Generalized R-estimators under Conditional heteroscedasticity.

Mukherjee, Kanchan (2007) Generalized R-estimators under Conditional heteroscedasticity. Journal of Econometrics, 141 (2). pp. 383-415. ISSN 0304-4076

[thumbnail of Final_Version(T).pdf]
Preview
PDF (Final_Version(T).pdf)
Final_Version(T).pdf

Download (313kB)

Abstract

In this paper, we extend the classical idea of Rank estimation of parameters from homoscedastic problems to heteroscedastic problems. In particular, we define a class of rank estimators of the parameters associated with the conditional mean function of an autoregressive model through a three-steps procedure and then derive their asymptotic distributions. The class of models considered includes Engel's ARCH model and the threshold heteroscedastic model. The class of estimators includes an extension of Wilcoxon-type rank estimator. The derivation of the asymptotic distributions depends on the uniform approximation of a randomly weighted empirical process by a perturbed empirical process through a very general weight-dependent partitioning argument.

Item Type:
Journal Article
Journal or Publication Title:
Journal of Econometrics
Additional Information:
The final, definitive version of this article has been published in the Journal, Journal of Econometrics 141 (2), 2007, © ELSEVIER.
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/1200/1207
Subjects:
?? rank estimationheteroscedastic modelweighted empirical processuniform approximationhistory and philosophy of scienceeconomics and econometricsapplied mathematicsqa mathematics ??
ID Code:
868
Deposited By:
Deposited On:
20 Dec 2007 12:03
Refereed?:
Yes
Published?:
Published
Last Modified:
04 Mar 2024 00:50