Research Handbook on Economic Models of Law
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Research Handbook on Economic Models of Law

Edited by Thomas J. Miceli and Matthew J. Baker

One of the great successes of the law and economics movement has been the use of economic models to explain the structure and function of broad areas of law. The original contributions to this volume epitomize that tradition, offering state-of-the-art research on the many facets of economic modeling in law.
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Chapter 6: Incentives for care, litigation, and tort reform under self-serving bias

Claudia M. Landeo, Maxim Nikitin and Sergei Izmalkov


In civil litigation, although most cases settle before trial, many do not settle early, and some do not settle at all. Delayed settlement or impasse causes high costs for the parties and for society. Babcock et al. (1995a, 1997), Babcock and Loewenstein (1997) and Loewenstein et al. (1993) propose an explanation for disputes that rests on a judgment error called ìself-serving bias.î Self-serving bias refers to the litigantís biased beliefs that the court decision will favor his case due to the interpretation of the facts of the dispute in his own favor. In information environments characterized by ambiguity, even when the parties are exposed to the exact same information, they might arrive at expectations of an adjudicated settlement that are biased in a self-serving manner. As a result, higher likelihood of disputes might be observed. Note that the litigation outcomes might influence potential injurersí level of care, i.e., their expenditures on accident prevention (Png, 1987; Landeo et al., 2006, 2007a, 2007b). Hence, the defendantís level of care, social welfare and the effects of tort reform might also be affected by self-serving bias. Despite the active experimental literature on self-serving bias and pretrial bargaining, and the robustness of these findings, there has been very little theoretical work on this topic. This chapter presents a strategic model of incentives for care and litigation under asymmetric information and self-serving bias, and studies the effects of caps on non-economic damages.

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