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
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
关键词：Long memory, semiparametric estimation, local Whittle estimator
