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Combining Overlapping Information

Author

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  • 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
    DOI: 10.1287/mnsc.33.3.373
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    Citations

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    Cited by:

    1. Erin Baker & Olaitan Olaleye, 2013. "Combining Experts: Decomposition and Aggregation Order," Risk Analysis, John Wiley & Sons, vol. 33(6), pages 1116-1127, June.
    2. Andrejs Bessonovs, 2015. "Suite of Latvia's GDP forecasting models," Working Papers 2015/01, Latvijas Banka.
    3. Zvi Schwartz & Timothy Webb & Jean-Pierre I van der Rest & Larissa Koupriouchina, 2021. "Enhancing the accuracy of revenue management system forecasts: The impact of machine and human learning on the effectiveness of hotel occupancy forecast combinations across multiple forecasting horizo," Tourism Economics, , vol. 27(2), pages 273-291, March.
    4. Robert F. Bordley, 2009. "Combining the Opinions of Experts Who Partition Events Differently," Decision Analysis, INFORMS, vol. 6(1), pages 38-46, March.
    5. 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.
    6. Timmermann, Allan, 2006. "Forecast Combinations," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 4, pages 135-196, Elsevier.
    7. David J. Johnstone, 2007. "The Parimutuel Kelly Probability Scoring Rule," Decision Analysis, INFORMS, vol. 4(2), pages 66-75, June.
    8. 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.
    9. 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.
    10. 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.
    11. Laborda, Ricardo, 2018. "Optimal combination of currency strategies," The North American Journal of Economics and Finance, Elsevier, vol. 43(C), pages 129-140.
    12. Jason R. W. Merrick, 2008. "Getting the Right Mix of Experts," Decision Analysis, INFORMS, vol. 5(1), pages 43-52, March.
    13. Jason R. W. Merrick & Rene Van Dorp, 2006. "Speaking the Truth in Maritime Risk Assessment," Risk Analysis, John Wiley & Sons, vol. 26(1), pages 223-237, February.
    14. 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.
    15. 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.
    16. 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.
    17. 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.
    18. 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.
    19. Ulrich Gunter & Irem Önder & Egon Smeral, 2020. "Are Combined Tourism Forecasts Better at Minimizing Forecasting Errors?," Forecasting, MDPI, vol. 2(3), pages 1-19, June.
    20. Thomas Theobald, 2012. "Combining Recession Probability Forecasts from a Dynamic Probit Indicator," IMK Working Paper 89-2012, IMK at the Hans Boeckler Foundation, Macroeconomic Policy Institute.
    21. James E. Smith & Detlof von Winterfeldt, 2004. "Anniversary Article: Decision Analysis in Management Science," Management Science, INFORMS, vol. 50(5), pages 561-574, May.
    22. 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.
    23. Robert J. Budnitz & George Apostolakis & David M. Boore & Lloyd S. Cluff & Kevin J. Coppersmith & C. Allin Cornell & Peter A. Morris, 1998. "Use of Technical Expert Panels: Applications to Probabilistic Seismic Hazard Analysis," Risk Analysis, John Wiley & Sons, vol. 18(4), pages 463-469, August.

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