Information-Theoretic Analysis of Serial Dependence and Cointegration

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dc.contributor.author Aparicio, Felipe M.
dc.contributor.author Escribano, Álvaro
dc.date.accessioned 2009-02-17T16:58:31Z
dc.date.available 2009-02-17T16:58:31Z
dc.date.issued 1998
dc.identifier.bibliographicCitation Studies in Nonlinear Dynamics & Econometrics, 1998, vol.3, nº 3, p. 119-140
dc.identifier.issn 1558-3708
dc.identifier.uri http://hdl.handle.net/10016/2560
dc.description.abstract This paper is devoted to presenting wider characterizations of memory and cointegration in time series, in terms of information-theoretic statistics such as the entropy and the mutual information between pairs of variables. We suggest a nonparametric and nonlinear methodology for data analysis and for testing the hypotheses of long memory and the existence of a cointegrating relationship in a nonlinear context. This new framework represents a natural extension of the linear-memory concepts based on correlations. Finally, we show that our testing devices seem promising for exploratory analysis with nonlinearly cointegrated time series.
dc.format.mimetype text/plain
dc.format.mimetype application/pdf
dc.language.iso eng
dc.language.iso eng
dc.publisher Berkeley Electronic Press
dc.rights © The Berkeley Electronic Press
dc.title Information-Theoretic Analysis of Serial Dependence and Cointegration
dc.type article
dc.type.review PeerReviewed
dc.description.status Publicado
dc.relation.publisherversion http://www.bepress.com/snde/vol3/iss3/art1
dc.subject.eciencia Economía
dc.rights.accessRights openAccess
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