Journal of Statistics Applications & Probability
Abstract
The main objective of this paper is to investigate the dynamic relationship between the COVID-19 infected cases and the number of deaths due to COVID-19 using the Johnsen-Fisher co-integration test, vector error correction model and Granger causality test. The daily COVID-19-infected new cases and daily deaths due to COVID-19 in the United States, Canada, Ukraine and India were collected from the website for the period from 01-04-2020 to 26-12-2010. The summary statistics revealed that the highest numbers of COVID-19-infected cases were registered in the United States, followed by India, Canada and Ukraine; the highest numbers of deaths due to COVID-19 were registered in the United States, followed by India, Ukraine and Canada. The death percentage is exceedingly high in Canada, followed by the United States, Ukraine and India. The Johnsen-Fisher co-integration test results reveal the existence of one co-integration equation. The vector error correction model and Granger causality test reveal that long-term and short-term causality exists between COVID-19 infection and death cases. The speed of adjustment is found to be 9.9%.
Digital Object Identifier (DOI)
http://dx.doi.org/10.18576/jsap/110116
Recommended Citation
Arunachalam, Rajarathinam and Pakkirisamy, Tamilselvan
(2022)
"Vector Error Correction Modeling of COVID-19 Infected Cases and Deaths,"
Journal of Statistics Applications & Probability: Vol. 11:
Iss.
1, Article 16.
DOI: http://dx.doi.org/10.18576/jsap/110116
Available at:
https://digitalcommons.aaru.edu.jo/jsap/vol11/iss1/16