IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v14y2021i17p5468-d627685.html
   My bibliography  Save this article

Decomposition of Industrial Electricity Efficiency and Electricity-Saving Potential of Special Economic Zones in China Considering the Heterogeneity of Administrative Hierarchy and Regional Location

Author

Listed:
  • Jianmin You

    (School of Economics and Statistics, Guangzhou University, Guangzhou 510006, China
    Guizhou Institute of Local Modernized Governance, Guizhou Academy of Social Science, Guiyang 550002, China)

  • Xiqiang Chen

    (School of Economics and Statistics, Guangzhou University, Guangzhou 510006, China)

  • Jindao Chen

    (School of Economics and Statistics, Guangzhou University, Guangzhou 510006, China)

Abstract

Special Economic Zones (SEZs), an important engine of industrial economic development in China, consume large amounts of energy resources and emit considerable CO2. However, existing research pays little attention to industrial energy usage in SEZs and ignores the heterogeneity of administrative hierarchy and regional location. Considering the dual heterogeneity, this study proposes an improved two-dimension and two-level meta-frontier data envelopment analytical model to decompose the industrial electricity efficiency (IEE) and electricity-saving potential of SEZs in Guizhou Province, China, based on 4-year field survey data (2016–2019). Results show that the IEE rankings of three administrative hierarchies within SEZs are provincial administration SEZs, county administration SEZs, and municipality administration SEZs. The SEZs located in energy resource-rich areas and better ecological environmental areas have higher IEE than those in resource-poor areas and ecology fragile areas, respectively. This study can provide reference for policymakers to formulate effective policies for improving the electricity use efficiency of SEZs in China.

Suggested Citation

  • Jianmin You & Xiqiang Chen & Jindao Chen, 2021. "Decomposition of Industrial Electricity Efficiency and Electricity-Saving Potential of Special Economic Zones in China Considering the Heterogeneity of Administrative Hierarchy and Regional Location," Energies, MDPI, vol. 14(17), pages 1-22, September.
  • Handle: RePEc:gam:jeners:v:14:y:2021:i:17:p:5468-:d:627685
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/14/17/5468/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/14/17/5468/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Tanaka, Kenta & Managi, Shunsuke, 2021. "Industrial agglomeration effect for energy efficiency in Japanese production plants," Energy Policy, Elsevier, vol. 156(C).
    2. Inglesi-Lotz, R. & Blignaut, J.N., 2012. "Electricity intensities of the OECD and South Africa: A comparison," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(7), pages 4491-4499.
    3. Joshua Linn, 2008. "Energy Prices and the Adoption of Energy-Saving Technology," Economic Journal, Royal Economic Society, vol. 118(533), pages 1986-2012, November.
    4. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    5. Zhou, P. & Ang, B.W. & Han, J.Y., 2010. "Total factor carbon emission performance: A Malmquist index analysis," Energy Economics, Elsevier, vol. 32(1), pages 194-201, January.
    6. Zheng, Guo & Barbieri, Elisa & Di Tommaso, Marco R. & Zhang, Lei, 2016. "Development zones and local economic growth: zooming in on the Chinese case," China Economic Review, Elsevier, vol. 38(C), pages 238-249.
    7. Mark A. Andor & David H. Bernstein & Stephan Sommer, 2021. "Determining the efficiency of residential electricity consumption," Empirical Economics, Springer, vol. 60(6), pages 2897-2923, June.
    8. Manderson, Edward J. & Kneller, Richard, 2020. "Energy endowments and the location of manufacturing firms," Journal of Environmental Economics and Management, Elsevier, vol. 101(C).
    9. Liu, Lingxuan & Zhang, Bing & Bi, Jun & Wei, Qi & He, Pan, 2012. "The greenhouse gas mitigation of industrial parks in China: A case study of Suzhou Industrial Park," Energy Policy, Elsevier, vol. 46(C), pages 301-307.
    10. Teresa Annunziata Branca & Barbara Fornai & Valentina Colla & Maria Ilaria Pistelli & Eros Luciano Faraci & Filippo Cirilli & Antonius Johannes Schröder, 2021. "Industrial Symbiosis and Energy Efficiency in European Process Industries: A Review," Sustainability, MDPI, vol. 13(16), pages 1-37, August.
    11. Matias Busso & Jesse Gregory & Patrick Kline, 2013. "Assessing the Incidence and Efficiency of a Prominent Place Based Policy," American Economic Review, American Economic Association, vol. 103(2), pages 897-947, April.
    12. Hu, Jin-Li & Wang, Shih-Chuan, 2006. "Total-factor energy efficiency of regions in China," Energy Policy, Elsevier, vol. 34(17), pages 3206-3217, November.
    13. He, Yongxiu & Guang, Fengtao & Wang, Meiyan, 2018. "The efficiency of electricity-use of China and its influencing factors," Energy, Elsevier, vol. 163(C), pages 258-269.
    14. Cheng, Zhonghua & Liu, Jun & Li, Lianshui & Gu, Xinbei, 2020. "Research on meta-frontier total-factor energy efficiency and its spatial convergence in Chinese provinces," Energy Economics, Elsevier, vol. 86(C).
    15. Broadstock, David C. & Li, Jiajia & Zhang, Dayong, 2016. "Efficiency snakes and energy ladders: A (meta-)frontier demand analysis of electricity consumption efficiency in Chinese households," Energy Policy, Elsevier, vol. 91(C), pages 383-396.
    16. Özkara, Yücel & Atak, Mehmet, 2015. "Regional total-factor energy efficiency and electricity saving potential of manufacturing industry in Turkey," Energy, Elsevier, vol. 93(P1), pages 495-510.
    17. Shi, Xunpeng & Sun, Sizhong, 2017. "Energy price, regulatory price distortion and economic growth: A case study of China," Energy Economics, Elsevier, vol. 63(C), pages 261-271.
    18. Fan, Meiting & Shao, Shuai & Yang, Lili, 2015. "Combining global Malmquist–Luenberger index and generalized method of moments to investigate industrial total factor CO2 emission performance: A case of Shanghai (China)," Energy Policy, Elsevier, vol. 79(C), pages 189-201.
    19. Mukherjee, Abhiroop & Singh, Manpreet & Žaldokas, Alminas, 2017. "Do corporate taxes hinder innovation?," Journal of Financial Economics, Elsevier, vol. 124(1), pages 195-221.
    20. Pastor, Jesus T. & Lovell, C.A. Knox, 2005. "A global Malmquist productivity index," Economics Letters, Elsevier, vol. 88(2), pages 266-271, August.
    21. Liddle, Brantley, 2009. "Electricity intensity convergence in IEA/OECD countries: Aggregate and sectoral analysis," Energy Policy, Elsevier, vol. 37(4), pages 1470-1478, April.
    22. Jan K. Kazak & Joanna A. Kamińska & Rafał Madej & Marta Bochenkiewicz, 2020. "Where Renewable Energy Sources Funds are Invested? Spatial Analysis of Energy Production Potential and Public Support," Energies, MDPI, vol. 13(21), pages 1-26, October.
    23. Ronald B. Davies, T. Huw Edwards, and Arman Mazhikeyev, 2018. "The Impact of Special Economic Zones on Electricity Intensity of Firms," The Energy Journal, International Association for Energy Economics, vol. 0(Special I).
    24. Jindao Chen & Yuhong Wang & Qian Shi & Xu Peng & Juhuan Zheng, 2021. "An international comparison analysis of CO2 emissions in the construction industry," Sustainable Development, John Wiley & Sons, Ltd., vol. 29(4), pages 754-767, July.
    25. Wang, Zhaohua & Feng, Chao & Zhang, Bin, 2014. "An empirical analysis of China's energy efficiency from both static and dynamic perspectives," Energy, Elsevier, vol. 74(C), pages 322-330.
    26. He, Yong & Fu, Feifei & Liao, Nuo, 2021. "Exploring the path of carbon emissions reduction in China’s industrial sector through energy efficiency enhancement induced by R&D investment," Energy, Elsevier, vol. 225(C).
    27. Twerefou, Daniel Kwabena & Abeney, Jacob Opantu, 2020. "Efficiency of household electricity consumption in Ghana," Energy Policy, Elsevier, vol. 144(C).
    28. Zhao, Hongli & Lin, Boqiang, 2019. "Will agglomeration improve the energy efficiency in China’s textile industry: Evidence and policy implications," Applied Energy, Elsevier, vol. 237(C), pages 326-337.
    29. Wang, Hongsheng & Lei, Yue & Wang, Haikun & Liu, Miaomiao & Yang, Jie & Bi, Jun, 2013. "Carbon reduction potentials of China's industrial parks: A case study of Suzhou Industry Park," Energy, Elsevier, vol. 55(C), pages 668-675.
    30. An, Qingxian & Wu, Qifan & Li, Jinlin & Xiong, Beibei & Chen, Xiaohong, 2019. "Environmental efficiency evaluation for Xiangjiang River basin cities based on an improved SBM model and Global Malmquist index," Energy Economics, Elsevier, vol. 81(C), pages 95-103.
    31. Fare, R. & Grosskopf, S. & Roos, P., 1995. "Productivity and quality changes in Swedish pharmacies," International Journal of Production Economics, Elsevier, vol. 39(1-2), pages 137-144, April.
    32. Inglesi-Lotz, Roula & Blignaut, James N., 2014. "Improving the electricity efficiency in South Africa through a benchmark-and-trade system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 30(C), pages 833-840.
    33. Du, Kerui & Lu, Huang & Yu, Kun, 2014. "Sources of the potential CO2 emission reduction in China: A nonparametric metafrontier approach," Applied Energy, Elsevier, vol. 115(C), pages 491-501.
    34. George Battese & D. Rao & Christopher O'Donnell, 2004. "A Metafrontier Production Function for Estimation of Technical Efficiencies and Technology Gaps for Firms Operating Under Different Technologies," Journal of Productivity Analysis, Springer, vol. 21(1), pages 91-103, January.
    35. Lin, Boqiang & Zhu, Junpeng, 2020. "Chinese electricity demand and electricity consumption efficiency: Do the structural changes matter?," Applied Energy, Elsevier, vol. 262(C).
    36. Yigitcanlar, Tan & Sabatini-Marques, Jamile & da-Costa, Eduardo Moreira & Kamruzzaman, Md & Ioppolo, Giuseppe, 2019. "Stimulating technological innovation through incentives: Perceptions of Australian and Brazilian firms," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 403-412.
    37. Ouyang, Xiaoling & Chen, Jiaqi & Du, Kerui, 2021. "Energy efficiency performance of the industrial sector: From the perspective of technological gap in different regions in China," Energy, Elsevier, vol. 214(C).
    38. Alkon, Meir, 2018. "Do special economic zones induce developmental spillovers? Evidence from India’s states," World Development, Elsevier, vol. 107(C), pages 396-409.
    Full references (including those not matched with items on IDEAS)

    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. Feng, Chao & Zhang, Hua & Huang, Jian-Bai, 2017. "The approach to realizing the potential of emissions reduction in China: An implication from data envelopment analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 71(C), pages 859-872.
    2. Qin, Quande & Li, Xin & Li, Li & Zhen, Wei & Wei, Yi-Ming, 2017. "Air emissions perspective on energy efficiency: An empirical analysis of China’s coastal areas," Applied Energy, Elsevier, vol. 185(P1), pages 604-614.
    3. Feng, Chao & Wang, Miao, 2018. "Analysis of energy efficiency in China's transportation sector," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 565-575.
    4. Feng, Chao & Wang, Miao & Liu, Guan-Chun & Huang, Jian-Bai, 2017. "Sources of economic growth in China from 2000–2013 and its further sustainable growth path: A three-hierarchy meta-frontier data envelopment analysis," Economic Modelling, Elsevier, vol. 64(C), pages 334-348.
    5. Wang, Zhaohua & Feng, Chao, 2015. "Sources of production inefficiency and productivity growth in China: A global data envelopment analysis," Energy Economics, Elsevier, vol. 49(C), pages 380-389.
    6. Ying Xie & Minglong Zhang, 2023. "Influence of Clean Energy and Financial Structure on China’s Provincial Carbon Emission Efficiency—Empirical Analysis Based on Spatial Spillover Effects," Sustainability, MDPI, vol. 15(4), pages 1-25, February.
    7. Takayabu, Hirotaka, 2020. "CO2 mitigation potentials in manufacturing sectors of 26 countries," Energy Economics, Elsevier, vol. 86(C).
    8. Zhang, Hui & Zhou, Peng & Sun, Xiumei & Ni, Guanqun, 2024. "Disparities in energy efficiency and its determinants in Chinese cities: From the perspective of heterogeneity," Energy, Elsevier, vol. 289(C).
    9. Fang-Rong Ren & Ze Tian & Yu-Ting Shen & Yung-Ho Chiu & Tai-Yu Lin, 2019. "Energy, CO 2 , and AQI Efficiency and Improvement of the Yangtze River Economic Belt," Energies, MDPI, vol. 12(4), pages 1-17, February.
    10. Cheng, Zhonghua & Li, Lianshui & Liu, Jun & Zhang, Huiming, 2018. "Total-factor carbon emission efficiency of China's provincial industrial sector and its dynamic evolution," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 330-339.
    11. Chen, Weidong & Geng, Wenxin, 2017. "Fossil energy saving and CO2 emissions reduction performance, and dynamic change in performance considering renewable energy input," Energy, Elsevier, vol. 120(C), pages 283-292.
    12. He, Yongxiu & Guang, Fengtao & Wang, Meiyan, 2018. "The efficiency of electricity-use of China and its influencing factors," Energy, Elsevier, vol. 163(C), pages 258-269.
    13. Ying Li & Yung-Ho Chiu & Liang Chun Lu, 2018. "Regional Energy, CO 2 , and Economic and Air Quality Index Performances in China: A Meta-Frontier Approach," Energies, MDPI, vol. 11(8), pages 1-20, August.
    14. Bian, Yiwen & Hu, Miao & Wang, Yousen & Xu, Hao, 2016. "Energy efficiency analysis of the economic system in China during 1986–2012: A parallel slacks-based measure approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 990-998.
    15. Jinkai Li & Jingjing Ma & Wei Wei, 2020. "Analysis and Evaluation of the Regional Characteristics of Carbon Emission Efficiency for China," Sustainability, MDPI, vol. 12(8), pages 1-22, April.
    16. Lin, Boqiang & Sai, Rockson, 2022. "Has mining agglomeration affected energy productivity in Africa?," Energy, Elsevier, vol. 244(PA).
    17. Zhi Li & Lu Lv & Zuo Zhang, 2022. "Research on the Characteristics and Influencing Factors of Chinese Urban Households’ Electricity Consumption Efficiency," Energies, MDPI, vol. 15(20), pages 1-15, October.
    18. Zhang, Ning & Wang, Bing & Liu, Zhu, 2016. "Carbon emissions dynamics, efficiency gains, and technological innovation in China's industrial sectors," Energy, Elsevier, vol. 99(C), pages 10-19.
    19. Xiangyu Teng & Danting Lu & Yung-ho Chiu, 2019. "Emission Reduction and Energy Performance Improvement with Different Regional Treatment Intensity in China," Energies, MDPI, vol. 12(2), pages 1-18, January.
    20. Wang, Zhaohua & Feng, Chao & Zhang, Bin, 2014. "An empirical analysis of China's energy efficiency from both static and dynamic perspectives," Energy, Elsevier, vol. 74(C), pages 322-330.

    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:17:p:5468-:d:627685. 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.