Justin McCrary

Paul J. Evanson Professor of Law,
Columbia Law School;
Senior Advisor, Cornerstone Research

For more information, contact:

  • Celeste C. Saravia
  • Samid Hussain
  • Rainer Schwabe
  • Bryan M. Ricchetti

or any member of our senior staff.


Justin McCrary is an expert on statistical methods and economic modeling at the intersection of law and economics. Professor McCrary has testified on issues related to class certification, antitrust, labor, and statistics. His experience covers a range of industries and markets, including healthcare, life sciences, labor, telecommunications, high tech, and retail.

Class certification

Professor McCrary provided testimony in two seminal no-poach litigation matters involving the McDonald’s and Jimmy John’s franchises. In both matters, he analyzed the potential procompetitive benefits of the challenged clauses and opined on issues of class certification. Class certification was denied in both cases, with both U.S. district court judges relying on Professor McCrary’s analyses in their opinions.

Professor McCrary has testified on class certification issues in a high-profile gender discrimination case focused on pay and promotion outcomes at a large U.S. retailer. He has also filed reports on class certification issues in false advertising, product liability, and breach of contract matters.


Professor McCrary has extensive experience as an expert in antitrust cases. In a significant matter in a high-tech industry, he addressed allegations of conspiracy to fix prices, as well as analyzed and rebutted an opposing expert’s damages model. He has analyzed damages resulting from alleged collusion among pharmacies in South America. In AT&T’s acquisition of T-Mobile, Professor McCrary served as a consulting expert for the U.S. Department of Justice.

Statistical methods and analysis

An authority on high-performance computing and statistical techniques, Professor McCrary has testified at deposition on sampling, probability theory, and statistical methods. His experience includes multiple mortgage-backed securities and insider trading matters. He has also examined the statistical evidence for alleged overbilling of Medicare by healthcare providers in both government audit and False Claim Act matters.

Research and teaching

Professor McCrary has published research on econometric methods for measuring damages in antitrust litigation. In addition, his scholarship covers a wide range of topics, including employment discrimination, high-frequency trading, financial market structure, and monetary policy. A prolific author and co-author, his work has appeared in leading journals, including the American Economic Review, the Journal of Econometrics, and the Review of Economics and Statistics. Professor McCrary is a faculty research associate at the National Bureau of Economic Research.

Prior to joining Columbia University, Professor McCrary taught at the School of Law at the University of California, Berkeley. He is the founding director of the UC Berkeley Social Sciences Data Laboratory, or “D-Lab,” which focuses on emerging big data techniques in social science research.


In Re Twitter Inc. v. Elon Musk et al.


United States et al. v. Sava Senior Care Inc. et al.

Press Release

WWL: Global Leader Competition—Economists 2022

Press Release

Cornerstone Research Staff and Affiliated Experts Submit Comments to the Joint FTC-DOJ Inquiry on Merger Enforcement

Press Release

Cornerstone Research Named among Top Global Antitrust Economic Consultancies in 2022


No-Poach Clauses in QSR Litigation

Press Release

Who’s Who Legal: Competition 2021—Economists


The Role of Artificial Intelligence and Machine Learning in Competition Proceedings: Key Takeaways

  • “Private Enforcement in the Financial Services: Risks & Opportunities of Financial Antitrust Litigation,” 4th Annual Antitrust in the Financial Sector: Hot Issues and Global Perspectives, Concurrences Review, 22 September 2020
  • “Expert Testimony of the Future: Machine Learning and How It Will Impact Litigation,” Litigation Section of the Bar Association of San Francisco, 12 July 2017
  • “Expert Testimony of the Future: Machine Learning,” American Bar Association Section of Antitrust Law Spring Meeting, 29 March 2017