Covid-19 and oil and gold price volatilities: Evidence from China market.

Gold and crude oil are the influential commodities of the stock markets and real economy of the world in financial crises as well as in COVID-19 periods. However literature mainly focused on the effects of these commodities' prices only, and the volatilities in the prices of these commodities altogether with the prices got little attention. To fill in a major research gap, our study intends to estimate the dynamic relationship between oil prices, gold prices, oil prices volatilities and gold prices volatilities on the stock market of China. Using daily data over the period from 2009 to 2021, the study applied Autoregressive Distributed Lag (ARDL) bound test approach for the purpose of empirical estimation. Moreover, Non linear ARDL and asymmetric Causality analysis has also been applied for more comprehensive asymmetric estimation. The findings of our study indicated that gold prices and oil prices negatively affect stock market of China in the long run. In terms of implied volatility index of these commodities, study finds negative impact of price volatility of oil but positive impact of the price volatility of gold on the country's stock market in the long run. However, in the short run, only oil price and gold prices have significant effect on the China's stock market. On the basis of our findings, we recommend the investors to make rational decisions in response to the uncertainties in these markets and should consider gold as a safe haven to hedge themselves in times of uncertainty. Policymakers should take appropriate actions and adopt proper mechanisms for dealing with the quick uncertainty flow of information from the oil to the stock market.

Covid-19 and oil and gold price volatilities: Evidence from China market

Gold and crude oil are the influential commodities of the stock markets and real economy of the world in financial crises as well as in COVID-19 periods. However literature mainly focused on the effects of these commodities' prices only, and the volatilities in the prices of these commodities altogether with the prices got little attention. To fill in a major research gap, our study intends to estimate the dynamic relationship between oil prices, gold prices, oil prices volatilities and gold prices volatilities on the stock market of China. Using daily data over the period from 2009-2021, the study applied Autoregressive Distributed Lag (ARDL) bound test approach for the purpose of empirical estimation. Moreover, Non linear ARDL and asymmetric Causality analysis has also been applied for more comprehensive asymmetric estimation. The findings of our study indicated that gold prices and oil prices negatively affect stock market of China in the long run. In terms of implied volatility index of these commodities, study finds negative impact of price volatility of oil but positive impact of the price volatility of gold on the country's stock market in the long run. However, in the short run, only oil price and gold prices have significant effect on the China's stock market. On the basis of our findings, we recommend the investors to make rational decisions in response to the uncertainties in these markets and should consider gold as a safe haven to hedge themselves in times of uncertainty. Policymakers should take appropriate actions and adopt proper mechanisms for dealing with the quick uncertainty flow of information from the oil to the stock market.

Modeling the turnover intentions of Thai health-care personnel in pandemic times: moderating role of Covid-19 burnout.

PURPOSE: Covid-19 cases are rising at a high rate in Thailand. Thailand's administration has formulated many initiatives to combat the spread of coronavirus. However, during a pandemic, health-care workers have a diverse range of tasks that make it more challenging to continue working in hospitals. Consequently, the authors modeled the turnover intentions of health-care personnel to capture relevant psychological aspects of employees during the pandemic. Specifically, this study aims to focused on the moderating role of Covid-19 burnout (CBO) in the relationship between transformational leadership (TL) and job turnover intentions (JTI) with job satisfaction (JS) and knowledge hiding (KH) as mediators. DESIGN/METHODOLOGY/APPROACH: This research collected data using self-administered questionnaire. A two-stage partial least square-structural equation modeling (PLS-SEM) is carried out as an analysis technique to measure the linear relationship among constructs. The study tests hypotheses (direct and indirect effects) using 310 sample size of health-care personnel. FINDINGS: The findings indicated that CBO intensified the JTI of health-care personnel and strengthened the association of JS and KH with JTI during the Covid-19 pandemic. TL had a negative indirect effect on JTI. In addition, JS had a negative impact on JTI. ORIGINALITY/VALUE: The study highlights the importance of TL and JS as ways to reduce or alleviate JTI in health-care personnel during the Covid-19 pandemic in Thailand. Furthermore, CBO and KH can enhance JTI in health-care personnel.

Does COVID-19 pandemic cause natural resources commodity prices volatility? Empirical evidence from China.

COVID-19 pandemic caused havoc around the globe in both economic and non-economic sectors. This paper, unlike previous studies, evaluates the role of COVID-19 on the volatility in natural resources. The volatility of natural resources commodity prices has been the center of discussion, especially during the pandemic. Unlike previous studies, this study aims to evaluate the role of the pandemic, i.e., Covid-19 and its possible impact on volatility in natural resources commodity prices for China. China has been the center of this epidemic disease and is considered one of the major economies affected by the Covid-19; therefore, it is better to conduct this study for China. This study uses data from January 2020 till September 2021 to capture the peak time of Covid-19. Moreover, this study employs the novel wavelet power spectrum and wavelet coherence approach to better capture volatility within commodity prices volatility and Covid-19 and evaluate the association between both variables. The empirical results reveal that only natural resources commodity prices are volatile and only short. While Covid-19 positive cases and Covid-19 deaths are not vulnerable during the study period. Moreover, the wavelet coherence conforms that both Covid-19 positive cases and Covid-19 deaths significantly cause volatility in natural resources commodity prices. Although, volatility is found at different periods; still, volatility is observed only in the short-run. The study also provides relevant policy implications to ensure a relevant and timely solution for the existing issue. Moreover, future research guidelines and the study's limitations are also provided.

Asymmetric effects of fine particulate matter and stringency policy on COVID-19 intensity.

This study aims to examine the influence of environmental performance (PM2.5) on COVID-19 intensity . For this purpose, we employ the newly introduced Hidden Panel Cointegration test and Nonlinear Panel Autoregressive Distributed Lag model. Results indicate the asymmetric linkages between PM2.5 and COVID-19 intensity, as the positive shock in PM2.5 raises the COVID-19 intensity by 21%, whereas the negative shock in PM2.5 decreases COVID-19 intensity by 12% in long-run. On the contrary, the positive shock in stringency measures decreases COVID-19 intensity by 42.8%, while the negative shock in stringency policy increases COVID-19 intensity by 66.7%. These findings imply that higher pollution increases the COVID-19 severity while higher stringency measures slow down people's movement and reduce COVID-19 intensity. However, a sudden negative shock in lockdown increases people's interaction, leading to a higher spread of the virus. These results suggest that governments should adopt stringent action plans to contain the transmissibility of COVID-19.