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分类依据与纠错

AI 根据所提供的论文材料归类:摘要聚焦一次参数变化的检验功效,并明确比较相关误差及含滞后因变量的动态回归,对应结构变化与时间序列。

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关注这篇论文的作者
Ai Deng
Pierre Perron

从非局部视角分析 CUSUM 及平方 CUSUM 结构变化检验的功效

研究问题
面对线性回归参数的一次变化,局部渐近功效能否解释有限样本表现,较大变化又会如何影响两类 CUSUM 检验?
方法与思路
作者推导保留备择下变化幅度相关项的统计量展开,分析非局部变化,并比较误差相关性、动态回归及非正态修正。
材料陈述的贡献
摘要称,理论解释不同模型中的功效差异,并指出某些情形下功效随变化增大而非单调甚至趋零,模拟支持这些解释。
阅读关注点
应核对功效下降出现在哪些模型和变化方向下、展开适用条件,以及误差相关性和非正态修正如何改变检验行为。
阅读边界
依据所给工作论文版本摘要,不能推断刊本变化;摘要未列出各异常功效情形的完整条件,也未提供模拟数值。

原文摘要

We consider the power properties of the CUSUM and CUSUM of squares tests in the presence of a one-time change in the parameters of a linear regression model. A result due to Ploberger and Krämer (1990) is that the CUSUM of squares test has only trivial asymptotic local power in this case, while the CUSUM test has non-trivial local asymptotic power unless the change is orthogonal to the mean regressor. The main theme of the paper is that such conclusions obtained from a local asymptotic framework are not reliable guides to what happens in finite samples. The approach we take is to derive expansions of the test statistics that retain terms related to the magnitude of the change under the alternative hypothesis. This enables us to analyze what happens for non-local to zero breaks. Our theoretical results are able to explain how the power function of the tests can be drastically different depending on whether one deals with a static regression with uncorrelated errors, a static regression with correlated errors, a dynamic regression with lagged dependent variables, or whether a correction for non-Normality is applied in the case of the CUSUM of squares. We discuss in which cases the tests are subject to a non-monotonic power function that goes to zero as the magnitude of the change increases, and uncover some curious properties. All theoretical results are verified to yield good guides to the finite sample power through simulation experiments. We finally highlight the practical importance of our results.

笔记与分组
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