Another Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimator / Kenneth D. West.

By:

West, Kenneth D

Contributor(s):

National Bureau of Economic Research

Material type: Text

TextSeries: Technical Working Paper Series (National Bureau of Economic Research) ; no. t0183.Publication details: Cambridge, Mass. National Bureau of Economic Research 1995.Description: 1 online resource: illustrations (black and white)Online resources:

Available additional physical forms:

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Abstract: A þT consistent estimator of a heteroskedasticity and autocorrelation consistent covariance matrix estimator is proposed and evaluated. The relevant applications are ones in which the regression disturbance follows a moving average process of known order. In a system of þ equations, this `MA-þ' estimator entails estimation of the moving average coefficients of an þ-dimensional vector. Simulations indicate that the MA-þ estimator's finite sample performance is better than that of the estimators of Andrews and Monahan (1992) and Newey and West (1994) when cross-products of instruments and disturbances are sharply negatively autocorrelated, comparable or slightly worse otherwise.

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July 1995.

A þT consistent estimator of a heteroskedasticity and autocorrelation consistent covariance matrix estimator is proposed and evaluated. The relevant applications are ones in which the regression disturbance follows a moving average process of known order. In a system of þ equations, this `MA-þ' estimator entails estimation of the moving average coefficients of an þ-dimensional vector. Simulations indicate that the MA-þ estimator's finite sample performance is better than that of the estimators of Andrews and Monahan (1992) and Newey and West (1994) when cross-products of instruments and disturbances are sharply negatively autocorrelated, comparable or slightly worse otherwise.