IDEAS home Printed from https://ideas.repec.org/a/eee/eneeco/v91y2020ics0140988320302711.html
   My bibliography  Save this article

Assessment and optimization of provincial CO2 emission reduction scheme in China: An improved ZSG-DEA approach

Author

Listed:
  • Yang, Mian
  • Hou, Yaru
  • Ji, Qiang
  • Zhang, Dayong

Abstract

This paper applies the zero-sum gains data envelopment analysis (ZSG-DEA) model to assess the provincial CO2 emission reduction scheme of China in 2020 and then calculates optimized values for the provinces in 2030. Results from two standard optimization procedures to solve the ZSG-DEA model are compared. We also extend the current methods by improving the iterative approach and then introduce fairness to the efficiency-oriented approach for the 2030 case. We found that the choice of optimization procedures has only a minimal impact on the results, but the specification of model does matter. For 2020, a standard DEA approach shows that only 2 provinces out of 30 are efficient. According to the estimation results of the ZSG-DEA model, 12 provinces need to set higher reduction targets, whereas the other 18 provinces could have lower target values to achieve overall efficiency. These results are generally consistent across different optimization approaches. The improved approach is applied to further evaluate a number of scenarios in 2030, in which the adjustment values towards optimum can be calculated for each scenario. Furthermore, we show that the inclusion of fairness can significantly affect the adjustment targets, which is of great importance to policymakers

Suggested Citation

  • Yang, Mian & Hou, Yaru & Ji, Qiang & Zhang, Dayong, 2020. "Assessment and optimization of provincial CO2 emission reduction scheme in China: An improved ZSG-DEA approach," Energy Economics, Elsevier, vol. 91(C).
    • Handle: RePEc:eee:eneeco:v:91:y:2020:i:c:s0140988320302711
    DOI: 10.1016/j.eneco.2020.104931
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0140988320302711
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.eneco.2020.104931?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. Beasley, J. E., 2003. "Allocating fixed costs and resources via data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 147(1), pages 198-216, May.
    2. Li, Yan & Wei, Yigang & Zhang, Xiaoling & Tao, Yuan, 2020. "Regional and provincial CO2 emission reduction task decomposition of China's 2030 carbon emission peak based on the efficiency, equity and synthesizing principles," Structural Change and Economic Dynamics, Elsevier, vol. 53(C), pages 237-256.
    3. Ma, Gang & Li, Xu & Zheng, Jianping, 2020. "Efficiency and equity in regional coal de-capacity allocation in China: A multiple objective programming model based on Gini coefficient and Data Envelopment Analysis," Resources Policy, Elsevier, vol. 66(C).
    4. Wang, Ying & Zhang, Dayong & Ji, Qiang & Shi, Xunpeng, 2020. "Regional renewable energy development in China: A multidimensional assessment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 124(C).
    5. Dayong Zhang & David C. Broadstock, 2016. "Club Convergence in the Energy Intensity of China," The Energy Journal, , vol. 37(3), pages 137-158, July.
    6. Yang, Mian & Yang, Fuxia & Sun, Chuanwang, 2018. "Factor market distortion correction, resource reallocation and potential productivity gains: An empirical study on China's heavy industry sector," Energy Economics, Elsevier, vol. 69(C), pages 270-279.
    7. Yue-Jun Zhang & Jun-Fang Hao, 2017. "Carbon emission quota allocation among China’s industrial sectors based on the equity and efficiency principles," Annals of Operations Research, Springer, vol. 255(1), pages 117-140, August.
    8. Wang, Ke & Zhang, Xian & Wei, Yi-Ming & Yu, Shiwei, 2013. "Regional allocation of CO2 emissions allowance over provinces in China by 2020," Energy Policy, Elsevier, vol. 54(C), pages 214-229.
    9. E G Gomes & M P E Lins, 2008. "Modelling undesirable outputs with zero sum gains data envelopment analysis models," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(5), pages 616-623, May.
    10. Wu, Jie & Zhu, Qingyuan & Liang, Liang, 2016. "CO2 emissions and energy intensity reduction allocation over provincial industrial sectors in China," Applied Energy, Elsevier, vol. 166(C), pages 282-291.
    11. Lins, Marcos P. Estellita & Gomes, Eliane G. & Soares de Mello, Joao Carlos C. B. & Soares de Mello, Adelino Jose R., 2003. "Olympic ranking based on a zero sum gains DEA model," European Journal of Operational Research, Elsevier, vol. 148(2), pages 312-322, July.
    12. Wang, Qunwei & Chiu, Yung-Ho & Chiu, Ching-Ren, 2015. "Driving factors behind carbon dioxide emissions in China: A modified production-theoretical decomposition analysis," Energy Economics, Elsevier, vol. 51(C), pages 252-260.
    13. Lozano, S. & Villa, G. & Brännlund, R., 2009. "Centralised reallocation of emission permits using DEA," European Journal of Operational Research, Elsevier, vol. 193(3), pages 752-760, March.
    14. Ji, Qiang & Zhang, Dayong, 2019. "How much does financial development contribute to renewable energy growth and upgrading of energy structure in China?," Energy Policy, Elsevier, vol. 128(C), pages 114-124.
    15. Li, Jun & Zhang, Dayong & Su, Bin, 2019. "The Impact of Social Awareness and Lifestyles on Household Carbon Emissions in China," Ecological Economics, Elsevier, vol. 160(C), pages 145-155.
    16. Wang, Qunwei & Hang, Ye & Su, Bin & Zhou, Peng, 2018. "Contributions to sector-level carbon intensity change: An integrated decomposition analysis," Energy Economics, Elsevier, vol. 70(C), pages 12-25.
    17. Fang, Kai & Zhang, Qifeng & Long, Yin & Yoshida, Yoshikuni & Sun, Lu & Zhang, Haoran & Dou, Yi & Li, Shuai, 2019. "How can China achieve its Intended Nationally Determined Contributions by 2030? A multi-criteria allocation of China’s carbon emission allowance," Applied Energy, Elsevier, vol. 241(C), pages 380-389.
    18. Yi, Wen-Jing & Zou, Le-Le & Guo, Jie & Wang, Kai & Wei, Yi-Ming, 2011. "How can China reach its CO2 intensity reduction targets by 2020? A regional allocation based on equity and development," Energy Policy, Elsevier, vol. 39(5), pages 2407-2415, May.
    19. Pang, Rui-zhi & Deng, Zhong-qi & Chiu, Yung-ho, 2015. "Pareto improvement through a reallocation of carbon emission quotas," Renewable and Sustainable Energy Reviews, Elsevier, vol. 50(C), pages 419-430.
    20. Wang, Qunwei & Su, Bin & Zhou, Peng & Chiu, Ching-Ren, 2016. "Measuring total-factor CO2 emission performance and technology gaps using a non-radial directional distance function: A modified approach," Energy Economics, Elsevier, vol. 56(C), pages 475-482.
    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. Yu, Anyu & Lee, Andy & Chen, Yao, 2021. "Carbon allocation targeting with abatement capability: A firm-level study," International Journal of Production Economics, Elsevier, vol. 235(C).
    2. Fang, Kai & Zhang, Qifeng & Long, Yin & Yoshida, Yoshikuni & Sun, Lu & Zhang, Haoran & Dou, Yi & Li, Shuai, 2019. "How can China achieve its Intended Nationally Determined Contributions by 2030? A multi-criteria allocation of China’s carbon emission allowance," Applied Energy, Elsevier, vol. 241(C), pages 380-389.
    3. Anyu Yu & Hao Zhang & Hu-chen Liu & Yu Shi & Weilong Bi, 2024. "Dynamic centralized resource allocation approach with contextual impacts: analyzing Chinese carbon allocation plans," Annals of Operations Research, Springer, vol. 341(1), pages 451-483, October.
    4. Jiekun Song & Rui Chen & Xiaoping Ma, 2022. "Provincial Allocation of Energy Consumption, Air Pollutant and CO 2 Emission Quotas in China: Based on a Weighted Environment ZSG-DEA Model," Sustainability, MDPI, vol. 14(4), pages 1-21, February.
    5. Sun, J. & Wen, W. & Wang, M. & Zhou, P., 2022. "Optimizing the provincial target allocation scheme of renewable portfolio standards in China," Energy, Elsevier, vol. 250(C).
    6. Zhou, P. & Wang, M., 2016. "Carbon dioxide emissions allocation: A review," Ecological Economics, Elsevier, vol. 125(C), pages 47-59.
    7. Xie, Qiwei & Xu, Qifan & Zhu, Da & Rao, Kaifeng & Dai, Qianzhi, 2020. "Fair allocation of wastewater discharge permits based on satisfaction criteria using data envelopment analysis," Utilities Policy, Elsevier, vol. 66(C).
    8. Jie Wu & Jun-Fei Chu & Liang Liang, 2016. "Target setting and allocation of carbon emissions abatement based on DEA and closest target: an application to 20 APEC economies," 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. 84(1), pages 279-296, November.
    9. Xi Jin & Bin Zou & Chan Wang & Kaifeng Rao & Xiaowen Tang, 2019. "Carbon Emission Allocation in a Chinese Province-Level Region Based on Two-Stage Network Structures," Sustainability, MDPI, vol. 11(5), pages 1-24, March.
    10. Shi, Wei & Li, Wei & Qiao, Fuwei & Wang, Weijuan & An, Yi & Zhang, Guowei, 2023. "An inter-provincial carbon quota study in China based on the contribution of clean energy to carbon reduction," Energy Policy, Elsevier, vol. 182(C).
    11. Wang, Ke & Zhang, Xian & Wei, Yi-Ming & Yu, Shiwei, 2013. "Regional allocation of CO2 emissions allowance over provinces in China by 2020," Energy Policy, Elsevier, vol. 54(C), pages 214-229.
    12. Yang, Mian & Hou, Yaru & Fang, Chao & Duan, Hongbo, 2020. "Constructing energy-consuming right trading system for China's manufacturing industry in 2025," Energy Policy, Elsevier, vol. 144(C).
    13. Xin Zheng & Shenya Mao & Siqi Lv & Sheng Wang, 2022. "An Optimization Study of Provincial Carbon Emission Allowance Allocation in China Based on an Improved Dynamic Zero-Sum-Gains Slacks-Based-Measure Model," Sustainability, MDPI, vol. 14(12), pages 1-22, June.
    14. Feng, Zhiying & Tang, Wenhu & Niu, Zhewen & Wu, Qinghua, 2018. "Bi-level allocation of carbon emission permits based on clustering analysis and weighted voting: A case study in China," Applied Energy, Elsevier, vol. 228(C), pages 1122-1135.
    15. Chu, Junfei & Hou, Tianteng & Li, Feng & Yuan, Zhe, 2024. "Dynamic bargaining game DEA carbon emissions abatement allocation and the Nash equilibrium," Energy Economics, Elsevier, vol. 134(C).
    16. Siqin Xiong & Yushen Tian & Junping Ji & Xiaoming Ma, 2017. "Allocation of Energy Consumption among Provinces in China: A Weighted ZSG-DEA Model," Sustainability, MDPI, vol. 9(11), pages 1-12, November.
    17. A Z Milioni & J V G de Avellar & T N Rabello & G M de Freitas, 2011. "Hyperbolic frontier model: a parametric DEA approach for the distribution of a total fixed output," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(6), pages 1029-1037, June.
    18. Han, Rong & Li, Jianglong & Guo, Zhi, 2022. "Optimal quota in China's energy capping policy in 2030 with renewable targets and sectoral heterogeneity," Energy, Elsevier, vol. 239(PA).
    19. Zhao, Zhibo & Shi, Xunpeng & Zhao, Lingdi & Zhang, Jinggu, 2020. "Extending production-theoretical decomposition analysis to environmentally sensitive growth: Case study of Belt and Road Initiative countries," Technological Forecasting and Social Change, Elsevier, vol. 161(C).
    20. Zhu, Qingyuan & Li, Xingchen & Li, Feng & Wu, Jie & Zhou, Dequn, 2020. "Energy and environmental efficiency of China's transportation sectors under the constraints of energy consumption and environmental pollutions," Energy Economics, Elsevier, vol. 89(C).

    More about this item

    Keywords

    CO2 emissions; DEA; Efficiency; Fairness; ZSG-DEA;
    All these keywords.

    JEL classification:

    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:91:y:2020:i:c:s0140988320302711. 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.