Meaningful Learning in Weighted Voting Games: An Experiment

Eric Guerci, Nobuyuki Hanaki and Naoki Watanabe
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Naoki Watanabe: University of Tsukuba, Japan

No 2015-40, GREDEG Working Papers from Groupe de REcherche en Droit, Economie, Gestion (GREDEG CNRS), Université Côte d'Azur, France

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.

Keywords: Learning; voting game; experiment; two-armed bandit problem (search for similar items in EconPapers)
JEL-codes: C79 C92 D72 D83 (search for similar items in EconPapers)
Pages: 27 pages
Date: 2015-10
New Economics Papers: this item is included in nep-cdm, nep-exp, nep-gth and nep-pol
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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Related works:
Journal Article: Meaningful learning in weighted voting games: an experiment (2017)
Working Paper: Meaningful Learning in Weighted Voting Games: An Experiment (2017)
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Persistent link: https://EconPapers.repec.org/RePEc:gre:wpaper:2015-40

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