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Repeat offenders: If they learn, we punish them more severely

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  • Mungan, Murat C.

Abstract

Many legal systems are designed to punish repeat offenders more severely than first time offenders. However, existing economic literature generally offers either mixed or qualified results regarding optimal punishment of repeat offenders. This paper analyzes optimal punishment schemes in a two period model, where the social planner announces possibly different sanctions for offenders based on their detection history. When offenders learn how to evade the detection mechanism employed by the government, escalating punishments can be optimal. The contributions of this paper can be listed as follows: First, it identifies and formalizes a source which may produce a marginal effect in the direction of punishing repeat offenders more severely, namely learning. Next, it identifies conditions under which the tendency in legal systems to punish repeat offenders more severely is justified. Overall, the findings suggest that traditional variables identified so far in the literature are not the only relevant ones in deciding how repeat offenders should be punished, and that learning dynamics should also be taken into account.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:irlaec:v:30:y:2010:i:2:p:173-177
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    References listed on IDEAS

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    1. 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.
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    Cited by:

    1. repec:mhr:jinste:urn:sici:0932-4569(201612)172:4_727:beocra_2.0.tx_2-v is not listed on IDEAS
    2. Baumann, Florian & Friehe, Tim, 2012. "Self-report to self-control? A note," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 41(5), pages 727-729.
    3. Thomas J. Miceli, 2012. "Escalating Interest in Escalating Penalties," Working papers 2012-08, University of Connecticut, Department of Economics.
    4. Saori Chiba & Kaiwen Leong, 2016. "Behavioral Economics of Crime Rates and Punishment Levels," Journal of Institutional and Theoretical Economics (JITE), Mohr Siebeck, Tübingen, vol. 172(4), pages 727-754, December.
    5. Mungan, Murat C., 2011. "Welfare enhancing regulation exemptions," International Review of Law and Economics, Elsevier, vol. 31(4), pages 249-255.
    6. Alfred Endres & Bianca Rundshagen, 2012. "Escalating penalties: a supergame approach," Economics of Governance, Springer, vol. 13(1), pages 29-49, March.
    7. Mungan, Murat C., 2014. "A behavioral justification for escalating punishment schemes," International Review of Law and Economics, Elsevier, vol. 37(C), pages 189-197.
    8. repec:eee:jeborg:v:137:y:2017:i:c:p:398-409 is not listed on IDEAS
    9. repec:bla:scotjp:v:64:y:2017:i:5:p:467-482 is not listed on IDEAS
    10. 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.
    11. repec:bla:ecinqu:v:55:y:2017:i:4:p:1833-1867 is not listed on IDEAS

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