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Uncertain R&D, Backstop Technology and GHGs Stabilization

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Listed:
  • Valentina Bosetti

    (Fondazione Eni Enrico Mattei)

  • Massimo Tavoni

    (Fondazione Eni Enrico Mattei)

Abstract

This paper analyses optimal investments in innovation when dealing with a stringent climate target and with the uncertain effectiveness of R&D. The innovation needed to achieve the deep cut in emissions is modelled by a backstop carbon-free technology whose cost depends on R&D investments. To better represent the process of technological progress, we assume that R&D effectiveness is uncertain. By means of a simple analytical model, we show how accounting for the uncertainty that characterizes technological advancement yields higher investments in innovation and lower policy costs. We then confirm the results via a numerical analysis performed with a stochastic version of WITCH, an energy-economy-climate model. The results stress the importance of a correct specification of the technological change process in economy-climate models.

Suggested Citation

  • Valentina Bosetti & Massimo Tavoni, 2007. "Uncertain R&D, Backstop Technology and GHGs Stabilization," Working Papers 2007.6, Fondazione Eni Enrico Mattei.
  • Handle: RePEc:fem:femwpa:2007.6
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    References listed on IDEAS

    as
    1. Valentina Bosetti & Carlo Carraro & Marzio Galeotti & Emanuele Massetti & Massimo Tavoni, 2006. "WITCH. A World Induced Technical Change Hybrid Model," Working Papers 2006_46, Department of Economics, University of Venice "Ca' Foscari".
    2. Valentina Bosetti & Carlo Carraro & Marzio Galeotti & Emanuele Massetti & Massimo Tavoni, 2006. "A World Induced Technical Change Hybrid Model," The Energy Journal, , vol. 27(2_suppl), pages 13-37, June.
    3. Valentina Bosetti & Emanuele Massetti & Massimo Tavoni, 2007. "The WITCH Model. Structure, Baseline, Solutions," Working Papers 2007.10, Fondazione Eni Enrico Mattei.
    4. Michael Grubb, Carlo Carraro and John Schellnhuber, 2006. "Technological Change for Atmospheric Stabilization: Introductory Overview to the Innovation Modeling Comparison Project," The Energy Journal, International Association for Energy Economics, vol. 0(Special I), pages 1-16.
    5. Baker, Erin & Clarke, Leon & Shittu, Ekundayo, 2008. "Technical change and the marginal cost of abatement," Energy Economics, Elsevier, vol. 30(6), pages 2799-2816, November.
    6. Popp, David, 2004. "ENTICE: endogenous technological change in the DICE model of global warming," Journal of Environmental Economics and Management, Elsevier, vol. 48(1), pages 742-768, July.
    7. 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.
    8. 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.
    9. Buonanno, Paolo & Carraro, Carlo & Galeotti, Marzio, 2003. "Endogenous induced technical change and the costs of Kyoto," Resource and Energy Economics, Elsevier, vol. 25(1), pages 11-34, February.
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    More about this item

    Keywords

    Climate Change; Information and Uncertainty; Environmental Policy; Optimal R&D Investments;
    All these keywords.

    JEL classification:

    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming
    • Q55 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environmental Economics: Technological Innovation

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