Abstract
We consider the implications of choosing weighting matrix (projection) on the asymptotic risk of the restricted GMM and WLS estimators. Decomposing expected square error risk into variance part and squared bias part, we show that for both GMM and WLS its variance part is minimized by choosing classical optimal weighting matrix, whereas the squared bias part is minimized using the weighting matrix chosen for the asymptotic risk function.
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