We develop a microeconomic model of endogenous growth where clean and dirty technologies compete in production and innovation-in the sense that research can be directed to either clean or dirty technologies. If dirty technologies are more advanced to start with, the potential transition to clean technology can be di¢ cult both because clean research must climb several rungs to catch up with dirty technology and because this gap discourages research e¤ort directed towards clean technologies. Carbon taxes and research subsidies may nonetheless encourage production and innovation in clean technologies, though the transition will typically be slow. We characterize certain general properties of the transition path from dirty to clean technology. We then estimate the model using a combination of regression analysis on the relationship between R&D and patents, and simulated method of moments using microdata on employment, production, R&D, …rm growth, entry and exit from the US energy sector. The model's quantitative implications match a range of moments not targeted in the estimation quite well. We then characterize the optimal policy path implied by the model and our estimates. Optimal policy makes heavy use of research subsidies as well as carbon taxes. We use the model to evaluate the welfare consequences of a range of alternative policies. JEL Classi…cation: O30, O31, O33, C65.
We develop a microeconomic model of endogenous growth where clean and dirty technologies compete in production and innovation-in the sense that research can be directed to either clean or dirty technologies. If dirty technologies are more advanced to start with, the potential transition to clean technology can be di¢ cult both because clean research must climb several rungs to catch up with dirty technology and because this gap discourages research e¤ort directed towards clean technologies. Carbon taxes and research subsidies may nonetheless encourage production and innovation in clean technologies, though the transition will typically be slow. We characterize certain general properties of the transition path from dirty to clean technology. We then estimate the model using a combination of regression analysis on the relationship between R&D and patents, and simulated method of moments using microdata on employment, production, R&D, …rm growth, entry and exit from the US energy sector. The model's quantitative implications match a range of moments not targeted in the estimation quite well. We then characterize the optimal policy path implied by the model and our estimates. Optimal policy makes heavy use of research subsidies as well as carbon taxes. We use the model to evaluate the welfare consequences of a range of alternative policies. JEL Classi…cation: O30, O31, O33, C65.
This paper introduces a general equilibrium model of endogenous technical change through basic and applied research. Basic research differs from applied research in the nature and the magnitude of the generated spillovers. We propose a novel way of empirically identifying these spillovers and embed them in a framework with private firms and a public research sector. After characterizing the equilibrium, we estimate our model using micro-level data on research expenditures by French firms. Our key finding is that standard innovation policies (e.g., uniform R&D tax credits) can accentuate the dynamic misallocation in the economy by oversubsidizing applied research. Policies geared towards public basic research and its transmission to the private sector are significantly welfare improving.
Mexico), and Midwest Macro. Researcher(s)' own analyses were calculated (or derived) based in part on data from The Nielsen Company (US) LLC and marketing databases provided through the Nielsen data sets at the Kilts Center for Marketing Data Center at the University of Chicago Booth School of Business. The conclusions drawn from the Nielsen data are those of the researcher(s) and do not reflect the views of Nielsen. Nielsen is not responsible for, had no role in, and was not involved in analyzing and preparing the results reported herein. The views expressed here are those of the authors and not necessarily those of the Federal Reserve Bank of Atlanta or the Federal Reserve System. Any remaining errors are the authors' responsibility.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.