Hostname: page-component-586b7cd67f-rdxmf Total loading time: 0 Render date: 2024-11-30T20:54:34.374Z Has data issue: false hasContentIssue false
  • English
  • Français

VALID EDGEWORTH EXPANSION FOR THE SAMPLE AUTOCORRELATION FUNCTION UNDER LONG RANGE DEPENDENCE

Published online by Cambridge University Press:  07 February 2001

Offer Lieberman ,
Judith Rousseau  and
David M. Zucker
Offer Lieberman
Affiliation:
Technion—Israel Institute of Technology
Judith Rousseau
Affiliation:
University of Paris 5 and CREST-ENSAE
David M. Zucker
Affiliation:
Hebrew University of Jerusalem
Get access Rights & Permissions [Opens in a new window]

Abstract

We prove in this paper the validity of an Edgeworth expansion to the joint distribution of the sample autocorrelations of a stationary Gaussian long memory process. The method of proof relies on a verification of the suitably modified conditions for the validity of a multivariate Edgeworth expansion of Durbin (1980, Biometrika 67, 311–333). A simulation study proves the expansion to be useful and accurate.

Type
Research Article
Information
Econometric Theory , Volume 17 , Issue 1 , February 2001 , pp. 257 - 275
Copyright
© 2001 Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)