Migration and Automation – Spatial Clustering of Foreign Populations by Risk of Technology-Induced Job Loss in Denmark

Marcin Stonawski , Statistics Denmark / CASPAR
Vegard Skirbekk, University of Oslo and Norwegian Institute of Public Health

This article examines the relationship between migration, automation, and spatial segregation in Denmark by analyzing patterns of residential clustering relate to migrants’ risk of technology-induced job loss. Automation reduces demand for routine, automatable tasks while increasing demand for both high-skill and low-skill service occupations. Migrant workers are disproportionately affected, as they are overrepresented in sectors highly exposed to automation risk, such as manufacturing and agriculture, while also concentrated in expanding care and domestic work sectors. Using longitudinal, geo-coded Danish register data (2007–2023), we investigate whether migrants are spatially clustered not only by socioeconomic status but also by their risk of technology-induced job loss. To measure occupational exposure to automation, we employ the Routine Task Intensity (RTI) index developed by Autor et al. (2003) and updated for ISCO-2 digit occupations by Lewandowski et al. (2022). Spatial analysis is conducted using a Geographic Information System (GIS) approach that constructs individualized, scalable neighborhoods, thereby avoiding the modifiable areal unit problem (MAUP). This enables the identification of areas where migrants with high RTI scores are concentrated and where communities may be most vulnerable to automation-driven labor shifts. Focusing on Denmark’s four largest cities—Copenhagen, Aarhus, Aalborg, and Odense—we explore long-term changes in spatial clustering across skill levels and household compositions. We hypothesize that migrants, particularly low-skilled individuals and households, will exhibit stronger clustering patterns by automation risk than by traditional socioeconomic indicators, revealing new dimensions of inequality in the era of technological change.

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 Presented in Session P4. Migration, Migrants, and Mobility