The Short-Term Dynamics of Conflict-Driven Displacement: Bayesian Modeling of Disaggregated Data from Somalia

Zens, G. & Thalheimer, L. (2024). The Short-Term Dynamics of Conflict-Driven Displacement: Bayesian Modeling of Disaggregated Data from Somalia. IIASA Working Paper. Laxenburg, Austria: WP-24-002

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Abstract

Understanding the short-run dynamics of conflict and forced displacement is crucial for policy intervention, yet quantitative analyses in this realm are sparse. This is primarily due to the scarcity of high-frequency displacement data and methodological challenges arising when modeling imperfect data collected in conflict zones. Addressing both issues, we develop a Bayesian panel regression model to assess the short-term impact of conflict on displacement in Somalia, utilizing weekly panel data that encompasses 8 million displacements and 19,000 conflict events from 2017 to 2023. Results suggest a rapid and non-linear displacement response post-conflict, with significant heterogeneity in effects dependent on the nature of conflict events. In a displacement forecasting exercise, our model outperforms standard benchmarks, underscoring its relevance for informed decision-making in crisis scenarios.

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