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The swing voter's curse in social networks

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  • Buechel, Berno
  • Mechtenberg, Lydia

Abstract

We study communication in social networks prior to a majority vote on two alternative policies. Some agents receive a private imperfect signal about which policy is correct. They can recommend a policy to their neighbors in the social network prior to the vote. We show theoretically and empirically that communication can undermine efficiency and hence reduce welfare in a common-interest setting. Both efficiency and existence of fully informative equilibria in which vote recommendations are truthfully given and followed hinge on the structure of the 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 laboratory experiment and find rather inefficient equilibrium selection. Based on this result, there is support for the comparative statics of our model and, more generally, for the importance of the network structure for voting behavior.

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  • Buechel, Berno & Mechtenberg, Lydia, 2019. "The swing voter's curse in social networks," Games and Economic Behavior, Elsevier, vol. 118(C), pages 241-268.
  • Handle: RePEc:eee:gamebe:v:118:y:2019:i:c:p:241-268
    DOI: 10.1016/j.geb.2019.08.009
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    1. Marco Battaglini & Rebecca B. Morton & Thomas R. Palfrey, 2010. "The Swing Voter's Curse in the Laboratory," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 77(1), pages 61-89.
    2. Benjamin Golub & Matthew O. Jackson, 2010. "Naïve Learning in Social Networks and the Wisdom of Crowds," American Economic Journal: Microeconomics, American Economic Association, vol. 2(1), pages 112-149, February.
    3. Austen-Smith, David & Banks, Jeffrey S., 1996. "Information Aggregation, Rationality, and the Condorcet Jury Theorem," American Political Science Review, Cambridge University Press, vol. 90(1), pages 34-45, March.
    4. Jeong, Daeyoung, 2019. "Using cheap talk to polarize or unify a group of decision makers," Journal of Economic Theory, Elsevier, vol. 180(C), pages 50-80.
    5. Timothy Feddersen & Wolfgang Pesendorfer, 1997. "Voting Behavior and Information Aggregation in Elections with Private Information," Econometrica, Econometric Society, vol. 65(5), pages 1029-1058, September.
    6. Francis Bloch & Gabrielle Demange & Rachel Kranton, 2018. "Rumors And Social Networks," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 59(2), pages 421-448, May.
    7. Gilat Levy & Ronny Razin, 2015. "Correlation Neglect, Voting Behavior, and Information Aggregation," American Economic Review, American Economic Association, vol. 105(4), pages 1634-1645, April.
    8. Morton, Rebecca B. & Tyran, Jean-Robert, 2011. "Let the experts decide? Asymmetric information, abstention, and coordination in standing committees," Games and Economic Behavior, Elsevier, vol. 72(2), pages 485-509, June.
    9. Guarnaschelli, Serena & McKelvey, Richard D. & Palfrey, Thomas R., 2000. "An Experimental Study of Jury Decision Rules," American Political Science Review, Cambridge University Press, vol. 94(2), pages 407-423, June.
    10. repec:oup:qjecon:v:132:y:2016:i:1:p:485-549. is not listed on IDEAS
    11. Thomas R Palfrey & Kirill Pogorelskiy, 2019. "Communication Among Voters Benefits the Majority Party," The Economic Journal, Royal Economic Society, vol. 129(618), pages 961-990.
    12. Feddersen, Timothy J & Pesendorfer, Wolfgang, 1996. "The Swing Voter's Curse," American Economic Review, American Economic Association, vol. 86(3), pages 408-424, June.
    13. Dittmann, Ingolf & Kübler, Dorothea & Maug, Ernst & Mechtenberg, Lydia, 2014. "Why votes have value: Instrumental voting with overconfidence and overestimation of others' errors," Games and Economic Behavior, Elsevier, vol. 84(C), pages 17-38.
    14. Großer, Jens & Seebauer, Michael, 2016. "The curse of uninformed voting: An experimental study," Games and Economic Behavior, Elsevier, vol. 97(C), pages 205-226.
    15. Peter M. DeMarzo & Dimitri Vayanos & Jeffrey Zwiebel, 2003. "Persuasion Bias, Social Influence, and Unidimensional Opinions," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 118(3), pages 909-968.
    16. Feddersen, Timothy & Pesendorfer, Wolfgang, 1998. "Convicting the Innocent: The Inferiority of Unanimous Jury Verdicts under Strategic Voting," American Political Science Review, Cambridge University Press, vol. 92(1), pages 23-35, March.
    17. Kohei Kawamura & Vasileios Vlaseros, 2013. "Expert Information and Majority Decisions," Edinburgh School of Economics Discussion Paper Series 220, Edinburgh School of Economics, University of Edinburgh.
    18. 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).
    19. Liu, Shuo, 2019. "Voting with public information," Games and Economic Behavior, Elsevier, vol. 113(C), pages 694-719.
    20. McLennan, Andrew, 1998. "Consequences of the Condorcet Jury Theorem for Beneficial Information Aggregation by Rational Agents," American Political Science Review, Cambridge University Press, vol. 92(2), pages 413-418, June.
    21. 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.
    22. Bock, Olaf & Baetge, Ingmar & Nicklisch, Andreas, 2014. "hroot: Hamburg Registration and Organization Online Tool," European Economic Review, Elsevier, vol. 71(C), pages 117-120.
    23. Austen-Smith, David & Feddersen, Timothy J., 2006. "Deliberation, Preference Uncertainty, and Voting Rules," American Political Science Review, Cambridge University Press, vol. 100(2), pages 209-217, May.
    24. Lloyd Shapley & Bernard Grofman, 1984. "Optimizing group judgmental accuracy in the presence of interdependencies," Public Choice, Springer, vol. 43(3), pages 329-343, January.
    25. Benjamin Golub & Matthew O. Jackson, 2012. "How Homophily Affects the Speed of Learning and Best-Response Dynamics," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 127(3), pages 1287-1338.
    26. Jacob K. Goeree & Leeat Yariv, 2011. "An Experimental Study of Collective Deliberation," Econometrica, Econometric Society, vol. 79(3), pages 893-921, May.
    27. Pietro Ortoleva & Erik Snowberg, 2015. "Overconfidence in Political Behavior," American Economic Review, American Economic Association, vol. 105(2), pages 504-535, February.
    28. Marco Battaglini, 2017. "Public Protests and Policy Making," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 132(1), pages 485-549.
    29. Crawford, Vincent P & Sobel, Joel, 1982. "Strategic Information Transmission," Econometrica, Econometric Society, vol. 50(6), pages 1431-1451, November.
    30. Matias Iaryczower & Xiaoxia Shi & Matthew Shum, 2018. "Can Words Get in the Way? The Effect of Deliberation in Collective Decision Making," Journal of Political Economy, University of Chicago Press, vol. 126(2), pages 688-734.
    31. Coughlan, Peter J., 2000. "In Defense of Unanimous Jury Verdicts: Mistrials, Communication, and Strategic Voting," American Political Science Review, Cambridge University Press, vol. 94(2), pages 375-393, June.
    32. Ignacio Esponda Jr. & Emanuel Vespa Jr., 2014. "Hypothetical Thinking and Information Extraction in the Laboratory," American Economic Journal: Microeconomics, American Economic Association, vol. 6(4), pages 180-202, November.
    33. Kawamura, Kohei & Vlaseros, Vasileios, 2017. "Expert information and majority decisions," Journal of Public Economics, Elsevier, vol. 147(C), pages 77-88.
    34. Nitzan, Shmuel & Paroush, Jacob, 1982. "Optimal Decision Rules in Uncertain Dichotomous Choice Situations," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 23(2), pages 289-297, June.
    35. Gerardi, Dino & Yariv, Leeat, 2007. "Deliberative voting," Journal of Economic Theory, Elsevier, vol. 134(1), pages 317-338, May.
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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. Kerman, Toygar & Tenev, Anastas P., 2021. "Persuading communicating voters," Research Memorandum 003, Maastricht University, Graduate School of Business and Economics (GSBE).
    3. Jordi Brandts & Leonie Gerhards & Lydia Mechtenberg, 2018. "Deliberative Structures and their Impact on Voting under Economic Conflict," Working Papers 1022, Barcelona School of Economics.
    4. Kerman, Toygar & Herings, P. Jean-Jacques & Karos, Dominik, 2020. "Persuading Strategic Voters," Research Memorandum 004, Maastricht University, Graduate School of Business and Economics (GSBE).
    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. Guha Brishti, 2020. "Should Jurors Deliberate?," Review of Law & Economics, De Gruyter, vol. 16(2), pages 1-27, July.
    7. Sang-Hyun Kim,, 2024. "Transitive delegation in social networks: Theory and experiment," European Journal of Political Economy, Elsevier, vol. 82(C).
    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. 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.
    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).
    12. Guha, Brishti, 2017. "Should Jurors Deliberate?," MPRA Paper 79876, University Library of Munich, Germany.

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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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