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A Minimax Bias Estimator for OLS Variances under Heteroskedasticity (1405.0716v1)

Published 4 May 2014 in stat.ME, math.ST, and stat.TH

Abstract: Analytic evaluation of heteroskedasticity consistent covariance matrix estimates (HCCME) is difficult because of the complexity of the formulae currently available. We obtain new analytic formulae for the bias of a class of estimators of the covariance matrix of OLS in a standard linear regression model. These formulae provide substantial insight into the properties and performance characteristics of these estimators. In particular, we find a new estimator which minimizes the maximum possible bias and improves substantially on the standard Eicker-White estimate.

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