Several papers have tested the empirical validity of the migration models proposed by Borjas (1987) and Borjas, Bronars, and Trejo (1992). However, to our knowledge, none has been able to disentangle the separate impact of observable and unobservable individual characteristics, and their respective returns across different locations, on an individual's decision to migrate. We build a model in which individuals sort, in part, on potential earnings - where earnings across different locations are a function of both observable and unobservable characteristics. We focus on the inter-provincial migration patterns of Canadian physicians. We choose this particular group for several reasons including the fact that they are paid on a fee-for-service basis. Since wage rates are exogenous, earning differentials are driven by differences in productivity. We then estimate a mixed conditional-logit model to determine the effects of individual and destination-specific characteristics (particularly earnings differentials) on physician location decisions. We find, among other things, that high-productivity physicians (based on unobservables) are more likely to migrate to provinces where the productivity premium is greater, while low-productivity physicians are more likely to migrate to areas where the productivity premium is lower. These results are consistent with a modified Borjas model of self-selection in migration based on both unobservables and observables.
migration self-selection earnings longitudinal data productivity