Bayesian Modeling of Regional Economic Systems in Conditions of Uncertainty: Spatial and Temporal Structure Taking into Account the Distribution

Roman A. Zhukov, Artem D. Prachev

Financial University under the Government of the Russian Federation, Moscow, Russia

Abstract

An urgent aspect of studying the state and functioning of regional economic systems – the subjects of the Russian Federation – is to take into account the conditions of uncertainty, which makes it possible to strengthen the validity of the estimates and conclusions obtained, including using probabilistic approaches – Bayesian intelligent technologies – with the identification of types of distribution of performance characteristics. This allows us to partially understand the nature of the phenomena and the causes of the observed behavior of the structural elements of the system within the framework of the accepted classification. The purpose of the study is to model the functioning of regional economic systems in conditions of uncertainty, taking into account the types of distribution of gross domestic product by region that characterize the economy of regions within the framework of spatial and temporal classification. The working hypothesis of the study is the possibility of methodologically sound modeling of the functioning of the regional economy with the identification of types of distribution according to data for a specific subject of the Russian Federation on the basis of Bayesian intelligent technologies. The research procedure includes the formation of an empirical base; identification of the type of distribution with the elimination of the influence of trend on the results of such identification; building a framework of a hierarchical information model with its filling with probabilistic estimates of the effective features characterizing the functioning of regional economic systems, taking into account and without taking into account the type of distribution. Based on the example of 17 subjects of the Russian Federation of the Central Federal District, according to data for 2017-2023, the modeling of the functioning of the regional economy was carried out on the basis of performance indicators – the volume of gross domestic product by region – for 19 types of economic activity within the framework of the spatial and temporal classification. This made it possible to test the methodology with an assessment and analysis of the differences between the results with normal and abnormal (by type of distribution) representations. The theoretical significance of the study is to expand the methodology of Bayesian intelligent technologies by including a stage of identification of the type of distribution of indicators. The practical significance of the study lies in the possibility of taking into account the type of distribution of indicators when evaluating the results of the functioning of structural elements of regional economic systems, which enhances the validity of such estimates.

Keywords

gross domestic product by region; type of distribution; socio-ecological-economic system; model; Bayesian intellectual technologies; probabilistic estimation.

JEL classification

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Acknowledgements

The article was prepared based on the results of research carried out at the expense of budgetary funds on the state assignment of the Financial University.

About Authors

Roman Aleksandrovich Zhukov

Doctor of Economics, Associate Professor, Leading Researcher, Institute of Digital Technologies, Financial University under the Government of the Russian Federation, Moscow, Russia (125167, Moscow, Leningradsky prospekt, 49/2); ORCID https://orcid.org/0000-0002-2280-307X e-mail: pluszh@mail.ru

Artem Denisovich Prachev

Intern Researcher, Institute of Digital Technologies, Financial University under the Government of the Russian Federation, Moscow, Russia (125167, Moscow, Leningradsky prospekt, 49/2); ORCID https://orcid.org/0009-0007-8103-370X e-mail: 242104@edu.fa.ru

For citation

Zhukov, R.A., Prachev, A.D. (2026). Bayesian Modeling of Regional Economic Systems in Conditions of Uncertainty: Spatial and Temporal Structure Taking into Account the Distribution. Journal of Applied Economic Research, Vol. 25, No. 3, 911-939. https://doi.org/10.15826/vestnik.2026.25.3.030

Article info

Received March 24, 2026; Revised May 26, 2026; Accepted May 28, 2026.

DOI: http://dx.doi.org/10.15826/vestnik.2026.25.3.030

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