Economic activities' response to the COVID-19 pandemic in developing countries.

Since the occurrence of the COVID-19 pandemic, many governments around the world have instituted several economic policy responses to swathe the real sectors of their economies from the ramifications of the pandemic. However, most economies still remain vulnerable to the pandemic. In this paper, we evaluate and quantify the potential short-run impact of the COVID-19 pandemic on economic activities in eighteen (18) developing countries using monthly time series data on Industrial Production Index and Composite Index of Economic Activity from January 2010 to December 2020. In addition, we employ a state-space model (a Bayesian structural time series model) to estimate the absolute and relative effects of the COVID-19 pandemic on economic activities in those countries. The results of our Bayesian posterior estimate show that, in relative terms, economic activities of six countries have significantly reduced during the occurrence of the COVID-19 pandemic, usually between -4.4% and -16%. Our Bayesian posterior distribution graphs show that the significant negative impacts of the COVID-19 pandemic on economic activities of most of the countries are rather short-lived. This finding suggests that the real sectors of those countries have seen a recovery after being adversely affected by the COVID-19 pandemic. We recommend a continuation of the policy tools introduced by the central banks and the international organizations with a key focus on sectors of that economy that involves significant human interactions such as the hospitality and tourism as well as the aviation industry which was hugely hit by the pandemic.

The impact of COVID-19 on stock market performance in Africa: A Bayesian structural time series approach.

This paper evaluates and quantifies the short-term impact of the coronavirus disease of 2019 (COVID-19) on stock market performance in thirteen (13) African countries, using daily time series stock market data spanning 1st October 2019 to 30th June 2020. We employ a novel Bayesian structural time series approach (a state-space model) to estimate the relative effects of the COVID-19 pandemic on stock market performance in those countries. Generally, our Bayesian posterior estimates show that, in relative terms, stock market performances in Africa have significantly reduced during and after the occurrence of the COVID-19, usually between -2.7 % and -21 %. At the heterogeneous level, we find that 10 countries have their stock markets significantly and adversely affected by the COVID-19, whereas the remaining 3 countries see no significant impact (or a rather short-lived negative significant impact) of the COVID-19 pandemic on their stock markets. We find that, within our sample period, there is almost no chance that the COVID-19 pandemic would have positive effects on the stock market performance in Africa. Our findings contribute to the discussion and research on the economic impact of the COVID-19 pandemic by providing empirical evidence that the pandemic has restrictive effects on stock market performance in African economies.