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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 find 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, 2017. "The swing voter's curse in social networks," FSES Working Papers 485, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
  • Handle: RePEc:fri:fribow:fribow00485
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    References listed on IDEAS

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    Cited by:

    1. 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.
    2. 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.
    3. Guha, Brishti, 2017. "Should Jurors Deliberate?," MPRA Paper 79876, University Library of Munich, Germany.
    4. Kerman, Toygar & Tenev, Anastas P., 2021. "Persuading communicating voters," Research Memorandum 003, Maastricht University, Graduate School of Business and Economics (GSBE).
    5. Jordi Brandts & Leonie Gerhards & Lydia Mechtenberg, 2018. "Deliberative Structures and their Impact on Voting under Economic Conflict," Working Papers 1022, Barcelona School of Economics.
    6. Kerman, Toygar & Herings, P. Jean-Jacques & Karos, Dominik, 2020. "Persuading Strategic Voters," Research Memorandum 004, Maastricht University, Graduate School of Business and Economics (GSBE).
    7. 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.
    8. Guha Brishti, 2020. "Should Jurors Deliberate?," Review of Law & Economics, De Gruyter, vol. 16(2), pages 1-27, July.
    9. 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.
    10. Liu, Shuo, 2019. "Voting with public information," Games and Economic Behavior, Elsevier, vol. 113(C), pages 694-719.
    11. 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).

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    More about this item

    Keywords

    Strategic Voting; Social Networks; Swing Voter’s Curse; Information Aggregation;
    All these 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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