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This study attempts to investigate the factors determining COVID-19 deaths during the pandemic across countries by employing a rich dataset sourced from 94 countries updated till 6 February, 2022. For empirical analysis, the study makes use of cross-sectional linear regression technique in the first part and after required diagnostic tests use 2SLS regression technique for correcting possible endogeneity bias in the second part. Findings from the study indicate that factors like total reported cases, population size, population over 70 years of age, extreme poverty, and human development index play significant role in determining COVID-19-related death. Further, to check the robustness of the findings the present study employed LASSO regression. Findings from the study highlight the possibility of government intervention to devise appropriate policies to control COVID-related incidence and death.

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In this paper, we investigate the effect of the monetary policy uncertainty index for the US on the dollar index. In other words, in this study, the relationship between the US MPU (USM) and the Dollar index (XD) was examined. We employ the Hatemi-J (2012) asymmetric causality test from the period January 1986 through August 2020 by using monthly data. The results of the empirical analysis prove a strong non-linear causal relationship between the variable MPU index and XD. The overall result ascertains a positive and negative bidirectional asymmetric and non-linear causality existing between the variables XD and USM index. The results of the empirical investigation endorse important policy inputs for the macroeconomic policy formulators.