Patent Citations - An Analysis of Quality Differences and Citing Practices in Hybrid Corn

Abstract

Patents are the main source of data on innovation, but there are persistent concerns that patents may be a noisy and biased measure. An important challenge arises from unobservable variation in the size of the inventive step that is covered by a patent. The count of later patents that cite a patent as relevant prior art – so called forward citations – have become the standard measure to control for such variation. Citations may, however, also be a noisy and biased measure for the size of the inventive step. To address this issue, this paper examines field trial data for patented improvements in hybrid corn. Field trials report objective measures for improvements in hybrid corn, which we use to quantify the size of the inventive step. These data show a robust correlation between citations and improvements in yields, as the bottom line measure for improvements in hybrid corn. This correlation is robust to alternative measures for improvements in hybrid corn, and a broad range of other tests.We also investigate the process, by which patents generate citations. This analysis reveals that hybrids that serve as an input for genetically-related follow-on inventions are more likely to receive self-citations (by the same firm), which suggests that self-citations are a good predictor for follow-on invention.