ESTIMATION OF THE COVARIANCE-MATRIX OF THE LEAST-SQUARES REGRESSION-COEFFICIENTS WHEN THE DISTURBANCE COVARIANCE-MATRIX IS OF UNKNOWN FORM

This paper deals with the problem of estimating the covariance matrix of the least-squares regression coefficients under heteroskedasticity and/or autocorrelation of unknown form. We consider an estimator proposed by White [17] and give a relatively simple proof of its consistency. Our proof is based on more easily verifiable conditions than those of White. An alternative estimator with improved small sample properties is also presented. © 1991, Cambridge University Press. All rights reserved.