IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Login to save this paper or follow this series

The dynamics of technology diffusion and the impacts of climate policy instruments in the decarbonisation of the global electricity sector

  • Jean-Francois Mercure

    ()

    (Cambridge Centre for Climate Change Mitigation Research, Department of Land Economy, University of Cambridge)

  • Hector Pollitt

    ()

    (Cambridge Econometrics Ltd, Covent Garden, Cambridge, CB1 2HT, UK)

  • Unnada Chewpreecha

    ()

    (Cambridge Econometrics Ltd, Covent Garden, Cambridge, CB1 2HT, UK)

  • Pablo Salas

    ()

    (Cambridge Centre for Climate Change Mitigation Research, Department of Land Economy, University of Cambridge)

  • Aideen M. Foley

    ()

    (Cambridge Centre for Climate Change Mitigation Research, Department of Land Economy, University of Cambridge)

  • Philip B. Holden

    ()

    (Environment, Earth and Ecosystems, Open University)

  • Neil R. Edwards

    ()

    (Environment, Earth and Ecosystems, Open University)

This paper presents an analysis of possible uses of climate policy instruments for the decarbonisation of the global electricity sector in a non-equilibrium economic and technology innovation-diffusion perspective. Emissions reductions occur through changes in technology and energy consumption; in this context, investment decision-making opportunities occur periodically, which energy policy can incentivise in order to transform energy systems and meet reductions targets. Energy markets are driven by innovation, dynamic costs and technology diffusion; yet, the incumbent systems optimisation methodology in energy modelling does not address these aspects nor the effectiveness of policy onto decision-making since the dynamics modelled take their source from the top-down `social-planner' assumption. This leads to an underestimation of strong technology lock-ins in cost-optimal scenarios of technology. Breaking this tradition, our approach explores bottom-up investor dynamics led global diffusion of low carbon technology in connection to a highly disaggregated sectoral macroeconometric model of the global economy, FTT:Power-E3MG. A set of ten different projections to 2050 of the future global power sector in 21 regions based on different combinations of electricity policy instruments are modelled using this framework, with an analysis of their climate impacts. We show that in an environment emphasising diffusion and learning-by-doing, the impact of combinations of policies does not correspond to the sum of the impacts of individual instruments, but that strong synergies exist between policy schemes. We show that worldwide carbon pricing on its own is incapable of breaking the current fossil technology lock-in, but that under an elaborate set of policies, the global electricity sector can be decarbonised affordably by 89% by 2050 without early scrapping of capital.

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.

File URL: http://be.4cmr.group.cam.ac.uk/working-papers/pdf/4cmr_WP_06.pdf
File Function: First version, 2013
Download Restriction: no

Paper provided by University of Cambridge, Department of Land Economy, Cambridge Centre for Climate Change Mitigation Research in its series 4CMR Working Paper Series with number 006.

as
in new window

Length: 19 pages
Date of creation: Oct 2013
Date of revision:
Handle: RePEc:ccc:wpaper:006
Contact details of provider: Postal: 19 Silver Street, Cambridge CB3 9EP
Phone: +44 1223 337147
Fax: +44 1223 337130
Web page: http://www.4cmr.group.cam.ac.uk/

More information through EDIRC

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.:

as in new window
  1. Arrow, Kenneth & Bolin, Bert & Costanza, Robert & Dasgupta, Partha & Folke, Carl & Holling, C. S. & Jansson, Bengt-Owe & Levin, Simon & Maler, Karl-Goran & Perrings, Charles & Pimentel, David, 1995. "Economic growth, carrying capacity, and the environment," Ecological Economics, Elsevier, vol. 15(2), pages 91-95, November.
  2. Detlef Vuuren & James Edmonds & Mikiko Kainuma & Keywan Riahi & John Weyant, 2011. "A special issue on the RCPs," Climatic Change, Springer, vol. 109(1), pages 1-4, November.
  3. Sir Nicholas Stern, 2006. "What is the Economics of Climate Change?," World Economics, World Economics, Economic & Financial Publishing, 1 Ivory Square, Plantation Wharf, London, United Kingdom, SW11 3UE, vol. 7(2), pages 1-10, April.
  4. Loschel, Andreas, 2002. "Technological change in economic models of environmental policy: a survey," Ecological Economics, Elsevier, vol. 43(2-3), pages 105-126, December.
  5. Mercure, Jean-François & Salas, Pablo, 2013. "On the global economic potentials and marginal costs of non-renewable resources and the price of energy commodities," Energy Policy, Elsevier, vol. 63(C), pages 469-483.
  6. Saviotti, P P & Mani, G S, 1995. "Competition, Variety and Technological Evolution: A Replicator Dynamics Model," Journal of Evolutionary Economics, Springer, vol. 5(4), pages 369-92, December.
  7. Terry Barker, Haoran Pan, Jonathan Kohler, Rachel Warren, and Sarah Winne, 2006. "Decarbonizing the Global Economy with Induced Technological Change: Scenarios to 2100 using E3MG," The Energy Journal, International Association for Energy Economics, vol. 0(Special I), pages 241-258.
  8. Axsen, Jonn & Mountain, Dean C. & Jaccard, Mark, 2009. "Combining stated and revealed choice research to simulate the neighbor effect: The case of hybrid-electric vehicles," Institute of Transportation Studies, Working Paper Series qt02n9j6cv, Institute of Transportation Studies, UC Davis.
  9. J. -F. Mercure, 2013. "An age structured demographic theory of technological change," Papers 1304.3602, arXiv.org, revised Nov 2014.
  10. Karmeshu & Bhargava, S. C. & Jain, V. P., 1985. "A rationale for law of technological substitution," Regional Science and Urban Economics, Elsevier, vol. 15(1), pages 137-141, February.
  11. Arthur, W Brian, 1989. "Competing Technologies, Increasing Returns, and Lock-In by Historical Events," Economic Journal, Royal Economic Society, vol. 99(394), pages 116-31, March.
  12. Wilson, Charlie, 2012. "Up-scaling, formative phases, and learning in the historical diffusion of energy technologies," Energy Policy, Elsevier, vol. 50(C), pages 81-94.
  13. McDonald, Alan & Schrattenholzer, Leo, 2001. "Learning rates for energy technologies," Energy Policy, Elsevier, vol. 29(4), pages 255-261, March.
  14. David Anthoff & Richard Tol, 2013. "The uncertainty about the social cost of carbon: A decomposition analysis using fund," Climatic Change, Springer, vol. 117(3), pages 515-530, April.
  15. David Anthoff & Richard Tol, 2013. "Erratum to: The uncertainty about the social cost of carbon: A decomposition analysis using fund," Climatic Change, Springer, vol. 121(2), pages 413-413, November.
  16. Köhler, Jonathan & Whitmarsh, Lorraine & Nykvist, Björn & Schilperoord, Michel & Bergman, Noam & Haxeltine, Alex, 2009. "A transitions model for sustainable mobility," Ecological Economics, Elsevier, vol. 68(12), pages 2985-2995, October.
  17. J. F. Mercure & P. Salas, 2012. "An assessement of global energy resource economic potentials," Papers 1205.4693, arXiv.org, revised Aug 2012.
  18. Takeshita, Takayuki, 2011. "Competitiveness, role, and impact of microalgal biodiesel in the global energy future," Applied Energy, Elsevier, vol. 88(10), pages 3481-3491.
  19. Mercure, Jean-François, 2012. "FTT:Power : A global model of the power sector with induced technological change and natural resource depletion," Energy Policy, Elsevier, vol. 48(C), pages 799-811.
  20. Costanza, Robert, 1995. "Economic growth, carrying capacity, and the environment," Ecological Economics, Elsevier, vol. 15(2), pages 89-90, November.
  21. Geels, Frank W., 2002. "Technological transitions as evolutionary reconfiguration processes: a multi-level perspective and a case-study," Research Policy, Elsevier, vol. 31(8-9), pages 1257-1274, December.
  22. C. Wilson & A. Grubler & N. Bauer & V. Krey & K. Riahi, 2013. "Future capacity growth of energy technologies: are scenarios consistent with historical evidence?," Climatic Change, Springer, vol. 118(2), pages 381-395, May.
  23. Terry Barker & Annela Anger & Unnada Chewpreecha & Hector Pollitt, 2012. "A new economics approach to modelling policies to achieve global 2020 targets for climate stabilisation," International Review of Applied Economics, Taylor & Francis Journals, vol. 26(2), pages 205-221, October.
  24. William D. Nordhaus, 2014. "The Perils of the Learning Model for Modeling Endogenous Technological Change," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1).
  25. Geoffrey Hodgson & Kainan Huang, 2012. "Evolutionary game theory and evolutionary economics: are they different species?," Journal of Evolutionary Economics, Springer, vol. 22(2), pages 345-366, April.
  26. L. Randall Wray & Stephanie Bell, 2004. "Introduction," Chapters, in: Credit and State Theories of Money, chapter 1 Edward Elgar.
  27. Grubler, Arnulf & Nakicenovic, Nebojsa & Victor, David G., 1999. "Dynamics of energy technologies and global change," Energy Policy, Elsevier, vol. 27(5), pages 247-280, May.
  28. Rivers, Nic & Jaccard, Mark, 2006. "Useful models for simulating policies to induce technological change," Energy Policy, Elsevier, vol. 34(15), pages 2038-2047, October.
  29. Terry Barker and S. Serban Scrieciu, 2010. "Modeling Low Climate Stabilization with E3MG: Towards a 'New Economics' Approach to Simulating Energy-Environment-Economy System Dynamics," The Energy Journal, International Association for Energy Economics, vol. 0(Special I).
  30. Axsen, Jonn & Mountain, Dean C. & Jaccard, Mark, 2009. "Combining stated and revealed choice research to simulate the neighbor effect: The case of hybrid-electric vehicles," Resource and Energy Economics, Elsevier, vol. 31(3), pages 221-238, August.
  31. Hoogwijk, Monique & de Vries, Bert & Turkenburg, Wim, 2004. "Assessment of the global and regional geographical, technical and economic potential of onshore wind energy," Energy Economics, Elsevier, vol. 26(5), pages 889-919, September.
  32. Karolina Safarzyńska & Jeroen Bergh, 2010. "Evolutionary models in economics: a survey of methods and building blocks," Journal of Evolutionary Economics, Springer, vol. 20(3), pages 329-373, June.
  33. Shum, Kwok L. & Watanabe, Chihiro, 2010. "Network externality perspective of feed-in-tariffs (FIT) instruments--Some observations and suggestions," Energy Policy, Elsevier, vol. 38(7), pages 3266-3269, July.
Full references (including those not matched with items on IDEAS)

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

When requesting a correction, please mention this item's handle: RePEc:ccc:wpaper:006. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Aleix Altimiras-Martin)

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 references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link 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 profile, as there may be some citations waiting for confirmation.

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

This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.