IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v12y2020i8p3138-d345210.html
   My bibliography  Save this article

Analysis and Evaluation of the Regional Characteristics of Carbon Emission Efficiency for China

Author

Listed:
  • Jinkai Li

    (Center for Energy, Environment & Economy Research, Zhengzhou University, Zhengzhou 450000, China
    College of Tourism Management, Zhengzhou University, Zhengzhou 450000, China)

  • Jingjing Ma

    (Business School of Zhengzhou University, Zhengzhou 450000, China)

  • Wei Wei

    (Center for Energy, Environment & Economy Research, Zhengzhou University, Zhengzhou 450000, China
    College of Tourism Management, Zhengzhou University, Zhengzhou 450000, China)

Abstract

To promote economic and social development with reduced carbon dioxide emissions, the key lies in determining how to improve carbon emission efficiency (CEE). We first measured the CEE of each province by using the input-oriented three-stage Data Envelopment Analysis (DEA) and DEA-Malmquist model for the panel data of 30 provinces in China during 2000–2017. Then we explored the CEE differences and characteristics of different regions obtained by using hierarchical clustering of each province’s CEE. Finally, based on the regression model, we conducted an empirical analysis of the impact of each factor of total factor productivity (TFP) on CEE. The main findings of this research are as follows: (1) The industrial structure, energy structure, government regulation, technological innovation, and openness had a significant impact on CEE; (2) The variation trends of CEE and TFP in the eight regions we studied were convergent, while the variations of CEE among regions were diverse and all distributed stably in different ranges; (3) The eight regions’ efficiency basically showed a downward trend of eastern, central and western China; (4) Technological regression was the main reason for the decline in TFP. Technological progress and technological efficiency can contribute to an improvement in CEE. Based on the findings above, we provide decision-making references for comprehensively improving the efficiency of various regions and accelerating China’s energy conservation, emissions reduction, and coordinated development.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:8:p:3138-:d:345210
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/12/8/3138/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/12/8/3138/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. Pretis, Felix & Roser, Max, 2017. "Carbon dioxide emission-intensity in climate projections: Comparing the observational record to socio-economic scenarios," Energy, Elsevier, vol. 135(C), pages 718-725.
    4. Ferreira, Ana & Pinheiro, Manuel Duarte & de Brito, Jorge & Mateus, Ricardo, 2018. "Combined carbon and energy intensity benchmarks for sustainable retail stores," Energy, Elsevier, vol. 165(PB), pages 877-889.
    5. 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.
    6. Gómez-Calvet, Roberto & Conesa, David & Gómez-Calvet, Ana Rosa & Tortosa-Ausina, Emili, 2014. "Energy efficiency in the European Union: What can be learned from the joint application of directional distance functions and slacks-based measures?," Applied Energy, Elsevier, vol. 132(C), pages 137-154.
    7. 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.
    8. Yuan Chen & Bingsheng Liu & Yinghua Shen & Xueqing Wang, 2018. "Spatial analysis of change trend and influencing factors of total factor productivity in China’s regional construction industry," Applied Economics, Taylor & Francis Journals, vol. 50(25), pages 2824-2843, May.
    9. Caves, Douglas W & Christensen, Laurits R & Diewert, W Erwin, 1982. "The Economic Theory of Index Numbers and the Measurement of Input, Output, and Productivity," Econometrica, Econometric Society, vol. 50(6), pages 1393-1414, November.
    10. Haifeng Huang & Tao Wang, 2017. "The Total-Factor Energy Efficiency of Regions in China: Based on Three-Stage SBM Model," Sustainability, MDPI, vol. 9(9), pages 1-20, September.
    11. 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.
    12. 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.
    13. Meng, Fanyi & Su, Bin & Thomson, Elspeth & Zhou, Dequn & Zhou, P., 2016. "Measuring China’s regional energy and carbon emission efficiency with DEA models: A survey," Applied Energy, Elsevier, vol. 183(C), pages 1-21.
    14. Song, Malin & An, Qingxian & Zhang, Wei & Wang, Zeya & Wu, Jie, 2012. "Environmental efficiency evaluation based on data envelopment analysis: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(7), pages 4465-4469.
    15. 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.
    16. 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.
    17. Jondrow, James & Knox Lovell, C. A. & Materov, Ivan S. & Schmidt, Peter, 1982. "On the estimation of technical inefficiency in the stochastic frontier production function model," Journal of Econometrics, Elsevier, vol. 19(2-3), pages 233-238, August.
    18. Yangho Chung & Rolf Fare, 1995. "Productivity and Undesirable Outputs: A Directional Distance Function Approach," Microeconomics 9511002, University Library of Munich, Germany, revised 09 Nov 1995.
    19. Mahmoudabadi, Mohammad Zarei & Emrouznejad, Ali, 2019. "Comprehensive performance evaluation of banking branches: A three-stage slacks-based measure (SBM) data envelopment analysis," International Review of Economics & Finance, Elsevier, vol. 64(C), pages 359-376.
    20. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    21. Jia-Yin Yin & Yun-Fei Cao & Bao-Jun Tang, 2019. "Fairness of China’s provincial energy environment efficiency evaluation: empirical analysis using a three-stage data envelopment analysis model," 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 343-362, January.
    22. 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.
    23. JIANG,Mengyuan & QI,Chunjie, 2018. "Measurement and Analysis of Agricultural Production Efficiency in Taiwan of China Based on Three-stage DEA Model," Asian Agricultural Research, USA-China Science and Culture Media Corporation, vol. 10(07), July.
    24. 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.
    25. 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)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Huayong Niu & Zhishuo Zhang & Manting Luo, 2022. "Evaluation and Prediction of Low-Carbon Economic Efficiency in China, Japan and South Korea: Based on DEA and Machine Learning," IJERPH, MDPI, vol. 19(19), pages 1-28, October.
    2. Jianqing Zhang & Haichao Yu & Keke Zhang & Liang Zhao & Fei Fan, 2021. "Can Innovation Agglomeration Reduce Carbon Emissions? Evidence from China," IJERPH, MDPI, vol. 18(2), pages 1-24, January.
    3. Yanmei Li & Xin Sun & Xiushan Bai, 2022. "Differences of Carbon Emission Efficiency in the Belt and Road Initiative Countries," Energies, MDPI, vol. 15(4), pages 1-17, February.
    4. Tingting Wu & Junjun Chen & Chengchun Shi & Guidi Yang, 2023. "Carbon Emission Efficiency and Reduction Potential Based on Three-Stage Slacks-Based Measure with Data Envelopment Analysis and Malmquist at the City Scale in Fujian Province, China," Sustainability, MDPI, vol. 15(16), pages 1-15, August.
    5. Le Yang & Zhongqi Liang & Wentao Yao & Hongmin Zhu & Liangen Zeng & Zihan Zhao, 2023. "What Are the Impacts of Urbanisation on Carbon Emissions Efficiency? Evidence from Western China," Land, MDPI, vol. 12(9), pages 1-18, August.
    6. Da Gao & Xinlin Mo & Ruochan Xiong & Zhiliang Huang, 2022. "Tax Policy and Total Factor Carbon Emission Efficiency: Evidence from China’s VAT Reform," IJERPH, MDPI, vol. 19(15), pages 1-17, July.
    7. Jinpeng Liu & Delin Wei, 2020. "Analysis and Measurement of Carbon Emission Aggregation and Spillover Effects in China: Based on a Sectoral Perspective," Sustainability, MDPI, vol. 12(21), pages 1-22, October.
    8. Tomas Macak & Jan Hron & Jaromir Stusek, 2020. "A Causal Model of the Sustainable Use of Resources: A Case Study on a Woodworking Process," Sustainability, MDPI, vol. 12(21), pages 1-22, October.
    9. Heri Bezić & Davor Mance & Davorin Balaž, 2022. "Panel Evidence from EU Countries on CO 2 Emission Indicators during the Fourth Industrial Revolution," Sustainability, MDPI, vol. 14(19), pages 1-25, October.
    10. Ta-Thi Huong & Liang Dong & Izhar Hussain Shah & Hung-Suck Park, 2021. "Exploring the Sustainability of Resource Flow and Productivity Transition in Vietnam from 1978 to 2017: MFA and DEA-Based Malmquist Productivity Index Approach," Sustainability, MDPI, vol. 13(21), pages 1-26, October.
    11. Li, Feng & Liu, Hao & Ma, Yinhan & Xie, Xiaohua & Wang, Yunshu & Yang, Yejun, 2022. "Low-carbon spatial differences of renewable energy technologies: Empirical evidence from the Yangtze River Economic Belt," Technological Forecasting and Social Change, Elsevier, vol. 183(C).
    12. Feng Dong & Chang Qin & Xiaoyun Zhang & Xu Zhao & Yuling Pan & Yujin Gao & Jiao Zhu & Yangfan Li, 2021. "Towards Carbon Neutrality: The Impact of Renewable Energy Development on Carbon Emission Efficiency," IJERPH, MDPI, vol. 18(24), pages 1-23, December.

    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, 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.
    2. 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.
    3. 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.
    4. Jingwen Yi & Yuchen Zhang & Kaicheng Liao, 2021. "Regional Differential Decomposition and Formation Mechanism of Dynamic Carbon Emission Efficiency of China’s Logistics Industry," IJERPH, MDPI, vol. 18(24), pages 1-25, December.
    5. Meng, Fanyi & Su, Bin & Thomson, Elspeth & Zhou, Dequn & Zhou, P., 2016. "Measuring China’s regional energy and carbon emission efficiency with DEA models: A survey," Applied Energy, Elsevier, vol. 183(C), pages 1-21.
    6. Demiral, Elif E. & Sağlam, Ümit, 2021. "Eco-efficiency and Eco-productivity assessments of the states in the United States: A two-stage Non-parametric analysis," Applied Energy, Elsevier, vol. 303(C).
    7. 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.
    8. Ji, Xiang & Li, Guo & Wang, Zhaohua, 2017. "Impact of emission regulation policies on Chinese power firms’ reusable environmental investments and sustainable operations," Energy Policy, Elsevier, vol. 108(C), pages 163-177.
    9. 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.
    10. Ning Zhang & Jong-Dae Kim, 2014. "Measuring sustainability by Energy Efficiency Analysis for Korean Power Companies: A Sequential Slacks-Based Efficiency Measure," Sustainability, MDPI, vol. 6(3), pages 1-13, March.
    11. Wang, Zhaohua & Li, Yi & Wang, Ke & Huang, Zhimin, 2017. "Environment-adjusted operational performance evaluation of solar photovoltaic power plants: A three stage efficiency analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 76(C), pages 1153-1162.
    12. 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.
    13. Xiang Ji & Jiasen Sun & Qunwei Wang & Qianqian Yuan, 2019. "Revealing Energy Over-Consumption and Pollutant Over-Emission Behind GDP: A New Multi-criteria Sustainable Measure," Computational Economics, Springer;Society for Computational Economics, vol. 54(4), pages 1391-1421, December.
    14. Nelson Amowine & Zhiqiang Ma & Mingxing Li & Zhixiang Zhou & Benjamin Azembila Asunka & James Amowine, 2019. "Energy Efficiency Improvement Assessment in Africa: An Integrated Dynamic DEA Approach," Energies, MDPI, vol. 12(20), pages 1-17, October.
    15. Yu, Dejian & He, Xiaorong, 2020. "A bibliometric study for DEA applied to energy efficiency: Trends and future challenges," Applied Energy, Elsevier, vol. 268(C).
    16. Mai, Nhat Chi, 2015. "Efficiency of the banking system in Vietnam under financial liberalization," OSF Preprints qsf6d, Center for Open Science.
    17. Liu, John S. & Lu, Louis Y.Y. & Lu, Wen-Min, 2016. "Research fronts in data envelopment analysis," Omega, Elsevier, vol. 58(C), pages 33-45.
    18. Teng, Xiangyu & Zhuang, Weiwei & Liu, Fan-peng & Chang, Tzu-han & Chiu, Yung-ho, 2023. "China's path of carbon neutralization to develop green energy and improve energy efficiency," Renewable Energy, Elsevier, vol. 206(C), pages 397-408.
    19. Chang, Young-Tae & Zhang, Ning & Danao, Denise & Zhang, Nan, 2013. "Environmental efficiency analysis of transportation system in China: A non-radial DEA approach," Energy Policy, Elsevier, vol. 58(C), pages 277-283.
    20. Mushtaq Taleb & Ruzelan Khalid & Ali Emrouznejad & Razamin Ramli, 2023. "Environmental efficiency under weak disposability: an improved super efficiency data envelopment analysis model with application for assessment of port operations considering NetZero," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(7), pages 6627-6656, July.

    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:12:y:2020:i:8:p:3138-:d:345210. 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.