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Title: Dying together: A convergence analysis of fatalities during COVID-19
Authors: Panagiotidis, Theodore
Papapanagiotou, Georgios
Stengos, Thanasis
Type: Article
Subjects: FRASCATI::Social sciences::Economics and Business::Economics
Keywords: Convergence clubs
Maximal clique algorithm
Long memory
Issue Date: Nov-2023
Publisher: Elsevier
Source: The Journal of Economic Asymmetries
Volume: 28
First Page: e00315
Abstract: Governments implemented countermeasures to mitigate the spread of the COVID-19 virus. This had a severe effect on the economy. We examine convergence patterns in the evolution of COVID-19 deaths across countries. We aim to investigate whether countries that implemented different measures managed to limit the number of COVID-19 deaths. We extend the most recent macro-growth convergence methodology to examine convergence of COVID-19 deaths. We combine a long memory stationarity framework with the maximal clique algorithm. This provides a rich and flexible club formation strategy that goes beyond the stationary/non stationary approach adopted in the previous literature. Our results suggest that strict measures (even belated) or an aggressive vaccination scheme can confine the spread of the disease while maintaining the strictness of the measures steady can lead to a burst of the virus. Finally, we observe that fiscal measures did not have an effect on the containment of the virus.
ISSN: 1703-4949
Other Identifiers: 10.1016/j.jeca.2023.e00315
Appears in Collections:Department of Economics

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