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Optimal CO2-abatement with Socio-economic Inertia and Induced Technological Change

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  • Malte Schwoon
  • Richard S.J. Tol

Abstract

The impact of induced technological change (ITC) in energy/climate models on the timing of optimal CO2-abatement depends on whether R&D or learning-by-doing (LBD) is the driving force. Bottom-up energy system models employing LBD suggest strong increases in optimal early abatement. In this paper we extend an existing top-down model supporting this view according to the notion that socio-economic inertia interferes with rapid technological change. We derive analytical results concerning the impact of inertia and ITC on optimal initial abatement and show a wide range of numerical simulations to illustrate magnitudes. Inertia now dominates the timing decision on early abatement, such that LBD might even have a negative effect on early abatement and the impact of R&D is limited. However, ITC still reduces costs of stabilizing atmospheric CO2-concentrations considerably.

Suggested Citation

  • Malte Schwoon & Richard S.J. Tol, 2006. "Optimal CO2-abatement with Socio-economic Inertia and Induced Technological Change," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4), pages 25-60.
  • Handle: RePEc:aen:journl:2006v27-04-a02
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    Cited by:

    1. 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.
    2. 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.
    3. Vogt-Schilb, Adrien & Hallegatte, Stéphane, 2014. "Marginal abatement cost curves and the optimal timing of mitigation measures," Energy Policy, Elsevier, vol. 66(C), pages 645-653.
    4. repec:hal:ciredw:hal-00916328 is not listed on IDEAS
    5. Lennox, James A. & Witajewski-Baltvilks, Jan, 2017. "Directed technical change with capital-embodied technologies: Implications for climate policy," Energy Economics, Elsevier, vol. 67(C), pages 400-409.
    6. Guo, Jian-Xin & Zhu, Lei & Fan, Ying, 2016. "Emission path planning based on dynamic abatement cost curve," European Journal of Operational Research, Elsevier, vol. 255(3), pages 996-1013.
    7. Vogt-Schilb, Adrien & Meunier, Guy & Hallegatte, Stephane, 2012. "How inertia and limited potentials affect the timing of sectoral abatements in optimal climate policy," Policy Research Working Paper Series 6154, The World Bank.
    8. Popp, David & Newell, Richard G. & Jaffe, Adam B., 2010. "Energy, the Environment, and Technological Change," Handbook of the Economics of Innovation, Elsevier.
    9. repec:hal:wpaper:hal-00916328 is not listed on IDEAS
    10. 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.
    11. 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.
    12. Edward B. Barbier, 2013. "Is a global crisis required to prevent climate change? A historical–institutional perspective," Chapters,in: Handbook on Energy and Climate Change, chapter 28, pages 598-614 Edward Elgar Publishing.
    13. David Popp & Nidhi Santen & Karen Fisher-Vanden & Mort Webster, 2012. "Technology Variation vs. R&D Uncertainty: What Matters Most for Energy Patent Success?," NBER Working Papers 17792, National Bureau of Economic Research, Inc.
    14. Raymond J.G.M. Florax & Henri L.F. de Groot & Peter Mulder, 2011. "Energy Efficiency and Technological Change," Chapters,in: Improving Energy Efficiency through Technology, chapter 1 Edward Elgar Publishing.

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    JEL classification:

    • F0 - International Economics - - General

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