Possibilities of Multidimensional, Factor and Cluster Methods of the Analysis of the Population’s Well-being of the Central Russia Regions

Abstract

Efficiency and expediency of use of multidimensional statistical analysis methods for estimation and monitoring of well-being and living standard of the regions’ population are demonstrated in the article. The results of monitoring of incomes and living standard of the Central Russia regions’ population for 2017-2018 carried out by the Institute of Socio-Economic Studies of the Population of the Russian Academy of Sciences are the empirical base of the research. Results of multidimensional correlation analysis of living standard indicators of the population which allow to essentially reduce the dimension of factor space of well-being indicators are presented. Factor analysis carried out on main a components method allowing to allocate two primary factors of population well-being - material welfare factor and the factor of inequality of monetary incomes. To classify regions according to informative indicators of well-being and living standard cluster analysis is carried out in the result of which three clusters with steady reference of all CFR regions on well-being standard are allocated. Besides, estimation of the degree of the regions’ population well-being with transformation of informative indicators values to values of Harrington’s desirability function is given. The results of regions ranging on two desirability functions are presented: basic one characterizing material welfare of the population and additional one reflecting inequality of monetary incomes.