Journal
ECOLOGICAL INDICATORS
Volume 69, Issue -, Pages 559-570Publisher
ELSEVIER
DOI: 10.1016/j.ecolind.2016.05.016
Keywords
Energy-environment efficiency; DEA window analysis; Tobit regression model; CO2 emission
Categories
Funding
- National Natural Science Foundation of China [71273028, 71322103]
- National Special Support Program for High-Level Personnel from the central government of China
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The transportation sector, particularly the road and the railway sectors, is an important source of CO2 emissions in China. This study combines the non-radial data envelopment analysis (DEA) model with window analysis to measure the energy-environment efficiency of the road and railway sectors of 30 provinces in China, then uses the Tobit regression model to analyze the factors affecting the energy environment efficiency. The findings suggest that, first of all, although these two sectors are both with high energy-environment efficiency, there is a higher probability for railway sector to improve its energy environment efficiency than that of road sector, with the average energy-environment efficiency 0.9307 and 0.9815, respectively. Second, the road sector in eastern China with the highest average energy environment efficiency, lower in the western region, and lowest in the central region. As for the railway sector, the western region has the highest average energy-environment efficiency, followed by the central and the eastern regions. Third, the relationship between energy-environment efficiency and income level in the road and railway sectors follow the U-shaped and inverted U-shaped curves, respectively. (C) 2016 Elsevier Ltd. All rights reserved.
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