Edgeworth expansions for spectral density estimates and studentized sample mean

Velasco, Carlos; Robinson, Peter M.

Publication:
Edgeworth expansions for spectral density estimates and studentized sample mean

dc.affiliation.dpto	UC3M. Departamento de Economía	es
dc.contributor.author	Velasco, Carlos
dc.contributor.author	Robinson, Peter M.
dc.date.accessioned	2009-04-15T10:15:17Z
dc.date.available	2009-04-15T10:15:17Z
dc.date.issued	2001
dc.description.abstract	We establish valid Edgeworth expansions for the distribution of smoothed nonparametric spectral estimates, and of studentized versions of linear statistics such as the sample mean, where the studentization employs such a nonparametric spectral estimate. Particular attention is paid to the spectral estimate at zero frequency and, correspondingly, the studentized sample mean, to reflect econometric interest in autocorrelation-consistent or long-run variance estimation. Our main focus is on stationary Gaussian series, though we discuss relaxation of the Gaussianity assumption. Only smoothness conditions on the spectral density that are local to the frequency of interest are imposed. We deduce empirical expansions from our Edgeworth expansions designed to improve on the normal approximation in practice and also deduce a feasible rule of bandwidth choice.
dc.description.status	Publicado
dc.format.mimetype	application/pdf
dc.identifier.bibliographicCitation	Econometric Theory, 2001, 17, 3, p. 497-539
dc.identifier.issn	1469-4360
dc.identifier.uri	https://hdl.handle.net/10016/3970
dc.language.iso	eng
dc.publisher	Cambridge University Press
dc.rights	Atribución-NoComercial-SinDerivadas 3.0 España
dc.rights.accessRights	open access
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subject.eciencia	Economía
dc.title	Edgeworth expansions for spectral density estimates and studentized sample mean
dc.type	research article	*
dc.type.review	PeerReviewed
dspace.entity.type	Publication