The driving force of carbon emissions in china: 1995-2015 hierarchically provincial evidence

2nd International Symposium on Resource Exploration and Environmental Science

生态环境科学

Ye, Qianting^1,2 ; Liang, Huajie^1

School of Economics and Commerce, South China University of Technology, Guangzhou, China^1

School of Geographical Sciences and Urban Planning, Arizona State University, Tempe, United States^2

关键词: Autoregressive errors;    Carbon emissions;    Empirical studies;    Hierarchical structures;    Socio-economics;    Spatial correlations;    Spatial error models;    Three-dimensional panel datum;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/170/3/032044/pdf
DOI  :  10.1088/1755-1315/170/3/032044

学科分类：环境科学（综合）

来源: IOP

【 摘 要 】

This paper computes the provincial carbon emissions, use a "region-province-time" three-dimensional panel data set from 1995 to 2015, and conduct an empirical study to explore the driving force of carbon emissions in China. A hierarchically spatial autoregressive error (HSEAR) model is established, which takes into account the hierarchical structure and spatial error effect. The empirical results suggest the carbon emission and per capita GDP forming an "N" shape Environment Kuznets Curve (EKC). Meanwhile, by the growth of coal population, consumption proportion and the number of private cars will significantly increase the carbon emissions. The significantly positive spatial correlation of the error terms implies that the error impact of carbon emissions in the area has a significant positive spatial correlation with the adjacent area, which corrects the error of the general spatial error model to the socio-economic reality.