Hybrid bootstrap aided unit root testing

Hybrid bootstrap aided unit root testing

ID:40081197

大小:1.59 MB

页数:19页

时间:2019-07-20

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1、ComputStatDOI10.1007/s00180-011-0290-0ORIGINALPAPERHybridbootstrapaidedunitroottestingC.Jentsch·J.-P.Kreiss·P.Mantalos·E.PaparoditisReceived:27November2009/Accepted:24October2011©Springer-Verlag2011AbstractInthispaper,weproposeahybridbootstrapprocedureforaugmentedDickey-Fuller(ADF)testsforthep

2、resenceofaunitroot.Thishybridproposalcom-binesatimedomainparametricautoregressivefittothedataandanonparametriccorrectionappliedinthefrequencydomaintocapturefeaturesthatarepossiblynotrepresentedbytheparametricmodel.Itisknownthatconsiderablesizeandpowerproblemscanoccurinsmallsamplesforunitroottes

3、tinginthepresenceofanMAparameterusingcriticalvaluesoftheasymptoticDickey-Fullerdistribution.Theben-efitofthesievebootstrapinthissituationhasbeeninvestigatedbyChangandPark(JTimeSerAnal24:379–400,2003).Theyshowedasymptoticvalidityaswellassubstantialimprovementsforsmallsamplesizes,buttheactualsize

4、softheirbootstraptestswerestillquitefarawayfromthenominalsize.ThefinitesampleperformancesofourprocedureareextensivelyinvestigatedthroughMonteCarlosimulationsandcomparedtothesievebootstrapapproach.Regardingthesizeofthetests,ourresultsshowthatthehybridbootstrapremarkablyoutperformsthesievebootstr

5、ap.KeywordsHybridbootstrap·Sievebootstrap·Unitroottesting·ADFtestsC.JentschDepartmentofEconomics,UniversityofMannheim,L7,3-5,68131Mannheim,GermanyJ.-P.KreissInstitutfürMathematischeStochastik,TechnischeUniversitätBraunschweig,Pockelsstraße14,38106Braunschweig,GermanyP.Mantalos(B)DepartmentofSt

6、atistics,SwedishBusinessSchool,UniversityofÖrebro,70182Örebro,Swedene-mail:panagiotis.mantalos@oru.seE.PaparoditisDepartmentofMathematicsandStatistics,UniversityofCyprus,P.O.Box20537,1678Nicosia,Cyprus123C.Jentschetal.1IntroductionWhenwestudythesmallsamplepropertiesofatestprocedurebycomparingd

7、ifferenttests,twoaspectsareofprimeimportance:(a)findingthetestthathasactualsizeclosesttothenominalsize,and,giventhat(a)holds;(b)findingthetestthathasthegreatestpower.Inmostcases,however,thedistributionoftheteststatisticweuseisknownonlyasy

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