Learning Liability Rules
We conduct experiments regarding the equilibrium and convergence properties of three different liability rules: negligence with contributory negligence, comparative negligence, and no-fault. Our experimental results show that, in comparison to contributory negligence, comparative negligence promotes a faster and more reliable convergence to the efficient equilibrium. Furthermore, as predicted by theory, the no-fault equilibrium yields suboptimal amounts of effort. Along the way we also test varioius hypotheses regarding learning and other adjustment dynamics. Thus our article extends the traditional static notion of institutional choice-liability rules with efficient equilibria are chosen-to a more dynamic perspective-rules that rapidly achieve efficient equilibria are chosen. Coauthors are Daniel Friedman, Stephanie Crevier, and Aaron Braskin. Copyright 1997 by the University of Chicago.
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