A robust version of the KPSS test based on ranks
Matteo Pelagatti () and
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Pranab Sen: Department of Statistics and Operations Research, University of North Carolina at Chapel Hill
No 20090701, Working Papers from Università degli Studi di Milano-Bicocca, Dipartimento di Statistica
This paper proposes a test of the null hypothesis of stationarity that is robust to the presence of fat-tailed errors. The test statistic is a modified version of the KPSS statistic, in which ranks substitute the original observations. The rank KPSS statistic has the same limiting distribution as the standard KPSS statistic under the null and diverges under I(1) alternatives. It features good power both under thin-tailed and fat-tailed distributions and it turns out to be a valid alternative to the original KPSS and the recently proposed Index KPSS (de Jong et al. 2007).
Keywords: Stationarity testing; Time series; Robustness; Rank statistics; Empirical processes (search for similar items in EconPapers)
JEL-codes: C12 C14 C22 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm and nep-ets
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Persistent link: https://EconPapers.repec.org/RePEc:mis:wpaper:20090701
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