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Judgement Aggregation in Search for the Truth

Author

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  • Bozbay, I.

    (Quantitative Economics)

  • Dietrich, F.K.
  • Peters, H.J.M.

    (Quantitative Economics)

Abstract
We analyze the problem of aggregating judgments over multiple issues from the perspective of whether aggregate judgments manage to efficiently use all voters' private information. While new in judgment aggregation theory, this perspective is familiar in a different body of literature about voting between two alternatives where voters' disagreements stem from conflicts of information rather than of interest. Combining the two bodies of literature, we consider a simple judgment aggregation problem and model the private information underlying voters' judgments. Assuming that voters share a preference for true collective judgments, we analyze the resulting strategic incentives and determine which voting rules efficiently use all private information. We find that in certain, but not all cases a quota rule should be used, which decides on each issue according to whether the proportion of ‘yes’ votes exceeds a particular quota.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Bozbay, I. & Dietrich, F.K. & Peters, H.J.M., 2011. "Judgement Aggregation in Search for the Truth," Research Memorandum 040, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
    • Handle: RePEc:unm:umamet:2011040
    DOI: 10.26481/umamet.2011040
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    References listed on IDEAS

    as
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    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Masaki Miyashita, 2021. "Premise-based vs conclusion-based collective choice," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 57(2), pages 361-385, August.
    2. Franz Dietrich, 2014. "Scoring rules for judgment aggregation," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 42(4), pages 873-911, April.
    3. Dietrich, Franz, 2016. "Judgment aggregation and agenda manipulation," Games and Economic Behavior, Elsevier, vol. 95(C), pages 113-136.
    4. Ruth Ben-Yashar & Leif Danziger, 2014. "On the optimal composition of committees," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 43(4), pages 973-980, December.
    5. de Clippel, Geoffroy & Eliaz, Kfir, 2015. "Premise-based versus outcome-based information aggregation," Games and Economic Behavior, Elsevier, vol. 89(C), pages 34-42.
    6. Ahn, David S. & Oliveros, Santiago, 2014. "The Condorcet Jur(ies) Theorem," Journal of Economic Theory, Elsevier, vol. 150(C), pages 841-851.
    7. John A Weymark, 2014. "Cognitive Diversity, Binary Decisions, and Epistemic Democracy," Vanderbilt University Department of Economics Working Papers 14-00008, Vanderbilt University Department of Economics.
    8. repec:esx:essedp:743 is not listed on IDEAS
    9. Shu-Heng Chen & Ragupathy Venkatachalam, 2017. "Information aggregation and computational intelligence," Evolutionary and Institutional Economics Review, Springer, vol. 14(1), pages 231-252, June.
    10. Irem Bozbay, 2019. "Truth-tracking judgment aggregation over interconnected issues," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 53(2), pages 337-370, August.
    11. Zoi Terzopoulou & Ulle Endriss, 2019. "Strategyproof judgment aggregation under partial information," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 53(3), pages 415-442, October.
    12. Ben-Yashar, Ruth & Danziger, Leif, 2016. "The unanimity rule and extremely asymmetric committees," Journal of Mathematical Economics, Elsevier, vol. 64(C), pages 107-112.
    13. Mitri Kitti, 2016. "Axioms for centrality scoring with principal eigenvectors," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 46(3), pages 639-653, March.
    14. Irem Bozbay, 2015. "Truth-Tracking Judgment Aggregation Over Interconnected Issues," School of Economics Discussion Papers 0916, School of Economics, University of Surrey.
    15. Bozbay, Irem & Peters, Hans, 2019. "Information aggregation with a continuum of types," Economics Letters, Elsevier, vol. 180(C), pages 46-49.
    16. Masaki Miyashita, 2017. "Binary Collective Choice with Multiple Premises," Discussion Paper Series DP2017-27, Research Institute for Economics & Business Administration, Kobe University.
    17. Aureli Alabert & Mercè Farré & Rubén Montes, 2023. "Optimal Decision Rules for the Discursive Dilemma," Group Decision and Negotiation, Springer, vol. 32(4), pages 889-923, August.
    18. Alex Albright & Peter Pedroni & Stephen Sheppard, 2018. "Uncorking Expert Reviews with Social Media: A Case Study Served with Wine," Department of Economics Working Papers 2018-03, Department of Economics, Williams College.

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    More about this item

    JEL classification:

    • C70 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - General
    • D70 - Microeconomics - - Analysis of Collective Decision-Making - - - General
    • D71 - Microeconomics - - Analysis of Collective Decision-Making - - - Social Choice; Clubs; Committees; Associations
    • D80 - Microeconomics - - Information, Knowledge, and Uncertainty - - - General
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design

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