考虑非管理因素的工业污染治理效率测度

Measurement of industrial pollution treatment efficiency based on non-management factors

考虑非管理因素和网络结构对效率测度结果的影响,将平行网络SBM模型与三阶段DEA方法结合,对我国各省(市、自治区)在2010—2015年期间的工业污染治理效率进行了测算和比较。研究结果表明,人均GDP、城镇化水平和环境规制对工业污染的治理效率有显著影响。剔除非管理因素的干扰后,河北和辽宁处于效率前沿面,大部分省(市、自治区)的工业污染治理效率明显降低,并且各个省份的效率呈现出集聚效应。从区域的角度看,东北地区、华北地区以及华东地区的三种效率明显高于其他地区,西北地区的各个效率值都极低;从工业污染治理的两个子过程看,我国工业废水的治理效率普遍低于工业废气的治理效率,废水治理大都处于中低水平,而废气治理在各个水平的分布相对均衡。

Considering the impacts of non-management factors and network structure on efficiency measurement, parallel network SBM model was combined with the three-stage DEA method to measure and compare the industrial pollution treatment efficiency of various provinces(cities and autonomous regions) in China during 2010—2015. The empirical results showed that per-capital GDP, urbanization level and environmental regulations had significant effects on industrial pollution treatment efficiency. After the non-management factors were excluded, Liaoning and Hebei were on the efficiency frontier, and the efficiencies of most provinces decreased obviously. Besides, the efficiency of each province showed the agglomeration effect. From a regional point of view, the northeast China, north China and east China behaved better than other areas, and the northwest China performed worst. Seeing from two sub-processes of industrial pollution treatment, the efficiency of industrial wastewater treatment in China was generally lower than that of waste gas treatment. The wastewater treatment efficiency of most provinces was at low and medium levels, while the waste gas treatment efficiency was more evenly distributed at different levels.