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Sustainability 2016, 8(3), 210; doi:10.3390/su8030210

Industrial Carbon Emissions of China’s Regions: A Spatial Econometric Analysis

1
Institute of Policy and Management, Chinese Academy of Sciences, Beijing 100190, China
2
Economic Forecasting Department, State Information Center, Beijing 100045, China
3
School of Economics, Jinan University, Guangzhou 510632, China
*
Authors to whom correspondence should be addressed.
Academic Editors: Bing Wang and Marc A. Rosen
Received: 22 December 2015 / Revised: 31 January 2016 / Accepted: 18 February 2016 / Published: 29 February 2016
View Full-Text   |   Download PDF [234 KB, uploaded 29 February 2016]

Abstract

This paper proposes an extended Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model to investigate the factors driving industrial carbon emissions in China. In the first stage, a spatial Durbin model is applied to investigate the determinants of regional industrial carbon emissions. In the second stage, a geographically and temporally weighted regression is applied to investigate temporal and spatial variations in the impacts of these driving factors on the scale and intensity of regional industrial carbon emissions. The empirical results suggest that the provinces with low carbon emissions act as exemplars for those with high carbon emissions and that driving factors impact carbon emission both directly and indirectly. All of the factors were investigated, except energy intensity, energy price, and openness, significantly impact carbon emissions. Overall, the results suggest that spatial correlation, heterogeneity, and spillover effects should be taken into account when formulating policies aiming at reducing industrial carbon emissions. The paper concludes with relevant policy recommendations taking full account of the regional industrial carbon emissions, heterogeneity and spillover. View Full-Text
Keywords: industrial carbon emissions; spatial Durbin panel data model; spatial spillover effects; geographically and temporally weighted regression industrial carbon emissions; spatial Durbin panel data model; spatial spillover effects; geographically and temporally weighted regression
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Liu, Y.; Xiao, H.; Zhang, N. Industrial Carbon Emissions of China’s Regions: A Spatial Econometric Analysis. Sustainability 2016, 8, 210.

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