Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation

Donald Andrews ()

Econometrica, 1991, vol. 59, issue 3, 817-58

Abstract: This paper is concerned with the estimation of covariance matrices in the presence of heteroskedasticity and autocorrelation of unknown forms. Currently available estimators that are designed for this context depend upon the choice of a lag truncation parameter and a weighting scheme. No results are available regarding the choice of lag truncation parameter for a fixed sample size, regarding data-dependent automatic lag truncation parameters, or regarding the choice of weighting scheme. This paper addresses these problems. Asymptotically optimal kernel/weighting scheme and bandwidth/lag truncation parameters are obtained. Using these results, data-dependent automatic bandwidth/lag truncation parameters are introduced. Copyright 1991 by The Econometric Society.

Date: 1991
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Related works:
Working Paper: Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation (1989)
Working Paper: Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation (1988)
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