Assessment of interregional inequality in the Russian Federation based on the index of social well-being of the population

Bobkov V.N. Gubarev R.V. Dzyuba E.I. Fayzullin F.S.

Журнал: Economic and Social Changes: Facts, Trends, Forecast @volnc-esc-en

Рубрика: Regional economy

Статья в выпуске: 5 т.17, 2024 года.

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As part of this study, the goal was to develop adequate (high-precision) tools that would allow for not only a retrospective, but also a prospective assessment of interregional inequality in living standards in the Russian Federation based on the index of social well-being of the population, which is the result of a convolution of private indices. At first, a hypothesis was put forward about the possibility of building an adequate prognostic (traditional econometric) model of dependence of per capita average monetary incomes of the population on a group of factors. The information base of the study was exclusively official data of regional statistics for 2020-2022. In the course of empirical research (correlation and regression analysis), three econometric models differing in the number of factors (from 2 to 4) were developed. However, they allow (according to the average approximation error, taking values from the interval from 8.8 to 9.6 % for different econometric models) approximating regional statistics data only with an acceptable degree of accuracy. Next, a similar hypothesis was tested, but involving the use of a different tool (index method in combination with artificial intelligence), which makes it possible to measure the dependence of the population’s standard of living on a group of factors. In the course of neuromodelling it was found that any of the 5 artificial neural networks included in the Bayesian ensemble allowed approximating the regional statistics data with a high degree of accuracy (with an average error from 2.8 to 3.9 %). Thus, the second hypothesis can be considered confirmed. As part of the study, the predictive function was implemented by forming a Bayesian ensemble of artificial neural networks. The obtained results of the empirical study can act as a scientific basis for adjusting (updating) the socio-economic policy of regulating the quality and standard of living of the population and its interregional inequality among the constituent entities of the Russian Federation.

regions of Russia \ interregional inequality \ standard of living \ cash income \ index method \ correlation-regression analysis \ artificial intelligence \ forecasting

Короткий адрес: https://sciup.org/147245884

IDS: 147245884   |   УДК: 332.14   |   DOI: 10.15838/esc.2024.5.95.3

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