Human capital, migration, and financial flows as drivers of post-crisis economic performance
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DOIhttp://dx.doi.org/10.21511/kpm.09(2).2025.19
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Article InfoVolume 9 2025, Issue #2, pp. 273-293
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Type of the article: Research Article
The global recovery from recent economic, health, and geopolitical crises, including the COVID-19 pandemic and the Russia–Ukraine war, increasingly depends on how economies mobilize human capital, migration, and financial flows. This article examines how human capital and its reallocation through migration and remittances, under different institutional conditions and economic system types, relate to configurations of human capital, net migration, political stability, and remittances that support sustained post-crisis economic recovery. Using a panel of 73 economies from 2010 to 2023, the empirical strategy combines descriptive rankings, multiple linear regression (MLR), and decision-tree classification, with an 80/20 split of the sample, primarily drawing on the WDI. Descriptive patterns highlight large asymmetries in both migration and growth: some advanced and emerging economies combine sizeable net migration inflows with robust GDP growth, whereas conflict-affected and fragile states, including the Syrian Arab Republic, Yemen, and Ukraine, experience substantial net outflows alongside persistent output losses. However, regression results indicate that differences in human capital primarily drive cross-country variation in post-crisis growth: HCI is the only statistically significant predictor, while net migration, political stability, and remittances display small and insignificant linear effects (R² ≈ 0.15; adjusted R² ≈ 0.10; n = 73). DTC reveals complex, non-linear relationships between migration, human capital, financial flows, and economic recovery, with outcomes concentrated in economies that combine higher skills and sizable remittances with stable institutions, effectively converting them into productive human capital.
Acknowledgments
The research was carried out with funds from the budget of the Ministry of Education and Science of Ukraine on the topic of the research project "Modeling educational transformations in wartime to preserve the intellectual capital and innovative potential of Ukraine" (0123U100114).
- Keywords
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JEL Classification (Paper profile tab)F22, O15, O57, J61
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References61
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Tables3
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Figures10
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- Figure 1. Average net migration by type of economy (2009–2023)
- Figure 2. Impact of average migration and economic system type on GDP growth (2010–2023)
- Figure 3. Impact of net migration on GDP growth (2010–2023)
- Figure 4. Impact of political stability on average GDP growth (2010–2023) across different types of economies
- Figure 5. Relationship between the human capital index and average GDP growth (2010–2023) by economic model
- Figure 6. Influence of personal remittances (% of GDP) on economic growth (2010–2023), differentiated by economy type
- Figure 7. Correlation matrix of key macroeconomic indicators (migration, political stability, human capital, and GDP growth)
- Figure 8. Decision tree for classifying successful economic recovery based on key migration-related indicators
- Figure 9. Feature importance in a decision tree classification model
- Figure 10. Comparison of actual and predicted values for the target variable (GDP recovery) in the decision tree model
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- Table 1. Top 10 and bottom 10 countries by average annual net migration, 2010–2023
- Table 2. Top 10 and bottom 10 countries by average GDP growth rates, 2010–2023
- Table 3. Results of multiple linear regression analysis on GDP growth (2010–2023)
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