Publication Type

Journal Article

Publication Date

4-2011

Abstract

A local limit theorem is given for the sample mean of a zero energy function of a nonstationary time series involving twin numerical sequences that pass to infinity. The result is applicable in certain nonparametric kernel density estimation and regression problems where the relevant quantities are functions of both sample size and bandwidth. An interesting outcome of the theory in nonparametric regression is that the linear term is eliminated from the asymptotic bias. In consequence and in contrast to the stationary case, the Nadaraya-Watson estimator has the same limit distribution (to the second order including bias) as the local linear nonparametric estimator.

Keywords

Brownian Local time, Cointegration, Integrated process, Local time density estimation, Nonlinear functionals, Nonparametric regression, Unit root, Zero energy functional

Discipline

Econometrics

Research Areas

Econometrics

Publication

Econometric Theory

Volume

27

Issue

2

First Page

235

Last Page

259

ISSN

0266-4666

Identifier

10.1017/S0266466610000277

Publisher

Cambridge University Press (CUP): HSS Journals

Copyright Owner and License

Authors

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Additional URL

http://doi.org/10.1017/S0266466610000277

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Econometrics Commons

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