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Title:A nonparametric regression estimator that adapts to error distribution of unknown form PDF Logo
Authors:Linton, Oliver Bruce
Xiao, Zhijie
Issue Date:2001
Series/Report no.:Discussion Papers, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes 2001,33
Abstract:We propose a new estimator for nonparametric regression based on local likelihood estimation using an estimated error score function obtained from the residuals of a preliminary nonparametric regression. We show that our estimator is asymptotically equivalent to the infeasible local maximum likelihood estimator [Staniswalis (1989)], and hence improves on standard kernel estimators when the error distribution is not normal. We investigate the finite sample performance of our procedure on simulated data.
Subjects:Adaptive Estimation
Asymptotic Expansions
Efficiency
Kernel
Local Likelihood Estimation
Nonparametrie Regression
JEL:C13
C14
C24
Persistent Identifier of the first edition:urn:nbn:de:kobv:11-10049681
Document Type:Working Paper
Appears in Collections:Discussion Papers, SFB 373, HU Berlin

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