Subject. This article discusses the issues of scenario forecasting, collection and processing of information on the level of economic development of the country's regions and differentiation of Russian regions by population's income level. Objectives. The article aims to determine a set of interrelated parameters that have the most significant impact on the standard of living of the population. Methods. For the study, we used a comprehensive analysis. Results. The article presents an author-developed mathematical model that may help assess possible changes in the standard of living of the population of the country's regions based on several scenarios. The model includes variants of the values of particular indicators and takes into account the general economic situation in Russia. Conclusions. A significant gap in living standards between the regions of Russia cannot be overcome in the future until 2026.
Keywords: living standards, Russian regions, modeling, medium-term forecast, rating, development scenarios, integral indicator
References:
Jeff-Anyeneh S.E., Ananwude A.C., Ezu G.K., Nnoje A.I. Government Expenditure and Standard of Living in an Emerging Market in Africa – Nigeria. Economic Journal of Emerging Markets, 2020, vol. 12, iss. 2, pp. 167–178. URL: Link
Yu G.B., Lee D.-J., Sirgy M.J., Bosnjak M. Household Income, Satisfaction with Standard of Living, and Subjective Well-Being. The Moderating Role of Happiness Materialism. Journal of Happiness Studies, 2020, vol. 21, iss. 8, pp. 2851–2872. URL: Link
Wolf F., Lohmann H., Böhnke P. The Standard of Living Among the Poor Across Europe. Does Employment Make a Difference? European Societies, 2022, vol. 24, iss. 5, pp. 548–579. URL: Link
Stepanov V.S., Bobkov V.N., Shamaeva E.F., Odintsova E.V. [Building a model linking the indicator of the standard of living of the population with a set of indicators of socio-economic policy in the regions of Russia]. Uroven' zhizni naseleniya regionov Rossii = Living Standards of the Population in the Regions of Russia, 2022, vol. 18, iss. 4, pp. 450–465. (In Russ.) URL: Link
Shishmakov V.T., Shishmakov S.V., Lutsenko E.L. [Evaluation and prediction of the quality of life of the population of Russian cities]. Vestnik NGIEI = Bulletin NGIEI, 2016, no. 1, pp. 87–95. (In Russ.)
Sapunova T.A., Bulanova E.A. [Prediction of quality of life]. Vektor ekonomiki, 2019, no. 4. (In Russ.) URL: Link
Mukhacheva A.V., Pastukhova E.Ya., Kiryukhina A.N. [Mathematical modeling of the quality of life of the region's population]. Vestnik Omskogo universiteta. Seriya: Ekonomika = Herald of Omsk University. Series: Economics, 2020, vol. 18, no. 1, pp. 149–161. URL: Link (In Russ.)
Khubaev G.N. [Forecasting the dynamics of indicators of the level of development of the country's economy: models, methods, tools (on the example of Germany, Russia and Sweden]. Vestnik Yuzhno-Rossiiskogo gosudarstvennogo tekhnicheskogo universiteta (NPI). Seriya: Sotsial'no-ekonomicheskie nauki = Bulletin of South-Russian State Technical University (NPI). Series: Socio-Economic Sciences, 2020, vol. 13, iss. 5, pp. 224–240. (In Russ.) URL: Link
Mondal S., Das R., Chakraborty M. Spatial Inequality in Standard of Living (SoL) in India: A Spatial Econometric Approach. GeoJournal, 2023, vol. 88, iss. 5, pp. 5305–5329. URL: Link
Latimaha R., Ismail N.A., Bahari Z. Cost of Living and Standard of Living Nexus: The Determinants of Cost of Living. Jurnal Ekonomi Malaysia, 2020, vol. 54, iss. 3, pp. 1–14. URL: Link
Bobkov V.N., Stepanov V.S. [The Well-being model for evaluating and forecasting the standards and quality of living]. Uroven' zhizni naseleniya regionov Rossii = Living Standards of the Population in the Regions of Russia,2014, no. 1, pp. 104–110. (In Russ.)
Mentsiev A.U., Aigumov T.G., Amirova E.F. [Methods and technologies for collecting and analyzing data in the digital economy]. Ekonomika: vchera, segodnya, zavtra = Economics: Yesterday, Today and Tomorrow, 2022, vol. 12, iss. 11A, pp. 282–288. URL: Link (In Russ.)
Fattakhov R.V., Nizamutdinov M.M., Oreshnikov V.V. [Assessment of the development of the social infrastructure of Russian regions and its impact on demographic processes]. Finansy: teoriya i praktika = Finance: Theory and Practice, 2020, vol. 24, no. 2, pp. 104–119. (In Russ.) URL: Link
Bunkovsky D.V., Kapustyuk P.A. [Salary as the element of the value added created in the hidden economy]. Vestnik Vostochno-Sibirskogo instituta MVD Rossii = Vestnik Eastern Siberia Institute of the Ministry of the Interior of the Russian Federation, 2017, no. 4, pp. 158–168. URL: Link (In Russ.)
Policardo L., Sanchez Carrera E.J. Can Income Inequality Promote Democratization? Metroeconomica, 2020, vol. 71, iss. 3, pp. 510–532. URL: Link
Özdemir O. The New Insights on the Relationship between Democracy and Income: Empirical Evidence from Advanced Economies. Electronic Journal of Social Sciences, 2019, vol. 18, iss. 72, pp. 1776–1796. URL: Link
Stroev P.V., Kashin V.K., Pivovarova O.V. et al. [Information support of geoinformation modeling of spatial development (the case of the TASED in the Khabarovsk Territory)]. Vestnik Tyumenskogo gosudarstvennogo universiteta. Sotsial'no-ekonomicheskie i pravovye issledovaniya = Tyumen State University Herald. Social, Economic, and Law Research, 2019, vol. 5, no. 3, pp. 60–81. (In Russ.) URL: Link
Nizamutdinov M.M. [Modeling municipal level territorial systems' development: conceptual and methodical aspects]. Upravlencheskie nauki = Management Sciences, 2017, vol. 7, no. 2, pp. 23–31. URL: Link (In Russ.)