Suchergebnisse

AbstractIn this paper, I use a real options approach to investigate patent litigation when enforcement is costly, winning is uncertain, and beliefs about validity are stochastic. I consider both finite horizon and infinite horizon models. The theoretical results demonstrate that patent value depends not only upon the underlying technology but also upon the degree of uncertainty over the property right. Additionally, imperfect enforceability creates an effective patent term that is less than the statutory term. Using simulation methods and patent data, I estimate the hazard rate of patent litigation. Contrary to previous studies, I find that the rate of forward citations is negatively associated with the litigation rate. The difference arises because (1) I use a dynamic model that exploits the information contained in the timing of litigation and citations, and (2) I control for truncation using a duration model. Using random effects models, I find that heterogeneity in patent litigation is embedded primarily in the heterogeneity in receiving patent citations. Because of this, the patent litigation decision can be modeled as a unilateral decision.

Abstract
Using a selection corrected probit, I estimate the probability that patents will be found valid and infringed at trial. I combine for the first time detailed adjudication data with detailed patent data. I find that the selection effects for validity adjudications and infringement adjudications differ systematically. Additionally, infringement estimates do not appear to suffer from a substantial selection bias. The results highlight the importance of correctly specifying the selection mechanism in policy analysis. In contrast with previous studies, I find that the win rate for patents that go to trial is biased towards 50%. The bias is much more substantial for validity decisions, where I find unconditional win rates of 75% for adjudicated patents and 85% for matched patents. Win rates conditional on adjudication are below 60%.