Abstract
The Stein, that one could improve frequentist risk by combining “independent” problems, has long been an intriguing paradox to statistics. We briefly review the Bayesian view of the paradox, and indicate that previous justifications of the Stein effect, through concerns of “Bayesian robustness,” were misleading. In the course of doing so, several existing robust Bayesian and Stein-effect estimators are compared for a variety of situations.