Suppr超能文献

金砖国家的政治风险是否会导致环境恶化?矩量分位数回归方法的证据。

Does political risk drive environmental degradation in BRICS countries? Evidence from method of moments quantile regression.

机构信息

Department of Business Administration, Faculty of Economics and Administrative Science, Cyprus International University, 99040, Nicosia, Turkey.

Research Department, Central Bank of Nigeria, Abuja, Nigeria.

出版信息

Environ Sci Pollut Res Int. 2022 May;29(21):32287-32297. doi: 10.1007/s11356-022-20002-w. Epub 2022 Apr 7.

Abstract

As a contribution to the political risk-environmental degradation literature, this study examines whether political risk drives environmental degradation in a multivariate framework. To achieve our study objective, we employed the method of moments quantile regression (MMQR) approach to analyze the effect of renewable energy use, economic growth, political risk, and globalization on quantiles of carbon emissions. The study utilized dataset stretching between 1990 and 2018 to investigate this interrelationship in the BRICS nations. The results generated from the MMQR mimic those of the three heterogeneous linear panel estimation techniques conducted (for robustness check), in terms of coefficient sign, magnitude, and significance. Using the MMQR technique, empirical results show that across quantiles (0.1-0.90), political risk, economic growth, and globalization positively affects environmental degradation. Renewable energy consumption, on the other hand, curb environmental degradation across all quantiles (0.10-0.90). Furthermore, the outcomes of the FMOLS, DOLS, and FEOLS corroborated the MMQR outcomes. In addition, the outcomes of the Dumitrescu-Hurlin panel causality revealed that renewable energy use, political risk, economic growth, and globalization can significantly predict CO emissions in the BRICS nations. The findings offer intuition for policymakers to lessen CO emissions in BRICS nations via diversification and clean energy technologies such as carbon capture and storage.

摘要

本研究在多变量框架下检验了政治风险是否会导致环境恶化,为政治风险-环境退化文献做出了贡献。为了实现我们的研究目标,我们采用矩分位数回归(MMQR)方法来分析可再生能源使用、经济增长、政治风险和全球化对碳排放分位数的影响。该研究利用 1990 年至 2018 年的数据来调查金砖国家之间的这种相互关系。MMQR 生成的结果与我们进行的三种异质线性面板估计技术(用于稳健性检查)的结果相似,包括系数符号、大小和显著性。使用 MMQR 技术,实证结果表明,在所有分位数(0.1-0.90)上,政治风险、经济增长和全球化都会对环境恶化产生积极影响。另一方面,可再生能源的使用在所有分位数(0.10-0.90)上都能遏制环境恶化。此外,FMOLS、DOLS 和 FEOLS 的结果也证实了 MMQR 的结果。此外,Dumitrescu-Hurlin 面板因果关系的结果表明,可再生能源使用、政治风险、经济增长和全球化可以显著预测金砖国家的 CO 排放。这些发现为决策者提供了直觉,通过多样化和清洁能源技术(如碳捕获和储存)来减少金砖国家的 CO 排放。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d06b/8986448/c5bc22649ee7/11356_2022_20002_Fig1_HTML.jpg

相似文献

1
Does political risk drive environmental degradation in BRICS countries? Evidence from method of moments quantile regression.
Environ Sci Pollut Res Int. 2022 May;29(21):32287-32297. doi: 10.1007/s11356-022-20002-w. Epub 2022 Apr 7.
2
The role of natural resources, renewable energy, and globalization in testing EKC Theory in BRICS countries: Method of Moments Quantile.
Environ Sci Pollut Res Int. 2022 Apr;29(16):23677-23689. doi: 10.1007/s11356-021-17557-5. Epub 2021 Nov 23.
4
The role of renewable energy consumption on environmental degradation in EU countries: do institutional quality, technological innovation, and GDP matter?
Environ Sci Pollut Res Int. 2023 Mar;30(15):44607-44624. doi: 10.1007/s11356-023-25428-4. Epub 2023 Jan 25.
6
BRICS carbon neutrality target: Measuring the impact of electricity production from renewable energy sources and globalization.
J Environ Manage. 2021 Nov 15;298:113460. doi: 10.1016/j.jenvman.2021.113460. Epub 2021 Aug 11.
7
Financial development, globalization, and CO emission in the presence of EKC: evidence from BRICS countries.
Environ Sci Pollut Res Int. 2018 Nov;25(31):31283-31296. doi: 10.1007/s11356-018-3034-7. Epub 2018 Sep 7.
9
Exploring the dynamic relationship between financial development, renewable energy, and carbon emissions: A new evidence from belt and road countries.
Environ Sci Pollut Res Int. 2022 Feb;29(10):14930-14947. doi: 10.1007/s11356-021-16641-0. Epub 2021 Oct 8.
10
Navigating carbon emissions in G-7 economies: a quantile regression analysis of environmental-economic interplay.
Environ Sci Pollut Res Int. 2023 Oct;30(47):104697-104712. doi: 10.1007/s11356-023-29722-z. Epub 2023 Sep 14.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验