How Nations Become Fragile: An AI-Augmented Bird’s-Eye View (with a Case Study of South Sudan)

Tohid Atashbar

No 2023/167, IMF Working Papers from International Monetary Fund

Abstract: In this study we introduce and apply a set of machine learning and artificial intelligence techniques to analyze multi-dimensional fragility-related data. Our analysis of the fragility data collected by the OECD for its States of Fragility index showed that the use of such techniques could provide further insights into the non-linear relationships and diverse drivers of state fragility, highlighting the importance of a nuanced and context-specific approach to understanding and addressing this multi-aspect issue. We also applied the methodology used in this paper to South Sudan, one of the most fragile countries in the world to analyze the dynamics behind the different aspects of fragility over time. The results could be used to improve the Fund’s country engagement strategy (CES) and efforts at the country.

Keywords: Fragile and Conflict-Affected States; Fragility Trap; Fragility Syndrome; Machine Learning; Artificial Intelligence; AI technique; fragility data; Bird's-Eye View; artificial intelligence technique; aggregate fragility; Artificial intelligence and machine learning; Global; Middle East; North Africa; South Asia; Sub-Saharan Africa (search for similar items in EconPapers)
Pages: 36
Date: 2023-08-11
New Economics Papers: this item is included in nep-ain, nep-big, nep-cmp and nep-dev
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