IDEAS home Printed from
   My bibliography  Save this article

Unanimity and Compromise Among Probability Forecasters


  • 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)


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

    Download full text from publisher

    File URL:
    Download Restriction: no


    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.

    Cited by:

    1. Sobel, Joel, 2014. "On the relationship between individual and group decisions," Theoretical Economics, Econometric Society, vol. 9(1), January.
    2. Kornbluth, J. S. H., 1997. "Identifying feasible orderings for performance appraisal," Omega, Elsevier, vol. 25(3), pages 329-334, June.
    3. 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.
    4. D. Johnstone, 2007. "The Value of a Probability Forecast from Portfolio Theory," Theory and Decision, Springer, vol. 63(2), pages 153-203, September.
    5. 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.
    6. 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.
    7. 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.
    8. James E. Smith & Detlof von Winterfeldt, 2004. "Anniversary Article: Decision Analysis in Management Science," Management Science, INFORMS, vol. 50(5), pages 561-574, May.


    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:inm:ormnsc:v:36:y:1990:i:7:p:767-779. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Mirko Janc). General contact details of provider: .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.