IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v14y2021i19p6418-d651520.html
   My bibliography  Save this article

Solar Photovoltaic Investment Changes across China Regions Using a Spatial Shift-Share Analysis

Author

Listed:
  • Ruxu Sheng

    (School of Public Policy and Management, Tsinghua University, Beijing 100084, China)

  • Juntian Du

    (School of Public Policy and Management, Tsinghua University, Beijing 100084, China)

  • Songqi Liu

    (School of Public Policy and Management, Tsinghua University, Beijing 100084, China)

  • Changan Wang

    (Research Institute of Economics and Management, Southwestern University of Finance and Economics, Chengdu 611130, China)

  • Zidi Wang

    (School of Public Policy and Management, Tsinghua University, Beijing 100084, China)

  • Xiaoqian Liu

    (Research Institute of Economics and Management, Southwestern University of Finance and Economics, Chengdu 611130, China)

Abstract

Solar photovoltaic (PV) has become the fastest-growing new energy in China and one of the main contributors to China’s clean energy transition. From 2013 to 2019, China’s solar PV installed capacity grew from 15,890 MW to 204,180 MW, increasing by 11.85 times. To explore solar PV investment changes across China regions, we use spatial shift-share analysis model to decompose solar PV investment changes from 2013 to 2019 into four components: national energy investment growth effect (NEG), national energy investment structure effect (NES), neighbor–nation solar PV investment competitive effect (NNC), and region–neighbor solar PV investment competitive effect (RNC). Based on the decomposition results, we find that the value of NNC of most western provinces is negative for the entire period, while the NNC of most central and eastern provinces is in the middle and lower range. There is little difference in RNC among these regions. While comparing the influence caused by the four effects, NNC and RNC play dominant roles in solar PV investment changes in eastern and central provinces, which means NEG and NES have relatively small impacts. By contrast, NEG and NES affect the solar PV investment changes at a larger scale in most western provinces. Comparing the NNC and RNC, we find that RNC played a prominent role in the eastern and central regions, while NNC played a dominant role in the west.

Suggested Citation

  • Ruxu Sheng & Juntian Du & Songqi Liu & Changan Wang & Zidi Wang & Xiaoqian Liu, 2021. "Solar Photovoltaic Investment Changes across China Regions Using a Spatial Shift-Share Analysis," Energies, MDPI, vol. 14(19), pages 1-14, October.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:19:p:6418-:d:651520
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/14/19/6418/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/14/19/6418/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Suahasil Nazara & Geoffrey J.D. Hewings, 2004. "Spatial Structure and Taxonomy of Decomposition in Shift‐Share Analysis," Growth and Change, Wiley Blackwell, vol. 35(4), pages 476-490, September.
    2. Carstens, Danielle Denes dos Santos & Cunha, Sieglinde Kindl da, 2019. "Challenges and opportunities for the growth of solar photovoltaic energy in Brazil," Energy Policy, Elsevier, vol. 125(C), pages 396-404.
    3. Giuseppe Espa & Danila Filipponi & Diego Giuliani & Davide Piacentino, 2014. "Decomposing regional business change at plant level in Italy: A novel spatial shift-share approach," Papers in Regional Science, Wiley Blackwell, vol. 93, pages 113-135, November.
    4. Ahmad, Salman & Tahar, Razman Mat & Muhammad-Sukki, Firdaus & Munir, Abu Bakar & Rahim, Ruzairi Abdul, 2015. "Role of feed-in tariff policy in promoting solar photovoltaic investments in Malaysia: A system dynamics approach," Energy, Elsevier, vol. 84(C), pages 808-815.
    5. Cheng, Cheng & Wang, Zhen & Liu, Mingming & Chen, Qiang & Gbatu, Abimelech Paye & Ren, Xiaohang, 2017. "Defer option valuation and optimal investment timing of solar photovoltaic projects under different electricity market systems and support schemes," Energy, Elsevier, vol. 127(C), pages 594-610.
    6. Lin, Gang & Jiang, Dong & Fu, Jingying & Wang, Di & Li, Xiang, 2019. "A spatial shift-share decomposition of energy consumption changes in China," Energy Policy, Elsevier, vol. 135(C).
    7. Esteban-Marquillas, J. M., 1972. "I. A reinterpretation of shift-share analysis," Regional and Urban Economics, Elsevier, vol. 2(3), pages 249-255, October.
    8. Kayser, Dirk, 2016. "Solar photovoltaic projects in China: High investment risks and the need for institutional response," Applied Energy, Elsevier, vol. 174(C), pages 144-152.
    9. Grossi, Luigi & Mussini, Mauro, 2018. "A spatial shift-share decomposition of electricity consumption changes across Italian regions," Energy Policy, Elsevier, vol. 113(C), pages 278-293.
    10. Wen, Daoyuan & Gao, Weijun & Kuroki, Soichiro & Gu, Qunyin & Ren, Jianxing, 2021. "The effects of the new Feed-In Tariff Act for solar photovoltaic (PV) energy in the wake of the Fukushima accident in Japan," Energy Policy, Elsevier, vol. 156(C).
    11. Zhou, Yuan & Dong, Fang & Kong, Dejing & Liu, Yufei, 2019. "Unfolding the convergence process of scientific knowledge for the early identification of emerging technologies," Technological Forecasting and Social Change, Elsevier, vol. 144(C), pages 205-220.
    12. Kong, Dejing & Zhou, Yuan & Liu, Yufei & Xue, Lan, 2017. "Using the data mining method to assess the innovation gap: A case of industrial robotics in a catching-up country," Technological Forecasting and Social Change, Elsevier, vol. 119(C), pages 80-97.
    13. Pillai, Unni, 2015. "Drivers of cost reduction in solar photovoltaics," Energy Economics, Elsevier, vol. 50(C), pages 286-293.
    14. Yuan Zhou & Zhongzhen Miao & Frauke Urban, 2020. "China’s leadership in the hydropower sector: identifying green windows of opportunity for technological catch-up," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 29(5), pages 1319-1343.
    15. Zhang, M.M. & Zhou, P. & Zhou, D.Q., 2016. "A real options model for renewable energy investment with application to solar photovoltaic power generation in China," Energy Economics, Elsevier, vol. 59(C), pages 213-226.
    16. Edgar S. Dunn, 1960. "A Statistical And Analytical Technique For Regional Analysis," Papers in Regional Science, Wiley Blackwell, vol. 6(1), pages 97-112, January.
    17. Ye, Liang-Cheng & Rodrigues, João F.D. & Lin, Hai Xiang, 2017. "Analysis of feed-in tariff policies for solar photovoltaic in China 2011–2016," Applied Energy, Elsevier, vol. 203(C), pages 496-505.
    18. Zhao, Zhen-yu & Zhang, Shuang-Ying & Hubbard, Bryan & Yao, Xue, 2013. "The emergence of the solar photovoltaic power industry in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 21(C), pages 229-236.
    19. Wang, Hongwei & Zheng, Shilin & Zhang, Yanhua & Zhang, Kai, 2016. "Analysis of the policy effects of downstream Feed-In Tariff on China’s solar photovoltaic industry," Energy Policy, Elsevier, vol. 95(C), pages 479-488.
    20. Natália Gava Gastaldo & Graciele Rediske & Paula Donaduzzi Rigo & Carmen Brum Rosa & Leandro Michels & Julio Cezar Mairesse Siluk, 2019. "What is the Profile of the Investor in Household Solar Photovoltaic Energy Systems?," Energies, MDPI, vol. 12(23), pages 1-18, November.
    21. Yuan Zhou & Xin Li & Rasmus Lema & Frauke Urban, 2016. "Comparing the knowledge bases of wind turbine firms in Asia and Europe: Patent trajectories, networks, and globalisation," Science and Public Policy, Oxford University Press, vol. 43(4), pages 476-491.
    22. Huiming Zhang & Kai Wu & Yueming Qiu & Gabriel Chan & Shouyang Wang & Dequn Zhou & Xianqiang Ren, 2020. "Solar photovoltaic interventions have reduced rural poverty in China," Nature Communications, Nature, vol. 11(1), pages 1-10, December.
    23. Martina Assereto & Julie Byrne, 2020. "The Implications of Policy Uncertainty on Solar Photovoltaic Investment," Energies, MDPI, vol. 13(23), pages 1-20, November.
    24. BumChoong Kim & Juhan Kim & Jinsoo Kim, 2019. "Evaluation Model for Investment in Solar Photovoltaic Power Generation Using Fuzzy Analytic Hierarchy Process," Sustainability, MDPI, vol. 11(10), pages 1-23, May.
    25. Chang, Byungik & Starcher, Ken, 2019. "Evaluation of wind and solar energy investments in Texas," Renewable Energy, Elsevier, vol. 132(C), pages 1348-1359.
    26. Lionel Artige & Leif Neuss, 2014. "A New Shift-Share Method," Growth and Change, Wiley Blackwell, vol. 45(4), pages 667-683, December.
    27. Zhi, Qiang & Sun, Honghang & Li, Yanxi & Xu, Yurui & Su, Jun, 2014. "China’s solar photovoltaic policy: An analysis based on policy instruments," Applied Energy, Elsevier, vol. 129(C), pages 308-319.
    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. Mohamed Derbeli & Cristian Napole & Oscar Barambones & Jesus Sanchez & Isidro Calvo & Pablo Fernández-Bustamante, 2021. "Maximum Power Point Tracking Techniques for Photovoltaic Panel: A Review and Experimental Applications," Energies, MDPI, vol. 14(22), pages 1-31, November.
    2. Mohana Alanazi & Abdulaziz Alanazi & Ahmad Almadhor & Hafiz Tayyab Rauf, 2022. "Photovoltaic Models’ Parameter Extraction Using New Artificial Parameterless Optimization Algorithm," Mathematics, MDPI, vol. 10(23), pages 1-32, December.

    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. Ruxu Sheng & Rong Zhou & Ying Zhang & Zidi Wang, 2021. "Green Investment Changes in China: A Shift-Share Analysis," IJERPH, MDPI, vol. 18(12), pages 1-15, June.
    2. Ye, Liang-Cheng & Rodrigues, João F.D. & Lin, Hai Xiang, 2017. "Analysis of feed-in tariff policies for solar photovoltaic in China 2011–2016," Applied Energy, Elsevier, vol. 203(C), pages 496-505.
    3. Chao Bao & Ruowen Liu, 2019. "Electricity Consumption Changes across China’s Provinces Using A Spatial Shift-Share Decomposition Model," Sustainability, MDPI, vol. 11(9), pages 1-15, April.
    4. Hengtian Wang & Xiaolong Yang & Xinxin Xu & Liu Fei, 2021. "Exploring Opportunities and Challenges of Solar PV Power under Carbon Peak Scenario in China: A PEST Analysis," Energies, MDPI, vol. 14(11), pages 1-28, May.
    5. Corwin, Samuel & Johnson, Timothy L., 2019. "The role of local governments in the development of China's solar photovoltaic industry," Energy Policy, Elsevier, vol. 130(C), pages 283-293.
    6. Pilar Campoy-Muñoz & Manuel Alejandro Cardenete & M. Carmen Delgado, 2015. "Employment trends in the key sectors of the Andalusian economy," ERSA conference papers ersa15p91, European Regional Science Association.
    7. Valente J. Matlaba & Mark Holmes & Philip McCann & Jacques Poot, 2014. "Classic and Spatial Shift-Share Analysis of State-Level Employment Change in Brazil," Advances in Spatial Science, in: Karima Kourtit & Peter Nijkamp & Robert Stimson (ed.), Applied Regional Growth and Innovation Models, edition 127, chapter 0, pages 139-172, Springer.
    8. Xuemei Zhou & Xiaodan Lin & Xiangfeng Ji & Jiahui Liang, 2021. "Effects of High-Speed Railway Construction and Operation on Related Industries in China," Sustainability, MDPI, vol. 13(11), pages 1-17, May.
    9. Lin, Gang & Jiang, Dong & Fu, Jingying & Wang, Di & Li, Xiang, 2019. "A spatial shift-share decomposition of energy consumption changes in China," Energy Policy, Elsevier, vol. 135(C).
    10. Roberto Patuelli & Aura Reggiani & Peter Nijkamp & Uwe Blien, 2006. "New Neural Network Methods for Forecasting Regional Employment: an Analysis of German Labour Markets," Spatial Economic Analysis, Taylor & Francis Journals, vol. 1(1), pages 7-30.
    11. Claudia V. Montanía & Miguel A. Márquez & Teresa Fernández‐Núñez & Geoffrey J.D. Hewings, 2021. "Spatial shift‐share analysis: Some new developments," Papers in Regional Science, Wiley Blackwell, vol. 100(2), pages 305-325, April.
    12. Jean‐François Ruault & Yves Schaeffer, 2020. "Scalable shift‐share analysis: Novel framework and application to France," Papers in Regional Science, Wiley Blackwell, vol. 99(6), pages 1667-1690, December.
    13. Umberto Di Maggio & Giuseppe Notarstefano & Giuseppe Terzo, 2020. "The spatial determinants of employment growth in the cooperative sector: an analysis of Italian provinces," RIEDS - Rivista Italiana di Economia, Demografia e Statistica - The Italian Journal of Economic, Demographic and Statistical Studies, SIEDS Societa' Italiana di Economia Demografia e Statistica, vol. 74(3-4), pages 123-134, July-Dece.
    14. Jian Luo & Yongchun Yang, 2023. "Rediscovering the Shift-Share EM2 Model: A Decomposition Framework of Unbalanced Employment Growth at the Industrial Level," Sustainability, MDPI, vol. 15(6), pages 1-16, March.
    15. Guannan Xu & Weijie Hu & Yuanyuan Qiao & Yuan Zhou, 2020. "Mapping an innovation ecosystem using network clustering and community identification: a multi-layered framework," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(3), pages 2057-2081, September.
    16. Campoy-Muñoz, Pilar & Cardenete, Manuel Alejandro & Delgado, M. Carmen, 2015. "Strategic sectors and employment during the crisis: The case of Andalusia || Sectores estratégicos y empleo durante la crisis: el caso de Andalucía," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 20(1), pages 25-52, December.
    17. repec:rdg:wpaper:em-dp2010-06 is not listed on IDEAS
    18. Francesca Silvia Rota & Marco Bagliani & Paolo Feletig, 2020. "Breaking the Black-Box of Regional Resilience: A Taxonomy Using a Dynamic Cumulative Shift-Share Occupational Approach," Sustainability, MDPI, vol. 12(21), pages 1-27, October.
    19. Li, Lili & Taeihagh, Araz, 2020. "An in-depth analysis of the evolution of the policy mix for the sustainable energy transition in China from 1981 to 2020," Applied Energy, Elsevier, vol. 263(C).
    20. Dejing Kong & Jianzhong Yang & Lingfeng Li, 2020. "Early identification of technological convergence in numerical control machine tool: a deep learning approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 1983-2009, December.
    21. Duro, Juan Antonio & Esteban, Joan, 1998. "Factor decomposition of cross-country income inequality, 1960-1990," Economics Letters, Elsevier, vol. 60(3), pages 269-275, September.

    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:gam:jeners:v:14:y:2021:i:19:p:6418-:d:651520. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.