This paper studies supermodular mechanism design in environments with arbitrary (finite) type spaces and interdependent valuations. In these environments, the designer may have to use Bayesian equilibrium as a solution concept, because ex-post implementation may not be possible. We propose...

We study a stochastic version of Fudenberg–Tirole's preemption game. Two firms contemplate entering a new market with stochastic demand. Firms differ in sunk costs of entry. If the demand process has no upward jumps, the low cost firm enters first, and the high cost firm follows. If leader's...

Reputations often guide sequential decisions to trust and to reward trust. We consider situations where each player is randomly matched with a partner in every period. One player – the truster – decides whether to trust. If trusted, the other player – the temptee – has a temptation to...

We consider discrete-time learning dynamics in finite strategic form games, and show that games that are close to a potential game inherit many of the dynamical properties of potential games. We first study the evolution of the sequence of pure strategy profiles under better/best response...

We study first- and second-order subjective expectations (beliefs) in strategic decision-making. We elicit probabilistically both first- and second-order beliefs and apply the method to a Hide-and-Seek experiment. We study the relationship between choice and beliefs in terms of whether observed...

We build on research from neurobiology to model the process through which the brain maps outside evidence into decisions. The sensory system encodes information through cell-firing. Cell-firing is measured against a threshold, and an action is triggered depending on whether the threshold is...

Financial, managerial, and medical decisions often involve alternatives whose possible outcomes have uncertain probabilities. In contrast to alternatives whose probabilities are known, these uncertain alternatives offer the benefits of learning. In repeat-choice situations, such learning brings...

Decision makers are often described as seeking higher expected payoffs and avoiding higher variance in payoffs. We provide some necessary and some sufficient conditions for learning rules, that assume the agent has little prior and feedback information about the environment, to reflect such...

Many real-life decisions have to be taken on the basis of probability judgements of which the decision maker is not entirely sure. This paper develops a decision rule for taking such decisions, which incorporates the decision makerʼs confidence in his probability judgements according to the...

A decision maker (DM) considers the acquisition of a multi-attribute object with uncertain qualities which can be discovered at a cost. DM's problem is to decide how much to invest in the discovery and whether to adopt or discard based on partial information. We characterize the solution in some...