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Testing for cointegration using induced-order statistics

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dc.affiliation.dptoUC3M. Departamento de Economíaes
dc.contributor.authorEscribano, Álvaro
dc.contributor.authorSantos, T.
dc.contributor.authorSipols, Ana E.
dc.date.accessioned2009-02-17T14:53:18Z
dc.date.available2009-02-17T14:53:18Z
dc.date.issued2008
dc.description.abstractIn this paper we explore the usefulness of induced-order statistics in the characterization of integrated series and of cointegration relationships. We propose a non-parametric test statistic for testing the null hypothesis of two independent random walks against wide cointegrating alternatives including monotonic nonlinearities and certain types of level shifts in the cointegration relationship. We call our testing device the induced-order Kolmogorov?Smirnov cointegration test (KS), since it is constructed from the induced-order statistics of the series, and we derive its limiting distribution. This non-parametric statistic endows the test with a number of desirable properties: invariance to monotonic transformations of the series, and robustness for the presence of important parameter shifts. By Monte Carlo simulations we analyze the small sample properties of this test. Our simulation results show the robustness of the induced order cointegration test against departures from linear and constant parameter models.
dc.description.statusPublicado
dc.format.mimetypetext/plain
dc.format.mimetypeapplication/pdf
dc.identifier.bibliographicCitationComputational Statistics, 2008, vol. 23, nº 1, p. 131-151
dc.identifier.doi10.1007/s00180-007-0081-9
dc.identifier.issn1613-9658
dc.identifier.urihttps://hdl.handle.net/10016/2585
dc.language.isoeng
dc.language.isoeng
dc.publisherSpringer
dc.relation.publisherversionhttp://www.springerlink.com/content/x781782321541301/fulltext.pdf
dc.relation.publisherversionhttp://dx.doi.org/10.1007/s00180-007-0081-9
dc.rights© Springer-Verlag
dc.rights.accessRightsopen access
dc.subject.ecienciaEconomía
dc.subject.otherUnit root tests
dc.subject.otherCointegration tests
dc.subject.otherNonlinearity
dc.subject.otherRobustness
dc.subject.otherInduced order statistics
dc.subject.otherEngle and Granger test
dc.titleTesting for cointegration using induced-order statistics
dc.typeresearch article*
dc.type.reviewPeerReviewed
dspace.entity.typePublication
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