Location of Repository

Adaptive estimation in ARCH models

By Oliver Linton

Abstract

We construct efficient estimators of the identifiable parameters in a regression model when the errors follow a stationary parametric ARCH(P) process. We do not assume a functional form for the conditional density of the errors, but do require that it be symmetric about zero. The estimators of the mean parameters are adaptive in the sense of Bickel [2]. The ARCH parameters are not jointly identifiable with the error density. We consider a reparameterization of the variance process and show that the identifiable parameters of this process are adaptively estimable

Topics: HB Economic Theory
Publisher: Cambridge University Press
Year: 1993
DOI identifier: 10.1017/S0266466600007970
OAI identifier: oai:eprints.lse.ac.uk:1289
Provided by: LSE Research Online
Download PDF:
Sorry, we are unable to provide the full text but you may find it at the following location(s):
  • http://journals.cambridge.org/... (external link)
  • http://eprints.lse.ac.uk/1289/ (external link)
  • Suggested articles


    To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.