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More Tickets, Fewer Accidents: How Cash-Strapped Towns Make for Safer Roads

Author

Listed:
  • Michael D. Makowsky

    (Department of Economics, Towson University)

  • Thomas Stratmann

    (Department of Economics, George Mason University)

Abstract

Traffic accidents are one of the leading causes of injury and death in the U.S. The role of traffic law enforcement in the reduction of accidents has been studied by relatively few papers and with mixed results that may be due to a simultaneity problem. Traffic law enforcement may reduce accidents, but police are also likely to be stricter in accident- prone areas. We use municipal budgetary shortfalls as an instrumental variable to identify the effect of traffic citations on traffic safety and show that budgetary shortfalls lead to more frequent issuance of tickets to drivers. Using a panel of municipalities in Massachusetts, we show that increases in the number of tickets written reduce motor vehicle accidents and accident related injuries. The findings show that failure to control for endogeneity results in a significant underestimation of the positive impact of law enforcement on traffic safety.

Suggested Citation

  • Michael D. Makowsky & Thomas Stratmann, 2009. "More Tickets, Fewer Accidents: How Cash-Strapped Towns Make for Safer Roads," Working Papers 2009-02, Towson University, Department of Economics, revised Jun 2009.
    • Handle: RePEc:tow:wpaper:2009-02
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    File URL: http://webapps.towson.edu/cbe/economics/workingpapers/2009-02.pdf
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    JEL classification:

    • K32 - Law and Economics - - Other Substantive Areas of Law - - - Energy, Environmental, Health, and Safety Law
    • K42 - Law and Economics - - Legal Procedure, the Legal System, and Illegal Behavior - - - Illegal Behavior and the Enforcement of Law
    • H71 - Public Economics - - State and Local Government; Intergovernmental Relations - - - State and Local Taxation, Subsidies, and Revenue
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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