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The Swing Voter's Curse in Social Networks

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  • Buechel, Berno
  • Mechtenberg, Lydia

Abstract

We study private communication in social networks prior to a majority vote on two alternative policies. Some (or all) agents receive a private imperfect signal about which policy is correct. They can, but need not, recommend a policy to their neighbors in the social network prior to the vote. We show theoretically and empirically that communication can undermine efficiency of the vote and hence reduce welfare in a common interest setting. Both efficiency and existence of fully informative equilibria in which vote recommendations are always truthfully given and followed hinge on the structure of the communication network. If some voters have distinctly larger audiences than others, their neighbors should not follow their vote recommendation; however, they may do so in equilibrium. We test the model in a lab experiment and strong support for the comparative-statics and, more generally, for the importance of the network structure for voting behavior.

Suggested Citation

  • Buechel, Berno & Mechtenberg, Lydia, "undated". "The Swing Voter's Curse in Social Networks," ETA: Economic Theory and Applications 253218, Fondazione Eni Enrico Mattei (FEEM).
    • Handle: RePEc:ags:feemth:253218
    DOI: 10.22004/ag.econ.253218
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    Citations

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    Cited by:

    1. Jordi Brandts & Leonie Gerhards & Lydia Mechtenberg, 2018. "Deliberative Structures and their Impact on Voting under Economic Conflict," Working Papers 1022, Barcelona School of Economics.
    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. Jordi Brandts & Leonie Gerhards & Lydia Mechtenberg, 2022. "Deliberative structures and their impact on voting under economic conflict," Experimental Economics, Springer;Economic Science Association, vol. 25(2), pages 680-705, April.
    4. Liu, Shuo, 2019. "Voting with public information," Games and Economic Behavior, Elsevier, vol. 113(C), pages 694-719.
    5. Pogorelskiy. Kirill & Shum, Matthew, 2019. "News We Like to Share : How News Sharing on Social Networks Influences Voting Outcomes," The Warwick Economics Research Paper Series (TWERPS) 1199, University of Warwick, Department of Economics.
    6. Marco Battaglini & Rebecca B. Morton & Eleonora Patacchini, 2020. "Social Groups and the Effectiveness of Protests," Working Papers 20200039, New York University Abu Dhabi, Department of Social Science, revised Feb 2020.
    7. Guha Brishti, 2020. "Should Jurors Deliberate?," Review of Law & Economics, De Gruyter, vol. 16(2), pages 1-27, July.
    8. Martin E Andresen & Martin Huber, 2021. "Instrument-based estimation with binarised treatments: issues and tests for the exclusion restriction," The Econometrics Journal, Royal Economic Society, vol. 24(3), pages 536-558.
    9. Sang-Hyun Kim,, 2024. "Transitive delegation in social networks: Theory and experiment," European Journal of Political Economy, Elsevier, vol. 82(C).
    10. Pogorelskiy, Kirill & Shum, Matthew, 2019. "News We Like to Share: How News Sharing on Social Networks Influences Voting Outcomes," CAGE Online Working Paper Series 427, Competitive Advantage in the Global Economy (CAGE).
    11. Guha, Brishti, 2017. "Should Jurors Deliberate?," MPRA Paper 79876, University Library of Munich, Germany.
    12. Kerman, Toygar & Tenev, Anastas P., 2021. "Persuading communicating voters," Research Memorandum 003, Maastricht University, Graduate School of Business and Economics (GSBE).

    More about this item

    Keywords

    ;

    JEL classification:

    • 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
    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation
    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior

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