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 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...

Foster and Hart propose a measure of riskiness for discrete random variables. Their defining equation has no solution for many common continuous distributions. We show how to extend consistently the definition of riskiness to continuous random variables. For many continuous random variables, the...

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...

Foster and Hart propose a measure of riskiness for discrete random variables. Their defining equation has no solution for many common continuous distributions. We show how to extend consistently the definition of riskiness to continuous random variables. For many continuous random variables, the...

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...

Consider repeated two-player games with perfect monitoring and discounting. We provide an algorithm that computes the set V* of payoff pairs of all pure-strategy subgame perfect equilibria with public randomization. The algorithm provides significant efficiency gains over the existing...

This paper extends a family of well-known stability theorems for monotone economies to a significantly larger class of models. We provide a set of general conditions for existence, uniqueness and stability of stationary distributions when monotonicity holds. The conditions in our main result are...