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The dynamics of carbon and energy intensity in a model of endogenous technical change

Author

Listed:
  • Carlo Carraro

    (Department of Economics, University Of Venice Ca� Foscari)

  • Valentina Bosetti

    (Fondazione Eni Enrico Mattei)

  • Marzio Galeotti

    (Fondazione Eni Enrico Mattei)

Abstract

T In recent years, a large number of papers have explored different attempts to endogenise technical change in climate models. This recent literature has emphasized that four factors � two inputs and two outputs � should play a major role when modelling technical change in climate models. The two inputs are R&D investments and Learning by Doing, the two outputs are energy-saving and fuel switching. Indeed, R&D investments and Learning by Doing are the main drivers of a climatefriendly technical change that eventually affect both energy intensity and fuel-mix. In this paper, we present and discuss an extension of the FEEM-RICE model in which these four factors are explicitly accounted for. In our new specification of endogenous technical change, an index of energy technical change depends on both Learning by Researching and Learning by Doing. This index enters the equations defining energy intensity (i.e. the amount of carbon energy required to produce one unit of output) and carbon intensity (i.e. the level of carbonization of primarily used fuels). This new specification is embodied in the RICE 99 integrated assessment climate model and then used to generate a baseline scenario and to analyze the relationship between climate policy and technical change. Sensitivity analysis is performed on different key parameters of the energy module in order to obtain crucial insights into the relative importance of the main channels through which technological changes affects the impact of human activities on climate.

Suggested Citation

  • Carlo Carraro & Valentina Bosetti & Marzio Galeotti, 2006. "The dynamics of carbon and energy intensity in a model of endogenous technical change," Working Papers 2006_11, Department of Economics, University of Venice "Ca' Foscari".
  • Handle: RePEc:ven:wpaper:2006_11
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    References listed on IDEAS

    as
    1. Castelnuovo, Efrem & Galeotti, Marzio & Gambarelli, Gretel & Vergalli, Sergio, 2005. "Learning-by-Doing vs. Learning by Researching in a model of climate change policy analysis," Ecological Economics, Elsevier, vol. 54(2-3), pages 261-276, August.
    2. Marzio Galeotti, 2003. "Environment and Economic Growth: Is Technical Change the Key to Decoupling?," Working Papers 2003.90, Fondazione Eni Enrico Mattei.
    3. Marzio Galeotti & Carlo Carraro, 2004. "Does Endogenous Technical Change Make a Difference in Climate Policy Analysis? A Robustness Exercise with the FEEM-RICE Model," Working Papers 2004.152, Fondazione Eni Enrico Mattei.
    4. 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.
    5. Valentina Bosetti & David Tomberlin, 2004. "Fondazione Eni Enrico Mattei," Working Papers 2004.102, Fondazione Eni Enrico Mattei.
    6. Loschel, Andreas, 2002. "Technological change in economic models of environmental policy: a survey," Ecological Economics, Elsevier, vol. 43(2-3), pages 105-126, December.
    7. Gerlagh, Reyer & van der Zwaan, Bob, 2003. "Gross world product and consumption in a global warming model with endogenous technological change," Resource and Energy Economics, Elsevier, vol. 25(1), pages 35-57, February.
    8. 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.
    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.
    10. Leonardo Barreto, Socrates Kypreos, 2002. "Multi-regional technological learning in the energysystems MARKAL model," International Journal of Global Energy Issues, Inderscience Enterprises Ltd, vol. 17(3), pages 189-213.
    11. Valentina Bosetti & Marzio Galeotti & Alessandro Lanza, 2006. "How consistent are alternative short-term climate policies with long-term goals?," Climate Policy, Taylor & Francis Journals, vol. 6(3), pages 295-312, May.
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    More about this item

    Keywords

    Climate Policy; Environmental Modelling; Integrated Assessment; Technical Change;
    All these keywords.

    JEL classification:

    • H0 - Public Economics - - General
    • H2 - Public Economics - - Taxation, Subsidies, and Revenue
    • H3 - Public Economics - - Fiscal Policies and Behavior of Economic Agents

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