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Mimicking, errors, and the optimal standard of proof

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  • Mungan, Murat C.
  • Samuel, Andrew

Abstract

Criminals often engage in costly avoidance to lower their likelihood of being detected and sanctioned. Such avoidance, in turn, affects the optimal enforcement policy. This paper studies how the optimal standard of proof is affected by a specific type of avoidance, namely investments by guilty defendants to mimic innocent individuals. We show that when mimicking is possible the optimal standard of proof is weaker than preponderance of the evidence. This stands in contrast to much of the literature, which shows that non-deterrence costs usually cause the standard of proof to be stronger than preponderance. Thus, it is important not to ignore criminals’ secondary behavior when determining the optimal standard of proof.

Suggested Citation

  • Mungan, Murat C. & Samuel, Andrew, 2019. "Mimicking, errors, and the optimal standard of proof," Economics Letters, Elsevier, vol. 174(C), pages 18-21.
    • Handle: RePEc:eee:ecolet:v:174:y:2019:i:c:p:18-21
    DOI: 10.1016/j.econlet.2018.10.002
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    References listed on IDEAS

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    1. Demougin, Dominique & Fluet, Claude, 2006. "Preponderance of evidence," European Economic Review, Elsevier, vol. 50(4), pages 963-976, May.
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    4. Eric Langlais, 2008. "Detection Avoidance and Deterrence: Some Paradoxical Arithmetic," Journal of Public Economic Theory, Association for Public Economic Theory, vol. 10(3), pages 371-382, June.
    5. Murat C. Mungan, 2011. "A Utilitarian Justification for Heightened Standards of Proof in Criminal Trials," Journal of Institutional and Theoretical Economics (JITE), Mohr Siebeck, Tübingen, vol. 167(2), pages 352-370, June.
    6. Avraham D. Tabbach, 2010. "The Social Desirability of Punishment Avoidance," The Journal of Law, Economics, and Organization, Oxford University Press, vol. 26(2), pages 265-289.
    7. Matteo Rizzolli & Margherita Saraceno, 2013. "Better that ten guilty persons escape: punishment costs explain the standard of evidence," Public Choice, Springer, vol. 155(3), pages 395-411, June.
    8. Claude-Denys Fluet & Murat C. Mungan, 2017. "The Signal-Tuning Function of Liability Regimes," Cahiers de recherche 1707, Centre de recherche sur les risques, les enjeux économiques, et les politiques publiques.
    9. Png, I. P. L., 1986. "Optimal subsidies and damages in the presence of judicial error," International Review of Law and Economics, Elsevier, vol. 6(1), pages 101-105, June.
    10. Louis Kaplow, 2011. "On the Optimal Burden of Proof," Journal of Political Economy, University of Chicago Press, vol. 119(6), pages 1104-1140.
    11. Dechenaux, Emmanuel & Samuel, Andrew, 2014. "Announced vs. surprise inspections with tipping-off," European Journal of Political Economy, Elsevier, vol. 34(C), pages 167-183.
    12. Lando, Henrik & Mungan, Murat C., 2018. "The effect of type-1 error on deterrence," International Review of Law and Economics, Elsevier, vol. 53(C), pages 1-8.
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    Cited by:

    1. Murat C. Mungan & Marie Obidzinski & Yves Oytana, 2020. "Accuracy and Preferences for Legal Error," Working Papers 2020-09, CRESE.
    2. Mungan, Murat C. & Wright, Joshua, 2022. "Optimal standards of proof in antitrust," International Review of Law and Economics, Elsevier, vol. 71(C).
    3. Lundberg, Alexander & Mungan, Murat, 2022. "The effect of evidentiary rules on conviction rates," Journal of Economic Behavior & Organization, Elsevier, vol. 203(C), pages 563-576.
    4. Mungan Murat C., 2020. "The Optimal Standard of Proof with Adjudication Avoidance," Review of Law & Economics, De Gruyter, vol. 16(1), pages 1-7, March.

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