This paper investigates the dynamic
relationships between the number of
COVID-19 infected cases and deaths in all the districts of Karnataka
state, India, from July 2020 to December 2021 based on the panel Generalized
Method of Moments (GMM). The panel GMM model with the first difference
transformation was found suitable for studying the dynamics of the number of
deaths due to COVID-19 infections over time. The one-period lag (DEATHS (-1))
has a positive and significant effect on the number of deaths (DEATH). The Wald
test confirms the validity of the coefficients' significance and adds
explanatory power to the model. The correlation between number of fatalities at
time t positively correlated with the number of deaths in the previous period.
Also, the number of infected cases positively and significantly influences the
number of deaths over time. Granger pairwise causality test reveals the
existence of bi-directional causality relationships between the COVID-19
infected cases and deaths.
classification numbers: E18, HO, I1, J64, J88.
Arellano-Bond serial correlation test, Cross-sectional dependence test,
Cointegration test, Granger causality test, Generalized Method of Moments, Kao
cointegration test, Hausman test, Levin-Lin-Chu unit root test, Wald test.