To Pool or Not to Pool: A Closer Look at the Use of Sub-Regressions in Antitrust Class Certification

Forthcoming, Journal of Competition Law & Economics.

Posted: 13 Mar 2017 Last revised: 25 Jul 2017

Ai Deng

Bates White, LLC; Johns Hopkins University

Date Written: July 22, 2017

Abstract

Did the anticompetitive conduct in question impact all or nearly all class members? This is a question central to a court’s class certification decision. To answer this question, a methodology — known as sub-regressions — is being increasingly employed, particularly by defendants’ expert witnesses. A key step of a sub-regression type analysis is to partition the data into various subgroups and then to examine data poolability. In this article, I focus on three areas of interest pertaining to sub-regressions. First, I review the related law and economics literature related to this methodology. I then analyze courts’ recent class certification decisions in cases where parties introduced sub-regression analysis. I then discuss several methodological challenges, many of which have not been previously acknowledged, and present potential ways to address these challenges. I emphasize that a disciplined and rigorous implementation is crucial for the reliability of sub-regressions.

Keywords: Class certification, Common impact, Data mining, Poolability

JEL Classification: K00, K21

Suggested Citation

Deng, Ai, To Pool or Not to Pool: A Closer Look at the Use of Sub-Regressions in Antitrust Class Certification (July 22, 2017). Forthcoming, Journal of Competition Law & Economics.. Available at SSRN: https://ssrn.com/abstract=2931455 or http://dx.doi.org/10.2139/ssrn.2931455

Ai Deng (Contact Author)

Bates White, LLC ( email )

2001 K Street NW, North Building
Suite 500
Washington, DC DC 20006
United States

Johns Hopkins University ( email )

1717 Massachusetts Ave NW
Washington, DC DC 20036
United States

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