Time-frequency co-movement between COVID-19, crude oil prices, and atmospheric CO2 emissions: Fresh global insights from partial and multiple coherence approach.

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 CO2 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 CO2 emissions during the pandemic period. This study offers practical and policy implications and endorsements for individuals, environmental experts, and investors.

Co-variance nexus between COVID-19 mortality, humidity, and air quality index in Wuhan, China: New insights from partial and multiple wavelet coherence.

The worldwide outbreak of COVID-19 disease has caused immense damage to our health and economic and social life. This research article helps to determine the impact of climate on the lethality of this disease. Air quality index and average humidity are selected from the family of climate variables, to determine its impact on the daily new cases of COVID-19-related deaths in Wuhan, China. We have used wavelet analysis (wavelet transform coherence (WTC), partial (PWC), and multiple wavelet coherence (MWC), due to its advantages over traditional time series methods, to study the co-movement nexus between our selected data series. Findings suggest a notable coherence between air quality index, humidity, and mortality in Wuhan during a recent outbreak. Humidity is negatively related to the COVID-19-related deaths, and bad air quality leads to an increase in this mortality. These findings are important for policymakers to save precious human lives by better understanding the interaction of the environment with the COVID-19 disease.

Asymmetric nexus between temperature and COVID-19 in the top ten affected provinces of China: A current application of quantile-on-quantile approach.

The present study examines the asymmetrical effect of temperature on COVID-19 (Coronavirus Disease) from 22 January 2020 to 31 March 2020 in the 10 most affected provinces in China. This study used the Sim & Zhou' quantile-on-quantile (QQ) approach to analyze how the temperature quantities affect the different quantiles of COVID-19. Daily COVID-19 and, temperature data collected from the official websites of the Chinese National Health Commission and Weather Underground Company (WUC) respectively. Empirical results have shown that the relationship between temperature and COVID-19 is mostly positive for Hubei, Hunan, and Anhui, while mostly negative for Zhejiang and Shandong provinces. The remaining five provinces Guangdong, Henan, Jiangxi, Jiangsu, and Heilongjiang are showing the mixed trends. These differences among the provinces can be explained by the differences in the number of COVID-19 cases, temperature, and the province's overall hospital facilitations. The study concludes that maintaining a safe and comfortable atmosphere for patients while COVID-19 is being treated may be rational.