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Predicting the 'Unpredictable': An Empirical Analysis of U.S. Patent Infringement Awards

30 Pages Posted: 21 Oct 2012  

Michael J. Mazzeo

Northwestern University - Kellogg School of Management

Jonathan H. Ashtor

Paul, Weiss, Rifkind, Wharton & Garrison LLP; George Mason University School of Law

Samantha Zyontz

Massachusetts Institute of Technology (MIT) - Sloan School of Management

Date Written: October 20, 2012

Abstract

Patent infringement awards are commonly thought to be unpredictable, which raises concerns that patents can lead to unjust enrichment and impede the progress of innovation. We investigate the predictability of patent damages by conducting a large-scale econometric analysis of award values. We begin by analyzing the outcomes of 340 cases decided in US federal courts between 1995 and 2008 in which infringement was found and damages were awarded. Our data include the amount awarded, along with information about the litigants, case specifics and economic value of the patents-at-issue. Using these data, we construct an econometric model that explains over 75% of the variation in awards. We further conduct in-depth analysis of the key factors affecting award value, via targeted regressions involving selected variables. We find a high degree of significance between award value and ex ante-identifiable factors collectively, and we also identify significant relationships with accepted indicators of patent value. Our findings demonstrate that infringement awards are systematically predictable and, moreover, highlight the critical elements that can be expected to result in larger or smaller awards.

Keywords: Patent, Reform, Empirical, Data, Predict

Suggested Citation

Mazzeo, Michael J. and Ashtor, Jonathan H. and Zyontz, Samantha, Predicting the 'Unpredictable': An Empirical Analysis of U.S. Patent Infringement Awards (October 20, 2012). Available at SSRN: https://ssrn.com/abstract=2164787 or http://dx.doi.org/10.2139/ssrn.2164787

Michael J. Mazzeo (Contact Author)

Northwestern University - Kellogg School of Management ( email )

2001 Sheridan Road
Evanston, IL 60208
United States
847-467-7551 (Phone)

Jonathan H. Ashtor

Paul, Weiss, Rifkind, Wharton & Garrison LLP ( email )

New York, NY 10019
United States
212-373-3823 (Phone)

George Mason University School of Law ( email )

4400 University Drive
Fairfax, VA 22030
United States

Samantha Zyontz

Massachusetts Institute of Technology (MIT) - Sloan School of Management ( email )

100 Main Street
E62-416
Cambridge, MA 02142
United States

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