Regional Human Capital: Assessment of Exogenous Factors of its Development Based on the Cluster Analysis

   Relevance. Today, in modern economic conditions, issues in the field of development, accumulation and effective use of regional human capital are becoming more and more relevant. Human capital as an economic resource plays a key role in achieving competitive advantages in the socio-economic development of regions.
   The purpose is to identify groups of regions with similar socio-economic characteristics for the regional differentiation of human capital.
   Objectives: conduct a cluster analysis on the example of seventy-eight regions of the Russian Federation as of 2010 and 2019; to identify stable groups of regions according to homogeneous characteristics.
   Methodology. In the course of the research, general scientific methods, the method of comparative analysis were used. The fundamental method of research that allowed us to come to key results and conclusions is cluster analysis.
   Results. As a result of the study, four stable clusters were identified that unite regions according to the level of human capital development, determined using the human development index. As a result of the study, according to the results of 2019, the first regional cluster includes the regions that are leaders in life expectancy; the second cluster includes the regions with the highest value of the average monthly nominal accrued salary, as well as the highest regional coefficient of allowance; the third and fourth clusters are the most numerous, and their indicators have an average estimate.
   Conclusions. The main conclusion of this article is that the performed cluster analysis made it possible to distribute the set of regions of the Russian Federation into homogeneous groups of clusters based on four features: longevity index, education index, unemployment index and wage index. Also, cluster analysis allowed us to identify similar problems in the field of development and use of human capital among the identified stable groups of regions.

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