Human capital in a fragile state: an econometric and machine learning analysis of development aid, humanitarian assistance, conflict, and economic conditions in Somalia

Résumé

Introduction Human capital is central to economic development, particularly in fragile and conflict-affected states where instability, aid dependence, and weak institutions shape long-term development outcomes. This study examines the effects of development aid, humanitarian assistance, conflict, and economic conditions on human capital in Somalia. Methods The study uses annual data for Somalia covering 1990–2023. A Human Capital Index is constructed from life expectancy and labor force participation due to limited long-term education data. An integrated econometric and machine-learning approach is applied, combining ARDL, Random Forest, and Bayesian regression to capture short- and long-run dynamics, variable importance, and parameter uncertainty. Results The findings show that development aid has a positive short-run effect but a negative long-run relationship with human capital. Humanitarian assistance consistently supports human capital, while conflict has a strong negative effect. GDP per capita shows a weaker and less stable association. Discussion The results suggest that human capital outcomes in fragile contexts are shaped by the interaction of short-term support, long-term structural conditions, and persistent instability. The study highlights the need to align external assistance with domestic systems to support sustainable human capital development in Somalia.

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