Macroeconomic Dynamics in Conditions of Instability

The purpose of this paper is to evaluate some macroeconomic variables (namely, growths of nominal and real GDP, as well as unemployment rate) in periods of pandemic, caused by COVID-19. It uses quarterly data from publicly available sources, The International Monetary Fund (IMF) and Johns Hopkins Coronavirus Resource Center publicly available database from 2015 to 2022. Since generally GDP growth and unemployment could be explained by their lags, the dynamic panel data model is suitable for use, which is then estimated using Arellano-Bond estimator, using the general method of moments. Regressions are derived for these variables for countries, for which time series are stationary. The models pass Sargan-Hansen test as well as Arellano-Bond tests of AR(1) and AR(2). The main finding are that with occurrence of stringency index fatality rate becomes insignificant, while change in the strictness of the lockdown is significant at 1% significance level for the 1st, 2nd, as well as 4th lags both for nominal GDP growth as the dependent variable, and for the first difference in real GDP growth, with positive coefficients, leading to conclusion about positive association between increasing strictness of the lockdown and reducing downturn of the economy. The increase in unemployment rate is found to be associated with an increase in strictness of the lockdown (significant at 1% significance level), thus presenting a trade-off between reduction of GDP growth and increase in unemployment rate.