环境治理
溢出效应
污染
环境质量
环境污染
面板数据
环境经济学
业务
自然资源经济学
公司治理
经济
环境科学
环境保护
政治学
计量经济学
生物
微观经济学
法学
生态学
财务
作者
Xiaoman Zhao,Shanbing Lu,Shengchao Yuan
标识
DOI:10.1016/j.jclepro.2023.137670
摘要
Digitalization has become the core engine of a scientific and technological revolution and a new phase of industrial transformation, while the integrated digitalization development and environmental governance has become a strategic choice for high-quality development in the modern era. Focusing on the relationship between the digitalization of government environmental governance (DGEG) and environmental pollution, this study empirically tested the impact of DGEG on environmental pollution and its spatial spillover effect using the spatial Durbin model based on provincial panel data for China from 2015 to 2019. The threshold effect of this impact was examined using the threshold regression model from the perspective of digital infrastructure as well as digitalization developments in economic and social spheres. We found that DGEG can not only reduce environmental pollution in the local area but also improve the environmental quality of surrounding areas through the spatial spillover effect, showing an obvious “digital pollution reduction dividend”. However, this spillover effect has a spatial spillover boundary, only playing a role in pollution reduction within a certain geographical range. The impact of DGEG on environmental pollution has a single threshold effect based on digital infrastructure. As the digital infrastructure has improved over time, the “digital pollution reduction dividend” of DGEG has continued to strengthen, showing a characteristic of “increasing marginal revenue”. Under the constraints of digitalization development in the economic and social spheres, the impact of DGEG on environmental pollution has developed the characteristics of a single threshold, i.e., the pollution reduction effect of DGEG is not significant or even positive in the initial stage, but its impact gradually becomes prominent once it exceeds a certain threshold value.
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