Estimating the returns to schooling : a likelihood approach based on normal mixtures

Abstract

Abstract: In this paper we develop likelihood based methods for statistical inference in a joint system of equations for the choice of length of schooling and earnings. The model for schooling choice is assumed to be an ordered probit model, whereas the earnings equation contains variables that are flexible transformations of schooling and experience, with corresponding coefficients that are allowed to be heterogeneous across individuals. Under the assumption that the distribution of the random terms of the model can be expressed as a particular finite mixture of multinormal distributions, we show that the joint probability distribution for schooling and earnings can be expressed on closed form. In an application of our method on Norwegian data, we find that the mixed Gaussian model offers a substantial improvement in fit to the (heavy-tailed) empirical distribution of log-earnings compared to a multinormal benchmark model. Keywords: Schooling choice, earnings equation, normal mixtures, treatment effects, self-selection, random coefficients, full information maximum likelihood