When making choices, decision makers often either lack information about alternatives or lack the cognitive capacity to analyze every alternative. To capture these situations, we formulate a framework to study behavioral search by utilizing the idea of consideration sets. Consumers engage in a...

We characterize prior-by-prior Bayesian updating using a model proposed by Gilboa, Maccheroni, Marinacci and Schmeidler (2010) that jointly considers objective and subjective rationality. These rationality concepts are subject to the Bewley unanimity rule and maxmin expected utility,...

We propose a model of “choice overload,” which refers to a stronger tendency to select the default option in larger choice problems. Our main finding is a behavioral characterization of an asymmetric regret representation that depicts a decision maker who does not consider the possibility of...

Following Kreps (1979), I consider a decision maker who is uncertain about her future taste. This uncertainty leaves the decision maker with a preference for flexibility: When choosing among menus containing alternatives for future choice, she weakly prefers menus with additional alternatives....

We show how information acquisition costs can be identified using observable choice data. Identifying information costs from behavior is especially relevant when these costs depend on factors-such as time, effort, and cognitive resources-that are difficult to observe directly, as in models of...

Is it possible to guarantee that the mere exposure of a subject to a belief elicitation task will not affect the very same beliefs that we are trying to elicit? In this paper, we introduce mechanisms that make it simultaneously strictly dominant for the subject (a) not to acquire any information...

Motivated by the literature on ``choice overload'', we study a boundedly rational agent whose choice behavior admits a \textit{monotone threshold representation}: There is an underlying rational benchmark, corresponding to maximization of a utility function $v$, from which the agent's choices...