School of Management and Economics, Beijing Institute of Technology, Beijing, 100081, China.
Center of Energy and Environmental Policy, Beijing Institute of Technology, Beijing, 100081, China.
Environ Sci Pollut Res Int. 2018 Sep;25(26):26030-26045. doi: 10.1007/s11356-018-2654-2. Epub 2018 Jul 2.
This study aims to investigate the nexus between financial instability and CO emissions within the multivariate framework in Saudi Arabia's economy over 1971-2016. Autoregressive Distributed Lag (ARDL) model is used to estimate long-run dynamics followed by Vector Error Correction Model (VECM) to detect the direction of causality. The result of the study reveals that financial instability has an insignificant impact on CO emissions. However, electricity consumption has an adverse impact on environmental quality by producing a huge amount of CO emissions in the atmosphere. The coefficients of oil and non-oil GDPs also suggest that both oil and non-oil GDPs contribute to producing a massive amount of CO emissions. Bi-directional causality is observed among all the core variables of the study. Moreover, the reliability and validity are confirmed by applying several diagnostic tests. This study provides novel findings which not only help to advance the existing literature but can be a particular interest to the country's policymakers regarding financial sector and its role in environmental degradation.
本研究旨在 1971-2016 年期间,在沙特阿拉伯经济的多元框架内,研究金融不稳定性与二氧化碳排放之间的关系。采用自回归分布滞后 (ARDL) 模型来估计长期动态,然后采用向量误差修正模型 (VECM) 来检测因果关系的方向。研究结果表明,金融不稳定性对二氧化碳排放的影响不大。然而,电力消耗通过在大气中产生大量的二氧化碳排放,对环境质量产生不利影响。石油和非石油 GDP 的系数也表明,石油和非石油 GDP 都有助于产生大量的二氧化碳排放。研究的所有核心变量之间都存在双向因果关系。此外,通过应用几种诊断测试,证实了可靠性和有效性。本研究提供了新的发现,不仅有助于推进现有文献,而且可能对该国的金融部门及其在环境退化中的作用的政策制定者特别感兴趣。