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Credit Access is Associated with Improved Food Security in the Horn of Africa

arXiv 2609.24382 ↗First posted 21 Sep 2026cs.LGcited by 0

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Abstract (arXiv)

The intensification of climate change poses a growing threat to food security, especially in vulnerable communities. This study employs an observational machine-learning framework to estimate the causal association between access to credit and acute food insecurity in Somalia and across the Horn of Africa, drawing on a harmonized dataset spanning key environmental, socioeconomic, and conflict-related factors from 2015 to 2022. Results indicate that greater credit access is associated with a 2% reduction in acute food insecurity at the population level over the study period. Given that, on average, 16% of the population is in crisis, this effect represents a meaningful shift within the at-risk group. We interpret these estimates under explicit identification assumptions and complement them with robustness and refutation tests. The results provide context-specific evidence on how financial access correlates with food security outcomes in data-scarce, crisis-affected settings, and offer a transparent framework for integrating heterogeneous data sources when randomized evaluations are infeasible.

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References · 2

  1. 2017Meta-learners for Estimating Heterogeneous Treatment Effects using Machine Learningcited by 478
  2. 2020DoWhy: An End-to-End Library for Causal Inferencecited by 95

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