Publication Type
Journal Article
Version
publishedVersion
Publication Date
8-2012
Abstract
We analyze the applicability of standard normal asymptotic theory for linear process models near the boundary of stationarity. Limit results are given for estimation of the mean, autocovariance and autocorrelation functions within the broad region of stationarity that includes near boundary cases which vary with the sample size. The rate of consistency and the validity of the normal asymptotic approximation for the corresponding estimators is determined both by the sample size n and a parameter measuring the proximity of the model to the unit root boundary. (C) 2012 Elsevier B.V. All rights reserved.
Keywords
Asymptotic normality, Integrated periodogram, Linear process, Local to unity, Localizing coefficient
Discipline
Econometrics
Research Areas
Econometrics
Publication
Journal of Econometrics
Volume
169
Issue
2
First Page
166
Last Page
178
ISSN
0304-4076
Identifier
10.1016/j.jeconom.2012.01.020
Publisher
Elsevier
Citation
GIRAITIS, Liudas and PHILLIPS, Peter C. B..
Mean and Autocovariance Function Estimation Near the Boundary of Stationarity. (2012). Journal of Econometrics. 169, (2), 166-178.
Available at: https://ink.library.smu.edu.sg/soe_research/1831
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/10.1016/j.jeconom.2012.01.020