Abstract
Traditional data envelopment analysis (DEA) models ignore the influence of environmental variables and statistical noise, which may result in biased efficiency estimates. To solve this problem, three-stage DEA models have been proposed and widely applied in many areas. This study evaluates China's regional energy efficiency by using a three-stage DEA model based on the statistical data of 2010 and discusses the divergence of three different efficiency assessment methods. The empirical results show that environmental factors indeed influence the regional energy efficiency performance. After adjusting the environmental variables, the national energy efficiency average estimated by the three-stage DEA model decreased significantly relative to the estimate of the traditional DEA model, but the environmental influence in different regions varies due to diverse features. Some regional averages were overestimated by using the traditional DEA model, while some regional averages were underestimated. The three-stage DEA model is able to reflect the true efficiency by eliminating environmental effects compared with other methods.
| Original language | English |
|---|---|
| Pages (from-to) | 262-276 |
| Number of pages | 15 |
| Journal | International Journal of Global Energy Issues |
| Volume | 36 |
| Issue number | 2-4 |
| DOIs | |
| Publication status | Published - 2013 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
Keywords
- China
- Environmental influence
- Evaluation
- Regional energy efficiency
- SFA
- Three-stage DEA model
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