Ethnic segregation in schools, firms and neighborhoods

The economic assimilation of migrants in the host societies poses a major challenge for policy makers all over the world. It is important to understand the consequences of ethnic segregation in schools, firms and neighborhoods for the educational and labor market outcomes of ethnic minorities. In this project, I adopt a life course perspective on segregation, i.e. I investigate the effects of segregation at different stages in the life of immigrants in Austria, a country that has experienced an increase in immigration for the last 50 years. In the first part of the project, I study segregation in schools. Using register data of 22 cohorts of compulsory school students in Linz, the third largest city in Austria, I estimate the causal impact of the ethnic composition in the grade on educational success. To achieve identification, I use the variation in the ethnic composition of adjacent cohorts within schools. Moreover, several strategies are conducted to control for unobserved factors within schools that change over time and might be correlated with the share of migrants in the grade. After school, the young people enter the labor market. At this stage, their social network might influence their employment opportunities. As several studies have shown, social networks form along geographic and ethnic dimensions and are widely used as job information networks, generally benefitting their members by reducing uncertainties and job search frictions. There is also some evidence that social networks are only beneficial if their members hold high paying jobs. Ethnic segregation might alter labor market outcomes for ethnic minorities through such network effects. In the second part of the project, I study the impact of ethnic concentration in firms and neighborhoods on labor market outcomes of immigrants. I focus on the effects of firm and residential segregation at the community-level on wages, wage growth, tenure, unemployment incidence and duration, using large sets of Austrian register data. Considering firm segregation, the identification strategy is based on aggregation to the community-level (to eliminate within community sorting of individuals to firms) and differencing by nationality and time (to control for across community sorting). For this part of the project, I use data from the Austrian Social Security Database, a matched employer-employee database covering the employment histories of all private-sector employees in Austria between 1972 and 2008. For the analysis of residential segregation, I use the guest-worker movement to Austria in the 1960s-70s as natural experiment. I use the share of migrants in 1971 in the communities as Instrumental Variable for the share of migrants later on or the change in the share of migrants later on. I use data from the Austrian Tax Register, containing information on the residing working population between 1994 and 2005 and the Austrian census of 1971.