SHU-UTS SILC Business School, Shanghai University, China.
SHU-UTS SILC Business School, Shanghai University, China; UTS Business School, University of Technology Sydney, Australia.
J Environ Manage. 2019 Oct 15;248:109244. doi: 10.1016/j.jenvman.2019.07.015. Epub 2019 Jul 13.
This paper presents new evidence on the impact of industrial agglomeration on environmental performance with a sample of prefectural-cities in China. When environmental performance is represented by pollution intensity, the impacts of industrial agglomeration on pollution intensity in terms of sulfur dioxide and soot show the heterogeneous pattern. The results support the existence of a non-linear pattern between agglomeration and emission intensity of sulfur dioxide, whereas the non-linear model could not hold for the emission intensity of soot. However, when we measure environmental performance with environmental efficiency estimated by a data envelopment analysis approach, it documents a U-shape relationship between industrial agglomeration and environmental efficiency. Specifically, environmental efficiency deteriorates in the early stage of industrial agglomeration and then improves as local industrial agglomeration proceeds. Different estimation strategies provide consistent evidence to verify such U-shape pattern.
本文利用中国地级市样本，提供了产业集聚对环境绩效影响的新证据。当环境绩效以污染强度来表示时，产业集聚对二氧化硫和烟尘污染强度的影响呈现出异质模式。结果支持集聚与二氧化硫排放强度之间存在非线性模式的存在，而对于烟尘排放强度来说，这种非线性模型并不成立。然而，当我们用数据包络分析方法估算的环境效率来衡量环境绩效时，它记录了产业集聚与环境效率之间存在着 U 型关系。具体来说，环境效率在产业集聚的早期阶段恶化，然后随着当地产业集聚的推进而改善。不同的估计策略提供了一致的证据来验证这种 U 型模式。
