Subject. This article considers the economic potential and living standards of the population of the Central Federal District regions and discusses the problems of employment and rational use of labor resources. Objectives. The article aims to assess the differentiation of the Central Federal District regions according to the importance of the main economic and demographic parameters. Methods. For the study, we used a cluster analysis. Results. The article finds that among all the Central Federal District regions, only the City of Moscow is characterized by high values of most indicators of socio-demographic development. The dangerous demographic situation in many regions is primarily due to the low value of the gross regional product per capita. Conclusions. To eliminate the negative trends in the development of many regions, the main of which is the birth rate decline, it is necessary to create jobs, normal housing conditions, and ensure sustainable growth in real incomes of the population.
Keywords: Central Federal District, demographic development, demographic situation, cluster analysis, fertility rate, mortality rate
References:
Luk'yanchenko N.D., Ibragimkhalilova T.V. [Typology as a method of researching the social and economic development of territories: marketing aspect]. Vestnik Instituta ekonomicheskikh issledovanii = Vestnik of Institute of Economic Research, 2018, no. 2, pp. 48–55. URL: Link (In Russ.)
Suvorova A.V. [Features of typologization of regions: approaches and options of criteria]. Ekonomika i biznes: teoriya i praktika = Economy and Business: Theory and Practice, 2019, no. 11-3, pp. 71–74. (In Russ.) URL: Link
Lokosov V.V., Ryumina E.V., Ul'yanov V.V. [Macroregions of Russia: characteristic of human potential]. Narodonaselenie = Population, 2018, vol. 21, no. 3, pp. 37–51. URL: Link (In Russ.)
Lokosov V.V., Ryumina E.V., Ul'yanov V.V. [Regional differentiation of human potential indicators]. Ekonomika regiona = Economy of Region, 2015, no. 4, pp. 185–196. URL: Link (In Russ.)
Lokosov V.V., Ryumina E.V., Ul'yanov V.V. [Clustering of regions by indicators of quality of life and quality of population]. Narodonaselenie = Population, 2019, vol. 22, no. 4, pp. 4–17. (In Russ.) URL: Link
Rossoshanskii A.I. [Typology of the Russian regions in terms of quality indices of life of the population]. Gosudarstvennyi sovetnik, 2018, no. 3, pp. 5–9. (In Russ.) URL: Link
Zholudeva V.V., Mel'nichenko N.F., Kozlov G.E. [Statistical estimation of the life quality of Central Federal District population]. Ekonomika, statistika i informatika. Vestnik UMO = Economics, Statistics and Informatics. Bulletin of Educational Methodical Association, 2015, no. 2, pp. 173–177. (In Russ.) URL: Link
Gulyaeva T.I., Takmakova E.V. [Assessing the living standards of the population of Russia's regions based on a cluster analysis]. Ekonomicheskii analiz = Economic Analysis: Theory and Practice, 2021, vol. 20, iss. 5, pp. 810–828. (In Russ.) URL: Link
Filipova A.G., Eskova A.V., Inzartsev A.V. [Social potential of a region: experience of using cluster analysis]. Regionologiya = Russian Journal of Regional Studies, 2017, vol. 25, no. 3, pp. 438–455. URL: Link (In Russ.)
Orlova I.V., Filonova E.S. [Cluster analysis of the regions of the Central Federal District socio-economic and demographic indicators]. Ekonomika, statistika i informatika. Vestnik UMO = Economics, Statistics and Informatics. Bulletin of Educational Methodical Association, 2015, no. 5, no. 111–115. (In Russ.) URL: Link
Korolenko A.V. [Mortality differentiation in Russia’s regions: the multidimensional grouping method]. Voprosy territorial'nogo razvitiya, 2020, vol. 8, no. 5. (In Russ.) URL: Link
Kostina S.N., Trynov A.V. [Cluster analysis of the dynamics of the birth rate of fourth and subsequent children in Russian regions]. Ekonomicheskie i sotsial'nye peremeny: fakty, tendentsii, prognoz = Economic and Social Changes: Facts, Trends, Forecast, 2021, vol. 14, no. 3, pp. 232–245. (In Russ.) URL: Link
Bagirova A.P., Bykova D.G., Voroshilova A.I. et al. Rozhdaemost' i roditel'stvo v Rossii: determinanty i regional'naya differentsiatsiya: monografiya [Fertility and parenthood in Russia: determinants and regional differentiation: a monograph]. Yekaterinburg, Ural Federal University named after the first President of Russia B.N. Yeltsin Publ., 2018, 157 p.
Shubat O.M., Shmarova I.V. [Cluster analysis as an analytical tool of population policy]. Ekonomika regiona = Economy of Region, 2017, vol. 13, iss. 4, pp. 1175–1183. (In Russ.) URL: Link
Fattakhov R.V., Nizamutdinov M.M., Oreshnikov V.V. [Ranking of regions of Russia by the demographic situation considering the level of development of social infrastructure]. Mir novoi ekonomiki = The World of New Economy, 2020, vol. 14, no. 4, pp. 96–109. (In Russ.) URL: Link
Maravelakis P. The Use of Statistics in Social Sciences. Journal of Humanities and Applied Social Sciences, 2019, vol. 1, iss. 2, pp. 87–97. URL: Link
Wahyuni R. K-Means Clustering for Grouping Indonesia Underdeveloped Regions in 2020 Based on Poverty Indicators. Parameter: Journal of Statistics, 2021, vol. 2, iss. 1, pp. 8–15. URL: Link
Laxmi K.D., Bidhubhusan M., Anjali B. et al. Intra-cluster Correlations in Socio-Demographic Variables and Their Implications: An Analysis Based on Large-scale Surveys in India. SSM – Population Health, 2023, vol. 21. no. 101317. URL: Link
