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Exploring carbon emissions, economic growth, energy and RD investment in China by ARDL approach

机译:通过ARDL方法探索中国碳排放,经济增长,能源和研发投资

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This paper examines the causal relationship among economic growth, energy structure, R&D investment and carbon emission in China by using autoregressive distributed lag bounds testing approach of cointegration during the period of 1990–2011. In order to examine this linkage, theauthors use the two-step procedures. Firstly, theauthors conducted the unit root tests to measure whether the single integrated of time series is not more than 1. Secondly, theauthors explore the long-run relationships between the variables by using ARDL bounds testing approach complemented by Johansen-Juselius maximum likelihood procedure in a multivariate framework. The findings are as follows:when carbon emissions and economic growth, respectively, are the dependent variable, the other independent variables show the long-term stability cointegration relationship of the dependent variable. Whether in the short-run or long-run relationship, the impact of economic growth and R&D investment on carbon emission is not statistically significant. In the long term and short term relationships, carbon emissions have a positive impact on the economic growth. However, energy structure has a negative impact on the economic growth. The decrease in energy structure will cause carbon emissions reduction and boost economic growth in both the long-run and short-run period. Therefore, China's government should give more attention to the optimization of energy structure and make a reasonable and feasible energy saving policy.
机译:本文通过在1990 - 2011年期间使用自回归分布滞后滞后测试方法,研究了中国经济增长,能源结构,研发投资和碳排放的因果关系。为了检查这一联系,末端使用两步程序。首先,TheAuthors进行了单位根测试,以测量单一的时间序列序列是否不超过1.其次,通过使用Johansen-Juselius最大似然程序互补的ARDL绑定测试方法探讨变量之间的长期关系多变量框架。结果如下:当碳排放和经济增长分别是依赖变量时,其他独立变量显示了因变量的长期稳定协整协整。无论是在短期或长期关系中,经济增长和研发投资对碳排放的影响都没有统计学意义。在长期和短期关系中,碳排放对经济增长产生了积极影响。然而,能量结构对经济增长产生负面影响。能源结构的减少将导致碳排放减少,并在长期和短期期间提高经济增长。因此,中国政府应更加关注能源结构的优化,并制定合理和可行的节能政策。

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