Stein on Probability and Incentives

Alex Stein of Cardozo School of Law has posted Probability and Incentives on SSRN.
Although the paper is not directly addressed to civil procedure topics, the issues surrounding the intersection of mathematical probability and motions to dismiss, summary judgment, and issues of proof remain ever important in the procedure context.

Abstract:     
This Article challenges the mathematical probability system that underlies law and economics and behavioral analysis and argues that many of the core insights of both approaches are irremediably flawed. The Article demonstrates that mathematical probability is only suitable for pure gambles and hence does not provide a useful epistemic tool for analyzing individual decision-making. As a result, mathematical probability cannot serve as a useful tool for lawmakers. Mathematical probability, the Article proposes, ought to be replaced with causative probability.

Originating from the writings of John Stuart Mill and Francis Bacon, causative probability differs from its mathematical cousin both conceptually and substantively. By contrast to the mathematical system that bases probability estimates on abstract averages, the causative system bases probability estimates upon case-specific evidential variety. Under the causative system, the probability that a person’s action will bring about a particular consequence - harm or gain - is determined by the number and scope of the consequence’s evidential confirmations in the individual case, and not by general averages that are usually irrelevant to the individual determination at hand. Causative probability allows a person to develop a better epistemic grasp of her individual case relative to what she could achieve under the mathematical system.

The causative-probability account has important implications for individual law-compliance, law-enforcement, and the design of legal policies. Causative determinations are intrinsic to all law-enforcement decisions: courts, prosecutors and other law-enforcers implement legal rules by responding to the information about what the relevant actor did, rather than by conducting a lottery. Legal rules are causative as well: they set up mechanisms that allow individuals to reap the benefits of their productive activities and force them to pay for the harms they cause. All this turns causative probability into a superior tool for understanding how law-enforcement mechanisms work, for improving those mechanisms, and for defining the rationality of individuals’ decisions.

RJE