Accessing provincial energy efficiencies in China's transport sector

Research output: Contribution to journalArticlepeer-review


Colleges, School and Institutes

External organisations

  • University of Birmingham
  • University of Mining and Technology


The transport sector is attracting increasingly attention in the context of climate change and sustainable development, for its rapidly growing demand for energy and heavy reliance on oil products. Especially in China, where the demands for transportation are tremendous and ever-increasing, it is worthy to explore the provincial variations in energy efficiency in the transport sector, in order to enhance energy efficiency and to promote energy savings in this sector. By using stochastic frontier analysis (SFA) approach, this paper calculates the provincial energy efficiency as well as energy saving potential in China's provincial transport sector over 2007–2016. Results suggest that China's national average energy input efficiency in the transport industry is 0.673 during the sample period, which implied that relatively large degree of non-efficiency exists in this sector. Besides, the increase of government support (GS), the improvement of road condition (RC) and public transport (PT) are influencing factors for the improvement of China's provincial energy efficiency in the transport industry. Additionally, energy saving potential in the transport sector is also estimated in this paper. It is shown that, although energy efficiency in the eastern China is the highest (much higher than the country-wide level), the estimated absolute amount of the energy saving potential in the eastern area is significantly larger than those in the central area and western area due to the fact that the eastern area contributes to the largest share of the total energy consumption in this sector.


Original languageEnglish
Pages (from-to)525-532
Number of pages8
JournalEnergy Policy
Early online date1 Oct 2018
Publication statusPublished - 1 Dec 2018


  • Energy efficiency, Energy-saving potential, Stochastic frontier analysis, Transport sector