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Dynamic optimal law enforcement with learning

Author

Listed:
  • Mohamed Jellal
  • Nuno Garoupa

Abstract

We incorporate the process of enforcement learning by assuming that the agency's current marginal cost is a decreasing function of its past experience of detecting and convicting. The agency accumulates data and information (on criminals, on opportunities of crime) enhancing the ability to apprehend in the future at a lower marginal cost. We focus on the impact of enforcement learning on optimal stationary compliance rules. In particular, we show that the optimal stationary fine could be less-than-maximal and the optimal stationary probability of detection could be higher-than-otherwise.

Suggested Citation

  • Mohamed Jellal & Nuno Garoupa, 1999. "Dynamic optimal law enforcement with learning," Economics Working Papers 402, Department of Economics and Business, Universitat Pompeu Fabra.
    • Handle: RePEc:upf:upfgen:402
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    References listed on IDEAS

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    7. Polinsky, A. Mitchell & Shavell, Steven, 1998. "On offense history and the theory of deterrence," International Review of Law and Economics, Elsevier, vol. 18(3), pages 305-324, September.
    8. Davis, Michael L, 1988. "Time and Punishment: An Intertemporal Model of Crime," Journal of Political Economy, University of Chicago Press, vol. 96(2), pages 383-390, April.
    9. Ben-Shahar, Omri, 1997. "Playing without a rulebook: Optimal enforcement when individuals learn the penalty only by committing the crime," International Review of Law and Economics, Elsevier, vol. 17(3), pages 409-421, September.
    10. Nuno Garoupa, 1997. "The Theory of Optimal Law Enforcement," Journal of Economic Surveys, Wiley Blackwell, vol. 11(3), pages 267-295, September.
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    12. repec:bla:jecsur:v:11:y:1997:i:3:p:267-95 is not listed on IDEAS
    13. Shavell, Steven, 1993. "The Optimal Structure of Law Enforcement," Journal of Law and Economics, University of Chicago Press, vol. 36(1), pages 255-287, April.
    14. repec:bla:econom:v:62:y:1995:i:245:p:65-87 is not listed on IDEAS
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    Cited by:

    1. Florian Baumann & Tim Friehe & Tobias Wenzel, 2023. "Imperfect Information About Consumer Rights: Implications for Efficiency and Distribution," American Law and Economics Review, American Law and Economics Association, vol. 25(1), pages 86-128.
    2. Nuno Garoupa, 2004. "Dynamic Law Enforcement with Learning," The Journal of Law, Economics, and Organization, Oxford University Press, vol. 20(1), pages 192-206, April.
    3. Eide, Erling & Rubin, Paul H. & Shepherd, Joanna M., 2006. "Economics of Crime," Foundations and Trends(R) in Microeconomics, now publishers, vol. 2(3), pages 205-279, December.
    4. Lars Hansen & Signe Krarup & Clifford Russell, 2006. "Enforcement and Information Strategies," Journal of Regulatory Economics, Springer, vol. 30(1), pages 45-61, July.
    5. Friehe, Tim & Miceli, Thomas J., 2015. "Focusing law enforcement when offenders can choose location," International Review of Law and Economics, Elsevier, vol. 42(C), pages 105-112.
    6. Buechel, Berno & Feess, Eberhard & Muehlheusser, Gerd, 2020. "Optimal law enforcement with sophisticated and naïve offenders," Journal of Economic Behavior & Organization, Elsevier, vol. 177(C), pages 836-857.
    7. D’Antoni, Massimo & Galbiati, Roberto, 2007. "A signaling theory of nonmonetary sanctions," International Review of Law and Economics, Elsevier, vol. 27(2), pages 204-218.
    8. João Ricardo Faria & Gonçalo Monteiro, "undated". "The Tenure Game: Building Up Academic Habits," Discussion Papers 05/32, Department of Economics, University of York.
    9. Laure Batz, 2020. "Financial impact of regulatory sanctions on listed companies," European Journal of Law and Economics, Springer, vol. 49(2), pages 301-337, April.

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    More about this item

    Keywords

    Fine; probability of detection and punishment; learning;
    All these keywords.

    JEL classification:

    • K4 - Law and Economics - - Legal Procedure, the Legal System, and Illegal Behavior

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