Energy and Environmental Innovation
Paper Session
Sunday, Jan. 8, 2023 8:00 AM - 10:00 AM (CST)
- Chair: Kevin Bryan, University of Toronto
The Private Value of Clean Energy Innovation
Abstract
We examine the distribution of the private value of clean and dirty innovation using new methods based on patent data. We document that the value of clean innovations is higher and more dispersed. We find an overall decline in the variability of private values and returns in the wake of the Great Recession. This is consistent with the idea that financial restrictions have made investors and innovators more risk averse. Because clean and dirty innovations show different exposures to such risk aversion, the recession could have contributed to the decline of clean relative to dirty innovation.We develop a method to quantify counterfactual clean and dirty innovation that would have prevailed if the distribution of private values (or returns) would have stayed fixed. The results suggest that shying away from risky R&D in the wake of the Great Recession has considerably depressed the relative share of clean innovation but is not responsible for the clean drop in absolute terms. More broadly, our results suggest that financial constraints in the wake of crises may be an important barrier on the path to the clean equilibrium.
How Do (Green) Innovators Respond to Climate Change Scenarios? Evidence from a Field Experiment
Abstract
This paper aims to unpack the pro-social motivations of green innovators. In a field experiment inviting SBIR grantees to learn more about and apply to MIT Solve, we provide scientifically valid scenarios varying the time-frame and scale of human cost of climate change. Innovators’ response in clicks and applications increases with both scale and immediacy treatments. Our structural model estimates a welfare discount rate of 0.76%, providing a measure of innovators’ value of future generations, and an elasticity to lives lost of 0.23, implying diminishing marginal concern to human loss.Producing and Steering Inventors
Abstract
Increasing and steering innovation towards clean energy technologies will be critical for addressing climate change, but little is known about how to cost-effectively produce energy innovators, those that generate the knowledge upon which inventions are built. Most innovation policies provide incentives to firms that reduce the cost of investing in R&D, which could increase the demand for innovators, but they do not create scientific human capital directly. They also may just increase the wages of high-skilled workers if the supply of innovators is inelastic.In this paper, we study the returns to public investment in human capital by constructing a novel data set of PhD dissertations and estimating the effect of public funding for energy research on U.S. higher education institutions' dissertation flows. We first show that dissertations are strongly associated with patenting, demonstrating how dissertations serve as a reasonable proxy for inventors. We then exploit exogenous variation in technology-specific Congressional R&D appropriations that is generated by funding “windfalls” (i.e., the difference between requested and allocated funding) and estimate the effect of funding on the production of inventors. Our findings indicate that a 1% increase in funding produces about an additional third of an energy technology dissertation. We also show that the flow of PhDs is an important mechanism through which public funding for R&D shapes innovation, as up to 80% of the effect of funding on patents can be explained by how the funding creates PhD scientists.
Discussant(s)
Jennifer Kao
,
University of California-Los Angeles
Reinhilde Veugelers
,
KU Leuven
Jeff Shrader
,
Columbia University
Kevin Bryan
,
University of Toronto
JEL Classifications
- Q5 - Environmental Economics
- Q4 - Energy