A review of uncertainties in technology experience curves
The use of log-linear experience curves (or learning curves) relating reductions in the unit cost of technologies to their cumulative production or installed capacity has become a common method of representing endogenous technical change in energy-economic models used for policy analysis. Yet, there are significant uncertainties in such formulations whose impact on key model results have been insufficiently examined or considered. This paper reviews the major types of uncertainty in log-linear experience curves and their effect on projected rates of cost reduction. Uncertainties are found not only in the learning rate parameter of a log-linear model, but also in the functional form that determines the shape of an experience curve. Evidence for alternative forms such as an S-shaped curve is reviewed along with case studies that demonstrate the uncertainties associated with cost increases during early commercialization of a technology—a phenomena that is widely recognized but rarely quantified or incorporated in learning models. Additional factors discussed include the effects of learning discontinuities, institutional forgetting, and the influence of social, economic and political factors. We then review other models of causality, which aim to improve modelers’ ability to explain and predict the influence of other underlying processes that contribute to technology cost reductions in addition to learning. Ignoring other types of underlying mechanisms can create a false sense of precision and overestimate the true contribution of learning. Currently, however, uncertainties in such multi-factor models remain large due to the difficulties of estimating key parameters (such as private-sector R&D investments) and extending models of a specific technology to a broader suite of technologies and cost projections. Pending the development and validation of more robust models of technological change, we suggest ways to significantly improve the characterization and reporting of current learning model uncertainties and their impacts on the results of energy-economic models to help reduce the potential for drawing inappropriate or erroneous policy conclusions.
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- Ibenholt, Karin, 2002. "Explaining learning curves for wind power," Energy Policy, Elsevier, vol. 30(13), pages 1181-1189, October.
- McDonald, Alan & Schrattenholzer, Leo, 2001. "Learning rates for energy technologies," Energy Policy, Elsevier, vol. 29(4), pages 255-261, March.
- Colpier, Ulrika Claeson & Cornland, Deborah, 2002. "The economics of the combined cycle gas turbine--an experience curve analysis," Energy Policy, Elsevier, vol. 30(4), pages 309-316, March.
- Gavin Sinclair & Steven Klepper & Wesley Cohen, 2000. "What's Experience Got to Do With It? Sources of Cost Reduction in a Large Specialty Chemicals Producer," Management Science, INFORMS, vol. 46(1), pages 28-45, January.
- Rubin, Edward S. & Yeh, Sonia & Antes, Matt & Berkenpas, Michael & Davison, John, 2007. "Use of experience curves to estimate the future cost of power plants with CO2 capture," Institute of Transportation Studies, Working Paper Series qt46x6h0n0, Institute of Transportation Studies, UC Davis.
- Rao, Anand B. & Rubin, Edward S. & Keith, David W. & Granger Morgan, M., 2006. "Evaluation of potential cost reductions from improved amine-based CO2 capture systems," Energy Policy, Elsevier, vol. 34(18), pages 3765-3772, December.
- van der Zwaan, B. C. C. & Gerlagh, R. & G. & Klaassen & Schrattenholzer, L., 2002. "Endogenous technological change in climate change modelling," Energy Economics, Elsevier, vol. 24(1), pages 1-19, January.
- Patrik Söderholm & Ger Klaassen, 2007. "Wind Power in Europe: A Simultaneous Innovation–Diffusion Model," Environmental & Resource Economics, European Association of Environmental and Resource Economists, vol. 36(2), pages 163-190, February.
- 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.
- Dutton, John M. & Thomas, Annie & Butler, John E., 1984. "The History of Progress Functions as a Managerial Technology," Business History Review, Cambridge University Press, vol. 58(02), pages 204-233, June.
- Yeh, Sonia & Rubin, Edward S., 2007.
"A centurial history of technological change and learning curves for pulverized coal-fired utility boilers,"
Elsevier, vol. 32(10), pages 1996-2005.
- Yeh, Sonia & Rubin, Edward S., 2007. "A centurial history of technological change and learning curves or pulverized coal-fired utility boilers," Institute of Transportation Studies, Working Paper Series qt96z5s545, Institute of Transportation Studies, UC Davis.
- Yeh, Sonia & Rubin, Edward, 2007. "A centurial history of technological change and learning curves or pulverized coal-fired utility boilers," Institute of Transportation Studies, Working Paper Series qt4xn4w7rn, Institute of Transportation Studies, UC Davis.
- Yeh, Sonia & Rubin, Edward S, 2007. "A centurial history of technological change and learning curves or pulverized coal-fired utility boilers," Institute of Transportation Studies, Working Paper Series qt3zz2w2wr, Institute of Transportation Studies, UC Davis.
- Yeh, Sonia & Rubin, Edward S., 2007. "A centurial history of technological change and learning curves or pulverized coal-fired utility boilers," Institute of Transportation Studies, Working Paper Series qt1f25b3xq, Institute of Transportation Studies, UC Davis.
- Neij, L, 1999. "Cost dynamics of wind power," Energy, Elsevier, vol. 24(5), pages 375-389.
- 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 S51-67, July.
- Riahi, Keywan & Rubin, Edward S. & Taylor, Margaret R. & Schrattenholzer, Leo & Hounshell, David, 2004. "Technological learning for carbon capture and sequestration technologies," Energy Economics, Elsevier, vol. 26(4), pages 539-564, July.
- Nemet, Gregory F., 2006. "Beyond the learning curve: factors influencing cost reductions in photovoltaics," Energy Policy, Elsevier, vol. 34(17), pages 3218-3232, November.
- James G. Hewlett, 1996. "Economic and Regulatory Factors Affecting the Maintenance of Nucleaer Power Plants," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4), pages 1-31.
- Rebecca Achee Thornton & Peter Thompson, 2001. "Learning from Experience and Learning from Others: An Exploration of Learning and Spillovers in Wartime Shipbuilding," American Economic Review, American Economic Association, vol. 91(5), pages 1350-1368, December.
- Tooraj Jamasb, 2007. "Technical Change Theory and Learning Curves: Patterns of Progress in Electricity Generation Technologies," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 51-72.
- Gillingham, Kenneth & Newell, Richard G. & Pizer, William A., 2008.
"Modeling endogenous technological change for climate policy analysis,"
Elsevier, vol. 30(6), pages 2734-2753, November.
- Gillingham, Kenneth T. & Newell, Richard G. & Pizer, William A., 2007. "Modeling Endogenous Technological Change for Climate Policy Analysis," Discussion Papers dp-07-14, Resources For the Future.
- Neij, Lena, 1997. "Use of experience curves to analyse the prospects for diffusion and adoption of renewable energy technology," Energy Policy, Elsevier, vol. 25(13), pages 1099-1107, November.
- William D. Nordhaus, 2009.
"The Perils of the Learning Model For Modeling Endogenous Technological Change,"
Cowles Foundation Discussion Papers
1685, Cowles Foundation for Research in Economics, Yale University.
- William D. Nordhaus, 2009. "The Perils of the Learning Model For Modeling Endogenous Technological Change," NBER Working Papers 14638, National Bureau of Economic Research, Inc.
- Cantor, Robin & Hewlett, James, 1988. "The economics of nuclear power : Further evidence on learning, economies of scale, and regulatory effects," Resources and Energy, Elsevier, vol. 10(4), pages 315-335, December.
- Söderholm, Patrik & Sundqvist, Thomas, 2007. "Empirical challenges in the use of learning curves for assessing the economic prospects of renewable energy technologies," Renewable Energy, Elsevier, vol. 32(15), pages 2559-2578.
- Junginger, Martin & de Visser, Erika & Hjort-Gregersen, Kurt & Koornneef, Joris & Raven, Rob & Faaij, Andre & Turkenburg, Wim, 2006. "Technological learning in bioenergy systems," Energy Policy, Elsevier, vol. 34(18), pages 4024-4041, December.
- Sturm, Roland, 1993. "Nuclear power in Eastern Europe : Learning or forgetting curves?," Energy Economics, Elsevier, vol. 15(3), pages 183-189, July.
- Yeh, Sonia & Rubin, Edward S. & Taylor, Margaret R., 2007. "Technology Innovations and Experience Curves for Nitrogen Oxides Control Technologies," Institute of Transportation Studies, Working Paper Series qt5nv9p7zh, Institute of Transportation Studies, UC Davis.
- Steven Klepper & Kenneth L. Simons, 2000. "The Making of an Oligopoly: Firm Survival and Technological Change in the Evolution of the U.S. Tire Industry," Journal of Political Economy, University of Chicago Press, vol. 108(4), pages 728-760, August.
- Fischer, Carolyn & Newell, Richard, 2004.
"Environmental and Technology Policies for Climate Mitigation,"
dp-04-05, Resources For the Future.
- Fischer, Carolyn & Newell, Richard G., 2008. "Environmental and technology policies for climate mitigation," Journal of Environmental Economics and Management, Elsevier, vol. 55(2), pages 142-162, March.
- Messner, S. & Golodnikov, A. & Gritsevskii, A., 1996. "A stochastic version of the dynamic linear programming model MESSAGE III," Energy, Elsevier, vol. 21(9), pages 775-784.
- Ferioli, F. & Schoots, K. & van der Zwaan, B.C.C., 2009. "Use and limitations of learning curves for energy technology policy: A component-learning hypothesis," Energy Policy, Elsevier, vol. 37(7), pages 2525-2535, July.
- Ostwald, Phillip F. & Reisdorf, John B., 1979. "Measurement of technology progress and capital cost for nuclear, coal-fired, and gas-fired power plants using the learning curve," Engineering and Process Economics, Elsevier, vol. 4(4), pages 435-454, December.
- Olivier Bahn, Socrates Kypreos, 2003. "Incorporating different endogenous learning formulations in MERGE," International Journal of Global Energy Issues, Inderscience Enterprises Ltd, vol. 19(4), pages 333-358.
- Klaassen, Ger & Miketa, Asami & Larsen, Katarina & Sundqvist, Thomas, 2005. "The impact of R&D on innovation for wind energy in Denmark, Germany and the United Kingdom," Ecological Economics, Elsevier, vol. 54(2-3), pages 227-240, August.
- Argote, L. & Epple, D., 1990. "Learning Curves In Manufacturing," GSIA Working Papers 89-90-02, Carnegie Mellon University, Tepper School of Business.
- Ad Seebregts & Tom Kram & Gerrit Jan Schaeffer & Alexandra Bos, 2000. "Endogenous learning and technology clustering: analysis with MARKAL model of the Western European energy system," International Journal of Global Energy Issues, Inderscience Enterprises Ltd, vol. 14(1/2/3/4), pages 289-319.
- Alan Manne & Richard Richels, 1992. "Buying Greenhouse Insurance: The Economic Costs of CO2 Emission Limits," MIT Press Books, The MIT Press, edition 1, volume 1, number 026213280x, December.
- Clarke, Leon & Weyant, John & Birky, Alicia, 2006. "On the sources of technological change: Assessing the evidence," Energy Economics, Elsevier, vol. 28(5-6), pages 579-595, November.
- Hettinga, W.G. & Junginger, H.M. & Dekker, S.C. & Hoogwijk, M. & McAloon, A.J. & Hicks, K.B., 2009. "Understanding the reductions in US corn ethanol production costs: An experience curve approach," Energy Policy, Elsevier, vol. 37(1), pages 190-203, January.
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