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Hang ’em with probability zero: Why does it not work?

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  • Sanjit Dhami
  • Ali al-Nowaihi

Abstract

A celebrated result in the economics of crime, which we call the Becker proposition (BP), states that it is optimal to impose the severest possible punishment (to maintain effective deterrence) at the lowest possible probability (to economize on enforcement costs). Several other applications, some unrelated to the economics of crime, arise when an economic agent faces punishments/ rewards with very low probabilities. For instance, insurance against low probability events, principal-agent contracts that impose punitive fines, seat belt usage and the usage of mobile phones among drivers etc. However, the BP, and the other applications mentioned above, are at variance with the evidence. The BP has largely been considered within an expected utility framework (EU). We re-examine the BP under rank dependent expected utility (RDU) and prospect theory (PT). We find that the BP always holds under RDU. However, under plausible scenarios within PT it does not hold, in line with the evidence.

Suggested Citation

  • Sanjit Dhami & Ali al-Nowaihi, 2006. "Hang ’em with probability zero: Why does it not work?," Discussion Papers in Economics 06/14, Division of Economics, School of Business, University of Leicester.
    • Handle: RePEc:lec:leecon:06/14
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    File URL: https://www.le.ac.uk/economics/research/RePEc/lec/leecon/dp06-14.pdf
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    References listed on IDEAS

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    1. David Friedman, 1999. "Why Not Hang Them All: The Virtues of Inefficient Punishment," Journal of Political Economy, University of Chicago Press, vol. 107(S6), pages 259-269, December.
    2. 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.
    3. Shlomo Benartzi & Richard H. Thaler, 1995. "Myopic Loss Aversion and the Equity Premium Puzzle," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 110(1), pages 73-92.
    4. Ali al-Nowaihi & Sanjit Dhami, 2005. "Insurance and Probability Weighting Functions," Discussion Papers in Economics 05/19, Division of Economics, School of Business, University of Leicester, revised Sep 2006.
    5. 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.
    6. Avner Bar-Ilan & Bruce Sacerdote, 2001. "The Response to Fines and Probability of Detection in a Series of Experiments," NBER Working Papers 8638, National Bureau of Economic Research, Inc.
    7. Bar-Ilan, Avner & Sacerdote, Bruce, 2004. "The Response of Criminals and Noncriminals to Fines," Journal of Law and Economics, University of Chicago Press, vol. 47(1), pages 1-17, April.
    8. Kolm, Serge-Christophe, 1973. "A note on optimum tax evasion," Journal of Public Economics, Elsevier, vol. 2(3), pages 265-270, July.
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    Cited by:

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    3. Neumärker, Bernhard & Pech, Gerald, 2010. "Penalties in the theory of equilibrium tax evasion: Solving King John's problem," The Constitutional Economics Network Working Papers 01-2010, University of Freiburg, Department of Economic Policy and Constitutional Economic Theory.
    4. Supanika Leurcharusmee, 2012. "Is penalty for academic cheating an incredible threat?," The Empirical Econometrics and Quantitative Economics Letters, Faculty of Economics, Chiang Mai University, vol. 1(2), pages 81-96, June.

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    More about this item

    Keywords

    Behavioral economics; Illegal activity; Expected utility theory; Rank dependent expected utility; Prospect theory; Prelec and higher order Prelec probability weighting functions;
    All these keywords.

    JEL classification:

    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • K42 - Law and Economics - - Legal Procedure, the Legal System, and Illegal Behavior - - - Illegal Behavior and the Enforcement of Law

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