Study on the relationship between economic growth andenvironmental pollution based on the Weibull andGamma specifications
基于Weibull函数和Gamma函数的环境污染与经济增长的关系

In the past twenty 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.Conventional studies usually use the linear model or the log-linear model to examine the existence of the Environmental Kuznets Curve.However,from analytical viewpoint and empirical behavior,the performance of the linear model or the log-linear model is suspected for their strict restrictions,such as linearity,nonnegative property,and symmetry.Consequently,conventional linear methods for the Environmental Kuznets Curve studies can not be a fine econometric tool.With a view to the above shortcomings in describing the Environmental Kuznets Curve with the linear model and the log-linear model,this paper investigates the relationship between economic growth and environmental pollution in China,using panel data models with the Weibull specification and the Gamma specification,where all the three parameters are used to describe the "shape","scale" and "shift" of the curves,respectively.In this study,we select per capita waste water emission,per capita waste gas emission and per capita solid wastes generated as the environmental indexes,and per capita gross domestic product(GDP) as the income index with the 29 provincial data over the period from 1989 to 2005.The results show that panel data models with the Weibull specification and the Gamma specification are both simulated better than that with the log-linear model,and their parameters have good explanatory capability.It is also suggested that with the rise of per capita income,per capita waste water emission in China first increases and then decreases,appearing a turning point around 25 000 yuan,while per capita solid wastes generated and per capita waste gas emission take on monotonously increasing relationships which have quite high income turning points.