The purpose of this research is to develop semi-parametric methods for the estimation of sample selection models. These methods will allow for the simultaneous estimation of choice equations and outcome equations. In addition to the estimation of the two equations sample-selection models, the estimation of more complicated sample-selection models will also be considered. All of these models have certain features in common, but they also have structures of their own. Such structures impose specific identification restrictions on the models. This project will develop semi-parametric estimation methods which explore the systematic structures of the models. Some of the systematic estimation methods to be investigated are the semi-parametric likelihood methods. Monte Carlo experiments will be performed to investigate the small sample performance of the proposed estimators. This research is important because sample-selection models have many important applications, such as in the analysis of job-search behavior, and the methods to be developed will permit for better estimating these and other models.
