Using the Sectoral Structure of the Economy to Select Competing Regions (on the Example of the Amur Region)

Abstract

One of the stages of the statistical study of the competitiveness of a region is the selection of competing regions.Purpose of the study. The purpose of the article is to form a statistical set of regions-competitors based on the sectoral structure of the economy.Materials and methods. As research methods in this article, the method of the main array, factorial, cluster methods, statistical methods are chosen. The statistical data of Rosstat were used for the study. To perform the calculations, the GVA was considered in the structure of Russian National Classifier of Types of Economic Activity2 for 2019. Results. With the help of factor analysis, 19 types of economic activity of the regions were grouped according to similarities and differences. As a result, six factors were formed, each of which collected dependent types of economic activity. The use of cluster analysis made it possible to form groups of regions with a similar sectoral structure of the economy. The study involved 85 regions of the Russian Federation. Cluster analysis made it possible to solve the methodological problem of determining the boundaries of GVA intervals for certain types of economic activity in the selection of competing regions.The paper shows that for the Amur Region, nine regions of the Russian Federation should be considered as competing regions. The regions of this cluster are united by a high share of gross value added by the types of activity “Transportation and storage”, “Public administration”, “Trade”. At the same time, competitors are regions from different federal districts: 70% of the regions of the Far Eastern Federal District, 20% of the Southern Federal District, 10% of the Siberian Federal District. The main results of the study are the following: 1) a high variation of the regions of the Russian Federation in 2019 was revealed by the type of economic activity “Mining” and “Manufacturing”; 2) a grouping of 19 types of economic activity of the regions was carried out using the factor analysis method; 3) a cluster analysis of the regions of the Russian Federation was carried out according to the sectoral structure of gross value added for 2019; five clusters were received. Conclusion. This paper shows that the selection of competing regions must be carried out using the sectoral structure of the region’s economy. Consideration of the region’ specialization is an important requirement of the selection methodology. The advantage of the author’s methodology is its universality, objectivity and reflection of the specialization of the region. As a direction for further research, one should consider determining the specialization of regions using localization coefficients and, on its basis, the formation of a statistical set of competing regions. The presented sample of regions is necessary for assessing their competitiveness.