IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v11y2019i8p2355-d224406.html
   My bibliography  Save this article

Provincial Carbon Emissions Efficiency and Its Influencing Factors in China

Author

Listed:
  • Shi Wang

    (School of Economics and Finance, Xi’an International Studies University, Xi’an 710128, China
    “One Belt One Road” Economic and Trade Cooperation Innovation Team, Xi’an International Studies University, Xi’an 710128, China)

  • Hua Wang

    (School of Foreign Studies, Xi’an Jiaotong University, Xi’an 710049, China)

  • Li Zhang

    (School of Journalism and New Media, Xi’an Jiaotong University, Xi’an 710049, China)

  • Jun Dang

    (School of Economics and Finance, Xi’an International Studies University, Xi’an 710128, China
    “One Belt One Road” Cross-Border Electronic Commerce Research Institute, Xi’an International Studies University, Xi’an 710128, China)

Abstract

We calculated provincial carbon emissions efficiency and related influencing factors in China with the purpose of providing a reference for other developing countries to develop a green economy. Using panel data covering the period from 2004–2016 from 30 provinces in China, we calculated the carbon emission performance (CEP) and the technology gap ratio of carbon emission (TGR) with the data envelopment analysis (DEA) method and the meta-frontier model separately to analyze provincial carbon emissions efficiency in China. No matter which indicator was employed, we found that distinct differences exist in the eastern, the central, and the western regions of China, and the eastern region has the highest carbon emission performance, followed by the central and the western regions. Then, the panel data Tobit regression model was employed to analyze the influencing factors of carbon emissions efficiency, and we found that scale economy, industrial structure, degree of opening up, foreign direct investment (FDI), energy intensity, government interference, ownership structure, and capital-labor ratio have different impacts on the carbon emission efficiency in different regions of China, which indicates different policies should be implemented in different regions.

Suggested Citation

  • Shi Wang & Hua Wang & Li Zhang & Jun Dang, 2019. "Provincial Carbon Emissions Efficiency and Its Influencing Factors in China," Sustainability, MDPI, vol. 11(8), pages 1-21, April.
  • Handle: RePEc:gam:jsusta:v:11:y:2019:i:8:p:2355-:d:224406
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/11/8/2355/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/11/8/2355/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Yujiro Hayami, 1969. "Sources of Agricultural Productivity Gap Among Selected Countries," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 51(3), pages 564-575.
    2. Ang, B. W., 1999. "Is the energy intensity a less useful indicator than the carbon factor in the study of climate change?," Energy Policy, Elsevier, vol. 27(15), pages 943-946, December.
    3. Li, Fangyi & Song, Zhouying & Liu, Weidong, 2014. "China's energy consumption under the global economic crisis: Decomposition and sectoral analysis," Energy Policy, Elsevier, vol. 64(C), pages 193-202.
    4. Ryoko Morioka & Keisuke Nansai & Koji Tsuda, 2018. "Role of linkage structures in supply chain for managing greenhouse gas emissions," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 7(1), pages 1-21, December.
    5. Luukkanen, Jyrki & Kaivo-oja, Jari, 2002. "ASEAN tigers and sustainability of energy use--decomposition analysis of energy and CO2 efficiency dynamics," Energy Policy, Elsevier, vol. 30(4), pages 281-292, March.
    6. Wang, Yiming & Zhang, Pei & Huang, Dake & Cai, Changda, 2014. "Convergence behavior of carbon dioxide emissions in China," Economic Modelling, Elsevier, vol. 43(C), pages 75-80.
    7. 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.
    8. Christopher O’Donnell & D. Rao & George Battese, 2008. "Metafrontier frameworks for the study of firm-level efficiencies and technology ratios," Empirical Economics, Springer, vol. 34(2), pages 231-255, March.
    9. Shao, Ling & Li, Yuan & Feng, Kuishuang & Meng, Jing & Shan, Yuli & Guan, Dabo, 2018. "Carbon emission imbalances and the structural paths of Chinese regions," Applied Energy, Elsevier, vol. 215(C), pages 396-404.
    10. Wang, H. & Ang, B.W. & Su, Bin, 2017. "A Multi-region Structural Decomposition Analysis of Global CO2 Emission Intensity," Ecological Economics, Elsevier, vol. 142(C), pages 163-176.
    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. Stern, David I. & Jotzo, Frank, 2010. "How ambitious are China and India's emissions intensity targets?," Energy Policy, Elsevier, vol. 38(11), pages 6776-6783, November.
    13. 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.
    14. Lixiao Zhang & Qiuhong Hu & Fan Zhang, 2014. "Input-Output Modeling for Urban Energy Consumption in Beijing: Dynamics and Comparison," PLOS ONE, Public Library of Science, vol. 9(3), pages 1-11, March.
    15. Ju, Yiyi & Fujikawa, Kiyoshi, 2019. "Modeling the cost transmission mechanism of the emission trading scheme in China," Applied Energy, Elsevier, vol. 236(C), pages 172-182.
    16. Fan, Ying & Liu, Lan-Cui & Wu, Gang & Tsai, Hsien-Tang & Wei, Yi-Ming, 2007. "Changes in carbon intensity in China: Empirical findings from 1980-2003," Ecological Economics, Elsevier, vol. 62(3-4), pages 683-691, May.
    17. Su, Bin & Ang, B.W. & Li, Yingzhu, 2017. "Input-output and structural decomposition analysis of Singapore's carbon emissions," Energy Policy, Elsevier, vol. 105(C), pages 484-492.
    18. Xie, Rui & Hu, Guangxiao & Zhang, Youguo & Liu, Yu, 2017. "Provincial transfers of enabled carbon emissions in China: A supply-side perspective," Energy Policy, Elsevier, vol. 107(C), pages 688-697.
    19. Lenzen, Manfred, 1998. "Primary energy and greenhouse gases embodied in Australian final consumption: an input-output analysis," Energy Policy, Elsevier, vol. 26(6), pages 495-506, May.
    20. Kok, Rixt & Benders, Rene M.J. & Moll, Henri C., 2006. "Measuring the environmental load of household consumption using some methods based on input-output energy analysis: A comparison of methods and a discussion of results," Energy Policy, Elsevier, vol. 34(17), pages 2744-2761, November.
    21. Wu, Libo & Kaneko, Shinji & Matsuoka, Shunji, 2006. "Dynamics of energy-related CO2 emissions in China during 1980 to 2002: The relative importance of energy supply-side and demand-side effects," Energy Policy, Elsevier, vol. 34(18), pages 3549-3572, December.
    22. Wang, Xi & Cai, Hua & Florig, H. Keith, 2016. "Energy-saving implications from supply chain improvement: An exploratory study on China's consumer goods retail system," Energy Policy, Elsevier, vol. 95(C), pages 411-420.
    23. Herendeen, Robert & Tanaka, Jerry, 1976. "Energy cost of living," Energy, Elsevier, vol. 1(2), pages 165-178.
    24. Wang, Juan & Zhang, Kezhong, 2014. "Convergence of carbon dioxide emissions in different sectors in China," Energy, Elsevier, vol. 65(C), pages 605-611.
    25. George E. Battese & D. S. Prasada Rao, 2002. "Technology Gap, Efficiency, and a Stochastic Metafrontier Function," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 1(2), pages 87-93, August.
    26. 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.
    27. Mingyue Wang & Yu Liu & Yawen Liu & Shunxiang Yang & Lingyu Yang, 2018. "Assessing Multiple Pathways for Achieving China’s National Emissions Reduction Target," Sustainability, MDPI, vol. 10(7), pages 1-16, June.
    28. Førsund, Finn R. & Kittelsen, Sverre A. C., 1998. "Productivity development of Norwegian electricity distribution utilities," Resource and Energy Economics, Elsevier, vol. 20(3), pages 207-224, September.
    29. Hu, Yi & Yin, Zhifeng & Ma, Jian & Du, Wencui & Liu, Danhe & Sun, Luxi, 2017. "Determinants of GHG emissions for a municipal economy: Structural decomposition analysis of Chongqing," Applied Energy, Elsevier, vol. 196(C), pages 162-169.
    30. Zhang, Ming & Mu, Hailin & Ning, Yadong & Song, Yongchen, 2009. "Decomposition of energy-related CO2 emission over 1991-2006 in China," Ecological Economics, Elsevier, vol. 68(7), pages 2122-2128, 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. Feifei Ye & Rongyan You & Haitian Lu & Sirui Han & Long-Hao Yang, 2023. "The Classification Impact of Different Types of Environmental Regulation on Chinese Provincial Carbon Emission Efficiency," Sustainability, MDPI, vol. 15(15), pages 1-24, August.
    2. Yayun Ren & Jian Yu & Shuhua Xu & Jiaomei Tang & Chang Zhang, 2023. "Green Finance and Industrial Low-Carbon Transition: Evidence from a Quasi-Natural Experiment in China," Sustainability, MDPI, vol. 15(6), pages 1-17, March.
    3. Ruijing Zheng & Yu Cheng & Haimeng Liu & Wei Chen & Xiaodong Chen & Yaping Wang, 2022. "The Spatiotemporal Distribution and Drivers of Urban Carbon Emission Efficiency: The Role of Technological Innovation," IJERPH, MDPI, vol. 19(15), pages 1-22, July.
    4. Yu, Yantuan & Zhang, Ning, 2021. "Low-carbon city pilot and carbon emission efficiency: Quasi-experimental evidence from China," Energy Economics, Elsevier, vol. 96(C).
    5. Liangen Zeng & Haiyan Lu & Yenping Liu & Yang Zhou & Haoyu Hu, 2019. "Analysis of Regional Differences and Influencing Factors on China’s Carbon Emission Efficiency in 2005–2015," Energies, MDPI, vol. 12(16), pages 1-21, August.
    6. Fan Zhang & Gui Jin & Junlong Li & Chao Wang & Ning Xu, 2020. "Study on Dynamic Total Factor Carbon Emission Efficiency in China’s Urban Agglomerations," Sustainability, MDPI, vol. 12(7), pages 1-17, March.
    7. Minyoung Yang & Jinsoo Kim, 2022. "A Critical Review of the Definition and Estimation of Carbon Efficiency," Sustainability, MDPI, vol. 14(16), pages 1-18, August.
    8. Fan, Meiting & Li, Mengxu & Liu, Jianghua & Shao, Shuai, 2022. "Is high natural resource dependence doomed to low carbon emission efficiency? Evidence from 283 cities in China," Energy Economics, Elsevier, vol. 115(C).
    9. Ying-yu Lu & Yue He & Bo Wang & Shuang-shuang Ye & Yidi Hua & Lei Ding, 2019. "Efficiency Evaluation of Atmospheric Pollutants Emission in Zhejiang Province China: A DEA-Malmquist Based Approach," Sustainability, MDPI, vol. 11(17), pages 1-19, August.
    10. Wasi Ul Hassan Shah & Yuting Lu & Gang Hao & Hong Yan & Rizwana Yasmeen, 2022. "Impact of “Three Red Lines” Water Policy (2011) on Water Usage Efficiency, Production Technology Heterogeneity, and Determinant of Water Productivity Change in China," IJERPH, MDPI, vol. 19(24), pages 1-23, December.
    11. Jianshi Wang & Chengxin Wang & Shangkun Yu & Mengcheng Li & Yu Cheng, 2022. "Coupling Coordination and Spatiotemporal Evolution between Carbon Emissions, Industrial Structure, and Regional Innovation of Counties in Shandong Province," Sustainability, MDPI, vol. 14(12), pages 1-16, June.
    12. 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.
    13. Yujing Liu & Dongxiao Niu, 2021. "Coupling and Coordination Analysis of Thermal Power Carbon Emission Efficiency under the Background of Clean Energy Substitution," Sustainability, MDPI, vol. 13(23), pages 1-17, November.
    14. 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).
    15. Li-Ming Xue & Zhi-Xue Zheng & Shuo Meng & Mingjun Li & Huaqing Li & Ji-Ming Chen, 2022. "Carbon emission efficiency and spatio-temporal dynamic evolution of the cities in Beijing-Tianjin-Hebei Region, China," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(6), pages 7640-7664, June.

    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. 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.
    2. 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.
    3. Wang, Qunwei & Chiu, Yung-Ho & Chiu, Ching-Ren, 2017. "Non-radial metafrontier approach to identify carbon emission performance and intensity," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 664-672.
    4. Du, Kerui & Lu, Huang & Yu, Kun, 2014. "Sources of the potential CO2 emission reduction in China: A nonparametric metafrontier approach," Applied Energy, Elsevier, vol. 115(C), pages 491-501.
    5. Afsharian, Mohsen & Ahn, Heinz & Harms, Sören Guntram, 2019. "Performance comparison of management groups under centralised management," European Journal of Operational Research, Elsevier, vol. 278(3), pages 845-854.
    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. Chiu, Yung-Ho & Lee, Jen-Hui & Lu, Ching-Cheng & Shyu, Ming-Kuang & Luo, Zhengying, 2012. "The technology gap and efficiency measure in WEC countries: Application of the hybrid meta frontier model," Energy Policy, Elsevier, vol. 51(C), pages 349-357.
    8. Zhu, Bangzhu & Su, Bin & Li, Yingzhu, 2018. "Input-output and structural decomposition analysis of India’s carbon emissions and intensity, 2007/08 – 2013/14," Applied Energy, Elsevier, vol. 230(C), pages 1545-1556.
    9. Li, Lan-bing & Liu, Bing-lian & Liu, Wei-lin & Chiu, Yung-Ho, 2017. "Efficiency evaluation of the regional high-tech industry in China: A new framework based on meta-frontier dynamic DEA analysis," Socio-Economic Planning Sciences, Elsevier, vol. 60(C), pages 24-33.
    10. 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.
    11. Fei, Rilong & Lin, Boqiang, 2016. "Energy efficiency and production technology heterogeneity in China's agricultural sector: A meta-frontier approach," Technological Forecasting and Social Change, Elsevier, vol. 109(C), pages 25-34.
    12. Wang, Qunwei & Zhao, Zengyao & Zhou, Peng & Zhou, Dequn, 2013. "Energy efficiency and production technology heterogeneity in China: A meta-frontier DEA approach," Economic Modelling, Elsevier, vol. 35(C), pages 283-289.
    13. Rodríguez, Miguel & Pena-Boquete, Yolanda, 2017. "Carbon intensity changes in the Asian Dragons. Lessons for climate policy design," Energy Economics, Elsevier, vol. 66(C), pages 17-26.
    14. Xie, Rui & Wang, Fangfang & Chevallier, Julien & Zhu, Bangzhu & Zhao, Guomei, 2018. "Supply-side structural effects of air pollutant emissions in China: A comparative analysis," Structural Change and Economic Dynamics, Elsevier, vol. 46(C), pages 89-95.
    15. Yongqi Feng & Haolin Zhang & Yung-ho Chiu & Tzu-Han Chang, 2021. "Innovation efficiency and the impact of the institutional quality: a cross-country analysis using the two-stage meta-frontier dynamic network DEA model," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(4), pages 3091-3129, April.
    16. Kaivo-oja, J. & Luukkanen, J. & Panula-Ontto, J. & Vehmas, J. & Chen, Y. & Mikkonen, S. & Auffermann, B., 2014. "Are structural change and modernisation leading to convergence in the CO2 economy? Decomposition analysis of China, EU and USA," Energy, Elsevier, vol. 72(C), pages 115-125.
    17. Hang, Ye & Sun, Jiasen & Wang, Qunwei & Zhao, Zengyao & Wang, Yizhong, 2015. "Measuring energy inefficiency with undesirable outputs and technology heterogeneity in Chinese cities," Economic Modelling, Elsevier, vol. 49(C), pages 46-52.
    18. Thanh Pham Thien Nguyen & Son Hong Nghiem & Eduardo Roca & Parmendra Sharma, 2016. "Efficiency, innovation and competition: evidence from Vietnam, China and India," Empirical Economics, Springer, vol. 51(3), pages 1235-1259, November.
    19. Xiongfeng Pan & Jing Zhang & Changyu Li & Xianyou Pan & Jinbo Song, 2019. "Analysis of China’s regional wind power generation efficiency and its influencing factors," Energy & Environment, , vol. 30(2), pages 254-271, March.
    20. Li, Jia Shuo & Zhou, H.W. & Meng, Jing & Yang, Q. & Chen, B. & Zhang, Y.Y., 2018. "Carbon emissions and their drivers for a typical urban economy from multiple perspectives: A case analysis for Beijing city," Applied Energy, Elsevier, vol. 226(C), pages 1076-1086.

    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:11:y:2019:i:8:p:2355-:d:224406. 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.