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Methods to Elicit Forecasts from Groups: Delphi and Prediction Markets Compared

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  • Green, Kesten C.
  • Armstrong, J. Scott
  • Graefe, Andreas

Abstract

Traditional groups meetings are an inefficient and ineffective method for making forecasts and decisions. We compare two structured alternatives to traditional meetings: the Delphi technique and prediction markets. Delphi is relatively simple and cheap to implement and has been adopted for diverse applications in business and government since its origins in the 1950s. It can be used for nearly any forecasting, estimation, or decision making problem not barred by complexity or ignorance. While prediction markets were used more than a century ago, their popularity waned until more recent times. As a consequence there is less evidence on their validity. Prediction markets need many participants. They need clear outcomes in order to determine participants’ pay-offs. Even so, relating their knowledge to market prices is not intuitive to everyone and constructing contracts that will provide a useful forecast may not be possible for some problems. It is difficult to maintain confidentiality with markets and they are vulnerable to manipulation. Delphi is designed to reveal panelists’ knowledge and opinions via their forecasts and the reasoning they provide. This format allows testing of knowledge and learning by panelists as they refine their forecasts. Such a process does not happen explicitly in prediction markets and may not happen at all. The reasoning provided as an output of the Delphi process is likely to be reassuring to forecast users who are uncomfortable with the “black box” nature of prediction markets. We consider that, half a century after its original development, Delphi is greatly under-utilized.

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Bibliographic Info

Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 4663.

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Date of creation: 31 Aug 2007
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Handle: RePEc:pra:mprapa:4663

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Keywords: accuracy; forecasting methods; groups; judgment; meetings; structure;

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References

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  1. Kesten C. Green & J. Scott Armstrong, 2004. "Value of Expertise For Forecasting Decisions in Conflicts," Monash Econometrics and Business Statistics Working Papers, Monash University, Department of Econometrics and Business Statistics 27/04, Monash University, Department of Econometrics and Business Statistics.
  2. Paul W. Rhode & Koleman S. Strumpf, 2004. "Historical Presidential Betting Markets," Journal of Economic Perspectives, American Economic Association, American Economic Association, vol. 18(2), pages 127-141, Spring.
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Cited by:
  1. Graefe, Andreas & Armstrong, J. Scott, 2011. "Comparing face-to-face meetings, nominal groups, Delphi and prediction markets on an estimation task," International Journal of Forecasting, Elsevier, Elsevier, vol. 27(1), pages 183-195, January.
  2. Kerr, Norbert L. & Tindale, R. Scott, 2011. "Group-based forecasting?: A social psychological analysis," International Journal of Forecasting, Elsevier, Elsevier, vol. 27(1), pages 14-40, January.
  3. Ricardo Gomes & Alfeu Marques & Joaquim Sousa, 2013. "District Metered Areas Design Under Different Decision Makers’ Options: Cost Analysis," Water Resources Management, Springer, Springer, vol. 27(13), pages 4527-4543, October.
  4. Palma, David & Dios Ortuzar, Juan de & Casaubon, Gerard & Rizzi, Luis I. & Agosin, Eduardo, 2013. "Measuring consumer preferences using hybrid discrete choice models," Working Papers, American Association of Wine Economists 164855, American Association of Wine Economists.
  5. Robert J. MacCoun, 2010. "Comment on "Rethinking America’s Illegal Drug Policy"," NBER Chapters, in: Controlling Crime: Strategies and Tradeoffs, pages 281-289 National Bureau of Economic Research, Inc.

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