Individual heterogeneity in the returns to schooling: instrumental variable quantile regression
2018
Draft
Abstract: The main focus of this paper is to investigate whether people with varying levels of unobserved ability obtain different earnings based on their years of schooling. This paper's contribution to the literature is to use the instrumental quantile regression method to capture the heterogeneity of returns on the twins' sample while controlling for ability and measurement error biases. After controlling all covariates and biases, the range of estimates is between 9 percent and 15 percent. Although there is a weak identification problem, the results from both the levels and the proxy models are statistically significant. This paper shows the existence of heterogeneity across individuals through the general Wald-type location shift test. This indicates the complementary relationship between education and schooling in the generation of earnings. Furthermore, I check the positive ability bias, negative measurement error, linearity of schooling, and the heterogeneity of returns of other covariates, including age, race, gender, union membership, and tenure.