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Cited 3 time in webofscience Cited 3 time in scopus
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Stationary bootstrapping for semiparametric panel unit root tests

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dc.contributor.authorHwang, Eunju-
dc.contributor.authorShin, Dong Wan-
dc.date.available2020-02-28T09:46:58Z-
dc.date.created2020-02-06-
dc.date.issued2015-03-
dc.identifier.issn0167-9473-
dc.identifier.urihttps://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/10714-
dc.description.abstractFor panels of possible cross-sectional and serial dependency, stationary bootstrapping is applied to construct unit root tests that are valid regardless of the nuisance parameters of such dependency. The tests are semiparametric in that no model structure is imposed on the serial correlation and the cross-sectional correlation. The statistics are Wald tests and t-bar type tests based on the OLSE (ordinary least squares estimator). Residual-based and difference-based stationary bootstrapping are applied to obtain valid critical values of the tests. Both ordinary and recursive mean adjustments are considered. Large sample validity of the bootstrap tests is established for a large time series dimension. A Monte-Carlo simulation compares the proposed tests, yielding some promising tests, i.e., the t-bar type tests based on difference-based bootstrapping and recursive adjustment. (C) 2014 Elsevier B.V. All rights reserved.-
dc.language영어-
dc.language.isoen-
dc.publisherELSEVIER SCIENCE BV-
dc.relation.isPartOfCOMPUTATIONAL STATISTICS & DATA ANALYSIS-
dc.subjectCROSS-SECTIONAL DEPENDENCY-
dc.subjectAUTOREGRESSIVE TIME-SERIES-
dc.titleStationary bootstrapping for semiparametric panel unit root tests-
dc.typeArticle-
dc.type.rimsART-
dc.description.journalClass1-
dc.identifier.wosid000347759700002-
dc.identifier.doi10.1016/j.csda.2014.09.004-
dc.identifier.bibliographicCitationCOMPUTATIONAL STATISTICS & DATA ANALYSIS, v.83, pp.14 - 25-
dc.identifier.scopusid2-s2.0-84908377308-
dc.citation.endPage25-
dc.citation.startPage14-
dc.citation.titleCOMPUTATIONAL STATISTICS & DATA ANALYSIS-
dc.citation.volume83-
dc.contributor.affiliatedAuthorHwang, Eunju-
dc.contributor.affiliatedAuthorShin, Dong Wan-
dc.type.docTypeArticle-
dc.subject.keywordAuthorCross-sectional dependence-
dc.subject.keywordAuthorDifference-based bootstrapping-
dc.subject.keywordAuthorRecursive mean adjustment-
dc.subject.keywordAuthorResidual-based bootstrapping-
dc.subject.keywordPlusCROSS-SECTIONAL DEPENDENCY-
dc.subject.keywordPlusAUTOREGRESSIVE TIME-SERIES-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalResearchAreaMathematics-
dc.relation.journalWebOfScienceCategoryComputer Science, Interdisciplinary Applications-
dc.relation.journalWebOfScienceCategoryStatistics & Probability-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
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