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Self-confidence and strategic behavior

Abstract

We suggest that overconfidence (conscious or unconscious) is motivated in part by strategic considerations, and test this experimentally. We find compelling supporting evidence in the behavior of participants who send and respond to others’ statements of confidence about how well they have scored on an IQ test. In two-player tournaments where the higher score wins, a player is very likely to choose to compete when he knows that his own stated confidence is higher than the other player’s, but rarely when the reverse is true. Consistent with this behavior, stated confidence is inflated by males when deterrence is strategically optimal and is instead deflated (by males and females) when luring (encouraging entry) is strategically optimal. This behavior is consistent with the equilibrium of the corresponding signaling game. Overconfident statements are used in environments that seem familiar, and we present evidence that suggests that this can occur on an unconscious level.

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Notes

  1. 1.

    We note that while overconfidence is found in many studies, there is mixed evidence for it (see for instance Clark and Friesen 2009) and might be overestimated (Heger and Papageorge 2015). Its prevalence depends on factors such as experience (Weinstein 1980) or task-difficulty (Kruger 1999; Hoelzl and Rustichini 2005).

  2. 2.

    In an environment of incomplete information, this is not per se conclusive evidence of overconfidence (Benoit and Dubra 2011; Burks et al. 2013).

  3. 3.

    We initially used an outside option of €3.5, but found that 28 of 30 receivers entered the tournament. We then switched to an outside option of €5.5.

  4. 4.

    Treatment 1 had some additional components in which we presented updating tasks to participants. We will not describe the results of that part in this paper. Details can be found in Charness et al. (2013).

  5. 5.

    We conducted more sessions of Treatment 1 because we were interested in updating behavior after being given noisy feedback about performance. Our basic finding is that people do relatively poorly when the feedback is about their own performance, but do quite well in an isomorphic task that does not involve their own performance. Again, details can be found in Charness et al. (2013).

  6. 6.

    We started collecting risk attitudes only after a while. We measured this among all participants in treatment Deter with the high outside option, in treatment Lure, and in a few sessions of Baseline.

  7. 7.

    Of course we have more than two types in our experiment, so that this is a simplification. Nevertheless, we feel that this simple model captures the essential features of the environment.

  8. 8.

    Kartik (2009) also analyzes a sender-receiver game with lying costs. His setup closely resembles that of Crawford and Sobel (1982), with the addition of lying costs. This transforms the cheap talk model of Crawford and Sobel into a signalling game. Kartik shows that in his setup senders almost always claim to be more confident than they really are. His game has a different setup, so we cannot directly apply his results. For instance, the action set of the receiver is different and we have two-sided instead of one-sided private information. The payoff structure also differs, such that our game is a monotonic signalling game whereas the one by Kartik is not.

  9. 9.

    While this suggests overconfidence, we cannot reject rational Bayesian updating using the Burks et al. (2013) allocation function. This may reflect our having only two intervals, either above or below the median.

  10. 10.

    Note that Ewers and Zimmerman (2015) do find evidence that participants report higher confidence if an audience can observe the reports. Possibly, the effects are stronger in their study because participants could identify other participants, while in our experiment participants remain anonymous to each other. However, they also find no audience effect when that audience receives feedback about the participant’s actual performance. That treatment is most similar to our setup, because in our setup the receiver also receives feedback, and learns whether or not the sender had a higher rank than the receiver.

  11. 11.

    The difference in reported confidence by male senders in Deter and Social is not significant (\(Z=0.883,\) \(p=0.378\)).

  12. 12.

    If we split reported confidence in treatment Deter by the low and high outside option, we get: Male senders, low outside option: 72; male senders, high outside option: 74; male receivers, low outside option: 75; male receivers, high outside option: 76; female senders, low outside option: 58; female senders, high outside option: 61; female receivers, low outside option: 66; female receivers, high outside option: 57.

  13. 13.

    We focus primarily on entry with the high outside option, since 28 of 30 receivers chose entry with the low outside option, so that statistical tests have little power.

  14. 14.

    To be more specific, we estimate: \(Prob(Enters|\cdot ) = \Phi (\beta _0+\beta _1*\Delta Confidence+\beta _2*{{1}}_{\Delta Confidence \ge 0}+\varepsilon )\), where \(\Delta Confidence\) is the difference in confidence. The coefficient \(\beta _2\) is significantly different from zero in Lure but not in Deter. Estimates from a linear probability model yields significant coefficients in both treatments.

  15. 15.

    Estimates from a Linear Probability Model are qualitatively very similar.

  16. 16.

    With the caveat that the data is not sufficiently rich to exclude that receivers discount signals to a small degree.

  17. 17.

    Furthermore, when an article on the dangers of overconfidence appears, it may well be published in a women’s journal. See, for example, “When Confidence Can Be a Bad Thing,” in Women’s Health Magazine online, http://www.womenshealthmag.com/life/overconfidence.

  18. 18.

    The exact magnitude depends on the assumptions we make. In particular, the distribution of types matters. We have also estimated optimal reporting for alternative distributions (assuming a different mean or a uniform instead of normal distribution) but the under-inflating and deflating seems robust to different specifications.

  19. 19.

    These sessions were run in 2014. See Appendix D of the Online Supplementary Materials for more details.

  20. 20.

    We thank a referee for suggesting this idea.

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Acknowledgements

We acknowledge helpful comments from three anonymous referees, the Editor (Lise Vesterlund), and from Alex Brown, Juan Carrillo, Peter Cramton, Catherine Eckel, Enrique Fatas, Sanjeev Goyal, Philippe Jehiel, Juanjuan Meng, Markus Möbius, Klaus Schmidt, Lones Smith, Vernon Smith, Joel Sobel, Anton Suvorov, Cheng-Zhong Qin, Daniel Zizzo, and seminar participants at several universities including SITE (Stanford), USC, Toulouse, Peking University, Jinan University, University of Texas A&M, University of Aarhus, Ca’Foscari, Chapman University, University of East Anglia, Cambridge University, Goethe University (Frankfurt), New Economic School (Moscow), University of Maryland, CesIfo, Maastricht University, Tilburg University, Stockholm University, University of Michigan, Pompeu Fabra, Autonoma, University of Southampton, Washington University (St. Louis), and University of Wisconsin.

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Correspondence to Gary Charness.

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Charness, G., Rustichini, A. & van de Ven, J. Self-confidence and strategic behavior. Exp Econ 21, 72–98 (2018). https://doi.org/10.1007/s10683-017-9526-3

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Keywords

  • Self-confidence
  • Overconfidence
  • Strategic deterrence
  • Unconscious behavior
  • Self-deception
  • Luring
  • Experiment

JEL Classification

  • A12
  • C91
  • D03
  • D82