First time around: Local conditions and multi-dimensional integration of refugees

We study the effect of local unemployment and attitudes towards immigrants at the time of arrival on refugees’ multi-dimensional integration outcomes. We leverage a centralized allocation policy in Germany where refugees were centrally assigned to live in specific counties. To measure sentiments of native residents towards immigrants, we use geo-coded Twitter data, which provides our “negative sentiment index”. Our results show that attitudes towards immigrants are as important as local unemployment rates in shaping refugees’ integration outcomes. A one standard deviation increase in unemployment or in the negative sentiment index predicts five percentage points lower probability of refugees being employed in 2016 to 2018. In additional robustness check, we present an analysis that uses far-right vote share as an alternative measure of sentiments of native residents.