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A Bayesian Model of Voting in Juries

Author

Listed:
  • John Duggan

    (Department of Political Science, Department of Economics, University of Rochester)

  • Cesar Martinelli

    (Centro de Investigacion Economica (CIE), Instituto Tecnologico Autonomo de Mexico (ITAM))

Abstract

We take a game-theoretic approach to the analysis of juries by modelling voting as a game of incomplete information. Rather than the usual assumption of two possible signals (one indicating guilt, the other innocence), we allow jurors to perceive a full spectrum of signals. Given any voting rule requiring a fixed fraction of votes to convict, we characterize the unique symmetric equilibrium of the game, and we consider the possibility of asymmetric equilibria: we give a condition under which no asymmetric equilibria exist and show that, without under which no asymmetric equilibria exist and show that, without it, asymmetric equilibria may exist. We offer a condition under which unanimity rule exhibits a bias toward convicting the innocent, regardless of the size of the jury, and we exhibit an example showing this bias can be reversed. And we prove a "jury theorem" for our general model: as the size of the jury increases, the probability of a mistaken judgment goes to zero for every voting rule, except unanimity rule; for unanimity rule, we give a condition under which the probability of a mistake is bounded strictly above zero, and we show that, without this condition, the probability of a mistake may go to zero.

Suggested Citation

  • John Duggan & Cesar Martinelli, 1999. "A Bayesian Model of Voting in Juries," Working Papers 9904, Centro de Investigacion Economica, ITAM.
  • Handle: RePEc:cie:wpaper:9904
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    References listed on IDEAS

    as
    1. Chwe, Michael Suk-Young, 1999. "Minority Voting Rights Can Maximize Majority Welfare," American Political Science Review, Cambridge University Press, vol. 93(1), pages 85-97, March.
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    9. Duggan, John & Martinelli, Cesar, 2001. "A Bayesian Model of Voting in Juries," Games and Economic Behavior, Elsevier, vol. 37(2), pages 259-294, November.
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