Does University Licensing Facilitate or Restrict the Flow of Knowledge and Research Inputs Among Scientists?

As university involvement in technology transfer and entrepreneurship has increased, concerns over the patenting and licensing of scientific discoveries have grown. This paper examines the effect of licensing on the citation of academic publications associated with patents covering university scientific research. We analyze data on invention disclosures, patents, and licenses from the University of California, a leading US academic patenter and licensor, between 1997 and 2007. We also develop a novel “inventor– based” maximum–likelihood matching technique to automate and generalize Murray’s (2002) patent– paper “pairs” methodology. We use this methodology to identify the scientific publications associated with University of California patents and licenses. We find that, in general, licenses are associated with an increase in journal citations to related scientific publications. The timing of this effect supports earlier research that suggests that academic licenses may act as positive signals of research potential in the licensed technological area (Drivas et al. 2014). In contrast, we find the opposite effect of licensing on citations to related scientific publications when the underlying discovery is a research input (which we identify through the use of material transfer agreements (MTAs)). In these cases, the related scientific publications experience a significant decline in citations following the execution of the license. Our results suggest that, in general, licensing of academic patents does not limit scientific communication linked to patented academic research. Our findings on the effects of licenses on research inputs, however, raise the possibility that licensing may restrict the flow of inputs to further scientific research among researchers. We are grateful to Wendy Streitz, Ron Franck, and other employees of the U.C. Office of the President for access to the intellectual property data employed in this paper, and to Thompson Reuters for their data on scientific publications. We also thank Fiona Murray and Scott Stern for sharing their data. This work has greatly benefited from comments and suggestions by Janet Bercovitz, Paul David, Bronwyn Hall, Jennifer Kuan, Joanne Oxley, Rob Seamans, Brian Wright, Rosemarie Ziedonis, participants in seminars at the Copenhagen Business School, U.C. Berkeley, Santa Clara University, Stanford University, the 2011 NBER Economics of Intellectual Property Policy and Innovation Workshop, the 2011 Georgia Tech Roundtable for Engineering Entrepreneurship Research, and the 2012 Academy of Management annual meeting. The authors gratefully acknowledge financial support from the Institute for Business Innovation at the Haas School of Business, the National Science Foundation, the Industrial Partnerships Office at Lawrence Livermore National Laboratory, the Program in Law, Economics, and Technology at the University of Michigan Law School, the Rotman School of Management at the University of Toronto, and the Sloan Foundation. We also appreciate the support of the Stanford Institute of Economic Policy Research.