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Learning Curves For Energy Technology and Policy Analysis: A Critical Assessment

Author

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  • Jamasb, T.
  • Köhler, J.

Abstract

In this paper, which forms a chapter in the forthcoming Book “Delivering a Low Carbon Electricity System: Technologies, Economics and Policy”†, Jamasb and Kohler revisit the literature on learning curves and their application to energy technology and climate change policy analysis and modeling. The academic literature and policy documents have in recent years embraced the learning curves and applied the concept to technology analysis and forecasting cost reductions. We argue that learning curves have often been used or assumed uncritically in technology analysis and draw parallels between the use of learning rates in energy technological progress and climate change modeling to that of discount rates in social cost benefit analysis. The paper discusses that care needs to be taken in applying learning curves, originally developed as an empirical tool to assess the effect of learning by doing in manufacturing, to analysis innovation and technical change. Finally, we suggest some potential extensions of learning curves, e.g. by incorporating R&D and diffusion effects into learning models, and other areas where learning curves may potentially be a useful tool in energy technology policy and analysis.

Suggested Citation

  • Jamasb, T. & Köhler, J., 2007. "Learning Curves For Energy Technology and Policy Analysis: A Critical Assessment," Cambridge Working Papers in Economics 0752, Faculty of Economics, University of Cambridge.
  • Handle: RePEc:cam:camdae:0752
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    File URL: http://www.electricitypolicy.org.uk/pubs/wp/eprg0723.pdf
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    Citations

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    Cited by:

    1. Hansson, Anders & Bryngelsson, Mårten, 2009. "Expert opinions on carbon dioxide capture and storage--A framing of uncertainties and possibilities," Energy Policy, Elsevier, vol. 37(6), pages 2273-2282, June.
    2. Lee, Kangil & Han, Taek-Whan, 2016. "How vulnerable is the emissions market to transaction costs?: An ABMS Approach," Energy Policy, Elsevier, vol. 90(C), pages 273-286.
    3. repec:eee:enepol:v:106:y:2017:i:c:p:427-435 is not listed on IDEAS
    4. Tobias Wiesnethal & Arnaud Mercier & Burkhard Schade & H. Petric & Lazlo Szabo, 2010. "Quantitative Assessment of the Impact of the Strategic Energy Technology Plan on the European Power Sector," JRC Working Papers JRC61065, Joint Research Centre (Seville site).
    5. Adela Conchado & Pedro Linares, 2017. "A New ‘Cut’ on Technological Innovation Aiming for Sustainability in a Globalized World," SPRU Working Paper Series 2017-25, SPRU - Science and Technology Policy Research, University of Sussex.
    6. Egging, Ruud, 2013. "Drivers, trends, and uncertainty in long-term price projections for energy management in public buildings," Energy Policy, Elsevier, vol. 62(C), pages 617-624.
    7. Sovacool, Benjamin K. & Gilbert, Alex & Nugent, Daniel, 2014. "Risk, innovation, electricity infrastructure and construction cost overruns: Testing six hypotheses," Energy, Elsevier, vol. 74(C), pages 906-917.
    8. Nepal, Rabindra, 2011. "The roles and potentials of renewable energy in less-developed economies," MPRA Paper 31878, University Library of Munich, Germany, revised 29 Jun 2011.
    9. Audrey Laude & Christian Jonen, 2011. "Biomass and CCS: The influence of the learning effect," Working Papers halshs-00829779, HAL.
    10. Rubin, Edward S. & Azevedo, Inês M.L. & Jaramillo, Paulina & Yeh, Sonia, 2015. "A review of learning rates for electricity supply technologies," Energy Policy, Elsevier, vol. 86(C), pages 198-218.
    11. Christian JONEN & Audrey LAUDE, 2011. "Biomasse and CCS: The Influence of the Learning Effect," LEO Working Papers / DR LEO 273, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    12. Hayward, Jennifer A. & Graham, Paul W., 2013. "A global and local endogenous experience curve model for projecting future uptake and cost of electricity generation technologies," Energy Economics, Elsevier, vol. 40(C), pages 537-548.
    13. Laude, Audrey & Jonen, Christian, 2013. "Biomass and CCS: The influence of technical change," Energy Policy, Elsevier, vol. 60(C), pages 916-924.
    14. Kessides, Ioannis N., 2012. "The future of the nuclear industry reconsidered: Risks, uncertainties, and continued promise," Energy Policy, Elsevier, vol. 48(C), pages 185-208.
    15. repec:eee:energy:v:129:y:2017:i:c:p:158-170 is not listed on IDEAS
    16. Nepal, Rabindra, 2012. "Roles and potentials of renewable energy in less-developed economies: The case of Nepal," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(4), pages 2200-2206.
    17. Arias-Gaviria, Jessica & van der Zwaan, Bob & Kober, Tom & Arango-Aramburo, Santiago, 2017. "The prospects for Small Hydropower in Colombia," Renewable Energy, Elsevier, vol. 107(C), pages 204-214.

    More about this item

    Keywords

    Energy technology; electricity; technical change; learning curves.;

    JEL classification:

    • O3 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights
    • Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy

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