We use a production function framework to estimate how government-funded R&D leads to the creation of new scientists and science. Focusing on public investments into specific energy technologies by the US Department of Energy (DOE), we leverage quasi-experimental variation in R&D investment that emerges when Congress appropriates more or less funding than what the DOE requests to estimate the effect of public funding on dissertation flows and recover the marginal costs of producing new (potential) scientists as proxied by dissertation flows. We also document the relationship between dissertations (potential scientists) and patents (new science). Our use of the production function framework allows us to recover technology-specific productivity trends and estimate the number of scientists and amount of science that would have been produced under alternative funding allocations. Given how noise in the budgeting process is prevalent, our adaptation of the production function framework could prove useful in many other settings.
Contact person: Ulrike Morgalla
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