Demography and social economy

MODELING OF PENSION PAYMENT DYNAMICS: FACTORS, TRENDS, FORECASTS

Inna Dvornyk — 2026-03-24

The article analyzes the dynamics of the average pension size in Ukraine during 2004—2025. The relevance of the study lies in the identification of the transformation of the country’s economic growth into an increase in the welfare of pensioners. The forecast of the average pension size for 2026 was performed using the methods of correlation modeling, moving average, and exponential smoothing. It was found that all methods demonstrate different dynamics of pension growth; the most optimal and realistic can be considered the forecast obtained using the exponential smoothing method, since it best takes into account the trends of recent years and possible changes in growth rates. The forecast using the regression polynomial model of degree 5 should be considered optimistic.

Using correlation-regression analysis, the strength and direction of the relationship between the size of pensions and macroeconomic indicators: gross domestic product per capita, average wage. It was determined that there is a pronounced positive statistical relationship between them, which gives grounds to indicate the dependence of the size of pension payments on the economic capacity of the state. The results of modeling indicate that pension payments have shown a steady upward trend. However, an increase in the nominal size of pensions is not always accompanied by an equivalent increase in their real value, which confirms the impact of inflation. The mechanism of interaction between the pension size and macroeconomic indicators is highlighted: gross domestic product affects pension payments through employment, wage levels, receipts to the Pension Fund, and the state’s budgetary capabilities. At the same time, this relationship is not completely linear, but depends on the demographic structure, shadow economy, pension system, and inflationary processes. Economically sound solutions in the field of the pension system of Ukraine are proposed — indexation of pensions, strengthening the connection of pension payments with labor income, strengthening the financial base of the Pension Fund, taking into account inflation risks in pension forecasting, differentiation of the pension system, and integration with macroeconomic policy.

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POST-WAR ECONOMIC RECONSTRUCTION OF TERRITORIAL COMMUNITIES BASED ON INCLUSION

Halyna Kraievska — 2026-03-24

The article is devoted to the issue of rebuilding the local communities’ economy, taking into account existing and post-war challenges. The relevance of the work is determined by the need to study the inclusive principles of rebuilding local communities, aiming to take into account the needs of all population groups and involving citizens in economic processes, which increases overall stability and contributes to more effective recovery. The purpose of the publication is to substantiate the theoretical and methodological foundations and practical recommendations for ensuring the inclusive recovery of the economy of territorial communities in the context of Ukraine’s post-war reconstruction. The study uses general scientific methods of comparative analysis, a systematic approach, generalization, and induction, as well as specialized economic methods: grouping and statistical analysis.

The novelty lies in considering inclusion not only as a social component, but also as a fundamental economic prerequisite for the post-war recovery of territorial communities. Key approaches to defining inclusive development are considered. The feasibility of choosing the approach that is most relevant for post-war recovery is justified. The understanding of inclusiveness is deepened not only as a principle of creating conditions for physical accessibility or involving socially vulnerable groups in the economic processes of communities, but also as a unification of the capabilities of various participants in its development, which allows for maximum effectiveness of recovery. The inclusive principles of post-war economic recovery of territorial communities are substantiated, covering the principles, components of an inclusive environment, and vectors for ensuring inclusive recovery. The peculiarities of the multidimensional impact of social inclusion on the economic development of territorial communities have been identified. The main factors of the expediency of rebuilding the territorial communities’ economy based on inclusion have been revealed. Two main groups of stakeholders in rebuilding the economy of territorial communities based on inclusiveness have been identified: vulnerable and resilient. Their quantitative characteristics have been analyzed. It has been proven that modern inclusive development policy requires comprehensive measures aimed at combining the strengths of different participants, which allows for maximum effectiveness of recovery.

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NATURAL RESOURCE DOMINANTS OF THE RESILIENCE OF THE QUALITY OF LIFE OF THE POPULATION OF UKRAINE: A REGIONAL DIMENSION OF STRUCTURAL CHANGES

Мykhailo Khvesyk — 2026-03-24

Ensuring the resilience of the population’s quality of life in Ukraine under conditions of fullscale military aggression has acquired critical significance, as the destruction of critical infrastructure facilities, enterprise relocation, and massive internal population displacement have caused unprecedented structural changes in the territorial distribution of anthropogenic environmental pressure. The identification of natural resource dominants that determine the environmental component of resilience becomes a prerequisite for scientifically grounded planning of post-war reconstruction. The research aim is to develop methodological foundations and methodological tools for assessing the environmental conflict intensity of Ukrainian regions as a key characteristic of population quality of life resilience, as well as to identify natural resource dominants that determine the nature of structural environmental changes. The scientific novelty lies in substantiating a conceptual approach to understanding environmental conflict intensity as a dynamic characteristic of spatial formations and developing a methodology for calculating an integral index based on a system of five normalized indicators characterizing natural resource dominants of anthropogenic pressure. A complex of methods was applied to achieve the aim: systems approach, abstract-logical analysis, indicator normalization, and the equal interval method for regional grouping. Analysis of the regional dimension of structural changes has demonstrated a radical transformation of the territorial configuration of anthropogenic pressure, manifested in the geographical shift of environmental conflict intensity centers from the east and south to central regions. Four key dominants of structural environmental changes have been identified: the transformational impact of war, spatially polarized industrial pressure, intensive agricultural land exploitation, and institutional inefficiency, particularly in the sphere of waste management. Key patterns of territorial redistribution of anthropogenic pressure have been identified, and directions for further research on population quality of life resilience in the context of post-war reconstruction have been determined.

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[Пирожков, С. І., Божок, Є. В., & Хамітов, Н. В. (2021). Національна стійкість (резилієнтність) країни: стратегія і тактика випередження гібридних загроз. Вісник Національної академії наук України, 8, 74—82].

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16. Khvesyk, M., Bystryakov, I., Levkovska, L., & Mandzyk, V. (2024). Institutional support of ecological sustainability. Demography and Social Economy, 3 (57), 141—158. https://doi.org/10.15407/dse2024.03.141

[Хвесик, М., Бистряков, І., Левковська, Л., & Мандзик, В. (2024). Інституційна підтримка екологічної стійкості. Демографія та соціальна економіка, 3 (57), 141—158].

THE ECONOMICS OF EDUCATION AND NEUROPLASTICITY: HOW SCHOOL SHAPES THE RESILIENCE AND PRODUCTIVITY OF FUTURE GENERATIONS

Olena Palchuk — 2026-03-24

The article aims to provide an interdisciplinary rationale for trauma-informed education as a mechanism for building resilient human capital in the context of war and post-war recovery in Ukraine. The study draws on a theoretical and analytical review of contemporary research in neuroscience, economics of education, and trauma psychology, combined with systems thinking and structured logical analysis, to trace causal links between psycho-emotional safety, students’ cognitive functioning, educational outcomes, and long-term labour productivity. The scientific novelty of the study lies in conceptualising neuroplasticity as an economically significant factor that determines a child’s capacity to restore cognitive resources, improve educational outcomes, and subsequently develop higher labour productivity and adaptability in the labour market. The findings demonstrate that chronic stress and traumatic experiences undermine learning capacity through impairments in emotional regulation, attention and executive functioning, which in turn lead to lower educational attainment and reduced economic productivity in adulthood. The article argues that trauma-informed education, when embedded in pedagogical practices, school governance, and student support systems, helps create safe and neuroplastically favourable learning environments. Such environments foster self-regulation, critical thinking, emotional intelligence, and collaboration skills — competencies that are increasingly essential in a knowledge-based economy and a rapidly transforming labour market. The paper concludes that investment in trauma-informed education and children’s psycho-emotional recovery programmes should be treated as a macroeconomic priority, as it reduces long-term GDP losses associated with unrealised skills and strengthens the foundations of a resilient and innovation-driven economy.

REFERENCES / ЛІТЕРАТУРА

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7. Hirschmann, R., Blumenberg, C., Soares, P. S. M., Menezes, A. M. B., Wehrmeister, F. C., & Gonçalves, H. (2024). Relation between child maltreatment and human capital: Results from a population-based birth cohort. Cadernos de Saúde Pública, 40 (7), e00173623. https://doi.org/10.1590/0102-311XEN173623

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10. Safonov, Y., & Flіarkovska O. (2023). Ukrainian Education in the War and Post-War Periods: Psychological Factors and Economic Consequences. Problems of Education, 1 (98), 6—22. https://doi.org/10.52256/2710-3986.1-98.2023.01

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20. Hirschmann, R., Blumenberg, C., Soares, P. S. M., Menezes, A. M. B., Wehrmeister, F. C., & Gonçalves, H. (2024). Relation between child maltreatment and human capital: Results from a population-based birth cohort. Cadernos de Saúde Pública, 40 (7), e00173623.https://doi.org/10.1590/0102-311XEN173623

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22. Dorado, J. S., Martinez, M., McArthur, L. E., & Leibovitz, T. (2016). Healthy Environments and Response to Trauma in Schools (HEARTS): A whole-school, multi-level, prevention and intervention program for creating trauma-informed, safe and supportive schools. School Mental Health, 8 (1), 163—176. https://doi.org/10.1007/s12310-016-9177-0

ARTIFICIAL INTELLIGENCE, INSTITUTIONAL VULNERABILITY, AND DEMOGRAPHIC RISKS IN UKRAINE

Michael Zgurovsky — 2026-03-24

The article examines the impact of artificial intelligence (AI) development on socio-economic and demographic processes under conditions of digital transformation and growing global competition for human capital. It is shown that the diffusion of AI is associated not only with productivity gains but also with increasing social risks, including structural changes in labour markets and the intensification of selective migration of the working-age population. The aim of the article is to assess the impact of AI development on socio-economic and demographic processes and to substantiate the potential of AI-based tools for monitoring, modelling, and early detection of demographic risks in the context of institutional vulnerability and migration dynamics in Ukraine during 1991—2025.

Special attention is paid to demographic dynamics in Ukraine during 1991—2025 in the context of state institutional vulnerability. Using the Fragile States Index (FSI), with a focus on the indicator of human flight and brain drain (E3), the study applies an AI-oriented analytical framework to explore the relationship between institutional conditions and migration processes. The novelty of the study lies in conceptualizing artificial intelligence not only as a driver of technological change but also as an analytical instrument for formalizing and quantifying the relationship between demographic processes and institutional vulnerability, including the empirical validation of a statistically significant link between rising fragility and migration outflows. The results indicate a non-linear and cumulative pattern of migration outflows, which intensifies sharply once critical levels of institutional vulnerability are reached. The research employs an AI-oriented analytical framework that combines classical econometric modelling, time-series analysis, correlation-regression techniques, and machine learning methods to detect non-linear effects, threshold dynamics, structural breaks, and lagged interactions in demographic trends. The article substantiates the relevance of artificial intelligence as a tool for monitoring and early warning of demographic risks and for supporting preventive demographic and socio-economic policy in periods of profound institutional and technological transformation.

REFERENCES / ЛІТЕРАТУРА

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5. Zgurovsky, M. Z. (2025). Global Trends in Artificial Intelligence. Challenges, Opportunities, and Prospects. Cybernetics and Systems Analysis, 61, 533—553. https://doi.org/10.1007/s10559-025-00790-y

6. McKinsey Global Institute (2023). The economic potential of generative AI: The next productivity frontier. https://www.mckinsey.com/capabilities/tech-and-ai/our-insights/the-economic-potential-of-generative-ai-the-next-productivity-frontier

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8. World Economic Forum (2025). The Future of Jobs Report 2025. Geneva. https://www.weforum.org/publications/the-future-of-jobs-report-2025/

9. Libanova, E. M. (2025). Demographic Losses of Ukraine in the War. Svitohliad, 2, 34—40. https://www.mao.kiev.ua/biblio/jscans/svitogliad/svit-2025-20-2/svitoglyad-2-2025-libanova06.pdf

[Лібанова, Е. М. (2025). Демографічні втрати України у війні. Світогляд, 2, 34—40].

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[Оцінки чисельності населення України на підконтрольних територіях на початок 2025 року (експертна оцінка) (2025). За матеріалами Ukrainian National News (UNN). Інститут демографії та соціальних досліджень імені М. В. Птухи НАН України].

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DEMOGRAPHIC AND LABOR ATROPHY: FACTORS AND FEATURES OF DEVELOPMENT IN CONDITIONS OF POLYCRISIS

Viktoriіa Mykytenko — 2026-03-24

Under conditions of a polycrisis, demographic losses, the destruction of local labor markets, migration waves, and the deformation of motivational and behavioral patterns give rise to demographic and labour atrophy, which transcends conventional socio-demographic issues and emerges as a security risk to the resistance of socio-economic systems. The purpose of this study is to substantiate the nature, drivers, and specific features of the unfolding of demographic and labour atrophy in a polycrisis environment and to develop an integrated analytical framework for assessing its impact on territorial resistance. The study advances conceptual and methodological approaches by conceptualizing demographic and labour atrophy as a multidimensional atrophic syndrome of human potential depletion; identifying its key demographic, labour, behavioral-cognitive, institutional, spatial, and medico-genetic drivers; and establishing a cause-and-effect relationship between the depth of atrophic processes, the level of socio-economic system resistance, and spatial development constraints. An integrated analytical framework is proposed to assess vulnerability and resistance across macro-regional zones. The research applies interdisciplinary and spatial-structural approaches, including systems-structural, causal, conceptual-theoretical, spatial, and comparative analyses, as well as methods of generalization and interpretation.

Demographic and labour atrophy is identified as a self-reinforcing and spatially diffusive process that generates degradation cycles, reduces adaptive capacity, and constrains spatial recovery. The role of learned helplessness syndrome and medico-genetic factors in shaping the intergenerational inertia of demographic and labuor losses is substantiated. The proposed analytical framework enables the identification of critical risks and the differentiation of policy and managerial responses to spatial recovery. The findings provide a methodological basis for strengthening human potential policies, enhancing socio-economic system resistance, and reducing spatial disparities in Ukraine.

REFERENCES / ЛІТЕРАТУРА

1. Libanova, E., & Kotyhorenko, V. (2025). Building a sustainable economy in Ukraine: unlocking the potential of the management system. Science and Innovation, 21 (3), 3—15. https://doi.org/10.15407/scine21.03.003

[Лібанова, Е., & Котигоренко, В. (2025). Побудова стійкої економіки в Україні: розкриття потенціалу системи управління. Наука та інновації , 21 (3), 3—15].

2. Libanova, E. M. (2025). Demographic losses of Ukraine in the war. Svitoglyad, 2 (112), 34—42. https://www.nas.gov.ua/storage/editor/files/svitoglyad-2-2025.pdf

[Лібанова, Е. М. (2025). Демографічні втрати України у війні. Світогляд, 2 (112), 34—42].

3. Libanova, E. M., Khvesyk, M. A., Hutorov, A. O., Gutorov, O. I., & Yermolenko O. A. (2025). Synergistic approach to the resilience management of socio-ecological and economic development of Ukraine. Scientific Bulletin of the National Mining University, 3, 192—200. https://doi.org/10.33271/nvngu/2025-3/192

4. Libanova, E. M. (Ed.). (2025). Tools for ensuring the resilience of Ukrainian society. Kharkiv: FOP Liburkina L. M. https://surl.li/leyjcs

[Лібанова, Е. М. (Ред.). (2025). Інструменти забезпечення резильєнтності українського суспільства. Харків: ФОП Лібуркіна Л. М.].

5. Libanova, E. M. (Ed.). (2025). Institutional support for the resilience of the Ukrainian economy. Kharkiv: FOP Liburkina L. M. https://surl.li/ceadjj

[Лібанова, Е. М. (Ред.). (2025). Інституційне забезпечення резильєнтності економіки України. Харків: ФОП Лібуркіна Л.М.]

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7. Kalashnikova & T. M., Sheludko, N. M., & Gerasimenko, I. V. (2025). Resilience of the quality of life of the population: the role of social protection. Ukrainian Society, 3 (94), 73—85. https://doi.org/10.15407/socium2025.03.0733

[Калашнікова, Т. М., Шелудько, Н. М., & Герасименко, І. В. (2025). Резилієнтність якості життя населення: роль соціального захисту. Український соціум, 3 (94), 73—85].

8. Libanova, E. M., & Bystryakov, I. K. (2025). Postwar Ukraine: Innovative Organization of Spatial Development. Demography and Social Economy, 60 (2), 32—51. https://doi.org/10.15407/dse2025.02.032

[Лібанова, Е. М., & Бистряков, І. К. (2025). Україна повоєнного періоду: інноваційна організація просторового розвитку. Демографія та соціальна економіка, 60 (2), 32—51].

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10. Kyzym, M. O., Khaustova, V. E., Reshetnyak, O. I., & Yudenko, E. V. (2025). Analysis of the resilience of the economies of Ukraine and the world in 2007—2023. Business Inform, 7, 51—64. https://doi.org/10.32983/2222-4459-2025-7-51-64

[Кизим, М. О., Хаустова, В. Є., Решетняк, О. І., & Юденко, Є. В. (2025). Аналіз резильєнтності економік України та країн світу у 2007—2023 роках. Бізнес Інформ, 7, 51—64].

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[Микитенко, В. В., & Шелудько, Н. М. (2025). Реабілітація монофункціональних територій на основі моделі когнітивно-просторового відновлення. Український соціум, 2 (93), 158 —173].

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[Микитенко, В. В., & Микитенко, Д. О. (2025). Гібридна реабілітація монофункціональних територій: індустріально-когнітивні та медико-соціальні виклики в парадигмі ЄС —Україна. У: ЄС — Україна: діалог промислових політик в парадигмі сталого розвитку: колективна монографія (В. Омельяненко, Ред.), 83—106. Київ: ІЕП НАН України].

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INFORMATION SUPPORT FOR SOCIO-ECONOMIC POLICY IN UKRAINE: FROM FRAGMENTED DATA TO EVIDENCE-BASED DECISIONS IN THE CONTEXT OF EUROPEAN APPROACHES

Volodymyr Sarioglo — 2026-03-24

The article examines the challenges of information support for Ukraine’s socio-economic policy in the context of moving from fragmented and untimely data toward an integrated information field capable of enabling evidence-based and data-driven governance across policy design, implementation, monitoring, and evaluation. It is shown that during 2014— 2021, gaps in statistical and administrative data (lack of censuses, limited capacity to conduct international surveys, underdeveloped administrative registry systems, lack of comprehensive statistics on IDPs) have led to poor data quality and institutional fragmentation of data. Following Russia’s full-scale invasion, the situation further deteriorated due to the suspension or substantial limitation of multiple official statistical operations, increasing reliance on alternative sources that are often partial and unevenly verifiable. As a consequence, strategic documents and public programmes face heightened risks of setting goals and target indicators on an insufficiently robust empirical basis.

The purpose of the article is the identification of the EU regulatory and peculiarities of legal regulation regarding the main aspects of data collection, processing, storage, and use, and to justify the main directions for the formation of modern information support (information field) for socio-economic policy in Ukraine. The main research methods are general scientific methods of analysis and synthesis, induction and deduction, as well as special methods of comparative analysis and institutional analysis. The novelty of the article lies in the fact that, based on research and assessment of the experience of developed countries, primarily EU countries, the authors have identified the main features of a new paradigm for the formation of an information space for the development, implementation, monitoring, and evaluation of socio-economic policy. The main challenges and priorities for the development of the information space for the formation of socio-economic policy and the adoption of informed management decisions in Ukraine have been identified.

The theoretical and methodological part synthesises European approaches to building a “data space” for governance, science and the economy, emphasising interoperability, re-use, confidentiality, accountability, and responsible application of advanced analytics and algorithmic tools, including in the context of expanding AI use. The paper discusses the core EU regulatory landmarks shaping data governance (GDPR, the Open Data Directive, the Data Governance Act, and the Data Act) and their role in structuring responsibilities and boundaries for key actors in the data ecosystem.

The article substantiates the need for a multi-level integrated model of information support for governance in Ukraine, including harmonisation procedures, data-quality assurance mechanisms, and institutional arrangements such as trusted data intermediaries. It proposes a set of objectives and directions for developing a resilient national data environment as a prerequisite for higher-quality policy decisions and closer alignment with the European data and statistical acquis.

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NON-GOVERNMENTAL SAMPLE SURVEYS OF THE POPULATION IN THE SOCIAL SPHERE: INTERNATIONAL EXPERIENCE AND OPPORTUNITIES FOR UKRAINE

Yurii Kohatko — 2026-03-24

The purpose of the article is to examine international experience in the use of non-official household panel surveys in countries that have experienced large-scale socio-economic shocks (wars, crises, mass migration and displacement), intending to substantiate the feasibility and appropriateness of applying similar approaches in Ukraine to fill the gap in microdata on labour supply, household responses to shocks, and policy modelling for the reintegration of internally displaced persons (IDPs) and veterans under conditions of a longterm absence of official statistics.

The full-scale war in Ukraine since 2022 has led to the complete suspension of the official sample surveys, resulting in the emergence of a “blind zone” in representative microdata on the labour market and the quality of life of households. The article analyses panel studies such as the Syrians Barometer in Turkey, JHPS/KHPS in Japan, ELSOC in Chile, and HAALSA in South Africa. All projects share a panel design, a focus on vulnerable population groups, detailed modules on quality of life, health, and responses to shocks, as well as open access to microdata. The paper proposes adapting these templates for Ukraine through regional stratification (frontline, western, and central regions), dedicated modules for IDPs and veterans, inclusion of asset losses, return intentions, and the assessment of household resilience. It is shown that an independent Ukrainian panel survey is critically important for microsimulation modelling of reintegration policies, forecasting the impacts of housing programmes, veterans’ employment programmes, pension system needs, and post-war recovery as an issue of national economic security. The methodology includes general scientific methods (analysis, synthesis, comparison, and a systems approach) and specialised methods (content analysis of reports, publications, and questionnaires; logical-structural analysis for adaptation; and the method of analogies for transferring solutions). The information base consists of reports and publications of the reviewed projects, as well as materials of the State Statistics Service of Ukraine related to the Survey of living conditions of households, the Labor force survey, the Survey of Agricultural activity of the population in rural areas, and the Representative Survey of the socio-economic situation of households. The results are relevant for employment policy development, the reintegration of IDPs and veterans, and forecasting the labour market effects of large-scale shocks. The scientific novelty lies in a systematic comparison of methodological solutions used in international panel projects from the perspective of their adaptation to the Ukrainian context and in the development of a ready-made template for a Ukrainian household panel survey. Future research perspectives include the design of a Ukrainian panel survey, harmonisation with international standards, the creation of an open microdata base, and the testing of microsimulation models to assess policy impacts on the labour supply of vulnerable groups in the post-war period.

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