Washington D.C. - Venture-backed startups generate nine times the knowledge spillovers (e.g., patenting activity and citations) when compared to that produced by R&D investment of established companies, according to recent research. In Measuring the Spillovers of Venture Capital, researchers from the University of Munich found that, on average, two-thirds of this increase can be traced to more patenting by other companies within the VC-backed company’s spillover pool (e.g., companies with geographic or industry proximity). The companies that most benefited from the knowledge spillover were large, established companies.
Based upon their findings, the researchers contend that increased government support for venture capital is a more effective strategy for increasing regional commercialization and patenting activity than R&D subsidies for established companies. The researchers conclude with the policy proposal that subsidies for venture capital investment should be at least as large as current R&D subsidies for companies — specifically targeting investments in companies that engage in complex product technology development.
VC-backed startups that created the most knowledge spillovers were led by an experienced inventor team that held a patented technology at the time they received their first round of investment. The researchers also found that 'complex' product technology (e.g., computers) creates more spillover than startups that use a 'discrete' product technology (e.g., drugs). The researchers contend that discrete product technologies need less associated patents and have less incentive to work with other companies. In comparison, startups focused on complex product technologies are more likely to need industry partners to achieve the final product and create incentive to work with business in close proximity.
Methodology: To quantify knowledge spillover, the researchers developed a new method for identifying a set of additional companies — the spillover pool — that could potentially influence that company's innovation process. The new method combines information on a firm’s technology with information on the closeness of different technologies, based on patent citations. After identifying the spillover pools for both startup and established companies, the researchers calculated a matrix of all patent citation flows between technology classes and used it to determine the relevant pool of companies likely to be affected by spillovers. Through the new matrix-based model, the researchers contend that they were able to more accurately identify each company’s spillover than previous models because it not only includes potential spillover pool companies that are active in the same technology area, but are active in related technologies. The study was conducted using patent data from the National Bureau of Economic Research with firm level data of venture capital-financed companies and established companies in the U.S. from 1979 to 1999.
VC-backed startups that created the most knowledge spillovers were led by an experienced inventor team that held a patented technology at the time they received their first round of investment. The researchers also found that 'complex' product technology (e.g., computers) creates more spillover than startups that use a 'discrete' product technology (e.g., drugs). The researchers contend that discrete product technologies need less associated patents and have less incentive to work with other companies. In comparison, startups focused on complex product technologies are more likely to need industry partners to achieve the final product and create incentive to work with business in close proximity.
Methodology: To quantify knowledge spillover, the researchers developed a new method for identifying a set of additional companies — the spillover pool — that could potentially influence that company's innovation process. The new method combines information on a firm’s technology with information on the closeness of different technologies, based on patent citations. After identifying the spillover pools for both startup and established companies, the researchers calculated a matrix of all patent citation flows between technology classes and used it to determine the relevant pool of companies likely to be affected by spillovers. Through the new matrix-based model, the researchers contend that they were able to more accurately identify each company’s spillover than previous models because it not only includes potential spillover pool companies that are active in the same technology area, but are active in related technologies. The study was conducted using patent data from the National Bureau of Economic Research with firm level data of venture capital-financed companies and established companies in the U.S. from 1979 to 1999.
