Exploring the role of natural resources, natural gas and oil production for economic growth of China

Economic growth and natural resources commodity prices are the variables greatly influenced by events such as the Gulf war, the Asian financial crisis, the global financial crisis, and the recent COVID-19 pandemic. The on-hand research fills the research gap by investigating the role of natural resources, natural gas and oil production for pre and post COVID-19 periods. The authors employ the Wavelet power spectrum and Wavelet coherence approaches to trace the volatility for natural resources commodity prices and establish a correlation between each variable and economic growth. The empirical findings suggest high fluctuations in the natural resources such as total natural resources, natural gas resources and oil rent for the stated period. This study found a bidirectional causal association between economic performance, total natural resources, natural gas resources and oil rent. The current research guides relevant policy implications to capture the volatile nature of resources commodity prices and to prescribe relevant policy implications in this regard.

Environmental quality, climate indicators, and COVID-19 pandemic: insights from top 10 most affected states of the USA.

In the current context of the COVID-19 pandemic, researchers are working with health professionals to inform governments on how to formulate health strategies. In this study, we examine the correlation between environmental and climate indicators and COVID-19 outbreak in the top 10 most affected states of the USA. In doing so, PM2.5, temperature, humidity, environmental quality index, and rainfall are included as crucial meteorological and environmental factors. Kendall and Spearman rank correlation coefficients, quantile regression, and log-linear negative binominal analysis are employed as an estimation strategy. The empirical estimates conclude that temperature, humidity, environmental quality index, PM2.5, and rainfall are significant factors related to the COVID-19 pandemic in the top 10 most affected states of the USA. The empirical findings of the current study would serve as key policy input to mitigate the rapid spread of COVID-19 across the USA.

Nexus Between the COVID-19 Dynamics and Environmental Pollution Indicators in South America.

INTRODUCTION: In the current context of the COVID-19 pandemic, researchers are working with health professionals to inform governments to slow the virus's spread. The extant research contribution has been dedicated to examining the impact of climate indicators such as temperature, humidity, and rainfall. However, there is a lack of evidence regarding their combined association between environmental quality and climate indicators to combat COVID-19 in the South American context. METHODS: In this study, we collected data for environmental pollution indicators for the South America region, and correlation analysis and wavelet transform coherence were used as the analytical tools. RESULTS: Empirical estimates conclude that PM10, NO2, CO, and O3 are significant factors in the fight against the COVID-19 pandemic in South America. IMPLICATIONS: Our findings will serve as policy implications for the state, health officials, and regulators to combat the COVID-19 pandemic outbreak in South America.

Environmental pollution and COVID-19 outbreak: insights from Germany.

The impact of environmental pollutants and climate indicators on the outbreak of COVID-19 has gained considerable attention in the recent literature. However, specific investigation of industrial economies like Germany is not available. This provides us motivation to examine the association between environmental pollutants, climate indicators and the COVID-19 cases, recoveries, and deaths in Germany using daily data from February 24, 2020, to July 02, 2020. The correlation analysis and wavelet transform coherence (WTC) approach are the analytical tools, which are used to explore the association between variables included in the study. Our findings indicate that PM2.5, O3, and NO2 have a significant relationship with the outbreak of COVID-19. In addition, temperature is the only significant climate indicator which has significant correlation with the spread of COVID-19. Finally, PM10, humidity, and environmental quality index have a significant relationship only with the active cases from COVID-19 pandemic. Our findings conclude that Germany's successful response to COVID-19 is attributed to environmental legislation and the medical care system, which oversaw significant overhaul after the SARS and MERS outbreaks. The current study implicates that other industrial economies, especially European economies, that are still facing COVID-19 outbreak can follow the German model for pandemic response.

Correlation between environmental pollution indicators and COVID-19 pandemic: A brief study in Californian context.

In December 2019, the novel coronavirus COVID-19 outbreak was first detected in Wuhan Hubei province, China. The April 24, 2020, the Centers for Disease Control and Preventions (CDC) has confirmed more than 39,000 cases, including >1800 deaths. California's Governor Gavin Newsom ordered mandatory stay at home after World Health Organization (WHO) declared COVID-19 as a global pandemic in early March. We have evaluated the correlation between environmental pollution determinants and the COVID-19 outbreak in California by using the secondary published data from the Centers for Disease Control and the Environmental Pollution Agency (EPA). We employed Spearman and Kendall correlation tests to analyze the association of PM 2.5, PM 10, SO2, NO2, Pb, VOC, and CO with COVID-19 cases in California. Our findings indicate that environmental pollutants such as PM10, PM2.5, SO2, NO2, and CO have a significant correlation with the COVID-19 epidemic in California. Overall, our study is a useful supplement to encourage regulatory bodies to promote changes in environmental policies as pollution source control can reduce the harmful effects of environmental pollutants.

Correlation between climate indicators and COVID-19 pandemic in New York, USA.

This study analyzed the association between COVID-19 and climate indicators in New York City, USA. We used secondary published data from New York city health services and National weather service, USA. The climate indicators included in the study are average temperature, minimum temperature, maximum temperature, rainfall, average humidity, wind speed, and air quality. Kendall and Spearman rank correlation tests were chosen for data analysis. We find that average temperature, minimum temperature, and air quality were significantly associated with the COVID-19 pandemic. The findings of this study will help World Health Organization and health regulators such as Center for Disease Control (CDC) to combat COVID-19 in New York and the rest of the world.