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Punishment Deters Crime Because Humans Are Bounded in Their Strategic Decision-Making

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Is it rational to reduce criminal activities if punishments are increased? While intuition might suggest so, game theory concludes differently. From the game theoretical perspective, inspectors anticipate the effect of increased punishments on criminal behavior and reduce their inspection activities accordingly. This implies that higher punishments reduce inspections and do not affect crime rates. We present two laboratory experiments, which challenge this perspective by demonstrating that both, criminals and inspectors, are affected by punishment levels. Thereupon, we investigate with agent-based simulations, whether models of bounded rationality can explain our empirical data. We differentiate between two kinds of bounded rationality; the first considers bounded learning from social interaction, the second bounded decision-making. Our results suggest that humans show both kinds of bounded rationality in the strategic situation of crime, control and punishment. We conclude that it is not the rationality but the bounded rationality in humans that makes punishment effective.

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  • Heiko Rauhut & Marcel Junker, 2009. "Punishment Deters Crime Because Humans Are Bounded in Their Strategic Decision-Making," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 12(3), pages 1-1.
  • Handle: RePEc:jas:jasssj:2008-82-2
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    File URL: http://jasss.soc.surrey.ac.uk/12/3/1/1.pdf
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    1. Levitt, Steven D, 1997. "Using Electoral Cycles in Police Hiring to Estimate the Effect of Police on Crime," American Economic Review, American Economic Association, vol. 87(3), pages 270-290, June.
    2. Fudenberg Drew & Kreps David M., 1993. "Learning Mixed Equilibria," Games and Economic Behavior, Elsevier, vol. 5(3), pages 320-367, July.
    3. Ernst Fehr & Klaus M. Schmidt, 1999. "A Theory of Fairness, Competition, and Cooperation," The Quarterly Journal of Economics, Oxford University Press, vol. 114(3), pages 817-868.
    4. Falk, Armin & Fischbacher, Urs, 2002. ""Crime" in the lab-detecting social interaction," European Economic Review, Elsevier, vol. 46(4-5), pages 859-869, May.
    5. Gary S. Becker, 1974. "Crime and Punishment: An Economic Approach," NBER Chapters,in: Essays in the Economics of Crime and Punishment, pages 1-54 National Bureau of Economic Research, Inc.
    6. Axel Ockenfels & Gary E. Bolton, 2000. "ERC: A Theory of Equity, Reciprocity, and Competition," American Economic Review, American Economic Association, vol. 90(1), pages 166-193, March.
    7. repec:cup:apsrev:v:83:y:1989:i:01:p:77-91_08 is not listed on IDEAS
    8. Rabin, Matthew, 1993. "Incorporating Fairness into Game Theory and Economics," American Economic Review, American Economic Association, vol. 83(5), pages 1281-1302, December.
    9. Mark Walker & John Wooders, 2001. "Minimax Play at Wimbledon," American Economic Review, American Economic Association, vol. 91(5), pages 1521-1538, December.
    10. P.-A. Chiappori, 2002. "Testing Mixed-Strategy Equilibria When Players Are Heterogeneous: The Case of Penalty Kicks in Soccer," American Economic Review, American Economic Association, vol. 92(4), pages 1138-1151, September.
    11. Drew Fudenberg & David K. Levine, 1998. "The Theory of Learning in Games," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262061945, January.
    12. Cameron, Samuel, 1988. "The Economics of Crime Deterrence: A Survey of Theory and Evidence," Kyklos, Wiley Blackwell, vol. 41(2), pages 301-323.
    13. Urs Fischbacher, 2007. "z-Tree: Zurich toolbox for ready-made economic experiments," Experimental Economics, Springer;Economic Science Association, vol. 10(2), pages 171-178, June.
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    Cited by:

    1. Christoph Engel, 2016. "Experimental Criminal Law. A Survey of Contributions from Law, Economics and Criminology," Discussion Paper Series of the Max Planck Institute for Research on Collective Goods 2016_07, Max Planck Institute for Research on Collective Goods.
    2. Maria Fonoberova & Vladimir A. Fonoberov & Igor Mezic & Jadranka Mezic & P. Jeffrey Brantingham, 2012. "Nonlinear Dynamics of Crime and Violence in Urban Settings," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 15(1), pages 1-2.
    3. Flaminio Squazzoni, 2010. "The impact of agent-based models in the social sciences after 15 years of incursions," History of Economic Ideas, Fabrizio Serra Editore, Pisa - Roma, vol. 18(2), pages 197-234.
    4. Ammar Malik & Andrew Crooks & Hilton Root & Melanie Swartz, 2015. "Exploring Creativity and Urban Development with Agent-Based Modeling," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 18(2), pages 1-12.
    5. Christine Horne & Heiko Rauhut, 2013. "Using laboratory experiments to study law and crime," Quality & Quantity: International Journal of Methodology, Springer, vol. 47(3), pages 1639-1655, April.

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