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.

该项目包括四个不同但相互关联的领域， 概率泛函极限理论的研究。 它们是：（1） 参数恒定性的最优检验，（2）中位数无偏 非平稳估计与置信区间构造 时间序列，（3）经验过程极限理论的依赖 非同分布随机变量，以及（4） 半参数计量经济学方法 这项研究成果 将为应用经济分析提供强大的新工具 包括全球环境经济学研究 变化 关于参数恒定性的拟议工作包括以下测试： 具有未知变点的结构变化和 状态转换 这个项目的这一部分很重要，因为 目前还没有渐近最优检验可用于 当标准正则性 条件失败。 建议研究中位数无偏 估计和置信区间构造是重要的 因为当前测试具有低功率。 开发的新工具 在这个项目下，可以用来为分析师提供更多 时间序列问题类型的信息， 在经济学中经常遇到。 基本限制 相依非同分布随机变量的结果 变量在各种时间序列中也有应用 经济计量问题。 在第四个研究领域， 开发了异方差，自相关， 半参数和非参数渐近正态性 估计器。 半参数估计被广泛使用， 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， 这些新的测试可以用于非常广泛的 半参数估计 这些方法尤其 适合于预测和实证分析类型 全球变化经济学中遇到的问题， 数据质量差，许多数据的不确定性， 潜在的经济关系，以及变化的可能性 在所研究的经济体系结构中。