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大流行相关不确定性对一氧化碳排放的不对称影响:来自十大污染国家的证据。

Asymmetric impact of pandemics-related uncertainty on CO emissions: evidence from top-10 polluted countries.

作者信息

Chang Lei, Chen Kaiming, Saydaliev Hayot Berk, Faridi Muhammad Zahir

机构信息

School of Management, University of Science and Technology of China, Hefei, 230026 China.

School of Finance and Trade, Wenzhou Business College, Wenzhou, 325035 China.

出版信息

Stoch Environ Res Risk Assess. 2022;36(12):4103-4117. doi: 10.1007/s00477-022-02248-5. Epub 2022 Jul 16.

DOI:10.1007/s00477-022-02248-5
PMID:35873500
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9288206/
Abstract

The recent COVD-19 pandemic has been a major shock, affecting various macroeconomic indicators, including the environmental quality. The question of how the pandemics-related uncertainty will affect the environment is of paramount importance. The study analyzes the asymmetric impact of pandemic uncertainty on CO emissions in top-10 polluted economies (China, USA, India, Russia, Germany, Japan, Iran, South Korea, Indonesia, and Saudi Arabia). Taking panel data from 1996 to 2018, a unique technique, 'Quantile-on-Quantile (QQ)', is employed. CO emissions are used as an indicator of environmental quality. The outcomes define how the quantiles of pandemic uncertainty impact the quantiles of carbon emissions asymmetrically by providing an effective paradigm for comprehending the overall dependence framework. The outcomes reveal that pandemic uncertainty promotes environmental quality by lowering CO emissions in our sample countries at various quantiles. However, Japan shows mixed findings. The effect of PUN on CO is substantially larger in India, Germany, and South Korea and lower in Russia and Saudi Arabia. Furthermore, the magnitude of asymmetry in the pandemic uncertainty-CO emissions association differs by economy, emphasizing that government must pay particular caution and prudence when adopting pandemics-related uncertainty and environmental quality policies.

摘要

近期的新冠疫情是一次重大冲击,影响了包括环境质量在内的各项宏观经济指标。与疫情相关的不确定性将如何影响环境这一问题至关重要。该研究分析了疫情不确定性对十大污染经济体(中国、美国、印度、俄罗斯、德国、日本、伊朗、韩国、印度尼西亚和沙特阿拉伯)碳排放的非对称影响。利用1996年至2018年的面板数据,采用了一种独特的技术——“分位数对分位数(QQ)”方法。碳排放被用作环境质量的指标。研究结果通过提供一个理解整体依赖框架的有效范式,界定了疫情不确定性的分位数如何非对称地影响碳排放的分位数。结果显示,疫情不确定性通过在不同分位数水平上降低样本国家的碳排放来提升环境质量。然而,日本的情况则较为复杂。疫情不确定性对碳排放的影响在印度、德国和韩国较大,而在俄罗斯和沙特阿拉伯较小。此外,疫情不确定性与碳排放之间关联的非对称程度因经济体而异,这强调政府在制定与疫情相关的不确定性政策和环境质量政策时必须格外谨慎。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/11cb/9288206/6e570a06d6d9/477_2022_2248_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/11cb/9288206/ca1f3825a86a/477_2022_2248_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/11cb/9288206/f6601d94f07b/477_2022_2248_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/11cb/9288206/6e570a06d6d9/477_2022_2248_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/11cb/9288206/ca1f3825a86a/477_2022_2248_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/11cb/9288206/f6601d94f07b/477_2022_2248_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/11cb/9288206/6e570a06d6d9/477_2022_2248_Fig3_HTML.jpg

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