基于动态面板模型的中国区域碳排放影响因素研究

Research on Influential Factors of Regional Carbon Dioxide Emissions in China: Based on Dynamic Spatial Panel Model

摘要:

摘要：从省份层面研究低碳转型的关键因素，对发现碳减排潜力具有重要的现实指导意义。通过构建动态面板模型和系统矩估计方法，对影响碳排放强度的因素进行了研究。结果表明：(1). 碳排放强度滞后项对碳排放强度具有显著的正向效应，高碳排放省份的动态锁定效应不容忽视。(2). 人均GDP与产业结构对碳排放强度具有显著正向效应，环境库兹涅茨假说成立。(3). 研发投入对碳排放强度具有显著的负向作用，而人口、能源结构和外商直接投资未产生显著作用。因此，持续优化产业结构和加大绿色技术研发投入力度将是中国未来加速区域低碳转型的主要潜力方向，同时如何缓解高碳排放省份的动态锁定效应也是未来低碳经济转型中需重视的课题。

Abstract:

Abstract: Studying key factors of low carbon transformation from province level has great practical guiding significance for discovery carbon emission reduction potential. In this paper constructed dynamic panel data model and applied System-Generalized Method of Moments (SYS-GMM) to study influential factors affecting carbon emission intensity. Results are as follows: Firstly, lag variable of the explained variable (yt-1) is significant positive related to carbon emission intensity, dynamic locking-in effect of high carbon emission cannot be ignored. Secondly, GDP per capita and the industrial structure are significant positive factors, environmental Kuznets hypothesis is supported. Finally, R&D input has a significant negative related to carbon emission intensity，but urban population ratio, energy structure and foreign investment are not significant. Therefore, continuing optimize industrial structure and increasing investment in green technology research and development will be the main potential direction for China to accelerate regional low carbon transformation process。Simultaneously, how to relieve the dynamic locking-in effect of high carbon emission provinces is also a topic that needs attention for low carbon economy transformation in the future.