Subsampling change-point detection in persistence with heavy-tailed innovations

This paper considers how to detect structure change in persistence fromI(1) toI(0) with innovations in the domain of attraction of a κ-stable law. We derive the asymptotic distribution of test statistic and find that the asymptotic distribution of test statistics depends on the stable index κ which...

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Bibliographic Details
Published inJournal of applied mathematics & computing Vol. 23; no. 1-2; pp. 57 - 71
Main Authors Han, Sier, Tian, Zheng
Format Journal Article
LanguageEnglish
Published Dordrecht Springer Nature B.V 01.01.2007
Subjects
Asymptotic properties
Attraction
Computer simulation
Econometrics
Estimates
Mathematical analysis
Samples
Statistical analysis
Statistics
Studies
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Summary:This paper considers how to detect structure change in persistence fromI(1) toI(0) with innovations in the domain of attraction of a κ-stable law. We derive the asymptotic distribution of test statistic and find that the asymptotic distribution of test statistics depends on the stable index κ which is often typically unknown and difficult to estimate. Therefore the subsampling method is proposed to detect changes without estimating κ. We establish the asymptotic validity of this method and assess its performance in finite samples by means of simulation study.[PUBLICATION ABSTRACT]
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ISSN:1598-5865
1865-2085
DOI:10.1007/BF02831958