IDEAS home Printed from https://ideas.repec.org/a/eee/eneeco/v31y2009isupplement1ps27-s36.html
   My bibliography  Save this article

R&D investment strategy for climate change

Author

Listed:
  • Blanford, Geoffrey J.

Abstract

The economic costs of stabilizing greenhouse gas concentrations over the coming century depend critically on the development of new technologies in the energy sector. Our research and development (R&D) investment strategy is the control variable for technology availability. This paper proposes an analytic framework for determining optimal R&D investment allocation and presents some numerical results to demonstrate the implementation of the methodology. The value of technological advance in three targeted areas-fossil-based generation, renewables, and carbon capture and storage-is represented by the increase in expected welfare in the presence of an emissions policy constraint of initially uncertain stringency. R&D expenditure increases the probability of advance. Optimal investment is determined by its relationship with success probability, which is assumed to exhibit decreasing returns to scale, relative to the value of success. While the numerical results are speculative, the paper offers insights into the nature of an optimal technology strategy for addressing climate change.

Suggested Citation

  • Blanford, Geoffrey J., 2009. "R&D investment strategy for climate change," Energy Economics, Elsevier, vol. 31(Supplemen), pages 27-36.
    • Handle: RePEc:eee:eneeco:v:31:y:2009:i:supplement1:p:s27-s36
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0140-9883(08)00053-4
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Richard G. Richels & Thomas F. Rutherford & Geoffrey J. Blanford & Leon Clarke, 2007. "Managing the transition to climate stabilization," Climate Policy, Taylor & Francis Journals, vol. 7(5), pages 409-428, September.
    2. Christoph H. Loch & Stylianos Kavadias, 2002. "Dynamic Portfolio Selection of NPD Programs Using Marginal Returns," Management Science, INFORMS, vol. 48(10), pages 1227-1241, October.
    3. Manne, Alan & Mendelsohn, Robert & Richels, Richard, 1995. "MERGE : A model for evaluating regional and global effects of GHG reduction policies," Energy Policy, Elsevier, vol. 23(1), pages 17-34, January.
    4. Kenneth Arrow, 1962. "Economic Welfare and the Allocation of Resources for Invention," NBER Chapters, in: The Rate and Direction of Inventive Activity: Economic and Social Factors, pages 609-626, National Bureau of Economic Research, Inc.
    5. Stavins, Robert & Jaffe, Adam & Newell, Richard, 2000. "Technological Change and the Environment," Working Paper Series rwp00-002, Harvard University, John F. Kennedy School of Government.
    6. Ferdinand A. Gul & Judy S. L. Tsui, 2004. "Introduction and overview," Palgrave Macmillan Books, in: The Governance of East Asian Corporations, chapter 1, pages 1-26, Palgrave Macmillan.
    7. Weyant, John P., 2004. "Introduction and overview," Energy Economics, Elsevier, vol. 26(4), pages 501-515, July.
    8. Bosetti, Valentina & Tavoni, Massimo, 2009. "Uncertain R&D, backstop technology and GHGs stabilization," Energy Economics, Elsevier, vol. 31(Supplemen), pages 18-26.
    9. 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.
    10. Harry Markowitz, 1952. "Portfolio Selection," Journal of Finance, American Finance Association, vol. 7(1), pages 77-91, March.
    11. van der Zwaan, B. C. C. & Gerlagh, R. & G. & Klaassen & Schrattenholzer, L., 2002. "Endogenous technological change in climate change modelling," Energy Economics, Elsevier, vol. 24(1), pages 1-19, January.
    12. Goulder, Lawrence H. & Mathai, Koshy, 2000. "Optimal CO2 Abatement in the Presence of Induced Technological Change," Journal of Environmental Economics and Management, Elsevier, vol. 39(1), pages 1-38, January.
    13. Goulder, Lawrence H. & Schneider, Stephen H., 1999. "Induced technological change and the attractiveness of CO2 abatement policies," Resource and Energy Economics, Elsevier, vol. 21(3-4), pages 211-253, August.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Baker, Erin & Shittu, Ekundayo, 2008. "Uncertainty and endogenous technical change in climate policy models," Energy Economics, Elsevier, vol. 30(6), pages 2817-2828, November.
    2. Kalkuhl, Matthias & Edenhofer, Ottmar & Lessmann, Kai, 2012. "Learning or lock-in: Optimal technology policies to support mitigation," Resource and Energy Economics, Elsevier, vol. 34(1), pages 1-23.
    3. 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.
    4. Richels, Richard G. & Blanford, Geoffrey J., 2008. "The value of technological advance in decarbonizing the U.S. economy," Energy Economics, Elsevier, vol. 30(6), pages 2930-2946, November.
    5. Mort Webster & Karen Fisher-Vanden & David Popp & Nidhi Santen, 2017. "Should We Give Up after Solyndra? Optimal Technology R&D Portfolios under Uncertainty," Journal of the Association of Environmental and Resource Economists, University of Chicago Press, vol. 4(S1), pages 123-151.
    6. Gerlagh, Reyer, 2007. "Measuring the value of induced technological change," Energy Policy, Elsevier, vol. 35(11), pages 5287-5297, November.
    7. Gerlagh, Reyer & Lise, Wietze, 2005. "Carbon taxes: A drop in the ocean, or a drop that erodes the stone? The effect of carbon taxes on technological change," Ecological Economics, Elsevier, vol. 54(2-3), pages 241-260, August.
    8. Bistline, John E., 2016. "Energy technology R&D portfolio management: Modeling uncertain returns and market diffusion," Applied Energy, Elsevier, vol. 183(C), pages 1181-1196.
    9. Tol, Richard S.J., 2013. "Targets for global climate policy: An overview," Journal of Economic Dynamics and Control, Elsevier, vol. 37(5), pages 911-928.
    10. Gerlagh, Reyer, 2008. "A climate-change policy induced shift from innovations in carbon-energy production to carbon-energy savings," Energy Economics, Elsevier, vol. 30(2), pages 425-448, March.
    11. Shiell, Leslie & Lyssenko, Nikita, 2014. "Climate policy and induced R&D: How great is the effect?," Energy Economics, Elsevier, vol. 46(C), pages 279-294.
    12. Carraro, Carlo & De Cian, Enrica & Nicita, Lea & Massetti, Emanuele & Verdolini, Elena, 2010. "Environmental Policy and Technical Change: A Survey," International Review of Environmental and Resource Economics, now publishers, vol. 4(2), pages 163-219, October.
    13. Kverndokk, Snorre & Rosendahl, Knut Einar, 2007. "Climate policies and learning by doing: Impacts and timing of technology subsidies," Resource and Energy Economics, Elsevier, vol. 29(1), pages 58-82, January.
    14. Tunç Durmaz & Fred Schroyen, 2020. "Evaluating Carbon Capture And Storage In A Climate Model With Endogenous Technical Change," Climate Change Economics (CCE), World Scientific Publishing Co. Pte. Ltd., vol. 11(01), pages 1-47, February.
    15. Clarke, Leon & Weyant, John & Birky, Alicia, 2006. "On the sources of technological change: Assessing the evidence," Energy Economics, Elsevier, vol. 28(5-6), pages 579-595, November.
    16. Clarke, Leon & Weyant, John & Edmonds, Jae, 2008. "On the sources of technological change: What do the models assume," Energy Economics, Elsevier, vol. 30(2), pages 409-424, March.
    17. 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.
    18. Popp, David & Santen, Nidhi & Fisher-Vanden, Karen & Webster, Mort, 2013. "Technology variation vs. R&D uncertainty: What matters most for energy patent success?," Resource and Energy Economics, Elsevier, vol. 35(4), pages 505-533.
    19. Nidhi R. Santen & Mort D. Webster & David Popp & Ignacio Pérez-Arriaga, 2014. "Inter-temporal R&D and Capital Investment Portfolios for the Electricity Industry’s Low Carbon Future," NBER Working Papers 20783, National Bureau of Economic Research, Inc.
    20. Nidhi R. Santen & Mort D. Webster & David Popp & Ignacio Pérez-Arriaga, 2017. "Inter-temporal R&D and capital investment portfolios for the electricity industrys low carbon future," The Energy Journal, International Association for Energy Economics, vol. 0(Number 6).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:eneeco:v:31:y:2009:i:supplement1:p:s27-s36. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eneco .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.