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Adaptive estimation in ARCH models

Linton, Oliver (1993) Adaptive estimation in ARCH models. Econometric Theory, 9 (4). pp. 539-569. ISSN 0266-4666

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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.

Item Type: Article
Official URL: http://journals.cambridge.org/action/displayJourna...
Additional Information: © 1993 Cambridge University Press
Library of Congress subject classification: H Social Sciences > HB Economic Theory
Journal of Economic Literature Classification System: C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods: General > C14 - Semiparametric and Nonparametric Methods
Sets: Departments > Economics
Collections > Economists Online
Rights: http://www.lse.ac.uk/library/usingTheLibrary/academicSupport/OA/depositYourResearch.aspx
Date Deposited: 27 Apr 2007
URL: http://eprints.lse.ac.uk/1289/

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