Functional Limit Theory in Econometrics

计量经济学中的函数极限理论

• 批准号: 9121914
• 负责人: Donald Andrews
• 金额: $ 20.87万
• 依托单位: Yale University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1992
• 资助国家: 美国
• 起止时间: 1992-03-15 至 1995-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9121914&HistoricalAwards=false
• 关键词: Functional; Limit; Theory; Econometrics

This project encompasses four distinct, but interrelated areas of research in probabilistic functional limit theory. They are: (1) optimal tests of parameter constancy, (2) median unbiased estimation and confidence interval construction for nonstationary time series, (3) empirical process limit theory for dependent non-identically distributed random variables, and (4) semiparametric econometric methods. The results of this research will provide powerful, new tools for applied economic analysis including research on the economics of global environmental change. The proposed work on parameter constancy covers tests of structural change with an unknown change point and tests of regime switching. This part of the project is important because there currently are no asymptotically optimal tests available for testing for parameter constancy when the standard regularity conditions fail. The proposed research on median unbiased estimation and confidence interval construction is significant because current tests have low power. The new tools developed under this project can be used to provide analysts more information for the types of time series problems that are frequently encountered in empirical economics. The basic limit results for dependent non-identically distributed random variables also have applications in a wide variety of time series econometric problems. In the fourth area of research the project develops tests for heteroskedasticity, autocorrelation, asymptotic normality for semiparametric and nonparametric estimators. Semiparametric estimators are widely used by economists because the data for many economic problems do not fit the assumptions required for standard parametric analysis and these new tests can be used for a very wide range of semiparametric estimators. These methods are especially appropriate for the type of forecasting and empirical analytical problems encountered in the economics of global change because of the poor quality of the data, the uncertainty about many of the underlying economic relationships, and the possibility of changes in the structure of the economic system being studied.

该项目涵盖概率泛函极限理论的四个不同但相互关联的研究领域。 它们是：（1）参数稳定性的最优检验，（2）非平稳时间序列的中值无偏估计和置信区间构建，（3）非同分布随机变量的经验过程极限理论，以及（4）半参数计量经济学方法。 这项研究的结果将为应用经济分析（包括全球环境变化经济学研究）提供强大的新工具。 拟议的参数恒定性工作涵盖未知变化点的结构变化测试和状态切换测试。 该项目的这一部分很重要，因为当前没有渐近最优测试可用于在标准正则性条件失败时测试参数稳定性。 由于当前的检验功效较低，因此所提出的中值无偏估计和置信区间构建研究具有重要意义。 该项目开发的新工具可用于为分析师提供有关实证经济学中经常遇到的时间序列问题类型的更多信息。 相关非同分布随机变量的基本极限结果也可应用于各种时间序列计量经济学问题。 在第四个研究领域，该项目开发了半参数和非参数估计量的异方差性、自相关性、渐近正态性检验。 半参数估计量被经济学家广泛使用，因为许多经济问题的数据不符合标准参数分析所需的假设，而这些新检验可用于非常广泛的半参数估计量。 这些方法特别适用于全球变化经济学中遇到的预测和实证分析问题，因为数据质量差、许多潜在经济关系的不确定性以及经济结构可能发生变化。正在研究的经济体系。