Decomposition of wage gap between matched natives and refugees in Germany

Abstract: Prolonged and new regional violent conflicts have resulted in the displacement of residents in several countries. The thesis focuses on the people who arrived and applied for asylum in Germany between 2013 and 2016. Aimed to analyse their labour market integration in Germany, the thesis uses micro-data from Socio-Economic Panel (SOEP) to decompose the wage gap between refugee workers and native workers in 2018. Coarsened exact matching (CEM) is used to match the characteristics of native workers with refugee workers. Five sets are generated at four different matching levels of covariates. It is found that total wage gap reaches the greatest value in the unmatched set. As the two groups' characteristics getting more and more similar, explained wage gap gradually shrinks until it becomes statistically insignificant. However, discriminatory wage gap exists in all sets and cannot be wiped out even if the characteristics get similar. CEM helps to reduce the heterogeneity between the two groups and provides a more balanced dataset and a non-overestimated labour market discrimination value.