Consider two agents who learn the value of an unknown parameter by observing a sequence of private signals. The signals are independent and identically distributed across time but not necessarily across agents. We show that that when each agent's signal space is finite, the agents will commonly...

Consider two agents who learn the value of an unknown parameter by observing a sequence of private signals. The signals are independent and identically distributed across time but not necessarily agents. Does it follow that the agents will commonly learn its value, i.e., that the true value of...

We give a sufficient condition on the type space for revenue equivalence when the set of social alternatives consists of probability distributions over a finite set. Types are identified with real-valued functions that assign valuations to elements of this finite set, and the type space is...

Consider an agent (manager, artist, etc.) who has imperfect private information about his productivity. At the beginning of his career (period 1, short run"), the agent chooses among publicly observable actions that generate imperfect signals of his productivity. The actions can be ranked...

In this paper we compare two different approaches to modeling unawareness: the object-based approach of Board and Chung (2007) and the subjective-state-space approach of Heifetz, Meier and Schipper (2006).

Consider an agent (manager, artist, etc.) who has imperfect private information about his productivity. At the beginning of his career (period 1, short runʺ), the agent chooses among publicly observable actions that generate imperfect signals of his productivity. The actions can be ranked...