We examine the design of incentive-compatible screening mechanisms for dynamic environments in which the agents' types follow a (possibly non-Markov) stochastic process, decisions may be made over time and may affect the type process, and payoffs need not be time-separable. We derive a formula...

We argue that a patent system makes collusion among innovators more difficult. Our simple argument is based on two properties of the patent system. First, a patent not only protects against infringement but also against retaliation by former collusion members. Second, a deviator has an equal...

We study repeated Bayesian n-player games in which the players' privately known types evolve according an irreducible Markov chain. Our main result shows that, with communication, any Pareto-efficient payoff vector above a stationary minmax value can be approximated arbitrarily closely in a...