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Altruistic Observational Learning

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  • Christoph March
  • Anthony Ziegelmeyer

Abstract

We report two information cascade game experiments that directly test the impact of altruism on observational learning. Participants interact in two parallel sequences, the observed and the unobserved sequence. Only the actions of the observed entail informational benefits to subsequent participants. We find that observed contradict their private information significantly less often than unobserved when the monetary incentives to herd are moderately weak. Long laboratory cascades accumulate substantial public information which increases the earnings of participants. In Experiment 2, participants have better opportunities to learn about the strategies played by observed which amplifies the impact of altruism on observational learning.

Suggested Citation

  • Christoph March & Anthony Ziegelmeyer, 2016. "Altruistic Observational Learning," CESifo Working Paper Series 5792, CESifo.
    • Handle: RePEc:ces:ceswps:_5792
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    Cited by:

    1. Aleksei Smirnov & Egor Starkov, 2024. "Designing Social Learning," Papers 2405.05744, arXiv.org, revised Dec 2024.
    2. March, Christoph & Ziegelmeyer, Anthony, 2020. "Altruistic observational learning," Journal of Economic Theory, Elsevier, vol. 190(C).
    3. 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.

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    More about this item

    Keywords

    social learning; informational herding; altruistic behavior;
    All these keywords.

    JEL classification:

    • D64 - Microeconomics - - Welfare Economics - - - Altruism; Philanthropy; Intergenerational Transfers
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

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