IDEAS home Printed from https://ideas.repec.org/a/inm/ormnsc/v63y2017i11p3552-3565.html
   My bibliography  Save this article

Confidence Calibration in a Multiyear Geopolitical Forecasting Competition

Author

Listed:
  • Don A. Moore

    (University of California, Berkeley, Berkeley, California 94720)

  • Samuel A. Swift

    (Betterment, LLC, New York, New York 10010)

  • Angela Minster

    (University of Pennsylvania, Philadelphia, Pennsylvania 19104)

  • Barbara Mellers

    (University of Pennsylvania, Philadelphia, Pennsylvania 19104)

  • Lyle Ungar

    (University of Pennsylvania, Philadelphia, Pennsylvania 19104)

  • Philip Tetlock

    (University of Pennsylvania, Philadelphia, Pennsylvania 19104)

  • Heather H. J. Yang

    (Massachusetts Institute of Technology, Cambridge, Massachusetts 02139)

  • Elizabeth R. Tenney

    (University of Utah, Salt Lake City, Utah 84112)

Abstract

This research examines the development of confidence and accuracy over time in the context of forecasting. Although overconfidence has been studied in many contexts, little research examines its progression over long periods of time or in consequential policy domains. This study employs a unique data set from a geopolitical forecasting tournament spanning three years in which thousands of forecasters predicted the outcomes of hundreds of events. We sought to apply insights from research to structure the questions, interactions, and elicitations to improve forecasts. Indeed, forecasters’ confidence roughly matched their accuracy. As information came in, accuracy increased. Confidence increased at approximately the same rate as accuracy, and good calibration persisted. Nevertheless, there was evidence of a small amount of overconfidence (3%), especially on the most confident forecasts. Training helped reduce overconfidence, and team collaboration improved forecast accuracy. Together, teams and training reduced overconfidence to 1%. Our results provide reason for tempered optimism regarding confidence calibration and its development over time in consequential field contexts.

Suggested Citation

  • Don A. Moore & Samuel A. Swift & Angela Minster & Barbara Mellers & Lyle Ungar & Philip Tetlock & Heather H. J. Yang & Elizabeth R. Tenney, 2017. "Confidence Calibration in a Multiyear Geopolitical Forecasting Competition," Management Science, INFORMS, vol. 63(11), pages 3552-3565, November.
  • Handle: RePEc:inm:ormnsc:v:63:y:2017:i:11:p:3552-3565
    DOI: 10.1287/mnsc.2016.2525
    as

    Download full text from publisher

    File URL: https://doi.org/10.1287/mnsc.2016.2525
    Download Restriction: no

    File URL: https://libkey.io/10.1287/mnsc.2016.2525?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Jonathan Baron & Barbara A. Mellers & Philip E. Tetlock & Eric Stone & Lyle H. Ungar, 2014. "Two Reasons to Make Aggregated Probability Forecasts More Extreme," Decision Analysis, INFORMS, vol. 11(2), pages 133-145, June.
    2. Daniel Kahneman & Dan Lovallo, 1993. "Timid Choices and Bold Forecasts: A Cognitive Perspective on Risk Taking," Management Science, INFORMS, vol. 39(1), pages 17-31, January.
    3. 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.
    4. Markus Glaser & Martin Weber, 2007. "Overconfidence and trading volume," The Geneva Papers on Risk and Insurance Theory, Springer;International Association for the Study of Insurance Economics (The Geneva Association), vol. 32(1), pages 1-36, June.
    5. Keren, Gideon, 1987. "Facing uncertainty in the game of bridge: A calibration study," Organizational Behavior and Human Decision Processes, Elsevier, vol. 39(1), pages 98-114, February.
    6. Richard P. Larrick & Jack B. Soll, 2006. "Erratum--Intuitions About Combining Opinions: Misappreciation of the Averaging Principle," Management Science, INFORMS, vol. 52(2), pages 309-310, February.
    7. Jeremy Clark & Lana Friesen, 2009. "Overconfidence in Forecasts of Own Performance: An Experimental Study," Economic Journal, Royal Economic Society, vol. 119(534), pages 229-251, January.
    8. Meir Statman & Steven Thorley & Keith Vorkink, 2006. "Investor Overconfidence and Trading Volume," The Review of Financial Studies, Society for Financial Studies, vol. 19(4), pages 1531-1565.
    9. Pavel Atanasov & Phillip Rescober & Eric Stone & Samuel A. Swift & Emile Servan-Schreiber & Philip Tetlock & Lyle Ungar & Barbara Mellers, 2017. "Distilling the Wisdom of Crowds: Prediction Markets vs. Prediction Polls," Management Science, INFORMS, vol. 63(3), pages 691-706, March.
    10. Itzhak Ben-David & John R. Graham, 2013. "Managerial Miscalibration," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 128(4), pages 1547-1584.
    11. Heath, Chip & Gonzalez, Rich, 1995. "Interaction with Others Increases Decision Confidence but Not Decision Quality: Evidence against Information Collection Views of Interactive Decision Making," Organizational Behavior and Human Decision Processes, Elsevier, vol. 61(3), pages 305-326, March.
    12. Benson, P. George & Onkal, Dilek, 1992. "The effects of feedback and training on the performance of probability forecasters," International Journal of Forecasting, Elsevier, vol. 8(4), pages 559-573, December.
    13. Buehler, Roger & Messervey, Deanna & Griffin, Dale, 2005. "Collaborative planning and prediction: Does group discussion affect optimistic biases in time estimation?," Organizational Behavior and Human Decision Processes, Elsevier, vol. 97(1), pages 47-63, May.
    14. Dawes, Robyn M. & Mulford, Matthew, 1996. "The False Consensus Effect and Overconfidence: Flaws in Judgment or Flaws in How We Study Judgment?," Organizational Behavior and Human Decision Processes, Elsevier, vol. 65(3), pages 201-211, March.
    15. repec:cup:judgdm:v:5:y:2010:i:7:p:467-476 is not listed on IDEAS
    16. Erik Hoelzl & Aldo Rustichini, 2005. "Overconfident: Do You Put Your Money On It?," Economic Journal, Royal Economic Society, vol. 115(503), pages 305-318, April.
    17. Wright, George & Rowe, Gene & Bolger, Fergus & Gammack, John, 1994. "Coherence, Calibration, and Expertise in Judgmental Probability Forecasting," Organizational Behavior and Human Decision Processes, Elsevier, vol. 57(1), pages 1-25, January.
    18. Hall, Crystal C. & Ariss, Lynn & Todorov, Alexander, 2007. "The illusion of knowledge: When more information reduces accuracy and increases confidence," Organizational Behavior and Human Decision Processes, Elsevier, vol. 103(2), pages 277-290, July.
    19. Cooper, Arnold C. & Woo, Carolyn Y. & Dunkelberg, William C., 1988. "Entrepreneurs' perceived chances for success," Journal of Business Venturing, Elsevier, vol. 3(2), pages 97-108.
    20. Moore, Don A., 2007. "Not so above average after all: When people believe they are worse than average and its implications for theories of bias in social comparison," Organizational Behavior and Human Decision Processes, Elsevier, vol. 102(1), pages 42-58, January.
    21. Sniezek, Janet A. & Henry, Rebecca A., 1989. "Accuracy and confidence in group judgment," Organizational Behavior and Human Decision Processes, Elsevier, vol. 43(1), pages 1-28, February.
    22. Young Park & Luís Santos-Pinto, 2010. "Overconfidence in tournaments: evidence from the field," Theory and Decision, Springer, vol. 69(1), pages 143-166, July.
    23. Yates, J. Frank & Lee, Ju-Whei & Shinotsuka, Hiromi & Patalano, Andrea L. & Sieck, Winston R., 1998. "Cross-Cultural Variations in Probability Judgment Accuracy: Beyond General Knowledge Overconfidence?," Organizational Behavior and Human Decision Processes, Elsevier, vol. 74(2), pages 89-117, May.
    24. Larrick, Richard P. & Burson, Katherine A. & Soll, Jack B., 2007. "Social comparison and confidence: When thinking you're better than average predicts overconfidence (and when it does not)," Organizational Behavior and Human Decision Processes, Elsevier, vol. 102(1), pages 76-94, January.
    25. McKenzie, Craig R.M. & Liersch, Michael J. & Yaniv, Ilan, 2008. "Overconfidence in interval estimates: What does expertise buy you?," Organizational Behavior and Human Decision Processes, Elsevier, vol. 107(2), pages 179-191, November.
    26. Stone, Eric R. & Opel, Ryan B., 2000. "Training to Improve Calibration and Discrimination: The Effects of Performance and Environmental Feedback," Organizational Behavior and Human Decision Processes, Elsevier, vol. 83(2), pages 282-309, November.
    27. Richard P. Larrick & Jack B. Soll, 2006. "Intuitions About Combining Opinions: Misappreciation of the Averaging Principle," Management Science, INFORMS, vol. 52(1), pages 111-127, January.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Rahul Kapoor & Daniel Wilde, 2023. "Peering into a crystal ball: Forecasting behavior and industry foresight," Strategic Management Journal, Wiley Blackwell, vol. 44(3), pages 704-736, March.
    2. Don A Moore & Derek Schatz, 2020. "Overprecision increases subsequent surprise," PLOS ONE, Public Library of Science, vol. 15(7), pages 1-12, July.
    3. Ross Gruetzemacher & Kang Bok Lee & David Paradice, 2024. "Calibration training for improving probabilistic judgments using an interactive app," Futures & Foresight Science, John Wiley & Sons, vol. 6(2), June.
    4. Karvetski, Christopher W. & Meinel, Carolyn & Maxwell, Daniel T. & Lu, Yunzi & Mellers, Barbara A. & Tetlock, Philip E., 2022. "What do forecasting rationales reveal about thinking patterns of top geopolitical forecasters?," International Journal of Forecasting, Elsevier, vol. 38(2), pages 688-704.
    5. Astebro, Thomas B. & Fossen, Frank M. & Gutierrez, Cédric, 2024. "Entrepreneurs: Clueless, Biased, Poor Heuristics, or Bayesian Machines?," IZA Discussion Papers 17231, Institute of Labor Economics (IZA).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Lawrence, Michael & Goodwin, Paul & O'Connor, Marcus & Onkal, Dilek, 2006. "Judgmental forecasting: A review of progress over the last 25 years," International Journal of Forecasting, Elsevier, vol. 22(3), pages 493-518.
    2. Grieco, Daniela & Hogarth, Robin M., 2009. "Overconfidence in absolute and relative performance: The regression hypothesis and Bayesian updating," Journal of Economic Psychology, Elsevier, vol. 30(5), pages 756-771, October.
    3. Bruhin, Adrian & Santos-Pinto, Luís & Staubli, David, 2018. "How do beliefs about skill affect risky decisions?," Journal of Economic Behavior & Organization, Elsevier, vol. 150(C), pages 350-371.
    4. See, Kelly E. & Morrison, Elizabeth W. & Rothman, Naomi B. & Soll, Jack B., 2011. "The detrimental effects of power on confidence, advice taking, and accuracy," Organizational Behavior and Human Decision Processes, Elsevier, vol. 116(2), pages 272-285.
    5. Fellner-Röhling, Gerlinde & Krügel, Sebastian, 2014. "Judgmental overconfidence and trading activity," Journal of Economic Behavior & Organization, Elsevier, vol. 107(PB), pages 827-842.
    6. repec:cup:judgdm:v:12:y:2017:i:1:p:29-41 is not listed on IDEAS
    7. Merkle, Christoph & Weber, Martin, 2011. "True overconfidence: The inability of rational information processing to account for apparent overconfidence," Organizational Behavior and Human Decision Processes, Elsevier, vol. 116(2), pages 262-271.
    8. Stone, Eric R. & Opel, Ryan B., 2000. "Training to Improve Calibration and Discrimination: The Effects of Performance and Environmental Feedback," Organizational Behavior and Human Decision Processes, Elsevier, vol. 83(2), pages 282-309, November.
    9. Julia P. Prims & Don A. Moore, 2017. "Overconfidence over the lifespan," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 12(1), pages 29-41, January.
    10. repec:cup:judgdm:v:14:y:2019:i:4:p:395-411 is not listed on IDEAS
    11. Julia A. Minson & Jennifer S. Mueller & Richard P. Larrick, 2018. "The Contingent Wisdom of Dyads: When Discussion Enhances vs. Undermines the Accuracy of Collaborative Judgments," Management Science, INFORMS, vol. 64(9), pages 4177-4192, September.
    12. Oliver Gloede & Lukas Menkhoff, 2014. "Financial Professionals' Overconfidence: Is It Experience, Function, or Attitude?," European Financial Management, European Financial Management Association, vol. 20(2), pages 236-269, March.
    13. Michailova, Julija, 2010. "Development of the overconfidence measurement instrument for the economic experiment," MPRA Paper 34799, University Library of Munich, Germany, revised Nov 2011.
    14. Glaser, Markus & Weber, Martin, 2007. "Why inexperienced investors do not learn: They do not know their past portfolio performance," Finance Research Letters, Elsevier, vol. 4(4), pages 203-216, December.
    15. Itzhak Ben-David & John R. Graham & Campbell R. Harvey, 2007. "Managerial Overconfidence and Corporate Policies," NBER Working Papers 13711, National Bureau of Economic Research, Inc.
    16. Markus Glaser & Martin Weber, 2007. "Overconfidence and trading volume," The Geneva Papers on Risk and Insurance Theory, Springer;International Association for the Study of Insurance Economics (The Geneva Association), vol. 32(1), pages 1-36, June.
    17. Ferretti, Valentina & Guney, Sule & Montibeller, Gilberto & Winterfeldt, Detlof von, 2016. "Testing best practices to reduce the overconfidence bias in multi-criteria decision analysis," LSE Research Online Documents on Economics 67179, London School of Economics and Political Science, LSE Library.
    18. Robin M. Hogarth & Natalia Karelaia, 2012. "Entrepreneurial Success and Failure: Confidence and Fallible Judgment," Organization Science, INFORMS, vol. 23(6), pages 1733-1747, December.
    19. Krawczyk, Michał, 2012. "Incentives and timing in relative performance judgments: A field experiment," Journal of Economic Psychology, Elsevier, vol. 33(6), pages 1240-1246.
    20. Merkle, Christoph, 2018. "The curious case of negative volatility," Journal of Financial Markets, Elsevier, vol. 40(C), pages 92-108.
    21. Itzhak Ben-David & John R. Graham, 2013. "Managerial Miscalibration," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 128(4), pages 1547-1584.
    22. Merkle, Christoph, 2017. "Financial overconfidence over time: Foresight, hindsight, and insight of investors," Journal of Banking & Finance, Elsevier, vol. 84(C), pages 68-87.

    Corrections

    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:63:y:2017:i:11:p:3552-3565. See general information about how to correct material in RePEc.

    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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.