The contribution of this project comes from the development of semiparametric estimators for models that have not previously been considered, as well as new estimators for models that have been considered in the statistical and econometric literature. A great deal of research in econometrics has been devoted to the development of semiparametric methods because these methods permit analysts to obtain results from data even if very little is known about the underlying processes that generated the data. This project develops semi-parametric estimators for a number of different models. These include partially linear Tobit models, partially linear logit models, partially linear Poisson regression models, partially linear duration models, and Tobit models with sample selection. These estimators are defined by minimizing objective functions that are based on comparing all pairs of observations. An investigation of the asymptotic properties of estimators that are defined in this way will be conducted. Previous research on Tobit models with fixed effects will continue. The possibility of estimating fixed effects versions of the so- called Type 3 Tobit model will be addressed, and a two-step estimator is developed. Software will be developed to permit others to use these techniques.
