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Is cleaner more efficient? Exploring nonlinear impacts of renewable energy deployment on regional total factor energy efficiency

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  • Wang, Yongpei
  • Yan, Qing

Abstract

Improving the deployment and penetration of renewable energy is considered to be the fundamental way to solve environmental problems, but whether higher penetration of renewable energy means higher energy efficiency remains to be empirically tested. To reveal the relationship between cleanliness and efficiency in the energy sector, this paper first uses the three-stage data envelopment analysis (DEA)method to measure the total factor energy efficiency (TFEE) of 30 provinces in China, and then applies static and dynamic panel threshold regression (PTR)models to estimate the nonlinear effect of renewable energy share on TFEE. The results show that renewable energy is usually beneficial for improving TFEE, but there are prominent heterogeneity and nonlinear characteristics in net electricity exporting and net electricity importing provinces. Renewable energy in low rather than high regimes can significantly improve energy efficiency, indicating that provinces with lower levels of economic development and energy consumption receive higher marginal energy efficiency and are more likely to achieve sustainable development goals. More renewable energy quotas should be given to economically developed and high energy consuming provinces, and comprehensive energy efficiency guarantees and improvement measures must be provided to achieve optimal emission mitigation.

Suggested Citation

  • Wang, Yongpei & Yan, Qing, 2023. "Is cleaner more efficient? Exploring nonlinear impacts of renewable energy deployment on regional total factor energy efficiency," Renewable Energy, Elsevier, vol. 216(C).
    • Handle: RePEc:eee:renene:v:216:y:2023:i:c:s0960148123010248
    DOI: 10.1016/j.renene.2023.119110
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    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. Santos, João & Borges, Afonso S. & Domingos, Tiago, 2021. "Exploring the links between total factor productivity and energy efficiency: Portugal, 1960–2014," Energy Economics, Elsevier, vol. 101(C).
    3. Tanaka, Kenta & Managi, Shunsuke, 2021. "Industrial agglomeration effect for energy efficiency in Japanese production plants," Energy Policy, Elsevier, vol. 156(C).
    4. Berner, Anne & Bruns, Stephan & Moneta, Alessio & Stern, David I., 2022. "Do energy efficiency improvements reduce energy use? Empirical evidence on the economy-wide rebound effect in Europe and the United States," Energy Economics, Elsevier, vol. 110(C).
    5. Hansen, Bruce E., 1999. "Threshold effects in non-dynamic panels: Estimation, testing, and inference," Journal of Econometrics, Elsevier, vol. 93(2), pages 345-368, December.
    6. Wang, Zhao-Hua & Zeng, Hua-Lin & Wei, Yi-Ming & Zhang, Yi-Xiang, 2012. "Regional total factor energy efficiency: An empirical analysis of industrial sector in China," Applied Energy, Elsevier, vol. 97(C), pages 115-123.
    7. Wen, Jun & Okolo, Chukwuemeka Valentine & Ugwuoke, Ifeanyi Celestine & Kolani, Kibir, 2022. "Research on influencing factors of renewable energy, energy efficiency, on technological innovation. Does trade, investment and human capital development matter?," Energy Policy, Elsevier, vol. 160(C).
    8. 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.
    9. Bruce E. Hansen, 2000. "Sample Splitting and Threshold Estimation," Econometrica, Econometric Society, vol. 68(3), pages 575-604, May.
    10. Sueyoshi, Toshiyuki & Mo, Fei & Wang, Derek D., 2022. "Sustainable development of countries all over the world and the impact of renewable energy," Renewable Energy, Elsevier, vol. 184(C), pages 320-331.
    11. Zhang, Yu & Jin, Warren & Xu, Miao, 2021. "Total factor efficiency and convergence analysis of renewable energy in Latin American countries," Renewable Energy, Elsevier, vol. 170(C), pages 785-795.
    12. Dhakouani, Asma & Znouda, Essia & Bouden, Chiheb, 2019. "Impacts of energy efficiency policies on the integration of renewable energy," Energy Policy, Elsevier, vol. 133(C).
    13. Wilson, Bruce & Trieu, Luan Ho & Bowen, Bruce, 1994. "Energy efficiency trends in Australia," Energy Policy, Elsevier, vol. 22(4), pages 287-295, April.
    14. Zhao, Xin & Mahendru, Mandeep & Ma, Xiaowei & Rao, Amar & Shang, Yuping, 2022. "Impacts of environmental regulations on green economic growth in China: New guidelines regarding renewable energy and energy efficiency," Renewable Energy, Elsevier, vol. 187(C), pages 728-742.
    15. 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.
    16. Seo, Myung Hwan & Shin, Yongcheol, 2016. "Dynamic panels with threshold effect and endogeneity," Journal of Econometrics, Elsevier, vol. 195(2), pages 169-186.
    17. 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.
    18. Halleck Vega, Solmaria & van Leeuwen, Eveline & van Twillert, Nienke, 2022. "Uptake of residential energy efficiency measures and renewable energy: Do spatial factors matter?," Energy Policy, Elsevier, vol. 160(C).
    19. Wang, Yongpei & Yan, Weilong & Zhuang, Shangwen & Zhang, Qian, 2019. "Competition or complementarity ? The hydropower and thermal power nexus in China," Renewable Energy, Elsevier, vol. 138(C), pages 531-541.
    20. Wang, Yongpei & Yan, Weilong & Komonpipat, Supak, 2019. "How does the capacity utilization of thermal power generation affect pollutant emissions? Evidence from the panel data of China's provinces," Energy Policy, Elsevier, vol. 132(C), pages 440-451.
    21. Cartelle Barros, Juan José & Lara Coira, Manuel & de la Cruz López, María Pilar & del Caño Gochi, Alfredo, 2016. "Probabilistic life-cycle cost analysis for renewable and non-renewable power plants," Energy, Elsevier, vol. 112(C), pages 774-787.
    22. 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).
    23. Patterson, Murray G, 1996. "What is energy efficiency? : Concepts, indicators and methodological issues," Energy Policy, Elsevier, vol. 24(5), pages 377-390, May.
    24. Kneller, Richard & Manderson, Edward, 2012. "Environmental regulations and innovation activity in UK manufacturing industries," Resource and Energy Economics, Elsevier, vol. 34(2), pages 211-235.
    25. Michael E. Porter & Claas van der Linde, 1995. "Toward a New Conception of the Environment-Competitiveness Relationship," Journal of Economic Perspectives, American Economic Association, vol. 9(4), pages 97-118, Fall.
    26. 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).
    27. Chien, Taichen & Hu, Jin-Li, 2007. "Renewable energy and macroeconomic efficiency of OECD and non-OECD economies," Energy Policy, Elsevier, vol. 35(7), pages 3606-3615, July.
    28. Li, Ke & Lin, Boqiang, 2014. "The nonlinear impacts of industrial structure on China's energy intensity," Energy, Elsevier, vol. 69(C), pages 258-265.
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