Patent Citations Reexamined

Abstract

Existing measures of innovation often rely on patent citations to indicate intellectual lineage and impact. We show that the data generating process for patent citations has changed substantially since citation-based measures were validated a decade ago. Today, far more citations are created per patent, and the mean technological similarity between citing and cited patents has fallen significantly. These changes suggest that the use of patent citations for scholarship needs to be re-validated. We develop a novel vector space model to examine the information content of patent citations, and show that methods for sub-setting and/or weighting informative citations can substantially improve the predictive power of patent citation measures. We make data for a basic correction available for future scholarship through the Patent Research Foundation.