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Articles 1 - 3 of 3
Full-Text Articles in Law
Mutual Optimism And Risk Preferences In Litigation, Keith N. Hylton
Mutual Optimism And Risk Preferences In Litigation, Keith N. Hylton
Faculty Scholarship
Why do some legal disputes fail to settle? From a bird’s eye view, the literature offers two categories of reasons. One consists of arguments based on informational disparities. The other consists of psychological arguments. This paper explores the psychological theory. It presents a model of litigation driven by risk preferences and examines the model’s implications for trials and settlements. The model suggests a foundation in Prospect Theory for the Mutual Optimism model of litigation. The model’s implications for plaintiff win rates, settlement patterns, and informational asymmetry with respect to the degree of risk aversion are examined.
Information Costs And The Civil Justice System, Keith N. Hylton
Information Costs And The Civil Justice System, Keith N. Hylton
Faculty Scholarship
Litigation is costly because information is not free. Given that information is costly and perfect information prohibitively costly, courts will occasionally err. Finally, the fact that information is costly implies an unavoidable degree of informational asymmetry between disputants. This paper presents a model of the civil justice system that incorporates these features and probes its implications for compliance with the law, efficiency of law, accuracy in adjudication, trial outcome statistics, and the evolution of legal standards. The model’s claims are applied to and tested against the relevant empirical and legal literature. (JEL: D74, K10, K13, K41)
Trial Selection And Estimating Damages Equations, Keith N. Hylton
Trial Selection And Estimating Damages Equations, Keith N. Hylton
Faculty Scholarship
Many studies have employed regression analysis with data drawn from court opinions. For example, an analyst might use regression analysis to determine the factors that explain the size of damages awards or the factors that determine the probability that the plaintiff will prevail at trial or on appeal. However, the full potential of multiple regression analysis in legal research has not been realized, largely because of the sample selection problem. We propose a method for controlling for sample selection bias using data from court opinions.