Current projects
Current projects
with Sebastian Bähr (IAB)
Revise & Resubmit at American Journal of Sociology
While the fundamental link between place and inequality is well investigated, causal studies on neighborhood effects are limited. Using nationwide administrative data from Germany and a quasi-experimental identification approach, we investigate how employed network ties and role models in the residential neighborhood shape individual-level employment. In exploiting variation over time, within cities and between 1x1 kilometer grid cells, we provide a causal estimate of gendered neighborhood employment effects on refugee women's employment probability. Results support direct job referral effects of full-time employed female neighbors, which is most potent for other neighborhood women from refugee countries. Analyses of locally prevalent female work norms show a positive one-off effect of higher part-time employment shares of native neighbors indicating that neighbors serve as role models only before other structures are settled. In analyzing neighborhood effects by sex and nationality, our study reveals that even weak neighborhood ties can provide valuable resources for disadvantaged social groups in the labor market. Hence, the study stresses the necessity to break down dichotomies such as gender and ethnicity when not only explaining but also finding alternative pathways for circumventing combined hurdles of intersectionality.
Preprint here: SocArXiv Papers | Empowering through proximity: How female neighbors serve as network ties and role models for refugee women
with Leonard Wendering and Nan Zhang (both University of Mannheim)
Under Review
Scholars posit that childhood exposure to ethnic outgroups may durably improve intergroup relations. To date, however, few studies are able to track the consequences of childhood experiences across multiple decades. Moreover, existing research focuses overwhelming on majority populations and largely overlooks the consequences of exposure for minority groups. Using linked geocoded US census records from 1880 to 1900/1910, we analyze the impact of having childhood neighbors of a different ethnicity on subsequent marriage patterns for over 400,000 American, German and Irish men. To account for residential self-selection, we apply a machine-learning algorithm to identify historic ``ethnic" neighborhoods and compare individuals similar on sociodemographic and neighborhood characteristics, but who differ in the identity of their next-door neighbors. We consistently find that exposure to an ethnic outgroup in 1880 increases the likelihood of marriage to a member of that group in later life, while decreasing the likelihood of endogamous marriages. Overall, these findings underscore the potential for childhood experiences to erode ethnic group boundaries.
Preprint here: https://osf.io/preprints/socarxiv/t9w5p_v1
with Marie-Fleur Philipp (University Tübingen) and Eileen Peters (WSI)
Under Review
Individuals’ beliefs regarding maternal employment are central to the reproduction of gender inequalities in paid and unpaid work. While prior research has linked gender beliefs to personal characteristics and national policies, the influence of local contexts remains underexplored. Drawing on the perspective of gender as a social structure framework and social norm theory, we conceptualize neighborhoods as socio-cultural reference frames where local norms reflect and reinforce normative gender beliefs. Combining the German Panel Study 'Labour Market and Social Security' (2011/2016) with georeferenced administrative data on 1x1km grid cells, we investigate how neighborhood-level female employment patterns shape normative beliefs about maternal full-time employment in Germany. Support for a later maternal return to full-time employment is greater in neighborhoods with higher shares of marginal female employment and where traditional employment forms dominate, even after controlling for the socio-economic composition of surrounding grid cells. In contrast, higher local shares and dominance of female full-time employment among women are associated with greater support for an earlier maternal return to full-time employment. These associations are most pronounced among parents, for whom gender norms around maternal employment are most salient. The findings highlight the role of the neighborhood level for the everyday reproduction of gender inequalities.
Preprint here: https://osf.io/preprints/socarxiv/zemwh_v1
with Philipp Jaschke (IAB), Jonas Wiedner (WZB), Tae Kyeong Meixner-Yun (WZB), Yuliya Kosyakova (IAB) and Christian Hunkler (DIW)
Socio-spatial segregation among refugees carries significant consequences for socio-economic attainment, yet observational data cannot determine whether settlement patterns reflect residential preferences, structural constraints, or their interaction. This study provides the first experimental evidence on the neighborhood preferences of refugees in Europe. Drawing on Nee and Alba's neo-assimilation theory, we test whether immigrants' preferences evolve endogenously: as integration success opens access to mainstream resources, refugees should increasingly favor majority-oriented neighborhoods, whereas those facing disadvantage should value co-ethnic resources that require no mainstream credentials. We embed a conjoint experiment in the Socio-economic Panel (SOEP), presenting respondents with migration or refugee background hypothetical neighborhoods that vary along eight attributes spanning language, kinship proximity, schooling, local institutions, labor-market access, and resident origin. Critically, this design links experimentally elicited preferences to up to individual biographical and geocoded residential histories, allowing us to connect current preferences to prior integration experiences, residence-permit timing, and exposure to discrimination. Fielded in January 2026 with approximately 3,000 respondents completing seven choice tasks, the study clarifies how far segregation mirrors refugees' own preferences, quantifies how earlier structural constraints shape later desires, and offers a direct test of a central assimilation mechanism with implications for dispersal policy.
Preregistration here: https://osf.io/4q3t7/overview
with Leonard Wendering and Nan Zhang (both University of Mannheim)
Known as the “second generation advantage” or “immigrant paradox”, children from immigrant families often show more education and higher wages than their counterparts with native-born parents. In combining theories about occupational mobility and neighborhood literature, this project investigates early childhood contact with native neighbors as one factor in explaining occupational upward mobility in adulthood among immigrant children. Going beyond the focus on minorities, the paper also provides a joint analysis of minority-majority dynamics in investigating the role of contact to immigrant neighbors. The study is set at the turn of the 20th century, leveraging the 1880 US Census with more than 50 million individuals from 40 cities. We focus on a georeferenced subset of underaged boys that can be linked to their adult entries in 1910. We operationalize childhood exposure to other ethnic groups using the ordering of households within census enumeration sheets, informative down to the next-door households. Using coarsened exact matching and a fixed-neighborhoods estimation technique, we ask whether intergroup contact increases the likelihood of choosing a profession typical of that ethnicity in adulthood. We find that childhood exposure to natives facilitates occupational mobility into higher-status jobs for minorities, rather than shifting preferences between jobs of equal status. For boys from the majority, we find a significant change in occupational preferences not linked to changes in social status. Minority-minority dyads show smaller effects and are unaffected by restriction on horizontal moves. The findings suggest that interethnic neighborhood encounters can act both as a source of cultural adaptation and socioeconomic advancement.
with Nina Gläser (IAB, University Bamberg)
Income inequality and residential segregation have intensified across major German cities, contributing to growing urban divides and reinforcing spatial patterns of social inequality. While gentrification research widely acknowledges the pivotal role of high-status individuals in transforming low-income neighborhoods, identifying their causal impact remains difficult due to strong self-selection and feedback dynamics. We address this challenge by exploiting the well-documented phenomenon that artists, who systematically sort into low-rent, low-income neighborhoods but do not themselves raise local income levels, serve as pioneers whose presence increases the area’s cultural capital and attracts high-status in-movers over time. Using fine-grained georeferenced administrative panel data (500m² grids) covering nearly half a million neighborhood-year observations across 80 German cities (2001–2017), we construct a dynamic measure of gentrification based on city-specific changes in income and education. We leverage lagged inflows of artists as an instrument for the inflow of high-status residents and estimate a two-stage least squares model with rich controls and city-by-year fixed effects. Our results show that a one percent increase in the inflowing status of residents raises the probability of gentrification within three years by up to 8.16 percentage points in Germany’s top eight cities (top seven plus Leipzig). Effects for other cities with more than 100.000 inhabitants are positive but smaller, consistent with weaker amenity-driven sorting patterns outside the top cities. Complementary analyses use georeferenced rent-level data (RWI-GEO-RED) to further show that artist-induced inflows of high-status individuals explain rising median rent levels only for the top eight cities. By isolating the causal role of early high-status in-movers, our study advances understanding of the mechanisms accelerating early neighborhood gentrification and contributes to broader debates on how urban residential dynamics reproduce social inequality.
with Alexander Patzina (University Bamberg) and Katy Morris (SOFI)
This study examines the local and social factors influencing apprenticeship dropout decisions and their long-term labor market consequences in Germany. Using individual-level administrative data from the Federal Employment Agency (N=476,605), we investigate how local labor market conditions impact dropout probabilities and accumulated income ten years after termination of education and evaluate whether these associations are socially stratified. We first replicate existing literature by showing that apprenticeship dropout is more common in areas with low unemployment and many vacancies regardless of social background. While individuals from disadvantaged backgrounds drop out more often, the difference to more advantaged individuas remains stable for varying local economic conditions. Conversely, the findings on the consequences of dropping out of vocational training in initially good local labor markets suggest a high-risk, high-reward trade-off: dropouts earn less than graduates when local economies deteriorate, but may earn more than graduates f the local economy continues to improve. Furthermore, income trajectories of individuals from disadvantaged backgrounds appear more sensitive to local conditions. These findings highlight the complex interaction between local labor market conditions and social origin, with individuals from advantaged backgrounds being better able to mitigate the financial consequences when dropouts experience bad luck.
with Joscha Legewie (Harvard University)
Does exposure to hyper-local heat in urban settings impact student learning outcomes? In combining detailed sensory data, 2.5D landcover data and satellite data from New York City, supervised machine techniques and a Soil, Water, and Energy Integrated Model (SOLWEIG), the projects aims to predict hyper-local heat exposure for urban neighborhoods. After benchmarking these results with test data, we further test whether predicted hyper-local heat but also mean radiant temperatures affect students' learning outcomes.