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Detecting big structural breaks in large factor models

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dc.affiliation.dptoUC3M. Departamento de Economíaes
dc.contributor.authorChen, Liang
dc.contributor.authorDolado, Juan José
dc.contributor.authorGonzalo, Jesús
dc.contributor.editorUniversidad Carlos III de Madrid. Departamento de Economía
dc.date.accessioned2012-04-10T15:30:30Z
dc.date.available2012-04-10T15:30:30Z
dc.date.issued2011-12
dc.description.abstractTime invariance of factor loadings is a standard assumption in the analysis of large factor models. Yet, this assumption may be restrictive unless parameter shifts are mild (i.e., local to zero). In this paper we develop a new testing procedure to detect big breaks in these loadings at either known or unknown dates. It relies upon testing for parameter breaks in a regression of the first of the r¯ factors estimated by PCA on the remaining r¯ − 1 factors, where r¯ is chosen according to Bai and Ng’s (2002) information criteria. The test fares well in terms of power relative to other recently proposed tests on this issue, and can be easily implemented to avoid forecasting failures in standard factor-augmented (FAR, FAVAR) models where the number of factors is a priori imposed on the basis of theoretical considerations.
dc.format.mimetypeapplication/pdf
dc.identifier.issn2340-5031
dc.identifier.repecwe1141
dc.identifier.urihttps://hdl.handle.net/10016/14000
dc.identifier.uxxiDT/0000000880
dc.language.isoeng
dc.relation.ispartofseriesUC3M Working papers. Economics
dc.relation.ispartofseries11-41
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 España
dc.rights.accessRightsopen access
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subject.ecienciaEconomía
dc.subject.jelC12
dc.subject.jelC33
dc.subject.otherStructural break
dc.subject.otherLarge factor model
dc.subject.otherLoadings
dc.subject.otherPrincipal components
dc.titleDetecting big structural breaks in large factor models
dc.typeworking paper*
dc.type.hasVersionSMUR*
dspace.entity.typePublication
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