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 unpredictability of patent damages by conducting a large-scale econometric analysis of award values. We...

This report updates and expands the paper, patent, and company datasets collected for Zyontz and Pomeroy-Carter (2021) through 2022. Particular attention is paid to worldwide CRISPR activity in plant applications. The results from the databases updated for this report reveal a number of...

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...

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...

Patent litigation is widely regarded as one of the most complex types of civil litigation, with costs often totaling millions of dollars and typical case durations stretching for years. Also, the burdens of patent case complexity land on both sides of the technology divide, as large producers...

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...