IDEAS home Printed from https://ideas.repec.org/h/spr/nrmchp/978-3-030-77760-9_14.html
   My bibliography  Save this book chapter

Econometrics in Litigation: Challenges at Class Certification

In: Modern Agricultural and Resource Economics and Policy

Author

Listed:
  • Gareth Macartney

    (OnPoint Analytics)

Abstract

This chapter describes the increasing challenges faced by econometrics in antitrust class actions. The main hurdle for plaintiffs in any class action in the United States is to get the court to approve that the case be tried as a class in the first place. This phase of the case is colloquially referred to as “class cert.” Much of the battle is fought by economic experts, analyzing whether common evidence can be used to prove that “all or virtually all” class members were injured by the alleged antitrust violation (known as “common impact”) and whether common evidence can be used to estimate aggregate class-wide damages. In the last decade or so, through several landmark rulings, the legal standard for plaintiffs to prevail at class cert has increased substantially. We discuss the repercussions of these rising standards, including a decrease in class actions in favor of direct actions, the new burden placed on regression models, and the erroneous methods increasingly used by defendants’ experts to impugn plaintiffs’ experts’ models. Traditional econometric models can struggle to meet this burden, as the emphasis shifts from measuring average effects on the class, in the direction of measuring individual effects specific to each class member, but using a common econometric model to do so. Specifically, whereas in the past econometric models were tasked with estimating an average price increase to prove aggregate class-wide damages, they are increasingly also being asked to predict what prices each individual class member would have paid absent the antitrust violation, in order to prove common impact. We describe the challenges econometric models have in achieving this. We explore hypothesis testing of common impact and how individual prediction might be improved, including through machine learning techniques. We also describe the challenges for such techniques to be accepted by courts.

Suggested Citation

  • Gareth Macartney, 2022. "Econometrics in Litigation: Challenges at Class Certification," Natural Resource Management and Policy, in: Harry de Gorter & Jill McCluskey & Johan Swinnen & David Zilberman (ed.), Modern Agricultural and Resource Economics and Policy, pages 311-346, Springer.
  • Handle: RePEc:spr:nrmchp:978-3-030-77760-9_14
    DOI: 10.1007/978-3-030-77760-9_14
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:nrmchp:978-3-030-77760-9_14. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.