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Testing Covariance Stationarity

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Author Info
Zhijie Xiao
Luiz Renato Lima

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Abstract

In this paper, we show that the widely used stationarity tests such as the Kwiatkowski Phillips, Schmidt, and Shin (KPSS) test have power close to size in the presence of time-varying unconditional variance. We propose a new test as a complement of the existing tests. Monte Carlo experiments show that the proposed test possesses the following characteristics: (i) in the presence of unit root or a structural change in the mean, the proposed test is as powerful as the KPSS and other tests; (ii) in the presence of a changing variance, the traditional tests perform badly whereas the proposed test has high power comparing to the existing tests; (iii) the proposed test has the same size as traditional stationarity tests under the null hypothesis of stationarity. An application to daily observations of return on U.S. Dollar/Euro exchange rate reveals the existence of instability in the unconditional variance when the entire sample is considered, but stability is found in subsamples.

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Publisher Info
Article provided by Taylor and Francis Journals in its journal Econometric Reviews.

Volume (Year): 26 (2007)
Issue (Month): 6 ()
Pages: 643-667
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Handle: RePEc:taf:emetrv:v:26:y:2007:i:6:p:643-667

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Related research
Keywords: Asymptotic theory; KPSS; Stationarity testing; Time-varying variance;

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References listed on IDEAS
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