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Heuristic and exact solutions to the inverse power index problem for small voting bodies

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  • Sascha Kurz
  • Stefan Napel

Abstract

Power indices are mappings that quantify the influence of the members of a voting body on collective decisions a priori. Their nonlinearity and discontinuity makes it difficult to compute inverse images, i.e., to determine a voting system which induces a power distribution as close as possible to a desired one. The paper considers approximations to this inverse problem for the Penrose-Banzhaf index by hill-climbing algorithms and exact solutions which are obtained by enumeration and integer linear programming techniques. They are compared to the results of three simple solution heuristics. The heuristics perform well in absolute terms but can be improved upon very considerably in relative terms. The findings complement known asymptotic results for large voting bodies and may improve termination criteria for local search algorithms. Copyright Springer Science+Business Media New York 2014

Suggested Citation

  • Sascha Kurz & Stefan Napel, 2014. "Heuristic and exact solutions to the inverse power index problem for small voting bodies," Annals of Operations Research, Springer, vol. 215(1), pages 137-163, April.
  • Handle: RePEc:spr:annopr:v:215:y:2014:i:1:p:137-163:10.1007/s10479-012-1293-0
    DOI: 10.1007/s10479-012-1293-0
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    Citations

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    Cited by:

    1. Matthias Weber, 2014. "Solving the Inverse Power Problem in Two-Tier Voting Settings," Tinbergen Institute Discussion Papers 14-019/I, Tinbergen Institute.
    2. Sascha Kurz, 2020. "Are weighted games sufficiently good for binary voting?," Papers 2006.05330, arXiv.org, revised Jul 2021.
    3. Kurz, Sascha & Maaser, Nicola & Napel, Stefan, 2018. "Fair representation and a linear Shapley rule," Games and Economic Behavior, Elsevier, vol. 108(C), pages 152-161.
    4. Grimmett, Geoffrey R., 2019. "On influence and compromise in two-tier voting systems," Mathematical Social Sciences, Elsevier, vol. 100(C), pages 35-45.
    5. Sascha Kurz, 2021. "Are Weighted Games Sufficiently Good for Binary Voting?," Homo Oeconomicus: Journal of Behavioral and Institutional Economics, Springer, vol. 38(1), pages 29-36, December.
    6. Weber, Matthias, 2016. "Two-tier voting: Measuring inequality and specifying the inverse power problem," Mathematical Social Sciences, Elsevier, vol. 79(C), pages 40-45.
    7. Le Breton, Michel & Lepelley, Dominique & Macé, Antonin & Merlin, Vincent, 2017. "Le mécanisme optimal de vote au sein du conseil des représentants d’un système fédéral," L'Actualité Economique, Société Canadienne de Science Economique, vol. 93(1-2), pages 203-248, Mars-Juin.
    8. Sascha Kurz, 2016. "The inverse problem for power distributions in committees," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 47(1), pages 65-88, June.
    9. N. Maaser, 2017. "Simple vs. Sophisticated Rules for the Allocation of Voting Weights," Homo Oeconomicus: Journal of Behavioral and Institutional Economics, Springer, vol. 34(1), pages 67-78, April.
    10. Freixas, Josep & Kurz, Sascha, 2016. "The cost of getting local monotonicity," European Journal of Operational Research, Elsevier, vol. 251(2), pages 600-612.
    11. Matthias Weber, 2014. "Choosing Voting Systems behind the Veil of Ignorance: A Two-Tier Voting Experiment," Tinbergen Institute Discussion Papers 14-042/I, Tinbergen Institute.
    12. de Mouzon, Olivier & Laurent, Thibault & Le Breton, Michel, 2020. "One Man, One Vote Part 2: Measurement of Malapportionment and Disproportionality and the Lorenz Curve," TSE Working Papers 20-1089, Toulouse School of Economics (TSE).
    13. Sascha Kurz & Nicola Maaser & Stefan Napel & Matthias Weber, 2014. "Mostly Sunny: A Forecast of Tomorrow's Power Index Research," Tinbergen Institute Discussion Papers 14-058/I, Tinbergen Institute.

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    More about this item

    Keywords

    Electoral systems; Simple games; Weighted voting games; Square root rule; Penrose limit theorem; Penrose-Banzhaf index; Institutional design;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C71 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Cooperative Games
    • D02 - Microeconomics - - General - - - Institutions: Design, Formation, Operations, and Impact

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