Collaborative Research: Robust Predictions In Games With Private Information

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In many economic environments the participants do not have the same informationabout the relevant aspects of their situation. For example, in a financial market eachinvestor may have different pieces of information about the underlying value of an assetor a company. In product markets, each competiting firm may have private informationabout its cost structure. In auctions, such as the wireless spectrum auctions organizedby the Federal Communications Commission or the offshore oil tracts auctioned off bythe U.S. Department of the Interior, the bidders have private information about theirvaluations and also some, possibly noisy, information about the valuations of theircompetitors.The private information of an agent, whether it is about his/her own valuations or thevaluations of the competing agents will determine the behavior and the strategy of theagent. But in practice, the theoretical and/or empirical analysts do not have a clearunderstanding of what the economic agents know and, in particular, what they do or donot know about each other. The missing and incomplete information si also highlyrelevant from a policy perspective as the supervising or regulatory authority in manymarkets face similar informational constraints.The PIs develop methods that allow predictions about the behavior of economic agentsand the reulting market allocations in such settings. These predictions are robust to alarge class of private information structures by the agents. They identify conditions onthe nature of the interaction and the market under which it is possible to make uniquepredictions about economic behavior. When these conditions are not met, the PIsestablish robust bounds on the distribution of possible economic outcomes, especiallythe mean and the variance of the outcomes. They use these bounds to predict thewelfare impact of information sharing in markets. They also use the bounds to designrobust mechanisms, such as auction and voting methods, that perform well in manyinformation environments.This project provides an economic theory that can lead to practical solutions to marketand mechanism design problems. It also provides a theoretical foundation for futurework in econometrics aimed at testing models in situations where the researcher doesnot know the market's information structure.This research will have broader impacts for the many different areas of social sciencethat use game theory as a fundamental tool. In addition, the project has directimplications for antitrust policy, since whether or not to allow sellers to share informationis a question for price-fixing policy.