Efficient estimation of a semiparametric partially linear varying coefficient model

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dc.creatorAhmad, Ibrahim
dc.creatorLeelahanon, Sittisak
dc.creatorLi, Qi
dc.date2005-04-25
dc.date.accessioned2026-07-07T08:06:51Z
dc.date.available2026-07-07T08:06:51Z
dc.descriptionIn this paper we propose a general series method to estimate a semiparametric partially linear varying coefficient model. We establish the consistency and \sqrtn-normality property of the estimator of the finite-dimensional parameters of the model. We further show that, when the error is conditionally homoskedastic, this estimator is semiparametrically efficient in the sense that the inverse of the asymptotic variance of the estimator of the finite-dimensional parameter reaches the semiparametric efficiency bound of this model. A small-scale simulation is reported to examine the finite sample performance of the proposed estimator, and an empirical application is presented to illustrate the usefulness of the proposed method in practice. We also discuss how to obtain an efficient estimation result when the error is conditional heteroskedastic.
dc.descriptionPublished at http://dx.doi.org/10.1214/009053604000000931 in the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org)
dc.identifierhttps://arxiv.org/abs/math/0504510
dc.identifierhttp://arxiv.org/abs/math/0504510
dc.identifierAnnals of Statistics 2005, Vol. 33, No. 1, 258-283
dc.identifierdoi:10.1214/009053604000000931
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/130747
dc.subjectStatistics Theory
dc.subject62G08. (Primary)
dc.titleEfficient estimation of a semiparametric partially linear varying coefficient model
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