Conditional Quantile Estimation and Inference for Arch Models

Roger Koenker and Quanshui Zhao

Econometric Theory, 1996, vol. 12, issue 05, pages 793-813

Abstract: Quantile regression methods are suggested for a class of ARCH models. Because conditional quantiles are readily interpretable in semiparametric ARCH models and are inherendy easier to estimate robustly than population moments, they offer some advantages over more familiar methods based on Gaussian likelihoods. Related inference methods, including the construction of prediction intervals, are also briefly discussed.

Date: 1996
View citations in EconPapers

Downloads: (external link)
http://journals.cambridge.org/abstract_S0266466600007167 link to article abstract page (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: http://EconPapers.repec.org/RePEc:cup:etheor:v:12:y:1996:i:05:p:793-813_00

Access Statistics for this article

More articles in Econometric Theory from Cambridge University Press
Address: The Edinburgh Building, Shaftesbury Road, Cambridge CB2 2RU UK
Series data maintained by Mike Eden ().