Modeling the Dynamics of Financial and Consumer Behavior of Russians

Abstract

The issue of studying the socio-economic inequality of the population in the regional context is a broad field for research. Of interest are studies based on the analysis of the relationships between the population’s income, debt load or the propensity to accumulation of money, as well as the population’s ability to spend leisure time in restaurants and other similar establishments. The purpose of the article is to identify the features and analyze the dynamics of financial and consumer behavior of the population of the Russian Federation in the regional context. The article studies the financial and consumer behavior of the population of Russian regions, both in time and spatial terms, based on open data from SBER. The spatial regression heterogeneity of data is proved by using the multidimensional classification methods and the time heterogeneity of data is proved by using special statistical criteria used in time series analysis. The revealed differentiation of the regions of the Russian Federation in terms of financial and consumer behavior shows the stability of the class with the highest incomes and consumer expenditures. This class includes the capital regions and the Northern regions where mining operations as economic activity is developed. Meanwhile, almost all of Central Russia belongs to regions with very low incomes, which means that the population of these regions does not have the opportunity to saving up. The population of these regions is characterized by the lowest spending not only in restaurants, but also in fast food cafes. The developed system of equations model based on panel data has a scientific novelty, which allows displaying structural relationships between the population’s income, financial and consumer behavior. In future research, when information for 2020 becomes publicly available, the model parameters should be re-evaluated, and to account for the impact of quarantine measures, appropriate variables (dummies, perhaps) may be introduced into the model. The obtained results and conclusions can be used in the development and evaluation of the effectiveness of projects aimed at demographic development or any socio-economic programs.