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Technical Change Theory and Learning Curves: Patterns of Progress in Energy Technologies

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  • Tooraj Jamasb

    (Faculty of Economics, University of |Cambridge)

Abstract

This paper presents a comparative analysis of energy technology learning and progress within the framework of Schumpeter’s invention-innovation-diffusion paradigm. We estimate learning by doing and research rates for a range of energy technologies in four stages of technical progress. Emerging and mature technologies respond slowly to research and development (R&D) and capacity expansion; evolving technologies exhibit high learning-by-doing and research rates; reviving technologies exhibit considerable response to learning-by-research although they do not face significant market constraints. We generally find higher learning-by-doing than learning-by-research rates but do not find any development stage where learning-by-doing alone is the dominant driver of technical change. Also, high capital intensity and market constraints appear to slow down the pace of progress of emerging and evolving technologies. We find little scope for potential substitution between learning-by-doing and learning-by-research across the technologies and different stages of their development path.
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Suggested Citation

  • Tooraj Jamasb, 2006. "Technical Change Theory and Learning Curves: Patterns of Progress in Energy Technologies," Working Papers EPRG 0608, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.
    • Handle: RePEc:enp:wpaper:eprg0608
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    Cited by:

    1. Yu, Yang & Li, Hong & Che, Yuyuan & Zheng, Qiongjie, 2017. "The price evolution of wind turbines in China: A study based on the modified multi-factor learning curve," Renewable Energy, Elsevier, vol. 103(C), pages 522-536.
    2. Kahouli-Brahmi, Sondes, 2009. "Testing for the presence of some features of increasing returns to adoption factors in energy system dynamics: An analysis via the learning curve approach," Ecological Economics, Elsevier, vol. 68(4), pages 1195-1212, February.
    3. Hong, Sungjun & Chung, Yanghon & Woo, Chungwon, 2015. "Scenario analysis for estimating the learning rate of photovoltaic power generation based on learning curve theory in South Korea," Energy, Elsevier, vol. 79(C), pages 80-89.
    4. Kim, Dong Wook & Chang, Hyun Joon, 2012. "Experience curve analysis on South Korean nuclear technology and comparative analysis with South Korean renewable technologies," Energy Policy, Elsevier, vol. 40(C), pages 361-373.
    5. Santhakumar, Srinivasan & Meerman, Hans & Faaij, André, 2021. "Improving the analytical framework for quantifying technological progress in energy technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 145(C).
    6. Kahouli, Sondès, 2011. "Effects of technological learning and uranium price on nuclear cost: Preliminary insights from a multiple factors learning curve and uranium market modeling," Energy Economics, Elsevier, vol. 33(5), pages 840-852, September.
    7. Huang, Weilong & Chen, Wenying & Anandarajah, Gabrial, 2017. "The role of technology diffusion in a decarbonizing world to limit global warming to well below 2 °C: An assessment with application of Global TIMES model," Applied Energy, Elsevier, vol. 208(C), pages 291-301.
    8. Tooraj Jamasb, 2006. "Technical Change Theory and Learning Curves: Patterns of Progress in Energy Technologies," Working Papers EPRG 0608, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.
    9. Yu, C.F. & van Sark, W.G.J.H.M. & Alsema, E.A., 2011. "Unraveling the photovoltaic technology learning curve by incorporation of input price changes and scale effects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(1), pages 324-337, January.
    10. Gan, Peck Yean & Li, ZhiDong, 2015. "Quantitative study on long term global solar photovoltaic market," Renewable and Sustainable Energy Reviews, Elsevier, vol. 46(C), pages 88-99.
    11. Kahouli-Brahmi, Sondes, 2008. "Technological learning in energy-environment-economy modelling: A survey," Energy Policy, Elsevier, vol. 36(1), pages 138-162, January.

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    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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