UNEMPLOYMENT BEHAVIOUR IN THE COVID-19 PANDEMIC: EVIDENCE FROM DEVELOPING COUNTRIES

Abstract

This paper explores the impacts of the COVID-19 pandemic, corruption and other determinants on unemployment in developing countries using panel dataset for 89 developing countries from January to December 2020. The proposed unemployment model is estimated utilising a newly formulated conceptual framework to examine whether COVID-19 pandemic, corruption, and human capital, play a moderating role on unemployment determination in our selected developing countries. The model is estimated using the dynamic panel system generalised method of moments (GMM) estimator. Apart from output, inflation and human capital, our results show that the COVID-19 pandemic and corruption are major variables in explaining the unemployment rate for our sampled countries. Furthermore, and more notably, we find evidence that the COVID-19 pandemic and corruption appear to significantly restrain and alter the role of outputs and human capital in impacting unemployment. Therefore, the detrimental effects of the COVID-19 pandemic and corruption on the economies and labour markets of countries examined should not be under-estimated. Additionally, findings show that, while policy initiatives to combat the COVID-19 pandemic are critical, strengthening anti-corruption regulations would further improve the efficiency of any attempt to reduce unemployment rates associated with the COVID-19 period.