IDEAS home Printed from https://ideas.repec.org/p/mse/cesdoc/23008.html
   My bibliography  Save this paper

From local to global estimations of confidence in perceptual decisions

Author

Abstract

Perceptual confidence has been an important topic recently. However, one key limitation in current approaches is that most studies have focused on confidence judgments made for single decisions. In three experiments, we investigate how these local confidence judgments relate and contribute to global confidence judgments, by which observers summarize their performance over a series of perceptual decisions. We report two main results. First, we find that participants exhibit more overconfidence in their local than in their global judgments of performance, an observation mirroring the aggregation effect in knowledge-based decisions. We further show that this effect is specific to confidence judgments and does not reflect a calculation bias. Second, we document a novel effect by which participants global confidence is larger for sets which are more heterogeneous in terms of difficulty, even when actual performance is controlled for. Surprisingly, we find that this effect of variability also occurs at the level of local confidence judgments, in a manner that fully explains the effect at the global level. Overall, our results indicate that global confidence is based on local confidence, although these two processes can be partially dissociated. We discuss possible theoretical accounts to relate and empirical investigations of how observers develop and use a global sense of perceptual confidence

Suggested Citation

  • Quentin Cavalan & Jean-Christophe Vergnaud & Vincent De Gardelle, 2023. "From local to global estimations of confidence in perceptual decisions," Documents de travail du Centre d'Economie de la Sorbonne 23008, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
  • Handle: RePEc:mse:cesdoc:23008
    as

    Download full text from publisher

    File URL: https://shs.hal.science/halshs-04075783
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Marine Hainguerlot & Jean-Christophe Vergnaud & Vincent de Gardelle, 2018. "Metacognitive ability predicts learning cue-stimulus associations in the absence of external feedback," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-01761531, HAL.
    2. 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.
    Full references (including those not matched with items on IDEAS)

    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. Thunström, Linda & Nordström, Jonas & Shogren, Jason F., 2015. "Certainty and overconfidence in future preferences for food," Journal of Economic Psychology, Elsevier, vol. 51(C), pages 101-113.
    2. Daniel Fonseca Costa & Francisval Carvalho & Bruno César Moreira & José Willer Prado, 2017. "Bibliometric analysis on the association between behavioral finance and decision making with cognitive biases such as overconfidence, anchoring effect and confirmation bias," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(3), pages 1775-1799, June.
    3. Herz, Holger & Schunk, Daniel & Zehnder, Christian, 2014. "How do judgmental overconfidence and overoptimism shape innovative activity?," Games and Economic Behavior, Elsevier, vol. 83(C), pages 1-23.
    4. David Hirshleifer & Angie Low & Siew Hong Teoh, 2012. "Are Overconfident CEOs Better Innovators?," Journal of Finance, American Finance Association, vol. 67(4), pages 1457-1498, August.
    5. Chih-Chung Ting & Nahuel Salem-Garcia & Stefano Palminteri & Jan B. Engelmann & Maël Lebreton, 2023. "Neural and computational underpinnings of biased confidence in human reinforcement learning," Nature Communications, Nature, vol. 14(1), pages 1-18, December.
    6. Tuan Pham, Michel & Meyvis, Tom & Zhou, Rongrong, 2001. "Beyond the Obvious: Chronic Vividness of Imagery and the Use of Information in Decision Making," Organizational Behavior and Human Decision Processes, Elsevier, vol. 84(2), pages 226-253, March.
    7. Brenner, Lyle & Griffin, Dale & Koehler, Derek J., 2005. "Modeling patterns of probability calibration with random support theory: Diagnosing case-based judgment," Organizational Behavior and Human Decision Processes, Elsevier, vol. 97(1), pages 64-81, May.
    8. 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.
    9. Ludwig, Sandra & Fellner-Röhling, Gerlinde & Thoma, Carmen, 2017. "Do women have more shame than men? An experiment on self-assessment and the shame of overestimating oneself," European Economic Review, Elsevier, vol. 92(C), pages 31-46.
    10. 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.
    11. repec:cup:judgdm:v:14:y:2019:i:4:p:395-411 is not listed on IDEAS
    12. Markus Glaser & Thomas Langer & Martin Weber, 2007. "On the Trend Recognition and Forecasting Ability of Professional Traders," Decision Analysis, INFORMS, vol. 4(4), pages 176-193, December.
    13. Fellner-Röhling, Gerlinde & Krügel, Sebastian, 2014. "Judgmental overconfidence and trading activity," Journal of Economic Behavior & Organization, Elsevier, vol. 107(PB), pages 827-842.
    14. Kausel, Edgar E. & Culbertson, Satoris S. & Madrid, Hector P., 2016. "Overconfidence in personnel selection: When and why unstructured interview information can hurt hiring decisions," Organizational Behavior and Human Decision Processes, Elsevier, vol. 137(C), pages 27-44.
    15. Craig R. Fox & Robert T. Clemen, 2005. "Subjective Probability Assessment in Decision Analysis: Partition Dependence and Bias Toward the Ignorance Prior," Management Science, INFORMS, vol. 51(9), pages 1417-1432, September.
    16. Danková, Katarína & Servátka, Maroš, 2019. "Gender robustness of overconfidence and excess entry," Journal of Economic Psychology, Elsevier, vol. 72(C), pages 179-199.
    17. Jiatao Li & Yi Tang, 2013. "The Social Influence of Executive Hubris," Management International Review, Springer, vol. 53(1), pages 83-107, February.
    18. repec:hal:wpaper:hal-00623966 is not listed on IDEAS
    19. Andersson, Patric, 2005. "Overconfident but yet well-calibrated and underconfident : a research not on judgmental miscalibration and flawed self-assessment," Papers 05-37, Sonderforschungsbreich 504.
    20. repec:cup:judgdm:v:15:y:2020:i:6:p:994-1008 is not listed on IDEAS
    21. Bonaccio, Silvia & Dalal, Reeshad S., 2006. "Advice taking and decision-making: An integrative literature review, and implications for the organizational sciences," Organizational Behavior and Human Decision Processes, Elsevier, vol. 101(2), pages 127-151, November.
    22. Michailova, Julija, 2010. "Development of the overconfidence measurement instrument for the economic experiment," MPRA Paper 34799, University Library of Munich, Germany, revised Nov 2011.
    23. Smith, Michael, 2022. "Monetizing virtuous employees," Accounting, Organizations and Society, Elsevier, vol. 98(C).

    More about this item

    Keywords

    overconfidence; confidence-frequency effect; aggregation effect;
    All these keywords.

    JEL classification:

    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making

    Statistics

    Access and download statistics

    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:mse:cesdoc:23008. 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: Lucie Label (email available below). General contact details of provider: https://edirc.repec.org/data/cenp1fr.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.