A nonparametric regression estimator that adapts to error distribution of unknown form

Linton, Oliver and Xiao, Zhijie (2001) A nonparametric regression estimator that adapts to error distribution of unknown form. Econometrics; EM/2001/419 (EM/01/419). Suntory and Toyota International Centres for Economics and Related Disciplines, London, UK.

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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.

Item Type:	Monograph (Discussion Paper)
Official URL:	http://sticerd.lse.ac.uk
Additional Information:	© 2001 the authors
Divisions:	Financial Markets Group STICERD Economics
Subjects:	H Social Sciences > HB Economic Theory
JEL classification:	C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods: General > C14 - Semiparametric and Nonparametric Methods C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods: General > C13 - Estimation C - Mathematical and Quantitative Methods > C2 - Econometric Methods: Single Equation Models; Single Variables > C24 - Truncated and Censored Models
Date Deposited:	27 Apr 2007
Last Modified:	11 Dec 2024 18:29
URI:	http://eprints.lse.ac.uk/id/eprint/2120

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