IDEAS home Printed from https://ideas.repec.org/a/eee/eneeco/v67y2017icp278-286.html
   My bibliography  Save this article

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

Author

Listed:
  • 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.

Suggested Citation

  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0140988317302645
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.eneco.2017.08.008?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    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. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-1054, July.
    2. Stephen Bond & Anke Hoeffler & Jonathan Temple, 2001. "GMM Estimation of Empirical Growth Models," Economics Papers 2001-W21, Economics Group, Nuffield College, University of Oxford.
    3. 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.
    4. 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.
    5. Liu, Yingqi & Kokko, Ari, 2010. "Wind power in China: Policy and development challenges," Energy Policy, Elsevier, vol. 38(10), pages 5520-5529, October.
    6. 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.
    7. 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.
    8. Hitaj, Claudia, 2013. "Wind power development in the United States," Journal of Environmental Economics and Management, Elsevier, vol. 65(3), pages 394-410.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. Stephen Bond & Anke Hoeffler, 2001. "GMM Estimation of Empirical Growth Models," Economics Series Working Papers 2001-W21, University of Oxford, Department of Economics.
    15. 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.
    16. 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.
    17. 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.
    18. 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.
    19. 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.
    20. 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.
    21. Nickell, Stephen J, 1981. "Biases in Dynamic Models with Fixed Effects," Econometrica, Econometric Society, vol. 49(6), pages 1417-1426, November.
    22. 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.
    23. 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.
    24. 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.
    25. 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.
    26. 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.
    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. Zheng, Xuemei & Li, Cao & Fang, Xingming & Zhang, Ning, 2021. "Price sensitivity and consumers’ support for renewable energy in China," Energy, Elsevier, vol. 222(C).
    2. Chen, Hao & Chen, Jiachuan & Han, Guoyi & Cui, Qi, 2022. "Winding down the wind power curtailment in China: What made the difference?," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
    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.
    4. Yu, Chin-Hsien & Wu, Xiuqin & Lee, Wen-Chieh & Zhao, Jinsong, 2021. "Resource misallocation in the Chinese wind power industry: The role of feed-in tariff policy," Energy Economics, Elsevier, vol. 98(C).
    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.

    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. Martin Andersson & Hans Lööf, 2011. "Agglomeration and productivity: evidence from firm-level data," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 46(3), pages 601-620, June.
    2. Fernando Mayoral & Carlos Garcimartín, 2013. "The impact of population on the reduction of steady-state disparities across Spanish regions," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 50(1), pages 49-69, February.
    3. Zheng, Xinye & Li, Fanghua & Song, Shunfeng & Yu, Yihua, 2013. "Central government's infrastructure investment across Chinese regions: A dynamic spatial panel data approach," China Economic Review, Elsevier, vol. 27(C), pages 264-276.
    4. Martin Andersson & Hans Lööf, 2009. "Learning‐by‐Exporting Revisited: The Role of Intensity and Persistence," Scandinavian Journal of Economics, Wiley Blackwell, vol. 111(4), pages 893-916, December.
    5. Yerrabati, Sridevi, 2022. "Does vulnerable employment alleviate poverty in developing countries?," Economic Modelling, Elsevier, vol. 116(C).
    6. Vogel, Johanna, 2013. "Regional Convergence in Europe: A Dynamic Heterogeneous Panel Approach," MPRA Paper 51794, University Library of Munich, Germany.
    7. Wei, Yifan, 2022. "Reprint of: Regional governments and opportunity entrepreneurship in underdeveloped institutional environments: An entrepreneurial ecosystem perspective," Research Policy, Elsevier, vol. 51(9).
    8. Wei, Yifan, 2022. "Regional governments and opportunity entrepreneurship in underdeveloped institutional environments: An entrepreneurial ecosystem perspective," Research Policy, Elsevier, vol. 51(1).
    9. Diego Bastourre & Jorge Carrera & Javier Ibarlucia, 2009. "What is Driving Reserve Accumulation? A Dynamic Panel Data Approach," Review of International Economics, Wiley Blackwell, vol. 17(4), pages 861-877, September.
    10. Berk, Istemi & Kasman, Adnan & Kılınç, Dilara, 2020. "Towards a common renewable future: The System-GMM approach to assess the convergence in renewable energy consumption of EU countries," Energy Economics, Elsevier, vol. 87(C).
    11. Carlos Usabiaga & E. Macarena Hernández-Salmerón, 2016. "Regional Growth and Convergence in Spain: Is the Decentralization Model Important?," EcoMod2016 9358, EcoMod.
    12. Xuemei Liu, 2016. "Why Has Wind Power Capacity Been Overinvested Under Uncertainty in China?," Review of Economics & Finance, Better Advances Press, Canada, vol. 6, pages 1-12, February.
    13. Abonazel, Mohamed R., 2016. "Bias Correction Methods for Dynamic Panel Data Models with Fixed Effects," MPRA Paper 70628, University Library of Munich, Germany.
    14. Qu, Guangjun & Sylwester, Kevin & Wang, Feng, 2016. "Anticorruption and Growth: Evidence from China," MPRA Paper 72190, University Library of Munich, Germany.
    15. Annita Nugent & Ho Fai Chan & Uwe Dulleck, 2022. "Government funding of university-industry collaboration: exploring the impact of targeted funding on university patent activity," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(1), pages 29-73, January.
    16. Maurice J.G. Bun & Sarafidis, V., 2013. "Dynamic Panel Data Models," UvA-Econometrics Working Papers 13-01, Universiteit van Amsterdam, Dept. of Econometrics.
    17. Gnangnon, Sèna Kimm, 2023. "Duration of membership in the world trade organization and investment-oriented remittances inflows," The Quarterly Review of Economics and Finance, Elsevier, vol. 88(C), pages 258-277.
    18. Brülhart, Marius & Mathys, Nicole A., 2008. "Sectoral agglomeration economies in a panel of European regions," Regional Science and Urban Economics, Elsevier, vol. 38(4), pages 348-362, July.
    19. Gnangnon, Sèna Kimm, 2022. "Duration of WTO Membership and Investment-Oriented Remittances Flows," EconStor Preprints 251274, ZBW - Leibniz Information Centre for Economics.
    20. Joan Costa-Font & Cristina Vilaplana-Prieto, 2023. "‘Investing’ in care for old age? An examination of long-term care expenditure dynamics and its spillovers," Empirical Economics, Springer, vol. 64(1), pages 1-30, January.

    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

    Statistics

    Access and download statistics

    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:67:y:2017:i:c:p:278-286. 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.