This paper studies how the growing presence of high-skilled workers affects urban labor and housing markets as well as incumbent inhabitants. Using fine-grained geocoded administrative employment data for the 14 largest German cities between 2000 and 2024, I document increasing residential and workplace sorting of skill groups (high-, medium-, and low-skilled), particularly along the distance to the city center. Using a shift-share predictor based on the initial age composition of high-skilled residents, I find that neighborhoods receiving high-skilled workers grow in all groups but low- and medium-skilled residents less than proportionally and have higher asking rents. Further, medium-skilled workers are more likely to move out of neighborhoods that experience high-skilled growth and move farther away; low-skilled incumbents show no significant association with moving, but those who stay are observed working closer to their residence and the ones that do move have large increases in commuting times. In every group, those who relocate end up farther from the city center and in cheaper parts of the rent distribution, hinting at a trade-off between commuting and prices. To interpret these patterns under equilibrium conditions, I develop a quantitative spatial equilibrium model with heterogeneous workers and productivities. The model is used to study further productivity gains in high-skilled employment and housing policies aimed at limiting potential displacement.

Presented at: CREST Urban and Spatial Workshop, Paris 2025; IAB Urban Labor Markt Workshop, Nuremberg 2025; Young Female Researchers in Urban Geography and Spatial Economics LSE, March 2026; University of Reading Workshop in Urban Economics and Economic Geography, Reading 2026

Rising inflows of educated high-income individuals into metropolitan areas raise concerns about inequality and prices in cities worldwide. This paper examines the consequences of high-status inflows on neighborhood change, with particular focus on the initial wave of pioneer gentrifiers. For our analysis, we use fine-grained georeferenced administrative panel data 500x500m grid cells) covering the 80 largest German cities from 2001 to 2017, split into top cities and other metropolitan areas. First, we document a rising inflow of high-status individuals, measured by income and university education. Second, we estimate the effect of these inflows on neighborhood inequality, rents, and out-mobility. As they play a crucial role in initiating gentrification by attracting subsequent inflows, we isolate the effect of the pioneer high-status in-movers. Acknowledging sorting biases and feedback dynamics, we leverage artists who locate in disadvantaged neighborhoods and attract high-status individuals as an instrumental variable. The results show that a one percent increase in the status of pioneer gentrifiers significantly raises neighborhood inequality measured by the income Gini by up to 0.04. In addition, higher status inflows relate to rising housing prices and to higher out-mobility.

Presented at: CREST Urban and Spatial Workshop Paris 2025 (by Kerstin Ostermann), UEA Eu 2026, Barcelona. 

Rising living costs, particularly rents, may reduce the residential sorting options of working-class households, especially in dense urban markets with inelastic housing supply. This may particularly affect blue-collar workers, such as craft workers, vocationally trained workers, and workers in health-related occupations. In the context of gentrification, these individuals may face constrained choices: leaving high-cost areas, adjusting their labor-market behavior, for example by changing jobs, or bearing higher commuting costs and associated welfare losses. Using rich panel data on price indices and worker characteristics, I examine which German labor markets experienced the strongest rent increases over the past two decades and how different worker groups respond. I focus especially on Germany’s top regions and whether wages adjust to potential worker shortages. I further examine adjustments through commuting, retraining, unemployment, or relocation.

We document substantial misallocation of female workers and especially married women across space using data on the universe of German workers. To rationalize these facts, we extend the standard quantitative spatial model to include couples who use intra-household bargaining to decide on a joint location. We estimate the model using administrative German employment data (IEB). We study the allocation and welfare consequences of various counterfactuals that change couples’ location decisions. 

Presented at: UEA EU 2025, Berlin; Women in Macro 2025, Berlin; Rockwool Foundation Berlin; UEA 2025 NA, Monréal (by Milan Quentel)

This article shows the potentials of georeferenced data for labor market research. We review developments in the literature and highlight areas that can benefit from exploiting georeferenced data. Moreover, we share our experiences in geocoding administrative employment data including wage and socioeconomic information of almost the entire German workforce between 2000 and 2017. To make the data easily accessible for research, we create 1-square-kilometer grid cells aggregating a rich set of labor market characteristics and sociodemographics of unprecedented spatial precision. These unique data provide detailed insights into inner-city distributions for all German cities with more than 100,000 inhabitants. Accordingly, we provide an extensive series of maps in the Additional file 1 and describe Berlin and Munich in greater detail. The small-scale maps reveal substantial differences in various labor market aspects within and across cities.