Efficient estimation of a semiparametric partially linear varying coefficient model
Abbreviated Journal Title
series estimation method; partially linear; varying coefficient; asymptotic normality; semiparametric efficiency; GENERALIZED CROSS-VALIDATION; REGRESSION-MODELS; ASYMPTOTIC NORMALITY; LOCAL ASYMPTOTICS; SERIES ESTIMATORS; LONGITUDINAL DATA; CP; Statistics & Probability
In this paper we propose a general series method to estimate a semiparametric partially linear varying coefficient model. We establish the consistency and root n-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.
Annals of Statistics
"Efficient estimation of a semiparametric partially linear varying coefficient model" (2005). Faculty Bibliography 2000s. 4942.