Econometric Model for Identifying Factors of Income Differentiation of the Population

Purpose of the study. On the basis of the construction of a multifactorial econometric model, it is necessary to identify the factors of income differentiation of the population. In accordance with the goal, the following tasks are set: 1) to propose a typology of factors of household income differentiation; 2) on the basis of correlation analysis, to assess the closeness of the relationship between the average income of the population and those statistical indicators that maximally reflect the level of formation, the content and nature of the factors’ influence of household income differentiation; 3) using a step-by-step regression analysis algorithm to construct an econometric model to quantify the relationship between the factors of income differentiation and the income of the population.Materials and methods. In the process of preparing the article, the authors used information from the website of the Federal State Statistics Service, analytical statistical materials, scientific works of Russian and foreign scientists. The following methods were used in the paper: system analysis method (to develop a typology of factors for differentiating household income); the method of economic and mathematical modeling (when building an econometric model to quantify the relationship between the factors of income differentiation and the income of the population).Results. The classification of the factors of differentiation of household incomes was carried out according to three criteria: the level of formation, the content and nature of the influence of the factors. Four groups of statistical indicators have been formed, which, to the maximum extent, are the essence of the factors of income differentiation. An analysis of the correlation coefficients indicates a close relationship between the average income of the population of the Russian Federation regions and the overwhelming majority of statistical indicators. Assessment of the statistical significance of the regression coefficients made it possible to identify those indicators with which the indicator of the average income of the population has a significant quantitative dependence, namely: retail trade turnover per capita; the volume of personal services per capita; average monthly nominal accrued wages; the value of the subsistence minimum. This made it possible to build a four-factor econometric model.Conclusion. A typology of factors of household incomes’ differentiation is proposed, which combines such classification features as: the level of formation, the content and nature of the influence of factors. Those statistical indicators that reflect to the maximum extent the level of formation, content and nature of the influence of the previously considered factors of income differentiation on the level of income of the population are selected and grouped according to the corresponding criterion. Based on the correlation analysis, an assessment of the closeness of the relationship between the average income of the population and statistical indicators reflecting the factors of income differentiation was carried out. Using the algorithm of stepby-step regression analysis, a multivariate econometric model was built, which made it possible to identify a quantitative relationship between the factors of income differentiation and the average income of the population.