A large literature suggests that many individuals do not apply Bayes Rule correctly when making decisions that depend on them correctly pooling prior information and sample data. We replicate and extend a classic experimental study of Bayesian updating from psychology, employing the methods of...

The moderate utility model represents the probability of choosing an option in a pairwise comparison as an increasing function of utility difference divided by a dissimilarity metric. We provide a single, directly testable property that characterizes the model: choices are moderately transitive....

In this paper we show that decision makers who maximize expected utility on a two-dimensional set of the real numbers (i.e., who maximize expected utility on R×R) rather than on the real numbers alone, can act in ways predicted by the Allais paradox. In particular, we show that the ‘common...

This paper proposes a model of expected utility maximization which accounts for the Ellsberg paradox and Machina's extension of it. In the model, decision makers use a ring of hypercomplex numbers, and they do so in order to decompose their beliefs into ‘ambiguous' or ‘unambiguous' parts –...

Upon observing a signal, a Bayesian decision maker updates her probability distribution over the state space, chooses an action, and receives a payoff that depends on the state and the action taken. An information structure determines the set of possible signals and the probability of each...

We propose a multiple-prior model of preferences under ambiguity that provides a unified lens through which to understand different formalizations of ambiguity aversion, as well as context-dependent negative and positive ambiguity attitudes documented in experiments. This model, Boolean...