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2009-05-13Buch DOI: 10.18452/4193
Optimal Smoothing for a Computationally and Statistically Efficient Single Index Estimator
dc.contributor.authorXia, Yingcun
dc.contributor.authorHärdle, Wolfgang Karl
dc.contributor.authorLinton, Oliver
dc.date.accessioned2017-06-15T23:55:57Z
dc.date.available2017-06-15T23:55:57Z
dc.date.created2009-05-20
dc.date.issued2009-05-13
dc.identifier.issn1860-5664
dc.identifier.urihttp://edoc.hu-berlin.de/18452/4845
dc.description.abstractIn semiparametric models it is a common approach to under-smooth the nonparametric functions in order that estimators of the finite dimensional parameters can achieve root-n consistency. The requirement of under-smoothing may result as we show from inefficient estimation methods or technical difficulties. Based on local linear kernel smoother, we propose an estimation method to estimate the single-index model without under-smoothing. Under some conditions, our estimator of the single-index is asymptotically normal and most efficient in the semi-parametric sense. Moreover, we derive higher expansions for our estimator and use them to define an optimal bandwidth for the purposes of index estimation. As a result we obtain a practically more relevant method and we show its superior performance in a variety of applications.eng
dc.language.isoeng
dc.publisherHumboldt-Universität zu Berlin, Wirtschaftswissenschaftliche Fakultät
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/
dc.subjectADEeng
dc.subjectAsymptoticseng
dc.subjectBandwidtheng
dc.subjectMAVE methodeng
dc.subjectSemi-parametric efficiencyeng
dc.subject.ddc330 Wirtschaft
dc.titleOptimal Smoothing for a Computationally and Statistically Efficient Single Index Estimator
dc.typebook
dc.identifier.urnurn:nbn:de:kobv:11-10097778
dc.identifier.doihttp://dx.doi.org/10.18452/4193
local.edoc.container-titleSonderforschungsbereich 649: Ökonomisches Risiko
local.edoc.pages33
local.edoc.type-nameBuch
local.edoc.container-typeseries
local.edoc.container-type-nameSchriftenreihe
local.edoc.container-volume2009
local.edoc.container-issue28
local.edoc.container-year2009
local.edoc.container-erstkatid2195055-6

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