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Efficient Design with Multidimensional, Continuous Types, and Interdependent Valuations

Author

Listed:
  • Johnson, Scott
  • Miller, Nolan

    (Harvard U)

  • Pratt, John W.

    (Harvard U)

  • Zeckhauser, Richard

    (Harvard U)

Abstract

We consider mechanism design in social choice problems in which agents’ types are continuous, multidimensional, and mutually payoff-relevant, and there are three or more agents. If the center receives a signal that is stochastically related to the agents’ types and direct returns are bounded, then for any decision rule there is a balanced transfer function that ensures that any strategy that is not arbitrarily close to truthful is dominated by one that is. If direct returns are continuous as well, truthful revelation becomes an -dominant strategy, all Bayes-Nash equilibrium strategies are nearly truthful, and at least one such strategy exists. If the center’s information is not informative but agents’ types are stochastically related, then there exist balanced transfers under which truthful revelation is a Bayesian -equilibrium, again for any decision rule. Analogous results hold for decentralized decision problems when agents also take mutually payoff-relevant actions in advance of any action by the center.

Suggested Citation

  • Johnson, Scott & Miller, Nolan & Pratt, John W. & Zeckhauser, Richard, 2003. "Efficient Design with Multidimensional, Continuous Types, and Interdependent Valuations," Working Paper Series rwp03-020, Harvard University, John F. Kennedy School of Government.
    • Handle: RePEc:ecl:harjfk:rwp03-020
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    References listed on IDEAS

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    Cited by:

    1. Jehiel, Philippe & Moldovanu, Benny, 2005. "Allocative and Informational Externalities in Auctions and Related Mechanisms," Discussion Paper Series of SFB/TR 15 Governance and the Efficiency of Economic Systems 142, Free University of Berlin, Humboldt University of Berlin, University of Bonn, University of Mannheim, University of Munich.
    2. Nolan Miller & Paul Resnick & Richard Zeckhauser, 2005. "Eliciting Informative Feedback: The Peer-Prediction Method," Management Science, INFORMS, vol. 51(9), pages 1359-1373, September.

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