4.6 Article

Analysis of the Water-Energy Coupling Efficiency in China: Based on the Three-Stage SBM-DEA Model with Undesirable Outputs

期刊

WATER
卷 11, 期 4, 页码 -

出版社

MDPI
DOI: 10.3390/w11040632

关键词

Water-Energy coupling efficiency; Three-Stage Data Envelopment Analysis (DEA); Slacks-Based Measure (SBM); Stochastic Frontier Approach (SFA); index system of environmental factors

资金

  1. Key Program of the Chinese National Social Science Foundation [16AJY009]

向作者/读者索取更多资源

Although the relationships between water and energy systems have been widely researched globally, such studies have not properly considered the coupling and driving mechanisms of the nexus between water and energy. Based on panel data from 30 Chinese provinces and cities, we used a three-stage Slacks-Based Measure model for Data Envelopment Analysis (SBM-DEA) to estimate the Water-Energy coupling efficiency in China from 2003-2015. Using the Stochastic Frontier Approach (SFA) regression model, we constructed an index of environmental factors that affect the Water-Energy coupling efficiency from the four aspects of resource environment, social environment, economic environment, and ecological environment. The results indicate that the Water-Energy coupling efficiency scores in most provinces in China are high and stable, and that the coupling efficiency of water and energy in China has a distribution pattern of northeast > east > west > central. Compared to the results in the first stage of analysis, the efficiency values in the third stage (after removal of environmental and stochastic factors) were smaller, illustrating that the coupling efficiency of water and energy in China depends on a favorable external environment. In the sample period, we also found that the improvement of the resource and social environments was the most conducive way to improve the Water-Energy coupling efficiency. Overall, the management level of technological innovation in China still has some room for improvement.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.6
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据