Faculty Journal Articles and Book Chapters
ORCID (Links to author’s additional scholarship at ORCID.org)
Hillel J. Bavli: https://orcid.org/0000-0003-4888-2842
Recent papers have highlighted the use of claim aggregation as a tool for reducing the unpredictability of legal outcomes. Specifically, it has been argued that sampling methods can be used in the class action context, and comparable-case guidance – information regarding awards in comparable cases as guidance for determining damage awards – can be used in the individual-claim context, to reduce variability and improve the accuracy of awards. In this paper, we examine a third form of claim aggregation based on a statistical method called “shrinkage estimation,” which is used to aggregate information and thereby improve estimation. We examine the conditions under which “shrinkage” can improve the accuracy of damage awards, and we apply it to gain a deeper understanding of the benefits and limitations of claim aggregation in the sampling and comparable-case guidance contexts with respect to accuracy.
Review of Law & Economics
accuracy, judgment variability, class action, claim aggregation, shrinkage estimation, sampling, pain and suffering, punitive damages, comparable-case guidance, jury awards, damages
Hillel J. Bavli and Yang Chen, Shrinkage Estimation in the Adjudication of Civil Damage Claims, 13 Rev. L. & Econ., 1 (2017)