LEARNING LIABILITY RULES

We conduct experiments regarding the equilibrium and convergence prope rties of three different liability rules: negligence with contributory negligence, comparative negligence, and no-fault. Our experimental re sults show that, in comparison to contributory negligence, comparative negligence promotes a faster and more reliable convergence to the eff icient equilibrium. Furthermore, as predicted by theory, the no-fault equilibrium yields suboptimal amounts of effort. Along the way we also test various hypotheses regarding learning and other adjustment dynam ics. Thus our article extends the traditional static notion of institu tional choice - liability rules with efficient equilibria are chosen - to a more dynamic perspective - rules that rapidly achieve efficient equilibria are chosen.