Robust Covariance Matrix Estimation with Data-Dependent VAR Prewhitening Order

Wouter den Haan and Andrew Levin
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Wouter den Haan: University of Amsterdam
Andrew Levin: Federal Reserve Board of Governors
Authors registered in the RePEc Author Service: Wouter Denhaan ()

No 2000-11, University of California at San Diego, Economics Working Paper Series from Department of Economics, UC San Diego

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.

Keywords: VAR; covariance matrix estimation (search for similar items in EconPapers)
Date: 2000-06-01
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Working Paper: Robust Covariance Matrix Estimation with Data-Dependent VAR Prewhitening Order (2000)
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