Spurious Relationship of AR(P) Stable Sequences in Presence of Trends Breaks

Cong Yu, Xuefeng Wang, J. Ma
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Abstract

This paper analyzes spurious regression phenomenon involving AR(p) stable processes with trend breaks. It shows that when those time series are used in ordinary least squares regression, the convenient t-ratios procedures wrongly indicate that the spurious relationship is present as the pair of independent stable series contains trend changes. The spurious relationship becomes stronger as the sample size approaches to infinite. As a result, spurious effects might occur more often than we previously believed as they can arise even between AR(p) stable series in present of trend breaks.
趋势断裂存在下AR(P)稳定序列的伪关系
本文分析了具有趋势中断的AR(p)稳定过程的伪回归现象。结果表明,当这些时间序列用于普通最小二乘回归时,方便的t比率程序错误地表明,由于独立稳定序列对包含趋势变化,因此存在虚假关系。当样本量接近无穷大时,虚假关系变得更强。因此,虚假效应可能比我们以前认为的更频繁地发生,因为它们甚至可以出现在当前趋势中断的AR(p)稳定序列之间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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