people can be trusted and that people are helpful, but less likely to agree that people are fair. They are also less worried about crime. These differences, however, are small, and they are almost zero with respect to caution towards foreigners and donations. In Appendix A.3, we report the descriptive statistics for the estimation sample.

The goal of the econometric analysis is to see whether the _change_ in attitudes after the inflow versus before was different among people in high-inflow vs. low-inflow areas. The descriptive analysis in Figure 4 suggests that this was not the case: for most outcomes, the gap between people’s attitudes in high- and low-inflow areas is similar before and after the inflow.

**Data on Anti-Immigrant Violence** To investigate whether the inflows of refugees and asylum seekers affect natives’ behavior towards foreigners — and not only their attitudes — we use information on anti-immigrant violence in Germany. We use a geo-referenced event dataset reporting all instances of anti-refugee violent actions that have been documented by the project _Mut gegen rechte Gewalt_ by the Antonio Amadeu Foundation. The foundation collected information on anti-immigrant incidents such as assaults, attacks against refugee housing and arson, as well as anti-immigrant demonstrations. For each incident, the database records information on the time, location, number of victims and perpetrators as well as a description of the incident and a link to the original source. The information was mostly taken from newspaper articles, press releases by the German police, parliamentary interpellations, as well as publicly accessible reports by local and regional organizations offering advice to victims of right-wing violence. For our analysis, we use a dataset provided by Bencek andˇ Strasheim (2016), who scraped the database from the Foundation from 2013 to 2018. Based on their code, we additionally scraped all entries up until 2020.

Figure 5 shows the overall number of anti-immigrant incidents in Germany between 2014 and 2017 as well as the number of asylum applications per month. The number of incidents was low until mid-2015 and increased in the second half of 2015, when most asylum seekers arrived in Germany. The number of incidents increased sharply in early 2016 and gradually declined to its pre-2015 level in 2017. A recent study by Frey (2020) suggests that this sharp increase was caused by the events in Cologne on New Year’s Eve 2015/16. In Appendix B, we present additional descriptive statistics on the number of incidents in different categories as well as the frequency of events per year and county. By far the largest number of incidents were attacks on refugee housing. Other incidents such as arson or assaults play a minor role in explaining the pattern in Figure 5. Regarding the frequency of anti-immigrant violence, the median county experiences 5.6 incidents per 100,000 inhabitants per year, although there is considerable variation in the number of incidents. There are few counties with zero incidents, whereas the majority ranges between one and 20 incidents per 100,000 inhabitants per year.

# **4.2 Identification Strategy**

Our goal is to quantify the effect of the local presence of asylum seekers on social attitudes and antiimmigrant violence. In general, identifying the causal effect of immigration is challenging because the same factors that attract migrants may also affect the outcomes of interest. For example, migrants may be attracted to cities that offer high wages. The resulting correlation between immigration and 17