More Efficient Kernel Estimation in Nonparametric Regression with Autocorrelated Errors

Raymond J Carroll, Oliver Linton, Enno Mammen and Zhijie Xiao

STICERD - Econometrics Paper Series from Suntory and Toyota International Centres for Economics and Related Disciplines, LSE

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.

Keywords: Backfitting; efficiency; kernel estimation; time series. (search for similar items in EconPapers)
Date: 2002-06
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Citations: View citations in EconPapers (2)

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Related works:
Working Paper: More Efficient Kernel Estimation in Nonparametric Regression with Autocorrelated Errors (2002)
Working Paper: More efficient kernel estimation in nonparametric regression with autocorrelated errors (2002)
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Persistent link: https://EconPapers.repec.org/RePEc:cep:stiecm:435

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