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Prediction Markets as Decision Support Systems

Author

Listed:
  • Joyce E. Berg

    (University of Iowa)

  • Thomas A. Rietz

    (University of Iowa)

Abstract

Valuations from “prediction markets” reveal expectations about the likelihood of events. “Conditional prediction markets” reveal expectations conditional on other events occurring. For example, in 1996, the Iowa Electronic Markets (IEM) ran markets to predict the chances that different candidates would become the Republican Presidential nominee. Other concurrent IEM markets predicted the vote shares that each party would receive conditional on the Republican nominee chosen. Here, using these markets as examples, we show how such markets could be used for decision support. In this example, Republicans could have inferred that Dole was a weak candidate and that his nomination would result in a Clinton victory. This is only one example of the widespread potential for using specific decision support markets.

Suggested Citation

  • Joyce E. Berg & Thomas A. Rietz, 2003. "Prediction Markets as Decision Support Systems," Information Systems Frontiers, Springer, vol. 5(1), pages 79-93, January.
    • Handle: RePEc:spr:infosf:v:5:y:2003:i:1:d:10.1023_a:1022002107255
    DOI: 10.1023/A:1022002107255
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    References listed on IDEAS

    as
    1. Edmond Malinvaud, 1974. "The Allocation of Individual Risks in Large Markets," International Economic Association Series, in: Jacques H. Drèze (ed.), Allocation under Uncertainty: Equilibrium and Optimality, chapter 8, pages 110-125, Palgrave Macmillan.
    2. Forsythe, Robert & Forrest Nelson & George R. Neumann & Jack Wright, 1992. "Anatomy of an Experimental Political Stock Market," American Economic Review, American Economic Association, vol. 82(5), pages 1142-1161, December.
    3. T. Reitz & R. Myerson & R. Weber, 1998. "Campaign Finance Levels as Coordinating Signals in Three‐way, Experimental Elections," Economics and Politics, Wiley Blackwell, vol. 10(3), pages 185-218, November.
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