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The Learning Process and Technological Change in Wind Power: Evidence from China's CDM Wind Projects

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  • Tian Tang
  • David Popp

Abstract

The Clean Development Mechanism (CDM) is a project-based carbon trade mechanism that subsidizes the users of climate-friendly technologies and encourages technology transfer. The CDM has provided financial support for a large share of Chinese wind projects since 2002. Using pooled cross-sectional data of 486 registered CDM wind projects in China from 2002 to 2009, we examine the determinants of technological change in wind power from a learning perspective. We estimate the effects of different channels of learning--learning through R&D in wind turbine manufacturing, learning from previous experience of installation, and learning through the network interaction between project developer and turbine manufacturer--on technological change, measured as reductions in projected costs or as increased capacity factor across CDM wind projects. While we find that a manufacturer's R&D and previous installation experience matter, interactions between wind turbine manufacturers and wind project developer lead to the largest cost reductions. Whereas existing literature suggests that wind power firms can learn from the experience of other wind farm developers, our results indicate that wind power firms mainly learn from their own experience and that knowledge spillovers mostly occur within certain partnerships between wind project developer and foreign turbine manufacturers in China's wind power industry.

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  • Tian Tang & David Popp, 2014. "The Learning Process and Technological Change in Wind Power: Evidence from China's CDM Wind Projects," NBER Working Papers 19921, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:19921
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    References listed on IDEAS

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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. Dechezleprêtre, Antoine & Glachant, Matthieu & Ménière, Yann, 2008. "The Clean Development Mechanism and the international diffusion of technologies: An empirical study," Energy Policy, Elsevier, vol. 36(4), pages 1273-1283, April.
    3. Patrik Söderholm & Ger Klaassen, 2007. "Wind Power in Europe: A Simultaneous Innovation–Diffusion Model," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 36(2), pages 163-190, February.
    4. Jaffe, Adam B. & Newell, Richard G. & Stavins, Robert N., 2005. "A tale of two market failures: Technology and environmental policy," Ecological Economics, Elsevier, vol. 54(2-3), pages 164-174, August.
    5. 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.
    6. Xiliang Zhang & Shiyan Chang & Molin Huo & Ruoshui Wang, 2009. "China's wind industry: policy lessons for domestic government interventions and international support," Climate Policy, Taylor & Francis Journals, vol. 9(5), pages 553-564, September.
    7. Yang, Ming & Nguyen, François & De T'Serclaes, Philippine & Buchner, Barbara, 2010. "Wind farm investment risks under uncertain CDM benefit in China," Energy Policy, Elsevier, vol. 38(3), pages 1436-1447, March.
    8. 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.
    9. Seres, Stephen & Haites, Erik & Murphy, Kevin, 2009. "Analysis of technology transfer in CDM projects: An update," Energy Policy, Elsevier, vol. 37(11), pages 4919-4926, November.
    10. Schneider, Malte & Holzer, Andreas & Hoffmann, Volker H., 2008. "Understanding the CDM's contribution to technology transfer," Energy Policy, Elsevier, vol. 36(8), pages 2920-2928, August.
    11. Lewis, Joanna I., 2010. "The evolving role of carbon finance in promoting renewable energy development in China," Energy Policy, Elsevier, vol. 38(6), pages 2875-2886, June.
    12. Junginger, M. & Faaij, A. & Turkenburg, W. C., 2005. "Global experience curves for wind farms," Energy Policy, Elsevier, vol. 33(2), pages 133-150, January.
    13. Andrew C. Inkpen & Steven C. Currall, 2004. "The Coevolution of Trust, Control, and Learning in Joint Ventures," Organization Science, INFORMS, vol. 15(5), pages 586-599, October.
    14. Wang, Bo, 2010. "Can CDM bring technology transfer to China?--An empirical study of technology transfer in China's CDM projects," Energy Policy, Elsevier, vol. 38(5), pages 2572-2585, May.
    15. Wang, Zhongying & Qin, Haiyan & Lewis, Joanna I., 2012. "China's wind power industry: Policy support, technological achievements, and emerging challenges," Energy Policy, Elsevier, vol. 51(C), pages 80-88.
    16. 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.
    17. Berry, David, 2009. "Innovation and the price of wind energy in the US," Energy Policy, Elsevier, vol. 37(11), pages 4493-4499, November.
    18. Grubler, Arnulf & Nakicenovic, Nebojsa & Victor, David G., 1999. "Dynamics of energy technologies and global change," Energy Policy, Elsevier, vol. 27(5), pages 247-280, May.
    19. Dechezleprêtre, Antoine & Glachant, Matthieu & Ménière, Yann, 2009. "Technology transfer by CDM projects: A comparison of Brazil, China, India and Mexico," Energy Policy, Elsevier, vol. 37(2), pages 703-711, February.
    20. Kahouli-Brahmi, Sondes, 2008. "Technological learning in energy-environment-economy modelling: A survey," Energy Policy, Elsevier, vol. 36(1), pages 138-162, January.
    21. Popp, David, 2004. "ENTICE: endogenous technological change in the DICE model of global warming," Journal of Environmental Economics and Management, Elsevier, vol. 48(1), pages 742-768, July.
    22. Huang, Cui & Su, Jun & Zhao, Xiaoyuan & Sui, Jigang & Ru, Peng & Zhang, Hanwei & Wang, Xin, 2012. "Government funded renewable energy innovation in China," Energy Policy, Elsevier, vol. 51(C), pages 121-127.
    23. Malte Schneider & Tobias S. Schmidt & Volker H. Hoffmann, 2010. "Performance of renewable energy technologies under the CDM," Climate Policy, Taylor & Francis Journals, vol. 10(1), pages 17-37, January.
    24. Nemet, Gregory F., 2006. "Beyond the learning curve: factors influencing cost reductions in photovoltaics," Energy Policy, Elsevier, vol. 34(17), pages 3218-3232, November.
    25. Ivan Haščič & Nick Johnstone, 2011. "CDM and international technology transfer: empirical evidence on wind power," Climate Policy, Taylor & Francis Journals, vol. 11(6), pages 1303-1314, November.
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    Cited by:

    1. Armon Rezai & Frederick Ploeg, 2017. "Second-Best Renewable Subsidies to De-carbonize the Economy: Commitment and the Green Paradox," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 66(3), pages 409-434, March.
    2. Lam, Long T. & Branstetter, Lee & Azevedo, Inês M.L., 2017. "China's wind industry: Leading in deployment, lagging in innovation," Energy Policy, Elsevier, vol. 106(C), pages 588-599.
    3. Huenteler, Joern & Schmidt, Tobias S. & Ossenbrink, Jan & Hoffmann, Volker H., 2016. "Technology life-cycles in the energy sector — Technological characteristics and the role of deployment for innovation," Technological Forecasting and Social Change, Elsevier, vol. 104(C), pages 102-121.

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    More about this item

    JEL classification:

    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • O38 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Government Policy
    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources
    • Q48 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Government Policy
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming
    • Q55 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environmental Economics: Technological Innovation

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