Poverty under the influence of COVID-19 and the full-scale war in Ukraine: retrospective microsimulation and forecasting
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- Category: Content №1 2026
- Last Updated on 27 February 2026
- Published on 30 November -0001
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Authors:
E. M. Libanova*, orcid.org/0000-0001-7170-7159, Mykhailo Ptoukha Institute for Demography and Life Quality Research of the National Academy of Sciences of Ukraine, Kyiv, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
L. M. Cherenko, orcid.org/0000-0003-1606-6170, Mykhailo Ptoukha Institute for Demography and Life Quality Research of the National Academy of Sciences of Ukraine, Kyiv, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
V. S. Shyshkin, orcid.org/0000-0003-0011-4246, Mykhailo Ptoukha Institute for Demography and Life Quality Research of the National Academy of Sciences of Ukraine, Kyiv, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
Y. A. Klymenko, orcid.org/0000-0002-0086-2933, Mykhailo Ptoukha Institute for Demography and Life Quality Research of the National Academy of Sciences of Ukraine, Kyiv, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
* Corresponding author e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu. 2026, (1): 166 - 174
https://doi.org/10.33271/nvngu/2026-1/166
Abstract:
Purpose. To implement microsimulation of hypothetical scenarios without catastrophic phenomena in order to assess how rapid and long-lasting the impact of disasters of various nature on poverty could be, as well as to produce a hypothetical and realistic forecasts to understand the specifics of the crisis processes in the context of their impact on poverty and assess the prospects for restoring positive trend.
Methodology. The method of microsimulation is the best approach to study the impact of the COVID-19 pandemic and the full-scale war on poverty in Ukraine. This method is effective for situations where statistical or econometric models cannot be used, but there is enough information about the conditions of the processes that have directly affected, are affecting or are expected to affect the phenomenon or object we are studying. The constructed algorithm is easily programmable, which allows making additional adjustments to the simulated input indicators and obtaining more reasonable results.
Findings. According to the estimates based on microsimulation using data of 2016‒2021 Sample Survey of Living Conditions of Households and the 2023 Household Socio-Economic Status Survey, the pandemic has led to an increase in the number of poor people by 1.8 million. However, it was not catastrophic, as the positive trend was not disrupted. The war caused an increase of poor people by 6.1 million, reaching a total of 13.5 million people. This has reversed the gains in poverty reduction and set us back decades. According to the microsimulation results, in the absence of war, Ukraine could recover from the pandemic quite quickly, even reducing poverty to minimal rates within five years. The realistic forecast scenario is based on actual data for 2023 and assumes economic recovery starting in 2025. Under this scenario, the poverty rate is expected to reach 20.1 % in 2027, which is lower than in 2019.
Originality. The paper determines the depth of the impact of disastrous events (COVID-19 pandemic and full-scale war) on the Ukrainian population, in particular in terms of poverty growth. On this basis, the losses from disasters over the last half decade were estimated due to the increase in the number of poor people that could have been avoided in the absence of these events, and in time terms due to the number of years we were thrown back on the path of overcoming poverty. In order to develop a policy to respond to the negative consequences of crises in the future, the importance of establishing a recovery period is assessed both from the standpoint of achieving pre-crisis values and in comparison with the results that could occur in a hypothetical scenario without catastrophic events.
Practical value. The proposed comprehensive approach to the analysis of the impact of the COVID-19 pandemic and the full-scale war on the poverty rate in Ukraine provides an opportunity to form a holistic methodological framework for assessing the scale of poverty under the influence of disasters of various nature.
Keywords: poverty, microsimulation, forecast, COVID-19, full-scale war
References.
1. Eurostat (2019‒2021). At-risk-of-poverty rate by poverty threshold. Retrieved from https://ec.europa.eu/eurostat/databrowser/view/ilc_li02/bookmark/table?lang=en&bookmarkId=b8408b76-942b-49ea-b259-1faad53cbf3d&c=1749745341114
2. Eurostat (2019‒2021). Persons at risk of poverty or social exclusion. Retrieved from https://ec.europa.eu/eurostat/databrowser/view/ilc_peps01n/default/table?lang=en
3. Eurostat (2019‒2021). Gini coefficient of equivalised disposable income. Retrieved from https://ec.europa.eu/eurostat/databrowser/view/ilc_di12/default/table?lang=en
4. Updated macro forecast: Cabinet of Ministers improves GDP growth forecast (2019). Retrieved from https://minfin.com.ua/2019/10/23/39477102
5. World bank (2020). Global Growth: Modest Pickup to 2.5 % in 2020 amid Mounting Debt and Slowing Productivity Growth. Retrieved from https://www.worldbank.org/en/news/press-release/2020/01/08/modest-pickup-in-2020-amid-mounting-debt-and-slowing-productivity-growth
6. (2019). IMF expects Ukraine’s GDP to grow in 2020 Interfax. Retrieved from https://interfax.com.ua/news/economic/618981.html
7. National Bank of Ukraine (2019). Inflation Report. Retrieved from https://bank.gov.ua/news/all/natsionalniy-bank-zberig-prognoz-inflyatsiyi-na-2019-2021-roki-i-polipshiv-otsinku-zrostannya-ekonomiki-7024
8. Cherenko, L., Poliakova, S., Shyshkin, V., Reut, A., Vasyliev, O., Kohatko, Yu., …, & Novosilska, T. (2020). The impact of the coronavirus crisis on poverty: first consequences for Ukraine. Institute for Demography and Life Quality Problems of the NAS of Ukraine. ISBN 978-966-02-9310-6.
9. Lancour, C. (n.d.). War and Poverty: Looking Back at the Balkans’ History. The Borgen magazine. Retrieved from https://www.borgenmagazine.com/war-and-poverty/
10. Laderchi, C., & Savastano, S. (2012). Overview: Poverty and Exclusion in the Western Balkans: New Directions in Policy and Analysis. Poverty and Exclusion in the Western Balkans, 1-11.
11. Sotiropoulos, D. (2014). The Social Effects of the Economic Crisis in the Western Balkans: A Case Study of Unreconstructed Welfare Regimes. Southeastern Europe, 250-266. https://doi.org/10.1163/18763332-03802004
12. Caukin, C. (n.d.). Facts about Poverty in the Balkans. The Borgen magazine. Retrieved from https://borgenproject.org/about-poverty-in-the-balkans/
13. Sutherland, H., & Figari, F. (2013). EUROMOD: the European Union tax-benefit microsimulation model. International Journal of Microsimulation, 6(1), 4-26.
14. Bronka, P., Collado, D., & Richiardi, M. (2020). The Covid-19 Crisis Response Helps the Poor: The Distributional and Budgetary Consequences of the UK lock-down, 32.
15. Cantó, O., Figari, F., & Fiorio, C.V. (2021). Welfare Resilience at the Onset of the COVID-19 Pandemic in a Selection of European Countries: Impact on Public Finance and Household Incomes. https://doi.org/10.1111/roiw.12530
16. Almeida, V., Barrios, S., & Christl, M. (2021). The impact of COVID-19 on households´ income in the EU. The Journal of Economic Inequality. https://doi.org/10.1007/s10888-021-09485-8
17. Eurostat (2020). Nowcasting income indicators during the pandemic. Methodological development. Retrieved from https://ec.europa.eu/eurostat/documents/7894008/8256843/Methodological-note-2020.pdf/9a70fb55-ceb7-d25a-1b31-ab0c030095d2?t=1625228771763
18. O’Donoghue, C., Sologon, D., Kyzyma, I., & McHale, J. (2021). A Microsimulation Analysis of the Distributional Impact over the Three Waves of the COVID-19 Crisis in Ireland. International Journal of Microsimulation, 14(2).
19. Lustig, N. (2021). The impact of COVID-19 on inequality and poverty in Mexico. Estudios Económicos De El Colegio De México, 36(1), 7-25. https://doi.org/10.24201/ee.v36i1.416
20. Moyer, J., Verhagen, W., Mapes, B., Bohl, D., Xiong, Y., Yang, V., …, & Hughes, B. (2022). How many people is the COVID-19 pandemic pushing into poverty? A long-term forecast to 2050 with alternative scenarios. Plos one. https://doi.org/10.1371/journal.pone.0270846
21. Huber, Fl., Koop, G., Onorante, L., Pfarrhofer, M., & Schreiner, J. (2021). Nowcasting in a pandemic using non-parametric mixed frequency VARs. ECB Working Paper Series, 42, (2510).
22. Li, J., Vidyattama, Y., La, H., Miranti, R., & Sologon, D. (2022). Estimating the Impact of Covid-19 and Policy Responses on Australian Income Distribution Using Incomplete Data. Social Indicators Research, 162, 1-31.
23. D’Amuri Fr., & Marcucci, J. (2021). The predictive power of Google searches in forecasting US unemployment. International Journal of Forecasting. Retrieved from https://www.sciencedirect.com/science/article/abs/pii/S0169207017300389
24. World bank (2023). Household Monitoring Systems to Track the Impacts of the COVID-19 Pandemic. Retrieved from https://www.worldbank.org/en/topic/poverty/brief/high-frequency-monitoring-surveys
25. Laborde, D., Martin, W., & Vos, R. (2020). Estimating the Poverty Impact of COVID-19. International Food Policy Research Institute, 1-19.
26. Dang, H. Anh, Lanjouw, P., Luoto, J., & McKenzie, D. (2014). Using repeated cross-sections to explore movements into and out of poverty. Journal of Development Economics. Retrieved from
https://www.sciencedirect.com/science/article/abs/pii/S0304387813001521
27. Colgan, Br. (2023). EU-SILC and the potential for synthetic panel estimates Empirical Economics, 64, 1247-1280.
28. Klevmarken, A. (2022). Microsimulation: A tool for economic analysis. International Journal of Microsimulation, 15(1), 6-14. https://doi.org/10.34196/ijm.00246
29. Vos, R., & Sánchez, M. V. (2010). A non-parametric microsimulation approach to assess changes in inequality and poverty. United Nations, Department of Economic and Social Affairs. Working Paper No. 94, 1-24.
30. State Statistics Service of Ukraine (2021). Household living conditions survey. Retrieved from https://www.ukrstat.gov.ua/operativ/micro_dani/mic_doch_i_umovy_2021.zip
31. UNICEF (December 2023–February 2024). Household Socio-Economic Status Survey (HSESS). Retrieved from https://www.unicef.org/ukraine/documents/social-economical-state-2023-24
32. Libanova, E., Cherenko, L., Poliakova, S., Shyshkin, V., Reut, A., Vasyliev, O., …, & Krykun, O. (2024). Poverty and inequality in Ukraine under the influence of COVID-19: Assessment approaches (2 nd ed.). Institute for Demography and Life Quality Problems of the NAS of Ukraine. ISBN 978-617-14-0382-6.
33. Cherenko, L. (2024). Measuring Poverty in the Conditions of War in Ukraine. Economic Commission for Europe Conference of European Statisticians. Retrieved from https://unece.org/sites/default/files/2024-11/_W_Multidimensional%20poverty_Ukraine%20UNICEF_paper.pdf
34. Cherenko, L., Zaiats, V., Klymenko, Yu., Kohatko, Yu., Krykun, O., Poliakova, S., …, & Shyshkin, V. (2025). Poverty and the situation of children in wartime. Institute for Demography and Life Quality Problems of the NAS of Ukraine. ISBN 978-617-14-0381-9.
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