“一带一路”经济体的技术创新、自然资源、普惠金融和环境恶化问题

IF 1.8 4区 环境科学与生态学 Q3 ENVIRONMENTAL SCIENCES
Kishwar Ali, Jianguo Du, Derviş Kırıkkaleli, Z. Bács, J. Oláh
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引用次数: 4

摘要

本研究旨在考察2001年至2018年“一带一路”沿线地区普惠金融(FNI)、技术创新(TIN)和自然资源(NRS)之间的关系及其对环境退化的影响。本研究利用广义矩-面板向量自回归方法等先进计量经济学方法,以及普通最小二乘和动态普通最小二乘等传统方法,以碳足迹(CFP)和生态足迹(EFP)为测量指标,考察了这些因素与环境退化之间的关系。长期估计证实,NRS和FNI似乎导致了更高的区域cfp和EFP压力。同时,与TIN、经济治理制度(政府有效性和规律性质量)和人力资本的关系有助于克服环境退化和提高环境可持续性。本研究结果对“一带一路”地区的政策制定者和中央政府应对环境退化和促进可持续发展具有重要意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Technological innovation, natural resources, financial inclusion, and environmental degradation in BRI economies
This research aimed to examine the relationship between financial inclusion (FNI), technological innovation (TIN), and natural resources (NRS) and their impact on environmental degradation in the 45‐belt and road initiative (BRI) region from 2001 to 2018. The study utilized advanced econometric techniques, including the generalized method of moments–panel vector autoregressive, as well as traditional methods such as ordinary least squares and dynamic ordinary least squares, to examine the relationship between these factors and environmental degradation, measured by carbon footprint (CFP) and ecological footprint (EFP). The long‐run estimate confirms that NRS and FNI appear to have led to higher regional CFPs and EFP pressure. Meanwhile, the relationship with TIN, economic governance institutions (government effectiveness and regularity quality), and human capital contribute to overcoming environmental degradation and increasing environmental sustainability. The findings of this study have important implications for policymakers and central authorities in the BRI region to address environmental degradation and promote sustainable development.
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来源期刊
Natural Resource Modeling
Natural Resource Modeling 环境科学-环境科学
CiteScore
3.50
自引率
6.20%
发文量
28
审稿时长
>36 weeks
期刊介绍: Natural Resource Modeling is an international journal devoted to mathematical modeling of natural resource systems. It reflects the conceptual and methodological core that is common to model building throughout disciplines including such fields as forestry, fisheries, economics and ecology. This core draws upon the analytical and methodological apparatus of mathematics, statistics, and scientific computing.
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