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In Dubio Pro Reo. Behavioral explanations of pro-defendant bias in procedures

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  • Antonio Nicita
  • Matteo Rizzolli

Abstract

The standard model of optimal deterrence predicts that the probability of wrongful conviction of the innocent is, at the margin, as detrimental to deterrence as the wrongful acquittal of guilty individuals. We extend the model in several directions: using expected utility as well as nonexpected utility to consider the role of risk aversion, non-linear probability weighting and loss aversion. We also consider how relevant emotions such as guilt, shame and indignation play out. Several of these factors support the intuition that wrongful convictions of the innocent do have a larger detrimental impact on deterrence and thus the policy implications are reconciled with the widely shared maxim in dubio pro reo. We then draw some theoretical implications such as a novel justification for the different standards of proof in criminal vs civil law as well as other policy implications.

Suggested Citation

  • Antonio Nicita & Matteo Rizzolli, 2012. "In Dubio Pro Reo. Behavioral explanations of pro-defendant bias in procedures," Department of Economics University of Siena 637, Department of Economics, University of Siena.
  • Handle: RePEc:usi:wpaper:637
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    Cited by:

    1. Rizzolli, Matteo & Tremewan, James, 2018. "Hard labor in the lab: Deterrence, non-monetary sanctions, and severe procedures," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 77(C), pages 107-121.
    2. Obidzinski, Marie & Oytana, Yves, 2019. "Identity errors and the standard of proof," International Review of Law and Economics, Elsevier, vol. 57(C), pages 73-80.
    3. Marie Obidzinski & Yves Oytana, 2018. "Identity mistakes and the standard of proof," Working Papers halshs-01879555, HAL.
    4. Marie Obidzinski & Yves Oytana, 2020. "Presumption of Innocence and Deterrence," Journal of Institutional and Theoretical Economics (JITE), Mohr Siebeck, Tübingen, vol. 176(2), pages 377-412.
    5. Markussen, Thomas & Putterman, Louis & Tyran, Jean-Robert, 2016. "Judicial error and cooperation," European Economic Review, Elsevier, vol. 89(C), pages 372-388.
    6. Yves Oytana & Marie Obidzinski, 2017. "How does the probability of wrongful conviction affect the standard of proof?," Working Papers 2017-02, CRESE.
    7. Mungan Murat C., 2018. "Mere Preparation," Review of Law & Economics, De Gruyter, vol. 14(2), pages 1-15, July.
    8. 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.
    9. Roee Sarel, 2022. "Crime and punishment in times of pandemics," European Journal of Law and Economics, Springer, vol. 54(2), pages 155-186, October.
    10. Mungan, Murat C., 2015. "Wrongful convictions and the punishment of attempts," International Review of Law and Economics, Elsevier, vol. 42(C), pages 79-87.
    11. Matteo Rizzolli, 2016. "Adjudication: Type-I and Type-II Errors," CERBE Working Papers wpC15, CERBE Center for Relationship Banking and Economics.
    12. Alice Guerra & Barbara Luppi & Francesco Parisi, 2022. "Do presumptions of negligence incentivize optimal precautions?," European Journal of Law and Economics, Springer, vol. 54(3), pages 349-368, December.

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    More about this item

    Keywords

    wrongful convictions; Type I errors; wrongful acquittals; Type II errors; evidence; optimal under-deterrence; behavioral economics; risk aversion; loss aversion; prospect theory; prelec function;
    All these keywords.

    JEL classification:

    • K14 - Law and Economics - - Basic Areas of Law - - - Criminal Law
    • K41 - Law and Economics - - Legal Procedure, the Legal System, and Illegal Behavior - - - Litigation Process
    • K42 - Law and Economics - - Legal Procedure, the Legal System, and Illegal Behavior - - - Illegal Behavior and the Enforcement of Law

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