Forward citations are arguably the most widely used empirical metric for patents, including as indicators of patent information content, cumulative innovation, value, and knowledge flows. However, forward citations have major shortcomings. Citations require long time horizons to accrue, and...

We investigate the relationship between the exclusive rights of patents, their information disclosures, and the impact they have on the development of future technologies. We discover a significant positive relationship. Specifically, we find that the private rights and technological impact of...

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...

This study uses machine learning techniques to model patent claim clarity and analyze how clarity relates to important patent policy objectives. Specifically, machine learning models are trained on a dataset of over 600,000 U.S. patent applications that were (or were not) rejected for...