File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)
Supplementary

Article: F-tests for seasonal differencing with a break-point

TitleF-tests for seasonal differencing with a break-point
Authors
Issue Date1997
PublisherElsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/jspi
Citation
Journal of Statistical Planning and Inference, 1997, v. 65, p. 87-107 How to Cite?
AbstractThe classification between stochastic trend stationarity and deterministic broken trend stationarity is important because incorrect inferences can follow if a stationary series with a broken trend is incorrectly classified as integrated. In this paper, we consider joint tests for regular and seasonal unit roots null hypothesis against broken trend stationarity alternatives where the location of the break is known or unknown. Based on the F-test proposed by Hasza and Fuller (1982, Ann. Statist. 10, 1209–1216), we develop testing procedures for distinguishing these two types of process. The asymptotic distributions of test statistics are derived as functions of Wiener processes. A response surface regression analysis directed to relating the finite sample distributions and the breaking position is studied. Simulation experiments suggest that the power of the test is reasonable. The testing procedure is illustrated by the Canadian consumer price index series.
Persistent Identifierhttp://hdl.handle.net/10722/83056
ISSN
2015 Impact Factor: 0.727
2015 SCImago Journal Rankings: 1.090
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorNg, TMen_HK
dc.contributor.authorLi, WKen_HK
dc.date.accessioned2010-09-06T08:36:25Z-
dc.date.available2010-09-06T08:36:25Z-
dc.date.issued1997en_HK
dc.identifier.citationJournal of Statistical Planning and Inference, 1997, v. 65, p. 87-107en_HK
dc.identifier.issn0378-3758en_HK
dc.identifier.urihttp://hdl.handle.net/10722/83056-
dc.description.abstractThe classification between stochastic trend stationarity and deterministic broken trend stationarity is important because incorrect inferences can follow if a stationary series with a broken trend is incorrectly classified as integrated. In this paper, we consider joint tests for regular and seasonal unit roots null hypothesis against broken trend stationarity alternatives where the location of the break is known or unknown. Based on the F-test proposed by Hasza and Fuller (1982, Ann. Statist. 10, 1209–1216), we develop testing procedures for distinguishing these two types of process. The asymptotic distributions of test statistics are derived as functions of Wiener processes. A response surface regression analysis directed to relating the finite sample distributions and the breaking position is studied. Simulation experiments suggest that the power of the test is reasonable. The testing procedure is illustrated by the Canadian consumer price index series.-
dc.languageengen_HK
dc.publisherElsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/jspien_HK
dc.relation.ispartofJournal of Statistical Planning and Inferenceen_HK
dc.rightsJournal of Statistical Planning and Inference. Copyright © Elsevier BV.en_HK
dc.titleF-tests for seasonal differencing with a break-pointen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0378-3758&volume=65&spage=87&epage=107&date=1997&atitle=F-tests+for+seasonal+differencing+with+a+break-pointen_HK
dc.identifier.emailLi, WK: hrntlwk@hkucc.hku.hken_HK
dc.identifier.authorityLi, WK=rp00741en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1016/S0378-3758(97)00053-0-
dc.identifier.scopuseid_2-s2.0-0031498322-
dc.identifier.hkuros29798en_HK
dc.identifier.isiWOS:000071469600005-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats