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A statistical model for Condorcet efficiency based on simulation under spatial model assumptions

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  • Samuel Merrill

Abstract

This essay evaluates six single-winner, multicandidate electoral systems with respect to their tendency to choose Condorcet candidates. To this end I calibrate a logistic multiple regression model from Monte Carlo simulations, based on a multivariate normal spatial model, in which I vary the number of candidates, number of dimensions, correlation structure, and relative dispersion of candidates and voters. I investigate additional spatial-model variations by comparing further simulation results with predictions of the basic statistical model. The results suggest that for many electoral systems, Condorcet efficiency would increase with perceptual uncertainty of candidates' positions and would be low in a polarized society. Of the voting systems studied, approval voting and the Coombs systems appear least sensitive to variations in assumptions. Copyright Martinus Nijhoff Publishers 1985

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  • Samuel Merrill, 1985. "A statistical model for Condorcet efficiency based on simulation under spatial model assumptions," Public Choice, Springer, vol. 47(2), pages 389-403, January.
    • Handle: RePEc:kap:pubcho:v:47:y:1985:i:2:p:389-403
    DOI: 10.1007/BF00127534
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    References listed on IDEAS

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    1. Aldrich, John H. & McKelvey, Richard D., 1977. "A Method of Scaling with Applications to the 1968 and 1972 Presidential Elections," American Political Science Review, Cambridge University Press, vol. 71(1), pages 111-130, March.
    2. Chamberlin, John R. & Cohen, Michael D., 1978. "Toward Applicable Social Choice Theory: A Comparison of Social Choice Functions under Spatial Model Assumptions," American Political Science Review, Cambridge University Press, vol. 72(4), pages 1341-1356, December.
    3. Samuel Merrill, 1981. "Strategic decisions under one-stage multi-candidate voting systems," Public Choice, Springer, vol. 36(1), pages 115-134, January.
    4. Nurmi, Hannu, 1983. "Voting Procedures: A Summary Analysis," British Journal of Political Science, Cambridge University Press, vol. 13(2), pages 181-208, April.
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    Cited by:

    1. Mostapha Diss & Ahmed Doghmi, 2016. "Multi-winner scoring election methods: Condorcet consistency and paradoxes," Public Choice, Springer, vol. 169(1), pages 97-116, October.
    2. Conal Duddy, 2017. "Geometry of run-off elections," Public Choice, Springer, vol. 173(3), pages 267-288, December.
    3. Stephen Wright & William Riker, 1989. "Plurality and runoff systems and numbers of candidates," Public Choice, Springer, vol. 60(2), pages 155-175, February.
    4. Lirong Xia, 2021. "Semi-Random Impossibilities of Condorcet Criterion," Papers 2107.06435, arXiv.org, revised Aug 2022.
    5. Matteo Migheli & Guido Ortona & Ferruccio Ponzano, 2014. "Competition among parties and power: an empirical analysis," Annals of Operations Research, Springer, vol. 215(1), pages 201-214, April.
    6. Menezes, Mozart B.C. & da Silveira, Giovani J.C. & Drezner, Zvi, 2016. "Democratic elections and centralized decisions: Condorcet and Approval Voting compared with Median and Coverage locations," European Journal of Operational Research, Elsevier, vol. 253(1), pages 195-203.
    7. Lirong Xia, 2021. "The Smoothed Satisfaction of Voting Axioms," Papers 2106.01947, arXiv.org.
    8. Postl, Peter, 2017. "Évaluation et comparaison des règles de vote derrière le voile de l’ignorance : Tour d'horizon sélectif et analyse des règles de scores à deux paramètres," L'Actualité Economique, Société Canadienne de Science Economique, vol. 93(1-2), pages 249-290, Mars-Juin.
    9. Scott Feld & Bernard Grofman & Nicholas Miller, 1988. "Centripetal forces in spatial voting: On the size of the Yolk," Public Choice, Springer, vol. 59(1), pages 37-50, October.

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