuania (86%), Czechia (79%) and the Slovak Republic (72%) (EU Labour Force Survey).
In sum, while young people in Hungary are less likely to start working with relatively low wages and unstable contracts than in other OECD countries, more could be done to protect them from labour-market risks. Moreover, the fraction of those neither in employment nor in education and training shows untapped potential, especially outside main cities. Fully mobilising the workforce will be key to sustain living standards as population ages. The suggested fiscal reform aiming at lowering the labour tax wedge (Chapter 1) would increase labour demand for young people. Nevertheless, ensuring that young people are increasingly well educated before they start working will also be key for Hungary’s long-term economic development and capacity to move up value chains in various sectors. Beyond initial education, adult education is crucial to allow the workforce keeping up with technological progress (Chapter 4).
3.2.2. Towards a more inclusive and efficient initial education system
Educational attainment trends have stalled for more than a decade
As in most OECD countries, young people’s integration in the labour market is closely related to initial education. In 2024, the unemployment rate was 15.5% for young adults aged 25-34 without upper secondary education, 4.3% for those with upper secondary education, and 2.4% for those with tertiary education. Moreover, financial returns to higher education are high in international comparison (Figure 3.9).
Percentage change in hourly wages associated with a one-standard-deviation increase in years of education
Note: Data are based on employed adults aged 25-65 not in formal education. Wages are gross hourly earnings for employed and self-employed individuals, including bonuses, in PPP-adjusted 2022 USD.
Source: OECD (2024), “Survey of Adult Skills 2023”, OECD Skills Studies, Table A.4.8 (L, N, A) in Annex A.
Nevertheless, Hungary’s educational attainment trends have stalled for more than a decade, contrary to what has happened in most OECD countries. The share of Hungary’s 25-34-year-old population with completed secondary education has risen only slowly over the last 20 years (Figure 3.10, Panel A), and while the 2022 PISA outcomes for students aged 15 are close to the OECD average, they also show an absolute performance decline in mathematics and sciences since 2000.
Source: Hungarian Central Statistical Office (KSH), OECD calculations.
Beyond secondary education, the proportion of young (25-34) adults with tertiary education has stagnated since the early 2010s and is now one of the lowest in the OECD. In most other OECD countries, the proportion of tertiary-educated people in the younger (25-34) generation is significantly higher than in the previous (45-54) generation, but hardly so in Hungary (Figure 3.10, Panel B). While the government points to a rise in tertiary admissions of 15% in the last two academic years, led by enrolment in STEM fields, sustaining this improvement will be key to meet the objective of raising adult tertiary attainment to 45% by 2030.
Low educational attainments translate into limited skills in the adult population. Hungary scored below the OECD average in both literacy and numeracy in the latest OECD PIAAC Survey to measure adult competencies. At 32%, the share of low performers in literacy was the fifth highest in the OECD, and much larger than in the previous (2017) Survey (OECD, 2025[37]). Outcomes in numeracy also deteriorated more than anywhere else except Lithuania and Poland. The performance was especially low for Hungarians aged less than 25 who did not outperform their elders, contrary to what could be seen in other countries. These results were obtained despite relatively high government expenditure on education, at 5.2% of GDP in 2022, above the EU average of 4.7%. Therefore, a rethinking of the general education system more than a significant increase in expenditure is probably needed.
Note: Panel B: Data refers to 2023 for Iceland and the United States. The OECD aggregate is an unweighted average.
Source: Panel A: Hungarian Central Statistical Office (KSH); Panel B: OECD Database on Adults’ Educational Attainments
The social background of students has a strong influence on educational attainments
The social background of students is a key factor explaining educational outcomes in Hungary, suggesting that some barriers prevent Hungarian students from rationally responding to market incentives and wage signals when they are in initial education. Some specific hurdles affect the Roma population where 60% of students leave school with at most lower-secondary education (ERGO Network, 2024[34]), but educational barriers extend much beyond the Roma population. Socio-economic background played a larger role in explaining the mathematics performance of students aged 15 in the latest (2022) OECD PISA Survey than in any other OECD country except the Slovak Republic and Israel (Figure 3.11, Panel A). A similar impact of social background can be observed in Hungary’s own National Assessment of Basic Competencies (OKM) and in adult competencies assessed by the OECD PIAAC Survey. Hungarian adults with at least one tertiary-educated parent scored significantly higher in literacy than adults from families where neither parent attained upper-secondary education. The change in overall literacy scores over time in Hungary seems partly related to the comparatively large increase in the gap between those who completed tertiary education and those with only upper-secondary education.
Socio-economic backgrounds also have a strong impact on the probability of completing tertiary education. While Hungarians with at least one tertiary-educated parent are as likely to reach tertiary education as in other OECD countries, only 6% of those with no parent at upper-secondary level reach tertiary education, reflecting more limited upward social mobility than in most OECD countries (Figure 3.11, Panel B). Among the 16 countries participating in the European Social Survey since the early 2000s, Hungary is the one where the influence of parental education on the probability of completing tertiary education has increased the most (Róbert, 2019[38]). Even within the tertiary education system, students with disadvantaged socio-economic backgrounds are more likely to select shorter studies and to prolong their degrees, and they are less likely to study abroad due to financial constraints, even though such experience is valued as demonstrated by higher wages in the labour market (Hordósy and Szanyi, 2020[39]).
Note: Panel A: A socio-economically advantaged (disadvantaged) student is a student in the top (bottom) quarter of the PISA index of economic, social and cultural status in his or her own country.
Source: Panel A: OECD (2023), PISA 2022 Results (Volume I, Table I.2). Panel B: OECD Education at a Glance (2025[40]).
Increasing the overall education level by leaving no one behind
In order to raise the number of students in tertiary education, the government has recently lowered admission requirements for Bachelor and Master programmes. Nevertheless, accompanying support measures to ensure that the new entrants reach the expected level and complete their degree will probably be needed as well. Moreover, policies to promote higher educational achievements should address issues appearing early in life, including by developing early childhood education and care, reducing class sizes in the most disadvantaged primary schools, and providing additional information and mentoring to disadvantaged students and their families.
Expanding early childhood education and care for children below three would not only facilitate the return to work of mothers and avoid costly interruptions in their careers, as discussed above. It would also limit the influence of socio-economic backgrounds on educational outcomes and reduce inequalities of opportunities. Empirical evidence shows that early childhood education is particularly effective in remedying initial cognitive and social development disadvantages of children raised in poorer families (Heckman and Masterov, 2007[41]) (Havnes and Mogstad, 2015[42]).
More than in any other EU country, students with different socio-economic backgrounds usually attend different schools in Hungary, thus reducing opportunities for catching up. Ensuring that a significant share of budgetary resources and good teachers are allocated to disadvantaged schools would help restore the equality of opportunities for all. Nevertheless, the proportions of teachers without specific qualifications and of unfilled teacher positions are also two to three times higher in schools with a large proportion of disadvantaged students than in other schools (Hajdu et al., 2024[43]). Nevertheless, empirical evidence shows that teacher quality is particularly important to support the long-term success of children in disadvantaged areas. In the United States, students assigned to high value-added teachers, measured by how much they improve children’s test scores on average, are more likely to attend high-ranked colleges, earn higher salaries and live in higher socio-economic status neighbourhoods (Chetty et al., 2014[44]). Financial incentives have a role to play in recruiting teachers and allocating those with specific qualifications to disadvantaged schools. Since 2024, the government has paid a salary premium of 20% to teachers working in disadvantaged municipalities or schools with a high share of disadvantaged pupils. This measure is welcome, and its impact on teacher assignments should be evaluated whenever possible. Non-financial incentives such as faster career progression or the free choice of a new assignment after having served in a disadvantaged school could also be used to attract teachers with specific qualifications to those schools.
Beyond teachers themselves, teaching conditions are essential to promote access to higher education for all. For example, empirical evidence consistently shows that smaller class sizes at primary level improve academic performance, the likelihood of accessing higher education and adult learning, especially for students from disadvantaged backgrounds. Given the added tax revenues resulting from the higher income of beneficiaries, simulations for France even show that class splitting in primary education is self-financing in the long term (Fajeau et al., 2025[45]). As the average class size in Hungarian primary schools is above the OECD average (Figure 3.12), class-size reduction could significantly improve educational achievements. To maximise efficiency and limit the burden for public finances in the short term, this policy should target disadvantaged primary schools in priority.
At secondary level, a rising and above-OECD average proportion of Hungarian students is over-aged, which is likely related to frequent grade repetition (Figure 3.13, Panel A). While empirical evidence points to possible positive effects on academic performance in the short term, they are mostly observed at primary level and when grade repetition is combined with other support measures, such as tutoring and smaller class sizes. Nevertheless, grade repetition also comes with heightened risk of early school leaving in the longer term (Jacob and Lefgren, 2009[46]), which is consistent with relatively high out-of-school rates at upper secondary level in Hungary (Panel B), and low follow-on from upper-secondary to tertiary education. Such measures should thus be reserved to exceptional cases.
Tutoring is a more efficient way than grade repetition to help students that are lagging behind. Empirical evidence shows that supplementary instruction provided to individual or small groups of students is an effective way to boost academic performance, especially if it is delivered during school hours in primary education and by people who are closely connected to the education system such as teaching assistants or university students (Nickow, Oreopoulos and Quan, 2020[47]). Integrating the mentoring of younger students into university programmes and granting specific European Credit Transfer System credits may encourage university students to engage in such activity.
Average class size in primary education, 2023
Note: The OECD aggregate refers to the unweighted average of 34 countries.
Source: OECD Education at a Glance (2025[40]).
Note: The OECD aggregate refers to the unweighted average of 33 countries in Panel A and 38 countries in Panel B.
Source: Panel A: OECD Education at a Glance (2025[40]); Panel B: OECD Education at a Glance (2024[48]).
Beyond academic support, career guidance and soft skills are also key, especially for disadvantaged students. Mismatch between career and education expectations is widespread for such students in Hungary. For example, half of the 15-year-old Hungarian students with a disadvantaged social background envisaging to work in managing or professional positions do not expect to attend tertiary education. This mismatch is well above the OECD average. Moreover, social background is a stronger determinant of plans for tertiary education than academic ability. Only half of the best performers in the school system expect to reach tertiary education when they have a low social background, which is one of the lowest proportions in the OECD and even below the tertiary education expectations of low performing students with a higher social background. By comparison, nearly 90% of the high-performing students with a privileged social background expect to complete tertiary education in Hungary. This shows that tutoring should not only be about academic topics but also about career guidance and softer skills such as perseverance and self-esteem, which are critical for learning and matter for long-term professional success, even controlling for academic achievement (Grenet and Landais, 2025[49]). Beyond career conversations, job fair and workplace visits, and volunteer part-time work and internships are especially useful to align career and education expectations. In Hungary, relatively low proportions of 15-year-old students have ever visited a job fair or spoken with a career advisor either in or out of school (OECD, 2025[50]).
Vocational training programmes, in which close to 50% of upper-secondary Hungarian students are enrolled, have a key role to play to foster social mobility. Despite recent progress, the balance between VET qualifications and labour market needs, as well as access from VET to tertiary education could be improved.
All VET programmes for students below 25 in Hungary now combine school- and work-based learning, well above the OECD average of 45% (OECD, 2023[51]). Upper-secondary vocational graduates in Hungary also have a high employment rate (87% in 2024), exceeding that of upper-secondary graduates from the general education system (83%). Nevertheless, only 53% of VET students who graduated in 2022 found a position in a sector corresponding to their qualification (CEDEFOP, 2023[52]). Sectoral Skills Councils (ÁKT), which are business representative bodies created in 2020 to support the continuous development of VET, are now closely involved in the definition of VET curricula and examinations, which is a welcome step, but further progress is needed.
Following recent changes included in Hungary’s VET 4.0 Strategy, all VET programmes now provide pathways to tertiary education. Such pathways exist both for students completing five-year technician programmes who can even transfer some learning credits to higher-education institutions, and for students completing three-year practice-oriented VET programmes provided that they continue general education within the vocational school system and complete a two-year follow-up programme to obtain the baccalaureate (matura). Such pathways should be systematically promoted in student discussions with career advisors.
References
[26] Aksoy, C. et al. (2025), “Working from home in 2025: Five key facts”, Mimeo, https://siepr.stanford.edu/publications/essay/working-home-2025-five-key-facts.
[35] Boza, I. and J. Krekó (2022), “What Happened to Jobseekers After Being Registered?”, The Hungarian Labour Market 2020, https://kti.krtk.hu/wp-content/uploads/2021/06/hlm-2020.pdf.
[6] Breda, T. et al. (2023), “How Effective are Female Role Models in Steering Girls Towards STEM? Evidence from French High Schools”, The Economic Journal, Vol. 133/653, pp. 1773-1809.
[15] Canaan, S. et al. (2022), “Maternity Leave and Paternity Leave: Evidence on the Impact of Legislative Changes in High-Income Countries”, IZA DP No. 15129.
[27] Cappelli, P. and R. Nehmen (2025), “Hybrid Still Isn’t Working”, Harvard Business Review, https://hbr.org/2025/07/hybrid-still-isnt-working.
[31] Cattaneo, A. et al. (2025), “The burden of informal family caregiving in Europe, 2000–2050: a microsimulation modelling study”, The Lancet Regional Health - Europe, Vol. 53, p. 101295.
[52] CEDEFOP (2023), “Vocational education and training in Europe - Hungary: system description”, https://www.cedefop.europa.eu/en/print/pdf/node/157474.
[44] Chetty, R. et al. (2014), “Where is the land of Opportunity? The Geography of Intergenerational Mobility in the United States”, The Quarterly Journal of Economics, Vol. 129/4, pp. 1553-1623.
[16] Ciminelli, G., C. Schwellnus and B. Stadler (2021), “Sticky floors or glass ceilings? The role of human capital, working time flexibility and discrimination in the gender wage gap”, OECD Economics Department Working Papers, No. 1668, OECD Publishing, Paris, https://doi.org/10.1787/02ef3235-en.
[23] Contreras, D. and P. Sepulveda (2017), “Effect of Lengthening the School Day on Mother’s Labor Supply”, The World Bank Economic Review, Vol. 31/3, pp. 747-766, https://doi.org/10.1093/wber/lhw003.
[18] Cools, S., J. Fiva and L. Kirkebøen (2015), “Causal Effects of Paternity Leave on Children and Parents”, The Scandinavian Journal of Economics, Vol. 117/3, pp. 801-828, https://doi.org/10.1111/sjoe.12113.
[11] Csákné Filep, J., Á. Szennay and G. Timár (2024), Opportunities, motivation, environment : Entrepreneurship in Hungary, Budapest Business University, https://doi.org/10.29180/978-615-6342-87-4.
[13] EIGE (2022), Gender-Responsive Public Procurement in the EU, https://eige.europa.eu/gender-mainstreaming/tools-methods/gender-responsive-public-procurement.
[32] EIGE (2019), Gender Equality Index, https://eige.europa.eu/gender-equality-index/2019.
[5] Einiö, E., J. Feng and X. Jaravel (2025), “Social Push and the Direction of Innovation”, Pre-print, https://www.xavierjaravel.com/_files/ugd/bacd2d_cfc4070bdc3647cd9242751a877a014e.pdf.
[34] ERGO Network (2024), Roma Access to Decent and Sustainable Employment in Hungary, https://ergonetwork.org/wp-content/uploads/2024/11/HUNGARY-Roma-access-to-decent-and-sustainable-employment-final.pdf.
[21] Eros, H., M. Smoter and J. Kreko (2022), Young women on the Labour Market in Hungary and Poland, https://www.budapestinstitute.eu/Policy_paper_gender_final_2022.pdf.
[45] Fajeau, M. et al. (2025), “Economic Efficiency of Reducing Class Size”, Focus du Conseil d’Analyse Economique, Vol. 113, https://cae-eco.fr/en/efficacite-economique-de-la-reduction-de-la-taille-des-classes.
[24] Felfe, C., M. Lechner and P. Thiemann (2016), “After-school care and parents’ labor supply”, Labour Economics, Vol. 42, pp. 64-75, https://doi.org/10.1016/j.labeco.2016.06.009.
[2] Fluchtmann, J., M. Keese and W. Adema (2024), “Gender equality and economic growth”, OECD Social, Employment and Migration Working Papers, No. 304, OECD Publishing, Paris, https://doi.org/10.1787/fb0a0a93-en.
[17] Fodor, É. and A. Balogh (2010), “Back to the kitchen? Gender role attitudes in 13 East European countries”, Journal of Family Research, Vol. 22/3, pp. 289-307, https://doi.org/10.20377/jfr-259.
[9] Global Entrepreneurship Monitor (2025), GEM 2024/2025 Global Report, https://gemconsortium.org/report/gem-20242025-global-report-entrepreneurship-reality-check-4.
[7] Gonne, N. and M. Trincão (2024), “Gender mainstreaming in OECD Economic Surveys”, OECD Economics Department Working Papers, No. 1831, OECD Publishing, Paris, https://doi.org/10.1787/4d7041d7-en.
[49] Grenet, J. and C. Landais (2025), “Education: How to Better Target Public Spending”, Les notes du Conseil d’Analyse Economique, Vol. 84, https://cae-eco.fr/en/education-comment-mieux-orienter-la-depense-publique.
[30] Gyarmati, A. (2019), “Ageing and Care for the Elderly in Hungary: General Survey and Problems”, Friedrich Ebert Stiftung, https://library.fes.de/pdf-files/bueros/budapest/15482.pdf.
[43] Hajdu, T. et al. (2024), “Indicator system of public education 2023 [in Hungarian]”, https://kti.krtk.hu/wp-content/uploads/2024/05/Indikatorkotet_2023.pdf.
[42] Havnes, T. and M. Mogstad (2015), “Is universal child care leveling the playing field?”, Journal of Public Economics, Vol. 127, pp. 100-114, https://doi.org/10.1016/j.jpubeco.2014.04.007.
[20] Heckman, J. (2008), “Schools, Skills and Synapses”, Economic Inquiry, Vol. 46/3, pp. 289-324, https://doi.org/10.1111/j.1465-7295.2008.00163.x.
[41] Heckman, J. and D. Masterov (2007), “The Productivity Argument for Investing in Young Children”, Review of Agricultural Economics, Vol. 29/3, pp. 446-493, https://www.jstor.org/stable/4624854.
[39] Hordósy, R. and E. Szanyi (2020), “Moving Through and Moving Away: (Higher) Education Strategies of Hungarian Students”, Intersections: East European Journal of Society and Politics, Vol. 6/4, pp. 34-62, https://doi.org/10.17356/ieejsp.v6i4.600.
[46] Jacob, B. and L. Lefgren (2009), “The Effects of Grade Retention on High-School Completion”, Ameriacn Economic Journal: Applied Economics, Vol. 1/3, pp. 33-58, https://doi.org/10.1257/app.1.3.33.
[14] Köllö, J. (2022), Change in Measuring Employment in 2021, https://kti.krtk.hu/wp-content/uploads/2022/11/MT2020_teljes-kotet.pdf.
[33] Kyriakopoulou, A. (2021), What are the individual consequences of being NEET?, https://www.cedefop.europa.eu/en/tools/neets/blog/what-are-individual-consequences-being-neet.
[3] Mostafa, T. (2019), “Why don’t more girls choose to pursue a science career?”, PISA in Focus, No. 93, OECD Publishing, Paris, https://doi.org/10.1787/02bd2b68-en.
[47] Nickow, A., P. Oreopoulos and V. Quan (2020), The Impressive Effects of Tutoring on PreK-12 Learning, NBER, Cambridge, MA, https://doi.org/10.3386/w27476.
[40] OECD (2025), Education at a Glance 2025: OECD Indicators, OECD Publishing, Paris, https://doi.org/10.1787/1c0d9c79-en.
[37] OECD (2025), Survey of Adult Skills 2023 Technical Report, OECD Skills Studies, OECD Publishing, Paris, https://doi.org/10.1787/80d9f692-en.
[50] OECD (2025), The State of Global Teenage Career Preparation, OECD Publishing, Paris, https://doi.org/10.1787/d5f8e3f2-en.
[4] OECD (2024), Do Adults Have the Skills They Need to Thrive in a Changing World?: Survey of Adult Skills 2023, OECD Skills Studies, OECD Publishing, Paris, https://doi.org/10.1787/b263dc5d-en.
[48] OECD (2024), Education at a Glance 2024: OECD Indicators, OECD Publishing, Paris, https://doi.org/10.1787/c00cad36-en.
[29] OECD (2024), Is Care Affordable for Older People?, OECD Health Policy Studies, OECD Publishing, Paris, https://doi.org/10.1787/450ea778-en.
[36] OECD (2024), OECD Economic Surveys: Hungary 2024, OECD Publishing, Paris, https://doi.org/10.1787/795451e5-en.
[22] OECD (2023), Database on Net Childcare Costs, https://www.oecd.org/en/data/indicators/net-childcare-costs.html.
[10] OECD (2023), Joining Forces for Gender Equality: What is Holding us Back?, OECD Publishing, Paris, https://doi.org/10.1787/67d48024-en.
[51] OECD (2023), Spotlight on Vocational Education and Training: Findings from Education at a Glance 2023, OECD Publishing, Paris, https://doi.org/10.1787/acff263d-en.
[1] OECD (2022), Reducing the Gender Employment Gap in Hungary, Gender Equality at Work, OECD Publishing, Paris, https://doi.org/10.1787/fe5bc945-en.
[12] OECD (2021), “Promoting gender equality through public procurement”, OECD Public Governance Policy Papers, No. 09, OECD Publishing, Paris, https://doi.org/10.1787/5d8f6f76-en.
[8] OECD (2021), The Role of Firms in Wage Inequality: Policy Lessons from a Large Scale Cross-Country Study, OECD Publishing, Paris, https://doi.org/10.1787/7d9b2208-en.
[38] Róbert, P. (2019), “Intergenerational Educational Mobility in European Societies Before and After the Crisis”, TARKI Social Research Institute, pp. 120-136, https://tarki.hu/sites/default/files/2019-02/120_136_Robert.pdf.
[25] Shure, N. (2019), “School Hours and Maternal Labor Supply”, Kyklos, Vol. 72/1, pp. 118-151, https://doi.org/10.1111/kykl.12195.
[19] Szabo, B. et al. (2022), “The Impact of Childcare on Maternal Employment”, Institute of Economics - Centre for Economic and Regional Studies, https://kti.krtk.hu/wp-content/uploads/2022/10/CERSIEWP202220.pdf.
[28] Touzet, C. (2023), “Teleworking through the gender looking glass: Facts and gaps”, OECD Social, Employment and Migration Working Papers, No. 285, OECD Publishing, Paris, https://doi.org/10.1787/8aff1a74-en.