Research on immigration has emphasized the role that statistical discrimination plays in hiring decisions. A better understanding of how immigrants overcome this type of discrimination might lead to better interventions to improve their labour market participation. In this paper, we use qualitative interviews to examine how immigrants can reduce statistical discrimination by signalling their similarity to employers in their job applications. Specifically, we find that immigrants who demonstrate signal similarity to employers in the type of education, job experience and religion tend to reduce their statistical discrimination by employers. We suggest how further research can build on these results to provide possible tools for immigrant integration.
Testing for Asymmetric Employer Learning and Statistical Discrimination
