Due to the implementation of “electrical energy substitution” strategy in China, the proportion of electrical energy in terminal energy consumption is increasing. The improvement of electrical energy efficiency could increase overall energy efficiency. Thus, a special attention should be paid on electrical energy efficiency. An input-oriented epsilon-based measure-DEA (data envelopment analysis) model was used to measure electrical energy efficiency from the perspective of total factor, and the spatial-temporal variability of electrical energy efficiency was investigated. Results draw that the overall electrical energy efficiency is relatively low and shows a downward trend. The eastern region has the best scores of electrical energy efficiency, followed by the central region and then the western region. Furthermore, the main associated determinants were investigated by panel Tobit regression model. It was found that the effect of industrial structure and economic opening degree on electrical energy efficiency is positive on the whole country level, whereas the effect of government intervention and urbanization is negative. From a regional perspective, there are great differences in the effect of each influencing factors. Some corresponding policy recommendations are given.
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The project was jointly supported by the Humanities and Social Sciences Planned Fund of Ministry of Education of China (Grant No. 19YJA630103), the Open Funds of Regional Innovation Capabilities Monitoring and Analysis Soft Science Research Base of Hubei Province (Grant No. HBQY2020z12 and No. HBQY2020z05) and the Fundamental Research Funds for the Central Universities, China University of Geosciences (Wuhan) (Grant No. CUGQY1942).
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1. Electrical energy efficiency in China is decreasing.
2. Improving industrial structure could increase electrical energy efficiency.
3. Economic opening degree has positive effect on electrical energy efficiency.
Responsible editor: Nicholas Apergis
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Guang, F. Electrical energy efficiency of China and its influencing factors. Environ Sci Pollut Res (2020). https://doi.org/10.1007/s11356-020-09486-6
- Electrical energy efficiency
- Undesirable results
- Epsilon-based measure