上海市生态福利绩效评价研究

生态福利绩效是指自然消耗转化为福利水平的效率。随着全球生态约束时代的到来,自然资本变得绝对稀缺,如何在生态极限内提高人类的福利水平是可持续发展的终极目标。本文基于DEA方法,从投入产出角度构建了城市生态福利绩效评价指标体系,并结合主成分分析法(PCA),运用改进的基于非径向非角度的超效率DEA模型(Super-SBM模型)对上海市2006—2014年的生态福利绩效水平进行综合测评,并与2014年我国35个主要城市(省级和副省级城市)进行横向对比研究。结果表明:12006—2014年期间,上海的总体生态福利绩效水平不高,并未处于DEA有效的前沿面,其中仅3个年份为DEA有效,其余6个年份均为DEA无效,DEA有效年份数占样本总数的33.33%,但从整个发展态势来看,近几年来有逐步改善和提高的趋势。22014年,我国35个主要城市的生态福利绩效整体水平不高,深圳、海口排名前两位,而上海仅排名第30位,资源环境消耗过高是生态福利绩效值偏低的主要原因。从投入冗余情况来看,上海市在水资源和土地两方面消耗过高,存在过度冗余,环境污染排放也具有较大的优化空间,资源环境问题成为制约上海建设生态宜居城市的主要瓶颈。3PCA-DEA组合模型比DEA模型下所测算出来的绩效值更精确,且考虑松弛变量的非径向Super-SBM模型比基于径向的DEA模型精确度更高,对于相关领域的资源环境绩效或生态效率评价具有较好的适用性和借鉴价值。最后根据实证分析结果可知,上海应淘汰过剩产能并转变生产和生活消费方式、发展绿色低碳的共享经济,同时构建紧凑型城市,实现城市"精明增长"。

A study on Shanghai's ecological well-being performance

Ecological well-being performance (EWP) refers to the efficiency of natural depletion to deliver human well-being.With the advent of global ecological constraints, natural capital has become scarce, how to improve the human well-being level within the ecological limit is the ultimate goal of sustainable development.By adopting the input-output perspective, an attempt is made to establish an index system for urban ecological well-being performance evaluation;then, a revised DEA model (Super-SBM model) based on non-radial and non-angle is employed to make an overall assessment on Shanghai's EWP during the period 2006-2014.For an in-depth study, a comparative analysis is conducted among 35 major cities in China with the cross-sectional data of 2014.The results show as follows: ①The overall EWP of Shanghai is found at a relatively low level from 2006 to 2014, and falls out in the DEA effective frontier, as for the single year, only 3 years perform efficiently while the remain 6 six years are DEA inefficient, and the proportion of efficient years is 33.33% in terms of the sampling period.②In 2014, the average level of EWP among 35 major cities in China is also relatively low, top two belong to Shenzhen and Haikou while Shanghai ranks only in the 30th place due to its high resources consumption and severe environmental pollutions.Considering the input slacks, there is an excessive redundancy both in water consumption and land use for urban construction in Shanghai compared with the remaining major cities, and there is a big room for improvement.③The PCA-DEA model demonstrates a higher preciseness than traditional DEA models in terms of efficiency evaluation.Furthermore, a non-radial slack-based measure (SBM) of super efficiency in Data Envelopment Analysis (DEA) is better than the traditional DEA models with a radial angle.Finally, based on the results, Shanghai should further facilitate its industrial structure adjustment and eliminate excess manufacturing capacity, change the mode of production and consumption, develop green and low-carbon sharing economy, and construct a compact city to achieve smart growth.