FACTOR ANALYSIS OF THE CENTRAL BLACK EARTH MACROREGION AREAS ECONOMIC DEVELOPMENT
Effective implementation of regional policy is impossible without assessing the current environment of the region’s functioning, which is formed under the influence of internal factors. Among the many factors that determine the socio-economic development of the region, we have identified: human potential, innovation potential, investment potential, digitalization of the economy, production potential, quality of life and infrastructure development. Each of the selected factors can be characterized by using a system of statistical indicators. In regional forecasts, internal factors act as control parameters, changing them it is possible to find an opportunity to change the course and direction of socio-economic processes in the region. This explains the necessity and relevance of the study. The purpose of this article is to form a set of indicators to assess the factor load on the socio-economic development of the region and determine its vector. The method of factor analysis on an indicative basis was used for achieving this goal. The importance of factorial analysis lies, first of all, in the fact that its results will make it possible to assess the share of influence of each factor on the “level of socio-economic development of the region” and to develop appropriate tools for managing growth factors. Taking into account the formed system of indicators, an analysis of the Central Black Earth macroregion areas economic development was carried out. The greatest factor load on the socio-economic development of the region is exerted by the innovation potential, production potential and human potential of the region. As a result of the study, a matrix of the regions distribution by the level of socio-economic development was built, reflecting the position of the region in dynamics. During the study period, the Voronezh region occupies a leading position, and the Tambov region is an outsider region. In addition, for each region, growth factors and restrictions on the development of the region were identified, which must be taken into account when building regional forecasts.