Data Mining for Estimating Living Standards in the Constituent Entities of the Russian Federation

Abstract

The issues of increasing the efficiency of socio-economic management processes aimed at improving the living standards of the population in the Russian Federation are of great importance. To make rational, well-grounded management decisions, accurate information about the current situation in the constituent entities of the Russian Federation is required. Analytical information is formed by performing various studies to determine the index of living standard to assess regional differences and analyze the well-being of the population, taking into account the degree of its differentiation. Methods of data mining, in particular, the method of principal components and method of cluster analysis, are used as a toolkit for determining the index of the population living standards. The information material for the study is the indicators of the standard of living of the population published in the official bulletins of the Federal State Statistics Service of the Russian Federation. The analysis procedure is performed in the Statgraphics software package. The article presents a cluster structure of the standard of living of the population in the regions of the Russian Federation, including six clusters. The characteristics of each cluster are formed in terms of GRP, monetary income of the population, unemployment, housing provision, mortality, migration flows, etc. The results of the study make it possible to increase the validity of decisionmaking in the management of socio-economic systems from the standpoint of sustainable development of the standard of living of the population.