TY - JOUR
T1 - Effect of government environmental attention on green transformation
T2 - Empirical analysis from a spatiotemporal perspective in China
AU - Man, Haojie
AU - Sun, Yueyue
AU - Wang, Xinyu
AU - Qin, Zhuangyan
AU - Chen, Shuangwen
AU - Chen, Jianbin
N1 - Publisher Copyright:
© 2024 Elsevier Ltd
PY - 2024/10/1
Y1 - 2024/10/1
N2 - As the primary policymaker and implementer, the government plays an essential role in driving regional green transformation development (GTD). The study of the impact mechanisms of government environmental attention (GEA) on GTD can offer a scientific basis and reference for policy-making and regional governance. However, the varying focus of local governments on environmental issues and the externalities of environmental governance underscore the complexities in the influence of GEA on GTD. This paper proposes a method that integrates multi-source data to explore the impact of GEA on GTD from a spatiotemporal perspective. A text mining framework is first proposed to provide a more accurate measurement of the GEA, and the geographically and temporally weighted regression model is used to analyze the spatiotemporal characteristic and mechanism of GEA's impact. Additionally, the spatial correlation effect is explored based on the gravity model. The results indicate that the level of GTD in China demonstrates an increasing trend with an average annual growth rate (AAGR) of 3.22%, while the variance between provinces is also increasing. GEA has a significant positive effect on GTD (R2 = 0.866), with an average growth rate of 18.1% following the implementation of major environmental policies. The spatial distribution pattern of GEA's impact shows the characteristics of “central > eastern > western > northeastern”. GEA promotes GTD by increasing environmental governance expenditure and enhancing public environmental services, while the transmission pathway of promoting green innovation has not yet worked. The spatial correlation and spillover effects of GEA have shown an overall increasing trend, with the AAGR of 8.92% in the gravity value. Inter-provincial cooperation can promote GTD, and certain collaborative clusters among provinces have been formed. This paper provides novel insights into the theoretical connection between GEA and GTD. The research findings can serve as a reference for the government to propose targeted policies for promoting regional green transformation.
AB - As the primary policymaker and implementer, the government plays an essential role in driving regional green transformation development (GTD). The study of the impact mechanisms of government environmental attention (GEA) on GTD can offer a scientific basis and reference for policy-making and regional governance. However, the varying focus of local governments on environmental issues and the externalities of environmental governance underscore the complexities in the influence of GEA on GTD. This paper proposes a method that integrates multi-source data to explore the impact of GEA on GTD from a spatiotemporal perspective. A text mining framework is first proposed to provide a more accurate measurement of the GEA, and the geographically and temporally weighted regression model is used to analyze the spatiotemporal characteristic and mechanism of GEA's impact. Additionally, the spatial correlation effect is explored based on the gravity model. The results indicate that the level of GTD in China demonstrates an increasing trend with an average annual growth rate (AAGR) of 3.22%, while the variance between provinces is also increasing. GEA has a significant positive effect on GTD (R2 = 0.866), with an average growth rate of 18.1% following the implementation of major environmental policies. The spatial distribution pattern of GEA's impact shows the characteristics of “central > eastern > western > northeastern”. GEA promotes GTD by increasing environmental governance expenditure and enhancing public environmental services, while the transmission pathway of promoting green innovation has not yet worked. The spatial correlation and spillover effects of GEA have shown an overall increasing trend, with the AAGR of 8.92% in the gravity value. Inter-provincial cooperation can promote GTD, and certain collaborative clusters among provinces have been formed. This paper provides novel insights into the theoretical connection between GEA and GTD. The research findings can serve as a reference for the government to propose targeted policies for promoting regional green transformation.
KW - Geographically and temporally weighted regression
KW - Government environmental attention
KW - Green transformation
KW - Spatiotemporal heterogeneity
KW - Text mining algorithm
UR - http://www.scopus.com/inward/record.url?scp=85203284063&partnerID=8YFLogxK
U2 - 10.1016/j.jclepro.2024.143595
DO - 10.1016/j.jclepro.2024.143595
M3 - Article
AN - SCOPUS:85203284063
SN - 0959-6526
VL - 473
JO - Journal of Cleaner Production
JF - Journal of Cleaner Production
M1 - 143595
ER -