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Spatial econometric analysis of factors influencing regional energy efficiency in China

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Abstract

Increased environmental pollution and energy consumption caused by the country’s rapid development has raised considerable public concern, and has become the focus of the government and public. This study employs the super-efficiency slack-based model–data envelopment analysis (SBM–DEA) to measure the total factor energy efficiency of 30 provinces in China. The estimation model for the spatial interaction intensity of regional total factor energy efficiency is based on Wilson’s maximum entropy model. The model is used to analyze the factors that affect the potential value of total factor energy efficiency using spatial dynamic panel data for 30 provinces during 2000–2014. The study found that there are differences and spatial correlations of energy efficiency among provinces and regions in China. The energy efficiency in the eastern, central, and western regions fluctuated significantly, and was mainly because of significant energy efficiency impacts on influences of industrial structure, energy intensity, and technological progress. This research is of great significance to China’s energy efficiency and regional coordinated development.

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Authors and Affiliations

  1. School of Statistics and Applied Mathematics, Anhui University of Finance and Economics, Bengbu, China

    Malin Song & Yu Chen

  2. School of Business, Central South University, Changsha, China

    Qingxian An

Authors
  1. Malin Song
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  2. Yu Chen
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  3. Qingxian An
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Correspondence to Malin Song.

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Responsible editor: Philippe Garrigues

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Song, M., Chen, Y. & An, Q. Spatial econometric analysis of factors influencing regional energy efficiency in China. Environ Sci Pollut Res 25, 13745–13759 (2018). https://doi.org/10.1007/s11356-018-1574-5

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  • DOI: https://doi.org/10.1007/s11356-018-1574-5

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