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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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    Cited by:

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

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    More about this item

    Keywords

    Elections; Expected margin of victory; Law of large numbers; Local limit theorem;
    All these keywords.

    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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