Excessive or Unpredictable? An Empirical Analysis of Patent Infringement Awards

Abstract

Over the past several years, the US patent reform debate has considered the question of excessive infringement damages. More recently, claims that awards are unpredictable have gained prominence in policy discussions. This paper evaluates the charges of excessive and unpredictable awards 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. We find (1) no evidence of systematic excessiveness and (2) a high correlation between award value and ex ante-identifiable factors. First, we find that the largest eight awards are isolated occurrences that represent nearly half of the aggregate amount of damages over the target period. Second, we construct an econometric model that explains over 75% of the variation in awards. These data and findings refute claims that infringement awards are systematically excessive or unpredictable and provide empirical support for the approach recently taken in the America Invents Act. More generally, they counsel for increased focus on econometric analysis as the tool for identification of problem areas and prescription of policy solutions in legal systems.

Keywords: Patent, Reform, Empirical, Data