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中国碳排放与经济发展存在倒U型关系吗?——考虑时间相关效应和异质性的研究
引用本文:田成诗,刘怡.中国碳排放与经济发展存在倒U型关系吗?——考虑时间相关效应和异质性的研究[J].运筹与管理,2021,30(9):232-239.
作者姓名:田成诗  刘怡
作者单位:东北财经大学 统计学院,辽宁 大连 116025
基金项目:2020年辽宁省高等学校创新人才支持计划;辽宁省教育厅科学研究项目(LN2019Z12)
摘    要:随着我国经济进入高质量发展阶段,经济发展与碳排放之间的关系日益受到关注。本文基于1997~2016年省级面板数据,运用非参数广义加性混合模型研究了中国碳排放与经济发展的关系。文中,不可观测的时间相关效应和残差自相关结构被作为独立变量加入模型,收入效应和时间相关效应对碳排放的影响可能存在异质性也予以考虑。实证结果显示,东部和中部地区的最适模型中收入效应具有异质性,西部地区的最适模型中包含异质性时间相关效应;中国碳排放与经济发展之间不存在倒U型关系;在未来的节能减排工作中,应充分考虑中国经济发展阶段性、区域差异性及碳排放驱动因素的异质性。

关 键 词:碳排放  广义加性混合模型  时间相关效应  异质性  
收稿时间:2017-11-14

Is There an Inverted U-shaped Relationship between Carbon Emissions and Economic Development in China? ——Accounting Time-related Effects and Heterogeneity
TIAN Cheng-shi,LIU Yi.Is There an Inverted U-shaped Relationship between Carbon Emissions and Economic Development in China? ——Accounting Time-related Effects and Heterogeneity[J].Operations Research and Management Science,2021,30(9):232-239.
Authors:TIAN Cheng-shi  LIU Yi
Institution:College of Statistics, Dongbei University of Finance and Economics, Dalian 116025, China
Abstract:As economy enters a period of high-quality development, the relationship between economic development and carbon emission has been paid more and more attention. The paper empirically explores the relationship between carbon emissions and economic development in China by nonparametric Generalized Additive Mixed Models based on the panel data of provinces from 1997 to 2016.In the paper, as independent variables the unobserved time-related effects and the residual auto-correlation structure are taken into the model and the possibly heterogeneous of the income and time-related effects across provinces are considered. The empirical results show that the income effects in the eastern and central regions is heterogeneous and time-related effects in the western region is heterogeneous. There is no inverted U-shaped relationship between carbon emissions and economic development. We should take into account the economic development stages,regional differences and the heterogeneity of drivers of carbon emissions in the energy-saving and emission-reduction in the future.
Keywords:carbon emission  generalized additive mixed models  time-related factors  heterogeneity  
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