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Efficient Incentives in Social Networks: Gamification and the Coase Theorem

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  • Daske, Thomas

Abstract

This study explores mechanism design for networks of interpersonal relationships. Agents' social (more or less altruistic or spiteful) preferences and private payoffs are all subject to asymmetric information. Remarkably, the asymmetry of information about agents' social preferences can be operationalized to satisfy agents' participation constraints. The main result is a constructive proof of the Coase theorem, in its typical mechanism-design interpretation, for networks of at least three agents: If endowments are sufficiently large, any such network can resolve any given allocation problem with an ex-post budget-balanced mechanism that is Bayesian incentive-compatible, interim individually rational, and ex-post Pareto-efficient. The endogenously derived solution concept is interpreted as gamification: Resolve the agents' allocation problem with an efficient social-preference robust mechanism; attract agents' participation by complementing this mechanism with a budget-balanced game that operates on their social preferences and provides them with a platform to live out their propensities to cooperate or compete.
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  • Daske, Thomas, 2020. "Efficient Incentives in Social Networks: Gamification and the Coase Theorem," EconStor Preprints 213805, ZBW - Leibniz Information Centre for Economics.
  • Handle: RePEc:zbw:esprep:213805
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    1. Daske, Thomas, 2021. "The Incentive Costs of Welfare Judgments," EconStor Preprints 230318, ZBW - Leibniz Information Centre for Economics.

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    More about this item

    JEL classification:

    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
    • C78 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Bargaining Theory; Matching Theory
    • D62 - Microeconomics - - Welfare Economics - - - Externalities
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design

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