Interim monitoring of cost dynamics for publicly supported energy technologies
AbstractThe combination of substantial public funding of nascent energy technologies and recent increases in the costs of those that have been most heavily supported has raised questions about whether policy makers should sustain, alter, enhance, or terminate such programs. This paper uses experience curves for photovoltaics (PV) and wind to (1) estimate ranges of costs for these public programs and (2) introduce new ways of evaluating recent cost dynamics. For both technology cases, the estimated costs of the subsidies required to reach targets are sensitive to the choice of time period on which cost projections are based. The variation in the discounted social cost of subsidies exceeds an order of magnitude. Vigilance is required to avoid the very expensive outcomes contained within these distributions of social costs. Two measures of the significance of recent deviations are introduced. Both indicate that wind costs are within the expected range of prior forecasts but that PV costs are not. The magnitude of the public funds involved in these programs heightens the need for better analytical tools with which to monitor and evaluate cost dynamics.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Bibliographic InfoArticle provided by Elsevier in its journal Energy Policy.
Volume (Year): 37 (2009)
Issue (Month): 3 (March)
Contact details of provider:
Web page: http://www.elsevier.com/locate/enpol
Technology policy Experience curves Learning curves;
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.:
- Sabine Messner, 1997. "Endogenized technological learning in an energy systems model," Journal of Evolutionary Economics, Springer, vol. 7(3), pages 291-313.
- Neij, Lena, 2008. "Cost development of future technologies for power generation--A study based on experience curves and complementary bottom-up assessments," Energy Policy, Elsevier, vol. 36(6), pages 2200-2211, June.
- Nemet, Gregory F., 2006. "Beyond the learning curve: factors influencing cost reductions in photovoltaics," Energy Policy, Elsevier, vol. 34(17), pages 3218-3232, November.
- 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.
- 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.
- 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.
- Kahouli-Brahmi, Sondes, 2008. "Technological learning in energy-environment-economy modelling: A survey," Energy Policy, Elsevier, vol. 36(1), pages 138-162, January.
- Neij, Lena & Astrand, Kerstin, 2006. "Outcome indicators for the evaluation of energy policy instruments and technical change," Energy Policy, Elsevier, vol. 34(17), pages 2662-2676, November.
- Alberth, Stephan & Hope, Chris, 2007. "Climate modelling with endogenous technical change: Stochastic learning and optimal greenhouse gas abatement in the PAGE2002 model," Energy Policy, Elsevier, vol. 35(3), pages 1795-1807, March.
- Albrecht, Johan, 2007. "The future role of photovoltaics: A learning curve versus portfolio perspective," Energy Policy, Elsevier, vol. 35(4), pages 2296-2304, April.
- 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.
- Junginger, M. & Faaij, A. & Turkenburg, W. C., 2005. "Global experience curves for wind farms," Energy Policy, Elsevier, vol. 33(2), pages 133-150, January.
- Freeman, Chris & Louca, Francisco, 2001. "As Time Goes By: From the Industrial Revolutions to the Information Revolution," OUP Catalogue, Oxford University Press, number 9780199241071.
- Koomey, Jonathan & Hultman, Nathan E., 2007. "A reactor-level analysis of busbar costs for US nuclear plants, 1970-2005," Energy Policy, Elsevier, vol. 35(11), pages 5630-5642, November.
- Sue Wing, Ian, 2006. "Representing induced technological change in models for climate policy analysis," Energy Economics, Elsevier, vol. 28(5-6), pages 539-562, November.
- Geels, Frank W., 2002. "Technological transitions as evolutionary reconfiguration processes: a multi-level perspective and a case-study," Research Policy, Elsevier, vol. 31(8-9), pages 1257-1274, December.
- Arthur, W. Brian, 2006. "Out-of-Equilibrium Economics and Agent-Based Modeling," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 32, pages 1551-1564 Elsevier.
- Arthur van Benthem & Kenneth Gillingham & James Sweeney, 2008. "Learning-by-Doing and the Optimal Solar Policy in California," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 131-152.
- Shum, Kwok L. & Watanabe, Chihiro, 2007. "Photovoltaic deployment strategy in Japan and the USA--an institutional appraisal," Energy Policy, Elsevier, vol. 35(2), pages 1186-1195, February.
- McDonald, Alan & Schrattenholzer, Leo, 2001. "Learning rates for energy technologies," Energy Policy, Elsevier, vol. 29(4), pages 255-261, March.
- Gritsevskyi, Andrii & Nakicenovi, Nebojsa, 2000. "Modeling uncertainty of induced technological change," Energy Policy, Elsevier, vol. 28(13), pages 907-921, November.
- Gregory F. Nemet & Erin Baker, 2009. "Demand Subsidies Versus R&D: Comparing the Uncertain Impacts of Policy on a Pre-commercial Low-carbon Energy Technology," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4), pages 49-80.
- Uyterlinde, Martine A. & Junginger, Martin & de Vries, Hage J. & Faaij, Andre P.C. & Turkenburg, Wim C., 2007. "Implications of technological learning on the prospects for renewable energy technologies in Europe," Energy Policy, Elsevier, vol. 35(8), pages 4072-4087, August.
- Goldemberg, Jose & Coelho, Suani Teixeira & Lucon, Oswaldo, 2004. "How adequate policies can push renewables," Energy Policy, Elsevier, vol. 32(9), pages 1141-1146, June.
- Nemet, Gregory F., 2010. "Robust incentives and the design of a climate change governance regime," Energy Policy, Elsevier, vol. 38(11), pages 7216-7225, November.
- Rüther, Ricardo & Zilles, Roberto, 2011. "Making the case for grid-connected photovoltaics in Brazil," Energy Policy, Elsevier, vol. 39(3), pages 1027-1030, March.
- Schmid, Eva & Pahle, Michael & Knopf, Brigitte, 2013. "Renewable electricity generation in Germany: A meta-analysis of mitigation scenarios," Energy Policy, Elsevier, vol. 61(C), pages 1151-1163.
- Dinica, Valentina, 2011. "Renewable electricity production costs--A framework to assist policy-makers' decisions on price support," Energy Policy, Elsevier, vol. 39(7), pages 4153-4167, July.
- Qiu, Yueming & Anadon, Laura D., 2012. "The price of wind power in China during its expansion: Technology adoption, learning-by-doing, economies of scale, and manufacturing localization," Energy Economics, Elsevier, vol. 34(3), pages 772-785.
- Rigter, Jasper & Vidican, Georgeta, 2010. "Cost and optimal feed-in tariff for small scale photovoltaic systems in China," Energy Policy, Elsevier, vol. 38(11), pages 6989-7000, November.
- Edenhofer, Ottmar & Hirth, Lion & Knopf, Brigitte & Pahle, Michael & Schlömer, Steffen & Schmid, Eva & Ueckerdt, Falko, 2013. "On the economics of renewable energy sources," Energy Economics, Elsevier, vol. 40(S1), pages S12-S23.
- Arnaud De La Tour & Matthieu Glachant, 2013. "How do solar photovoltaic feed-in tariffs interact with solar panel and silicon prices? An empirical study," Working Papers hal-00809449, HAL.
- Lindman, Åsa & Söderholm, Patrik, 2012. "Wind power learning rates: A conceptual review and meta-analysis," Energy Economics, Elsevier, vol. 34(3), pages 754-761.
- Partridge, Ian, 2013. "Renewable electricity generation in India—A learning rate analysis," Energy Policy, Elsevier, vol. 60(C), pages 906-915.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Zhang, Lei).
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.