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How well does Learning-by-doing Explain Cost Reductions in a Carbon-free Energy Technology?

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  • Nemet, Gregory F.

Abstract

The incorporation of experience curves has enhanced the treatment of technological change in models used to evaluate the cost of climate and energy policies. However, the set of activities that experience curves are assumed to capture is much broader than the set that can be characterized by learning-by-doing, the primary connection between experience curves and economic theory. How accurately do experience curves describe observed technological change? This study examines the case of photovoltaics (PV), a potentially important climate stabilization technology with robust technology dynamics. Empirical data are assembled to populate a simple engineering-based model identifying the most important factors affecting the cost of PV over the past three decades. The results indicate that learning from experience only weakly explains change in the most important cost-reducing factors' plant size, module efficiency, and the cost of silicon. They point to other explanatory variables to include in future models. Future work might also evaluate the potential for efficiency gains from policies that rely less on riding down the learning curve and more on creating incentives for firms to make investments in the types of cost-reducing activities quantified in this study.

Suggested Citation

  • Nemet, Gregory F., 2006. "How well does Learning-by-doing Explain Cost Reductions in a Carbon-free Energy Technology?," Climate Change Modelling and Policy Working Papers 12051, Fondazione Eni Enrico Mattei (FEEM).
  • Handle: RePEc:ags:feemcc:12051
    DOI: 10.22004/ag.econ.12051
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    1. Argote, L. & Epple, D., 1990. "Learning Curves In Manufacturing," GSIA Working Papers 89-90-02, Carnegie Mellon University, Tepper School of Business.
    2. Buonanno, Paolo & Carraro, Carlo & Galeotti, Marzio, 2003. "Endogenous induced technical change and the costs of Kyoto," Resource and Energy Economics, Elsevier, vol. 25(1), pages 11-34, February.
    3. Freeman, Chris & Louca, Francisco, 2002. "As Time Goes By: From the Industrial Revolutions to the Information Revolution," OUP Catalogue, Oxford University Press, number 9780199251056.
    4. Madsen, Erik Strøjer & Jensen, Camilla & Hansen, Jørgen Drud, 2002. "Scale in Technology and Learning-by-Doing in the Windmill Industry," Working Papers 02-2, University of Aarhus, Aarhus School of Business, Department of Economics.
    5. Romer, Paul M, 1990. "Endogenous Technological Change," Journal of Political Economy, University of Chicago Press, vol. 98(5), pages 71-102, October.
    6. Sabine Messner, 1997. "Endogenized technological learning in an energy systems model," Journal of Evolutionary Economics, Springer, vol. 7(3), pages 291-313.
    7. Freeman, Chris, 1994. "The Economics of Technical Change," Cambridge Journal of Economics, Oxford University Press, vol. 18(5), pages 463-514, October.
    8. Per Dannemand Andersen, 2004. "Sources of experience – theoretical considerations and empirical observations from Danish wind energy technology," International Journal of Energy Technology and Policy, Inderscience Enterprises Ltd, vol. 2(1/2), pages 33-51.
    9. van der Zwaan, Bob & Rabl, Ari, 2004. "The learning potential of photovoltaics: implications for energy policy," Energy Policy, Elsevier, vol. 32(13), pages 1545-1554, September.
    10. Irwin, Douglas A & Klenow, Peter J, 1994. "Learning-by-Doing Spillovers in the Semiconductor Industry," Journal of Political Economy, University of Chicago Press, vol. 102(6), pages 1200-1227, December.
    11. Paul S. Adler & Kim B. Clark, 1991. "Behind the Learning Curve: A Sketch of the Learning Process," Management Science, INFORMS, vol. 37(3), pages 267-281, March.
    12. Richard Duke & Daniel M. Kammen, 1999. "The Economics of Energy Market Transformation Programs," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4), pages 15-64.
    13. Ottmar Edenhofer, Kai Lessmann, Claudia Kemfert, Michael Grubb and Jonathan Kohler, 2006. "Induced Technological Change: Exploring its Implications for the Economics of Atmospheric Stabilization: Synthesis Report from the Innovation Modeling Comparison Project," The Energy Journal, International Association for Energy Economics, vol. 0(Special I), pages 57-108.
    14. Cristiano Antonelli & Dominique Foray & Bronwyn H. Hall & W. Edward Steinmueller (ed.), 2006. "New Frontiers in the Economics of Innovation and New Technology," Books, Edward Elgar Publishing, number 3286.
    15. K. J. Arrow, 1971. "The Economic Implications of Learning by Doing," Palgrave Macmillan Books, in: F. H. Hahn (ed.), Readings in the Theory of Growth, chapter 11, pages 131-149, Palgrave Macmillan.
    16. Peter Thompson, 2001. "How Much Did the Liberty Shipbuilders Learn? New Evidence for an Old Case Study," Journal of Political Economy, University of Chicago Press, vol. 109(1), pages 103-137, February.
    17. Junginger, M. & Faaij, A. & Turkenburg, W. C., 2005. "Global experience curves for wind farms," Energy Policy, Elsevier, vol. 33(2), pages 133-150, January.
    18. Zvi Griliches, 1998. "R&D and Productivity: The Econometric Evidence," NBER Books, National Bureau of Economic Research, Inc, number gril98-1, September.
    19. 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.
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    1. 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.
    2. 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.
    3. Avril, S. & Mansilla, C. & Busson, M. & Lemaire, T., 2012. "Photovoltaic energy policy: Financial estimation and performance comparison of the public support in five representative countries," Energy Policy, Elsevier, vol. 51(C), pages 244-258.

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    More about this item

    Keywords

    Environmental Economics and Policy;

    JEL classification:

    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives
    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources
    • Q48 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Government Policy
    • Q55 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environmental Economics: Technological Innovation

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