Nonstationarity-extended Whittle Estimation

dc.creatorShao, Xiaofeng
dc.date2009-03-18
dc.date.accessioned2026-07-07T12:53:37Z
dc.date.available2026-07-07T12:53:37Z
dc.descriptionFor long memory time series models with uncorrelated but dependent errors, we establish the asymptotic normality of the Whittle estimator under mild conditions. Our framework includes the widely used FARIMA models with GARCH-type innovations. To cover nonstationary fractionally integrated processes, we extend the idea of Abadir, Distaso and Giraitis (2007, Journal of Econometrics 141, 1353-1384) and develop the nonstationarity-extended Whittle estimation. The resulting estimator is shown to be asymptotically normal and is more efficient than the tapered Whittle estimator. Finally, the results from a small simulation study are presented to corroborate our theoretical findings.
dc.description32 pages, 3 tables
dc.identifierhttps://arxiv.org/abs/0903.3180
dc.identifierhttp://arxiv.org/abs/0903.3180
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/223685
dc.subjectMethodology
dc.subjectStatistics Theory
dc.titleNonstationarity-extended Whittle Estimation
dc.typetext

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