TY - JOUR
T1 - Spatiotemporal heterogeneity of industrial pollution in China
AU - Cheng, Jinhua
AU - Dai, Sheng
AU - Ye, Xinyue
N1 - Funding Information:
We are very grateful for the valuable comments and suggestions from Belton M. Fleisher (executive editor), Nicholas Holtkamp (editorial assistant) and two anonymous reviewers, as well as the financial support from National Social Science Foundation of China ( 11&ZD040 ; 11BKS045 ; 12CKS022 ) and Fundamental Research Funds for the Central Universities ( CUGW160401 ). We would also like to express our great gratitude to Bo Huang at CUHK for his Matlab package.
Publisher Copyright:
© 2016 Elsevier Inc.
PY - 2016/9/1
Y1 - 2016/9/1
N2 - Due to the lack of effective institutional constraints, the negative externality from industrial production will lead to environmental pollution and spatial spillover on neighboring units. Because the self-purification capacity of the environmental system is limited, a strong time effect is witnessed. Time lag and spatial spillover need to be considered to mitigate the effect of industrial pollution. Using geographically weighted regression (GWR) and geographically and temporally weighted regression (GTWR), this paper decomposes the spatiotemporal heterogeneity of industrial pollution in China. Results show a significant spatio-temporality in the evolution of the provincial-level industrial pollution since 2007. As the major participants, state-owned enterprises play a leading role in the state economy and greatly affect pollutant emissions. In the central and eastern regions, an increasing proportion of state-owned output values is related to the decrease of industrial pollution emissions, whereas western regions witness an opposite trend. Emissions charge plays a positive role in curbing the emission from industrial enterprises in the central and western regions. A better understanding of the spatiotemporal heterogeneity of industrial pollution is the prerequisite in the alleviation of industrial pollutions to achieve a sustainable economic growth.
AB - Due to the lack of effective institutional constraints, the negative externality from industrial production will lead to environmental pollution and spatial spillover on neighboring units. Because the self-purification capacity of the environmental system is limited, a strong time effect is witnessed. Time lag and spatial spillover need to be considered to mitigate the effect of industrial pollution. Using geographically weighted regression (GWR) and geographically and temporally weighted regression (GTWR), this paper decomposes the spatiotemporal heterogeneity of industrial pollution in China. Results show a significant spatio-temporality in the evolution of the provincial-level industrial pollution since 2007. As the major participants, state-owned enterprises play a leading role in the state economy and greatly affect pollutant emissions. In the central and eastern regions, an increasing proportion of state-owned output values is related to the decrease of industrial pollution emissions, whereas western regions witness an opposite trend. Emissions charge plays a positive role in curbing the emission from industrial enterprises in the central and western regions. A better understanding of the spatiotemporal heterogeneity of industrial pollution is the prerequisite in the alleviation of industrial pollutions to achieve a sustainable economic growth.
KW - China
KW - GWR & GTWR
KW - Industrial economic
KW - Industrial pollution
KW - Spatiotemporal heterogeneity
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U2 - 10.1016/j.chieco.2016.07.001
DO - 10.1016/j.chieco.2016.07.001
M3 - Article
AN - SCOPUS:84978372355
SN - 1043-951X
VL - 40
SP - 179
EP - 191
JO - China Economic Review
JF - China Economic Review
ER -