Journal
ENERGY POLICY
Volume 158, Issue -, Pages -Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.enpol.2021.112557
Keywords
Resource allocation; Carbon emissions; Spatial durbin model; Spatial autocorrelation
Funding
- key projects of natural science research of universities in Anhui province [KJ2018A0109]
- Anhui polytechnic university [2018YQQ022]
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The study shows that there are differences in industrial resource allocation efficiency among provinces, and factors affecting carbon emissions are not the same. Improving industrial resource allocation can reduce carbon emissions nationwide, but the effects vary by region.
Analyzing the relationship between industrial resource allocation and carbon emissions from the regional level will promote cross-regional environmental coordinated governance. Based on the panel data of 30 provinces from 2007 to 2016, this paper explores the spatial distribution of industrial resource allocation, spatial auto correlation of carbon emissions, and the relationship from a spatial econometric perspective. The results show that compared with other provinces, Jilin, Zhejiang, and Guangdong have relatively higher industrial resource allocation efficiency. The provinces with higher carbon emissions are spatially adjacent, and the provinces with lower carbon emissions are also spatially adjacent. On a national level, the improvement of industrial resource allocation can reduce carbon emissions. On a regional level, the impact of industrial resource allocation efficiency on carbon emissions is somewhat different. Industrial resource allocation can significantly reduce carbon emissions in the eastern region. However, it is not clear whether the improvement in the industrial resource allocation efficiency can reduce carbon emissions in the central, western, and northeast regions.
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