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An Empirical Test of the Comparative and Contributory Negligence Rules in Accident Law

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  • Michelle J. White
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    Abstract

    Scholars in the field of law and economics have developed an extensive theoretical literature on the effects of liability rules in accident law, but have done little testing of their theoretical models. In this article, I develop an empirically testable model of the incentives for injurers and victims to avoid accidents under both the older contributory negligence rule and the newer rule of comparative negligence. The model takes account of the fact that in the automobile accident context, drivers do not know in advance with whom they will be involved in an accident, and whether they will be the injurer or the victim, or both. It also allows for uncertainty in legal decision making. The model is tested using a data set of rear-end automobile accidents litigated in court. The results suggest, first, that incentives to take care to avoid accidents are stronger under the contributory negligence rule than under the newer rule of comparative negligence and, second, the incentives set up by the comparative negligence rule for drivers to avoid accidents are weaker than is economically efficient.

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    Bibliographic Info

    Article provided by The RAND Corporation in its journal RAND Journal of Economics.

    Volume (Year): 20 (1989)
    Issue (Month): 3 (Autumn)
    Pages: 308-330

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    Handle: RePEc:rje:randje:v:20:y:1989:i:autumn:p:308-330

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    Cited by:
    1. Alma Cohen & Rajeev Dehejia, 2003. "The Effect of Automobile Insurance and Accident Liability Laws in Traffic Fatalities," NBER Working Papers 9602, National Bureau of Economic Research, Inc.
    2. Allan M. Feldman & Jeonghyun Kim, 2003. "Victim or Injurer:Negligence-Based Liability Rules Under Role-Type Uncertainty, With An Extension to Collisions Of Different-Sized Vehicles," Working Papers 2003-17, Brown University, Department of Economics.
    3. Eric Helland & Jonathan Klick & Alexander Tabarrok, 2005. "Data Watch: Tort-uring the Data," Journal of Economic Perspectives, American Economic Association, vol. 19(2), pages 207-220, Spring.
    4. Hoffmann, Sandra & Schwartz, Warren & Dharmapala, Dhammika, 2001. "A Neglected Interdependency in Liability Theory," Discussion Papers dp-01-13, Resources For the Future.

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