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A Nonequilibrium Analysis of Unanimity Rule, Majority Rule, and Pareto


  • Keith L. Dougherty
  • Julian Edward


It is widely held that in the absence of transaction costs unanimity rule is more effective at producing Pareto improvements and Pareto optimal outcomes than majority rule. We compare unanimity rule and majority rule in their ability to adhere to the Pareto criterion and to select Pareto-optimal alternatives using a single-dimensional spatial voting model without rational proposals. This produces two interesting results. First, if proposals are random, then majority rule is almost always more adept at selecting Pareto-optimal alternatives than unanimity rule. Second, if individuals propose their ideal points, then majority rule selects Pareto-optimal outcomes at least as well as unanimity rule. These results contrast with equilibrium analyses, which typically show that unanimity rule is the best voting procedure for maintaining Pareto optimality. (JEL D7, C61) Copyright 2005, Oxford University Press.

Suggested Citation

  • Keith L. Dougherty & Julian Edward, 2005. "A Nonequilibrium Analysis of Unanimity Rule, Majority Rule, and Pareto," Economic Inquiry, Western Economic Association International, vol. 43(4), pages 855-864, October.
  • Handle: RePEc:oup:ecinqu:v:43:y:2005:i:4:p:855-864

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    Cited by:

    1. Keith Dougherty, 2012. "Buchanan and Tullock’s apple," Public Choice, Springer, vol. 152(3), pages 403-406, September.
    2. Laurent Bouton & Aniol Llorente-Saguer & Frédéric Malherbe, 2014. "Get Rid of Unanimity: The Superiority of Majority Rule with Veto Power," NBER Working Papers 20417, National Bureau of Economic Research, Inc.
    3. Keith Dougherty & Julian Edward, 2012. "Voting for Pareto optimality: a multidimensional analysis," Public Choice, Springer, vol. 151(3), pages 655-678, June.

    More about this item

    JEL classification:

    • D7 - Microeconomics - - Analysis of Collective Decision-Making
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis


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