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The Response to Fines and Probability of Detection in a Series of Experiments

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  • Avner Bar-Ilan
  • Bruce Sacerdote

Abstract

We use traffic data from a series of experiments in the United States and Israel to examine how illegal behavior is deterred by various penalty schemes and whether deterrence varies with age, income, driving record and criminal record. We find that red light running decreases sharply in response to an increase in the fine or an increase in the probability of being caught. The elasticity of violations with respect to the fine is larger for younger drivers and drivers with older cars. Drivers convicted of violent offenses or property offenses run more red lights on average but have the same elasticity as drivers without a criminal record. Within Israel, members of ethnic minority groups have the smallest elasticity with respect to a fine increase.

Suggested Citation

  • 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.
    • Handle: RePEc:nbr:nberwo:8638
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    Cited by:

    1. Daniel Mejía & Pascual Restrepo & Sandra V. Rozo, 2017. "On the Effects of Enforcement on Illegal Markets: Evidence from a Quasi-Experiment in Colombia," The World Bank Economic Review, World Bank, vol. 31(2), pages 570-594.
    2. Rafael Di Tella & Ernesto Schargrodsky, 2004. "Do Police Reduce Crime? Estimates Using the Allocation of Police Forces After a Terrorist Attack," American Economic Review, American Economic Association, vol. 94(1), pages 115-133, March.
    3. DeAngelo, Gregory & Gee, Laura Katherine, 2018. "Peers or Police? Detection and Sanctions in the Provision of Public Goods," IZA Discussion Papers 11540, Institute of Labor Economics (IZA).
    4. Ali al-Nowaihi & Sanjit Dhami, 2010. "Probability Weighting Functions," Discussion Papers in Economics 10/10, Division of Economics, School of Business, University of Leicester.
    5. Dean Yang, 2008. "Can Enforcement Backfire? Crime Displacement in the Context of Customs Reform in the Philippines," The Review of Economics and Statistics, MIT Press, vol. 90(1), pages 1-14, February.
    6. Sanjit Dhami & Ali al-Nowaihi, 2010. "The Behavioral Economics of Crime and Punishment," Discussion Papers in Economics 10/14, Division of Economics, School of Business, University of Leicester, revised Jul 2010.
    7. Hsiao-Chi Chen & Shi-Miin Liu, 2007. "Dynamic Incentive Contracts in Multiple Penalty Systems with No-commitment to Tenure-track Auditing," Journal of Economics, Springer, vol. 90(3), pages 255-294, April.
    8. Ali al-Nowaihi & Sanjit Dhami, 2010. "Composite Prospect Theory: A proposal to combine ‘prospect theory’ and ‘cumulative prospect theory’," Discussion Papers in Economics 10/11, Division of Economics, School of Business, University of Leicester.
    9. Jingkang Gao & Jinhua Zhao, 2017. "Normative and image motivations for transportation policy compliance," Urban Studies, Urban Studies Journal Limited, vol. 54(14), pages 3318-3336, November.
    10. Gider, Jasmin, 2014. "Do SEC Detections Deter Insider Trading? Evidence from Earnings Announcements," VfS Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100343, Verein für Socialpolitik / German Economic Association.
    11. 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.
    12. Nicola Persico, 2002. "Racial Profiling, Fairness, and Effectiveness of Policing," American Economic Review, American Economic Association, vol. 92(5), pages 1472-1497, December.

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    JEL classification:

    • J0 - Labor and Demographic Economics - - General
    • K0 - Law and Economics - - General

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