Migration shocks, Elections, and Political Selection

Abstract

This paper analyzes the electoral performance of local council candidates with an immigrant background. Do voters evaluate these candidates differently when a new wave of refugee immigrants arrives? We study this question using hand-collected candidate-level data on municipal elections (2001-2021) and detailed administrative data on asylum seekers for the German state of Hesse. We rely on existing machine learning classification tools to infer the immigrant background from candidates’ names. Descriptively, candidates with an immigrant background face a small electoral disadvantage relative to candidates without an immigrant background. Using a difference-in-differences strategy with continuous treatment, we find that the intake of asylum seekers in the relevant municipality increases the chances of candidates with an immigrant background to get elected into the council.