Climate-induced migration or immobility? Evidence from Nigeria

The complex relationship between climate shocks, adaptation, and migration hinders a rigorous understanding of the heterogeneous mobility outcomes of farm households exposed to climate stress. To unpack this heterogeneity, we couple causal machine learning methods, tailored to a conceptual framework bridging economic migration theory and the poverty traps literature, with longitudinal multi-topic household data from Nigeria. This approach allows us to produce fine-grained, non-parametric evidence that identifies the factors driving divergent mobility outcomes across different household groups affected by the same shocks. The estimated conditional average treatment effects suggest that key variables—pre-shock asset levels, in situ adaptive capacity, and weather exposure during the previous survey period—shape not only the magnitude but also the sign of the impact of agriculture-relevant weather anomalies on the mobility outcomes of farming households. While in situ adaptation serves as an alternative to migration, the role played by wealth constraints and multiple shock exposure is consistent with the existence of climate-induced immobility traps.