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How to win a large election

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  • Mandler, Michael

Abstract

We consider the optimization problem of a campaign trying to win an election when facing aggregate uncertainty, where agentsʼ voting probabilities are uncertain. Even a small amount of uncertainty will in a large electorate eliminate many of counterintuitive results that arise when voting probabilities are known. In particular, a campaign that can affect the voting probabilities of a fraction of the electorate should maximize the expected difference between its candidateʼs and the opposing candidateʼs share of the fractionʼs potential vote. When a campaign can target only finitely many voters, maximization of the same objective function remains optimal if a convergence condition is satisfied. When voting probabilities are certain, this convergence condition obtains only at knife-edge combinations of parameters, but when voting probabilities are uncertain the condition is necessarily satisfied.

Suggested Citation

  • Mandler, Michael, 2013. "How to win a large election," Games and Economic Behavior, Elsevier, vol. 78(C), pages 44-63.
  • Handle: RePEc:eee:gamebe:v:78:y:2013:i:c:p:44-63
    DOI: 10.1016/j.geb.2012.09.005
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    References listed on IDEAS

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    1. Aranson, Peter H. & Hinich, Melvin J. & Ordeshook, Peter C., 1974. "Election Goals and Strategies: Equivalent and Nonequivalent Candidate Objectives," American Political Science Review, Cambridge University Press, vol. 68(1), pages 135-152, March.
    2. John Ledyard, 1984. "The pure theory of large two-candidate elections," Public Choice, Springer, vol. 44(1), pages 7-41, January.
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    5. John Patty, 2007. "Generic difference of expected vote share and probability of victory maximization in simple plurality elections with probabilistic voters," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 29(1), pages 149-173, July.
    6. Myerson, Roger B., 2000. "Large Poisson Games," Journal of Economic Theory, Elsevier, vol. 94(1), pages 7-45, September.
    7. Feddersen, Timothy J & Pesendorfer, Wolfgang, 1996. "The Swing Voter's Curse," American Economic Review, American Economic Association, vol. 86(3), pages 408-424, June.
    8. Hinich, Melvin J., 1977. "Equilibrium in spatial voting: The median voter result is an artifact," Journal of Economic Theory, Elsevier, vol. 16(2), pages 208-219, December.
    9. Nathaniel Beck, 1975. "A note on the probability of a tied election," Public Choice, Springer, vol. 23(1), pages 75-79, September.
    10. Mandler, Michael, 2012. "The fragility of information aggregation in large elections," Games and Economic Behavior, Elsevier, vol. 74(1), pages 257-268.
    11. Myerson, Roger B., 2002. "Comparison of Scoring Rules in Poisson Voting Games," Journal of Economic Theory, Elsevier, vol. 103(1), pages 219-251, March.
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    Cited by:

    1. Mandler, Michael, 2012. "The fragility of information aggregation in large elections," Games and Economic Behavior, Elsevier, vol. 74(1), pages 257-268.
    2. Jan Zápal, 2017. "Crafting consensus," Public Choice, Springer, vol. 173(1), pages 169-200, October.

    More about this item

    Keywords

    Elections; Expected margin of victory; Law of large numbers; Local limit theorem;

    JEL classification:

    • D72 - Microeconomics - - Analysis of Collective Decision-Making - - - Political Processes: Rent-seeking, Lobbying, Elections, Legislatures, and Voting Behavior
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty

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