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Optimal Penalties for Repeat Offenders – The Role of Offence History

Author

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  • Endres Alfred

    (Department of Economics, University of Hagen, Universitätsstr. 11, 58084 Hagen, Germany University of Witten/Herdecke, 58448 Witten, Germany)

  • Rundshagen Bianca

    (Department of Economics, University of Hagen, Universitätsstr. 11, 58084 Hagen, Germany)

Abstract

Within an infinite and a corresponding finite game framework we analyse intertemporal punishment for repeat offenders. The legal authority is assumed to maximize social welfare by minimizing the sum of harm from crimes and cost of punishment. We show that the time horizon considerably affects the structure of the optimal penalty scheme. In the finite game framework decreasing as well as escalating penalty schemes may be optimal. For the more appropriate infinite game framework we show three main results: First, any penalty scheme can be replaced by a (weakly) escalating penalty scheme that leads to the same criminal activity and the same social penalization cost. Second, the optimal penalty scheme is of the escalating type. Third, the socially optimal level of crime under escalating penalties may be higher than the level which would be optimal under uniform penalties.

Suggested Citation

  • Endres Alfred & Rundshagen Bianca, 2016. "Optimal Penalties for Repeat Offenders – The Role of Offence History," The B.E. Journal of Theoretical Economics, De Gruyter, vol. 16(2), pages 545-578, June.
  • Handle: RePEc:bpj:bejtec:v:16:y:2016:i:2:p:545-578:n:3
    DOI: 10.1515/bejte-2014-0098
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    References listed on IDEAS

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    1. Matthew J. Baker & Niklas J. Westelius, 2013. "Crime, expectations, and the deterrence hypothesis," Chapters, in: Thomas J. Miceli & Matthew J. Baker (ed.), Research Handbook on Economic Models of Law, chapter 12, pages 235-280, Edward Elgar Publishing.
    2. Thomas J. Miceli & Matthew J. Baker, 2013. "Introduction to: Research Handbook on Economic Models of Law," Working papers 2013-07, University of Connecticut, Department of Economics.
    3. Thomas J. Miceli & Matthew J. Baker (ed.), 2013. "Research Handbook on Economic Models of Law," Books, Edward Elgar Publishing, number 14720.
    4. Alessandro Barbarino & Giovanni Mastrobuoni, 2014. "The Incapacitation Effect of Incarceration: Evidence from Several Italian Collective Pardons," American Economic Journal: Economic Policy, American Economic Association, vol. 6(1), pages 1-37, February.
    5. Binmore, Ken, 2007. "Playing for Real: A Text on Game Theory," OUP Catalogue, Oxford University Press, number 9780195300574.
    6. Mailath, George J. & Samuelson, Larry, 2006. "Repeated Games and Reputations: Long-Run Relationships," OUP Catalogue, Oxford University Press, number 9780195300796.
    7. Evgenia Motchenkova, 2014. "Cost minimizing sequential punishment policies for repeat offenders," Applied Economics Letters, Taylor & Francis Journals, vol. 21(5), pages 360-365, March.
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    Cited by:

    1. Leshem, Shmuel & Tabbach, Avraham, 2023. "The option value of record-based sanctions," Games and Economic Behavior, Elsevier, vol. 137(C), pages 1-22.
    2. Wolfgang Eggert & Steffen Minter & Maximilian Stephan & Handirk Ungern-Sternberg, 2017. "Sanctions for repeat offenders: a question of wealth?," Scottish Journal of Political Economy, Scottish Economic Society, vol. 64(5), pages 467-482, November.

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    More about this item

    Keywords

    crime prevention; repeat offenders; infinite time horizon;
    All these keywords.

    JEL classification:

    • K14 - Law and Economics - - Basic Areas of Law - - - Criminal Law
    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games

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