@techreport{NBERt0183,
 title = "Another Heteroskedasticity and Autocorrelation Consistent Covariance    Matrix Estimator",
 author = "Kenneth D. West",
 institution = "National Bureau of Economic Research",
 type = "Working Paper",
 series = "Technical Working Paper Series",
 number = "183",
 year = "1995",
 month = "July",
 URL = "http://www.nber.org/papers/t0183",
 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.},
}