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. EM (497). Suntory and Toyota International Centres for Economics and Related Disciplines, London, UK.

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Abstract

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 are 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 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 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:	Monograph (Discussion Paper)
Official URL:	http://sticerd.lse.ac.uk
Additional Information:	© 2006 Violetta Dalla, Liudas Giraitis and Javier Hidalgo
Divisions:	STICERD Economics
Subjects:	H Social Sciences > HB Economic Theory Q Science > QA Mathematics
JEL classification:	C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods: General > C14 - Semiparametric and Nonparametric Methods C - Mathematical and Quantitative Methods > C2 - Econometric Methods: Single Equation Models; Single Variables > C22 - Time-Series Models
Date Deposited:	09 Jul 2008 11:37
Last Modified:	01 Dec 2024 07:00
URI:	http://eprints.lse.ac.uk/id/eprint/6813

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