出版社：Suntory Toyota International Centres for Economics and Related Disciplines
摘要：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 speci c 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 esti- mator of the memory parameter of a stationary process is consistent and to examine its rate of convergence. We show that these conditions are satis ed for linear processes and a wide class of nonlinear models, among others, signal plus noise processes, nonlinear transforms of a Gaussian process t and EGARCH models. Special cases where the es- timator satis es the central limit theorem are discussed. The nite sample performance of the estimator is investigated in a small Monte-Carlo study.
