Semiparametric and Nonparametric Methods in Econometrics

计量经济学中的半参数和非参数方法

• 批准号: 0352675
• 负责人: Joel Horowitz
• 金额: $ 21.99万
• 依托单位: Northwestern University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-07-01 至 2008-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0352675&HistoricalAwards=false
• 关键词: Semiparametric; Nonparametric; Methods; Econometrics

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.

该项目分为三个部分。 (1) 开发比现有模型更好地拟合数据的新半参数和非参数模型； (2) 开发在工具变量存在的情况下半参数和非参数估计和规范检验的方法，以及 (3) 开发受经济理论获得的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用于实现降维的方法，从而提高半参数或非参数估计中的估计精度，但不一定适合应用中感兴趣的数据。 该研究将开发比现有模型和方法更灵活的模型和方法，但仍能实现通过实际规模的数据集获得有用结果所需的降维。 新模型将应用于现有模型不能很好拟合的数据。 第 (2) 部分涉及非参数工具变量 (NPIV) 估计。 目标之一是开发 NPIV 估计的降维方法。 另一个是开发在存在工具变量的情况下针对非参数替代方案测试参数模型的方法。 有大量文献关于针对非参数替代方案测试条件均值或分位数函数的参数模型，但使用工具变量进行测试是一个新的研究领域。 第（3）部分将开发受单调性约束和经济理论的斯卢茨基条件约束的需求函数的非参数估计方法。 有一篇关于单调性和/或凸性限制下的估计的文献，但斯卢茨基条件是非线性的，因此提出了特殊的挑战。 进一步的目标是开发方法来检验抽样群体中满足斯卢茨基条件的假设。这项研究将产生几个更广泛的影响。 首先，其结果将被纳入由研究者和其他人教授的研究生和本科生课程中。 其次，该项目将支持博士生的研究。将解决项目产生的问题的学生。 第三，该项目的结果可能会被纳入公共机构的政策研究，从而造福整个社会。 除其他方式外，这将通过调查员为向联邦政府提供建议的委员会和其他团体提供服务来完成。