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Unanimity and Compromise Among Probability Forecasters

Author

Listed:
  • Robert T. Clemen

    (College of Business Administration, University of Oregon, Eugene, Oregon 97403)

  • Robert L. Winkler

    (Fuqua School of Business, Duke University, Durham, North Carolina 27706)

Abstract

When two forecasters agree regarding the probability of an uncertain event, should a decision maker adopt that probability as his or her own? A decision maker who does so is said to act in accord with the unanimity principle. We examine a variety of Bayesian consensus models with respect to their conformance (or lack thereof) to the unanimity principle and a more general compromise principle. In an analysis of a large set of probability forecast data from meteorology, we show how well the various models, when fit to the data, reflect the empirical pattern of conformance to these principles.

Suggested Citation

  • Robert T. Clemen & Robert L. Winkler, 1990. "Unanimity and Compromise Among Probability Forecasters," Management Science, INFORMS, vol. 36(7), pages 767-779, July.
    • Handle: RePEc:inm:ormnsc:v:36:y:1990:i:7:p:767-779
    DOI: 10.1287/mnsc.36.7.767
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    Citations

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    Cited by:

    1. Clemen, Robert T. & Murphy, Allan H. & Winkler, Robert L., 1995. "Screening probability forecasts: contrasts between choosing and combining," International Journal of Forecasting, Elsevier, vol. 11(1), pages 133-145, March.
    2. Paola Monari & Patrizia Agati, 2001. "Fiducial inference in combining expert judgements," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 10(1), pages 81-97, January.
    3. Patrizio Frederic & Mario Di Bacco & Frank Lad, 2012. "Combining expert probabilities using the product of odds," Theory and Decision, Springer, vol. 73(4), pages 605-619, October.
    4. Valsecchi, Irene, 2008. "Learning from Experts," International Energy Markets Working Papers 36756, Fondazione Eni Enrico Mattei (FEEM).
    5. Marios Kokkodis & Panagiotis G. Ipeirotis, 2016. "Reputation Transferability in Online Labor Markets," Management Science, INFORMS, vol. 62(6), pages 1687-1706, June.
    6. Joseph Lipscomb & Giovanni Parmigiani & Vic Hasselblad, 1998. "Combining Expert Judgment by Hierarchical Modeling: An Application to Physician Staffing," Management Science, INFORMS, vol. 44(2), pages 149-161, February.
    7. Robert T. Clemen & Robert L. Winkler, 1999. "Combining Probability Distributions From Experts in Risk Analysis," Risk Analysis, John Wiley & Sons, vol. 19(2), pages 187-203, April.
    8. ,, 2014. "On the relationship between individual and group decisions," Theoretical Economics, Econometric Society, vol. 9(1), January.
    9. Jason R. W. Merrick & J. Rene van Dorp & Jack Harrald & Thomas Mazzuchi & John E. Spahn & Martha Grabowski, 2000. "A systems approach to managing oil transportation risk in Prince William Sound," Systems Engineering, John Wiley & Sons, vol. 3(3), pages 128-142.
    10. Kornbluth, J. S. H., 1997. "Identifying feasible orderings for performance appraisal," Omega, Elsevier, vol. 25(3), pages 329-334, June.
    11. D. Johnstone, 2007. "The Value of a Probability Forecast from Portfolio Theory," Theory and Decision, Springer, vol. 63(2), pages 153-203, September.
    12. Szwed, P. & Dorp, J. Rene van & Merrick, J.R.W. & Mazzuchi, T.A. & Singh, A., 2006. "A Bayesian paired comparison approach for relative accident probability assessment with covariate information," European Journal of Operational Research, Elsevier, vol. 169(1), pages 157-177, February.
    13. David V. Budescu & Hsiu-Ting Yu, 2006. "To Bayes or Not to Bayes? A Comparison of Two Classes of Models of Information Aggregation," Decision Analysis, INFORMS, vol. 3(3), pages 145-162, September.
    14. James E. Smith & Detlof von Winterfeldt, 2004. "Anniversary Article: Decision Analysis in Management Science," Management Science, INFORMS, vol. 50(5), pages 561-574, May.

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