We consider small area estimation under a nested error linear regres-
sion model with measurement errors in the covariates. We propose an objective
Bayesian analysis of the model to estimate the ¯nite population means of the small
areas. In particular, we derive Je®reys' prior for model parameters. We also show
that Je®reys' prior, which is improper, leads, under very general conditions, to a
proper posterior distribution. We have also performed a simulation study where
we have compared the Bayes estimates of the ¯nite population means under the
Je®reys' prior with other Bayesian estimates obtained via the use of the standard
°at prior and with non-Bayesian estimates, i.e., the corresponding empirical Bayes
estimates and the direct estimates.