Abstract

http://ssrn.com/abstract=235687
 
 

References (36)



 


 



Robust Covariance Matrix Estimation with Data-Dependent VAR Prewhitening Order


Wouter J. Den Haan


University of Amsterdam; Centre for Economic Policy Research (CEPR); Tinbergen Institute

Andrew T. Levin


Federal Reserve Board

June 2000

NBER Working Paper No. t0255

Abstract:     
This paper analyzes the performance of heteroskedasticity-and-autocorrelation-consistent (HAC) covariance matrix estimators in which the residuals are prewhitened using a vector autoregressive (VAR) filter. We highlight the pitfalls of using an arbitrarily fixed lag order for the VAR filter, and we demonstrate the benefits of using a model selection criterion (either AIC or BIC) to determine its lag structure. Furthermore, once data-dependent VAR prewhitening has been utilized, we find negligible or even counter-productive effects of applying standard kernel-based methods to the prewhitened residuals; that is, the performance of the prewhitened kernel estimator is virtually indistinguishable from that of the VARHAC estimator.

Number of Pages in PDF File: 38

working papers series





Download This Paper

Date posted: August 23, 2000  

Suggested Citation

den Haan, Wouter J. and Levin, Andrew T., Robust Covariance Matrix Estimation with Data-Dependent VAR Prewhitening Order (June 2000). NBER Working Paper No. t0255. Available at SSRN: http://ssrn.com/abstract=235687

Contact Information

Wouter J. Den Haan (Contact Author)
University of Amsterdam ( email )
Spui 21
Amsterdam, 1018 WB
Netherlands
HOME PAGE: http://www1.feb.uva.nl/toe/content/people/content/denhaan/pers.htm
Centre for Economic Policy Research (CEPR)
77 Bastwick Street
London, EC1V 3PZ
United Kingdom
Tinbergen Institute ( email )
Burg. Oudlaan 50
Rotterdam, 3062 PA
Netherlands
Andrew Levin
Federal Reserve Board ( email )
20th and C Streets, NW
Washington, DC 20551
United States
202-452-3541 (Phone)
202-452-2301 (Fax)
Feedback to SSRN


Paper statistics
Abstract Views: 815
Downloads: 37
References:  36

© 2014 Social Science Electronic Publishing, Inc. All Rights Reserved.  FAQ   Terms of Use   Privacy Policy   Copyright   Contact Us
This page was processed by apollo1 in 0.297 seconds