How to improve total factor energy efficiency? An empirical analysis of the Yangtze River economic belt of China
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DOI: 10.1016/j.energy.2021.121375
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Citations
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- Li, Bo & Han, Yukai & Wang, Chensheng & Sun, Wei, 2022. "Did civilized city policy improve energy efficiency of resource-based cities? Prefecture-level evidence from China," Energy Policy, Elsevier, vol. 167(C).
- Hongcheng Shen & Zihao Yang & Yuxin Bao & Xiaonuan Xia & Dan Wang, 2022. "Impact of Urban Mining on Energy Efficiency: Evidence from China," Sustainability, MDPI, vol. 14(22), pages 1-16, November.
- Min Ge & Kaili Yu & Ange Ding & Gaofeng Liu, 2022. "Input-Output Efficiency of Water-Energy-Food and Its Driving Forces: Spatial-Temporal Heterogeneity of Yangtze River Economic Belt, China," IJERPH, MDPI, vol. 19(3), pages 1-15, January.
- Senhua Huang & Lingming Chen, 2023. "The Impact of the Digital Economy on the Urban Total-Factor Energy Efficiency: Evidence from 275 Cities in China," Sustainability, MDPI, vol. 15(4), pages 1-20, February.
- 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).
- Chen, Lei & Li, Ke & Chen, Shuying & Wang, Xiaofei & Tang, Liwei, 2021. "Industrial activity, energy structure, and environmental pollution in China," Energy Economics, Elsevier, vol. 104(C).
- Yu, Chenyang & Tan, Yuanfang & Zhou, Yu & Zang, Chuanxiang & Tu, Chenglin, 2022. "Can functional urban specialization improve industrial energy efficiency? Empirical evidence from China," Energy, Elsevier, vol. 261(PA).
- Jun Liu & Yu Qian & Yuanjun Yang & Zhidan Yang, 2022. "Can Artificial Intelligence Improve the Energy Efficiency of Manufacturing Companies? Evidence from China," IJERPH, MDPI, vol. 19(4), pages 1-18, February.
- Wang, Shiyan & Li, Chengjiang & Zhang, Wei & Sui, Jingyu & Negnevitsky, Michael, 2024. "Assessing the impact of prefabricated buildings on urban green total factor energy efficiency," Energy, Elsevier, vol. 297(C).
- Yuanying Chi & Wenbing Zhou & Songlin Tang & Yu Hu, 2022. "Driving Factors of CO 2 Emissions in China’s Power Industry: Relative Importance Analysis Based on Spatial Durbin Model," Energies, MDPI, vol. 15(7), pages 1-15, April.
- Pang, Qinghua & Dong, Xianwei & Zhang, Lina & Chiu, Yung-ho, 2023. "Drivers and key pathways of the household energy consumption in the Yangtze river economic belt," Energy, Elsevier, vol. 262(PA).
- Weiguang Wang & Yangyang Wang, 2023. "Regional Differences, Dynamic Evolution and Driving Factors Analysis of PM 2.5 in the Yangtze River Economic Belt," Sustainability, MDPI, vol. 15(4), pages 1-24, February.
- Ma, Guangcheng & Cao, Jianhua & Famanta, Mahamane, 2023. "Does the coordinated development of two-way FDI increase the green energy efficiency of Chinese cities? Evidence from Chinese listed companies," Structural Change and Economic Dynamics, Elsevier, vol. 65(C), pages 59-77.
- Menghan Zhang & Suocheng Dong & Fujia Li & Shuangjie Xu & Kexin Guo & Qian Liu, 2022. "Spatial–Temporal Evolution and Improvement Measures of Embodied Carbon Emissions in Interprovincial Trade for Coal Energy Supply Bases: Case Study of Anhui, China," IJERPH, MDPI, vol. 19(24), pages 1-16, December.
- Shao, Jun & Wang, Lianghu, 2023. "Can new-type urbanization improve the green total factor energy efficiency? Evidence from China," Energy, Elsevier, vol. 262(PB).
- Wang, Hai-jie & Tang, Kai, 2023. "Extreme climate, innovative ability and energy efficiency," Energy Economics, Elsevier, vol. 120(C).
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Keywords
Luenberger-Hicks-Moorsteen productivity indicator; Total factor energy efficiency; Yangtze River economic belt; Relative importance analysis;All these keywords.
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