IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v274y2023ics0360544223007387.html
   My bibliography  Save this article

Congestion effects of energy and capital in China's carbon emission reduction: Evidence from provincial levels

Author

Listed:
  • Pang, Qinghua
  • Qiu, Man
  • Zhang, Lina
  • Chiu, Yung-ho

Abstract

Global carbon emission control and resource conservation are important measures to realize sustainable development goals. There are few researches on carbon emissions from the perspective of congestion with the data envelopment analysis method. Congestion effects not only help us to reduce carbon emissions, but also achieve reasonable allocation of resources. This paper expands traditional congestion into undesirable congestion and desirable congestion, and both are divided into undesirable congestion of energy (capital) and desirable congestion of energy (capital) in 30 Chinese provinces with a two-stage model. So, purely technical inefficiency is separated from congestion, and energy and capital utilization can be analyzed simultaneously. The results show that: (1) China has a higher carbon emission reduction potential under natural disposability than that under managerial disposability. (2) The number of provinces with undesirable congestion of energy in the eastern region is small, while that with undesirable congestion of capital in the western region is small. (3) The number of provinces with desirable congestion increases. Desirable congestion of energy and capital is mainly concentrated in the eastern and central regions. Exploring the congestion effects of energy and capital will help China to achieve “dual carbon” targets and promote the environmental, social, and governance investment.

Suggested Citation

  • Pang, Qinghua & Qiu, Man & Zhang, Lina & Chiu, Yung-ho, 2023. "Congestion effects of energy and capital in China's carbon emission reduction: Evidence from provincial levels," Energy, Elsevier, vol. 274(C).
    • Handle: RePEc:eee:energy:v:274:y:2023:i:c:s0360544223007387
    DOI: 10.1016/j.energy.2023.127344
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544223007387
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2023.127344?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. Noura, A.A. & Hosseinzadeh Lotfi, F. & Jahanshahloo, G.R. & Rashidi, S. Fanati & Parker, Barnett R., 2010. "A new method for measuring congestion in data envelopment analysis," Socio-Economic Planning Sciences, Elsevier, vol. 44(4), pages 240-246, December.
    2. Wang, En-Ze & Lee, Chien-Chiang, 2022. "The impact of clean energy consumption on economic growth in China: Is environmental regulation a curse or a blessing?," International Review of Economics & Finance, Elsevier, vol. 77(C), pages 39-58.
    3. Zhang, Yue-Jun & Liu, Jing-Yue & Su, Bin, 2020. "Carbon congestion effects in China's industry: Evidence from provincial and sectoral levels," Energy Economics, Elsevier, vol. 86(C).
    4. Zhao, Pengjun & Zeng, Liangen & Li, Peilin & Lu, Haiyan & Hu, Haoyu & Li, Chengming & Zheng, Mengyuan & Li, Haitao & Yu, Zhao & Yuan, Dandan & Xie, Jinxin & Huang, Qi & Qi, Yuting, 2022. "China's transportation sector carbon dioxide emissions efficiency and its influencing factors based on the EBM DEA model with undesirable outputs and spatial Durbin model," Energy, Elsevier, vol. 238(PC).
    5. Tone, Kaoru & Sahoo, Biresh K., 2004. "Degree of scale economies and congestion: A unified DEA approach," European Journal of Operational Research, Elsevier, vol. 158(3), pages 755-772, November.
    6. Zhong, Meirui & Huang, Gangli & He, Ruifang, 2022. "The technological innovation efficiency of China's lithium-ion battery listed enterprises: Evidence from a three-stage DEA model and micro-data," Energy, Elsevier, vol. 246(C).
    7. 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.
    8. Ang, James B., 2009. "CO2 emissions, research and technology transfer in China," Ecological Economics, Elsevier, vol. 68(10), pages 2658-2665, August.
    9. Sueyoshi, Toshiyuki & Wang, Derek, 2018. "DEA environmental assessment on US petroleum industry: Non-radial approach with translation invariance in time horizon," Energy Economics, Elsevier, vol. 72(C), pages 276-289.
    10. Cooper, William W. & Deng, H. & Huang, Zhimin & Li, Susan X., 2004. "Chance constrained programming approaches to congestion in stochastic data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 155(2), pages 487-501, June.
    11. Lee, Chi-Chuan & Lee, Chien-Chiang, 2022. "How does green finance affect green total factor productivity? Evidence from China," Energy Economics, Elsevier, vol. 107(C).
    12. Sueyoshi, Toshiyuki & Goto, Mika, 2014. "Investment strategy for sustainable society by development of regional economies and prevention of industrial pollutions in Japanese manufacturing sectors," Energy Economics, Elsevier, vol. 42(C), pages 299-312.
    13. Toshiyuki Sueyoshi & Yan Yuan & Aijun Li & Daoping Wang, 2017. "Social Sustainability of Provinces in China: A Data Envelopment Analysis (DEA) Window Analysis under the Concepts of Natural and Managerial Disposability," Sustainability, MDPI, vol. 9(11), pages 1-18, November.
    14. 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.
    15. Cooper, W. W. & Deng, Honghui & Huang, Zhimin M. & Li, Susan X., 2002. "A one-model approach to congestion in data envelopment analysis," Socio-Economic Planning Sciences, Elsevier, vol. 36(4), pages 231-238, December.
    16. Wei, Quanling & Yan, Hong, 2004. "Congestion and returns to scale in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 153(3), pages 641-660, March.
    17. Sueyoshi, Toshiyuki & Goto, Mika, 2012. "Returns to scale and damages to scale on U.S. fossil fuel power plants: Radial and non-radial approaches for DEA environmental assessment," Energy Economics, Elsevier, vol. 34(6), pages 2240-2259.
    18. Sueyoshi, Toshiyuki & Goto, Mika, 2019. "The intermediate approach to sustainability enhancement and scale-related measures in environmental assessment," European Journal of Operational Research, Elsevier, vol. 276(2), pages 744-756.
    19. Sueyoshi, Toshiyuki & Goto, Mika & Ueno, Takahiro, 2010. "Performance analysis of US coal-fired power plants by measuring three DEA efficiencies," Energy Policy, Elsevier, vol. 38(4), pages 1675-1688, April.
    20. Fare, Rolf, et al, 1989. "Multilateral Productivity Comparisons When Some Outputs Are Undesirable: A Nonparametric Approach," The Review of Economics and Statistics, MIT Press, vol. 71(1), pages 90-98, February.
    21. Xu, Bin & Lin, Boqiang, 2019. "Can expanding natural gas consumption reduce China's CO2 emissions?," Energy Economics, Elsevier, vol. 81(C), pages 393-407.
    22. Chen, Zhenling & Li, Jinkai & Zhao, Weigang & Yuan, Xiao-Chen & Yang, Guo-liang, 2019. "Undesirable and desirable energy congestion measurements for regional coal-fired power generation industry in China," Energy Policy, Elsevier, vol. 125(C), pages 122-134.
    23. Cooper, William W. & Seiford, Lawrence M. & Zhu, Joe, 2000. "A unified additive model approach for evaluating inefficiency and congestion with associated measures in DEA," Socio-Economic Planning Sciences, Elsevier, vol. 34(1), pages 1-25, March.
    24. Hao, Yu & Wang, Ling-Ou & Lee, Chien-Chiang, 2020. "Financial development, energy consumption and China's economic growth: New evidence from provincial panel data," International Review of Economics & Finance, Elsevier, vol. 69(C), pages 1132-1151.
    25. Sueyoshi, Toshiyuki & Goto, Mika, 2012. "DEA radial and non-radial models for unified efficiency under natural and managerial disposability: Theoretical extension by strong complementary slackness conditions," Energy Economics, Elsevier, vol. 34(3), pages 700-713.
    26. Fare, Rolf & Svensson, Leif, 1980. "Congestion of Production Factors," Econometrica, Econometric Society, vol. 48(7), pages 1745-1753, November.
    27. Cooper, W. W. & Deng, Honghui & Gu, Bisheng & Li, Shanling & Thrall, R. M., 2001. "Using DEA to improve the management of congestion in Chinese industries (1981-1997)," Socio-Economic Planning Sciences, Elsevier, vol. 35(4), pages 227-242, December.
    28. Yue-Jun Zhang & Jing-Yue Liu, 2019. "Does carbon emissions trading affect the financial performance of high energy-consuming firms in 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. 95(1), pages 91-111, January.
    29. Sueyoshi, Toshiyuki & Goto, Mika, 2016. "Undesirable congestion under natural disposability and desirable congestion under managerial disposability in U.S. electric power industry measured by DEA environmental assessment," Energy Economics, Elsevier, vol. 55(C), pages 173-188.
    30. Sueyoshi, Toshiyuki & Goto, Mika, 2012. "Weak and strong disposability vs. natural and managerial disposability in DEA environmental assessment: Comparison between Japanese electric power industry and manufacturing industries," Energy Economics, Elsevier, vol. 34(3), pages 686-699.
    31. Cooper, W. W. & Gu, Bisheng & Li, Shanling, 2001. "Comparisons and evaluations of alternative approaches to the treatment of congestion in DEA," European Journal of Operational Research, Elsevier, vol. 132(1), pages 62-74, July.
    32. Fare, R. & Grosskopf, S. & Pasurka, C., 1986. "Effects on relative efficiency in electric power generation due to environmental controls," Resources and Energy, Elsevier, vol. 8(2), pages 167-184, June.
    33. Hunjra, Ahmed Imran & Kijkasiwat, Ploypailin & Arunachalam, Murugesh & Hammami, Helmi, 2021. "Covid-19 health policy intervention and volatility of Asian capital markets," Technological Forecasting and Social Change, Elsevier, vol. 169(C).
    34. Sueyoshi, Toshiyuki & Goto, Mika, 2018. "Resource utilization for sustainability enhancement in Japanese industries," Applied Energy, Elsevier, vol. 228(C), pages 2308-2320.
    35. Sueyoshi, Toshiyuki & Goto, Mika, 2014. "Environmental assessment for corporate sustainability by resource utilization and technology innovation: DEA radial measurement on Japanese industrial sectors," Energy Economics, Elsevier, vol. 46(C), pages 295-307.
    36. Sueyoshi, Toshiyuki & Goto, Mika, 2012. "Environmental assessment by DEA radial measurement: U.S. coal-fired power plants in ISO (Independent System Operator) and RTO (Regional Transmission Organization)," Energy Economics, Elsevier, vol. 34(3), pages 663-676.
    37. Fare, Rolf & Grosskopf, Shawna & Yoon, Bong Joon, 1982. "A theoretical and empirical analysis of the highway speed-volume relationship," Journal of Urban Economics, Elsevier, vol. 12(1), pages 115-121, July.
    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. Liu, Bingchun & Huo, Xiankai, 2024. "Prediction of Photovoltaic power generation and analyzing of carbon emission reduction capacity in China," Renewable Energy, Elsevier, vol. 222(C).

    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. Zhang, Yue-Jun & Liu, Jing-Yue & Su, Bin, 2020. "Carbon congestion effects in China's industry: Evidence from provincial and sectoral levels," Energy Economics, Elsevier, vol. 86(C).
    2. Sueyoshi, Toshiyuki & Yuan, Yan, 2016. "Returns to damage under undesirable congestion and damages to return under desirable congestion measured by DEA environmental assessment with multiplier restriction: Economic and energy planning for s," Energy Economics, Elsevier, vol. 56(C), pages 288-309.
    3. Sueyoshi, Toshiyuki & Yuan, Yan & Goto, Mika, 2017. "A literature study for DEA applied to energy and environment," Energy Economics, Elsevier, vol. 62(C), pages 104-124.
    4. Sueyoshi, Toshiyuki & Wang, Derek, 2017. "Measuring scale efficiency and returns to scale on large commercial rooftop photovoltaic systems in California," Energy Economics, Elsevier, vol. 65(C), pages 389-398.
    5. Sueyoshi, Toshiyuki & Wang, Derek, 2014. "Sustainability development for supply chain management in U.S. petroleum industry by DEA environmental assessment," Energy Economics, Elsevier, vol. 46(C), pages 360-374.
    6. Mehdiloozad, Mahmood & Zhu, Joe & Sahoo, Biresh K., 2018. "Identification of congestion in data envelopment analysis under the occurrence of multiple projections: A reliable method capable of dealing with negative data," European Journal of Operational Research, Elsevier, vol. 265(2), pages 644-654.
    7. Sueyoshi, Toshiyuki & Goto, Mika, 2017. "Measurement of returns to scale on large photovoltaic power stations in the United States and Germany," Energy Economics, Elsevier, vol. 64(C), pages 306-320.
    8. Ren, Xian-tong & Fukuyama, Hirofumi & Yang, Guo-liang, 2022. "Eliminating congestion by increasing inputs in R&D activities of Chinese universities," Omega, Elsevier, vol. 110(C).
    9. Sueyoshi, Toshiyuki & Yuan, Yan, 2017. "Social sustainability measured by intermediate approach for DEA environmental assessment: Chinese regional planning for economic development and pollution prevention," Energy Economics, Elsevier, vol. 66(C), pages 154-166.
    10. Pang, Qinghua & Qiu, Man & Zhang, Lina & Chiu, Yung-ho, 2024. "Congestion effects of energy and its influencing factors: China's transportation sector," Socio-Economic Planning Sciences, Elsevier, vol. 92(C).
    11. Sueyoshi, Toshiyuki & Yuan, Yan, 2016. "Marginal Rate of Transformation and Rate of Substitution measured by DEA environmental assessment: Comparison among European and North American nations," Energy Economics, Elsevier, vol. 56(C), pages 270-287.
    12. Sueyoshi, Toshiyuki & Wang, Derek, 2018. "DEA environmental assessment on US petroleum industry: Non-radial approach with translation invariance in time horizon," Energy Economics, Elsevier, vol. 72(C), pages 276-289.
    13. Sueyoshi, Toshiyuki & Goto, Mika, 2015. "DEA environmental assessment in time horizon: Radial approach for Malmquist index measurement on petroleum companies," Energy Economics, Elsevier, vol. 51(C), pages 329-345.
    14. Sueyoshi, Toshiyuki & Goto, Mika, 2015. "Japanese fuel mix strategy after disaster of Fukushima Daiichi nuclear power plant: Lessons from international comparison among industrial nations measured by DEA environmental assessment in time hori," Energy Economics, Elsevier, vol. 52(PA), pages 87-103.
    15. Chen, Zhenling & Li, Jinkai & Zhao, Weigang & Yuan, Xiao-Chen & Yang, Guo-liang, 2019. "Undesirable and desirable energy congestion measurements for regional coal-fired power generation industry in China," Energy Policy, Elsevier, vol. 125(C), pages 122-134.
    16. Sueyoshi, Toshiyuki & Goto, Mika & Wang, Derek, 2017. "Malmquist index measurement for sustainability enhancement in Chinese municipalities and provinces," Energy Economics, Elsevier, vol. 67(C), pages 554-571.
    17. Sueyoshi, Toshiyuki & Yuan, Yan & Li, Aijun & Wang, Daoping, 2017. "Methodological comparison among radial, non-radial and intermediate approaches for DEA environmental assessment," Energy Economics, Elsevier, vol. 67(C), pages 439-453.
    18. Sueyoshi, Toshiyuki & Yuan, Yan, 2015. "Comparison among U.S. industrial sectors by DEA environmental assessment: Equipped with analytical capability to handle zero or negative in production factors," Energy Economics, Elsevier, vol. 52(PA), pages 69-86.
    19. Sueyoshi, Toshiyuki & Goto, Mika, 2015. "Environmental assessment on coal-fired power plants in U.S. north-east region by DEA non-radial measurement," Energy Economics, Elsevier, vol. 50(C), pages 125-139.
    20. Jun Wang & Yong Zha, 2014. "Distinguishing Technical Inefficiency from Desirable and Undesirable Congestion with an Application to Regional Industries in China," Sustainability, MDPI, vol. 6(12), pages 1-19, December.

    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:energy:v:274:y:2023:i:c:s0360544223007387. 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.journals.elsevier.com/energy .

    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.