CLUSTER ANALYSIS OF RUSSIAN REGIONS BY ECONOMIC AND DEMOGRAPHIC INDICATORS TO IMPROVE THE STRATEGIES OF DEVELOPMENT INSTITUTIONS

Resumo

Objective: The aim of the study is to create a classification of the subjects of the Russian Federation by economic development and demographics. Methods: The classification of the subjects of the Russian Federation is performed using cluster analysis. The study of relationships focuses on the following indicators: gross regional product per capita, average per capita amount of fixed assets and investment, share of small and medium-sized entrepreneurship in gross regional product, labor productivity index, per capita gross regional product index, subsistence minimum, median income of the population, the excess of the median income over the subsistence minimum, and percentage of the population with incomes below the subsistence minimum. For each cluster group, Pearson and Spearman correlation coefficients are calculated, and the relationship of the indicators is evaluated. Results: Research into the economic conditions of the regions suggests five cluster groups similar in their economic situation and problems. In the presence of relationships, power regression models are constructed, on the basis of which the influence of factor attributes on the resultant is quantitatively evaluated. Conclusion: Clustering by demographic indicators reveals the division of the population of Russian regions into three cluster groups. The cluster with a poor demographic situation includes almost half of the Russian regions (40 constituent entities), characterized by low birth rates, high mortality, and negative migratory population growth. The study also touches upon the issue of regional unemployment, which rose in all Russian regions in 2021. Based on the conducted research, economic conclusions are derived for the purpose of developing an effective strategy for development institutions.