I estimate the effect of immigration on wages of native male workers correcting for endogenous allocation of immigrants across education-experience cells. Exogenous variation is obtained from interactions of push factors, distance, and skill-cell dummies: distance mitigates the effect of push factors more severely for some skill groups. 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 with a restricted sub-sample of interest. Asymptotic properties are discussed. Results show important OLS biases. For U.S. and Canada, Sub-Sample 2SLS elasticities average around minus one, very stable across alternative specifications and different instruments.
JEL Codes: J61, J31, C26.Sub-Sample 2SLS estimated wage elasticities to immigration average − 1, which more than doubles OLS counterparts. This result is very stable across alternative push factors, definitions of distance, and fixed effects specifications, suggesting that treatment effects could be homogeneous, and the resulting wage elasticity, an average treatment effect. All in all, the main conclusion is that, even when the national-level cross-skill-cell approach is used, endogenous allocation of immigrants across labor markets creates a substantial bias in the estimation of wage effects of immigration.