Managing the reproduction potential of the population of Russian regions based on machine learning models
Research Article
Acknowledgments
The study was supported by the Russian Foundation for Basic Research, project No. 20-010-00307.
How to Cite
Sukiasyan A.G. Managing the reproduction potential of the population of Russian regions based on machine learning models. Population. 2022. Vol. 25. No. 4. P. 16-29. DOI: https://doi.org/10.19181/population.2022.25.4.2 (in Russ.).
Abstract
The article is devoted to study of the patterns of development of potential for the reproduction of the population of Russian regions, considering the socio-economic situation in them. The purpose of the work is to identify the factors of socio-economic development of Russian regions that have the greatest impact on the level of population reproduction and to analyze the sensitivity of this characteristic to changes in the state of socio-economic situation in Russian regions. To achieve this goal, the key characteristics of the population reproduction potential were analyzed the marginal rate of population reproduction and standardized birth rates for five-year age groups of mothers for the period from 1990 to 2020.The results presented in the article were obtained in the course of studying the dynamics of population reproduction and interdependencies with the main socio-economic indicators of the regions, assessed by the methods of correlation analysis and machine learning, on the results of testing of which the most informative factors were identified that have a significant impact on the process of reproduction of the country and its regions with the account of the age structure of mothers. In particular, it was found that with an increase in the age of mother, the influence of factors characterizing economic well-being increases when deciding to have a child, while in younger age groups the indicators of social well-being become more important. On the basis of these models, estimates of the sensitivity of indicators of population reproduction and birth rates in each of the studied age groups of mothers were obtained in case of changes in the socio-economic factors. Based on the analysis, there were drawn conclusions about the impact of the socio-economic situation in the country and regions on the birth rates in different age groups of mothers, as well as on the reproductive potential in general.
Keywords:
age-specific fertility, expanded population reproduction, depopulation, marginal reproduction rate, machine learning models
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14. Arkhangelsky V. N. Issledovanije problem rozhdaemosti [The study of fertility issues]. Uroven' zhizni naselenija regionov Rossii [Living Standards of the Population in the Regions of Russia]. 2008. No. 3-4(121-122). P. 80-93. (in Russ.)
15. Minchenko M. M., Nozdrina N. N. Dinamika dostupnosti zhil'ja dlja naselenija Rossii v 2008¬2014 gg. [Dynamics of housing affordability for the population of Russia in 2008-2014] Problemy prognozirovanija [Studies on Russian Economic Development]. 2017. No. 2(161). P. 89-105. (in Russ.)
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Article
Received: 06.07.2022
Accepted: 09.12.2022
Citation Formats
Other cite formats:
APA
Sukiasyan, A. G. (2022). Managing the reproduction potential of the population of Russian regions based on machine learning models. Population, 25(4), 16-29. https://doi.org/10.19181/population.2022.25.4.2
Section
DEMOGRAPHY: THEORY AND PRACTICE ISSUES
