IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v184y2016icp1142-1153.html
   My bibliography  Save this article

Total-factor CO2 emission performance of China’s provincial industrial sector: A meta-frontier non-radial Malmquist index approach

Author

Listed:
  • Yao, Xin
  • Guo, Chengwen
  • Shao, Shuai
  • Jiang, Zhujun

Abstract

The Chinese government has promised that China should peak its carbon emissions by 2030 and that the share of non-fossil fuels in primary energy consumption should rise to around 20%. Since the industrial sector is the largest CO2 emitter in China, emission reduction in the industrial sector is significant to the realization of those targets. Using the panel data of provincial industrial sectors in China during 1998–2011, we apply the meta-frontier non-radial Malmquist CO2 emission performance index (MNMCPI) to estimate the changes in China’s CO2 emission performance as well as their driving forces, and compare MNMCPI with other traditional CO2 emission performance indices, such as the Malmquist CO2 emission Performance Index (MCPI). The results indicate that the CO2 emission performance of China’s provincial industrial sector during 1998–2011 grew at an average annual rate of 5.53%, and that the average CO2 emission performance of industrial sector in Eastern, Central and Western China decreased in turn. MCPI overestimates CO2 emission performance. The efficiency change (EC) index based on MNMCPI increases by the average annual rate of 2.297%. EC of CO2 emission performance in 21 provinces shows an increasing trend. The innovation effect indicated by best-practice gap change (BPC) is significant. We also find that the increase in the CO2 emission performance of industrial sector of 23 provinces is mainly driven by technology innovation, but the CO2 emission performance of industrial sector of other 6 provinces is mainly driven by technology efficiency improvement. In terms of technology gap change (TGC) index, none of the three regions seem to be a technology leader, and the inter-temporal frontier of three regions has been shifting away from the global frontier.

Suggested Citation

  • Yao, Xin & Guo, Chengwen & Shao, Shuai & Jiang, Zhujun, 2016. "Total-factor CO2 emission performance of China’s provincial industrial sector: A meta-frontier non-radial Malmquist index approach," Applied Energy, Elsevier, vol. 184(C), pages 1142-1153.
    • Handle: RePEc:eee:appene:v:184:y:2016:i:c:p:1142-1153
    DOI: 10.1016/j.apenergy.2016.08.064
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261916311515
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2016.08.064?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. Chang, Tzu-Pu & Hu, Jin-Li, 2010. "Total-factor energy productivity growth, technical progress, and efficiency change: An empirical study of China," Applied Energy, Elsevier, vol. 87(10), pages 3262-3270, October.
    2. 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.
    3. Jaraitė, Jūratė & Di Maria, Corrado, 2012. "Efficiency, productivity and environmental policy: A case study of power generation in the EU," Energy Economics, Elsevier, vol. 34(5), pages 1557-1568.
    4. 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.
    5. Rolf Färe & Shawna Grosskopf & Carl A Pasurka, Jr., 2001. "Accounting for Air Pollution Emissions in Measures of State Manufacturing Productivity Growth," Journal of Regional Science, Wiley Blackwell, vol. 41(3), pages 381-409, August.
    6. 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.
    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. Sueyoshi, Toshiyuki & Goto, Mika, 2011. "DEA approach for unified efficiency measurement: Assessment of Japanese fossil fuel power generation," Energy Economics, Elsevier, vol. 33(2), pages 292-303, March.
    9. 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.
    10. Zaim, Osman, 2004. "Measuring environmental performance of state manufacturing through changes in pollution intensities: a DEA framework," Ecological Economics, Elsevier, vol. 48(1), pages 37-47, January.
    11. Kumar, Surender, 2006. "Environmentally sensitive productivity growth: A global analysis using Malmquist-Luenberger index," Ecological Economics, Elsevier, vol. 56(2), pages 280-293, February.
    12. Cui, Qiang & Li, Ye, 2015. "An empirical study on the influencing factors of transportation carbon efficiency: Evidences from fifteen countries," Applied Energy, Elsevier, vol. 141(C), pages 209-217.
    13. Tol, Richard S.J. & Pacala, Stephen W. & Socolow, Robert H., 2009. "Understanding Long-Term Energy Use and Carbon Dioxide Emissions in the USA," Journal of Policy Modeling, Elsevier, vol. 31(3), pages 425-445, May.
    14. Fukuyama, Hirofumi & Weber, William L., 2009. "A directional slacks-based measure of technical inefficiency," Socio-Economic Planning Sciences, Elsevier, vol. 43(4), pages 274-287, December.
    15. 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.
    16. 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.
    17. Fan, Meiting & Shao, Shuai & Yang, Lili, 2015. "Combining global Malmquist–Luenberger index and generalized method of moments to investigate industrial total factor CO2 emission performance: A case of Shanghai (China)," Energy Policy, Elsevier, vol. 79(C), pages 189-201.
    18. Zhang, Ning & Zhou, P. & Choi, Yongrok, 2013. "Energy efficiency, CO2 emission performance and technology gaps in fossil fuel electricity generation in Korea: A meta-frontier non-radial directional distance functionanalysis," Energy Policy, Elsevier, vol. 56(C), pages 653-662.
    19. Lin, Boqiang & Du, Kerui, 2015. "Energy and CO2 emissions performance in China's regional economies: Do market-oriented reforms matter?," Energy Policy, Elsevier, vol. 78(C), pages 113-124.
    20. Lin, Boqiang & Du, Kerui, 2015. "Modeling the dynamics of carbon emission performance in China: A parametric Malmquist index approach," Energy Economics, Elsevier, vol. 49(C), pages 550-557.
    21. Boyd, Gale A. & Pang, Joseph X., 2000. "Estimating the linkage between energy efficiency and productivity," Energy Policy, Elsevier, vol. 28(5), pages 289-296, May.
    22. Picazo-Tadeo, Andres J. & Reig-Martinez, Ernest & Hernandez-Sancho, Francesc, 2005. "Directional distance functions and environmental regulation," Resource and Energy Economics, Elsevier, vol. 27(2), pages 131-142, June.
    23. Zhang, Ning & Choi, Yongrok, 2013. "A comparative study of dynamic changes in CO2 emission performance of fossil fuel power plants in China and Korea," Energy Policy, Elsevier, vol. 62(C), pages 324-332.
    24. Unknown, 2016. "Energy for Sustainable Development," Conference Proceedings 253270, Guru Arjan Dev Institute of Development Studies (IDSAsr).
    25. Wang, Ke & Wei, Yi-Ming, 2014. "China’s regional industrial energy efficiency and carbon emissions abatement costs," Applied Energy, Elsevier, vol. 130(C), pages 617-631.
    26. R. Ramanathan, 2002. "Combining indicators of energy consumption and CO 2 emissions: a cross-country comparison," International Journal of Global Energy Issues, Inderscience Enterprises Ltd, vol. 17(3), pages 214-227.
    27. 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.
    28. Zhang, Ning & Zhou, Peng & Kung, Chih-Chun, 2015. "Total-factor carbon emission performance of the Chinese transportation industry: A bootstrapped non-radial Malmquist index analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 41(C), pages 584-593.
    29. Zhang, Ning & Choi, Yongrok, 2013. "Total-factor carbon emission performance of fossil fuel power plants in China: A metafrontier non-radial Malmquist index analysis," Energy Economics, Elsevier, vol. 40(C), pages 549-559.
    30. Song, Ma-Lin & Zhang, Lin-Ling & Liu, Wei & Fisher, Ron, 2013. "Bootstrap-DEA analysis of BRICS’ energy efficiency based on small sample data," Applied Energy, Elsevier, vol. 112(C), pages 1049-1055.
    31. Caves, Douglas W & Christensen, Laurits R & Diewert, W Erwin, 1982. "Multilateral Comparisons of Output, Input, and Productivity Using Superlative Index Numbers," Economic Journal, Royal Economic Society, vol. 92(365), pages 73-86, March.
    32. Dong-hyun Oh & Jeong-dong Lee, 2010. "A metafrontier approach for measuring Malmquist productivity index," Empirical Economics, Springer, vol. 38(1), pages 47-64, February.
    33. Wang, Ke & Wei, Yi-Ming & Zhang, Xian, 2013. "Energy and emissions efficiency patterns of Chinese regions: A multi-directional efficiency analysis," Applied Energy, Elsevier, vol. 104(C), pages 105-116.
    34. Zhou, P. & Ang, B.W. & Poh, K.L., 2008. "A survey of data envelopment analysis in energy and environmental studies," European Journal of Operational Research, Elsevier, vol. 189(1), pages 1-18, August.
    35. Barros, Carlos Pestana & Peypoch, Nicolas, 2008. "Technical efficiency of thermoelectric power plants," Energy Economics, Elsevier, vol. 30(6), pages 3118-3127, November.
    36. Zhou, P. & Ang, B.W. & Wang, H., 2012. "Energy and CO2 emission performance in electricity generation: A non-radial directional distance function approach," European Journal of Operational Research, Elsevier, vol. 221(3), pages 625-635.
    37. Yao, Xin & Zhou, Hongchen & Zhang, Aizhen & Li, Aijun, 2015. "Regional energy efficiency, carbon emission performance and technology gaps in China: A meta-frontier non-radial directional distance function analysis," Energy Policy, Elsevier, vol. 84(C), pages 142-154.
    38. Wang, Haikun & Zhang, Yanxia & Lu, Xi & Nielsen, Chris P. & Bi, Jun, 2015. "Understanding China׳s carbon dioxide emissions from both production and consumption perspectives," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 189-200.
    39. Wang, H. & Zhou, P. & Wang, Qunwei, 2016. "Constructing slacks-based composite indicator of sustainable energy development for China: A meta-frontier nonparametric approach," Energy, Elsevier, vol. 101(C), pages 218-228.
    40. Chambers, Robert G. & Chung, Yangho & Fare, Rolf, 1996. "Benefit and Distance Functions," Journal of Economic Theory, Elsevier, vol. 70(2), pages 407-419, August.
    41. 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. 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.
    2. Cheng, Zhonghua & Li, Lianshui & Liu, Jun & Zhang, Huiming, 2018. "Total-factor carbon emission efficiency of China's provincial industrial sector and its dynamic evolution," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 330-339.
    3. Zhang, Ning & Choi, Yongrok, 2013. "Total-factor carbon emission performance of fossil fuel power plants in China: A metafrontier non-radial Malmquist index analysis," Energy Economics, Elsevier, vol. 40(C), pages 549-559.
    4. Lin, Boqiang & Sai, Rockson, 2021. "A multi factor Malmquist CO2emission performance indices: Evidence from Sub Saharan African public thermal power plants," Energy, Elsevier, vol. 223(C).
    5. Zhang, Ning & Kong, Fanbin & Choi, Yongrok & Zhou, P., 2014. "The effect of size-control policy on unified energy and carbon efficiency for Chinese fossil fuel power plants," Energy Policy, Elsevier, vol. 70(C), pages 193-200.
    6. Zhang, Ning & Choi, Yongrok, 2013. "A comparative study of dynamic changes in CO2 emission performance of fossil fuel power plants in China and Korea," Energy Policy, Elsevier, vol. 62(C), pages 324-332.
    7. Yu, Dejian & He, Xiaorong, 2020. "A bibliometric study for DEA applied to energy efficiency: Trends and future challenges," Applied Energy, Elsevier, vol. 268(C).
    8. 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.
    9. Zhang, Ning & Wei, Xiao, 2015. "Dynamic total factor carbon emissions performance changes in the Chinese transportation industry," Applied Energy, Elsevier, vol. 146(C), pages 409-420.
    10. Zhang, Ning & Zhou, Peng & Kung, Chih-Chun, 2015. "Total-factor carbon emission performance of the Chinese transportation industry: A bootstrapped non-radial Malmquist index analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 41(C), pages 584-593.
    11. Nabavieh, Alireza & Gholamiangonabadi, Davoud & Ahangaran, Ali Asghar, 2015. "Dynamic changes in CO2 emission performance of different types of Iranian fossil-fuel power plants," Energy Economics, Elsevier, vol. 52(PA), pages 142-150.
    12. Zhang, Ning & Wang, Bing & Liu, Zhu, 2016. "Carbon emissions dynamics, efficiency gains, and technological innovation in China's industrial sectors," Energy, Elsevier, vol. 99(C), pages 10-19.
    13. Lin, Boqiang & Sai, Rockson, 2022. "Towards low carbon economy: Performance of electricity generation and emission reduction potential in Africa," Energy, Elsevier, vol. 251(C).
    14. 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.
    15. Zhang, Ning & Kong, Fanbin & Choi, Yongrok, 2014. "Measuring sustainability performance for China: A sequential generalized directional distance function approach," Economic Modelling, Elsevier, vol. 41(C), pages 392-397.
    16. Zhang, Ning & Wang, Bing & Chen, Zhongfei, 2016. "Carbon emissions reductions and technology gaps in the world's factory, 1990–2012," Energy Policy, Elsevier, vol. 91(C), pages 28-37.
    17. Zhang, Ning & Zhou, P. & Choi, Yongrok, 2013. "Energy efficiency, CO2 emission performance and technology gaps in fossil fuel electricity generation in Korea: A meta-frontier non-radial directional distance functionanalysis," Energy Policy, Elsevier, vol. 56(C), pages 653-662.
    18. Zhang, Yijun & Song, Yi, 2020. "Unified efficiency of coal mining enterprises in China: An analysis based on meta-frontier non-radial directional distance functions," Resources Policy, Elsevier, vol. 65(C).
    19. Emrouznejad, Ali & Yang, Guo-liang, 2016. "CO2 emissions reduction of Chinese light manufacturing industries: A novel RAM-based global Malmquist–Luenberger productivity index," Energy Policy, Elsevier, vol. 96(C), pages 397-410.
    20. Zhang, Ning & Wang, Bing, 2015. "A deterministic parametric metafrontier Luenberger indicator for measuring environmentally-sensitive productivity growth: A Korean fossil-fuel power case," Energy Economics, Elsevier, vol. 51(C), pages 88-98.

    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:appene:v:184:y:2016:i:c:p:1142-1153. 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/wps/find/journaldescription.cws_home/405891/description#description .

    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.