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Explaining experience curves for new energy technologies: A case study of liquefied natural gas

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  • Greaker, Mads
  • Lund Sagen, Eirik

Abstract

Many new energy technologies seem to experience a fall in unit price as they mature. In this paper we study the unit price of liquefying natural gas in order to make it transportable by ship to gas power installations all over the world. Our point of departure is the experience curve approach, however unlike many other studies of new energy technologies, we also seek to account for autonomous technological change, scale effects and the effects of upstream competition among technology suppliers. To our surprise we find that upstream competition is by far the most important factor contributing to the fall in unit price. With respect to the natural gas business, this may have implications for the future development in prices as the effect of increased upstream competition is temporary and likely to weaken a lot sooner than effects from learning and technological change. Another more general policy implication, is that while promoting new energy technologies, governments must not forget to pay attention to competition policy.

Suggested Citation

  • Greaker, Mads & Lund Sagen, Eirik, 2008. "Explaining experience curves for new energy technologies: A case study of liquefied natural gas," Energy Economics, Elsevier, vol. 30(6), pages 2899-2911, November.
  • Handle: RePEc:eee:eneeco:v:30:y:2008:i:6:p:2899-2911
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    1. Ibenholt, Karin, 2002. "Explaining learning curves for wind power," Energy Policy, Elsevier, vol. 30(13), pages 1181-1189, October.
    2. A. M. Spence, 1981. "The Learning Curve and Competition," Bell Journal of Economics, The RAND Corporation, vol. 12(1), pages 49-70, Spring.
    3. Paul Joskow & Nancy L. Rose, 1985. "The Effects of Technological Change, Experience, and Environmental Regulation on the Construction Cost of Coal-Burning Generating Units," RAND Journal of Economics, The RAND Corporation, vol. 16(1), pages 1-17, Spring.
    4. 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.
    5. Martin B. Zimmerman, 1982. "Learning Effects and the Commercialization of New Energy Technologies: The Case of Nuclear Power," Bell Journal of Economics, The RAND Corporation, vol. 13(2), pages 297-310, Autumn.
    6. 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.
    7. 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.
    8. Drew Fudenberg & Jean Tirole, 1983. "Learning-by-Doing and Market Performance," Bell Journal of Economics, The RAND Corporation, vol. 14(2), pages 522-530, Autumn.
    9. Isoard, Stephane & Soria, Antonio, 2001. "Technical change dynamics: evidence from the emerging renewable energy technologies," Energy Economics, Elsevier, vol. 23(6), pages 619-636, November.
    10. 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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    2. Chyong, C-K., 2019. "Challenges to the Future of European Single Market in Natural Gas," Cambridge Working Papers in Economics 1918, Faculty of Economics, University of Cambridge.
    3. Rai, Varun & Victor, David G. & Thurber, Mark C., 2010. "Carbon capture and storage at scale: Lessons from the growth of analogous energy technologies," Energy Policy, Elsevier, vol. 38(8), pages 4089-4098, August.
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    5. Chi Kong Chyong, 2019. "European Natural Gas Markets: Taking Stock and Looking Forward," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 55(1), pages 89-109, August.
    6. Li, Sheng & Zhang, Xiaosong & Gao, Lin & Jin, Hongguang, 2012. "Learning rates and future cost curves for fossil fuel energy systems with CO2 capture: Methodology and case studies," Applied Energy, Elsevier, vol. 93(C), pages 348-356.
    7. Li, Sheng & Gao, Lin & Zhang, Xiaosong & Lin, Hu & Jin, Hongguang, 2012. "Evaluation of cost reduction potential for a coal based polygeneration system with CO2 capture," Energy, Elsevier, vol. 45(1), pages 101-106.
    8. Chi-Kong Chyong, 2015. "Markets and long-term contracts: The case of Russian gas supplies to Europe," Cambridge Working Papers in Economics 1542, Faculty of Economics, University of Cambridge.
    9. Massol, Olivier & Tchung-Ming, Stéphane, 2010. "Cooperation among liquefied natural gas suppliers: Is rationalization the sole objective?," Energy Economics, Elsevier, vol. 32(4), pages 933-947, July.
    10. Chi-Kong Chyong & Roman Kazmin, 2016. "The economics of global LNG trade: the case of Atlantic and Pacific inter-basin arbitrage in 2010-2014," Cambridge Working Papers in Economics 1604, Faculty of Economics, University of Cambridge.
    11. Fukui, Rokuhei & Greenfield, Carl & Pogue, Katie & van der Zwaan, Bob, 2017. "Experience curve for natural gas production by hydraulic fracturing," Energy Policy, Elsevier, vol. 105(C), pages 263-268.
    12. Svensson, Elin & Berntsson, Thore, 2011. "Planning future investments in emerging energy technologies for pulp mills considering different scenarios for their investment cost development," Energy, Elsevier, vol. 36(11), pages 6508-6519.

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