We study the alternating-offers bargaining problem of assigning an indivisible and commonly valued object to one of two players in return for some payment among players. The players are asymmetrically informed about the object's value and have veto power over any settlement. There is no...

We study the alternating-offer bargaining problem of sharing a common value pie under incomplete information on both sides and no depreciation between two identical players. We characterise the essentially unique perfect Bayesian equilibrium of this game which turns out to be in gradually...

We study mechanism design in non-Bayesian settings of incomplete information, when the designer has no information about the players, and the players have arbitrary, heterogeneous, first-order, and possibilistic beliefs about their opponents' payoff types.

We study the alternating-offer bargaining problem of sharing a common value pie under incomplete information on both sides and no depreciation between two identical players. We characterise the essentially unique perfect Bayesian equilibrium of this game which turns out to be in gradually...

We study the alternating-offers bargaining problem of assigning an indivisible and commonly valued object to one of two players in return for some payment among players. The players are asymmetrically informed about the object’s value and have veto power over any settlement. There is no...

For an incomplete-information model of public-good provision with interim participation constraints, we show that efficient outcomes can be approximated, with approximately full surplus extraction, when there are many agents and each agent is informationally small. The result holds even if...

We provide conditions to allow modelling situations of asymmetric information in a tractable manner. In addition, we show a novel relationship between certain games of asymmetric information and corresponding games of symmetric information. This framework establishes links between certain games...

We describe a methodology for making counterfactual predictions when the information held by strategic agents is a latent parameter. The analyst observes behavior which is rationalized by a Bayesian model in which agents maximize expected utility, given partial and differential information...

In contexts in which players have no priors, we analyze a learning process based on ex-post regret as a guide to understand how to play games of incomplete information under private values. The conclusions depend on whether players interact within a fixed set (fixed matching) or they are...