The Behavior of Tests for Structural Change in Dynamic Econometric Models

有大量的统计学和计量经济学文献， 在未知时间进行结构变化的统计测试。 的 对这些测试的研究反映了它们在获得 对经济关系的准确、无偏估计， 系列数据 这个项目的贡献来自于 更好地了解现有的 结构变化的测试和开发新的测试， 更好的性能。 这些测试用于改善 宏观经济学和金融经济学的实证研究。 这个项目分析了结构变化测试的行为 在时间序列背景下，最终允许系列具有 一般的相关结构和可能的非平稳性， 或者是多项式时间趋势的形式， 由单位根的存在引起的性质。 的组件 调查内容包括：1）分析 现有检验的有限样本性质 结构变化，允许存在序列 相关性，例如，Chow试验、LR试验和其他; 2） 使用非标准解释有限样本行为 渐近分布理论，例如，连续时间渐近 和小西格玛渐近; 3）替代方案的开发 具有更好的有限样本性质的统计程序; 4)将现有程序扩展到案件 其中时间序列的特征在于确定性的 或随机趋势; 5）渐近的推导 分布和有限样本性质的分析 用于趋势结构变化的检验; 6）经验 适用于与宏观经济变量有关的问题， 特别强调测试趋势函数的变化， 单变量时间序列

There is an extensive statistics and econometrics literature on statistical tests for structural changes at an unknown time. The research on these tests reflect their important role in getting accurate, unbiased estimates of economic relationships from time series data. The contribution of this project comes from providing a better understanding of the properties of existing tests for structural change and from developing new tests with better properties. These tests are then used to improve empirical studies in macroeconomics and financial economics. This project analyzes the behavior of tests for structural change in a time series context that ultimately allows for series having a general correlation structure and possible nonstationarity, either of the form of a polynomial time trend or of a stochastic nature induced by the presence of a unit root. The components of the investigation consist of the following: 1) Analysis of the finite sample properties of current available tests for structural change which allow for the presence of serial correlation, e.g., CUSUM, Chow test, LR test, and others; 2) Explanation of the finite sample behavior using non-standard asymptotic distribution theory, e.g., continuous-time asymptotic and small-sigma asymptotic; 3) Development of alternative statistical procedures that have better finite sample properties; 4) Extensions of currently available procedures to the case where the time series is characterized by either a deterministic or stochastic trend; 5) Derivation of the asymptotic distributions and the analysis of the finite sample properties for tests for structural change with trending; 6) Empirical application to issues related to macroeconomic variables with special emphasis on testing for a change in the trend function of a univariate time series.