  Under mild conditions, it is shown the strong consistency of the Bayes
estimator of the density. Moreover, the Bayes risk (for some common loss
functions) of the Bayes estimator of the density (i.e. the posterior predictive
density) reaches zero when the sample size goes to $\infty$. In passing, a
similar result is obtained for the estimation of the sampling distribution.
