Publication: Improving the Accuracy of Civil Damage Awards With Claim Aggregation
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2017-02-08
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Bavli, Hillel J. 2017. Improving the Accuracy of Civil Damage Awards With Claim Aggregation. Doctoral dissertation, Harvard University, Graduate School of Arts & Sciences.
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Abstract
A legal proceeding can be understood as an estimation problem, where the quality of the legal outcome depends on the information used to adjudicate it. This Ph.D. Dissertation is a compilation of five papers that examine a set of methods for improving the information used to adjudicate legal outcomes in the context of civil claims for damages. The papers analyze the possibility of improving civil damage awards by aggregating information across different claims—first, across claims in the class-action context, and second, across claims in altogether separate cases over time. The papers examine such methods statistically, analyzing whether, and under what conditions, aggregating information regarding damage awards or facts in separate claims would improve the quality of awards. And they examine such methods legally, assessing whether, and under what conditions, such methods are permissible under evidentiary, procedural, and constitutional frameworks. The final paper reports and interprets results from a factorial experiment designed to test certain conclusions relating to these methods. In summary, the papers demonstrate that the methods discussed are capable of improving damage awards substantially, and are generally permissible under the law.
Citations and links for the final published versions of each section of this dissertation:
Section I. Hillel J. Bavli, Aggregating for Accuracy: A Closer Look at Sampling and Accuracy in Class Action Litigation, 14 Law, Prob. & Risk 67 (2015). Link: https://doi.org/10.1093/lpr/mgu016.
Section II. Hillel J. Bavli, Sampling and Reliability in Class Action Litigation, 2016 Card. L. Rev. de novo 207 (2016). Link: http://cardozolawreview.com/sampling-and-reliability-in-class-action-litigation/.
Section III. Hillel J. Bavli, The Logic of Comparable-Case Guidance in the Determination of Awards for Pain and Suffering and Punitive Damages, 85 U. Cin. L. Rev. 1 (2017). Link: https://scholar.smu.edu/law_faculty/50/.
Section IV. Hillel J. Bavli & Yang Chen, Shrinkage Estimation in the Adjudication of Civil Damage Claims, 13 Rev. L. & Econ. 1 (2017). Link: https://doi.org/10.1515/rle-2015-0010.
Section V. Hillel J. Bavli & Reagan Mozer, The Effects of Comparable-Case Guidance on Awards for Pain and Suffering and Punitive Damages: Evidence from a Randomized Controlled Trial, 37 Yale L. & Pol’y Rev. 405 (2019). Link: https://ylpr.yale.edu/effects-comparable-case-guidance-awards-pain-and-suffering-and-punitive-damages-evidence-randomized.
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http://doi.org/10.1093/lpr/mgu016
http://cardozolawreview.com/sampling-and-reliability-in-class-action-litigation/
http://scholar.smu.edu/law_faculty/50/
http://doi.org/10.1515/rle-2015-0010
http://ylpr.yale.edu/effects-comparable-case-guidance-awards-pain-and-suffering-and-punitive-damages-evidence-randomized
http://cardozolawreview.com/sampling-and-reliability-in-class-action-litigation/
http://scholar.smu.edu/law_faculty/50/
http://doi.org/10.1515/rle-2015-0010
http://ylpr.yale.edu/effects-comparable-case-guidance-awards-pain-and-suffering-and-punitive-damages-evidence-randomized
Keywords
damage awards, aggregation
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