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Abstract:

Econometrics Paper
A Nonparametric Regression Estimator that Adapts to Error Distribution of Unknown Form
Oliver Linton and Zhijie Xiao
June 2001
Paper No' EM/2001/419:
Full Paper (pdf)

Tags: adaptive estimation; asymptotic expansions; efficiency; kernel; local likelihood estimation; nonparametric regression.

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.