[go: up one dir, main page]

IDEAS home Printed from https://ideas.repec.org/a/eee/proeco/v235y2021ics0925527321000682.html
   My bibliography  Save this article

Carbon allocation targeting with abatement capability: A firm-level study

Author

Listed:
  • Yu, Anyu
  • Lee, Andy
  • Chen, Yao
Abstract
The allocation mechanism of carbon abatement quotas is an important regulation to abate carbon emissions. Data envelopment analysis (DEA) is adopted in this study to measure the allocation among industrial firms. Different from previous studies, our research takes the carbon abatement capability (CAC) as one crucial focus. A DEA model is developed to measure the CAC by using slacks. A novel centralized allocation model incorporating the slacks-based target is proposed, with both DEA-determined and user-determined settings of carbon abatement bounds. We further propose two scenarios to represent the utilization possibilities of CAC in allocation, and they are CAC-minimum and maximum scenarios. The CAC-minimum scenario is defined as making full use of the CAC in allocation, while the CAC- maximum scenario focuses on reserving the most CAC for the future. Both mechanisms are applied to an application of 499 Chinese industrial firms to determine the effectiveness. By measuring the allocation results between the two scenarios, the consideration of CAC is proved to affect the allocation significantly. Comparisons in allocation results between scenarios and between different firm groups are also investigated. Firms in CAC-minimum scenario will make full use of current CAC to achieve the allocation. Such allocation would result in less economic loss and require minimal technological progress. Firms in CAC-maximum scenario are more environmental-friendly and aim to achieve the most carbon abatement possible. This allocation scenario should be advocated to enhance the firm's future competitiveness. Both scenarios are analyzed in the research to design a balanced allocation.

Suggested Citation

  • 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).
  • Handle: RePEc:eee:proeco:v:235:y:2021:i:c:s0925527321000682
    DOI: 10.1016/j.ijpe.2021.108092
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0925527321000682
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ijpe.2021.108092?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. William W. Cooper & Lawrence M. Seiford & Joe Zhu (ed.), 2011. "Handbook on Data Envelopment Analysis," International Series in Operations Research and Management Science, Springer, number 978-1-4419-6151-8, December.
    2. Wang, Ke & Wei, Yi-Ming & Huang, Zhimin, 2016. "Potential gains from carbon emissions trading in China: A DEA based estimation on abatement cost savings," Omega, Elsevier, vol. 63(C), pages 48-59.
    3. Choi, Yongrok & Zhang, Ning & Zhou, P., 2012. "Efficiency and abatement costs of energy-related CO2 emissions in China: A slacks-based efficiency measure," Applied Energy, Elsevier, vol. 98(C), pages 198-208.
    4. Yu, Shiwei & Wei, Yi-Ming & Wang, Ke, 2014. "Provincial allocation of carbon emission reduction targets in China: An approach based on improved fuzzy cluster and Shapley value decomposition," Energy Policy, Elsevier, vol. 66(C), pages 630-644.
    5. Boaz Golany & Eran Tamir, 1995. "Evaluating Efficiency-Effectiveness-Equality Trade-Offs: A Data Envelopment Analysis Approach," Management Science, INFORMS, vol. 41(7), pages 1172-1184, July.
    6. Chen, Kun & Zhu, Joe, 2019. "Computational tractability of chance constrained data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 274(3), pages 1037-1046.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. He, Weijun & Yang, Yi & Wang, Zhaohua & Zhu, Joe, 2018. "Estimation and allocation of cost savings from collaborative CO2 abatement in China," Energy Economics, Elsevier, vol. 72(C), pages 62-74.
    12. Yiwen Bian & Kangjuan Lv & Anyu Yu, 2017. "China’s regional energy and carbon dioxide emissions efficiency evaluation with the presence of recovery energy: an interval slacks-based measure approach," Annals of Operations Research, Springer, vol. 255(1), pages 301-321, August.
    13. Sebastián Lozano & Gabriel Villa, 2004. "Centralized Resource Allocation Using Data Envelopment Analysis," Journal of Productivity Analysis, Springer, vol. 22(1), pages 143-161, July.
    14. Chen, Kun & Zhu, Joe, 2017. "Second order cone programming approach to two-stage network data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 262(1), pages 231-238.
    15. Feng, Chenpeng & Chu, Feng & Ding, Jingjing & Bi, Gongbing & Liang, Liang, 2015. "Carbon Emissions Abatement (CEA) allocation and compensation schemes based on DEA," Omega, Elsevier, vol. 53(C), pages 78-89.
    16. Seiford, Lawrence M. & Zhu, Joe, 1999. "An investigation of returns to scale in data envelopment analysis," Omega, Elsevier, vol. 27(1), pages 1-11, February.
    17. Guo, Chuanyin & Wei, Fajie & Chen, Yao, 2017. "A note on second order cone programming approach to two-stage network data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 263(2), pages 733-735.
    18. Cook, Wade D. & Kress, Moshe, 1999. "Characterizing an equitable allocation of shared costs: A DEA approach," European Journal of Operational Research, Elsevier, vol. 119(3), pages 652-661, December.
    19. Zhang, Yue-Jun & Wang, Ao-Dong & Da, Ya-Bin, 2014. "Regional allocation of carbon emission quotas in China: Evidence from the Shapley value method," Energy Policy, Elsevier, vol. 74(C), pages 454-464.
    20. Yu, Anyu & You, Jianxin & Rudkin, Simon & Zhang, Hao, 2019. "Industrial carbon abatement allocations and regional collaboration: Re-evaluating China through a modified data envelopment analysis," Applied Energy, Elsevier, vol. 233, pages 232-243.
    21. 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.
    22. 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.
    23. 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.
    24. Jiasen Sun & Yelin Fu & Xiang Ji & Ray Y. Zhong, 2017. "Allocation of emission permits using DEA-game-theoretic model," Operational Research, Springer, vol. 17(3), pages 867-884, October.
    25. Mahdiloo, Mahdi & Ngwenyama, Ojelanki & Scheepers, Rens & Tamaddoni, Ali, 2018. "Managing emissions allowances of electricity producers to maximize CO2 abatement: DEA models for analyzing emissions and allocating emissions allowances," International Journal of Production Economics, Elsevier, vol. 205(C), pages 244-255.
    26. 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.
    27. Ciardiello, F. & Genovese, A. & Simpson, A., 2019. "Pollution responsibility allocation in supply networks: A game-theoretic approach and a case study," International Journal of Production Economics, Elsevier, vol. 217(C), pages 211-217.
    28. Zhu, Bangzhu & Jiang, Mingxing & He, Kaijian & Chevallier, Julien & Xie, Rui, 2018. "Allocating CO2 allowances to emitters in China: A multi-objective decision approach," Energy Policy, Elsevier, vol. 121(C), pages 441-451.
    29. 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.
    30. Jiang, Bing & Sun, Zhenqing & Liu, Meiqin, 2010. "China's energy development strategy under the low-carbon economy," Energy, Elsevier, vol. 35(11), pages 4257-4264.
    31. Tone, Kaoru, 2001. "A slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 498-509, May.
    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. Rahmoune, Mahdi & Radjef, Mohammed Said & Boukherroub, Tasseda & Carvalho, Margarida, 2024. "A new integrated cooperative game and optimization model for the allocation of forest resources," European Journal of Operational Research, Elsevier, vol. 316(1), pages 329-340.
    2. 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.
    3. 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).
    4. Linghu, Dazhi & Wu, Xilin & Lai, Kee-Hung & Ye, Fei & Kumar, Ajay & Tan, Kim Hua, 2022. "Implementation strategy and emission reduction effectiveness of carbon cap-and-trade in heterogeneous enterprises," International Journal of Production Economics, Elsevier, vol. 248(C).
    5. Yutong Lang & Xiaoyu Ji & Yingtong Wang & Yingfu He, 2024. "Carbon Asset Management Mode Selection for Capital-Constrained Enterprises," Mathematics, MDPI, vol. 12(22), pages 1-29, November.

    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. 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.
    2. Yu, Anyu & You, Jianxin & Rudkin, Simon & Zhang, Hao, 2019. "Industrial carbon abatement allocations and regional collaboration: Re-evaluating China through a modified data envelopment analysis," Applied Energy, Elsevier, vol. 233, pages 232-243.
    3. 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).
    4. 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.
    5. 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.
    6. 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).
    7. Yongjun Li & Wenhui Hou & Weiwei Zhu & Feng Li & Liang Liang, 2021. "Provincial carbon emission performance analysis in China based on a Malmquist data envelopment analysis approach with fixed-sum undesirable outputs," Annals of Operations Research, Springer, vol. 304(1), pages 233-261, September.
    8. 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).
    9. Wu, Yinyin & Wang, Ping & Liu, Xin & Chen, Jiandong & Song, Malin, 2020. "Analysis of regional carbon allocation and carbon trading based on net primary productivity in China," China Economic Review, Elsevier, vol. 60(C).
    10. Zhou, P. & Wang, M., 2016. "Carbon dioxide emissions allocation: A review," Ecological Economics, Elsevier, vol. 125(C), pages 47-59.
    11. 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).
    12. 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.
    13. Lozano, Sebastián & Contreras, Ignacio, 2022. "Centralised resource allocation using Lexicographic Goal Programming. Application to the Spanish public university system," Socio-Economic Planning Sciences, Elsevier, vol. 84(C).
    14. 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.
    15. Shihong Zeng & Yan Xu & Liming Wang & Jiuying Chen & Qirong Li, 2016. "Forecasting the Allocative Efficiency of Carbon Emission Allowance Financial Assets in China at the Provincial Level in 2020," Energies, MDPI, vol. 9(5), pages 1-18, May.
    16. Jie Wu & Qingyuan Zhu & Junfei Chu & Qingxian An & Liang Liang, 2016. "A DEA-based approach for allocation of emission reduction tasks," International Journal of Production Research, Taylor & Francis Journals, vol. 54(18), pages 5618-5633, September.
    17. Tao Ding & Ya Chen & Huaqing Wu & Yuqi Wei, 2018. "Centralized fixed cost and resource allocation considering technology heterogeneity: a DEA approach," Annals of Operations Research, Springer, vol. 268(1), pages 497-511, September.
    18. Chen, Zhenling & Yuan, Xiao-Chen & Zhang, Xiaoling & Cao, Yunfei, 2020. "How will the Chinese national carbon emissions trading scheme work? The assessment of regional potential gains," Energy Policy, Elsevier, vol. 137(C).
    19. 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.
    20. 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.

    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:proeco:v:235:y:2021:i:c:s0925527321000682. 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/ijpe .

    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.