Dynamic effects of natural resource abundance, green financing, and government environmental concerns toward the sustainable environment in China

中国 政府(语言学) 自然资源经济学 业务 自然资源 丰度(生态学) 可持续发展 资源(消歧) 环境资源管理 经济 生态学 地理 计算机网络 哲学 语言学 考古 计算机科学 生物
作者
Qilong Wan,Xiaodong Miao,Sahar Afshan
出处
期刊:Resources Policy [Elsevier]
卷期号:79: 102954-102954 被引量:24
标识
DOI:10.1016/j.resourpol.2022.102954
摘要

The factors affecting sustainable environmental performance have recently been a heated debate among policy experts. Therefore, this study investigates the role of natural resources, green financing, and environmental regulations in reducing carbon emissions in China from 2000 to 2019. The study employs an advanced econometric estimation entitled Bootstrap ARDL proposed by McNown et al. (2018). The stated method covers advanced cointegration features in the dynamic process. The long-run estimations of Bootstrap ARDL demonstrate that natural resource management, green investment, and environmental taxes abate environmental emissions. However, economic growth was a critical contribution to China's carbon emissions, suggesting greater potential for effective measures. Similarly, the short-run estimations confirm that natural resources, green investment, and environmental taxes are conducive to enhancing environmental sustainability. However, their marginal contribution is more substantial in the long run. Lastly, the Error Correction Term is significantly negative and implies a convergence toward steady-state equilibrium in the long run with a 23% quarterly convergence rate. Based on the findings, this study suggests that China could efficiently improve its environmental quality through effective natural resources management, green investment, and the implementation of carbon taxes. • Bootstrap ARDL applied on China's Quarterly data. • Natural Resource Management is imperative for Sustainability. • Green Financing and Environmental Regulations encourage environmental Sustainability. • Economic growth is a core contributor to ecological emissions.
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