Climate change and optimal energy technology R&D policy
Public policy response to global climate change presents a classic problem of decision making under uncertainty. Theoretical work has shown that explicitly accounting for uncertainty and learning in climate change can have a large impact on optimal policy, especially technology policy. However, theory also shows that the specific impacts of uncertainty are ambiguous. In this paper, we provide a framework that combines economics and decision analysis to implement probabilistic data on energy technology research and development (R&D) policy in response to global climate change. We find that, given a budget constraint, the composition of the optimal R&D portfolio is highly diversified and robust to risk in climate damages. The overall optimal investment into technical change, however, does depend (in a non-monotonic way) on the risk in climate damages. Finally, we show that in order to properly value R&D, abatement must be included as a recourse decision.
If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Baker, Erin & Chon, Haewon & Keisler, Jeffrey, 2009. "Advanced solar R&D: Combining economic analysis with expert elicitations to inform climate policy," Energy Economics, Elsevier, vol. 31(Supplemen), pages 37-49.
- Goeschl, Timo & Perino, Grischa, 2009.
"On backstops and boomerangs: Environmental R&D under technological uncertainty,"
Elsevier, vol. 31(5), pages 800-809, September.
- Timo Goeschl & Grischa Perino, 2007. "On Backstops and Boomerangs: Environmental R&D under Technological Uncertainty," Working Papers 0437, University of Heidelberg, Department of Economics, revised Jan 2007.
- Farzin, Y H & Kort, P M, 2000. " Pollution Abatement Investment When Environmental Regulation Is Uncertain," Journal of Public Economic Theory, Association for Public Economic Theory, vol. 2(2), pages 183-212.
- Kort, P.M. & Farzin, Y.H., 2000. "Pollution abatement investment when environmental regulation is uncertain," Other publications TiSEM 90e78d8b-95d9-4d17-9d0f-4, Tilburg University, School of Economics and Management.
- Blanford, Geoffrey J., 2009. "R&D investment strategy for climate change," Energy Economics, Elsevier, vol. 31(Supplemen), pages 27-36.
- Baker, Erin & Shittu, Ekundayo, 2006. "Profit-maximizing R&D in response to a random carbon tax," Resource and Energy Economics, Elsevier, vol. 28(2), pages 160-180, May.
- Baker, Erin & Adu-Bonnah, Kwame, 2008. "Investment in risky R&D programs in the face of climate uncertainty," Energy Economics, Elsevier, vol. 30(2), pages 465-486, March.
- Ronald A. Howard, 1988. "Decision Analysis: Practice and Promise," Management Science, INFORMS, vol. 34(6), pages 679-695, June.
- Sue Wing, Ian, 2006. "Representing induced technological change in models for climate policy analysis," Energy Economics, Elsevier, vol. 28(5-6), pages 539-562, November.
- Rothschild, Michael & Stiglitz, Joseph E., 1970. "Increasing risk: I. A definition," Journal of Economic Theory, Elsevier, vol. 2(3), pages 225-243, September.
- Pizer, William A. & Popp, David, 2008. "Endogenizing technological change: Matching empirical evidence to modeling needs," Energy Economics, Elsevier, vol. 30(6), pages 2754-2770, November.
- Pizer, William A. & Popp, David, 2007. "Endogenizing Technological Change: Matching Empirical Evidence to Modeling Needs," Discussion Papers dp-07-11, Resources For the Future.
- William A. Pizer & David Popp, 2007. "Endogenizing Technological Change: Matching Empirical Evidence to Modeling Needs," NBER Working Papers 13053, National Bureau of Economic Research, Inc.
- repec:spr:compst:v:58:y:2003:i:1:p:57-68 is not listed on IDEAS
- Gillingham, Kenneth & Newell, Richard G. & Pizer, William A., 2008. "Modeling endogenous technological change for climate policy analysis," Energy Economics, Elsevier, vol. 30(6), pages 2734-2753, November.
- Gillingham, Kenneth T. & Newell, Richard G. & Pizer, William A., 2007. "Modeling Endogenous Technological Change for Climate Policy Analysis," Discussion Papers dp-07-14, Resources For the Future.
- Laurent Gilotte & Valentina Bosetti, 2007. "The impact of carbon capture and storage on overall mitigation policy," Climate Policy, Taylor & Francis Journals, vol. 7(1), pages 3-12, January.
- L. Gilotte & V. Bosetti, 2007. "The impact of carbon capture and storage on overall mitigation policy," Post-Print hal-00716171, HAL.
- Popp, David, 2006. "ENTICE-BR: The effects of backstop technology R&D on climate policy models," Energy Economics, Elsevier, vol. 28(2), pages 188-222, March.
- Valentina Bosetti & Laurent Drouet, 2005. "Accounting for Uncertainty Affecting Technical Change in an Economic-Climate Model," Working Papers 2005.147, Fondazione Eni Enrico Mattei.
- Baker, Erin & Shittu, Ekundayo, 2008. "Uncertainty and endogenous technical change in climate policy models," Energy Economics, Elsevier, vol. 30(6), pages 2817-2828, November. Full references (including those not matched with items on IDEAS)