中国广义环境库兹涅茨曲线协整分析
The Cointegration Analysis of the Generalized Environmental Kuznets Curve of China
摘要: 根据1998~2013年中国31个省域人均GDP (Yi,t)和SO2 (EPi,t)排放面板数据,对原始EKC回归方程进行改进,建立变指数γ-EKC回归方程。基于协整分析理论对面板数据进行平稳性检验,Fisher-ADF和PP-Fisher检验结论表明Yi,tYi,tγEPi,t水平序列非平稳,一阶差分序列平稳,即均为一阶单整序列I (1);分别拟合混合估计模型、个体固定效应模型和个体随机效应模型,当γ=3时,个体固定效应模型残差平方和最小,残差序列非平稳,回归方程非协整。本文的研究结论揭示了现有研究中基于原始二次或三次EKC回归方程之所以非协整,并非因为回归方程本身,而在于污染和收入代理变量之间的“虚假回归”关系。
Abstract: Based on the panel data of per capita GDP (Yi,t) and SO2 (EPi,) emissions across 31 provinces of China during the year 1998 and 2013, this paper improves the conventional regression model of EKC and the variational exponential model is established. Testing the stationarity of panel data according to the theory of cointegration analysis, results of Fisher-ADF test and PP-Fisher test show that the level sequences of Yi,t,Yi,tγ and EPi,t are non-stationary, and the first-order differences of them are stationary, which means they are integrated variables with the order of one (I (1)). Using pooled OLS, entity fixed-effect and entity random-effect techniques to fit the model respectively, we find that when γ=3, the sum of squared residuals (SSR) of the entity fixed-effect model is the smallest, but the residual series are non-stationary, and the regression equation does not reflect a cointegrating relationship. Conclusion dressed from this study implies that the failure of cointegration of the conventional EKC regression in EKC literature is not because of the quadratic or cubic functional form itself, but because of the spurious relationship between the indicators of pollutants and income agent.
文章引用:杨洲木, 蔡京京, 曹蔚. 中国广义环境库兹涅茨曲线协整分析[J]. 统计学与应用, 2021, 10(5): 805-815. https://doi.org/10.12677/SA.2021.105083

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