Methodological approach to modeling and forecasting the impact of the spatial heterogeneity of the COVID-19 spread on the economic development of Russian regions

Наумов, И. В.; Otmakhova, Yu S.; Krasnykh, Sergey

doi:10.20537/2076-7633-2021-13-3-629-648

Cited by 8 publications

(3 citation statements)

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“…De plus, l ' impact de l ' environnement naturel et des facteurs économiques et sociaux sur la propagation de l ' épidémie se reflète principalement dans la température, l ' humidité, la vitesse du vent, les polluants atmosphériques, les mouvements de population, le niveau de développement économique et les installations médicales et aussi sanitaires. Naumov et al (2021) se proposent d ' évaluer l ' hétérogénéité spatiale de la propagation de l ' infection par le coronavirus, et de simuler les effets de l ' aggravation de la situation épidémiologique sur la dynamique du développement économique des systèmes régionaux. La particularité de l ' approche développée est le regroupement spatial des systèmes régionaux en fonction du niveau d ' incidence du COVID-19, réalisé à l ' aide d ' indices d ' autocorrélation spatiale globaux et locaux.…”

Section: Fondements Théoriques De La Dépendance Spatialeunclassified

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Analyse exploratoire spatiale des effets sanitaires et économiques de la COVID-19 à partir de données mondiales

Diandy

2023

RIELF

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Exploratory spatial analysis of the health and economic effects of COVID-19 using global data. Purpose : This article analyses the health and economic effects of the COVID-19 pandemic. Design/methodology/approach : The sample includes 132 countries, and the methodology is based on Exploratory Spatial Data Analysis. The calculation of the output gap by the Hodrick-Prescott filter allows to highlight the economic impact of the health crisis, through the output gaps in 2020. The health variable, for its part, is measured by the incidence rates of COVID-19. Findings : The results of the estimations validated the hypothesis of spatial autocorrelation for both the health and economic variables. Examination of the Moran scatter plot confirms the positive local spatial association pattern, i.e. the existence of similarities between neighbouring countries in the manifestation of the pandemic and spatial heterogeneity between groups of countries. More specifically, the results show the existence of clusters with low levels of COVID-19 incidence in Africa and Asia, compared with Europe and North America. In addition, while high-income countries were generally more affected in terms of health, they developed greater economic resilience. Originality/value : These results show that taking space into account could provide a better understanding of the dynamics of health and economic shocks.

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Section: Fondements Théoriques De La Dépendance Spatialeunclassified

“…Ces résultats sont similaires avec ceux obtenus par Naumov et al (2021). Ils sont aussi conformes à la synthèse des résultats empirique faite par Xie et al (2021) sur l ' importance de l ' environnement naturel et du niveau de développement économique dans la propagation de la pandémie.…”

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Analyse exploratoire spatiale des effets sanitaires et économiques de la COVID-19 à partir de données mondiales

Diandy

2023

RIELF

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“…The deterioration of the epidemiological situation in Russia caused by the spread of the novel coronavirus infection (Naumov et al, 2021) has spatial heterogeneity. There are poles of growth in the incidence of the COVID-19 (regions with a high concentration of cases), spatial clusters (regions with similar characteristics), and zones of their influence (directions in which the infection is spreading).…”

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Scenario forecasting of the socio-economic consequences of the COVID-19 pandemic in Russian regions

Наумов

Krasnykh

Otmakhova

2022

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Relevance. There is a perceived lack of methods that can accurately, reliably and comprehensively reflect the epidemiological situation in regions and its impact on their socio-economic development. The approaches that are currently described in research literature do not take into account the multivariance of scenarios of the COVID-19 pandemic, both in time and space. Research objective. The article aims to present a methodological framework that could be used to predict the socio-economic consequences of the COVID-19 pandemic in regions and to detect the most vulnerable regions. Data and methods. The study relies on a set of methods, including the methods of regression modeling, ARIMA forecasting and spatial correlation analysis. Results. The panel regression analysis has confirmed the negative impact of the pandemic on socio-economic development, in particular, the growth of overdue wage arrears, unemployment, arrears, the number of liquidated organizations, and the industrial production index. We have also identified the most vulnerable regions that need to be prioritized for government support. Conclusions. The resulting models and scenarios can be used by policy-makers to set the priorities of state policy for the economic support of the regions and stabilization of the epidemiological situation in the country.

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Regional Digital Space and Digitalisation of Industry: Spatial Econometric Analysis

Akberdina

Наумов

Krasnykh

2023

Lecture Notes in Information Systems and Organisation

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Methodological approach to modeling and forecasting the impact of the spatial heterogeneity of the COVID-19 spread on the economic development of Russian regions

Abstract: The article was prepared with the financial support of the grant of the Russian Foundation for Basic Research No. 20-04-60188 "Methods for forecasting and scenario modeling of socio-economic consequences of viral epidemics, taking into account spatial and communicative interactions."

Cited by 8 publications

References 1 publication

Analyse exploratoire spatiale des effets sanitaires et économiques de la COVID-19 à partir de données mondiales

Analyse exploratoire spatiale des effets sanitaires et économiques de la COVID-19 à partir de données mondiales

Scenario forecasting of the socio-economic consequences of the COVID-19 pandemic in Russian regions

Regional Digital Space and Digitalisation of Industry: Spatial Econometric Analysis

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