IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v16y2024i17p7318-d1464000.html

Measurement and Spatial-Temporal Evolution of Industrial Carbon Emission Efficiency in Western China

Author

Listed:
  • Ruixia Suo

    (School of Management, Xi’an University of Science and Technology, Xi’an 710054, China)

  • Yangyuqing Bai

    (School of Management, Xi’an University of Science and Technology, Xi’an 710054, China)

Abstract

As it is an important industrial base in China, it is of great significance to improve the industrial carbon emission efficiency in the western region to promote the low-carbon sustainable development of the region. This paper selects the input–output panel data of 11 provinces in western China from 2010 to 2021, and adopts the three-stage DEA model to measure the industrial carbon emission efficiency in western China under a non-traditional geographic division at the overall and regional levels and analyze its influencing factors. The Dagum Gini coefficient, its decomposition method, and the kernel density estimation method are used to analyze the regional differences and dynamic evolution process of industrial carbon emission efficiency in the western region. The results of the study show that (1) after removing environmental and random factors, the industrial carbon emission efficiency in western China has been improved, but there are inter-regional differences, characterized by “the third region > the second region > the first region”; (2) the levels of green development, shared development, innovative development, and coordinated development have a positive impact on the improvement of industrial carbon emission efficiency in western China, while the level of industrialization has a relatively smaller influence, and economic development, government support, open development level, and energy consumption structure have not yet played a significant role; (3) the spatial differences in the efficiency of industrial carbon emissions in western China have generally increased during the sample period, with inter-regional differences being the main source; and (4) the industrial carbon emission efficiency in western China is characterized by overall improvements in time and space but with stage differences and multi-polarization of regional differences. This study has a certain reference value for improving industrial carbon emission efficiency in western China.

Suggested Citation

  • Ruixia Suo & Yangyuqing Bai, 2024. "Measurement and Spatial-Temporal Evolution of Industrial Carbon Emission Efficiency in Western China," Sustainability, MDPI, vol. 16(17), pages 1-27, August.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:17:p:7318-:d:1464000
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/16/17/7318/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/16/17/7318/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Chai, Jian & Tian, Lingyue & Jia, Ruining, 2023. "New energy demonstration city, spatial spillover and carbon emission efficiency: Evidence from China's quasi-natural experiment," Energy Policy, Elsevier, vol. 173(C).
    2. H. Fried & C. Lovell & S. Schmidt & S. Yaisawarng, 2002. "Accounting for Environmental Effects and Statistical Noise in Data Envelopment Analysis," Journal of Productivity Analysis, Springer, vol. 17(1), pages 157-174, January.
    3. Sun, J. W., 2005. "The decrease of CO2 emission intensity is decarbonization at national and global levels," Energy Policy, Elsevier, vol. 33(8), pages 975-978, May.
    4. 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.
    5. Han, Yongming & Geng, Zhiqiang & Zhu, Qunxiong & Qu, Yixin, 2015. "Energy efficiency analysis method based on fuzzy DEA cross-model for ethylene production systems in chemical industry," Energy, Elsevier, vol. 83(C), pages 685-695.
    6. Seiford, Lawrence M. & Zhu, Joe, 2002. "Modeling undesirable factors in efficiency evaluation," European Journal of Operational Research, Elsevier, vol. 142(1), pages 16-20, October.
    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. Dong, Feng & Li, Xiaohui & Long, Ruyin & Liu, Xiaoyan, 2013. "Regional carbon emission performance in China according to a stochastic frontier model," Renewable and Sustainable Energy Reviews, Elsevier, vol. 28(C), pages 525-530.
    2. Feng Dong & Ruyin Long & Zhengfu Bian & Xihui Xu & Bolin Yu & Ying Wang, 2017. "Applying a Ruggiero three-stage super-efficiency DEA model to gauge regional carbon emission efficiency: evidence from China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 87(3), pages 1453-1468, July.
    3. Ding, Li-Li & Lei, Liang & Zhao, Xin & Calin, Adrian Cantemir, 2020. "Modelling energy and carbon emission performance: A constrained performance index measure," Energy, Elsevier, vol. 197(C).
    4. 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.
    5. Jens Kjærsgaard & Niels Vestergaard & Kristiaan Kerstens, 2009. "Ecological Benchmarking to Explore Alternative Fishing Schemes to Protect Endangered Species by Substitution: The Danish Demersal Fishery in the North Sea," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 43(4), pages 573-590, August.
    6. Wang, Q.W. & Zhou, P. & Shen, N. & Wang, S.S., 2013. "Measuring carbon dioxide emission performance in Chinese provinces: A parametric approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 21(C), pages 324-330.
    7. Guo, Xiao-Dan & Zhu, Lei & Fan, Ying & Xie, Bai-Chen, 2011. "Evaluation of potential reductions in carbon emissions in Chinese provinces based on environmental DEA," Energy Policy, Elsevier, vol. 39(5), pages 2352-2360, May.
    8. Zhang, Bin & Lu, Danting & He, Yan & Chiu, Yung-ho, 2018. "The efficiencies of resource-saving and environment: A case study based on Chinese cities," Energy, Elsevier, vol. 150(C), pages 493-507.
    9. Juan Du & Yongrui Duan & Jinghua Xu, 2019. "The infeasible problem of Malmquist–Luenberger index and its application on China’s environmental total factor productivity," Annals of Operations Research, Springer, vol. 278(1), pages 235-253, July.
    10. Tavana, Madjid & Ebrahimnejad, Ali & Santos-Arteaga, Francisco J. & Mansourzadeh, Seyed Mehdi & Matin, Reza Kazemi, 2018. "A hybrid DEA-MOLP model for public school assessment and closure decision in the City of Philadelphia," Socio-Economic Planning Sciences, Elsevier, vol. 61(C), pages 70-89.
    11. Jianglong Li & Boqiang Lin, 2016. "Green Economy Performance and Green Productivity Growth in China’s Cities: Measures and Policy Implication," Sustainability, MDPI, vol. 8(9), pages 1-21, September.
    12. Xing Zhao & Xin Zhang, 2022. "Research on the Evaluation and Regional Differences in Carbon Emissions Efficiency of Cultural and Related Manufacturing Industries in China’s Yangtze River Basin," Sustainability, MDPI, vol. 14(17), pages 1-22, August.
    13. Zhou, Haibo & Yang, Yi & Chen, Yao & Zhu, Joe, 2018. "Data envelopment analysis application in sustainability: The origins, development and future directions," European Journal of Operational Research, Elsevier, vol. 264(1), pages 1-16.
    14. Eyad Aldalou & Selçuk Perçin, 2025. "An innovative approach to evaluating sustainable development performance: The case of Turkey," Natural Resources Forum, Blackwell Publishing, vol. 49(1), pages 358-383, February.
    15. Cordero Ferrera, Jose Manuel & Alonso Morán, Edurne & Nuño Solís, Roberto & Orueta, Juan F. & Souto Arce, Regina, 2013. "Efficiency assessment of primary care providers: A conditional nonparametric approach," MPRA Paper 51926, University Library of Munich, Germany.
    16. Meng Ye & Yanan Jin & Fumin Deng, 2022. "Municipal waste treatment efficiency in 29 OECD countries using three-stage Bootstrap-DEA model," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(9), pages 11369-11391, September.
    17. Senchang Hu & Shaoyi Li & Xiangxin Meng & Yingzheng Peng & Wenzhe Tang, 2023. "Study on Regional Differences of Carbon Emission Efficiency: Evidence from Chinese Construction Industry," Energies, MDPI, vol. 16(19), pages 1-20, September.
    18. Wang, Qunwei & Su, Bin & Sun, Jiasen & Zhou, Peng & Zhou, Dequn, 2015. "Measurement and decomposition of energy-saving and emissions reduction performance in Chinese cities," Applied Energy, Elsevier, vol. 151(C), pages 85-92.
    19. Xian’En Wang & Shimeng Wang & Xipan Wang & Wenbo Li & Junnian Song & Haiyan Duan & Shuo Wang, 2019. "The Assessment of Carbon Performance under the Region-Sector Perspective based on the Nonparametric Estimation: A Case Study of the Northern Province in China," Sustainability, MDPI, vol. 11(21), pages 1-23, October.
    20. Zhang, Wei & Liu, Xuemeng & Wang, Die & Zhou, Jianping, 2022. "Digital economy and carbon emission performance: Evidence at China's city level," Energy Policy, Elsevier, vol. 165(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    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:gam:jsusta:v:16:y:2024:i:17:p:7318-:d:1464000. 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.