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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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    3. Tatiana Ladykova & Vladimir Bersenyov, 2018. "Typology of Macroeconomic Parameters of Population Income," Economy of region, Centre for Economic Security, Institute of Economics of Ural Branch of Russian Academy of Sciences, vol. 1(2), pages 380-394.
    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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