A panel cointegration rank test with structural breaks and cross-sectional dependence

Deniz Karaman Örsal and Antonia Arsova

VfS Annual Conference 2016 (Augsburg): Demographic Change from Verein für Socialpolitik / German Economic Association

Abstract: This paper proposes a new likelihood-based panel cointegration rank test which allows for a linear time trend with heterogeneous breaks and cross sectional dependence. It is based on a novel modification of the inverse normal method which combines the p-values of the individual likelihood-ratio trace statistics of Trenkler et al. (2007). We call this new test a correlation augmented inverse normal (CAIN) test. It infers the unknown correlation between the probits of the individual p-values from an estimate of the average absolute correlation between the VAR processes' innovations, which is readily observable in practice. A Monte Carlo study demonstrates that this simple test is robust to various degrees of cross-sectional dependence generated by common factors. It has better size and power properties than other meta-analytic tests in panels with dimensions typically encountered in macroeconometric analysis.

JEL-codes: C12 C15 C33 (search for similar items in EconPapers)
Date: 2016
New Economics Papers: this item is included in nep-ecm and nep-ets
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Related works:
Journal Article: A panel cointegrating rank test with structural breaks and cross-sectional dependence (2021)
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Persistent link: https://EconPapers.repec.org/RePEc:zbw:vfsc16:145822

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