Indiana University SPEA Edward J. Bloustein School of Planning and Public Policy University of Pennsylvania AIR American University

Panel Paper: Compulsory Licensing: Accelerating or Inhibiting Innovation? The Case of US Solid-State Lighting Research

Thursday, November 12, 2015 : 3:50 PM
Grenada (Hyatt Regency Miami)

*Names in bold indicate Presenter

Alexander M. Smith, Georgia Institute of Technology
To provide an evidence-basis for the design of programs for commercializing basic research, this proposal explores the impacts of compulsory licensing (CL) policies upon the inventiveness of firms who receive compulsory licenses to patents. CL policies require patent-owners to allow use of their patent-protected technology by others in exchange for a compensation level determined by a government authority. Government authorities have invoked CL policies in cases where widespread social benefits are obstructed by patent-owners. However, scholarly disposition on CL has been mixed. Some scholars have argued on principle that CL reduces incentives for researchers to pursue patents and could slow disclosure-based innovations. Conversely, other scholars have found evidence that CL increases the innovativeness of licensees, i.e. those who gain access to patents via CL.

The US Department of Energy (USDOE)’s solid-state lighting (SSL) research program serves as our case of interest. In 2005, as part of a new program for SSL research, the US DOE instituted a CL policy applied to patents from research funded by the US DOE’s new SSL program. The policy required owners of these patents to engage in non-exclusive, arbitrated licensing negotiations with a select group of firms. This group of firms was called the Next-Generation Lighting Alliance (NGLIA) and is composed of leading manufacturing and product development firms in the lighting industry. This proposal seeks to reveal the effects of the US DOE’s CL provision on the inventiveness of the members of NGLIA.

To reveal the impact of CL upon the NGLIA firms, I analyze multiple data sources via a panel-data fixed-effects difference-in-differences methodology. The NGLIA firms are identified via public documents on the US DOE’s website, as are the patents produced by the DOE SSL program; these are the patents subject to the DOE’s CL policy. I use patents within technology classes relevant to SSL and assigned to each firm in the NGLIA membership as the dependent variable. Data on these patents are gathered from the Derwent Innovations Index (DII). I gather data on key variables affecting patent propensity from MorningStar Advisors and Bloomberg business intelligence databases, as well as analyses of public web records on each NGLIA firm. I also select a group of comparison firms with similar characteristics as the NGLIA firms using the same datasets. In this way, variables affecting both total patent propensity and selection into the NGLIA group are controlled. The acquisition of data on the NGLIA firms and the comparison group of firms is supported by a qualitative analysis of a large amount of documentation of the activities of the DOE SSL program.  In addition to using NGLIA membership as the key independent variable, I use citations to the patents subject to CL as an upward-biased proxy for the unobserved patent licenses. After matching between the comparison group firms and the NGLIA firms, I compare the two groups’ patenting behavior and citations to DOE SSL-funded patents in order to identify the effect of CL on each of these outcomes.