Daniel L. Chen

Law and economics is divided between the consequentialist view that optimal policy should be based on calculations of costs and benefits and a non-consequentialist view that policy should be determined deontologically: from duties we derive what is the correct law—what is right and just.

Are there deontological motivations, and if there are, how might we formally model them? What are the implications for economics methods and policy, and what puzzles can we explain with deontological motivations that we cannot with standard models?

To answer these questions, his research has curated 12 terabytes of archival and administrative data on judges and courts, developed a programming language (oTree) for studying normative commitments in experiments—now used in 23+ countries—and spearheaded randomized impact evaluations to improve justice with high-frequency administrative data in 17 countries.

His work has been published in the AER, Econometrica, JPE, QJE, PNAS, Science Advances, and Nature Human Behavior, and covered by the NYT, Washington Post, Wall Street Journal, and NPR.