More efficient kernel estimation in nonparametric regression with autocorrelated errors

Carroll, Raymond J, Linton, Oliver, Mammen, Enno and Xiao, Zhijie (2002) More efficient kernel estimation in nonparametric regression with autocorrelated errors. Econometrics; EM/2002/435 (EM/02/435). Suntory and Toyota International Centres for Economics and Related Disciplines, London, UK.

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Abstract

We propose a modification of kernel time series regression estimators that improves efficiency when the innovation process is autocorrelated. The procedure is based on a pre-whitening transformation of the dependent variable that has to be estimated from the data. We establish the asymptotic distribution of our estimator under weak dependence conditions. It is shown that the proposed estimation procedure is more efficient than the conventional kernel method. We also provide simulation evidence to suggest that gains can be achieved in moderate sized samples.

Item Type:	Monograph (Discussion Paper)
Official URL:	http://sticerd.lse.ac.uk
Additional Information:	© 2002 the authors
Divisions:	Financial Markets Group Economics STICERD
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
Date Deposited:	27 Apr 2007
Last Modified:	11 Dec 2024 18:31
URI:	http://eprints.lse.ac.uk/id/eprint/2017

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