Overview
George J. Borjas is Professor of Economics and Social Policy at the Harvard Kennedy School. He is the leading labor economist studying immigrant self-selection and the labor market impacts of immigration. His adaptation of Roy (1951) to immigrant self-selection — showing that whether immigration is positively or negatively selected on skills depends on the relative inequality of the sending and receiving countries — is the standard framework in this literature. He has documented deteriorating relative wages of immigrant cohorts arriving after 1970 and is a prominent voice on the labor market competition effects of immigration.
Key Contributions / Features
- Roy model of immigrant self-selection (Borjas 1987 AER): Under equal migration costs, migrants from low-inequality countries (relative to the US) are positively selected on skills; migrants from high-inequality countries (e.g., Mexico) are negatively selected. Generates testable predictions about immigrant cohort quality. Contested by the Duleep-Regets IHCI model, which attributes declining entry earnings to declining skill transferability rather than declining ability.
- Immigrant cohort quality trends (Borjas 1985 JLE, 1995): Documented decline in relative wages of successive immigrant cohorts arriving after 1970 using pooled cross-sections across censuses; entry earnings fell from 65% to 41% of native median (1965–70 to 1985–90 cohorts). By 2000, new immigrants earned 19% less than natives (vs. +6.5% in 1960). Post-1970 cohorts unlikely to fully assimilate to native wage levels — a prognosis contradicted by Duleep-Dowhan longitudinal evidence showing substantial earnings convergence for these cohorts.
- Labor demand effects of immigration: Research on whether immigrant inflows reduce wages of native-born workers, particularly low-skilled workers; influential but contested by Card (2001) and others.
- Immigrant turnaround of the 1990s (with Friedberg 2006): Documented that the 1995–2000 cohort halted the declining relative wage trend for new immigrants, partly due to high-skilled tech workers.
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