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The uneven development of wind power in China: Determinants and the role of supporting policies

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  • Xia, Fang
  • Song, Feng

Abstract

We apply a partial adjustment model to investigate the driving factors of the regional disparity of China's wind power development. We have three major findings. First, similar to many industries, wind power shows an agglomeration effect, that is, existing installed capacity attracts new addition of capacity. Second, demand factors including both local demand, indicated by variables in the local economy, and demand outside the region, indicated by transmission capacity, do not significantly affect the location choice of wind power farms. Lastly, governmental supporting measures have heterogeneous effects on different regions. They are most effective in wind resource rich regions but have little impact in other regions.

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  • Xia, Fang & Song, Feng, 2017. "The uneven development of wind power in China: Determinants and the role of supporting policies," Energy Economics, Elsevier, vol. 67(C), pages 278-286.
    • Handle: RePEc:eee:eneeco:v:67:y:2017:i:c:p:278-286
    DOI: 10.1016/j.eneco.2017.08.008
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    as
    1. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-1054, July.
    2. Hu, Zheng & Wang, Jianhui & Byrne, John & Kurdgelashvili, Lado, 2013. "Review of wind power tariff policies in China," Energy Policy, Elsevier, vol. 53(C), pages 41-50.
    3. Liu, Yingqi & Kokko, Ari, 2010. "Wind power in China: Policy and development challenges," Energy Policy, Elsevier, vol. 38(10), pages 5520-5529, October.
    4. Fang, Yong & Li, Jing & Wang, Mingming, 2012. "Development policy for non-grid-connected wind power in China: An analysis based on institutional change," Energy Policy, Elsevier, vol. 45(C), pages 350-358.
    5. Menz, Fredric C. & Vachon, Stephan, 2006. "The effectiveness of different policy regimes for promoting wind power: Experiences from the states," Energy Policy, Elsevier, vol. 34(14), pages 1786-1796, September.
    6. Han, Jingyi & Mol, Arthur P.J. & Lu, Yonglong & Zhang, Lei, 2009. "Onshore wind power development in China: Challenges behind a successful story," Energy Policy, Elsevier, vol. 37(8), pages 2941-2951, August.
    7. Stephen Bond & Anke Hoeffler, 2001. "GMM Estimation of Empirical Growth Models," Economics Series Working Papers 2001-W21, University of Oxford, Department of Economics.
    8. Ellison, Glenn & Glaeser, Edward L, 1997. "Geographic Concentration in U.S. Manufacturing Industries: A Dartboard Approach," Journal of Political Economy, University of Chicago Press, vol. 105(5), pages 889-927, October.
    9. Rosenthal, Stuart S. & Strange, William C., 2004. "Evidence on the nature and sources of agglomeration economies," Handbook of Regional and Urban Economics, in: J. V. Henderson & J. F. Thisse (ed.), Handbook of Regional and Urban Economics, edition 1, volume 4, chapter 49, pages 2119-2171, Elsevier.
    10. 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.
    11. Liu, Xuemei, 2013. "The value of holding scarce wind resource—A cause of overinvestment in wind power capacity in China," Energy Policy, Elsevier, vol. 63(C), pages 97-100.
    12. 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.
    13. Zhang, Sufang & Andrews-Speed, Philip & Zhao, Xiaoli, 2013. "Political and institutional analysis of the successes and failures of China’s wind power policy," Energy Policy, Elsevier, vol. 56(C), pages 331-340.
    14. Arellano, Manuel & Bover, Olympia, 1995. "Another look at the instrumental variable estimation of error-components models," Journal of Econometrics, Elsevier, vol. 68(1), pages 29-51, July.
    15. Zhao, Xiaoli & Zhang, Sufang & Zou, Yasheng & Yao, Jin, 2013. "To what extent does wind power deployment affect vested interests? A case study of the Northeast China Grid," Energy Policy, Elsevier, vol. 63(C), pages 814-822.
    16. Stephen Bond & Anke Hoeffler & Jonathan Temple, 2001. "GMM Estimation of Empirical Growth Models," Economics Papers 2001-W21, Economics Group, Nuffield College, University of Oxford.
    17. Qiu, Yueming & Ortolano, Leonard & David Wang, Yi, 2013. "Factors influencing the technology upgrading and catch-up of Chinese wind turbine manufacturers: Technology acquisition mechanisms and government policies," Energy Policy, Elsevier, vol. 55(C), pages 305-316.
    18. Hitaj, Claudia, 2013. "Wind power development in the United States," Journal of Environmental Economics and Management, Elsevier, vol. 65(3), pages 394-410.
    19. Blundell, Richard & Bond, Stephen, 1998. "Initial conditions and moment restrictions in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 87(1), pages 115-143, August.
    20. Audretsch, David B & Feldman, Maryann P, 1996. "R&D Spillovers and the Geography of Innovation and Production," American Economic Review, American Economic Association, vol. 86(3), pages 630-640, June.
    21. He, Gang & Kammen, Daniel M., 2014. "Where, when and how much wind is available? A provincial-scale wind resource assessment for China," Energy Policy, Elsevier, vol. 74(C), pages 116-122.
    22. Schmidt, J. & Lehecka, G. & Gass, V. & Schmid, E., 2013. "Where the wind blows: Assessing the effect of fixed and premium based feed-in tariffs on the spatial diversification of wind turbines," Energy Economics, Elsevier, vol. 40(C), pages 269-276.
    23. Nickell, Stephen J, 1981. "Biases in Dynamic Models with Fixed Effects," Econometrica, Econometric Society, vol. 49(6), pages 1417-1426, November.
    24. Zifa Liu & Wenhua Zhang & Changhong Zhao & Jiahai Yuan, 2015. "The Economics of Wind Power in China and Policy Implications," Energies, MDPI, vol. 8(2), pages 1-18, February.
    25. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(2), pages 277-297.
    26. Zhao, Xiaoli & Wang, Feng & Wang, Mei, 2012. "Large-scale utilization of wind power in China: Obstacles of conflict between market and planning," Energy Policy, Elsevier, vol. 48(C), pages 222-232.
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    3. Thomas Lauf & Kristina Ek & Erik Gawel & Paul Lehmann & Patrik Söderholm, 2020. "The regional heterogeneity of wind power deployment: an empirical investigation of land-use policies in Germany and Sweden," Journal of Environmental Planning and Management, Taylor & Francis Journals, vol. 63(4), pages 751-778, March.
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    5. Song, Feng & Yu, Zichao & Zhuang, Weiting & Lu, Ao, 2021. "The institutional logic of wind energy integration: What can China learn from the United States to reduce wind curtailment?," Renewable and Sustainable Energy Reviews, Elsevier, vol. 137(C).
    6. Costa, Hélia & Veiga, Linda, 2021. "Local labor impact of wind energy investment: An analysis of Portuguese municipalities," Energy Economics, Elsevier, vol. 94(C).
    7. Engelhorn, Thorsten & Müsgens, Felix, 2021. "Why is Germany’s energy transition so expensive? Quantifying the costs of wind-energy decentralisation," Resource and Energy Economics, Elsevier, vol. 65(C).
    8. Lin, Boqiang & Chen, Yufang, 2019. "Impacts of policies on innovation in wind power technologies in China," Applied Energy, Elsevier, vol. 247(C), pages 682-691.
    9. Lundin, Erik, 2022. "Geographic price granularity and investments in wind power: Evidence from a Swedish electricity market splitting reform," Energy Economics, Elsevier, vol. 113(C).
    10. Zhang, ZhongXiang, 2018. "Energy Price Reform in China," ESP: Energy Scenarios and Policy 273368, Fondazione Eni Enrico Mattei (FEEM).
    11. Du, Yimeng & Takeuchi, Kenji, 2020. "Does a small difference make a difference? Impact of feed-in tariff on renewable power generation in China," Energy Economics, Elsevier, vol. 87(C).
    12. Xu, Ye & Li, Ye & Zheng, Lijun & Cui, Liang & Li, Sha & Li, Wei & Cai, Yanpeng, 2020. "Site selection of wind farms using GIS and multi-criteria decision making method in Wafangdian, China," Energy, Elsevier, vol. 207(C).
    13. He, Zhengxia & Cao, Changshuai & Kuai, Leyi & Zhou, Yanqing & Wang, Jianming, 2022. "Impact of policies on wind power innovation at different income levels: Regional differences in China based on dynamic panel estimation," Technology in Society, Elsevier, vol. 71(C).
    14. Xu, Bin & Lin, Boqiang, 2018. "Assessing the development of China's new energy industry," Energy Economics, Elsevier, vol. 70(C), pages 116-131.
    15. Xia, Fang & Lu, Xi & Song, Feng, 2020. "The role of feed-in tariff in the curtailment of wind power in China," Energy Economics, Elsevier, vol. 86(C).
    16. Che, Xiao-Jing & Zhou, P. & Wang, M., 2022. "The policy effect on photovoltaic technology innovation with regional heterogeneity in China," Energy Economics, Elsevier, vol. 115(C).
    17. Song, Feng & Bi, De & Wei, Chu, 2019. "Market segmentation and wind curtailment: An empirical analysis," Energy Policy, Elsevier, vol. 132(C), pages 831-838.
    18. María-Jesús Gutiérrez-Pedrero & María J. Ruiz-Fuensanta & Miguel-Ángel Tarancón, 2020. "Regional Factors Driving the Deployment of Wind Energy in Spain," Energies, MDPI, vol. 13(14), pages 1-13, July.
    19. Shuo Zhang & Li Chen & Yidan Zheng & Yingzi Li & Ying Li & Ming Zeng, 2021. "How Policies Guide and Promoted Wind Power to Market Transactions in China during the 2010s," Energies, MDPI, vol. 14(14), pages 1-24, July.
    20. Zhang, Pan, 2019. "Do energy intensity targets matter for wind energy development? Identifying their heterogeneous effects in Chinese provinces with different wind resources," Renewable Energy, Elsevier, vol. 139(C), pages 968-975.

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    More about this item

    Keywords

    Wind power; Agglomeration effect; Feed-in-tariff policy;
    All these keywords.

    JEL classification:

    • 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
    • R11 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Regional Economic Activity: Growth, Development, Environmental Issues, and Changes

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