Spatiotemporal heterogeneity of industrial pollution in China

Jinhua Cheng, Sheng Dai, Xinyue Ye

Research output: Contribution to journalArticlepeer-review

30 Scopus citations

Abstract

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.

Original languageEnglish (US)
Pages (from-to)179-191
Number of pages13
JournalChina Economic Review
Volume40
DOIs
StatePublished - Sep 1 2016
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Finance
  • Economics and Econometrics

Keywords

  • China
  • GWR & GTWR
  • Industrial economic
  • Industrial pollution
  • Spatiotemporal heterogeneity

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