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Natural Hazards

, Volume 95, Issue 1–2, pp 343–362 | Cite as

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

  • Jia-Yin Yin
  • Yun-Fei Cao
  • Bao-Jun TangEmail author
Original Paper
  • 115 Downloads

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.

Keywords

Energy environment efficiency Three-stage DEA model Regional equity China 

Notes

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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Copyright information

© Springer Nature B.V. 2018

Authors and Affiliations

  • Jia-Yin Yin
    • 1
    • 2
    • 3
    • 4
    • 5
  • Yun-Fei Cao
    • 1
    • 2
    • 3
  • Bao-Jun Tang
    • 1
    • 2
    • 3
    • 4
    • 5
    Email author
  1. 1.Center for Energy and Environmental Policy ResearchBeijing Institute of TechnologyBeijingChina
  2. 2.School of Management and EconomicsBeijing Institute of TechnologyBeijingChina
  3. 3.Beijing Key Lab of Energy Economics and Environmental ManagementBeijingChina
  4. 4.Sustainable Development Research Institute for Economy and Society of BeijingBeijingChina
  5. 5.Collaborative Innovation Center of Electric Vehicles in BeijingBeijingChina

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