Habib Yasir, Xia Enjun, Fareed Zeeshan, Hashmi Shujahat Haider
School of Management and Economics, Beijing Institute of Technology, Beijing, 100081 China.
School of Business, Huzhou University, Huzhou, Zhejiang China.
Environ Dev Sustain. 2021;23(6):9397-9417. doi: 10.1007/s10668-020-01031-2. Epub 2020 Oct 11.
This paper endeavors to analyze and provide fresh global insights from the asymmetric nexus between the recent outbreak of COVID-19, crude oil prices, and atmospheric CO emissions. The analysis employs a unique Morlet's wavelet method. More precisely, this paper implements comprehensive wavelet coherence analysis tools, including continuous wavelet coherence, partial wavelet coherence, and multiple wavelet coherence to the daily dataset spanning from December 31, 2019 to May 31, 2020. From the frequency perspective, this paper finds significant wavelet coherence and vigorous lead and lag connections. This analysis ascertains significant movement in variables over frequency and time domain. These results demonstrate strong but varying connotations between studied variables. The results also indicate that COVID-19 impacts crude oil prices and the most contributor to the reduction in CO emissions during the pandemic period. This study offers practical and policy implications and endorsements for individuals, environmental experts, and investors.
本文旨在分析近期新冠疫情爆发、原油价格与大气二氧化碳排放之间的不对称关系，并提供全新的全球视角见解。该分析采用了独特的莫雷特小波方法。更确切地说，本文对2019年12月31日至2020年5月31日的每日数据集运用了全面的小波相干分析工具，包括连续小波相干、偏小波相干和多重小波相干。从频率角度来看，本文发现了显著的小波相干以及活跃的领先和滞后联系。该分析确定了变量在频率和时域上的显著变动。这些结果表明所研究变量之间存在强烈但各异的内涵。结果还表明，新冠疫情影响原油价格，且在疫情期间是二氧化碳排放减少的最大贡献因素。本研究为个人、环境专家和投资者提供了实际和政策方面的启示与支持。
