摘要:为了对我国城市水资源利用效率问题进行分析和评价，本文基于数据包络分析方法，从农业、工业、生活、社会等几个方面共选取了5个输入指标及6个输出指标，利用AIC信息准则（Akaike information criterion）进行了变量选择，构建了较为科学合理的用水效率评价指标体系.在此基础上，采用香农熵指数提升了传统CCR（由Charnes A，Cooper W W，Rhodes E提出）模型的识别能力，选取我国31个省会城市为研究对象，给出了省会城市水资源效率的完整排名。结果表明：①绝大部分城市综合效率得分（CES，Comprehensive efficiency score）普遍不高，投入产出比仍有较大的进步空间；②拉萨、北京、天津、银川、海口、上海等城市CES得分相对较高，这说明一个城市水资源利用效率的高低与经济发展水平可能没有必然的联系，其他城市应结合自身情况向CES得分靠前的城市进行学习；③重庆、南宁、南昌、长沙等水资源较丰富的城市CES得分反而较低，表明这些城市可能存在大量水资源被浪费，应建立起节水机制，同时优化产业结构。



Abstract:Improving efficiency of water resources utilization is the key to alleviate the contradiction between water supply and demand while achieving sustainable economic and social development. In order to analyze and evaluate the water consumption efficiency of the provincial capital cities in China, this paper selected five input indicators and six output indicators from agriculture, industry, life and society based on data envelopment analysis method. Then we used Akaike Information Criterion (AIC) for variable selection and constructed a scientific and rational water-use efficiency indicator system. On this basis, the Shannon Entropy Index is used to enhance the recognition ability of the traditional CCR model, and the complete ranking of water resources efficiency in the provincial capitals is given. The results show that (1) the comprehensive efficiency scores (CES) of most cities are not high. Their input-output ratio still has a lot of room for improvement. (2) The scores of CES in Lasa, Beijing, Tianjin, Yinchuan, Haikou, Shanghai etc. are relatively high, which indicate that there may be no necessary connection between the level of water use efficiency of a city and the level of economic development. At the same time, other cities should combine their own conditions to learn from cities with higher scores in CES. (3) Cities such as Chongqing, Nanning, Nanchang, and Changsha are rich in water resources, but the CES is not ideal. This shows that a large amount of water resources may be wasted and these cities should optimize their industrial structures while establishing a water-saving mechanism. In addition, due to the lack of variable selection system in most literatures and the inadequacy of traditional models in the ability of efficiency identification, this paper innovatively combined the AIC variable selection method, data envelopment analysis method, and Shannon Entropy Index method. The combination of the three methods can achieve the advantages and disadvantages of complementarity, not only fully consider a large number of input and output variables, make the analysis closer to reality, the variable indicator system obtained by the AIC criterion also perfectly conforms to the meaning of actual water resource utilization efficiency.





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