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Computer Research and Modeling, 2021, Volume 13, Issue 3, Pages 629–648
DOI: https://doi.org/10.20537/2076-7633-2021-13-3-629-648
(Mi crm905)
 

This article is cited in 6 scientific papers (total in 6 papers)

MODELS OF ECONOMIC AND SOCIAL SYSTEMS

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

I. V. Naumova, Yu. S. Otmakhovab, S. S. Krasnykha

a Institute of Economics of the Ural Branch of RAS , 29 Moskovskaya st., Ekaterinburg, 620014, Russia
b Central Economics and Mathematics Institute RAS, 47 Nakhimovsky ave., Moscow, 117418, Russia
References:
Abstract: The article deals with the development of a methodological approach to forecasting and modeling the socio-economic consequences of viral epidemics in conditions of heterogeneous economic development of territorial systems. The relevance of the research stems from the need for rapid mechanisms of public management and stabilization of adverse epidemiological situation, taking into account the spatial heterogeneity of the spread of COVID-19, accompanied by a concentration of infection in large metropolitan areas and territories with high economic activity. The aim of the work is to substantiate a methodology to assess the spatial heterogeneity of the spread of coronavirus infection, find poles of its growth, emerging spatial clusters and zones of their influence with the assessment of inter-territorial relationships, as well as simulate the effects of worsening epidemiological situation on the dynamics of economic development of regional systems. The peculiarity of the developed approach is the spatial clustering of regional systems by the level of COVID-19 incidence, conducted using global and local spatial autocorrelation indices, various spatial weight matrices, and L. Anselin mutual influence matrix based on the statistical information of the Russian Federal State Statistics Service. The study revealed a spatial cluster characterized by high levels of infection with COVID-19 with a strong zone of influence and stable interregional relationships with surrounding regions, as well as formed growth poles which are potential poles of further spread of coronavirus infection. Regression analysis using panel data not only confirmed the impact of COVID-19 incidence on the average number of employees in enterprises, the level of average monthly nominal wages, but also allowed to form a model for scenario prediction of the consequences of the spread of coronavirus infection. The results of this study can be used to form mechanisms to contain the coronavirus infection and stabilize socio-economic at macroeconomic and regional level and restore the economy of territorial systems, depending on the depth of the spread of infection and the level of economic damage caused.
Keywords: spatial heterogeneity, spatial autocorrelation, clustering, local Moran's index, interregional relationships, coronavirus infection, spatio-temporal modeling, panel data, regional systems.
Funding agency Grant number
Russian Foundation for Basic Research 20-04-60188
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.”
Received: 16.12.2020
Revised: 15.03.2021
Accepted: 04.05.2021
Document Type: Article
UDC: 330.4+338.14+614.1
Language: Russian
Citation: I. V. Naumov, Yu. S. Otmakhova, S. S. Krasnykh, “Methodological approach to modeling and forecasting the impact of the spatial heterogeneity of the COVID-19 spread on the economic development of Russian regions”, Computer Research and Modeling, 13:3 (2021), 629–648
Citation in format AMSBIB
\Bibitem{NauOtmKra21}
\by I.~V.~Naumov, Yu.~S.~Otmakhova, S.~S.~Krasnykh
\paper Methodological approach to modeling and forecasting the impact of the spatial heterogeneity of the COVID-19 spread on the economic development of Russian regions
\jour Computer Research and Modeling
\yr 2021
\vol 13
\issue 3
\pages 629--648
\mathnet{http://mi.mathnet.ru/crm905}
\crossref{https://doi.org/10.20537/2076-7633-2021-13-3-629-648}
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  • https://www.mathnet.ru/eng/crm/v13/i3/p629
  • This publication is cited in the following 6 articles:
    Citing articles in Google Scholar: Russian citations, English citations
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    Computer Research and Modeling
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