Nonparametric Transformation to White Noise

Oliver Linton and Enno Mammen

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

Abstract: We consider a semiparametric distributed lag model in which the "news impact curve" m isnonparametric but the response is dynamic through some linear filters. A special case ofthis is a nonparametric regression with serially correlated errors. We propose an estimatorof the news impact curve based on a dynamic transformation that produces white noiseerrors. This yields an estimating equation for m that is a type two linear integral equation.We investigate both the stationary case and the case where the error has a unit root. In thestationary case we establish the pointwise asymptotic normality. In the special case of anonparametric regression subject to time series errors our estimator achieves efficiencyimprovements over the usual estimators, see Xiao, Linton, Carroll, and Mammen (2003). Inthe unit root case our procedure is consistent and asymptotically normal unlike the standardregression smoother. We also present the distribution theory for the parameter estimates,which is non-standard in the unit root case. We also investigate its finite sampleperformance through simulation experiments.

Keywords: Efficiency; Inverse Problem; Kernel Estimation; Nonparametric regression; Time Series; Unit Roots. (search for similar items in EconPapers)
JEL-codes: C14 (search for similar items in EconPapers)
Date: 2006-08
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Citations: View citations in EconPapers (4)

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Related works:
Journal Article: Nonparametric transformation to white noise (2008)
Working Paper: Nonparametric transformation to white noise (2006)
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Persistent link: https://EconPapers.repec.org/RePEc:cep:stiecm:503

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