The restricted maximum likelihood is preferred by many to the full maximum likelihood for estimation with variance component and other random coefficient models, because the variance estimator is unbiased. It is shown that this unbiasedness is accompanied in some balanced designs by an inflation of the mean squared error. An estimator of the cluster-level variance that is uniformly more efficient than the full maximum likelihood is derived. Estimators of the variance ratio are also studied.