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Calibration and the Aggregation of Probabilities

Author

Listed:
  • Robert T. Clemen

    (College of Business Administration, University of Oregon, Eugene, Oregon 97403-1208)

Abstract

In order to avoid the task of assessing a complicated likelihood function, Morris uses an axiomatic approach to develop a multiplicative rule for aggregating a decision maker's and an expert's probabilities. An essential shortcoming of the multiplicative rule is that it does not allow the decision maker to model his beliefs about the dependence between his assessment and the expert's. The root of the problem lies in the fact that the decision maker must calibrate the expert's information. When the calibration is done properly, the decision maker is forced to tackle the task which Morris proposes to avoid.

Suggested Citation

  • Robert T. Clemen, 1986. "Calibration and the Aggregation of Probabilities," Management Science, INFORMS, vol. 32(3), pages 312-314, March.
    • Handle: RePEc:inm:ormnsc:v:32:y:1986:i:3:p:312-314
    DOI: 10.1287/mnsc.32.3.312
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    Citations

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    Cited by:

    1. Klayman, Joshua & Soll, Jack B. & Gonzalez-Vallejo, Claudia & Barlas, Sema, 1999. "Overconfidence: It Depends on How, What, and Whom You Ask, , , , , , , , ," Organizational Behavior and Human Decision Processes, Elsevier, vol. 79(3), pages 216-247, September.
    2. David J. Johnstone, 2007. "The Parimutuel Kelly Probability Scoring Rule," Decision Analysis, INFORMS, vol. 4(2), pages 66-75, June.
    3. Mehrez, A. & Yuan, Y. & Gafni, A., 1995. "The search for information -- A patient perspective on multiple opinions," European Journal of Operational Research, Elsevier, vol. 85(2), pages 244-262, September.
    4. 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.
    5. Weyant John, 2014. "Integrated assessment of climate change: state of the literature," Journal of Benefit-Cost Analysis, De Gruyter, vol. 5(3), pages 377-409, December.
    6. Wang, W., 1997. "Subjective estimation of the delay time distribution in maintenance modelling," European Journal of Operational Research, Elsevier, vol. 99(3), pages 516-529, June.
    7. Jason R. W. Merrick & J. Rene van Dorp & Amita Singh, 2005. "Analysis of Correlated Expert Judgments from Extended Pairwise Comparisons," Decision Analysis, INFORMS, vol. 2(1), pages 17-29, March.
    8. 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.
    9. James E. Smith & Detlof von Winterfeldt, 2004. "Anniversary Article: Decision Analysis in Management Science," Management Science, INFORMS, vol. 50(5), pages 561-574, May.
    10. Ladha, Krishna K., 1995. "Information pooling through majority-rule voting: Condorcet's jury theorem with correlated votes," Journal of Economic Behavior & Organization, Elsevier, vol. 26(3), pages 353-372, May.
    11. Mark Steyvers & Thomas S. Wallsten & Edgar C. Merkle & Brandon M. Turner, 2014. "Evaluating Probabilistic Forecasts with Bayesian Signal Detection Models," Risk Analysis, John Wiley & Sons, vol. 34(3), pages 435-452, March.

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