Collaborative Research: Making Semiparametric Methods Operational: Bridging the Gap between Theory and Application

协作研究：使半参数方法可操作：弥合理论与应用之间的差距

• 批准号: 9813492
• 负责人: Petra Todd
• 金额: --
• 依托单位: University of Pennsylvania
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1998
• 资助国家: 美国
• 起止时间: 1998-07-01 至 2001-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9813492&HistoricalAwards=false
• 关键词: Collaborative; Research; Making; Semiparametric; Methods

9813492 Petra Much recent work in econometrics has been directed towards developing non-parametric and semi-parametric estimation approaches. These methods improve on traditional methods by allowing researchers to better uncover relationships in the data without having to make as many a priori modeling assumptions. They can also be used to test for the validity of parametric restrictions. Yet despite the potential broad applicability of these new estimation methods in empirical economic research, they are not widely used. This project addresses the reasons these methods are not used by: (1) resolving arbitrariness left in many semi-parametric procedures; (2) deriving general approximation results for data-dependent smoothing and trimming methods; (3) developing methods and software that overcome difficulties in computation with large data sets and (4) demonstrating how semi-parametric methods are useful for empirical work. The arbitrariness left in many semi-parametric procedures, which takes the form of parameters left unspecified, is addressed by developing effective, data-driven methods for choosing unspecified parameters. A preliminary Monte Carlo study comparing alternative methods demonstrates the effectiveness of the new methods. New asymptotic approximation results, needed to justify estimators that use data-dependent smoothing and trimming methods, are developed. Computational problems are resolved by adapting highly effective approximation techniques for use in estimating semi-parametric models. Two classes of empirical problems are shown to be promising areas to apply semi-parametric models: regression comparisons of two or more groups and the binary choice model.

9813492 PETRA最近在计量经济学方面进行了许多旨在开发非参数和半参数估计方法的工作。 这些方法通过允许研究人员更好地发现数据中的关系而不必做出那么多的先验建模假设，从而改善了传统方法。 它们也可以用于测试参数限制的有效性。 然而，尽管这些新的估计方法在经验经济研究中可能存在广泛的适用性，但它们并未被广泛使用。 该项目解决了这些方法未使用的原因：（1）解决许多半参数程序中留下的任意性； （2）得出有关数据依赖性平滑和修剪方法的一般近似结果； （3）开发使用大数据集克服计算困难的方法和软件，以及（4）证明半参数方法如何对经验工作有用。 通过开发选择未指定参数的有效数据驱动的方法来解决许多半参数过程中留下的任意性，这些任意性以未指定的参数形式来解决。 比较替代方法的初步蒙特卡洛研究证明了新方法的有效性。 开发了使用数据依赖于数据的平滑和修剪方法的估计器所需的新的渐近近似结果。 通过调整高效近似技术来估算半参数模型来解决计算问题。 两类的经验问题被证明是应用半参数模型的有希望的领域：两个或多个组的回归比较和二进制选择模型。