Abstract
The collaborative agglomeration of manufacturing and producer services is an essential tool for the green transformation of China’s economic model. This paper explores the impact of industrial collaborative agglomeration on carbon intensity, using the spatial Durbin model (SDM) based on China’s provincial panel data from 2012 to 2019. The empirical results indicate that there is an inverted N-shaped relationship between industrial collaborative agglomeration and carbon intensity, with the turning points of 2.5255 and 2.8575. Regional industrial collaborative agglomeration tends to initially reduce carbon intensity, then aggravates to carbon emission, then finally inhibits carbon intensity. There is an obvious heterogeneity in the impact of producer-service subsectors and manufacturing collaborative agglomeration on carbon intensity. When the industrial collaborative agglomeration level exceeds a certain threshold, the clustering of information transmission, software and information technology service, and financial intermediation service have the greatest emission reduction potential. Industrial collaborative agglomeration has obvious spatial spillover effect, and carbon intensity has obvious spatial convergence effect. This paper provides some novelties for research perspectives on carbon intensity reduction and theoretical references for the development and implementation of differentiated industrial collaborative agglomeration policies.
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Data availability
The datasets used and analyzed during the current study are available from the corresponding author on reasonable request.
Notes
China Statistical Yearbook: https://data.cnki.net/yearbook/Single/N2021110004
China Energy Statistical Yearbook: https://data.cnki.net/yearbook/Single/N2021050066
China Urban Yearbook: https://data.cnki.net/yearbook/Single/N2021050059
China Environmental Statistical Yearbook: https://data.cnki.net/yearbook/Single/N2021070128
According to Sinha et al. (2019), if a cubic EKC follows this equation (P = a0 + a1 * Y + a2 * Y2 + a3 * Y3), (1) a1, a3 < 0, a2 > 0 and (2) a22 − 3a1*a3 > 0 are the necessary and sufficient condition for the validity of the inverted N-shaped EKC. In this article, the estimation results of model 4 in Table 5 show that the cubic equation is: CI = a0 − 1.0401 * ICA + 2.1646 * ICA2 − 1.2554 * ICA3. Where a1 = −1.0401, a2 = 2.1646, a3 = −1.2554, a22 − 3a1*a3 = 3.3796 > 0, which indicates that both of the above conditions hold and the inverted N-shaped curve proposed in this paper is valid.
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This study was financially supported by the Fundamental Research Funds for the Central Universities (grant no. 2020ZDPYMS44).
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Meng, XN., Xu, SC. Can industrial collaborative agglomeration reduce carbon intensity? Empirical evidence based on Chinese provincial panel data. Environ Sci Pollut Res 29, 61012–61026 (2022). https://doi.org/10.1007/s11356-022-20191-4
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DOI: https://doi.org/10.1007/s11356-022-20191-4