Inequalities in school-to-work transitions

Report: Inequalities in school-to-work transitions Jan Paul Heisig WZB – Berlin Social Science Center Freie Universität Berlin Carla Hornberg WZB – Berlin Social Science Center Christian König WZB – Berlin Social Science Center Heike Solga WZB – Berlin Social Science Center Freie Universität Berlin Kadri Täht Tallinn University Marge Unt Tallinn University December 2025 Mapineq deliverable D4.4 Report: Inequalities in school-to-work transitions 2 Mapineq – Mapping inequalities through the life course– is a three-year project (20222025) that studies the trends and drivers of intergenerational, educational, labour market, and health inequalities over the life course during the last decades. The research is run by a consortium of eight partners: University of Turku, University of Groningen, National Distance Education University, WZB Berlin Social Science Center, Stockholm University, Tallinn University, Population Europe, and University of Oxford Website: www.mapineq.eu The Mapineq project has received funding from the European Union’s Horizon Europe research and innovation programme under the grant agreement No. 101061645. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union, the European Research Executive Agency, or their affiliated institutions. Neither the European Union nor the granting authority can be held responsible for them. Acknowledgement: The content of the document, including opinions expressed and any remaining errors, is the responsibility of the authors. Publication information: This work is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) license. You are free to share and adapt the material if you include proper attribution (see suggested citation), indicate if changes were made, and do not use or adapt the material in any way that suggests the licensor endorses you or your use. You may not use the material for commercial purposes. Summary history Version Date Comments 1.0 15.12.2025 Manuscript for review 1.1 22.12.2025 Manuscript reviewed for submission Suggested citation: Heisig, J.P., Hornberg, C., König, C., Solga, H., Täht, K., & Unt, M. (2025). Inequalities in school-to-work transitions. Mapineq deliverables. Turku: INVEST Research Flagship Centre / University of Turku. DOI: 10.5281/zenodo.18014306 Report: Inequalities in school-to-work transitions 3 Executive summary Successful school-to-work transitions (STWTs) are critical for long-term career success and affect other domains of adulthood, such as starting a family and living independently. This report presents findings on the complex dynamics of STWTs across European regions, highlighting key patterns and sources of inequalities that shape the labor market integration of young adults. The report documents significant regional variations in youth unemployment rates, both within and between countries. It provides several insights into the sources and consequences of these variations: − Differences in young adults’ family composition and health status explain a substantial part of the variation in labor market integration between countries. − Differences in educational attainment and place of residence (rural/urban) among young adults account for a substantial part of the variation in labor market integration between regions within countries. − Regional differences in unemployment rates at labor market entry are associated higher risks of nonemployment and low-skilled employment of young adults with only secondary education 5 to 10 years later. − Poor labor market conditions at entry have spillover effects on transitions into adulthood. Specifically, higher regional unemployment rates at entry increase the likelihood of motherhood, particularly of having at least two children, among women with only lower secondary education. The opposite is true for tertiary-educated women: Higher regional unemployment rates decrease their likelihood of motherhood, as well as they delay moving out of their parents' home and living with a partner. Moreover, a comparative analysis of Estonia and Germany suggests that housing costs are an important factor for young adults who do not live in university cities when deciding whether to attend university in either country (small or large), while distance seems to matter only in the larger country, despite the decentralized distribution of universities across Germany. In summary, the findings presented in the report suggest that inclusive and successful transitions can be promoted through coordinated policy interventions implemented across multiple policy areas, including not only education and labor market policies, but also health, family, social, and housing policies. These interventions would address structural economic factors, individual vulnerabilities, and spatial inequalities. In doing so, they would expand equitable opportunities for youth and strengthen social cohesion and longterm economic resilience in Europe. Report: Inequalities in school-to-work transitions 4 Abbreviations ALMP public spending on active labor market policies EPL employment protection legislation EU-SILC European Union Statistics on Income and Living Conditions Survey ISCO International Classification of Occupations ISEI International Socio-Economic Index NEET Not in employment, education or training NUTS Nomenclature of Territorial Units for Statistics PLMP public spending on passive labor market policies STWT School-to-work transition Report: Inequalities in school-to-work transitions 5 Content EXECUTIVE SUMMARY 3 ABBREVIATIONS 4 1. INTRODUCTION 6 2. LABOR MARKET INTEGRATION OF YOUNG ADULTS: PATTERNS AND PREDICTORS OF BETWEENAND WITHIN-COUNTRY VARIATIONS 7 3. THE IMPACT OF POOR MACROECONOMIC CONDITIONS AT LABOR MARKET ENTRY ON YOUNG ADULTS’ EMPLOYMENT OUTCOMES 5 TO 10 YEARS LATER 10 4. SPILL-OVER EFFECTS ON TRANSITIONS INTO ADULTHOOD 12 5. SOCIAL INEQUALITIES AT THE TRANSITION INTO TERTIARY EDUCATION: SOCIO-SPATIAL DETERMINANTS OF YOUNG ADULTS’ STUDY DECISIONS 13 6. CONCLUSIONS 16 7. REFERENCES 17 Tables TABLE 1. IMPORTANCE OF COMPOSITIONAL DIFFERENCES IN SOCIO-DEMOGRAPHIC AND SOCIO-ECONOMIC CHARACTERISTICS FOR BETWEENAND WITHIN-COUNTRY VARIATION IN LABOR MARKET INTEGRATION (DECOMPOSITION RESULTS) __________ 9 TABLE 2: REGRESSION RESULTS ON THE INFLUENCE OF INDIVIDUAL AND SPATIAL-CONTEXTUAL FACTORS ON YOUNG ADULTS’ TRANSITION TO UNIVERSITY IN ESTONIA AND GERMANY ____________________________________________ 15 Figures FIGURE 1. REGIONAL VARIATION IN UNEMPLOYMENT RATES BETWEEN AND WITHIN COUNTRIES, 2021 _________________ 7 FIGURE 2: LABOR MARKET CONSEQUENCES (NONEMPLOYMENT AND LOW-SKILLED EMPLOYMENT) OF HIGH REGIONAL UNEMPLOYMENT AT ENTRY BY GENDER AND EDUCATION ___________________________________________ 11 FIGURE 3: SPATIAL DISTRIBUTION OF RENTAL PRICES AND UNIVERSITY LOCATIONS IN ESTONIA AND GERMANY ___________ 14 Report: Inequalities in school-to-work transitions 6 Report: This report summarizes the results of various analyses of labor market integration—in terms of employment, NEET (not in employment, education or training), and occupational position—among young adults in different European countries and regions. The findings demonstrate the impact of regional differences. A substantial proportion of the variation in young adults’ labor market integration, both across and within countries, is attributable to differences in the socio-demographic and socio-economic composition of the young adult population (aged 16 to 34). Furthermore, higher unemployment rates at labor market entry have midto long-term consequences, though the degree of vulnerability varies by gender and education level. Cross-country variation in young adults’ labor market integration is mainly driven by differences in family composition and health. Regional variation within countries is driven by educational composition and whether young adults live in urban or rural areas. Poor labor market conditions at entry are related to poorer labor market attainment 5 to 10 years later, especially for individuals with only lower secondary education than for those with more education. Spillovers: Poor labor market entry conditions are associated with higher motherhood rates among less-educated women. In contrast, poor initial conditions delay childbirth and leaving the parents’ home for tertiary-educated women. ________ ________ ________ 1. Introduction School-to-work transitions (STWTs) are a crucial phase in the lives of young adults, that significantly impact their future career trajectories and broader life courses. Successfully entering the labor market, especially into stable and rewarding employment, is essential for achieving economic independence. Furthermore, early labor market experiences influence other significant aspects of adulthood, including family formation and residential autonomy. Therefore, understanding the factors that facilitate or hinder successful STWTs is important. There is a broad consensus across Europe on the importance of facilitating smooth and equitable STWTs. However, despite this shared understanding, considerable disparities exist within and between countries regarding the labor market integration of young adults. These disparities are likely to be shaped by various factors, including regional differences in the socio-demographic and socio-economic composition of young adults; for example, in terms of their education, health, family composition, migration background, and the urbanization level of their place of residence. Moreover, initial employment conditions can have longer-lasting effects on career development and occupational attainment. Report: Inequalities in school-to-work transitions 7 This paper synthesizes insights from several analyses on the patterns and predictors of young adults’ labor market integration across European countries and regions. It explores factors associated with country and regional differences in STWTs (Section 2) as well as the longer-term effects of macroeconomic conditions at labor market entry on employment trajectories (Section 3) and other features of the transition into adulthood, including the likelihood of having children and leaving the parental home (Section 4). Additionally, it examines social inequalities affecting transitions into tertiary education in Estonia and Germany, highlighting socio-spatial determinants, such as distance to universities and housing market conditions, that influence young people’s decisions about whether and where to study (Section 5). By providing a broad picture of regional and socio-economic disparities in STWTs, this report contributes to a better understanding of the unequal opportunities for young adults across Europe. 2. Labor market integration of young adults: Patterns and predictors of betweenand withincountry variations 1 In all 27 European countries analyzed here, the unemployment rate of young adults (aged 16 to 34) exceeds the rate for the overall working population. Many countries and regions also have high proportions of young adults in NEET status. Yet, our analysis also reveals substantial disparities in young people’s labor market integration, both between and within European countries. Figure 1 illustrates the extent of regional variation in unemployment rates, both between and within countries. Figure 1. Regional variation in unemployment rates between and within countries, 2021 Notes: Weighted results. Left: between countries, right: between regions. Autonomous regions of Portugal (Azores and Madeira) and Spain (Canary Islands) are not shown for better readability. Source: EU-SILC 2021, authors’ calculations. 1 This section summarizes selected results published in Hornberg, Heisig, and Solga (2024). Report: Inequalities in school-to-work transitions 8 For example, Luxembourg, Malta, and Switzerland perform quite well in facilitating the employment of young adults, whereas countries such as Italy, Serbia, and Greece have high youth unemployment and NEET rates. Furthermore, an analysis of the occupational status achieved by young adults (measured by ISEI scores, a commonly used indicator) shows that higher employment rates do not necessarily come at the expense of job quality. That is, countries with low levels of youth unemployment also tend to have a high proportion of young people in higher-status occupations. Conversely, employed young adults in high-unemployment countries tend to have lower average ISEI scores. Moreover, considerable variation exists within countries, particularly in Southern Europe. Regions in Italy, Spain, and Portugal, for instance, exhibit significant disparities in labor market integration. Predictors of labor market success Country-specific analyses of the associations between three labor market integration indicators (unemployment, NEET status, and occupational status) and a set of individual characteristics (see Box 1 below) reveal consistent patterns across the 27 European countries included in the study: − Educational attainment is a key predictor of successful labor market integration. − Health status (often neglected in STWT research) is the strongest predictor of NEET status: Young adults in poor health face the highest risk of being NEET. − Family composition is strongly associated with labor market integration. Having children, whether in a cohabiting or single-parent household, is a major predictor of NEET risk. Additionally, unemployment and NEET are more prevalent among young adults living with their parents than among those in childless partnerships. However, the direction of causality remains unclear, with results presented in Section 4 suggesting that poor labor market conditions shape these family-related outcomes rather than the other way around. − Place of residence is also an important predictor of labor market success. Rural residents tend to have lower occupational status because high-status occupations tend to be concentrated in urban centers. Explanations for regional variation in STWT outcomes The socio-economic and socio-demographic composition of the youth population varies considerably between countries and NUTS 1 regions. For example, some countries have a lower average health status among young adults than others. These differences in composition may help explain variations in labor market integration between and within countries. Shapley decompositions (see Box 1 below) show that a substantial proportion of the variation across and within country in young adults’ labor market outcomes is indeed attributable to compositional differences. Table 1 summarizes the relative importance of various characteristics of young adults in explaining betweenand within-country variation in labor market integration. Compositional differences in family composition (including whether young adults still live with their parents) and, to a lesser extent, (self-rated) health are the strongest predictors of cross-national variation in labor market integration. In contrast, regional variation within countries is primarily related to differences in educational composition. In the case of occupational status (ISEI), it is also related to the Report: Inequalities in school-to-work transitions 9 share of young adults living in cities or rural areas (place of residence/urbanization). These regional findings underscore the spatial dimension of labor market inequality. Table 1. Importance of compositional differences in socio-demographic and socioeconomic characteristics for betweenand within-country variation in labor market integration (decomposition results) Unemployment NEET ISEI Characteristics Country Region (NUTS1) Country Region (NUTS1) Country Region (NUTS1) Educational attainment +++ + +++ + +++ Health status ++ ++ Family composition +++ + +++ + ++ ++ Gender + Age + + + ++ Migration background + + Place of residence + +++ Notes: Symbols indicate how strongly a given set of characteristics (predictors) contributes to betweencountry or within-country regional variation according to Shapley decompositions of the corresponding explained variance measures from a multilevel model (see Box 1). +++ strong (R²-portion ≥ 0.2), ++ moderate (R²-portion ≥ 0.1), + weak association (R²-portion ≥ 0.05); empty = negligible or no association. Source: EU-SILC 2021, authors’ calculations. Further analysis suggests that some of the observed regional variations in young adults’ labor market integration reflect broader macroeconomic conditions. For instance, higher overall unemployment rates are associated with poorer labor market integration among young adults at both the country and regional (NUTS1) levels. While these findings are purely associative, the next section provides additional insights suggesting that these relationships are at least partly causal. Box 1: Data and methods for Section 2 The analyses are based on individual-level data from the 2021 wave of the European Union Statistics on Income and Living Conditions (EU-SILC). The analyses include 27 European countries and, for 14 of them, also the major socio-economic regions (NUTS 1 level). Small countries, such as Estonia and Luxembourg, are not subdivided further into NUTS 1. The focus is on young adults aged 16 to 34. Labor market integration is defined in terms of unemployment, NEET status, and occupational status (measured by ISEI scores). The role of differences in the socio-demographic and socioeconomic composition of the youth population for disparities in labor market success is estimated based on country-specific regressions. To assess their role for cross-country and regional variation in young adults’ labor market outcomes, we employ Shapley decompositions of the explained variance (R²) measures from a multilevel model. Decompositions of the between-country R² values are derived from two-level models for 27 countries, while those for the between-region (NUTS 1) R² are based on three-level models for 75 regions in 14 countries. See Hornberg, Heisig, and Solga (2024) for further details. Report: Inequalities in school-to-work transitions 16 costs in the nearest university city are negatively related to university transition rates within two years of graduation (Table 2, column 5). However, this seems to vary by parental education: Children of non-academic parents tend to be less likely to transition to a university city if they live farther away, whereas children of tertiary-educated parents seem to be unaffected (indicated by the sizeable interaction effect between parental education and distance, in Table 2, column 6; however only significant at the 10 % level). In sum, this comparative analysis suggests that housing costs are an important factor for young adults who do not live in university cities when deciding whether to attend university in either country (small or large), while distance seems to apply only to the larger country, despite the decentralized distribution of universities across Germany. 6. Conclusions This report presented key findings on young adults’ STWTs across Europe. The results demonstrate that macroeconomic conditions, as well as regional and national differences in socio-demographic compositions, substantially contribute to disparities in youth labor market integration. High regional unemployment at labor market entry not only reduces immediate employment prospects but also leads to long-lasting negative effects, Box 3: Data and methods for Section 5 Estonia: Linked administrative data. Primary source is the Estonian Education Information System (EHIS), which provides longitudinal information on educational trajectories for all graduates with a university entry qualification between 2014 and 2022. Administrative data was supplemented with municipal rental price statistics (2014-2022) from KV.ee, an online platform for housing ads, and geolocation data to calculate distances between municipalities. Germany: Survey data from the German National Educational Panel Study (NEPS) on a cohort of 9th graders including 3,471 young adults graduating from high school with a university entrance qualification between 2013 and 2016, linked with municipality-level rental price data from the Leibniz Institute for Economic Research (based on the online platform Immoscout24) and public university locations from the German Rectors’ Conference. Measures Dependent variable: Transition to university (equal to 1 if individuals attend university within 2 years of high school graduation, equal to 0 otherwise); covariates: Parental education (equal to 1 if at least one tertiary-educated parent, equal to 0 otherwise); residence in university city during high school (yes/no); distance to nearest university city; rents: median rental price at nearest university city for Germany and difference in mean rental price between Tallinn and municipality of origin for Estonia; control variable: high school GPA (available only for Germany). Separate analyses by country 1. Linear Probability Models (LPM) regressing transition to university on the individual-level covariates parental education, residence in a university city during high school, and GPA (Germany only) among all holders of a university entrance qualification. The aim is to assess whether living in a university city privileges attending university. 2. LPM regressing transition to university restricted to young adults who did not live in university cities during high school. These models include parental education, their distance to the nearest university, and a country-specific measure of rental prices. These regressions aim to assess the importance of distance and rents for tertiary education decisions (models without interaction terms) and potential differences by parental education (models with interaction terms). Report: Inequalities in school-to-work transitions 17 particularly for young adults with lower levels of education. In light of these insights, policymakers should consider multifaceted strategies to improve young people’s integration into the labor market and reduce subsequent inequalities. First, tackling regional economic disparities is essential. Investing in job creation and economic development in regions with high unemployment can improve employment opportunities for young adults entering the labor market. Regional support measures should also aim to improve young adults’ educational attainment and health status. Second, targeted support is necessary for vulnerable groups that are disproportionately affected by adverse economic conditions. This includes young adults, especially young women, with lower educational qualifications. Third, improving equitable access to tertiary education requires addressing socio-spatial barriers. Policies could include expanding higher education opportunities in underserved regions, providing financial support to offset housing and living costs, and improving transportation infrastructure to reduce access challenges. Finally, coordinated efforts are needed to mitigate the impact of labor market disadvantages on the transition into adulthood more broadly, such as independent living and family formation. Integrative approaches linking education, employment, and social policies―including measures to improve housing affordability―are crucial to supporting young adults’ comprehensive development. In summary, fostering inclusive and successful transitions from school to work requires coordinated policy interventions across various policy areas, including not only education and labor market policies but also health, family, social and housing policies. Concerted efforts to address structural economic factors, individual vulnerabilities, and spatial inequalities can provide more equitable opportunities for European youth, thereby enhancing social cohesion and long-term economic resilience. 7. References Arulampalam, W., Gregg, P., and Gregory, M. (2001) ‘Unemployment Scarring’, The Economic Journal, 111(475), pp. F577–F584. Available at: https://doi.org/10.1111/1468-0297.00663. Currie, J. and Schwandt, H. (2014) ‘Shortand long-term effects of unemployment on fertility’, Proceedings of the National Academy of Sciences, 111(41), pp. 14734–14739. Available at: https://doi.org/10.1073/pnas.1408975111. Hornberg, C., Heisig, J. P., and Solga, H. (2024). Decomposition of between and withincountry (regional) differences in the labour market attainment of young adults. Mapineq deliverables. Turku: INVEST Research Flagship Centre/University of Turku. Available at: https://zenodo.org/records/13364399. König, C., Biegert, T., Heisig, J. P., and Solga, H. (2025a). Cross-national analysis of the short-and longer-term effects of conditions at labor market entry. Mapineq deliverables. Turku: INVEST Research Flagship Centre/University of Turku. Available at: https://zenodo.org/records/15349521. König, C., Biegert, T., Heisig, J. P., and Solga, H. (2025b). Explorative analysis of the shortand longer-term effects of economic conditions at labor market entry on leaving the parental home and family formation Mapineq deliverables. Turku: Report: Inequalities in school-to-work transitions 18 INVEST Research Flagship Centre/University of Turku. Available at: https://zenodo.org/records/15585190. Acknowledgement: The report uses data from the National Educational Panel Study (NEPS). From 2008 to 2013, NEPS data was collected as part of the Framework Program for the Promotion of Empirical Educational Research funded by the German Federal Ministry of Education and Research (BMBF). As of 2014, NEPS is carried out by the Leibniz Institute for Educational Trajectories (LIfBi) in cooperation with a nationwide network.