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Combining Overlapping Information

Author

Listed:
  • Robert T. Clemen

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

Abstract

A decision maker trying to learn about an uncertain quantity may obtain divergent information from a number of sources (e.g., experts). In this paper we study the decision maker's problem of aggregating this information to form his posterior distribution when he believes that the experts' opinions are dependent due to shared information. Examples in both normal and Bernoulli frameworks lead to some surprising general insights regarding the impact of the dependence on the posterior distribution. The study has implications for practitioners who face real-world information-aggregation problems and for groups of experts who seek a consensus.

Suggested Citation

  • Robert T. Clemen, 1987. "Combining Overlapping Information," Management Science, INFORMS, vol. 33(3), pages 373-380, March.
  • Handle: RePEc:inm:ormnsc:v:33:y:1987:i:3:p:373-380
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    File URL: http://dx.doi.org/10.1287/mnsc.33.3.373
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    Citations

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    Cited by:

    1. Andrejs Bessonovs, 2015. "Suite of Latvia's GDP forecasting models," Working Papers 2015/01, Latvijas Banka.
    2. 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.
    3. Timmermann, Allan, 2006. "Forecast Combinations," Handbook of Economic Forecasting, Elsevier.
    4. Karsten R. Gerdrup & Anne Sofie Jore & Christie Smith & Leif Anders Thorsrud, 2009. "Evaluating ensemble density combination - forecasting GDP and inflation," Working Paper 2009/19, Norges Bank.
    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. Berg, Sven, 1997. "Indirect voting systems: Banzhaf numbers, majority functions and collective competence," European Journal of Political Economy, Elsevier, vol. 13(3), pages 557-573, September.
    7. repec:eee:ecofin:v:43:y:2018:i:c:p:129-140 is not listed on IDEAS
    8. Dewispelare, Aaron R. & Herren, L. Tandy & Clemen, Robert T., 1995. "The use of probability elicitation in the high-level nuclear waste regulation program," International Journal of Forecasting, Elsevier, vol. 11(1), pages 5-24, March.
    9. Karelaia, Natalia, 2006. "Thirst for confirmation in multi-attribute choice: Does search for consistency impair decision performance?," Organizational Behavior and Human Decision Processes, Elsevier, vol. 100(1), pages 128-143, May.
    10. Kelly, David L. & Letson, David & Nelson, Forrest & Nolan, David S. & Solís, Daniel, 2012. "Evolution of subjective hurricane risk perceptions: A Bayesian approach," Journal of Economic Behavior & Organization, Elsevier, vol. 81(2), pages 644-663.
    11. Budescu, David V. & Rantilla, Adrian K. & Yu, Hsiu-Ting & Karelitz, Tzur M., 2003. "The effects of asymmetry among advisors on the aggregation of their opinions," Organizational Behavior and Human Decision Processes, Elsevier, vol. 90(1), pages 178-194, January.
    12. 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.

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