This paper estimates the effect of immigration on native wages at the national level taking into account the endogenous allocation of immigrants across skill cells. Time-varying exogenous variation across skill cells for a given country is provided by interactions of push factors, distance, and skill cell dummies: distance mitigates the effect of push factors more severely for less educated and middle experienced. Because the analysis focuses on the United States and Canada, I propose a two-stage approach (Sub-Sample 2SLS) that estimates the first stage regression with an augmented sample of destination countries, and the second stage equation with the restricted sub-sample of interest. I derive asymptotic results for this estimator, and suggest several applications beyond the current one. The empirical analysis indicates a substantial bias in estimated OLS wage elasticities to immigration. Sub-Sample 2SLS estimates average - 1:2 and are very stable to the use of alternative instruments.
Forthcoming Journal of Human Resources