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The study investigates the time-varying correlation between El Ni~no phenomenon and agricultural commodity markets by employing the bootstrap full- and sub-sample rolling-window Granger causality tests. We find that the El Ni~no index (ENI) which measures the intensity of El Ni~no phenomenon, has both positive and negative impacts on agricultural commodity prices (ACP). The positive impact indicates that El Ni~no phenomenon may reduce the output of agriculture commodities, resulting in supply shortages and price increases. However, the negative impact suggests that affected by external uncertainties, ENI does not always cause ACP to change in the same direction. Conversely, we find ACP has negative impact on ENI, showing that agricultural commodity markets can reflect the extreme climate conditions globally in advance. The analyses can assist investors to adjust investment decisions and optimize asset allocation. Additionally, countries can improve the abnormal climate monitoring system to mitigate losses, and consider the impact of external uncertainties on agricultural commodity markets and ensure food security.

The novel COVID-19 virus, and the pandemic that has followed its spread, has had a massive impact on the banking industry on a global level. Therefore, considering this context, this study examines the effect of the COVID-19 pandemic on the banking sector’s performance in the Asian emerging economics, over a time span ranging from 2016Q1–2021Q2. For this purpose, this study makes use of the FE, RE, 2SLS, and PPML regression models. The empirical findings show that the GDP and banking size are positively related to bank performance in the pre-COVID era, and the COVID pandemics era thus far in the Asian emerging economies. In addition to this, the findings also reveal that the impact of GDP and bank size on banking performance is lower in the pandemic period, as compared to the pre-COVID period. Furthermore, the results show that the COVID pandemic has significantly affected the banking sector performance in the Asian emerging economies. Findings have also suggested that the central bank should shift their focus on the banking industry in the Asian emerging economies. Various other policy implications have also been suggested under the present study.

The objective of this study is to empirically assess the effect of government decisions on market growth in response to social distancing initiatives, government reactions, economic support provision, and containment and health responses, to name a few. A panel dataset of daily stock market returns is analysed in this study, changes in COVID-19 cases, and government responses to 17 countries in the Pacific and South Asia from 1st January 2020 to 31st December 2020. Findings indicate that social distancing policies have a significant negative effect on stock returns but a substantial positive impact on market growth when new cases’ growth rate declines after accounting for country characteristics and systematic risk due to foreign factors. A direct negative effect is seen almost immediately, and a subsequently indirect positive effect is noted. As expected, policies regarding social distancing have an immediate negative impact, attributed mainly to the expected negative effect on economic activity. Subsequently, we see an indirect positive effect on market return because social distancing measures reduced the growth of confirmed COVID-19 cases. Both awareness, containment, and health index (ACHI) and Income Support and Debt Relief Index (ISDRI) positively affect market growth, as they are perceived to support individuals’ socio-economic well-being and mainly result in positive market returns.

The tourism industry carries great significance in the economic development of any country. It has been observed that the COVID-19 crisis has affected global travel and tourism more than any other sector globally as well as in China. The travel restrictions, home isolation, and quarantine orders have given massive damage to China’s once thriving tourism industry. Despite this phenomenal impact, the existing literature has a dearth of empirical studies related to the impact of the COVID-19 pandemic on the tourism industry. This study attempts to reflect a thorough picture of the current scenario and the crisis effects under different intensities reflected through quantiles of Covid-19 related deaths. The study has utilized the QARDL model and the Wald test on the daily time series data of COVID-19 intensity, the real effective exchange rate, oil prices, and the tourism development index from January 1, 2020, to March 15, 2021. The outcomes indicate that COVID-19 related deaths have a negative, but significant impact on China’s tourism in the long run and short run. The oil prices also show a negative influence on tourism in the long run, but there is no significant impact of the oil prices on tourism in the short run. At the same time, the increase in the real effective exchange rates tends to support tourism in the long run, but does not influence tourism development in the short run.