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.
Authors
- DOI
- https://dx.doi.org/10.1596/1813-9450-10724
- Disclosure Date
- 2024/03/18
- Disclosure Status
- Disclosed
- Doc Name
- Climate Immobility Traps : A Household-Level Test
- Originating Unit
- Off of Sr VP Dev Econ/Chief Econ (DECVP)
- Product Line
- Research Activity
- Published in
- United States of America
- Rel Proj ID
- 1W-Towards Improved Data For Labor Mobility -- P176461
- Series Name
- Policy Research working paper ; no. WPS 10724; RRR: PLANET; LSMS;
- TF No/Name
- TF0B5250-Towards Improved Data for Labor Mobility and Territorial Development Po,TF0C1776-Labor_Mobility_Measurement_World
- Unit Owning
- Living Standards Measurement (DECLS),Development Data Group (DECDG)
- Version Type
- Final
- Volume No
- 1