WALD TESTS FOR DETECTING MULTIPLE STRUCTURAL CHANGES IN PERSISTENCE
检测持久性多重结构变化的 Wald 检验AI 解读 ↓
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AI 根据所提供的论文材料归类：摘要直接研究时间序列单位根与平稳状态之间的多重切换，属于时间序列与结构变化。
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检测持久性多重结构变化的 Wald 检验
- 研究问题
- 如何检验单变量时间序列是否从全样本单位根过程转为平稳与单位根状态交替，并辨别初始状态的持久性类型？
- 方法与思路
- 作者提出 sup-Wald 检验与混合检验程序，推导原假设下极限分布，并利用动态规划处理状态内及跨状态参数限制。
- 材料陈述的贡献
- 摘要称建立相关备择下的一致性，说明检验针对错误备择时不一致，并用混合程序帮助排除纯平稳变化的解释。
- 阅读关注点
- 应核对不同状态顺序对应的备择、错误备择下不一致性的含义、混合程序的拒绝解释，以及断点搜索与参数限制。
- 阅读边界
- 仅据所给 Crossref 摘要解读；摘要未说明断点数量限制、状态长度条件及模拟数值，有限样本表现良好只是作者所述结果。
原文摘要
This paper considers the problem of testing for multiple structural changes in the persistence of a univariate time series. We propose sup-Wald tests of the null hypothesis that the process has an autoregressive unit root throughout the sample against the alternative hypothesis that the process alternates between stationary and unit root regimes. We derive the limit distributions of the tests under the null and establish their consistency under the relevant alternatives. We further show that the tests are inconsistent when directed against the incorrect alternative, thereby enabling identification of the nature of persistence in the initial regime. We also propose hybrid testing procedures that allow ruling out of stable stationary processes or ones that are subject to only stationary changes under the null, thereby aiding the researcher in interpreting a rejection as emanating from a switch between a unit root and stationary regime. The computation of the test statistics as well as asymptotic critical values is facilitated by the dynamic programming algorithm proposed in Perron and Qu (2006, Journal of Econometrics 134, 373–399) which allows imposing within- and cross-regime restrictions on the parameters. Finally, we present Monte Carlo evidence to show that the proposed procedures perform well in finite samples relative to those available in the literature.