Demand Subsidies Versus R&D: Comparing the Uncertain Impacts of Policy on a Pre-commercial Low-carbon Energy Technology
Author
Abstract
Suggested Citation
DOI: 10.5547/ISSN0195-6574-EJ-Vol30-No4-2
Download full text from publisher
Other versions of this item:
- 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.
References listed on IDEAS
- 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.
- Robert T. Clemen & Robert L. Winkler, 1999. "Combining Probability Distributions From Experts in Risk Analysis," Risk Analysis, John Wiley & Sons, vol. 19(2), pages 187-203, April.
- Mark A. Moore & Anthony E. Boardman & Aidan R. Vining & David L. Weimer & David H. Greenberg, 2004. "“Just give me a number!” Practical values for the social discount rate," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 23(4), pages 789-812.
- 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.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Lohwasser, Richard & Madlener, Reinhard, 2013.
"Relating R&D and investment policies to CCS market diffusion through two-factor learning,"
Energy Policy, Elsevier, vol. 52(C), pages 439-452.
- Lohwasser, Richard & Madlener, Reinhard, 2010. "Relating R&D and Investment Policies to CCS Market Diffusion Through Two-Factor Learning," FCN Working Papers 6/2010, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN).
- Rubin, Edward S. & Azevedo, Inês M.L. & Jaramillo, Paulina & Yeh, Sonia, 2015. "A review of learning rates for electricity supply technologies," Energy Policy, Elsevier, vol. 86(C), pages 198-218.
- 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.
- Lindman, Åsa & Söderholm, Patrik, 2012. "Wind power learning rates: A conceptual review and meta-analysis," Energy Economics, Elsevier, vol. 34(3), pages 754-761.
- Nidhi R. Santen & Mort D. Webster & David Popp & Ignacio Pérez-Arriaga, 2014. "Inter-temporal R&D and Capital Investment Portfolios for the Electricity Industry’s Low Carbon Future," NBER Working Papers 20783, National Bureau of Economic Research, Inc.
- Lin, Boqiang & He, Jiaxin, 2016. "Learning curves for harnessing biomass power: What could explain the reduction of its cost during the expansion of China?," Renewable Energy, Elsevier, vol. 99(C), pages 280-288.
- Kahouli-Brahmi, Sondes, 2008. "Technological learning in energy-environment-economy modelling: A survey," Energy Policy, Elsevier, vol. 36(1), pages 138-162, January.
- Hayward, Jennifer A. & Graham, Paul W., 2013. "A global and local endogenous experience curve model for projecting future uptake and cost of electricity generation technologies," Energy Economics, Elsevier, vol. 40(C), pages 537-548.
- Criqui, P. & Mima, S. & Menanteau, P. & Kitous, A., 2015.
"Mitigation strategies and energy technology learning: An assessment with the POLES model,"
Technological Forecasting and Social Change, Elsevier, vol. 90(PA), pages 119-136.
- Patrick Criqui & Silvana Mima & Philippe Menanteau & Alban Kitous, 2015. "Mitigation strategies and energy technology learning: an assessment with the POLES model," Post-Print halshs-00999280, HAL.
- Schauf, Magnus & Schwenen, Sebastian, 2021. "Mills of progress grind slowly? Estimating learning rates for onshore wind energy," Energy Economics, Elsevier, vol. 104(C).
- Jeon, Chanwoong & Shin, Juneseuk, 2014. "Long-term renewable energy technology valuation using system dynamics and Monte Carlo simulation: Photovoltaic technology case," Energy, Elsevier, vol. 66(C), pages 447-457.
- Zhang, Mingming & Zhou, Dequn & Zhou, Peng, 2014. "A real option model for renewable energy policy evaluation with application to solar PV power generation in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 40(C), pages 944-955.
- Hong, Sungjun & Chung, Yanghon & Woo, Chungwon, 2015. "Scenario analysis for estimating the learning rate of photovoltaic power generation based on learning curve theory in South Korea," Energy, Elsevier, vol. 79(C), pages 80-89.
- Rout, Ullash K. & Blesl, Markus & Fahl, Ulrich & Remme, Uwe & Voß, Alfred, 2009. "Uncertainty in the learning rates of energy technologies: An experiment in a global multi-regional energy system model," Energy Policy, Elsevier, vol. 37(11), pages 4927-4942, November.
- Reinhard Haas & Marlene Sayer & Amela Ajanovic & Hans Auer, 2023. "Technological learning: Lessons learned on energy technologies," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 12(2), March.
- 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.
- Kahouli, Sondès, 2011. "Effects of technological learning and uranium price on nuclear cost: Preliminary insights from a multiple factors learning curve and uranium market modeling," Energy Economics, Elsevier, vol. 33(5), pages 840-852, September.
- Nidhi R. Santen & Mort D. Webster & David Popp & Ignacio Pérez-Arriaga, 2017. "Inter-temporal R&D and capital investment portfolios for the electricity industrys low carbon future," The Energy Journal, International Association for Energy Economics, vol. 0(Number 6).
- Castrejon-Campos, Omar & Aye, Lu & Hui, Felix Kin Peng, 2022. "Effects of learning curve models on onshore wind and solar PV cost developments in the USA," Renewable and Sustainable Energy Reviews, Elsevier, vol. 160(C).
- Castrejon-Campos, Omar & Aye, Lu & Hui, Felix Kin Peng & Vaz-Serra, Paulo, 2022. "Economic and environmental impacts of public investment in clean energy RD&D," Energy Policy, Elsevier, vol. 168(C).
More about this item
Keywords
Photovoltaics (PV); R&D; subsidies; climate change; technology policy; solar energy;All these keywords.
JEL classification:
- F0 - International Economics - - General
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:enejou:v:30:y:2009:i:4:p:49-80. See general information about how to correct material in RePEc.
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 CitEc recognized a bibliographic reference but did not link an item in RePEc 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 RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.