A conditional mean squared error of small area estimators

This paper suggests estimating the conditional mean squared error of small area estimators to evaluate their accuracy. This mean squared error is conditional in the sense that it measures the variability with respect to the sampling design for a particular realization of the smoothing model underlying the small area estimators. An unbiased estimators for the conditional mean squared error is easily constructed using Stein's Lemma for the expectation of normal random variables.