In standard models of Bayesian learning agents reduce their uncertainty about an eventÂ’s true probability because their consistent estimator concentrates almost surely around this probabilityÂ’s true value as the number of observations becomes large. This paper takes the empirically...

We combine new developments in decision theory with a standard consumption-based asset-pricing framework. In our model the efficient market hypothesis is violated if and only if agentsÂ’ beliefs' express ambiguity about the stochastic process driving economic fundamentals. Asset price...

Aumann (1976) derives his famous we cannot agree to disagree result under the assumption of rational Bayesian learning. Motivated by psychological evidence against this assumption, we develop formal models of optimistically, resp. pessimistically, biased Bayesian learning within the framework of...

Ample psychological evidence suggests that people’s learning behavior is often prone to a "myside bias" or "irrational belief persistence" in contrast to learning behavior exclusively based on objective data. In the context of Bayesian learning such a bias may result in diverging...

This paper experimentally tests whether violations of Savage's (1954) subjective expected utility theory decrease if the ambiguity of an uncertain decision situation is reduced through statistical learning. Because our data does not show such a decrease, existing models which formalize ambiguity...