Modelling of the Explanatory Factors of the Number of COVID-19 Deaths for a Panel of Countries

Abstract

This research attempts to explain the number of COVID-19 deaths. We use in this sense non-spatial and spatial econometric modelling for 14 socio-economic and geographic variables for a panel of 112 countries. The number of hospital beds and doctors in a country has a negative impact on the number of COVID-19 deaths. The proportion of the population aged 65 and over in a country, the number of tourist arrivals and its COVID-19 infections have a positive effect on COVID-19 deaths. The number of COVID-19 deaths in a country depends on the observable characteristics of its neighbours. When the number of COVID-19 infections in neighbouring countries of a given country increases and the proportion of their populations aged 65 and over is high, the number of COVID-19 deaths in the affected country increases. There is no substantial impact of diabetes prevalence, stringency index, even temporally lagged and population density on the reduction in the number of COVID-19 deaths. This research highlights the significant impact of five explanatory variables among the 14 variables selected on the number of COVID-19 deaths. There is a spatial autocorrelation for the variables selected. The spatial models show the existence of an exogenous interaction effect.