Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/62875 
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dc.contributor.authorKapetanios, Georgeen
dc.contributor.authorPsaradakis, Zachariasen
dc.date.accessioned2012-09-20T13:00:53Z-
dc.date.available2012-09-20T13:00:53Z-
dc.date.issued2006-
dc.identifier.urihttp://hdl.handle.net/10419/62875-
dc.description.abstractThis paper studies the properties of the sieve bootstrap for a class of linear processes which exhibit strong dependence. The sieve bootstrap scheme is based on residual resampling from autoregressive approximations the order of which increases slowly with the sample size. The first-order asymptotic validity of the sieve bootstrap is established in the case of the sample mean and sample autocovariances. The finite-sample properties of the method are also investigated by means of Monte Carlo experiments.en
dc.language.isoengen
dc.publisher|aQueen Mary University of London, Department of Economics |cLondonen
dc.relation.ispartofseries|aWorking Paper |x552en
dc.subject.jelC10en
dc.subject.jelC22en
dc.subject.jelC50en
dc.subject.ddc330en
dc.subject.keywordAutoregressive approximation, Linear process, Strong dependence, Sieve bootstrap, Stationary processen
dc.titleSieve bootstrap for strongly dependent stationary processes-
dc.typeWorking Paperen
dc.identifier.ppn506651193en
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungenen

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