We show that demanding team incentives to be robust to nonquantifiable uncertainty about the game played by the agents leads to contracts that align the agents' interests. Such contracts have a natural interpretation as team‐based compensation. Under budget balance they reduce to linear contracts, thus identifying profit‐sharing, or equity, as an optimal contract absent a sink or a source of funds. A linear contract also gives the best profit guarantee to an outside residual claimant. These contracts still suffer from the free‐rider problem, but a positive guarantee obtains if and only if the technology known to the contract designer is sufficiently productive.

We consider the value of persistent information in strictly competitive situations, formalized as stochastic zero-sum games where only the maximizer ob-serves the state that evolves according to an ergodic Markov operator. We say that operator Q is better for the maximizer than operator P if the value of the game under Q is higher than under P regardless of the stage game. We show that this defines a partial order on the space of ergodic Markov operators, and provide a full characterization of this partial order. An i.i.d. state is the best case for the informed player; however, a perfectly persistent state is not necessarily the worst case. The analysis relies on a novel characterization of the value of a stochastic game with incomplete information. Our results can alternatively be interpreted as pertaining to the limit of the minmax value in repeated Bayesian games with Markov types. 1.

We study repeated Bayesian games with communication and observable actions in which the players' privately known payoffs evolve according to an irreducible Markov chain whose transitions are independent across players. Our main result implies that, generically, any Pareto-efficient payoff vector above a stationary minmax value can be approximated arbitrarily closely in a perfect Bayesian equilibrium as the discount factor goes to 1. As an intermediate step, we construct an approximately efficient dynamic mechanism for long finite horizons without assuming transferable utility.

We consider learning and signalling in a dynamic Cournot oligopoly where firms have private information about their production costs and only observe the market price, which is subject to unobservable demand shocks. An equilibrium is Markov if play depends on the history only through the firms’ beliefs about costs and calendar time. We characterize symmetric linear Markov equilibria as solutions to a boundary value problem. In every such equilibrium, given a long enough horizon, play converges to the static complete information outcome for the realized costs, but each firm only learns its competitors’ average cost. The weights assigned to costs and beliefs under the equilibrium strategies are non-monotone over time. We explain this by decomposing incentives into signalling and learning, and discuss implications for prices, quantities, and welfare.

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Multiple innovators can and do come up with the same invention independently. A famous case is the telephone: two hours after Alexander Graham Bell filed a patent application for it, another application for the same invention arrived at the patent office. Many scholars, such as Ilkka Rahnasto (2003) and Hal R. Varian et al. (2004), argue that since Bell’s time, simultaneous innovation has become increasingly common. We feel, and our discussions with industry practitioners confirm, that the simultaneous model of innovation characterizes especially network industries such as consumer electronics, the Internet, software, telecommunications, and payment systems, where standardization limits the possible paths for future technologies and so firms concentrate their R&D activities on the same fields. We suggest that simultaneous or independent invention has major implications for intellectual property (IP) policy. In particular, the possibility of simultaneous innovation changes the patenting decision: firms tap patents for a defensive purpose, since the choice is no longer between patenting or resorting to trade secrecy, but between patenting or letting competitors patent. By exploiting the vulnerability of innovative firms to rival innovation, it is possible to design a welfareimproving patent system that induces innovators to patent rather than keep their innovations secret. Taking the simultaneous nature of innovation seriously also changes the way one should think about the relationship between IP and competition policies.