The paper incorporates qualitative differences of probabilistic beliefs into a rational (or normatively motivated) decision framework. Probabilistic beliefs can range from objective probabilities to pure guesstimates. The decision maker in the present model takes into account his confidence in...

The standard Bayesian model implies that information can never have a negative value. We put this implication to the proof. Our paper provides the first test of the value (positive or negative) of information under uncertainty. We show that the "Bayesian implication" stands in conflict with the...

This paper studies a problem of choice under uncertainty in which a decision-maker's (DM) choices randomly map to consumption outcomes. The primitive is a binary relation on menus, where a menu is a set of possible ex post outcomes. After the DM selects a menu, nature (not the DM) makes a...

We investigate what it means for one act to be more ambiguous than another. The question is evidently analogous to asking what makes one prospect riskier than another, but beliefs are neither objective nor representable by a unique probability. Our starting point is an abstract class of...

We provide theoretical foundations for several common (nested) representations of intrinsic linear habit formation. Our axiomatization introduces an intertemporal theory of weaning a decision-maker from her habits using the device of compensation. We clarify differences across specifications of...

Evidence shows that (i) people overweight low probabilities and underweight high probabilities, but (ii) ignore events of extremely low probability and treat extremely high probability events as certain. The main alternative decision theories, rank dependent utility (RDU) and cumulative prospect...

Stochastic independence (SI) has a complex status in probability theory. It is not part of the definition of a probability measure, but it is nonetheless an essential property for the mathematical development of this theory, hence a property that any theory on the foundations of probability...

We propose and axiomatize a new model of incomplete preferences under uncertainty, which we call hope-and-prepare preferences. An act is considered more desirable than another when, and only when, both an optimistic evaluation, computed as the welfare level attained in a best-case scenario, and...

Under dynamic random utility, an agent (or population of agents) solves a dynamic decision problem subject to evolving private information. We analyze the fully general and non-parametric model, axiomatically characterizing the implied dynamic stochastic choice behavior. A key new feature...

A decision-maker acquires payoff-relevant information until she reaches her storing capacity, at which point she either terminates the decision-making and chooses an action, or discards some information. By conditioning the probability of termination on the information collected, she controls...