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Testing for panel cointegration using common correlated effects estimators

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dc.contributor.authorBanerjee, Anindya
dc.contributor.authorCarrión i Silvestre, Josep Lluís
dc.date.accessioned2018-04-04T08:11:53Z
dc.date.available2018-12-31T06:10:23Z
dc.date.issued2017
dc.date.updated2018-04-04T08:11:53Z
dc.description.abstractSpurious regression analysis in panel data when the time series are cross-section dependent is analyzed in the paper. We show that consistent estimation of the long-run average parameter is possible once we control for cross-section dependence using cross-section averages in the spirit of the common correlated effects approach in Pesaran (2006). This result is used to design a panel cointegration test statistic accounting for cross-section dependence. The performance of the proposal is investigated in comparison with factor-based methods to control for cross-section dependence when strong, semi-weak and weak cross-section dependence may be present.
dc.format.extent27 p.
dc.format.mimetypeapplication/pdf
dc.identifier.idgrec666721
dc.identifier.issn0143-9782
dc.identifier.urihttps://hdl.handle.net/2445/121246
dc.language.isoeng
dc.publisherJohn Wiley & Sons
dc.relation.isformatofVersió postprint del document publicat a: https://doi.org/10.1111/jtsa.12234
dc.relation.ispartofJournal of Time Series Analysis, 2017, vol. 38, num. 4, p. 610-636
dc.relation.urihttps://doi.org/10.1111/jtsa.12234
dc.rights(c) John Wiley & Sons, 2017
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess
dc.sourceArticles publicats en revistes (Econometria, Estadística i Economia Aplicada)
dc.subject.classificationAnàlisi de regressió
dc.subject.classificationAnàlisi de dades de panel
dc.subject.classificationEconometria
dc.subject.otherRegression analysis
dc.subject.otherPanel analysis
dc.subject.otherEconometrics
dc.titleTesting for panel cointegration using common correlated effects estimators
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/acceptedVersion

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Articles publicats en revistes (Econometria, Estadística i Economia Aplicada)