Semiparametric and Nonparametric Methods in Econometrics

该项目有三个部分。(1)开发新的半参数和非参数模型，使其比现有模型更好地拟合数据;（2）在存在工具变量的情况下，开发半参数和非参数估计和规格检验的方法;（3）开发受经济理论形状限制的非参数估计方法。 第（1）部分的动机是观察到，现有的方法，实现降维，从而在半参数或非参数估计，更大的估计精度不一定适合感兴趣的数据的应用。 该研究将开发比现有模型和方法更灵活的模型和方法，但仍然可以实现必要的降维，以获得实际规模的数据集的有用结果。 新模型将应用于现有模型不能很好拟合的数据。 第（2）部分是关于非参数工具变量（NPIV）的估计。 一个目标是开发方法的降维NPIV估计。 另一个是开发方法来测试一个参数模型对非参数替代工具变量的存在。 有大量的文献测试的参数模型的条件均值或分位数函数对非参数的替代，但测试工具变量是一个新的研究领域。 第（3）部分将发展满足单调性约束和经济理论的Slutsky条件的需求函数的非参数估计方法。 有文献估计下的单调性和/或凸性的限制，但斯卢茨基条件是非线性的，因此，提出了一个特殊的挑战。 另一个目标是开发方法来检验抽样人口中满足斯卢茨基条件的假设。 首先，其结果将纳入研究人员和其他人教授的研究生和本科生课程中。 第二，该项目将支持博士研究。学生谁将工作的问题所产生的项目。 第三，该项目的成果很可能通过纳入公共机构的政策研究而造福于整个社会。 除其他方式外，这将通过调查员在向联邦政府提供咨询的委员会和其他团体中的服务来实现。

This project has three parts. (1) Development of new semi- and nonparametric models that fit data better than existing ones; (2) Development of methods for semi- and nonparametric estimation and specification testing in the presence of instrumental variables, and (3) Development of methods for nonparametric estimation subject to shape restrictions obtained from economic theory. Part (1) is motivated by the observation that existing methods for achieving dimension reduction and, thereby, greater estimation precision in semi- or nonparametric estimation do not necessarily fit the data of interest in applications. The research will develop models and methods that are more flexible than existing ones are but still achieve the dimension reduction necessary to obtain useful results with data sets of practical size. The new models will be applied to data that existing models do not fit well. Part (2) is concerned with nonparametric instrumental variables (NPIV) estimation. One objective is to develop methods of dimension reduction for NPIV estimation. The other is to develop methods for testing a parametric model against a nonparametric alternative in the presence of instrumental variables. There is a large literature on testing a parametric model of a conditional mean or quantile function against a nonparametric alternative, but testing with instrumental variables is a new area of research. Part (3) will develop methods for nonparametric estimation of demand functions subject to monotonicity constraints and the Slutsky conditions of economic theory. There is a literature on estimation under monotonicity and/or convexity restrictions, but the Slutsky conditions are nonlinear and, therefore, present a special challenge. A further objective is to develop methods for testing the hypothesis that the Slutsky conditions are satisfied in a sampled population.The research will have several broader impacts. First, its results will be incorporated into graduate and undergraduate courses that are taught by the investigator and others. Second, the project will support the research of Ph.D. students who will work on problems generated by the project. Third, the results of the project are likely to benefit society at large by being incorporated into policy studies for public agencies. This will be done, among other ways, through the investigator's service on committees and other groups that advise the Federal government.