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Industrial energy consumption and pollutant emissions: Combined decomposition of relative performance and absolute changes

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  • Sicen Liu
  • Xiaodong Chen
  • Zhiyang Shen
  • Tomas Baležentis

Abstract

Combined decomposition of relative productivity growth and absolute changes in input/output variables helps to identify the driving forces of energy conservation and emission reduction. This paper proposes a framework based on the Luenberger productivity indicator (LPI) and the logarithmic mean Divisia index (LMDI) approach to analyze the energy–economy–environment nexus. The empirical case of the China's industrial sector for 2006–2014 is analyzed. Following this approach, we present a variable‐specific decomposition framework which attributes the overall productivity change and its sources to individual input/output variables. Empirically, we examine the relationships between the productivity growth and energy consumption within the LPI–LMDI framework across China's province‐level regions. The results show important spatial variation in the productivity measures. The LPI–LMDI decomposition implies that the industrial energy consumption increased with productivity growth appearing as the only mitigating factor. As regards the industrial SO2 emission, the individual productivity growth effect and the efficiency change effect remained as suppressing factors for emission abatement. These results can be used for evidence‐based decision making.

Suggested Citation

  • Sicen Liu & Xiaodong Chen & Zhiyang Shen & Tomas Baležentis, 2022. "Industrial energy consumption and pollutant emissions: Combined decomposition of relative performance and absolute changes," Business Strategy and the Environment, Wiley Blackwell, vol. 31(7), pages 3454-3469, November.
    • Handle: RePEc:bla:bstrat:v:31:y:2022:i:7:p:3454-3469
    DOI: 10.1002/bse.3094
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    as
    1. Liu, Zuankuo & Xin, Li, 2019. "Has China's Belt and Road Initiative promoted its green total factor productivity？——Evidence from primary provinces along the route," Energy Policy, Elsevier, vol. 129(C), pages 360-369.
    2. Wu, Jie & Lv, Lin & Sun, Jiasen & Ji, Xiang, 2015. "A comprehensive analysis of China's regional energy saving and emission reduction efficiency: From production and treatment perspectives," Energy Policy, Elsevier, vol. 84(C), pages 166-176.
    3. 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.
    4. Goh, Tian & Ang, B.W. & Xu, X.Y., 2018. "Quantifying drivers of CO2 emissions from electricity generation – Current practices and future extensions," Applied Energy, Elsevier, vol. 231(C), pages 1191-1204.
    5. Haider, Salman & Danish, Mohd Shadab & Sharma, Ruchi, 2019. "Assessing energy efficiency of Indian paper industry and influencing factors: A slack-based firm-level analysis," Energy Economics, Elsevier, vol. 81(C), pages 454-464.
    6. Wang, Ke & Wei, Yi-Ming, 2016. "Sources of energy productivity change in China during 1997–2012: A decomposition analysis based on the Luenberger productivity indicator," Energy Economics, Elsevier, vol. 54(C), pages 50-59.
    7. Shuai Shao, Zhenbing Yang, Lili Yang, and Shuang Ma, 2019. "Can China's Energy Intensity Constraint Policy Promote Total Factor Energy Efficiency? Evidence from the Industrial Sector," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4).
    8. Ang, B. W., 2005. "The LMDI approach to decomposition analysis: a practical guide," Energy Policy, Elsevier, vol. 33(7), pages 867-871, May.
    9. Price, James & Keppo, Ilkka, 2017. "Modelling to generate alternatives: A technique to explore uncertainty in energy-environment-economy models," Applied Energy, Elsevier, vol. 195(C), pages 356-369.
    10. Zhou, P. & Ang, B.W., 2008. "Decomposition of aggregate CO2 emissions: A production-theoretical approach," Energy Economics, Elsevier, vol. 30(3), pages 1054-1067, May.
    11. Atakelty Hailu & Terrence S. Veeman, 2001. "Non-parametric Productivity Analysis with Undesirable Outputs: An Application to the Canadian Pulp and Paper Industry," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 83(3), pages 605-616.
    12. Song, Malin & Zhu, Shuai & Wang, Jianlin & Zhao, Jiajia, 2020. "Share green growth: Regional evaluation of green output performance in China," International Journal of Production Economics, Elsevier, vol. 219(C), pages 152-163.
    13. Li, Man, 2010. "Decomposing the change of CO2 emissions in China: A distance function approach," Ecological Economics, Elsevier, vol. 70(1), pages 77-85, November.
    14. Fare, Rolf & Shawna Grosskopf & Mary Norris & Zhongyang Zhang, 1994. "Productivity Growth, Technical Progress, and Efficiency Change in Industrialized Countries," American Economic Review, American Economic Association, vol. 84(1), pages 66-83, March.
    15. Wang, Qunwei & Chiu, Yung-Ho & Chiu, Ching-Ren, 2015. "Driving factors behind carbon dioxide emissions in China: A modified production-theoretical decomposition analysis," Energy Economics, Elsevier, vol. 51(C), pages 252-260.
    16. Ang, B.W. & Liu, F.L. & Chung, Hyun-Sik, 2004. "A generalized Fisher index approach to energy decomposition analysis," Energy Economics, Elsevier, vol. 26(5), pages 757-763, September.
    17. Shao, Shuai & Guo, Longfei & Yu, Mingliang & Yang, Lili & Guan, Dabo, 2019. "Does the rebound effect matter in energy import-dependent mega-cities? Evidence from Shanghai (China)," Applied Energy, Elsevier, vol. 241(C), pages 212-228.
    18. Emrouznejad, Ali & Yang, Guo-liang, 2016. "A framework for measuring global Malmquist–Luenberger productivity index with CO2 emissions on Chinese manufacturing industries," Energy, Elsevier, vol. 115(P1), pages 840-856.
    19. Chai, Jian & Liang, Ting & Lai, Kin Keung & Zhang, Zhe George & Wang, Shouyang, 2018. "The future natural gas consumption in China: Based on the LMDI-STIRPAT-PLSR framework and scenario analysis," Energy Policy, Elsevier, vol. 119(C), pages 215-225.
    20. An, Qingxian & Wu, Qifan & Li, Jinlin & Xiong, Beibei & Chen, Xiaohong, 2019. "Environmental efficiency evaluation for Xiangjiang River basin cities based on an improved SBM model and Global Malmquist index," Energy Economics, Elsevier, vol. 81(C), pages 95-103.
    21. Wang, Chunhua, 2007. "Decomposing energy productivity change: A distance function approach," Energy, Elsevier, vol. 32(8), pages 1326-1333.
    22. Sun, Jiasen & Li, Guo & Wang, Zhaohua, 2018. "Optimizing China’s energy consumption structure under energy and carbon constraints," Structural Change and Economic Dynamics, Elsevier, vol. 47(C), pages 57-72.
    23. 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.
    24. Oh, Dong-hyun, 2010. "A metafrontier approach for measuring an environmentally sensitive productivity growth index," Energy Economics, Elsevier, vol. 32(1), pages 146-157, January.
    25. Miao, Zhuang & Chen, Xiaodong, 2022. "Combining parametric and non-parametric approach, variable & source -specific productivity changes and rebound effect of energy & environment," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    26. 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.
    27. Wang, Changjian & Miao, Zhuang & Chen, Xiaodong & Cheng, Yu, 2021. "Factors affecting changes of greenhouse gas emissions in Belt and Road countries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 147(C).
    28. 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.
    29. Chen, Jiandong & Xu, Chong & Cui, Lianbiao & Huang, Shuo & Song, Malin, 2019. "Driving factors of CO2 emissions and inequality characteristics in China: A combined decomposition approach," Energy Economics, Elsevier, vol. 78(C), pages 589-597.
    30. Cheng, Zhonghua & Liu, Jun & Li, Lianshui & Gu, Xinbei, 2020. "Research on meta-frontier total-factor energy efficiency and its spatial convergence in Chinese provinces," Energy Economics, Elsevier, vol. 86(C).
    31. Ang, Frederic & Kerstens, Pieter Jan, 2017. "Decomposing the Luenberger–Hicks–Moorsteen Total Factor Productivity indicator: An application to U.S. agriculture," European Journal of Operational Research, Elsevier, vol. 260(1), pages 359-375.
    32. Song, Malin & Wang, Jianlin, 2018. "Environmental efficiency evaluation of thermal power generation in China based on a slack-based endogenous directional distance function model," Energy, Elsevier, vol. 161(C), pages 325-336.
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