Nonparametric frequency domain analysis of nonstationary multivariate time series

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dc.contributor.author Velasco, Carlos
dc.date.accessioned 2009-06-05T12:40:35Z
dc.date.available 2009-06-05T12:40:35Z
dc.date.issued 2003-09
dc.identifier.bibliographicCitation Journal of Statistical Planning and Inference. 2003, vol. 116, nº 1, p. 209-247
dc.identifier.issn 0378-3758
dc.identifier.uri http://hdl.handle.net/10016/4357
dc.description.abstract We analyse the properties of nonparametric spectral estimates when applied to long memory and trending nonstationary multiple time series. We show that they estimate consistently a generalized or pseudo-spectral density matrix at frequencies both close and away from the origin and we obtain the asymptotic distribution of the estimates. Using adequate data tapers this technique is consistent for observations with any degree of nonstationarity, including polynomial trends. We propose an estimate of the degree of fractional cointegration for possibly nonstationary series based on coherence estimates around zero frequency and analyse its finite sample properties in comparison with residual-based inference. We apply this new semiparametric estimate to an example vector time series.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher Elsevier
dc.rights © Elsevier
dc.subject.other Long memory
dc.subject.other Long-range dependence
dc.subject.other Fractional cointegration
dc.subject.other Coherence
dc.subject.other Semiparametric estimation
dc.subject.other Spectral density
dc.title Nonparametric frequency domain analysis of nonstationary multivariate time series
dc.type article
dc.type.review PeerReviewed
dc.description.status Publicado
dc.relation.publisherversion http://dx.doi.org/10.1016/S0378-3758(02)00235-5
dc.subject.eciencia Economía
dc.identifier.doi 10.1016/S0378-3758(02)00235-5
dc.rights.accessRights openAccess
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