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Dynamic Law Enforcement with Learning

Author

Listed:
  • Nuno Garoupa

Abstract

This article modifies a standard model of law enforcement to allow for learning by doing. 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 of future apprehension at a lower marginal cost. We focus on the impact of enforcement learning on optimal compliance rules. In particular, we show that the optimal fine could be less than maximal and the optimal probability of detection could be higher than otherwise. It is also suggested that the optimal imprisonment sentence could be higher than otherwise. Copyright 2004, Oxford University Press.

Suggested Citation

  • 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.
    • Handle: RePEc:oup:jleorg:v:20:y:2004:i:1:p:192-206
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    Cited by:

    1. Thomas J. Miceli, 2012. "Escalating Interest in Escalating Penalties," Working papers 2012-08, University of Connecticut, Department of Economics.
    2. João Ricardo Faria & Gonçalo Monteiro, "undated". "The Tenure Game: Building Up Academic Habits," Discussion Papers 05/32, Department of Economics, University of York.
    3. Miles Stan & Pyne Derek, 2017. "The Economics of Scams," Review of Law & Economics, De Gruyter, vol. 13(1), pages 1-18, March.
    4. Lisa R. Anderson & Gregory DeAngelo & Winand Emons & Beth Freeborn & Hannes Lang, 2017. "Penalty Structures And Deterrence In A Two-Stage Model: Experimental Evidence," Economic Inquiry, Western Economic Association International, vol. 55(4), pages 1833-1867, October.
    5. Mungan, Murat C., 2010. "Repeat offenders: If they learn, we punish them more severely," International Review of Law and Economics, Elsevier, vol. 30(2), pages 173-177, June.
    6. Stan Miles & Derek Pyne, 2015. "Deterring repeat offenders with escalating penalty schedules: a Bayesian approach," Economics of Governance, Springer, vol. 16(3), pages 229-250, August.

    More about this item

    JEL classification:

    • K42 - Law and Economics - - Legal Procedure, the Legal System, and Illegal Behavior - - - Illegal Behavior and the Enforcement of Law
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

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