IAB-Colloquium (en) Archive - IAB - Institut für Arbeitsmarkt- und Berufsforschung

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.

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.

Breaking Barriers or Reinforcing Inequalities? The Impact of Affordable Childcare on Entrepreneurship

This study exploits exogenous variation in the pricing of childcare caused by a nationwide reform.

We exploit exogenous variation in the pricing of childcare caused by a nationwide reform to estimate the impact of lower childcare costs and the propensity of individuals to start a firm. The reform capped the childcare prices, whereas the exogenous variation in the reduction of childcare prices comes from the pre-reform prices, which depended on the place of residence and family type. Decreasing the cost of childcare lowers both the capital and time constraint, which can lead to individuals becoming entrepreneurs.

We evaluate such potential mechanisms both for males and females separately in a difference-in-difference setting up to 5 years post reform. We find that reducing childcare costs increases entrepreneurial activity for both mothers and fathers.

Trade Integration, Import Competition, and Optimal Unemployment Insurance

This paper investigates the optimal design and implementation of labor market institutions within an open economy framework.

This paper investigates the optimal design and implementation of labor market institutions within an open economy framework. We develop a Heterogeneous Agent New Keynesian (HANK) DSGE model featuring search and matching frictions to analyze the interaction between labor market flexibility and international trade, with a specific focus on the German experience. Our findings suggest that labor market institutions, when analyzed in isolation, have a marginal impact on aggregate unemployment and welfare. However, their efficacy is significantly amplified when an economy is exposed to international trade.

We show that while import competition exerts upward pressure on unemployment in the short run, more flexible labor market institutions are essential for maximizing welfare in the long run. Crucially, we study the optimal policy sequence and find that a stepwise, sequential implementation of reforms is superior to a "big bang" approach. Such a trajectory maximizes aggregate welfare over a longer time horizon by effectively shielding heterogeneous agents from the regressive distributive effects of globalization shocks during the transition phase. Our results provide a normative rationale for gradualism in structural reform agendas within integrated economies.

Joint work with Andreas Hauptmann (IAB) and Benjamin Schwanebeck (FernUniversität in Hagen).

Spatial income inequality in Germany, 1957-2021

This study is about income inequality between and within German regions from 1957 to 2021 using a newly collected panel.

We analyze income inequality between and within German regions from 1957 to 2021 using a newly collected panel. We confirm previous evidence on convergence between regions during the decades after World War II, but do not find pronounced regional divergence since the 1990s - in contrast to some earlier studies.

Instead, the national income inequality rise since the 1980s is closely tracked by the near-unanimous rise in income concentration within regions, driven by overproportional labor income growth of the top income decile. Regression analysis suggests that regional growth switched from equality-enhancing to inequality-increasing in the 1990s.