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June 5, 2026
Neural Network Maps as a Method for Constructing Mathematical Models
Scientists from HSE University–Nizhny Novgorod and the Institute of Physics Belgrade, Serbia, are jointly exploring the application of machine learning techniques and neural networks to the study of nonlinear dynamics. Natalya Stankevich, Leading Research Fellow at the Laboratory of Topological Methods in Dynamics of the Faculty of Informatics, Mathematics, and Computer Science at HSE University–Nizhny Novgorod, spoke to the HSE News Service about this international project.
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Periods of high uncertainty: How fertility intentions in Russia changed during 2022–2023

Demographic Research. 2025. Vol. 52. P. 939–970.
Vakulenko E., Gorskiy D., Kondrateva V., Trofimenko I.

BACKGROUND

We study fertility intentions change in Russia, during the period of socio-economic shocks in 2022-2023, in response to the Russia-Ukraine armed conflict.

OBJECTIVE

Our objective is to identify factors that influence decision-making in a low fertility context during the crisis, including both objective characteristics and subjective assessment of the current situation.

METHODS

This paper is based on unique survey results, conducted in May 2023 (N=7,967). The sample includes Russian citizens aged 18-44 and represents Russia’s population by gender, age, and place of residence. The analysis is based on binary choice models (probit) and machine learning techniques (Honest trees), which was applied for assessing the heterogeneity of the sample.

RESULTS

The most important factors, which accounted for 76 percent of the explained variance, were linked to a subjective assessment of the situation and the respondent’s emotional state: the attitude to the political course of the country, feelings of happiness, anxiety, or fear. Traditional objective characteristics such as the age of respondents, marital status, and parenthood status play a less important role. We also found that women's fertility decisions are more associated with positive emotions such as happiness and peacefulness in comparison to men. We observe that subjective factors related to politics, conflict and emotions amplify each other's effects.

CONCLUSIONS

We indicate that in times of uncertainty, trust in state policy plays an important role in smoothing the population’s reaction to the shocks.

CONTRIBUTION

We provide a novel quantitative investigation into the role of subjective perceptions in shaping reproductive intentions during a period of high uncertainty in a low fertility rate country through econometric and ML tools, expand the group of factors which measure subjective perceptions including different emotions, attitudes to the country’s political course and government maternity capital programs, and show how they accelerate each other.

Research target: Economics and Management Sociology (including Demography and Anthropology
Language: English
Full text
DOI
Keywords: машинное обучениеRussiaопросmachine learningрепродуктивные намерениясубъективные оценкиreproductive intentionsSubjective perceptions Россияsocio-economic shockssample surveyсоциально-экономические шокиnarratives of the futureнарративы будущего
Publication based on the results of:
Life Choices: Factors and Mechanisms for Making Key Decisions at Different Life Stages (2024)
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