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Estimating the number of common factors in serially dependent approximate factor models

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dc.contributor.authorGreenaway-McGrevy, Ryan-
dc.contributor.authorHan, Chirok-
dc.contributor.authorSul, Donggyu-
dc.date.accessioned2021-09-06T15:58:07Z-
dc.date.available2021-09-06T15:58:07Z-
dc.date.created2021-06-18-
dc.date.issued2012-09-
dc.identifier.issn0165-1765-
dc.identifier.urihttps://scholar.korea.ac.kr/handle/2021.sw.korea/107536-
dc.description.abstractA simple data-dependent filtering method is proposed before applying the Bai-Ng method to estimate the number of common factors in the conventional approximate factor model. The asymptotic justification is provided and the finite-sample performance is examined. Published by Elsevier B.V.-
dc.languageEnglish-
dc.language.isoen-
dc.publisherELSEVIER SCIENCE SA-
dc.titleEstimating the number of common factors in serially dependent approximate factor models-
dc.typeArticle-
dc.contributor.affiliatedAuthorHan, Chirok-
dc.identifier.doi10.1016/j.econlet.2012.03.031-
dc.identifier.scopusid2-s2.0-84861897393-
dc.identifier.wosid000308449600073-
dc.identifier.bibliographicCitationECONOMICS LETTERS, v.116, no.3, pp.531 - 534-
dc.relation.isPartOfECONOMICS LETTERS-
dc.citation.titleECONOMICS LETTERS-
dc.citation.volume116-
dc.citation.number3-
dc.citation.startPage531-
dc.citation.endPage534-
dc.type.rimsART-
dc.type.docTypeArticle-
dc.description.journalClass1-
dc.description.journalRegisteredClassssci-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaBusiness & Economics-
dc.relation.journalWebOfScienceCategoryEconomics-
dc.subject.keywordAuthorFactor model-
dc.subject.keywordAuthorPrewhitening-
dc.subject.keywordAuthorLeast squares dummy variable (LSDV) filter-
dc.subject.keywordAuthorFactor number estimation-
dc.subject.keywordAuthorCross-section dependence-
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