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Persuading communicating voters

Author

Listed:
  • Kerman, Toygar

    (General Economics 0 (Onderwijs), RS: GSBE other - not theme-related research)

  • Tenev, Anastas P.

    (General Economics 0 (Onderwijs), RS: GSBE Theme Conflict & Cooperation)

Abstract

This paper studies a multiple-receiver Bayesian persuasion model, where a sender communicates with receivers who have homogeneous beliefs and aligned preferences. The sender wants to implement a proposal and commits to a communication strategy which sends private (possibly) correlated messages to the receivers, who are in an exogenous and commonly known network. Receivers can observe their neighbors’ private messages and after updating their beliefs, vote sincerely on the proposal. We examine how networks of shared information affect the sender’s gain from persuasion and find that in many cases it is not restricted by the additional information provided by the receivers’ neighborhoods. Perhaps surprisingly, the sender’s gain from persuasion is not monotonically decreasing with the density of the network.

Suggested Citation

  • Kerman, Toygar & Tenev, Anastas P., 2021. "Persuading communicating voters," Research Memorandum 003, Maastricht University, Graduate School of Business and Economics (GSBE).
    • Handle: RePEc:unm:umagsb:2021003
    DOI: 10.26481/umagsb.2021003
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    References listed on IDEAS

    as
    1. Emir Kamenica & Matthew Gentzkow, 2011. "Bayesian Persuasion," American Economic Review, American Economic Association, vol. 101(6), pages 2590-2615, October.
    2. Kerman, Toygar & Herings, P. Jean-Jacques & Karos, Dominik, 2020. "Persuading Strategic Voters," Research Memorandum 004, Maastricht University, Graduate School of Business and Economics (GSBE).
    3. Ozan Candogan & Kimon Drakopoulos, 2020. "Optimal Signaling of Content Accuracy: Engagement vs. Misinformation," Operations Research, INFORMS, vol. 68(2), pages 497-515, March.
    4. Buechel, Berno & Mechtenberg, Lydia, 2019. "The swing voter's curse in social networks," Games and Economic Behavior, Elsevier, vol. 118(C), pages 241-268.
    5. Chan, Jimmy & Gupta, Seher & Li, Fei & Wang, Yun, 2019. "Pivotal persuasion," Journal of Economic Theory, Elsevier, vol. 180(C), pages 178-202.
      • Jimmy Chan & Seher Gupta & Fei Li & Yun Wang, 2018. "Pivotal Persuasion," Working Papers 2018-11-03, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
    6. Bergemann, Dirk & Morris, Stephen, 2016. "Bayes correlated equilibrium and the comparison of information structures in games," Theoretical Economics, Econometric Society, vol. 11(2), May.
    7. Schnakenberg, Keith E., 2015. "Expert advice to a voting body," Journal of Economic Theory, Elsevier, vol. 160(C), pages 102-113.
    8. Yun Wang, 2015. "Bayesian Persuasion with Multiple Receivers," Working Papers 2015-03-24, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
    9. Ina Taneva, 2019. "Information Design," American Economic Journal: Microeconomics, American Economic Association, vol. 11(4), pages 151-185, November.
    10. Ricardo Alonso & Odilon Câmara, 2016. "Persuading Voters," American Economic Review, American Economic Association, vol. 106(11), pages 3590-3605, November.
    11. Bardhi, Arjada & Guo, Yingni, 2018. "Modes of persuasion toward unanimous consent," Theoretical Economics, Econometric Society, vol. 13(3), September.
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    Cited by:

    1. Itai Arieli & Yakov Babichenko & Fedor Sandomirskiy, 2022. "Bayesian Persuasion with Mediators," Papers 2203.04285, arXiv.org, revised Sep 2022.

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    More about this item

    JEL classification:

    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
    • D72 - Microeconomics - - Analysis of Collective Decision-Making - - - Political Processes: Rent-seeking, Lobbying, Elections, Legislatures, and Voting Behavior
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation

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