摘要
基于1997-2016年东北三省能源消费产生的碳排放量,运用Tapio脱钩模型探究了碳排放与经济增长的脱钩关系,利用要素分解、协整检验和脉冲响应分析等方法,深入研究了碳排放量的影响因素及其交互作用关系。结果表明:1)在研究区间内,各地区脱钩状态变化幅度较大。2)GDP对碳排放量增加的促进作用最明显,石油消费和人口因素次之,多因子交互作用比单因子作用更明显。3)GDP和碳排放量在不同滞后阶数呈现出平稳状态,二者之间存在着长期协整的相关关系。当GDP对碳排放量发起冲击时,黑龙江省的碳排放量先增后降;当碳排放量对GDP发起冲击时,吉林省、辽宁省的GDP的变化较为平稳。研究结论有利于了解影响碳排放量的各类影响因素,为政府进行合理决策和政策制定提供科学支撑。
Based on the carbon emissions generated by energy consumption in the three northeast provinces of China from 1997 to 2016,the decoupling relationship between carbon emissions and economic growth was explored by Tapio decoupling model,and the influencing factors of carbon emissions and their interaction were studied in depth by using element decomposition,cointegration test and impulse response analysis.The results show that:1)In the study period,the decoupling state of each region changed greatly.2)GDP has the most obvious promoting effect on the increase of carbon emissions,followed by the effect of oil consumption and demographic factor;the interaction effect of multiple factors is more obvious than that of single factor.3)GDP and carbon emissions are stable at different lag orders,and there is a correlation between them for long-term cointegration.When GDP has an impact on carbon emissions,the carbon emissions of Heilongjiang Province first increase and then decrease;when carbon emissions have an impact on GDP,the changes in GDP of Jilin Province and Liaoning Province are relatively stable.The conclusions of this study are conducive to the understanding of various influencing factors affecting carbon emissions and provide scientific support for the government to make reasonable decisions and policies.
作者
王勤升
王宁宁
韩欢欢
WANG Qinsheng;WANG Ningning;HAN Huanhuan(School of Information Management,Beijing Information Science&Technology University,Beijing 100192,China)
出处
《北京信息科技大学学报(自然科学版)》
2024年第1期76-82,共7页
Journal of Beijing Information Science and Technology University
基金
中国科学院重大课题(20210028)
北京市教委社科计划一般项目(SM202011232008)。
关键词
东北三省
脱钩模型
要素分解
协整检验
脉冲响应分析
three northeastern provinces of China
decoupling model
element decomposition
cointegration test
impulse response analysis