IDEAS home Printed from https://ideas.repec.org/a/eee/eneeco/v30y2008i6p2899-2911.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0140-9883(08)00054-6
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. John Foster & Liam Wagner & Phil Wild & Junhua Zhao & Lucas Skoofa & Craig Froome, 2011. "Market and Economic Modelling of the Intelligent Grid: End of Year Report 2009," Energy Economics and Management Group Working Papers 09, School of Economics, University of Queensland, Australia.
    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.
    4. Desroches, Louis-Benoit & Garbesi, Karina & Kantner, Colleen & Van Buskirk, Robert & Yang, Hung-Chia, 2013. "Incorporating experience curves in appliance standards analysis," Energy Policy, Elsevier, vol. 52(C), pages 402-416.
    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. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    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.

    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.
    1. Anelí Bongers, 2017. "Learning and forgetting in the jet fighter aircraft industry," PLOS ONE, Public Library of Science, vol. 12(9), pages 1-19, September.
    2. Samadi, Sascha, 2018. "The experience curve theory and its application in the field of electricity generation technologies – A literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 2346-2364.
    3. Yeh, Sonia & Rubin, Edward S., 2012. "A review of uncertainties in technology experience curves," Energy Economics, Elsevier, vol. 34(3), pages 762-771.
    4. Tombak, Mihkel M., 2006. "Strategic asymmetry," Journal of Economic Behavior & Organization, Elsevier, vol. 61(3), pages 339-350, November.
    5. Lehmann, Paul & Gawel, Erik, 2013. "Why should support schemes for renewable electricity complement the EU emissions trading scheme?," Energy Policy, Elsevier, vol. 52(C), pages 597-607.
    6. 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.
    7. 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.
    8. Iyer, Gokul C. & Clarke, Leon E. & Edmonds, James A. & Hultman, Nathan E. & McJeon, Haewon C., 2015. "Long-term payoffs of near-term low-carbon deployment policies," Energy Policy, Elsevier, vol. 86(C), pages 493-505.
    9. Lafond, François & Bailey, Aimee Gotway & Bakker, Jan David & Rebois, Dylan & Zadourian, Rubina & McSharry, Patrick & Farmer, J. Doyne, 2018. "How well do experience curves predict technological progress? A method for making distributional forecasts," Technological Forecasting and Social Change, Elsevier, vol. 128(C), pages 104-117.
    10. Stavins, Robert & Jaffe, Adam & Newell, Richard, 2000. "Technological Change and the Environment," Working Paper Series rwp00-002, Harvard University, John F. Kennedy School of Government.
    11. 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.
    12. Saman Majd & Robert S. Pindyck, 1989. "The Learning Curve and Optimal Production under Uncertainty," RAND Journal of Economics, The RAND Corporation, vol. 20(3), pages 331-343, Autumn.
    13. Lehmann, Paul, 2009. "Climate policies with pollution externalities and learning spillovers," UFZ Discussion Papers 10/2009, Helmholtz Centre for Environmental Research (UFZ), Division of Social Sciences (ÖKUS).
    14. Della Seta, Marco & Gryglewicz, Sebastian & Kort, Peter M., 2012. "Optimal investment in learning-curve technologies," Journal of Economic Dynamics and Control, Elsevier, vol. 36(10), pages 1462-1476.
    15. Liu, An-Hsiang & Siebert, Ralph B., 2022. "The competitive effects of declining entry costs over time: Evidence from the static random access memory market," International Journal of Industrial Organization, Elsevier, vol. 80(C).
    16. Ron Jarmin, 1996. "Learning by Doing and Plant Characteristics," Working Papers 96-5, Center for Economic Studies, U.S. Census Bureau.
    17. Ron Jarmin, 1993. "Asymmetric Learning Spillovers," Working Papers 93-7, Center for Economic Studies, U.S. Census Bureau.
    18. Levin, Mark (Левин, Марк) & Matrosova, K. (Матросова, К.), 2016. "Research, Modeling and Process Management Dissemination of Innovations in Socio-Economic Systems [Исследование, Моделирование И Управление Процессами Распространения Инноваций В Социально-Экономиче," Working Papers 1443, Russian Presidential Academy of National Economy and Public Administration.
    19. 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.
    20. Yuichiro Kamada & Fuhito Kojima, 2013. "Voter Preferences, Polarization, and Electoral Policies," Discussion Papers 12-021, Stanford Institute for Economic Policy Research.

    Corrections

    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:eee:eneeco:v:30:y:2008:i:6:p:2899-2911. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eneco .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.