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An Experiment On Social Mislearning

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  • Eyster, Erik

    (London School of Economics and Political Science)

  • Rabin, Matthew

    (Harvard University)

  • Weizsäcker, Georg

    (HU Berlin)

Abstract

We investigate experimentally whether social learners appreciate the redundancy of information conveyed by their observed predecessors\' actions. Each participant observes a private signal and enters an estimate of the sum of all earlier-moving participants\' signals plus her own. In a first treatment, participants move single-file and observe all predecessors\' entries; Bayesian Nash Equilibrium (BNE) predicts that each participant simply add her signal to her immediate predecessor\'s entry. Although 75% of participants do so, redundancy neglect by the other 25% generates excess imitation and mild inefficiencies. In a second treatment, participants move four per period; BNE predicts that most players anti-imitate some observed entries. Such anti-imitation occurs in 35% of the most transparent cases, and 16% overall. The remaining redundancy neglect creates dramatic excess imitation and inefficiencies: late-period entries are far too extreme, and on average participants would earn substantially more by ignoring their predecessors altogether.

Suggested Citation

  • Eyster, Erik & Rabin, Matthew & Weizsäcker, Georg, 2018. "An Experiment On Social Mislearning," Rationality and Competition Discussion Paper Series 73, CRC TRR 190 Rationality and Competition.
  • Handle: RePEc:rco:dpaper:73
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    Cited by:

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    2. Dasaratha, Krishna & He, Kevin, 2020. "Network structure and naive sequential learning," Theoretical Economics, Econometric Society, vol. 15(2), May.
    3. Cheng, Ing-Haw & Hsiaw, Alice, 2022. "Distrust in experts and the origins of disagreement," Journal of Economic Theory, Elsevier, vol. 200(C).
    4. Nicolas Astier, 2016. "Comparative Feedbacks under Incomplete Information," Working Papers hal-01465189, HAL.
    5. 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.
    6. Cary Frydman & Ian Krajbich, 2022. "Using Response Times to Infer Others’ Private Information: An Application to Information Cascades," Management Science, INFORMS, vol. 68(4), pages 2970-2986, April.
    7. Krishna Dasaratha & Kevin He, 2019. "Aggregative Efficiency of Bayesian Learning in Networks," Papers 1911.10116, arXiv.org, revised Aug 2023.
    8. 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).
    9. Sadler, Evan, 2020. "Innovation adoption and collective experimentation," Games and Economic Behavior, Elsevier, vol. 120(C), pages 121-131.
    10. Asanov, Igor, 2021. "Bandit cascade: A test of observational learning in the bandit problem," Journal of Economic Behavior & Organization, Elsevier, vol. 189(C), pages 150-171.
    11. Dasaratha, Krishna & He, Kevin, 2021. "An experiment on network density and sequential learning," Games and Economic Behavior, Elsevier, vol. 128(C), pages 182-192.
    12. Astier, Nicolas, 2018. "Comparative feedbacks under incomplete information," Resource and Energy Economics, Elsevier, vol. 54(C), pages 90-108.
    13. Marta Serra-Garcia & Uri Gneezy, 2021. "Mistakes, Overconfidence, and the Effect of Sharing on Detecting Lies," American Economic Review, American Economic Association, vol. 111(10), pages 3160-3183, October.
    14. March, Christoph & Ziegelmeyer, Anthony, 2020. "Altruistic observational learning," Journal of Economic Theory, Elsevier, vol. 190(C).

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    More about this item

    Keywords

    social learning; redundancy neglect; experiments; higher-order beliefs;
    All these keywords.

    JEL classification:

    • B49 - Schools of Economic Thought and Methodology - - Economic Methodology - - - Other

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