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Feasible best-response correspondences and quadratic scoring rules

Author

Listed:
  • Norde, Henk

    (CentER and Department of Econometrics and Operations Research, Tilburg University)

  • Voorneveld, Mark

    (Dept. of Economics)

Abstract

The rational choice paradigm in game theory and other fields of economics has agents best-responding to beliefs about factors that are outside their control. And making certain options a best response is a common problem in mechanism design and information elicitation. But not every correspondence can be made into a best-response correspondence. So what characterizes a feasible best-response correspondence? And once we know that, can we find some or even all utility functions that give rise to this best-response correspondence? We answer these three questions for an expected-utility maximizing agent with finitely many actions and probabilistic beliefs over finitely many states or opponents' strategies. We apply our results to information elicitation problems where contracts (scoring rules) are designed to financially reward an expected-payoff maximizing agent to truthfully reveal a property of her belief by sending a report from some finite set of messages. This leads to a number of new insights: firstly, we characterize exactly which properties can be elicited using scoring rules; secondly, we show that in this class of problems quadratic scoring rules are both necessary and sufficient methods of doing so.

Suggested Citation

  • Norde, Henk & Voorneveld, Mark, 2019. "Feasible best-response correspondences and quadratic scoring rules," SSE Working Paper Series in Economics 2019:2, Stockholm School of Economics.
  • Handle: RePEc:hhs:hastec:2019_002
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    References listed on IDEAS

    as
    1. Thomson, William, 1979. "Eliciting production possibilities from a well-informed manager," Journal of Economic Theory, Elsevier, vol. 20(3), pages 360-380, June.
    2. Mark Voorneveld & Peter Borm & Freek Van Megen & Stef Tijs & Giovanni Facchini, 1999. "Congestion Games And Potentials Reconsidered," International Game Theory Review (IGTR), World Scientific Publishing Co. Pte. Ltd., vol. 1(03n04), pages 283-299.
    3. Arthur Carvalho, 2016. "An Overview of Applications of Proper Scoring Rules," Decision Analysis, INFORMS, vol. 13(4), pages 223-242, December.
    4. Daniel Friedman, 1983. "Effective Scoring Rules for Probabilistic Forecasts," Management Science, INFORMS, vol. 29(4), pages 447-454, April.
    5. Theo Offerman & Joep Sonnemans & Gijs Van De Kuilen & Peter P. Wakker, 2009. "A Truth Serum for Non-Bayesians: Correcting Proper Scoring Rules for Risk Attitudes ," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 76(4), pages 1461-1489.
    6. Karl Schlag & James Tremewan & Joël Weele, 2015. "A penny for your thoughts: a survey of methods for eliciting beliefs," Experimental Economics, Springer;Economic Science Association, vol. 18(3), pages 457-490, September.
    7. Andrew Schotter & Isabel Trevino, 2014. "Belief Elicitation in the Laboratory," Annual Review of Economics, Annual Reviews, vol. 6(1), pages 103-128, August.
    8. Voorneveld, Mark, 2019. "An axiomatization of the Nash equilibrium concept," Games and Economic Behavior, Elsevier, vol. 117(C), pages 316-321.
    9. Michael Ostrovsky, 2012. "Information Aggregation in Dynamic Markets With Strategic Traders," Econometrica, Econometric Society, vol. 80(6), pages 2595-2647, November.
    10. Gneiting, Tilmann & Raftery, Adrian E., 2007. "Strictly Proper Scoring Rules, Prediction, and Estimation," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 359-378, March.
    11. Steffen Borgwardt & Rafael M. Frongillo, 2019. "Power Diagram Detection with Applications to Information Elicitation," Journal of Optimization Theory and Applications, Springer, vol. 181(1), pages 184-196, April.
    12. Voorneveld, Mark, 2019. "An elementary axiomatization of the Nash equilibrium concept," SSE Working Paper Series in Economics 2019:1, Stockholm School of Economics.
    13. Morris, Stephen & Ui, Takashi, 2004. "Best response equivalence," Games and Economic Behavior, Elsevier, vol. 49(2), pages 260-287, November.
    14. repec:fth:tilbur:9998 is not listed on IDEAS
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    More about this item

    Keywords

    best-response correspondence; best-response equivalence; information elicitation; scoring rule;
    All these keywords.

    JEL classification:

    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

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