Abstract
COVID-19 infections have plagued the world and led to deaths with a heavy pneumonia manifestation. The main objective of this investigation is to evaluate the performance of certain economies during the crisis derived from the COVID-19 pandemic. The gross domestic product (GDP) and global health security index (GHSI) of the countries belonging–or not–to the Organization for Economic Cooperation and Development (OECD) are considered. In this paper, statistical models are formulated to study this performance. The models’ specifications include, as the response variable, the GDP variation/growth percentage in 2020, and as the covariates: the COVID-19 disease rate from its start in March 2020 until 31 December 2020; the GHSI of 2019; the countries’ risk by default spreads from July 2019 to May 2020; belongingness or not to the OECD; and the GDP per capita in 2020. We test the heteroscedasticity phenomenon present in the modeling. The variable “COVID-19 cases per million inhabitants” is statistically significant, showing its impact on each country’s economy through the GDP variation. Therefore, we report that COVID-19 cases affect domestic economies, but that OECD membership and other risk factors are also relevant.
Highlights
Introduction and Review of LiteraturePublished: 2 July 2021The first cases reported through global news of pneumonia derived from an unknown pathogen virus were in December 2019, in Wuhan, China [1,2]
We evaluate the performance of the countries’ economies belonging or not to the Organization for Economic Cooperation and Development (OECD)
The COVID-19 cases per million inhabitants are significant statistically, indicating the effect that this variable has on each country’s economy in this study; In general, by increasing one case per million inhabitants, under the condition that all the remaining covariates remain fixed, we harm the gross domestic product (GDP) of 0.0026%, or 2.6%, per 1000 infected per million inhabitants on average; The results of the proposed models show an R2 of 12.6% on average, implying a low level of regression adjustment and suggesting that another type of model specification is required for better characterization
Summary
The first cases reported through global news of pneumonia derived from an unknown pathogen virus were in December 2019, in Wuhan, China [1,2]. The pathogen was detected as a novel enveloped ribonucleic acid betacoronavirus [3]. This pathogen has been named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) [3], known currently as COVID-19. The virus belongs to the phylogenetic tree of SARS-CoV [4]. The World Health Organization (WHO) declared the COVID-19 outbreak to be a global pandemic. On 27 March 2020, the number of cases exceeded 500,000, and it has continued to rise since that date [5].
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