ABSTRACT
This paper analyses a broad range of macro variables to assess the effects they have on the number of cases and deaths due to COVID-19. We consider 23 explanatory variables on health, political, and economic factors for 94 countries. Given the vast number of explanatory variables analysed, the paper employs advanced statistical tools for the analysis. We use regularised regression and dimension reduction methods to increase estimation efficiency. We find that alcohol drinking is associated with an increase in the number of cases and deaths due to COVID-19. In this regard, our results support the World Health Organization’s recommendation of reducing alcohol drinking during the pandemic. Furthermore, our results show that the level of trust inside the society is associated with both the number of cases and deaths. A higher level of trust in medical personnel is associated with fewer cases, while a higher level of trust in the government is associated with fewer deaths due to COVID-19. Finally, hospital beds per thousand inhabitants are a statistically significant factor in reducing the number of deaths. Our results are robust to the estimation method, and they are of interest to governments and authorities responsible for the control of the pandemic.
