关键词: 环境库兹尼茨曲线, 空间相关性, 空间面板数据

Abstract:

In the past 20 years, the Environmental Kuznets Curve has been regarded as one of the most powerful tools in studying the relationship between economic growth and environmental pollution. Among the conventional study in Environmental Kuznets Curve, most researchers implicitly assume that regional pollution is not affected by the neighboring regions. So, from analytical viewpoint and empirical behavior, the traditional methods used to examine the Environmental Kuznets Curve are suspected for neglecting spatial dependence among different regions. Consequently, the environmental policies based on the conclusions are hard to be convinced. With a view to the above shortcoming in describing the Environmental Kuznets Curve with the traditional methods, this paper investigates the relationship between environmental pollution and economic growth in China using panel data models which takes the spatial dependence into account. In this study, we select five types of pollution including waste water emission, waste gas emission, sulfur dioxide mission, dust emission and smoke dust emission as the environmental indexes and per capita GDP as the income index with 28 provincial data from 1993 to 2005. The results show that: (1) Pollution has spatial dependence in China and spatial panel data model is more suitable for studying the Environmental Kuznets Curve; (2) Considering spatial effect, the estimate result seems to be more robust than OLS estimate. Because the emissions of pollution are not only effected by the per capita income in the same region, but also largely impacted by the emissions from neighboring regions. (3) Resident environment quality-income is relatively low and does not take up a greater proportion in consumption demand.

Key words: Environmental Kuznets Curve, spatial correlation, spatial panel data