  The complex relationship between climate shocks, migration, and adaptation
hampers a rigorous understanding of the heterogeneous mobility outcomes of farm
households exposed to climate risk. To unpack this heterogeneity, the analysis
combines longitudinal multi-topic household survey data from Nigeria with a
causal machine learning approach, tailored to a conceptual framework bridging
economic migration theory and the poverty traps literature. The results show
that pre-shock asset levels, in situ adaptive capacity, and cumulative shock
exposure drive not just the magnitude but also the sign of the impact of
agriculture-relevant weather anomalies on the mobility outcomes of farming
households. While local adaptation acts as a substitute for migration, the
roles played by wealth constraints and repeated shock exposure suggest the
presence of climate-induced immobility traps.
