<abstract xmlns="http://www.w3.org/1999/xhtml"><p>The study develops and examines the spatial distribution of the Corona Virus Disease (COVID) on mortality outcomes using a global panel dataset of 79 countries. The empirical evidence is based on Fixed Effect (FE) and System Generalized Method of Moment (SGMM) estimator. The predicted variable is proxy with daily mortality outcomes, while the predictor variable is proxy with spatial COVID spread while controlling for social tension and average temperature. The global and regional findings of the study established that spatial variation in COVID spread had positive and significant relationships with mortality outcomes. Further results also indicate that social tension is a contributing factor to the rising daily mortality outcome from the COVD outbreak, whereas temperature variation reduces mortality outcome. Thus, the study recommends the use of statistical modelling to predict and manage the epidemic. Also, there is an urgent demand to deploy essential social need to the vulnerable proportion of the population to reduce the level of social unrest, while strengthening collaborative research among scientists to develop, produce and distribute vaccines that will put an end to the pandemic.</p></abstract>

The study develops and examines the spatial distribution of the Corona Virus Disease (COVID) on mortality outcomes using a global panel dataset of 79 countries. The empirical evidence is based on Fixed Effect (FE) and System Generalized Method of Moment (SGMM) estimator. The predicted variable is proxy with daily mortality outcomes, while the predictor variable is proxy with spatial COVID spread while controlling for social tension and average temperature. The global and regional findings of the study established that spatial variation in COVID spread had positive and significant relationships with mortality outcomes. Further results also indicate that social tension is a contributing factor to the rising daily mortality outcome from the COVD outbreak, whereas temperature variation reduces mortality outcome. Thus, the study recommends the use of statistical modelling to predict and manage the epidemic. Also, there is an urgent demand to deploy essential social need to the vulnerable proportion of the population to reduce the level of social unrest, while strengthening collaborative research among scientists to develop, produce and distribute vaccines that will put an end to the pandemic.

A Spatial Econometric Analysis on the Impact of COVID-19 on Mortality Outcome

Economics and Business

This work is licensed under the Creative Commons Attribution 4.0 International License.

{"article-title":"A Spatial Econometric Analysis on the Impact of COVID-19 on Mortality Outcome"}

The study develops and examines the spatial distribution of the Corona Virus Disease (COVID) on mortality outcomes using a global panel dataset of 79...

A Spatial Econometric Analysis on the Impact of COVID-19 on Mortality Outcome

Published Online: Oct 10, 2020

Page range: 179 - 200

DOI: https://doi.org/10.2478/eb-2020-0013

Keywords
COVID19, confirmed cases, mortality, System GMM

© 2020 Olatunji Shobande et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

A Spatial Econometric Analysis on the Impact of COVID-19 on Mortality Outcome

Published Online: Oct 10, 2020

Page range: 179 - 200

DOI: https://doi.org/10.2478/eb-2020-0013

KeywordsCOVID19, confirmed cases, mortality, System GMM

© 2020 Olatunji Shobande et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Keywords
COVID19, confirmed cases, mortality, System GMM