Search

With the growing emphasis on sustainable development, green policies have become a crucial factor influencing both environmental pollution and the career progression of officials in China and other countries. However, the mechanisms behind this relationship remain unclear. This paper aims to enhance the understanding of how environmental pollution impacts official promotion by analyzing the performance of provincial leaders in China and their incentives to address pollution. Using provincial panel data from 1998 to 2020 and a probit model, our study uncovers significant findings. We demonstrate that the intensified green attention by China's central government has notably reduced the promotion prospects for provincial officials with poor environmental protection records, particularly since 2013. Furthermore, our research extends the analysis of micro-level mechanisms, illustrating how the central government's political incentives effectively influence local environmental governance. This study underscores the central government's capability to leverage its personnel system to achieve desired outcomes in sustainable development. • Analysis unveils incentives for provincial governors to tackle pollution issues. • Green attention from top leadership lowers promotion chances for officials with poor environmental records. • Impact is stronger during periods of heightened national environmental awareness. • Central government's green attention influences local leaders' priorities towards quality or quantity. [ABSTRACT FROM AUTHOR]

The mechanism between financial agglomeration and environmental pollution is an important concern for both academia and policymaking. The main objective of this paper is to study the nonlinear impacts of financial agglomeration on environmental pollution. A theoretical framework was first constructed based on the scale effect, structure effect, and technology innovation effect of financial agglomeration and a Copeland-Taylor endogenous growth model. Using the panel data of 281 Chinese prefectural-level cities from 2003 to 2019, a panel threshold regression model was introduced to estimate the nonlinear association between financial agglomeration and environmental pollution. Industrial smoke (dust) emissions and industrial wastewater discharge were adopted to quantify current environmental pollution in China. The results show that financial agglomeration had a significant effect on improving the environment characterized by gradient thresholds; also notable is that 68.64% of the cities crossed the threshold value, entering the decelerating phase of financial agglomeration inhibiting environmental pollution. Both upgrading industrial structure and enhancing marketization could reduce environmental pollution, whereas increasing human capital, environmental regulation, and energy consumption had a deteriorating effect. The three channels for financial agglomeration to reduce environmental pollution were revealed to be financial scale, financial structure, and financial technology innovation. Our findings provide strong evidence for policymaking in sustainable development. [Display omitted] • Financial agglomeration (FA) is a crucial way to improve environment pollution (EP). • We built the theoretical framework of FA and EP based on the Copeland-Taylor model. • We tested the nonlinear impacts of FA on EP using the panel threshold model. • We revealed the transmission mechanism between FA and EP. [ABSTRACT FROM AUTHOR]

There is significant interest among policymakers and academics about whether or not green credit, which is a market-oriented environmental policy tool, has achieved its intended effect in improving the environment in China. This paper addresses this question from both theoretical and empirical perspectives. Using panel data from 30 provincial administrative regions of China from 2007 to 2016, we apply the fixed effect model and the gray correlation analysis method to examine the influence and its mechanism of green credit on China's environmental quality. The results show that green credit does improve China's environmental quality overall. Green credit can reduce environmental pollution through three mechanisms: improving enterprise performance, motivating enterprise innovation, and upgrading industrial structure. However, there are regional differences in the emission-reduction effect of green credit. Green credit improves the environmental quality in resource-based regions more than non-resource-based regions; the emission-reduction effect is significant in regions with developed financial markets, but not significant elsewhere. The results indicate that green credit policies should be regionally differentiated to more effectively achieve emission-reduction targets. • We examine the influence mechanism of green credit on China's environmental quality. • We use panel data from China's 30 provincial regions during 2007–2016. • We apply the fixed effect model and the gray correlation analysis method. • Green credit can reduce environmental pollution through three mechanisms. • There are some regional differences in the emission-reduction effect of green credit. [ABSTRACT FROM AUTHOR]