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The price of wind power in China during its expansion: Technology adoption, learning-by-doing, economies of scale, and manufacturing localization

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  • Qiu, Yueming
  • Anadon, Laura D.
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    Abstract

    Using the bidding prices of participants in China's national wind project concession programs from 2003 to 2007, this paper built up a learning curve model to estimate the joint learning from learning-by-doing and learning-by-searching, with a novel knowledge stock metric based on technology adoption in China through both domestic technology development and international technology transfer. The paper describes, for the first time, the evolution of the price of wind power in China, and provides estimates of how technology adoption, experience in building wind farm projects, wind turbine manufacturing localization, and wind farm economies of scale have influenced the price of wind power. The learning curve model presented includes several important control variables, namely, wind resource indicators and steel prices. The results indicate that joint learning from technology adoption and learning-by-doing through cumulative installed capacity, wind turbine manufacturing localization, and wind farm economies of scale comprise the three most significant factors associated with reductions in the price of wind power in China during the period under consideration. The two types of learning investigated are associated with a 4.1%–4.3% price reduction per doubling of installed capacity, providing an estimate of the evolution of the price of wind power, a technology widely used in other markets, which in China has benefited from technology leapfrogging, established supply chains, and operational experience in other countries. Because of the change of bidding rules in 2007, our estimates can be interpreted as the lower bound of the true joint learning rates. Our model also indicates that most learning about the installation and operation of wind farms was common to the whole industry (i.e., we found little evidence for intra-firm learning). The policies that have contributed to the growth of the Chinese knowledge stock through the promotion of technology adoption are also discussed.

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    Bibliographic Info

    Article provided by Elsevier in its journal Energy Economics.

    Volume (Year): 34 (2012)
    Issue (Month): 3 ()
    Pages: 772-785

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    Handle: RePEc:eee:eneeco:v:34:y:2012:i:3:p:772-785

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    Web page: http://www.elsevier.com/locate/eneco

    Related research

    Keywords: Wind power; Learning curve; China; Technology adoption; Learning-by-doing; Learning-by-searching;

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    References

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    Cited by:
    1. repec:rom:campco:v:9:y:2013:i:1:p:289-297 is not listed on IDEAS
    2. Trappey, Amy J.C. & Trappey, Charles V. & Liu, Penny H.Y. & Lin, Lee-Cheng & Ou, Jerry J.R., 2013. "A hierarchical cost learning model for developing wind energy infrastructures," International Journal of Production Economics, Elsevier, vol. 146(2), pages 386-391.
    3. Valentine, Scott Victor, 2014. "The socio-political economy of electricity generation in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 32(C), pages 416-429.
    4. Zhao, Zhen-yu & Sun, Guang-zheng & Zuo, Jian & Zillante, George, 2013. "The impact of international forces on the Chinese wind power industry," Renewable and Sustainable Energy Reviews, Elsevier, vol. 24(C), pages 131-141.
    5. 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.
    6. Partridge, Ian, 2013. "Renewable electricity generation in India—A learning rate analysis," Energy Policy, Elsevier, vol. 60(C), pages 906-915.
    7. 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.
    8. Zheng, Cheng & Kammen, Daniel M., 2014. "An innovation-focused roadmap for a sustainable global photovoltaic industry," Energy Policy, Elsevier, vol. 67(C), pages 159-169.
    9. Lam, J.C.K. & Woo, C.K. & Kahrl, F. & Yu, W.K., 2013. "What moves wind energy development in China? Show me the money!," Applied Energy, Elsevier, vol. 105(C), pages 423-429.
    10. Tian Tang & David Popp, 2014. "The Learning Process and Technological Change in Wind Power: Evidence from China's CDM Wind Projects," CESifo Working Paper Series 4705, CESifo Group Munich.

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