Carbon Emissions in China: A Spatial Econometric Analysis at the Regional Level

Sustainability

Yu Liu¹  Hongwei Xiao²  Precious Zikhali³ 

[1] Institute of Policy and Management, Chinese Academy of Sciences, Beijing 100190, China; E-Mail:;Economic Forecasting Department, State Information Center, Beijing 100045, China;Postnet Suite 122, Private Bag X1, Die Wilgers 0041, Pretoria, South Africa; E-Mail:

关键词: carbon emissions;    spatial Durbin panel data model;    spatial externality;    Stochastic Impacts by Regression on Population;    Affluence and Technology (STIRPAT);   

DOI  :  10.3390/su6096005

来源: mdpi

【 摘 要 】

An extended Stochastic Impacts by Regression on Population, Affluence and Technology (STIRPAT) model, incorporating factors that drive carbon emissions, is built from the regional perspective. A spatial Durbin model is applied to investigate the factors, including population, urbanization level, economic development, energy intensity, industrial structure, energy consumption structure, energy price, and openness, that impact both the scale and intensity of carbon emissions. After performing the model, we find that the revealed negative and significant impact of spatial-lagged variables suggests that the carbon emissions among regions are highly correlated. Therefore, the empirical results suggest that the provinces are doing an exemplary job of lowering carbon emissions. The driving factors, with the exception of energy prices, significantly impact carbon emissions both directly and indirectly. We, thus, argue that spatial correlation, endogeneity and externality should be taken into account in formulating polices that seek to reduce carbon emissions in China. Carbon emissions will not be met by controlling economic development, but by energy consumption and low-carbon path.

【 授权许可】

CC BY   
© 2014 by the authors; licensee MDPI, Basel, Switzerland.