Paving the Path to Accurately Predicting Legal Outcomes: A Comment on Professor Chien’s Predicting Patent Litigation

David L. Schwartz, IIT Chicago-Kent College of Law
Jay P. Kesan, University of Illinois College of Law
Ted M. Sichelman, University of San Diego School of Law

Abstract

Professor Colleen Chien recently developed an innovative and important model that relies on a patent's "after-acquired" characteristics to predict the chances that the patent will be involved in litigation. This comment critiques Professor Chien's model by identifying certain weaknesses, including that its dataset is limited to 1990 patents and its sample size may be too small to be sufficiently representative, as well as a number of endogeneity concerns. Additionally, we seek a more precise definition of data regarding the patent owner, further categorization ofreexamination data, and research into the timing of transfer. Finally, we question her policy recommendations given these weaknesses and propose areas of further inquiry.