This paper shows that a seemingly simple assumption, regarding the time horizon of economic agents, can reconcile the puzzling long run price dynamics of exhaustible resources such as oil, gas and metals. It does so by exploring the possibility that economic agents use a rolling planning...

When should retailers offer promotions with uncertain rewards? The current research investigates this question and finds there are instances when uncertain incentives may seem more attractive than their expected value. For example, a lottery between small and large rewards may even be as...

Experimental evidence suggests that individuals are more risk averse when they perceive risk that is gradually resolved over time. We address these findings by studying a decision maker (DM) who has recursive, non-expected utility preferences over compound lotteries. DM has preferences for...

We study a decision maker (DM) who has recursive preferences over compound lotteries and who cares about the way uncertainty is resolved over time. DM has preferences for one-shot resolution of uncertainty (PORU) if he always prefers any compound lottery to be resolved in a single stage. We...

We introduce a model in which agents observe signals about the state of the world, and some signals are open to interpretation. Our decision makers first interpret each signal based on their current belief and then form a posterior on the sequence of interpreted signals. This ‘double...

Building upon the works of Anscombe and Aumann (1963) and Karni and Schmeidler (1981), we develop a general axiomatic theory of quantifiable beliefs - a form of probabilistic sophistication that does not preclude state-dependent preferences and does not require the reduction of compound...

A major theme in behavioral economics focuses on experimental evidence that individuals learn from the choice problems they face and consequently violate the consistency requirements of revealed preference theory. Despite the experimental evidence, the testable implications of such contextual...

The properties of information, including "information uncertainty", can be understood only Bayesianly. Common formulations that define information uncertainty in terms of just statistical "precision" (i.e. sampling variance), or any one estimator characteristic (e.g. bias), are inadequate for...