China's strategy for carbon intensity mitigation pledge for 2020: evidence from a threshold cointegration model combined with Monte-Carlo simulation methods

被引:18
|
作者
Li, Ke [1 ,2 ]
Lin, Boqiang [2 ]
机构
[1] Hunan Normal Univ, Coll Math & Comp, Changsha 410081, Hunan, Peoples R China
[2] Xiamen Univ, Collaborat Innovat Ctr Energy Econ & Energy Polic, China Inst Studies Energy Policy, Xiamen 361005, Fujian, Peoples R China
关键词
Carbon intensity; Economic growth; Structural transformation; Threshold cointegration model; Monte Carlo simulations; ECONOMIC-GROWTH; CO2; EMISSIONS; DIOXIDE EMISSIONS; ENERGY-CONSUMPTION; INDUSTRIAL-STRUCTURE; DECOMPOSITION; IMPACT; TARGET; SCALE; LMDI;
D O I
10.1016/j.jclepro.2015.12.093
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
This paper specifies a nonlinear threshold cointegration to analyze the nonlinear relationship between carbon intensity and economic growth in China. The tests and estimated results clearly confirm that fast paced economic growth-that is the growth rate of gross domestic product (GDP) is greater than 9.053%-impede the reduction of carbon intensity because it weakens the negative effects of tertiary industry development and energy efficiency on carbon intensity while it also increases the positive effect of unclean energy mix on carbon intensity. In order to find a moderate range of economic growth rate that is both beneficial for industrial structuring and energy mix transformation, and at the same time, facilitate reduction in carbon intensity, Monte Carlo simulations are employed. The results show when the growth fate of GDP is between 7% and 8.4%, it can promote "structural bonus" of industrial structure and energy consumption structure on carbon intensity, and carbon intensity in 2020 would decline by about 40.60% compared to 2005 level. These conclusions mean it is necessary for China to carefully set its economic growth target through transformation and optimization of its economic structure and energy mix in order to continuously reduce carbon intensity. (C) 2016 Elsevier Ltd. All rights reserved.
引用
收藏
页码:37 / 47
页数:11
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