Climate change and other environmental challenges require the development of new energy technologies with lower emissions. In the near term, R&D investments, either by the government or the private sector, can reduce the costs of these lower-emitting technologies. However, the returns to R&D are uncertain, and there are many potential technologies that may emerge to play an important role in the future energy mix. In this paper, we address the problem of allocating scarce R&D resources across technologies when uncertainties exist. We develop a multistage stochastic dynamic programming version of an integrated assessment model of the climate and economy that represents endogenous technological change through R&D decisions for two substitutable noncarbon backstop technologies. We demonstrate that near-term R&D investment in the higher cost technology is justified and that the optimal R&D investment in the higher cost technology increases with both higher variance and higher skewness in the distribution of returns to R&D.
|Original language||English (US)|
|Journal||Journal of the Association of Environmental and Resource Economists|
|State||Published - Sep 1 2017|
All Science Journal Classification (ASJC) codes
- Economics and Econometrics
- Nature and Landscape Conservation
- Management, Monitoring, Policy and Law