Demographic Agent-based Model of the Luhansk People's Republic

A comprehensive study of the demographic situation of the Luhansk People's Republic (LNR) has been conducted, examining the specific causes of depopulation characteristic of many countries of the world and individual subjects of the Russian Federation. The key birth rates of the LPR are analyzed, and the preliminary root causes of the difficult demographic situation are described. Statistical calculations that characterize the current situation in the period from 2014 to 2022 are presented. An agent-based simulation model has been developed and tested to predict the population of the LPR in the current demographic crisis, burdened by the consequences of the military conflict. The presented model is implemented in the AnyLogic environment and can reproduce key demographic processes: fertility, mortality, aging and migration. The official statistical indicators of the LPR for the period 2014-2022 were used as the initial data. Three scenario experiments (basic, negative, and positive) were conducted, predicting demographic dynamics until 2027. The calculation results showed that if current trends continue (baseline scenario), the population of the LPR will decrease to 1,226 million people. A negative scenario (escalation of the conflict) will lead to a more serious drop to 1.214 million people. A positive scenario (the end of the SMO, the return of migrants, and an improvement in fertility and mortality rates) demonstrates the potential to stabilize the situation at the level of 1.329 million people. The practical significance of the research lies in the fact that the developed model is an effective tool for analyzing and forecasting demographic processes, which is the basis for developing targeted management decisions aimed at stabilizing the socio-economic situation in the region.

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Publication Details

Journal
Artificial Societies
Published
2026-01-01
DOI
https://doi.org/10.18254/s207751800038019-9
Primary Topic
Insurance, Mortality, Demography, Risk Management
Type
article
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article

Demographic Agent-based Model of the Luhansk People's Republic

Dmitry Evdokimov
Artificial Societies
Insurance, Mortality, Demography, Risk Management
article

Demographic Agent-based Model of the Luhansk People's Republic

Dmitry Evdokimov
article en

Abstract

A comprehensive study of the demographic situation of the Luhansk People's Republic (LNR) has been conducted, examining the specific causes of depopulation characteristic of many countries of the world and individual subjects of the Russian Federation. The key birth rates of the LPR are analyzed, and the preliminary root causes of the difficult demographic situation are described. Statistical calculations that characterize the current situation in the period from 2014 to 2022 are presented. An agent-based simulation model has been developed and tested to predict the population of the LPR in the current demographic crisis, burdened by the consequences of the military conflict. The presented model is implemented in the AnyLogic environment and can reproduce key demographic processes: fertility, mortality, aging and migration. The official statistical indicators of the LPR for the period 2014-2022 were used as the initial data. Three scenario experiments (basic, negative, and positive) were conducted, predicting demographic dynamics until 2027. The calculation results showed that if current trends continue (baseline scenario), the population of the LPR will decrease to 1,226 million people. A negative scenario (escalation of the conflict) will lead to a more serious drop to 1.214 million people. A positive scenario (the end of the SMO, the return of migrants, and an improvement in fertility and mortality rates) demonstrates the potential to stabilize the situation at the level of 1.329 million people. The practical significance of the research lies in the fact that the developed model is an effective tool for analyzing and forecasting demographic processes, which is the basis for developing targeted management decisions aimed at stabilizing the socio-economic situation in the region.

Artificial SocietiesVol. 21(1)
Central Economics and Mathematics Institute (RU)
Good health and well-being
Openalex Percentile: Top 18%
Insurance, Mortality, Demography, Risk Management
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