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Article: Testing for threshold autoregression with conditional heteroscedasticity

TitleTesting for threshold autoregression with conditional heteroscedasticity
Authors
KeywordsConditional heteroscedasticity
Gaussian process
Lagrange-multiplier test
Threshold time series model
Issue Date1997
PublisherOxford University Press. The Journal's web site is located at http://biomet.oxfordjournals.org/
Citation
Biometrika, 1997, v. 84 n. 2, p. 407-418 How to Cite?
AbstractThis paper addresses the null distribution of the Lagrange-multiplier statistic for the threshold autoregression with conditional heteroscedasticity. The problem is nonstandard because the threshold parameter is a nuisance parameter which is absent under the null hypothesis. We generalise the results of Chan (1990) and Chan & Tong (1990) to show that the asymptotic null distribution of the Lagrange-multiplier statistic is a functional of a zero-mean Gaussian process. The generalisation is not direct as the conditional variance is changing and the unconditional distribution of the process variable is no longer normal. In some special cases, we can reduce the problem to the asymptotic distribution of certain functions of Brownian bridges and the upper percentage points can be tabulated as in Chan (1991). Monte Carlo experiments show that the approximation and the power of the test are quite good. We also demonstrate the importance of using our test if the true model has conditional heteroscedasticity.
Persistent Identifierhttp://hdl.handle.net/10722/82792
ISSN
2015 Impact Factor: 1.13
2015 SCImago Journal Rankings: 2.801
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorWong, CSen_HK
dc.contributor.authorLi, WKen_HK
dc.date.accessioned2010-09-06T08:33:28Z-
dc.date.available2010-09-06T08:33:28Z-
dc.date.issued1997en_HK
dc.identifier.citationBiometrika, 1997, v. 84 n. 2, p. 407-418en_HK
dc.identifier.issn0006-3444en_HK
dc.identifier.urihttp://hdl.handle.net/10722/82792-
dc.description.abstractThis paper addresses the null distribution of the Lagrange-multiplier statistic for the threshold autoregression with conditional heteroscedasticity. The problem is nonstandard because the threshold parameter is a nuisance parameter which is absent under the null hypothesis. We generalise the results of Chan (1990) and Chan & Tong (1990) to show that the asymptotic null distribution of the Lagrange-multiplier statistic is a functional of a zero-mean Gaussian process. The generalisation is not direct as the conditional variance is changing and the unconditional distribution of the process variable is no longer normal. In some special cases, we can reduce the problem to the asymptotic distribution of certain functions of Brownian bridges and the upper percentage points can be tabulated as in Chan (1991). Monte Carlo experiments show that the approximation and the power of the test are quite good. We also demonstrate the importance of using our test if the true model has conditional heteroscedasticity.en_HK
dc.languageengen_HK
dc.publisherOxford University Press. The Journal's web site is located at http://biomet.oxfordjournals.org/en_HK
dc.relation.ispartofBiometrikaen_HK
dc.rightsBiometrika. Copyright © Oxford University Press.en_HK
dc.subjectConditional heteroscedasticityen_HK
dc.subjectGaussian processen_HK
dc.subjectLagrange-multiplier testen_HK
dc.subjectThreshold time series modelen_HK
dc.titleTesting for threshold autoregression with conditional heteroscedasticityen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0006-3444&volume=84&issue=2&spage=407&epage=418&date=1997&atitle=Testing+for+threshold+autoregression+with+conditional+heteroscedasticityen_HK
dc.identifier.emailLi, WK: hrntlwk@hku.hken_HK
dc.identifier.authorityLi, WK=rp00741en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1093/biomet/84.2.407-
dc.identifier.scopuseid_2-s2.0-0000235574en_HK
dc.identifier.hkuros23530en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-0000235574&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume84en_HK
dc.identifier.issue2en_HK
dc.identifier.spage407en_HK
dc.identifier.epage418en_HK
dc.identifier.isiWOS:A1997XK26000012-
dc.publisher.placeUnited Kingdomen_HK
dc.identifier.scopusauthoridWong, CS=20236705600en_HK
dc.identifier.scopusauthoridLi, WK=14015971200en_HK

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