From correlation to causation: Rethinking evidence in climate-conflict research
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In this podcast episode, host Marina Mastrorillo speaks with Tilman Brück of the International Security and Development Center and Antonio Scognamillo of FAO about one of climate-conflict research’s toughest questions: how to distinguish correlation from causation. They unpack endogeneity, overlapping drivers like food security and migration, and the limits of econometrics. The discussion highlights why causal inference matters, when correlations are still useful, and how evidence can better support policy and early warning.
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climate change, migration, conflicts, econometrics, econometric models