• 李茜,胡昊,罗海江,林兰钰,史宇,张殷俊,周磊.我国经济增长与环境污染双向作用关系研究——基于PVAR模型的区域差异分析[J].环境科学学报,2015,35(6):1875-1886

  • 我国经济增长与环境污染双向作用关系研究——基于PVAR模型的区域差异分析
  • Two-way coupling relationship between economic growth and environmental pollution—Regional difference analysis based on PVAR model
  • 基金项目:林业公益性行业科研专项经费项目(No.201304301)
  • 作者
  • 单位
  • 李茜
  • 中国环境监测总站, 北京 100012
  • 胡昊
  • 环境保护部信息中心, 北京 100029
  • 罗海江
  • 中国环境监测总站, 北京 100012
  • 林兰钰
  • 中国环境监测总站, 北京 100012
  • 史宇
  • 中国环境监测总站, 北京 100012
  • 张殷俊
  • 中国环境监测总站, 北京 100012
  • 周磊
  • 中国环境监测总站, 北京 100012
  • 摘要:采用PVAR模型,应用31个省份1985—2011年的面板数据,研究了我国经济增长与环境污染之间双向动态作用关系的时空特征.分别在东、中、西部三大区域,用计量经济学方法检验面板数据的有效性,以及变量间的协整性,基于PVAR模型研究了包含工业性和生活性污染、废水和废气污染的12项污染物排放指标与人均GDP之间的动态冲击响应特征.结果表明,不仅经济增长是污染物排放变化的重要原因,污染物排放对经济发展的反向作用也非常显著,并且这种双向作用关系存在显著的区域差异性,西部地区经济增长与环境质量之间的矛盾最为突出,中部地区次之,东部地区相对较为弱化.方差分解的结果表明,目前我国经济增长对环境污染的预测方差贡献度较大,而环境污染对经济增长反馈和约束的贡献度相对较小.
  • Abstract:This study estimates the dynamic two-way coupling relationship between economic growth and environmental pollution based on the panel data of 31 provinces during 1985—2011 using PVAR model. Econometric methods are used in eastern, central and western regions to test the data validation and cointegration between variables, and then analyze the impulse response functions between per capita GDP and 12 environmental pollution indices, including industrial and domestic pollution, waste water discharges and exhaust emissions. The estimate results show that apart from the marked impact from economic growth on environmental pollution, environmental pollution also has significant feedback mechanism to the regional economic growth. In addition, this two-way coupling relationship shows significant regional differences. The contradiction between economic growth and environmental pollution in the western region is the most serious, while the central region is moderate and the contradiction is the lowest in eastern region. The variance decomposition result indicates that, at present, economic growth is the main contributor to explain the forecasting mean square error of the environmental pollution, but the feedback mechanism is relatively weak.

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