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Fragility of Information Cascades: An Experimental Study using Elicited Beliefs

Author

Listed:
  • Frederic Koessler

    (Paris School of Economics and CNRS)

  • Anthony Ziegelmeyer

    (Max Planck Institute for Research into Economic Systems, Strategic Interaction Group, Jena, Germany)

  • Juergen Bracht

    (University of Aberdeen Business School)

  • Eyal Winter

    (Center for Rationality and Interactive Decision Theory, Hebrew University of Jerusalem)

Abstract

This paper examines the occurrence and fragility of information cascades in laboratory experiments. One group of low informed subjects make predictions in sequence. In a matched pairs design, another set of high informed subjects observe the decisions of the first group and make predictions. According to the theory of information cascades (Bikhchandani, Hirshleifer, and Welch, 1992), if initial decisions coincide, an information cascade should occur: it is rational for subsequent players with low quality information to follow the observed pattern regardless of their private information. However, an information cascade should be fragile: it is always rational for subsequent players with high quality information to follow their private information. In line with existing experiments on information cascades, we find some evidence that low informed subjects follow the herd when it is rational, and this herding behavior occurs more frequently if there is a pronounced imbalance. The main finding of this paper is that information cascades are not fragile. We find strong evidence that highly informed subjects follow the herd regardless of their private information. In accordance with those observations we show, by explicitly eliciting subjects' beliefs about the state, that beliefs are not constant in the number of previous decisions that coincide, whether or not an information cascade already occurred. Subjects' behavior can be understood with a statistical model that allows for the possibility of errors in earlier decisions.

Suggested Citation

  • Frederic Koessler & Anthony Ziegelmeyer & Juergen Bracht & Eyal Winter, 2008. "Fragility of Information Cascades: An Experimental Study using Elicited Beliefs," Jena Economics Research Papers 2008-094, Friedrich-Schiller-University Jena.
  • Handle: RePEc:jrp:jrpwrp:2008-094
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    References listed on IDEAS

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    Cited by:

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    2. Penczynski, Stefan P., 2017. "The nature of social learning: Experimental evidence," European Economic Review, Elsevier, vol. 94(C), pages 148-165.
    3. Christoph March, 2011. "Adaptive social learning," PSE Working Papers halshs-00572528, HAL.
    4. Manski, Charles F. & Neri, Claudia, 2013. "First- and second-order subjective expectations in strategic decision-making: Experimental evidence," Games and Economic Behavior, Elsevier, vol. 81(C), pages 232-254.
    5. Christoph March & Sebastian Krügel & Anthony Ziegelmeyer, 2012. "Do We Follow Private Information when We Should? Laboratory Evidence on Naive Herding," Working Papers halshs-00671378, HAL.
    6. March, Christoph & Ziegelmeyer, Anthony, 2020. "Altruistic observational learning," Journal of Economic Theory, Elsevier, vol. 190(C).
    7. Paolo Crosetto & Antonio Filippin, 2017. "The Sound of Others: Surprising Evidence of Conformist Behavior," Southern Economic Journal, John Wiley & Sons, vol. 83(4), pages 1038-1051, April.
    8. Drehmann, Mathias & Oechssler, Jorg & Roider, Andreas, 2007. "Herding with and without payoff externalities -- an internet experiment," International Journal of Industrial Organization, Elsevier, vol. 25(2), pages 391-415, April.
    9. Lukas Meub & Till Proeger & Hendrik Hüning, 2017. "A comparison of endogenous and exogenous timing in a social learning experiment," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 12(1), pages 143-166, April.
    10. Choijil, Enkhbayar & Méndez, Christian Espinosa & Wong, Wing-Keung & Vieito, João Paulo & Batmunkh, Munkh-Ulzii, 2022. "Thirty years of herd behavior in financial markets: A bibliometric analysis," Research in International Business and Finance, Elsevier, vol. 59(C).
    11. Bohren, J. Aislinn, 2016. "Informational herding with model misspecification," Journal of Economic Theory, Elsevier, vol. 163(C), pages 222-247.
    12. Duffy, John & Hopkins, Ed & Kornienko, Tatiana, 2021. "Lone wolf or herd animal? Information choice and learning from others," European Economic Review, Elsevier, vol. 134(C).
    13. Diefeng Peng & Yulei Rao & Xianming Sun & Erte Xiao, 2019. "Optional Disclosure and Observational Learning," Monash Economics Working Papers 05-18, Monash University, Department of Economics.
    14. Aislinn Bohren, 2014. "Informational Herding with Model Misspecification, Second Version," PIER Working Paper Archive 15-022, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 01 Nov 2014.
    15. Cao, Qian & Li, Jianbiao & Niu, Xiaofei, 2019. "The role of overconfidence in overweighting private information: Does gender matter?," EconStor Preprints 203448, ZBW - Leibniz Information Centre for Economics.
    16. Puput Tri Komalasari & Marwan Asri & Bernardinus M. Purwanto & Bowo Setiyono, 2022. "Herding behaviour in the capital market: What do we know and what is next?," Management Review Quarterly, Springer, vol. 72(3), pages 745-787, September.
    17. Christoph March & Anthony Ziegelmeyer, 2018. "Excessive Herding in the Laboratory: The Role of Intuitive Judgments," CESifo Working Paper Series 6855, CESifo.
    18. Van Parys, Jessica & Ash, Elliott, 2018. "Sequential decision-making with group identity," Journal of Economic Psychology, Elsevier, vol. 69(C), pages 1-18.
    19. Meub, Lukas & Proeger, Till & Hüning, Hendrik, 2013. "A comparison of endogenous and exogenous timing in a social learning experiment," University of Göttingen Working Papers in Economics 167, University of Goettingen, Department of Economics.
    20. Bossan, Benjamin & Jann, Ole & Hammerstein, Peter, 2015. "The evolution of social learning and its economic consequences," Journal of Economic Behavior & Organization, Elsevier, vol. 112(C), pages 266-288.
    21. Polonio, Luca & Coricelli, Giorgio, 2019. "Testing the level of consistency between choices and beliefs in games using eye-tracking," Games and Economic Behavior, Elsevier, vol. 113(C), pages 566-586.
    22. Duffy, John & Hopkins, Ed & Kornienko, Tatiana & Ma, Mingye, 2019. "Information choice in a social learning experiment," Games and Economic Behavior, Elsevier, vol. 118(C), pages 295-315.

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    More about this item

    Keywords

    Information cascades; elicited beliefs; experimental economics;
    All these keywords.

    JEL classification:

    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
    • C92 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Group Behavior
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design

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