Putting trapped populations into place: climate change and inter-district migration flows in Zambia
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Research shows that the association between adverse climate conditions and human migration is heterogeneous. One reason for this heterogeneity is the differential vulnerability of populations to climate change. This includes highly vulnerable, “trapped” populations that are too poor to migrate given deep and persistent poverty, the financial costs of migrating, and the erosion of already fragile economic livelihoods under climate change. Another reason for this heterogeneity is the differential vulnerability of places. However, despite the growing list of studies showing that the climate-migration relationship clearly varies across places, there is surprisingly little research on the characteristics of places themselves that trap, or immobilize, populations. Accordingly, we provide the first account of the “holding power” of places in the association between adverse climate conditions and migration flows among 55 districts in Zambia in 2000 and 2010. Methodologically, we combine high-resolution climate information with aggregated census micro data to estimate gravity models of inter-district migration flows. Results reveal that the association between adverse climate conditions and migration is positive only for wealthy migrant-sending districts. In contrast, poor districts are characterized by climate-related immobility. Yet, our findings show that access to migrant networks enables climate-related mobility in the poorest districts, suggesting a viable pathway to overcome mobility constraints. Planners and policy makers need to recognize the holding power of places that can trap populations and develop programs to support in situ adaptation and to facilitate migration to avoid humanitarian emergencies.
KeywordsClimate change Migration Zambia Trapped populations Holding power Migrant networks
The authors gratefully acknowledge the Central Statistical Office Zambia for providing the underlying data making this research possible. We thank Joshua Donato for help with the construction of the spatial variables and Deborah Balk for her helpful comments. We also thank Maryia Bakhtsiyarava for her help constructing the maps.
The authors gratefully acknowledge support from the Minnesota Population Center (#P2C HD041023), funded through grants from the Eunice Kennedy Shriver National Institute for Child Health and Human Development (NICHD). This work also received support from the National Science Foundation funded Terra Populus project (NSF Award ACI-0940818).
Compliance with ethical standards
The analyses described in this paper were performed using secondary data obtained from various publically available sources as outlined in the “Data and methods” section.
Conflict of interest
The authors declare that they have no conflict of interest.
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