基于VAR模型的中国能源消费碳排放影响因素分析

发布时间：2018-01-24 18:26

本文关键词： 碳排放量 VAR模型协整分析 Granger因果关系脉冲响应函数方差分解　出处：《生态经济》2014年01期 　论文类型：期刊论文

【摘要】：基于向量自回归(vector autoregression,VAR)模型分析方法,从能源消费总量、人均GDP、城市化水平和能源强度四个指标出发,分阶段分析了我国1953~2011年间的能源消费碳排放情况。研究表明:能源消费总量和城市化水平是驱动碳排放的核心动力,且两者作用相反。能源消费总量对碳排放起到正向驱动作用,碳排放对其响应与能源强度类似,持久且不稳定,说明中国能源"双控"政策的效果显现仍需很长一段时间,但两者的结构冲击对碳排放贡献大,效果明显。而城市化水平对碳排放有反向驱动作用,其响应可在短期内达到平稳状态,加之其结构冲击对碳排放贡献度可达10%,使之成为未来降低我国碳排放的有力措施。与此同时,把握住人均GDP与碳排放互为Granger因的特殊关系,积极推行绿色GDP,也可有效降低碳排放。
[Abstract]:Based on vector autoregressive vector autoregressive (VAR) model analysis method, total energy consumption, per capita GDP. Urbanization level and energy intensity four indicators. The carbon emissions of energy consumption in China from 1953 to 2011 are analyzed in stages. The results show that the total energy consumption and the level of urbanization are the core driving forces of carbon emissions. The total energy consumption plays a positive driving role on carbon emissions, and the response of carbon emissions is similar to the energy intensity, which is persistent and unstable. It shows that the effect of China's energy "double control" policy is still a long time to appear, but the structural impact of both has a great contribution to carbon emissions, the effect is obvious, and the urbanization level has a reverse driving effect on carbon emissions. The response can be stable in a short period of time, and the contribution of structural shock to carbon emissions can reach 10%, which makes it a powerful measure to reduce carbon emissions in China in the future. To grasp the special relationship between GDP per capita and carbon emissions as a result of Granger, to actively promote green GDP can also effectively reduce carbon emissions.
【作者单位】：华中科技大学文华学院;
【基金】：国家自然科学基金项目(71171089) 湖北省自然科学基金项目(2012FFB02702)
【分类号】：F426.2;F205;F224
【正文快照】： 能源活动CO2排放量作为衡量一个国家CO2排放情况的重要指标[1],已引起全球广泛关注。据丁铎尔气候变化研究中心的科研报告《维持全球升温低于2℃挑战》显示,2011年中国碳排放总量居全球首位。面对如此严峻的减排形势,中国共产党在十八大中首次将着力推进低碳发展理念写入党代

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