IDEAS home Printed from https://ideas.repec.org/a/bla/jecrev/v66y2015i2p271-284.html
   My bibliography  Save this article

Maximum Likelihood Social Choice Rule

Author

Listed:
  • Yuta Nakamura

Abstract

type="main"> This study is related to a Condorcetian problem of information aggregation that finds a “true” social ordering using individual orderings, that are supposed to partly contain the “truth”. In this problem, we introduce a new maximum likelihood rule and analyse its performance. This rule selects an alternative that maximizes the probability of realizing individual orderings, conditional on the alternative being the top according to a true social ordering. We show that under a neutrality condition of alternatives, the probability that our rule selects the true top alternative is higher than that of any other rule.

Suggested Citation

  • Yuta Nakamura, 2015. "Maximum Likelihood Social Choice Rule," The Japanese Economic Review, Japanese Economic Association, vol. 66(2), pages 271-284, June.
  • Handle: RePEc:bla:jecrev:v:66:y:2015:i:2:p:271-284
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/jere.12065
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Ruth Ben-Yashar & Jacob Paroush, 2001. "Optimal decision rules for fixed-size committees in polychotomous choice situations," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 18(4), pages 737-746.
    2. Mohamed Drissi-Bakhkhat & Michel Truchon, 2004. "Maximum likelihood approach to vote aggregation with variable probabilities," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 23(2), pages 161-185, October.
    3. Young, H. P., 1988. "Condorcet's Theory of Voting," American Political Science Review, Cambridge University Press, vol. 82(4), pages 1231-1244, December.
    4. Peyton Young, 1995. "Optimal Voting Rules," Journal of Economic Perspectives, American Economic Association, vol. 9(1), pages 51-64, Winter.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Marcus Pivato, 2013. "Voting rules as statistical estimators," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 40(2), pages 581-630, February.
    2. Pivato, Marcus, 2017. "Epistemic democracy with correlated voters," Journal of Mathematical Economics, Elsevier, vol. 72(C), pages 51-69.
    3. Stephen Gordon & Michel Truchon, 2008. "Social choice, optimal inference and figure skating," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 30(2), pages 265-284, February.
    4. Conitzer, Vincent, 2012. "Should social network structure be taken into account in elections?," Mathematical Social Sciences, Elsevier, vol. 64(1), pages 100-102.
    5. Nehring, Klaus & Pivato, Marcus & Puppe, Clemens, 2011. "Condorcet admissibility: Indeterminacy and path-dependence under majority voting on interconnected decisions," MPRA Paper 32434, University Library of Munich, Germany.
    6. Truchon, Michel, 2008. "Borda and the maximum likelihood approach to vote aggregation," Mathematical Social Sciences, Elsevier, vol. 55(1), pages 96-102, January.
    7. Antonio Cabrales & Irma Clots-Figueras & Roberto Hernán-Gonzalez & Praveen Kujal, 2020. "Instiutions, Opportunism and Prosocial Behavior: Some Experimental Evidence," Working Papers 20-17, Chapman University, Economic Science Institute.
    8. Davide Grossi, 2021. "Lecture Notes on Voting Theory," Papers 2105.00216, arXiv.org.
    9. Piketty, Thomas, 1999. "The information-aggregation approach to political institutions," European Economic Review, Elsevier, vol. 43(4-6), pages 791-800, April.
    10. Truchon, Michel & Gordon, Stephen, 2009. "Statistical comparison of aggregation rules for votes," Mathematical Social Sciences, Elsevier, vol. 57(2), pages 199-212, March.
    11. Ruth Ben‐Yashar & Miriam Krausz & Shmuel Nitzan, 2018. "Government loan guarantees and the credit decision‐making structure," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 51(2), pages 607-625, May.
    12. Azzini, Ivano & Munda, Giuseppe, 2020. "A new approach for identifying the Kemeny median ranking," European Journal of Operational Research, Elsevier, vol. 281(2), pages 388-401.
    13. Sergei Gepshtein & Yurong Wang & Fangchao He & Dinh Diep & Thomas D. Albright, 2020. "A perceptual scaling approach to eyewitness identification," Nature Communications, Nature, vol. 11(1), pages 1-10, December.
    14. Truchon, Michel, 2004. "Aggregation of Rankings in Figure Skating," Cahiers de recherche 0402, Université Laval - Département d'économique.
    15. Florian Brandl & Dominik Peters, 2019. "An axiomatic characterization of the Borda mean rule," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 52(4), pages 685-707, April.
    16. Truchon, Michel, 1999. "La démocratie : oui, mais laquelle?," L'Actualité Economique, Société Canadienne de Science Economique, vol. 75(1), pages 189-214, mars-juin.
    17. Florian Brandl & Felix Brandt, 2020. "Arrovian Aggregation of Convex Preferences," Econometrica, Econometric Society, vol. 88(2), pages 799-844, March.
    18. Eyal Baharad & Ruth Ben-Yashar, 2021. "Judgment Aggregation by a Boundedly Rational Decision-Maker," Group Decision and Negotiation, Springer, vol. 30(4), pages 903-914, August.
    19. Noelia Rico & Camino R. Vela & Raúl Pérez-Fernández & Irene Díaz, 2021. "Reducing the Computational Time for the Kemeny Method by Exploiting Condorcet Properties," Mathematics, MDPI, vol. 9(12), pages 1-12, June.
    20. Le Breton, Michel & Truchon, Michel, 1997. "A Borda measure for social choice functions," Mathematical Social Sciences, Elsevier, vol. 34(3), pages 249-272, October.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bla:jecrev:v:66:y:2015:i:2:p:271-284. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/jeaaaea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.