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Mathematical Modeling and Methodology for Assessing the Pace of Socio-Economic Development of the Russian Federation

Author

Listed:
  • Victor Orlov

    (Institute of Digital Technologies and Modeling in Construction, Moscow State University of Civil Engineering, Yaroslavskoye Shosse, 26, 129337 Moscow, Russia)

  • Tatyana Ivanova

    (Faculty of Economics, Chuvash State University Named I.N. Ulyanov, Moskovsky Prospect, 15, 428015 Cheboksary, Russia)

  • Tatyana Ladykova

    (Faculty of Economics, Chuvash State University Named I.N. Ulyanov, Moskovsky Prospect, 15, 428015 Cheboksary, Russia)

  • Galina Sokolova

    (Faculty of Economics, Chuvash State University Named I.N. Ulyanov, Moskovsky Prospect, 15, 428015 Cheboksary, Russia)

Abstract

The article develops the author’s methodology for assessing the rates of socio-economic development and their forecasting in the Russian Federation, which makes it possible to consider factors with heterogeneous metrics. For this, an index analysis of thirty-two indicators divided into seven macro-regional blocks (income, labor, business, ecology, society, prospects, finance) was carried out, integral indicators were calculated that characterize their changes and the pace of socio-economic development of the Russian Federation was determined. Further, using the means of mathematical modeling, a multifactorial mathematical model was built and tested in real-time, which makes it possible to obtain a high-quality predicted result. Based on the forecasts obtained, it can be stated that it is necessary to adjust certain indicators that actively influence the pace of development, which is a mathematical justification for making managerial decisions when developing strategies and programs related to socio-economic progress in the Russian Federation.

Suggested Citation

  • Victor Orlov & Tatyana Ivanova & Tatyana Ladykova & Galina Sokolova, 2022. "Mathematical Modeling and Methodology for Assessing the Pace of Socio-Economic Development of the Russian Federation," Mathematics, MDPI, vol. 10(11), pages 1-20, May.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:11:p:1869-:d:827791
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    References listed on IDEAS

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    4. Liu, W. & Ah-Kine, P. & Bretz, F. & Hayter, A.J., 2013. "Exact simultaneous confidence intervals for a finite set of contrasts of three, four or five generally correlated normal means," Computational Statistics & Data Analysis, Elsevier, vol. 57(1), pages 141-148.
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