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Please use this identifier to cite or link to this item: http://hdl.handle.net/2108/349

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contributor.authorAvarucci, Marco-
contributor.authorMarinucci, Domenico-
date.accessioned2007-07-11T10:50:38Z-
date.available2007-07-11T10:50:38Z-
date.issued2007-03-
identifier.urihttp://ssrn.com/abstract=967397-
identifier.urihttp://hdl.handle.net/2108/349-
description.abstractIn this paper we consider polynomial cointegrating relationships between stationary processes with long range dependence. We express the regression functions in terms of Hermite polynomials and we consider a form of spectral regression around frequency zero. For these estimates, we establish consistency by means of a more general result on continuously averaged estimates of the spectral density matrix at frequency zero.en
format.extent923457 bytes-
format.mimetypeapplication/pdf-
language.isoenen
publisherCEISen
relation.ispartofseriesCEIS Tor Vergata Research Paper; 100en
subjectnonlinear cointegrationen
subjectlong memoryen
subjectHermite polynomialsen
subjectspectral regressionen
subjectdiagram formulaen
subject.classificationSECS-P/05; Econometriaen
titlePolynomial cointegration between stationary processes with long memoryen
typeArticleen
subject.jelC; Mathematical and quantitative methodsen
subject.ams62M15; Spectral analysisen
subject.ams62M10; Time series, auto-correlation, regression, etc.en
subject.ams60G10; Stationary processesen
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