Wage Differences in the H-1B Visa Program in the American Tech Sector

Abstract

This thesis examines wage differences between H-1B visa recipients and U.S. native workers in the American tech sector. Utilizing a merged dataset consisting of Labor Condition Application (LCA) for H-1B workers and Current Population Survey (CPS) data from IPUMS for native workers, we estimate our results using a series of OLS regressions with fixed effects for occupation, state and wage level. Our baseline model identifies a statistically significant negative wage gap for H-1B visa holders, which is most pronounced at higher wage levels and varies considerably across occupations. These findings suggest that occupational sorting and geographic factors do not fully explain the observed wage disparities.