We conduct a survey experiment on the effect of information provision on attitudes towards immigration in Germany. The focus lies on two theory-based economic channels, labor market and welfare state concerns, and immigration policy preferences. Using probability-based representative survey data, we experimentally vary the quantity and the type of information provided to respondents. We find that a bundle of information on both the share and the unemployment rate of foreigners robustly decreases welfare state concerns about immigration. There are slightly less pronounced effects on the labor market and policy channels. Further data-driven analyses reveal heterogeneity in treatment effects. Our findings therefore suggest that careful composition and targeting of information interventions can increase their effectiveness in the public debate on immigration.
immigration attitudes survey experiment information provision belief updating welfare state labor market machine learning