NIH funding spills over into the private sector, increasing innovation all around

Modern growth theory highlights the importance of knowledge spillovers for long-run economic growth. These spillovers mean that private firms will under-invest in the production of knowledge. Two types of policies aim to ameliorate this “market failure”: patent policy and public funding of research. While there is now a significant body of empirical research on the former, the effects of public funding, and public funding of science in particular, have received less attention. One reason for this paucity of evidence on the impacts of public research investments is that it is difficult to measure the effects of knowledge that is both non-rival and difficult to appropriate (Griliches 1992). While the idea that public science has large effects is central to U.S. policy— going back to Vannevar Bush’s 1945 assertion that basic research is “the pacemaker of technological progress”—economists emphasize that evidence in support of this claim is rather limited (Garber and Romer 1996; Cockburn and Henderson 1998). In this paper, we examine the effects of public science on private sector innovation in the life sciences, focusing on funding by the largest funder of research in the world, the National Institutes of Health. Our results show that NIH investments in a research area increase subsequent private sector patenting in that area; a $10 million increase in funding for an area leads to 2.3 additional patents or, equivalently, we expect one private-sector patent generated for every two to three NIH funded grants. This result holds across a variety of OLS and IV specifications. This positive impact, moreover, does not appear to be associated with lower private investments in other research areas. We cannot perform a formal rate of return calculation since our analysis focuses on only one aspect of the effect of NIH funding, that of sales associated with patented drugs. One rough calculation suggests that $1 dollar in NIH funding generates around $1.40 in drug sales. We find that over half of the patents that result from NIH funding flow across disease areas. This has implications for measurement: had we looked only at patents in the same disease area, we would have missed half the output. This finding speaks to a long-standing question in postwar medical research policy: the feasibility and desirability of targeting research to diseases. Claims that scientific research often flows across disease areas have been common from NIH Directors since the agency’s founding, especially during Congressional debates about whether particular diseases are over/underfunded or in response to advocates lobbying for a new Institute for “their” disease (Sampat 2012). Our results support the view that there are strong cross-disease spillovers. The organization of the agency around disease-specific Institutes, though useful for mobilizing funding, may not reflect the importance of the interplay of ideas from different disease areas and fields in shaping biomedical research progress. Throughout the text, we emphasized numerous caveats. We highlight several here. First, we are examining only one type of return to NIH funding, those that flow through patented innovations. This neglects a number of other socially important benefits of publicly-funded medical research, including applied epidemiological and clinical research that changes medical practice or health behaviors. Previous research (Cutler and Kadiyala 2003; Heidenreich and McClellan 2003) suggests this research has high value. Ignoring these outcomes could lead to large underestimates of the value of NIH funding. A second potential limitation is the assumption that patent-to-publication citations reflect real linkages between the cited grant/publications and citing patents. For the goal of measuring knowledge spillovers from public research, these citations are much more meaningful than patentto-patent citations, for reasons already discussed. However, articles are cited in patents for legal reasons, to denote “prior art” material to patentability, and decisions about how much to cite are influenced by factors including patent importance and applicant patent strategy (Sampat 2010). Not all articles cited are crucial for the development of the citing patent. Citations that are not real intellectual influences would lead to overestimates of the effects of NIH funding. (At the same time there are false negatives—not all knowledge firms “build on” must be cited—which would lead to underestimates of the effects of NIH funding.) Third, our implied drug valuations were based on publicly available estimates on the distribution of drug sales, and assumptions about how to divide a drug’s value across its many patents. There is likely considerable heterogeneity in the private and social value of drugs (Garthwaite and Duggan 2012), and individual patents (Hemphill and Sampat 2011), which our back-of-the-envelope calculations could not fully incorporate. Finally, our analysis implicitly assumes a “linear” flow from science to technology, and does not account for the complementary investments made by other actors (e.g., the NSF, or venture capital firms) in the path from laboratory to marketplace, or the feedbacks from technology to the progress of science. This “linear model” of research is well known to be an oversimplification, but even its detractors acknowledge that it is more reasonable in the life sciences than in other fields, and that alternative models would be far less empirically tractable (Balconi et al. 2010). Despite these limitations, our analysis uses novel data and a new source of identification to provide estimates on an important but understudied component of the innovation production function: spillovers from public research. In future work, this framework could be extended to examine a range of other questions of interest to economists and policymakers, including heterogeneity in types of research (whether more or less targeted research has higher impact) and how the presence or absence of intellectual property rights affects returns to public research investments.