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

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Author Info
Jamasb, T.

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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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Publisher Info
Paper provided by Faculty of Economics, University of Cambridge in its series Cambridge Working Papers in Economics with number 0625.

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Length: 24
Date of creation: Mar 2006
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Handle: RePEc:cam:camdae:0625

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Related research
Keywords: Energy technology; electricity; technical change; learning curves;

Find related papers by JEL classification:
O3 - Economic Development, Technological Change, and Growth - - Technological Change
Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy

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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.:
  1. Argote, L. & Epple, D., 1990. "Learning Curves In Manufacturing," GSIA Working Papers 89-90-02, Carnegie Mellon University, Tepper School of Business.
  2. Ibenholt, Karin, 2002. "Explaining learning curves for wind power," Energy Policy, Elsevier, vol. 30(13), pages 1181-1189, October. [Downloadable!] (restricted)
  3. Miketa, Asami & Schrattenholzer, Leo, 2004. "Experiments with a methodology to model the role of R&D expenditures in energy technology learning processes; first results," Energy Policy, Elsevier, vol. 32(15), pages 1679-1692, October. [Downloadable!] (restricted)
  4. Spence, Michael, 1984. "Cost Reduction, Competition, and Industry Performance," Econometrica, Econometric Society, vol. 52(1), pages 101-21, January. [Downloadable!] (restricted)
  5. McDonald, Alan & Schrattenholzer, Leo, 2001. "Learning rates for energy technologies," Energy Policy, Elsevier, vol. 29(4), pages 255-261, March. [Downloadable!] (restricted)
  6. Papineau, Maya, 2006. "An economic perspective on experience curves and dynamic economies in renewable energy technologies," Energy Policy, Elsevier, vol. 34(4), pages 422-432, March. [Downloadable!] (restricted)
  7. 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. [Downloadable!] (restricted)
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