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Overconfident people are more exposed to “black swan” events: a case study of avalanche risk

Author

Listed:
  • Nicolao Bonini

    (University of Trento)

  • Stefania Pighin

    (University of Trento
    University of Verona)

  • Enrico Rettore

    (University of Trento
    FBK-IRVAPP
    IZA)

  • Lucia Savadori

    (University of Trento)

  • Federico Schena

    (University of Verona)

  • Sara Tonini

    (IZA
    University of Cape Town)

  • Paolo Tosi

    (University of Trento)

Abstract

Overconfidence is a well-established bias in which someone’s subjective confidence in their own judgment is systematically greater than their objective accuracy. There is abundant anecdotal evidence that overconfident people increase their exposure to risk. In this paper, we test whether overconfident backcountry skiers underestimate the probability of incurring a snow avalanche accident. An avalanche accident is a typical “black swan” event as defined by Taleb (The black swan: the impact of the highly improbable, Random House, New York, 2007) because it has a very low probability of occurring but with potentially dramatic consequences. To consider black swan events when studying overconfidence is particularly important, in light of previous findings on the role of overconfidence when feedbacks on tasks previously performed are inconclusive and infrequent. We run our test by measuring individual overconfidence using standard tools from the literature and then use a random effect logit model to measure its effect on the probability to take the ski route. We show that (1) overconfidence is widespread in our sample; (2) practitioners who are more prone to overestimate their knowledge are also more likely to take risks associated with a ski trip under the threat of avalanche danger, a result robust to a set of specification tests we perform. This suggests that overconfident people are more exposed to black swan events, by taking a risky decision that can bring about fatal consequences.

Suggested Citation

  • Nicolao Bonini & Stefania Pighin & Enrico Rettore & Lucia Savadori & Federico Schena & Sara Tonini & Paolo Tosi, 2019. "Overconfident people are more exposed to “black swan” events: a case study of avalanche risk," Empirical Economics, Springer, vol. 57(4), pages 1443-1467, October.
  • Handle: RePEc:spr:empeco:v:57:y:2019:i:4:d:10.1007_s00181-018-1489-5
    DOI: 10.1007/s00181-018-1489-5
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    References listed on IDEAS

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    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. Ulrike Malmendier & Geoffrey Tate, 2005. "CEO Overconfidence and Corporate Investment," Journal of Finance, American Finance Association, vol. 60(6), pages 2661-2700, December.
    3. Ulrike Malmendier & Timothy Taylor, 2015. "On the Verges of Overconfidence," Journal of Economic Perspectives, American Economic Association, vol. 29(4), pages 3-8, Fall.
    4. Ann-Renée Blais & Elke U. Weber, 2006. "A Domain-Specific Risk-Taking (DOSPERT)Scale for Adult Populations," CIRANO Working Papers 2006s-24, CIRANO.
    5. repec:cup:judgdm:v:1:y:2006:i::p:33-47 is not listed on IDEAS
    6. Hersh Shefrin, 2001. "Behavioral Corporate Finance," Journal of Applied Corporate Finance, Morgan Stanley, vol. 14(3), pages 113-126, September.
    7. Stefano DellaVigna & Ulrike Malmendier, 2006. "Paying Not to Go to the Gym," American Economic Review, American Economic Association, vol. 96(3), pages 694-719, June.
    8. Dan Lovallo & Colin Camerer, 1999. "Overconfidence and Excess Entry: An Experimental Approach," American Economic Review, American Economic Association, vol. 89(1), pages 306-318, March.
    9. Ronis, David L. & Yates, J. Frank, 1987. "Components of probability judgment accuracy: Individual consistency and effects of subject matter and assessment method," Organizational Behavior and Human Decision Processes, Elsevier, vol. 40(2), pages 193-218, October.
    10. J B Heaton, 2002. "Managerial Optimism and Corporate Finance," Financial Management, Financial Management Association, vol. 31(2), Summer.
    11. Roll, Richard, 1986. "The Hubris Hypothesis of Corporate Takeovers," The Journal of Business, University of Chicago Press, vol. 59(2), pages 197-216, April.
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    Cited by:

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    2. Kenneth Yung & Xiang Long, 2022. "CEO overconfidence and the adjustment speed of leverage and cash: evidence on cash is not the same as negative debt," Empirical Economics, Springer, vol. 63(2), pages 1081-1108, August.

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    More about this item

    Keywords

    Cognitive bias; Risky decision; Backcountry skiing; Measurement errors; Logit model;
    All these keywords.

    JEL classification:

    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior

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