Semi-Parametric Estimation of Microeconometric Models with Qualitative and Limited Dependent Variables

估计生产函数和其他微观模型是困难的 由于现有估计技术的统计困难， 即使在线性模型的情况下。 对于非线性模型， 现有技术的可靠性更低。该项目将 分析一些微观计量经济模型，包括单一方程 模型，方程组和联立方程模型，所有这些都与 定性或有限的因变量。 主要目标是 建立明确的识别条件，建立一致性， 估计量的渐近正态性。 此外，有限 估计量的样本性能将通过以下两种方法进行研究： 蒙特卡洛研究并将其应用于实际数据。 本项目的目的是开发一种半参数方法， 微观计量经济模型的估计。 这项研究很重要 因为半参数方法的发展为 更好地估计一大类非线性模型。 该估计 这种方法应该会被感兴趣的经济学家广泛应用 in empirical实证research研究.

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.