Hybrid Archive - IAB - Institut für Arbeitsmarkt- und Berufsforschung

The Eroding Lifetime Return to Cognitive Skills

We study how lifetime labor-market returns to cognitive and social skills have changed across Swedish birth cohorts. We combine administrative records for cohorts born 1951–1980 with skills measured at military enlistment and follow earnings, employment, and wages from 1985 to 2023. Because complete working lives are not observed for every cohort, we estimate age profiles and predict lifetime outcomes. Social skills are a stronger predictor of labor-market success than cognitive skills, largely through employment, although both skills predict wages. Across cohorts, lifetime returns to cognitive skills decline markedly, while returns to social skills increase. We also compare men and women, using brothers’ skills as proxies for own skills in both groups. Skill returns increased more among women than among men, with the largest relative increase for women’s social skills. The results highlight substantial variation in skill returns by skill type, age, cohort, and gender.

Joint with Erika Forsberg, Peter Fredriksson, Georg Graetz, and Björn Öckert

The Organisational Context of Ethnic Discrimination. Results From a Cross-National Factorial Survey Experiment

The study addresses this gap through a cross-nationally harmonised factorial survey experiment.

While ethnic discrimination in hiring is well documented, little is known about why some organisations – including private companies and public institutions – discriminate more than others. We address this gap through a cross-nationally harmonised factorial survey experiment (FSE) embedded in a comprehensive questionnaire, combining the rigour of experimental design with detailed organisational data.

The survey was conducted among more than 2,000 recruiters evaluating candidates for medium-skilled jobs in four European countries: Germany, Norway, Poland, and Romania. Results show that hiring discrimination is lower in organisations that make hiring decisions collectively, but higher in positions involving frequent customer interaction. Moreover, diversity policy measures implemented within organisations are strongly associated with lower levels of discrimination. Among these, inclusive hiring practices, mentoring or buddy programmes, and support systems for foreign workers appear particularly effective.

The study further demonstrates that the relationship between discrimination and organisational characteristics, such as size and ownership, is largely mediated by the presence of diversity policy measures.
Co-autors: Dominik Buttler, Vegar Bjørnshagen, Marta Palczyńska, Mateusz Smoter

Gender-inclusive language in labour markets

This study leverages a digital field experiment in a labour market setting to examine whether attitudinal effects translate into real-world behaviour.

This study leverages a digital field experiment in a labour market setting to examine whether attitudinal effects translate into real-world behaviour, while offering broader lessons for the design and interpretation of such experiments.

Gender-inclusive language in job descriptions has been shown to impact perceived fit, belonging, and occupational attractiveness, but its impact on actual behaviour remains uncertain. We used a crowdworking platform as an experimental labour market, where sign-up for our advertised study itself serves as an outcome variable. In this setting, we thus tested whether the use of gender-inclusive language in a job advertisement for a maths task increases both the share of women who sign-up and their subsequent performance.

We find no effect of gender-inclusive language on either the share of women or their performance. We provide a look behind the scenes of running a digital field experiment, reflecting on challenges along the way. We used the opportunity to learn about design elements that may have prevented the predicted effect from arising, and the moderating theoretical variables they allude to. One key conjecture that emerged from our assessment is that in tight labour markets, such as the crowdfunding platform we studied, participation is less gendered, with an attenuating effect on gendered performance expectations.

The paper is co-authored with Klarita Gërxhani and Arnout van de Rijt.

Identifying Long-Run Neighborhood Effects via Race-Based Neighborhood Sorting

The study is about children’s adult outcomes are influenced by both their parents’ socioeconomic status (SES) and the SES of the neighborhood.

Children’s adult outcomes are influenced by both their parents’ socioeconomic status (SES) and the SES of the neighborhood where they grew up. We explicitly distinguish between these factors to identify long-run neighborhood effects. We estimate an ordered probit model of neighborhood choice and use it to infer how population shares of parental SES in each neighbor hood vary along both observed and unobserved dimensions. We then regress the average observed outcomes in neighborhoods on these population shares to identify potential outcomes.

Using race based neighborhood sorting as an instrument, we estimate that about half of recent racial inequality in intergenerational mobility is explained by residential segregation.

Joint with Daniel Hartley and Chris Muris

Beyond the Sidelines: Shaping AI Infrastructure with Labor Market Data

This talk argues that as AI systems are deployed into high-risk labor market domains like matching and profiling.

As social scientists, we focus heavily on how AI is changing the labor market. Historically, our discipline has not viewed itself as central to shaping these computational models. This perspective falls short. Both methodologically and substantively, data-producing institutions like the IAB have an urgent opportunity and responsibility, to actively intervene in AI development.

Generative AI pipelines are currently saturated with unscientific behavioral measurements. AI agents routinely deploy unstandardized, fixed-choice questions generated by the models themselves, while Reinforcement Learning from Human Feedback (RLHF) relies on non-probability annotator pools that introduce systemic selection bias. The fundamental machine learning challenge - determining whose values and life circumstances a model represents - is, at its core, a target-population estimation problem. Social science possesses the exact estimation machinery required to diagnose and repair these data structures.

This talk argues that as AI systems are deployed into high-risk labor market domains like matching and profiling, compliance with the EU AI Act demands rigorous auditability. This regulatory shift creates an immediate mandate for the methodologies we produce. In this presentation, we will map how labor market data can directly shape AI pipelines through representative benchmarks, validated instruments, and advanced error diagnosis - including adapting record-linkage traditions to measure what models get wrong about specific demographic groups. Furthermore, we will explore how sampling theory and classic survey methodology can govern the ways AI agents ask questions.

At the UN level, AI readiness for data collected by official institutions has become a central theme. I hope to discuss this element and its broader institutional implications following the presentation.

Interlinked Transitions: Partnership Formation and Labour Market Entry among Young Male Refugees in Germany

This talk examines the interplay between partnership formation and labour market integration among Syrian and Afghan male refugees.

While research on refugees’ labour market integration is flourishing, research on partnership formation among forcibly displaced individuals in receiving countries remains fragmented. Yet for young refugees, partnership formation and labour market entry are key transitions to adulthood that often unfold under heightened uncertainty, including precarious legal status, limited transferability of skills, and restricted pools of co-ethnic partners. Understanding how these transitions interrelate is therefore central to research on refugee integration.

This talk examines the interplay between partnership formation and labour market integration among Syrian and Afghan male refugees who arrived in Germany during the 2015/16 refugee migration. Recent research by Bauer and Kogan (2006) shows that these refugees are more likely to be married than most other resident minority groups in Germany. Their marital partners are predominantly co-national, whereas German partners are relatively more common in non-marital unions. We ask how partnership trajectories are related to labour market trajectories and, in particular, whether earlier labour market integration predicts subsequent partnership outcomes and vice versa.

We use two waves of the PARFORM (Partnership Formation in the Context of Recent Refugee Migration) panel study, covering male Syrian and Afghan refugees aged 21–35 in 2022–2024 who arrived in Germany during the 2015/16 influx. Labour market integration is measured by employment status and occupational status (professional, managerial, or technical versus other occupations). Partnership outcomes capture whether respondents have a partner and, among partnered respondents, whether their female partner is German without a migration background or co-national. We examine reciprocal prospective associations between labour market and partnership outcomes using two-wave cross-lagged structural equation models.

Preliminary results indicate that employment at Wave 1 is associated with a higher likelihood of being partnered at Wave 2. Lower occupational status at Wave 1 is also associated with a slightly lower likelihood of having a German-origin partner at Wave 2. In the reverse direction, being partnered at Wave 1 is not associated with subsequent employment but is positively associated with higher occupational status at Wave 2. These findings point to an asymmetric relationship between the two transitions: labour market integration appears to precede partnership formation, whereas partnership formation is related to subsequent occupational advancement rather than employment itself.

Joint workwith Jana Kuhlemann.

Is Remote Work Attractive for Women Living in Peripheral Areas? A Survey-Based Experiment in Six EU Countries

This study is the first to explore the extent of job offers with remote work options.

Promoting remote work among women living in peripheral areas is a potential tool to limit gender and geographical imbalances in the labour market. This study is the first to explore the extent to which women living in peripheral municipalities (compared with those from metropolitan ones) are attracted to job offers with remote work options.

The study is based on a CAWI survey with a conjoint experiment conducted in Spring 2026 among 3,785 prime-aged women living in France, Italy, the Netherlands, Poland, Romania, and Sweden.

The initial results indicate that, on average, fully remote work (compared to fully on-site work) increases the probability of accepting a job offer to the same degree in both metropolises and peripheral municipalities, by around 14 percentage points. What is relevant, remote work remains attractive for peripheral respondents with lower than higher education, as well as for those with poor digital skills.

Employment Protection, Worker Mobility, and Endogenous Growth

This study characterizes optimal labor-market policy in a multi-sector economy.

This study characterizes optimal labor-market policy in a multi-sector economy that joins endogenous growth, frictional worker reallocation, and human-capital accumulation on an input–output network.

Our growth engine is portable human capital: within-match training lifts the economy’s growth frontier, but because trained skill is carried into unemployment and priced in the worker’s outside option, it compresses the bilateral surplus that funds job creation. In contrast to productivity differences across sectors differences in growth potential push labor out of the higher-growth sector. The model speaks at once to the human-capital and diffusion theory of growth and the recent growth-through reallocation literature. To correct for worker-stealing and incumbent-match externalities - similar to those in Fukui and Mukoyama, 2025 in a growth context - the social planner needs to use a complex system of hiring, firing, training, on the-job search, unemployed switching, and schooling taxes/subsidies that we characterize.

We find that if on-the-job search merely reshuffles workers the planner subsidizes separations and taxes hiring; when mobility instead builds portable skill, the prescriptions reverse. The framework delivers a unified, network-aware account of when worker mobility is socially valuable and how employment-protection policy might respond in a theory of second best.