The Socio-Economic Determinants of the Coronavirus Disease (COVID-19) Pandemic

Stojkoski, Viktor; Utkovski, Zoran; Jolakoski, Petar; Tevdovski, Dragan; Kocarev, Ljupčo

doi:10.2139/ssrn.3576037

Cited by 37 publications

(24 citation statements)

References 63 publications

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“…Even though making predictions ex-ante based on forecasting rather than real results has high macro-econometric uncertainty, macroeconomists still place value on such examinations. The effects of a pandemic result in health expenditures, travel cancelations, and other significant events and changes, which contribute to a depressed economy worldwide (Stojkoski et al 2020).…”

Section: Methodsmentioning

confidence: 99%

The macroeconomic effects of COVID-19 in Montenegro: a Bayesian VARX approach

Djurovic

Bojaj

2020

Financ Innov

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This study examines, diagnoses, and assesses appropriate macroeconomic policy responses of the Montenegrin Government to the outbreak of COVID-19. The model econometrically measures the macroeconomic costs using a Bayesian VARX Litterman/Minessota prior to the pandemic disease in terms of demand and supply loss due to illness and closed activities and their effects on GDP growth in various pandemic scenarios. We explore five economic scenarios—shocks—using the available data from January 2006 to December 2019, following real out-of-sample forecasts generated from January 2020 to December 2020. Sensitivity scenarios spanning January 2020 to June 2020 from ± 10 to ± 60% were analyzed. We observed what happens to the supply and demand sides, namely, GDP, tourism, capital stock, human capital, health expenditures, economic freedom, and unemployment. The results show a toll on the GDP, tourism, unemployment, capital stock, and especially human capital for 2020. The recommended policy measures are public finance spending initiatives focused on securing employment and keeping highly qualified staff in Montenegrin companies. Considering all uncertainties, the rebound of the Montenegrin economy could take a few years to reach pre-COVID 19 output levels.

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Section: Methodsmentioning

confidence: 99%

The macroeconomic effects of COVID-19 in Montenegro: a Bayesian VARX approach

Djurovic

Bojaj

2020

Financ Innov

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“…As of early June 2020, Israel had roughly 2000 active cases, less than 300 deaths and a fatality rate of 1.67%, substantially lower than that of most West European countries and well below the world average of 6.15%. 1 At the time of this writing, a second wave of Covid-19 is plaguing Israel. The present study explores morbidity rates in Israel on a residential community basis, aiming to identify associations with main sociodemographic variables, as they evolved under the lockdown practice.…”

Section: Introductionmentioning

confidence: 99%

“…Scholars have suggested numerous variables that may affect the spread and scope of the pandemic, including medical resources, health coverage, life expectancy, employment rates, income inequality, levels of social connectedness and education, alongside religious affiliation, household size, population age composition, population density and ecological footprint [1]. Of this wide array, the present study focuses on four variables that have been repeatedly suggested in Israel's public discourse, as influencing local morbidity rates: population density, socioeconomic status (SES), percentage of elderly population and minority status.…”

Section: Introductionmentioning

confidence: 99%

Covid-19 in Israel: socio-demographic characteristics of first wave morbidity in Jewish and Arab communities

Birenbaum‐Carmeli

Chassida

2020

Int J Equity Health

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Background The first wave of the Covid-19 pandemic hit Israel in late February 2020. The present study examines patterns of the first wave of Covid-19 morbidity in Israel at the macro level, during the period of late February to early June 2020, when the first wave has faded out. The analysis focuses on the significance of four sociodemographic variables: socioeconomic status, population density, rate of elderly population and minority status (Jewish / Arab identity) of the population in cities with 5000 residents or more. Additionally, we take a closer look into the association between morbidity rates and one SES component – home Internet access. Methods The article is a cross sectional study of morbidity rates, investigated on a residential community basis. Following the descriptive statistics, we move on to present multivariate analysis to explore associations between these variables and Covid-19 morbidity in Israel. Results Both the descriptive statistics and regressions show morbidity rates to be positively associated with population density. Socioeconomic status as well as the size of elderly population were both significantly related to morbidity, but only in Jewish communities. Interestingly, the association was inverse in both cases. i.e., the higher the SES the lower the morbidity and the larger the elderly population, the lower the community’s morbidity. Another interesting result is that overall, morbidity rates in Jewish cities were consistently higher than in Arab communities. Conclusions We attribute the low morbidity rates in communities with relatively small elderly populations to the exceptionally high fertility rates in ultra-orthodox communities that sustained increased rates of morbidity; the lower morbidity in Arab communities is attributed to several factors, including the spatial Jewish-Arab segregation.

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“…For example, the Census Bureau [19] provides thousands of fields for multiple geographic scales each year, but less than 20 factors are widely recognized and used in COVID-19-related analysis and studies [11,20]. Socioeconomic factors such as the policy stringency index [21,22] are broadly accessed and utilized at country level, but not at the state-level in the USA. It is necessary to leverage the state policy as a quantitative constrain with other dynamic spatiotemporal attributes in COVID-19 data collection.…”

Section: Discussionmentioning

confidence: 99%

A State-Level Socioeconomic Data Collection of the United States for COVID-19 Research

Sha

Malarvizhi

Liu

et al. 2020

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The outbreak of COVID-19 from late 2019 not only threatens the health and lives of humankind but impacts public policies, economic activities, and human behavior patterns significantly. To understand the impact and better prepare for future outbreaks, socioeconomic factors play significant roles in (1) determinant analysis with health care, environmental exposure and health behavior; (2) human mobility analyses driven by policies; (3) economic pressure and recovery analyses for decision making; and (4) short to long term social impact analysis for equity, justice and diversity. To support these analyses for rapid impact responses, state level socioeconomic factors for the United States of America (USA) are collected and integrated into topic-based indicators, including (1) the daily quantitative policy stringency index; (2) dynamic economic indices with multiple time frequency of GDP, international trade, personal income, employment, the housing market, and others; (3) the socioeconomic determinant baseline of the demographic, housing financial situation and medical resources. This paper introduces the measurements and metadata of relevant socioeconomic data collection, along with the sharing platform, data warehouse framework and quality control strategies. Different from existing COVID-19 related data products, this collection recognized the geospatial and dynamic factor as essential dimensions of epidemiologic research and scaled down the spatial resolution of socioeconomic data collection from country level to state level of the USA with a standard data format and high quality.

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The Socio-Economic Determinants of the Coronavirus Disease (COVID-19) Pandemic

Cited by 37 publications

References 63 publications

The macroeconomic effects of COVID-19 in Montenegro: a Bayesian VARX approach

The macroeconomic effects of COVID-19 in Montenegro: a Bayesian VARX approach

Covid-19 in Israel: socio-demographic characteristics of first wave morbidity in Jewish and Arab communities

A State-Level Socioeconomic Data Collection of the United States for COVID-19 Research

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