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Learning by Doing with Constrained Growth Rates: An Application to Energy Technology Policy

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  • Karsten Neuhoff

Abstract

Learning by doing methodology attributes cost reductions of a technology to cumulative investment and experience. This paper argues that in addition market growth rates must also be considered. Historically growth rates have been limited in most sectors, thus allowing for feedback in the learning process. When market growth is below the ‘optimal’ rate, the marginal value of additional investment could be a multiple of the direct learning benefit. Analytic and numeric models quantify this impact - emphasizing the need for tailored technology policy in addition to carbon pricing. Implications for the modeling of endogenous technological change are discussed. Isoard, S. and A. Soria (1997).“Learning curves and returns to scale dynamics: Evidence from the emerging renewable energy technologies.†IPTS Working Paper Series 97/05.

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  • Karsten Neuhoff, 2008. "Learning by Doing with Constrained Growth Rates: An Application to Energy Technology Policy," The Energy Journal, , vol. 29(2_suppl), pages 165-183, December.
    • Handle: RePEc:sae:enejou:v:29:y:2008:i:2_suppl:p:165-183
    DOI: 10.5547/ISSN0195-6574-EJ-Vol29-NoSI2-9
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    1. Jonathan Kohler, Michael Grubb, David Popp and Ottmar Edenhofer, 2006. "The Transition to Endogenous Technical Change in Climate-Economy Models: A Technical Overview to the Innovation Modeling Comparison Project," The Energy Journal, International Association for Energy Economics, vol. 0(Special I), pages 17-56.
    2. Karsten Neuhoff, 2005. "Large-Scale Deployment of Renewables for Electricity Generation," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 21(1), pages 88-110, Spring.
    3. C. Harmon, 2000. "Experience Curves of Photovoltaic Technology," Working Papers ir00014, International Institute for Applied Systems Analysis.
    4. Bass, Frank M, 1980. "The Relationship between Diffusion Rates, Experience Curves, and Demand Elasticities for Consumer Durable Technological Innovations," The Journal of Business, University of Chicago Press, vol. 53(3), pages 51-67, July.
    5. Nikolaos Kouvaritakis & Antonio Soria & Stephane Isoard, 2000. "Modelling energy technology dynamics: methodology for adaptive expectations models with learning by doing and learning by searching," International Journal of Global Energy Issues, Inderscience Enterprises Ltd, vol. 14(1/2/3/4), pages 104-115.
    6. Marvin B. Lieberman, 1984. "The Learning Curve and Pricing in the Chemical Processing Industries," RAND Journal of Economics, The RAND Corporation, vol. 15(2), pages 213-228, Summer.
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