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...

We study how changes to the informativeness of signals in Bayesian games and single‐agent decision problems affect the distribution of equilibrium actions. Focusing on supermodular environments, we provide conditions under which a more precise private signal for one agent leads to an...

A decision maker, named Alice, wants to know if an expert has significant information about payoff-relevant probabilities of future events. The expert, named Bob, either knows this probability almost perfectly or knows nothing about it. Hence, both Alice and the uninformed expert face...

We introduce a learning framework in which a principal seeks to determine the ability of a strategic agent. The principal assigns a test consisting of a finite sequence of tasks. The test is adaptive: each task that is assigned can depend on the agent's past performance. The probability of...

Our understanding of risk preferences can be sharpened by considering their evolutionary basis. The existing literature has focused on two sources of risk: idiosyncratic risk and aggregate risk. We introduce a new source of risk, heritable risk, in which there is a positive correlation between...

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 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...

Among the reasons behind the choice behavior of an individual taking a stochastic form are her potential indifference or indecisiveness between certain alternatives, and/or her willingness to experiment in the sense of occasionally deviating from choosing a best alternative in order to give a...

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...

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...