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Dynamic optimal law enforcement with learning

Author

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  • 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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    File URL: https://econ-papers.upf.edu/papers/402.pdf
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    References listed on IDEAS

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    1. Sah, Raaj K, 1991. "Social Osmosis and Patterns of Crime," Journal of Political Economy, University of Chicago Press, vol. 99(6), pages 1272-1295, December.
    2. Leung, Siu Fai, 1995. "Dynamic Deterrence Theory," Economica, London School of Economics and Political Science, vol. 62(245), pages 65-87, February.
    3. Polinsky, A. Mitchell & Shavell, Steven, 1984. "The optimal use of fines and imprisonment," Journal of Public Economics, Elsevier, vol. 24(1), pages 89-99, June.
    4. Steven Shavell & A. Mitchell Polinsky, 2000. "The Economic Theory of Public Enforcement of Law," Journal of Economic Literature, American Economic Association, vol. 38(1), pages 45-76, March.
    5. Nash, John, 1991. "To make the punishment fit the crime: The theory and statistical estimation of a multi-period optimal deterrence model," International Review of Law and Economics, Elsevier, vol. 11(1), pages 101-110, May.
    6. 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.
    7. 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.
    8. 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.
    9. Kaplow, Louis, 1990. "A note on the optimal use of nonmonetary sanctions," Journal of Public Economics, Elsevier, vol. 42(2), pages 245-247, July.
    10. Garoupa, Nuno, 1997. " The Theory of Optimal Law Enforcement," Journal of Economic Surveys, Wiley Blackwell, vol. 11(3), pages 267-295, September.
    11. 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.
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    Citations

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    Cited by:

    1. Nuno Garoupa, 2004. "Dynamic Law Enforcement with Learning," Journal of Law, Economics, and Organization, Oxford University Press, vol. 20(1), pages 192-206, April.
    2. 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.
    3. Lars Hansen & Signe Krarup & Clifford Russell, 2006. "Enforcement and Information Strategies," Journal of Regulatory Economics, Springer, vol. 30(1), pages 45-61, July.
    4. 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.
    5. 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.
    6. João Ricardo Faria & Gonçalo Monteiro, "undated". "The Tenure Game: Building Up Academic Habits," Discussion Papers 05/32, Department of Economics, University of York.

    More about this item

    Keywords

    Fine; probability of detection and punishment; learning;

    JEL classification:

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

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