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Fairness of China’s provincial energy environment efficiency evaluation: empirical analysis using a three-stage data envelopment analysis model

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Abstract

China has become the world’s largest carbon emitter since 2007; thus, reducing future emission has become an arduous task. Calculating energy efficiency fairly is paramount for formulating energy policies, given the different development levels of provinces. This study employed a three-stage data envelopment analysis model that considered environmental constraints to evaluate the energy efficiency of China’s 30 provinces in 2015 and redefined traditional energy efficiency as energy environment efficiency which calculated under environmental constraints. Different factors, such as urban development level and industrial structure in relation to energy environment efficiency, were analyzed. Three main results were obtained. First, the average energy environment efficiency in 2015 was only 0.73, which showed that China has roughly 30% capacity for improvement in the future. Second, stochastic frontier analysis demonstrated that the industrial structure, energy consumption structure, and central heating systems exerted negative impacts, and the level of city design and the degree of openness exerted positive effects on energy environment efficiency. Third, capital, manpower, and the extent of industrial concentration in central and western regions should be increased to improve China’s energy environment efficiency.

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Notes

  1. Capital was calculated from the consistent price in 1978. Labor was calculated through the Chinese statistical yearbook. The outputs consisted of desirable and undesirable factors. The industrial structure was calculated through the proportion of industrial added value to the GDP of a single province. The urbanization rate was determined through the share of urban population in the total population of one province. The quantity of coal consumption was measured by the proportion of coal consumption within the total energy consumption. The passiveness of the economy was measured through the volume of foreign trade to GDP. The quantum of electricity consumption was measured by the proportion of electricity consumption of each area to the total energy consumption. If one province was considered a region that was part of the central heating system, it was represented as 1; otherwise, it was 0.

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Acknowledgements

We gratefully acknowledge the financial support from the National Natural Science Foundation of China (Grant Nos. 71573013, 71521002, and 71642004), Special Items Fund for Cultivation and Development of Beijing Creative Base (Grant No. Z171100002217023), Key Project of Beijing Social Science Foundation Research Base (Grant No. 15DJA084), National Key R&D Program (Grant No. 2016YFA0602603), and Special Items Fund of Beijing Municipal Commission of Education.

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Authors and Affiliations

  1. Center for Energy and Environmental Policy Research, Beijing Institute of Technology, Beijing, 100081, China

    Jia-Yin Yin, Yun-Fei Cao & Bao-Jun Tang

  2. School of Management and Economics, Beijing Institute of Technology, Beijing, 100081, China

    Jia-Yin Yin, Yun-Fei Cao & Bao-Jun Tang

  3. Beijing Key Lab of Energy Economics and Environmental Management, Beijing, 100081, China

    Jia-Yin Yin, Yun-Fei Cao & Bao-Jun Tang

  4. Sustainable Development Research Institute for Economy and Society of Beijing, Beijing, 100081, China

    Jia-Yin Yin & Bao-Jun Tang

  5. Collaborative Innovation Center of Electric Vehicles in Beijing, Beijing, 100081, China

    Jia-Yin Yin & Bao-Jun Tang

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  1. Jia-Yin Yin
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  2. Yun-Fei Cao
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Correspondence to Bao-Jun Tang.

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Yin, JY., Cao, YF. & Tang, BJ. Fairness of China’s provincial energy environment efficiency evaluation: empirical analysis using a three-stage data envelopment analysis model. Nat Hazards 95, 343–362 (2019). https://doi.org/10.1007/s11069-018-3399-4

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