发表机构
Aalborg University; Center for Research in Energy: Economics and Markets (CoRE)（奥尔堡大学; 能源经济与市场研究中心）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文提出三种基于Engle-Granger统计量下确界的检验，用于检测时间序列仅在样本部分时段存在协整，并应用于海平面与温度数据，在5%水平下拒绝无协整假设。
AI 中文摘要
协整检验通常应用于覆盖整个样本的单一窗口，假设长期关系在整个样本期间成立。当这种关系仅存在于样本的一部分时，此类检验会失去功效，因为平稳阶段被无协整的时期稀释。我们提出了三个统计量，用于检验两个或多个序列是否仅在样本的一部分上存在协整，每个统计量都是Engle-Granger统计量在递归、向后扩展或双重灵活窗口上的下确界。我们推导了它们的极限分布，并确定了每个统计量对哪些备择假设具有一致性。只有双重灵活统计量对两种断裂方向都具有功效。受James G. MacKinnon开创性工作的启发，临界值通过模拟获得，并通过响应面回归进行总结。我们将这些检验应用于全球平均海平面和全球平均地表温度异常。所有三个检验在5%水平上拒绝了无协整的原假设，将其定位在1880—2019年记录中的一个子时期，该时期与海表温度数据收集中记录的不连续性相吻合。
英文摘要
Tests for cointegration are typically applied to a single window spanning the entire sample, assuming that the long-run relationship holds throughout. When it holds over only a part of the sample, such tests lose power, because the stationary episode is diluted by periods without cointegration. We propose three statistics for testing whether two or more series cointegrate only over a part of the sample, each an infimum of the Engle-Granger statistic over recursive, backward-expanding, or doubly-flexible windows. We derive their limiting distributions and establish which alternatives each is consistent against. Only the doubly-flexible statistic has power against both break directions. Inspired by the seminal work of James G. MacKinnon, critical values are obtained by simulation and summarized through response surface regressions. We apply the tests to global mean sea level and global mean surface temperature anomalies. All three reject the null of no cointegration at the 5% level, locating it in a sub-period of the 1880--2019 record that coincides with documented discontinuities in sea surface temperature data collection.
