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Consistent estimation of the memory parameter for nonlinear time series

Dalla, Violetta, Giraitis, Liudas and Hidalgo, Javier (2006) Consistent estimation of the memory parameter for nonlinear time series. Journal of Time Series Analysis, 27 (2). pp. 211-251. ISSN 0143-9782

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Identification Number: 10.1111/j.1467-9892.2005.00464.x


For linear processes, semiparametric estimation of the memory parameter, based on the log-periodogram and local Whittle estimators, has been exhaustively examined and their properties well established. However, except for some specific cases, little is known about the estimation of the memory parameter for nonlinear processes. The purpose of this paper is to provide the general conditions under which the local Whittle estimator of the memory parameter of a stationary process is consistent and to examine its rate of convergence. We show that these conditions are satisfied for linear processes and a wide class of nonlinear models, among others, signal plus noise processes, nonlinear transforms of a Gaussian process ξt and exponential generalized autoregressive, conditionally heteroscedastic (EGARCH) models. Special cases where the estimator satisfies the central limit theorem are discussed. The finite-sample performance of the estimator is investigated in a small Monte Carlo study.

Item Type: Article
Official URL:
Additional Information: © 2006 John Wiley & Sons, Inc
Divisions: Economics
Subjects: Q Science > QA Mathematics
Date Deposited: 19 Apr 2011 14:58
Last Modified: 16 May 2024 00:31

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