Published in

Elsevier, Journal of Environmental Economics and Management, 2(54), p. 146-161

DOI: 10.1016/j.jeem.2007.03.001

Links

Tools

Export citation

Search in Google Scholar

Innovation without magic bullets: Stock pollution and R&D sequences

Journal article published in 2007 by Timo Goeschl, Grischa Perino ORCID
This paper was not found in any repository, but could be made available legally by the author.
This paper was not found in any repository, but could be made available legally by the author.

Full text: Unavailable

Green circle
Preprint: archiving allowed
Red circle
Postprint: archiving forbidden
Red circle
Published version: archiving forbidden
Data provided by SHERPA/RoMEO

Abstract

We study the optimal R&D trajectory in a setting where new technologies are never perfect backstops in the sense that there is no perfectly clean technology that eventually solves the pollution problem once and for all. New technologies have strings attached, i.e. each emits a specific stock pollutant. Damages are convex in individual pollution stocks but additive across stocks, creating gains from diversification. The research and pollution policies are tightly linked in such a setting. We derive the optimal pollution path and R&D program. Pollution stocks overshoot and in the long-run all available technologies produce. Research is sequential and the optimal portfolio of technologies is finite.