A group of agents with a common prior receive informative signals about an unknown state repeatedly over time. If these signals were public, agents' beliefs would be identical and commonly known. This suggests that if signals were private, then the more correlated these are, the greater the...

We axiomatize a new class of recursive dynamic models that capture subjective constraints on the amount of information a decision maker can obtain, pay attention to, or absorb, via a Markov Decision Process for Information Choice (MIC). An MIC is a subjective decision process that specifies what...

We study Bayesian mechanism design in situations where agents' information may be multi-dimensional, concentrating on mechanisms that lead to efficient allocations. Our main result is that a generalization of the well-known Vickrey-Clarke-Groves mechanism maximizes the planner's "revenue" among...