Explaining spatial patterns of foreign employment in Germany

Abstract

This paper investigates the main determinants of the representation of foreign employees across German regions. Since migration determinants are not necessarily the same for workers of different nationalities, spatial patterns are explained not only for total foreign employment but also for the 35 most important migration countries to Germany. Based on a total census for all 402 German districts, the paper starts by showing the spatial distributions of workers with different nationalities and explains the emerging patterns by spatial error models. Although large heterogeneity in determinants across nationalities are found, similarities between country groups prevail. Economic conditions matter for most nationalities, whereas the importance of amenities and openness differ.

Where do immigrants move in Germany? The role of international migration in regional disparities in population development

“…For this purpose, we estimate the following cross‐sectional log–log regression model: where ln( represents the natural log of the above‐described NMR8 for the period of 2007–2014,9 represents a comprehensive set of county characteristics in the baseline year 2007, and ε i is a random error term. This approach is similar to that of previous studies estimating the general appeal of regions for migrants (Buch et al, 2014) or the regional distribution of foreign employment (Lehmann & Nagl, 2019) in Germany. However, unlike the former authors, we are particularly interested in the diverging locational preferences between the above‐described subgroups of migrants and between the external and internal migration of foreigners, and unlike the latter authors, we are interested in flows and their contribution to population development instead of the static distribution of foreigners.…”

“…Research on the subnational patterns and determinants of international migration in destination countries has often been limited due to severe data restrictions. Many studies are therefore based on roughly representative survey data (Bartel, 1989; Chiswick & Miller, 2004; Tanis, 2020) and/or take a strictly cross‐sectional perspective (Lymperopoulou, 2013, Lehmann & Nagl, 2019). In this regard, the relatively strict German registration law and the related administrative statistics—which provide the most important base for this paper—represent an interesting exception.…”

“…This is surprising insofar as the spatial patterns and determinants of international migration have important implications for regional development and the degree of demographic and economic disparities within a host country. Although there have been some very recent efforts to explain the spatial patterns of foreign employment (Lehmann & Nagl, 2019) and the location choices of EU migrants in the aftermath of the 2009 financial crisis (Tanis, 2020), the consequences of foreign migration for regional development and spatial divergence or convergence processes in Germany still remain a remarkable gap in the research. This paper aims to fill this gap by analysing the spatial patterns of foreign migrants at the county level (NUTS3) between 2007 and 2017.…”

“…or the regional distribution of foreign employment(Lehmann & Nagl, 2019) in Germany. However, unlike the former authors, we are particularly interested in the diverging locational preferences between the above-described subgroups of migrants and between the external and internal migration of foreigners, and unlike the latter authors, we are interested in flows and their contribution to population development instead of the static distribution of foreigners.F I G U R E 5 The spatial distribution of internal foreign migration in Germany (2007-2017) Notes: Migration balances per 1000 inhabitants in 2007.…”

Trade Exposure and the Decline in Collective Bargaining: Evidence from Germany

“…Since migration is generally concentrated at regions which are relatively close to the home country (for this distance pattern of migration from Central and Eastern European countries to Germany, see e.g. Lehmann and Nagl, 2018), we thereby exclude those plants that are arguably most strongly affected by migration from the East. Second, we use the full sample, but include additional controls to account for the number of migrants from the East at the district level.…”