Migration Shocks, Elections, and Political Selection

Abstract: Does the sudden arrival of a new wave of immigrants distort the electoral performance of local council candidates with an immigrant background? We combine hand-collected candidate-level data on council elections (2001-2021) with detailed administrative data on asylum seekers across Hessian municipalities. We infer candidates' immigrant background from their names via existing machine learning classification tools. Using a difference-in-differences strategy with a continuous treatment (change in the share of asylum seekers per municipality), we find that candidates with an immigrant background benefit from the arrival of relatively large numbers of asylum seekers such as in late 2015. Further results show that this effect exists exclusively for candidates with a Southern or Eastern European background which are culturally and ethnically relatively similar to native Germans.