Abstract submitted to the ESRA Conference, Prague, June 2007
An estimator is derived for the mean squared error (MSE) of the empirical Bayes and composite estimator of the local-area mean in the standard small-area setting. The motivation for it is that the inferential target is a fixed quantity (not altered in hypothetical replications), whereas its model representation is by a random variable. The MSE estimator is a composition of the established estimator based on the conditional expectation of the random deviation associated with the area and a naive estimator of the design-based MSE. Its performance is assessed by simulations. Variants of this MSE estimator are explored and some extensions outlined. The advantage of composition of estimators over choice among them as alternatives is emphasised throughout.
Based on a paper to appear in Survey Methodology in 2007