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How to improve total factor energy efficiency? An empirical analysis of the Yangtze River economic belt of China

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  • Tang, Liwei
  • He, Gang

Abstract

This study employs a Luenberger-Hicks-Moorsteen productivity indicator to measure the total factor energy efficiency (TFEE) of the Yangtze River Economic Belt (YREB) of China from 2005 to 2016. The relative importance analysis method is used to investigate the driving forces of the TFEE. The main results are as follows. (a) The TFEE has an average growth rate of 3.3% during the study period. The TFEE declines first, then rebounds, and declines again. The contribution of technological efficiency changes to the TFEE growth is almost zero which indicating no catch-up effect in the sample period. Technological progress contributes a negative impact to the TFEE, with an average annual decrease rate of 3.4%. The scale efficiency changes, with an average annual growth rate of 6.7%, are extremely important for the growth of TFEE. (b) The TFEE of the western region is narrowing the gap with the central and western regions, while the gap between the central region and the eastern region is increasing. (c) Research investment can improve the growth of TFEE significantly, while government expenditure and industrial structure are not. And government expenditure, economic development, and research investment are top factors to explain the variation of TFEE.

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  • Tang, Liwei & He, Gang, 2021. "How to improve total factor energy efficiency? An empirical analysis of the Yangtze River economic belt of China," Energy, Elsevier, vol. 235(C).
  • Handle: RePEc:eee:energy:v:235:y:2021:i:c:s0360544221016236
    DOI: 10.1016/j.energy.2021.121375
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    as
    1. Kerstens, Kristiaan & O’Donnell, Christopher & Van de Woestyne, Ignace, 2019. "Metatechnology frontier and convexity: A restatement," European Journal of Operational Research, Elsevier, vol. 275(2), pages 780-792.
    2. 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.
    3. Zhou, P. & Ang, B.W., 2008. "Linear programming models for measuring economy-wide energy efficiency performance," Energy Policy, Elsevier, vol. 36(8), pages 2901-2906, August.
    4. Bjurek, Hans, 1996. " The Malmquist Total Factor Productivity Index," Scandinavian Journal of Economics, Wiley Blackwell, vol. 98(2), pages 303-313, June.
    5. Walter Briec & Kristiaan Kerstens, 2004. "A Luenberger-Hicks-Moorsteen productivity indicator: its relation to the Hicks-Moorsteen productivity index and the Luenberger productivity indicator," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 23(4), pages 925-939, May.
    6. Borozan, Djula, 2018. "Technical and total factor energy efficiency of European regions: A two-stage approach," Energy, Elsevier, vol. 152(C), pages 521-532.
    7. 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.
    8. 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.
    9. Guo, Xiaoying & Lu, Ching-Cheng & Lee, Jen-Hui & Chiu, Yung-Ho, 2017. "Applying the dynamic DEA model to evaluate the energy efficiency of OECD countries and China," Energy, Elsevier, vol. 134(C), pages 392-399.
    10. 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).
    11. Shen, Zhiyang & Baležentis, Tomas & Ferrier, Gary D., 2019. "Agricultural productivity evolution in China: A generalized decomposition of the Luenberger-Hicks-Moorsteen productivity indicator," China Economic Review, Elsevier, vol. 57(C).
    12. Kerstens, Kristiaan & Shen, Zhiyang & Van de Woestyne, Ignace, 2018. "Comparing Luenberger and Luenberger-Hicks-Moorsteen productivity indicators: How well is total factor productivity approximated?," International Journal of Production Economics, Elsevier, vol. 195(C), pages 311-318.
    13. Honma, Satoshi & Hu, Jin-Li, 2014. "A panel data parametric frontier technique for measuring total-factor energy efficiency: An application to Japanese regions," Energy, Elsevier, vol. 78(C), pages 732-739.
    14. Özkara, Yücel & Atak, Mehmet, 2015. "Regional total-factor energy efficiency and electricity saving potential of manufacturing industry in Turkey," Energy, Elsevier, vol. 93(P1), pages 495-510.
    15. Alwyn Young, 2003. "Gold into Base Metals: Productivity Growth in the People's Republic of China during the Reform Period," Journal of Political Economy, University of Chicago Press, vol. 111(6), pages 1220-1261, December.
    16. Osnat Israeli, 2007. "A Shapley-based decomposition of the R-Square of a linear regression," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 5(2), pages 199-212, August.
    17. Li, Jianglong & Lin, Boqiang, 2017. "Ecological total-factor energy efficiency of China's heavy and light industries: Which performs better?," Renewable and Sustainable Energy Reviews, Elsevier, vol. 72(C), pages 83-94.
    18. Qi, Xiaoyan & Guo, Pibin & Guo, Yanshan & Liu, Xiuli & Zhou, Xijun, 2020. "Understanding energy efficiency and its drivers: An empirical analysis of China’s 14 coal intensive industries," Energy, Elsevier, vol. 190(C).
    19. 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).
    20. Chang, Ming-Chung, 2013. "A comment on the calculation of the total-factor energy efficiency (TFEE) index," Energy Policy, Elsevier, vol. 53(C), pages 500-504.
    21. Jean‐Philippe Boussemart & Walter Briec & Kristiaan Kerstens & Jean‐Christophe Poutineau, 2003. "Luenberger and Malmquist Productivity Indices: Theoretical Comparisons and Empirical Illustration," Bulletin of Economic Research, Wiley Blackwell, vol. 55(4), pages 391-405, October.
    22. Honma, Satoshi & Hu, Jin-Li, 2008. "Total-factor energy efficiency of regions in Japan," Energy Policy, Elsevier, vol. 36(2), pages 821-833, February.
    23. Zhao, Hongli & Lin, Boqiang, 2019. "Will agglomeration improve the energy efficiency in China’s textile industry: Evidence and policy implications," Applied Energy, Elsevier, vol. 237(C), pages 326-337.
    24. Honma, Satoshi & Hu, Jin-Li, 2014. "Industry-level total-factor energy efficiency in developed countries: A Japan-centered analysis," Applied Energy, Elsevier, vol. 119(C), pages 67-78.
    25. Zhang, Xing-Ping & Cheng, Xiao-Mei & Yuan, Jia-Hai & Gao, Xiao-Jun, 2011. "Total-factor energy efficiency in developing countries," Energy Policy, Elsevier, vol. 39(2), pages 644-650, February.
    26. Wendong Lv & Xiaoxin Hong & Kuangnan Fang, 2015. "Chinese regional energy efficiency change and its determinants analysis: Malmquist index and Tobit model," Annals of Operations Research, Springer, vol. 228(1), pages 9-22, May.
    27. Antonio Peyrache, 2014. "Hicks-Moorsteen versus Malmquist: a connection by means of a radial productivity index," Journal of Productivity Analysis, Springer, vol. 41(3), pages 435-442, June.
    28. Dezhu Ye & Yew-Kwang Ng & Yujun Lian, 2015. "Culture and Happiness," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 123(2), pages 519-547, September.
    29. Diewert, W. Erwin & Fox, Kevin J., 2017. "Decomposing productivity indexes into explanatory factors," European Journal of Operational Research, Elsevier, vol. 256(1), pages 275-291.
    30. 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.
    31. C. O’Donnell, 2012. "An aggregate quantity framework for measuring and decomposing productivity change," Journal of Productivity Analysis, Springer, vol. 38(3), pages 255-272, December.
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