Incentivizing Lawyers as Teams
32 Pages Posted: 29 Aug 2018 Last revised: 14 Jan 2020
Date Written: January 10, 2020
Federal multidistrict litigation now consumes over half of the federal civil docket. In these cases, judges assemble teams of law firms to represent the plaintiff side and then must decide how to pay the teams. The existing scholarship on how judges can best incentivize lawyers is not helpful because it almost always assumes single-principal-single-agent environments that are inapplicable to the single-principal-multiple-agent environment in multidistrict litigation. In this Article, we correct this deficiency by drawing upon the single-principal-multiple-agent models popular in the economics and industrial organization literatures. Even these models are lacking, however, because they rarely offer practical ways to assess the relative contribution each agent made to the team’s output. We improve upon this situation by devising two methods whereby judges can ask team members to report on each other’s relative contributions but not their own contribution. Our methods, drawn from least-squares optimization and Bayesian models, prevent team members from manipulating their own allocations and colluding on the allocations of others, and, we hope, offer judges practical ways to better incentivize lawyers in this important area.
Keywords: Attorney Fees, Fair Division, Lodestar, Complex Litigation, Mass Torts, Bayesian Methods, Optimization
JEL Classification: C11, C61
Suggested Citation: Suggested Citation