Publication Type
Journal Article
Version
publishedVersion
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
Citation
WANG, Qiying and Peter C. B. PHILLIPS.
Asymptotic Theory for Zero Energy Functionals with Nonparametric Regression Applications. (2011). Econometric Theory. 27, (2), 235-259.
Available at: https://ink.library.smu.edu.sg/soe_research/1822
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1017/S0266466610000277