  This paper characterizes the conditions under which the observed beliefs of a
group of agents are consistent with Bayesian updating. Beliefs are consistent
with Bayesianism if they arise from the application of Bayes' rule given some
subjective distribution for the state and the signals agents observe between
periods. The paper's main finding is that beliefs are consistent with
Bayesianism if and only if the mean of the distribution of posteriors is
uniformly absolutely continuous with respect to the prior. Furthermore, the
paper shows that the existing results on the empirical content of Bayesianism
rely on additional restrictions on permissible subjective distributions, such
as the requirement that agents have correct beliefs about the distribution of
signals.
