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Meaningful Learning in Weighted Voting Games: An Experiment

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  • Eric Guerci

    (GREDEG - Groupe de Recherche en Droit, Economie et Gestion - UNS - Université Nice Sophia Antipolis (1965 - 2019) - CNRS - Centre National de la Recherche Scientifique - UniCA - Université Côte d'Azur)

  • Nobuyuki Hanaki

    (GREDEG - Groupe de Recherche en Droit, Economie et Gestion - UNS - Université Nice Sophia Antipolis (1965 - 2019) - CNRS - Centre National de la Recherche Scientifique - UniCA - Université Côte d'Azur)

  • Naoki Watanabe

    (Faculty of Engineering, Information and Systems [Tsukuba] - Université de Tsukuba = University of Tsukuba)

Abstract

By employing binary committee choice problems, this paper investigates how varying or eliminating feedback about payoffs affects: (1) subjects' learning about the underlying relationship between their nominal voting weights and their expected payoffs in weighted voting games; and (2) the transfer of acquired learning from one committee choice problem to a similar but different problem. In the experiment, subjects choose to join one of two committees (weighted voting games) and obtain a payoff stochastically determined by a voting theory. We found that: (i) subjects learned to choose the committee that generates a higher expected payoff even without feedback about the payoffs they received; and (ii) there was statistically significant evidence of ``meaningful learning'' (transfer of learning) only for the treatment with no payoff-related feedback. This finding calls for re-thinking existing models of learning to incorporate some type of introspection.

Suggested Citation

  • Eric Guerci & Nobuyuki Hanaki & Naoki Watanabe, 2017. "Meaningful Learning in Weighted Voting Games: An Experiment," Post-Print halshs-01216244, HAL.
    • Handle: RePEc:hal:journl:halshs-01216244
    DOI: 10.1007/s11238-017-9588-x
    Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-01216244
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    Cited by:

    1. Eric Guerci & Nobuyuki Hanaki & Naoki Watanabe, 2017. "Meaningful learning in weighted voting games: an experiment," Theory and Decision, Springer, vol. 83(1), pages 131-153, June.
    2. Eric Guerci & Nobuyuki Hanaki & Naoki Watanabe & Gabriele Esposito & Xiaoyan Lu, 2014. "A methodological note on a weighted voting experiment," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 43(4), pages 827-850, December.
    3. Nicola Maaser & Fabian Paetzel & Stefan Traub, 2022. "Gender and Nominal Power in Multilateral Bargaining," Games, MDPI, vol. 13(1), pages 1-25, January.
    4. Naoki Watanabe, 2022. "Reconsidering Meaningful Learning in a Bandit Experiment on Weighted Voting: Subjects’ Search Behavior," The Review of Socionetwork Strategies, Springer, vol. 16(1), pages 81-107, April.
    5. Matthias Weber, 2014. "Choosing Voting Systems behind the Veil of Ignorance: A Two-Tier Voting Experiment," Tinbergen Institute Discussion Papers 14-042/I, Tinbergen Institute.

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    More about this item

    Keywords

    experiment; voting game; learning; two-armed bandit problem;
    All these keywords.

    JEL classification:

    • C79 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Other
    • C92 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Group Behavior
    • D72 - Microeconomics - - Analysis of Collective Decision-Making - - - Political Processes: Rent-seeking, Lobbying, Elections, Legislatures, and Voting Behavior
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

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