## State Fragility: Towards a Conceptual Framework

_IMF Working Papers, October 3, 2025_

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## Bibliographic details
- Authors: Aliona Cebotari, Enrique Chueca-Montuenga, Yoro Diallo, Yunsheng Ma, Rima A Turk, Weining Xin, Harold Zavarce
- Published: October 3, 2025
- Series: IMF Working Papers
- DOI: https://doi.org/10.5089/9798229028578.001

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### Overview
- Purpose: Proposes a general conceptual framework for state fragility that disentangles the identification of fragility from its underlying drivers.
- Core reduction: Identification of state fragility is reduced to the responsiveness of economic or political systems to shocks.
- Publication: IMF Working Papers, Working Paper No. 2025/205; Pages: 55; Volume: 2025; Issue: 205; DOI: https://doi.org/10.5089/9798229028578.001; ISBN: 9798229028578; ISSN: 1018-5941.
- Authors: Aliona Cebotari, Enrique Chueca-Montuenga, Yoro Diallo, Yunsheng Ma, Rima A Turk, Weining Xin, Harold Zavarce.
- Date: October 3, 2025.

### Conceptual framework and definitions
- Fragility definition (extension of Taleb’s work):
  - Fragility is a disproportionate (supra-linear) response to negative shocks.
  - Fragility includes an underwhelming (sub-linear) response to positive shocks or to time.
- Two distinct forms of fragility:
  - Fragility to stress: breakdowns in political or economic systems in response to negative shocks.
  - Chronic fragility: inability of economies to generate growth over time.

### Manifested fragility vs latent fragility
- Manifested fragility:
  - Identification where the produced list of fragile states closely aligns with classifications by international organizations.
- Latent fragility:
  - Identification where underlying drivers offer a probabilistic proximity to a fragile response.
  - Latent fragility can be used to infer risk even when fragility is not yet manifested.

### Methodology illustrated: coups d’état as a probe of political fragility
- Approach:
  - Focus on coups d’état as reflective of political fragility.
  - Use machine learning to examine coup drivers and their nonlinear interactions.
  - Derive implied coup probabilities across all countries.
- Emphasis:
  - Nonlinear interactions among drivers are central to identifying latent fragility.
  - Machine learning provides probabilistic assessments of proximity to fragile responses.

### Key findings and analytical insights
- The responsiveness framework separates identification (system response) from drivers (structural fundamentals and stressors).
- Fragility characterization:
  - Supra-linear responses to negative shocks identify systems prone to breakdown.
  - Sub-linear responses to positive shocks or to time identify systems with chronic growth incapacity.
- Application results:
  - Manifested fragility lists produced by the framework closely align with international organization classifications.
  - Latent fragility estimates (via coup probability modeling) provide cross-country implied probabilities of political fragility.

### Policy implications and recommendations
- Strategic priorities for engagement with fragile states:
  - Prioritize elimination of sources of fragility through strengthened structural fundamentals.
  - Mitigate stressors through stronger policies.
- Expected returns:
  - Both strengthening fundamentals and mitigating stressors have higher returns in chronically fragile environments.
- Operational lesson:
  - Distinguish interventions aimed at reducing susceptibility to negative shocks from those aimed at fostering sustained positive responses (growth over time).

*IMF Working Paper No. 2025/205. By Aliona Cebotari, Enrique Chueca-Montuenga, Yoro Diallo, Yunsheng Ma, Rima A Turk, Weining Xin, and Harold Zavarce. October 3, 2025.*

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_Source: https://www.imf.org/en/publications/wp/issues/2025/10/03/state-fragility-towards-a-conceptual-framework-570948_