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...

We propose two novel axioms for qualitative probability spaces (Bernstein, 1917; de Finetti, 1937; Koopman, 1940; Savage, 1954): (i) unlikely atoms, which requires that there is an event containing no atoms that is at least as likely as its complement; and (ii) third-order atom-swarming, which requires that...

Considerable evidence shows that people have optimistic beliefs about future outcomes. I present an axiomatic model of wishful thinking (WT), in which an endowed alternative, or status quo, influences the agent's beliefs over states and thus induces such optimism. I introduce a behavioral axiom...

We commonly think of information as an instrument for better decisions, yet evidence suggests that people often decline free information in non-strategic scenarios. This paper provides a theory for how a dynamically-consistent decision maker can be averse to partial information as a consequence...

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...

We introduce a model of random ambiguity aversion. Choice is stochastic due to unobserved shocks to both information and ambiguity aversion. This is modeled as a random set of beliefs in the maxmin expected utility model of Gilboa and Schmeidler (1989). We characterize the model and show that...

This paper studies static rational inattention problems with multiple actions and multiple shocks. We solve for the optimal signals chosen by agents and provide tools to interpret information processing. By relaxing restrictive assumptions previously used to gain tractability, we allow agents...

We consider a platform which provides probabilistic forecasts to a customer using some algorithm. We introduce a concept of miscalibration, which measures the discrepancy between the forecast and the truth. We characterize the platform's optimal equilibrium when it incurs some cost for...

We study sequential search without priors. Our interest lies in decision rules that are close to being optimal under each prior and after each history. We call these rules robust. The search literature employs optimal rules based on cutoff strategies, and these rules are not robust. We derive...

I propose an axiomatic framework for belief revision when new information is qualitative, of the form "event A is at least as likely as event B." My decision maker need not have beliefs about the joint distribution of the signal she will receive and the payoff-relevant states. I propose three...