In Good Company: Coethnic Advisors and Career Paths of Immigrant Ph.D. Students

In this paper, we examine the role of coethnic advisor-student matching in U.S. Ph.D. programs in attracting, training and guiding immigrant talent into top jobs in Artificial Intelligence (AI). Using comprehensive administrative data on 1,769 AI Ph.D. graduates from top U.S. programs, combined with their advisors’ profiles and post-Ph.D. employment outcomes, and complemented by original survey data, we document two new findings. First, immigrant students systematically match with coethnic thesis advisors at markedly higher rates than would be expected by chance. This matching is shaped by reputational spillovers, pre-Ph.D. contact, and preference for shared backgrounds. Second, immigrant students with coethnic advisors are more likely to enter high-quality industry jobs after graduation than their native counterparts. We find suggestive evidence that this is driven by access to industry internships, facilitated by these advisors' unique professional networks. Our findings reveal that universities, through their immigrant-origin faculty, act as critical conduits connecting global scientific talent to the U.S. innovation economy. An important organizational implication of our results is that disruptions to immigration may constrain firm-level access to talent and weaken the academic-to-industry pipeline.