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Crime and punishment: the economic burden of impunity

Author

Listed:
  • Mirta B. Gordon

    (AMA - Analyse de données, Modélisation et Apprentissage automatique [Grenoble] - LIG - Laboratoire d'Informatique de Grenoble - UPMF - Université Pierre Mendès France - Grenoble 2 - UJF - Université Joseph Fourier - Grenoble 1 - Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology - INPG - Institut National Polytechnique de Grenoble - CNRS - Centre National de la Recherche Scientifique)

  • J. R. Iglesias

    (Laboratory of Neuroheuristics - UNIL - Université de Lausanne = University of Lausanne)

  • Viktoriya Semeshenko

    (Departamento de Economía [Buenos Aires] - Facultad de Ciencias Económicas [Buenos Aires] - UBA - Universidad de Buenos Aires [Buenos Aires])

  • J. -P. Nadal

    (CAMS - Centre d'Analyse et de Mathématique sociales - EHESS - École des hautes études en sciences sociales - CNRS - Centre National de la Recherche Scientifique)

Abstract

Crime is an economically important activity, sometimes called the industry of crime. It may represent a mechanism of wealth distribution but also a social and economic charge because of the cost of the law enforcement system. Sometimes it may be less costly for the society to allow for some level of criminality. A drawback of such policy may lead to a high increase of criminal activity that may become hard to reduce. We investigate the level of law enforcement required to keep crime within acceptable limits and show that a sharp phase transition is observed as a function of the probability of punishment. We also analyze the growth of the economy, the inequality in the wealth distribution (the Gini coefficient) and other relevant quantities under different scenarios of criminal activity and probability of apprehension.

Suggested Citation

  • Mirta B. Gordon & J. R. Iglesias & Viktoriya Semeshenko & J. -P. Nadal, 2009. "Crime and punishment: the economic burden of impunity," Post-Print hal-00404403, HAL.
    • Handle: RePEc:hal:journl:hal-00404403
    DOI: 10.1140/epjb/e2009-00066-x
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    Cited by:

    1. Alves, Luiz G.A. & Ribeiro, Haroldo V. & Mendes, Renio S., 2013. "Scaling laws in the dynamics of crime growth rate," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(11), pages 2672-2679.
    2. Luiz G A Alves & Haroldo V Ribeiro & Ervin K Lenzi & Renio S Mendes, 2013. "Distance to the Scaling Law: A Useful Approach for Unveiling Relationships between Crime and Urban Metrics," PLOS ONE, Public Library of Science, vol. 8(8), pages 1-8, August.
    3. Alves, Luiz G.A. & Ribeiro, Haroldo V. & Rodrigues, Francisco A., 2018. "Crime prediction through urban metrics and statistical learning," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 435-443.
    4. Raimundo, Silvia Martorano & Yang, Hyun Mo & Rubio, Felipe Alves & Greenhalgh, David & Massad, Eduardo, 2023. "Modeling criminal careers of different levels of offence," Applied Mathematics and Computation, Elsevier, vol. 453(C).
    5. Abbas, Syed & Tripathi, Jai Prakash & Neha, A.A., 2017. "Dynamical analysis of a model of social behavior: Criminal vs non-criminal population," Chaos, Solitons & Fractals, Elsevier, vol. 98(C), pages 121-129.
    6. Gordon, Mirta B. & Laguna, M.F. & Gonçalves, S. & Iglesias, J.R., 2017. "Adoption of innovations with contrarian agents and repentance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 486(C), pages 192-205.
    7. Iglesias, J.R. & Semeshenko, V. & Schneider, E.M. & Gordon, M.B., 2012. "Crime and punishment: Does it pay to punish?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(15), pages 3942-3950.

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