Asymptotic Theory for Zero Energy Density Estimation with Nonparametric Regression Applications

Qiying Wang () and Peter Phillips

No 1687, Cowles Foundation Discussion Papers from Cowles Foundation for Research in Economics, Yale University

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 (search for similar items in EconPapers)
JEL-codes: C14 C22 (search for similar items in EconPapers)
Pages: 24 pages
Date: 2009-01
Note: CFP 1319
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Published in Econometric Theory (2011), 27(2): 235-259

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