Estimating production functions and other micro models is fraught with statistical difficulties given existing estimating techniques, even in the case of linear models. With nonlinear models, the reliability of existing techniques is even less. This project will analyze a number of microeconometric models, including single equation models, systems of equations and simultaneous equation models, all with qualitative or limited dependent variables. The major goals are to establish clear identification conditions, to establish consistency, and asymptotic normality of the estimators. In addition, the finite sample performance of the estimators will be investigated both by Monte Carlo studies and by applying them to actual data. The purpose of this project is to develop a semi-parametric method for the estimation of microeconometric models. This study is important because the development of semi-parametric methods offers a way to better estimate a large class of non-liner models. This estimation method should find a variety of applications by economists interested in empirical research.
