The question of whether environmental conditions influence human migration has recently gained considerable attention, driven by claims that global environmental change will displace large populations. Despite this high level of interest, few quantitative studies have investigated the potential effects of environmental factors on migration, particularly in the developing world and for gradual but pervasive forms of environmental change. To address this, a retrospective migration survey was conducted in rural Ecuador and linked to data on topography, climate, and weather shocks. These data were used to estimate multivariate event history models of alternative forms of mobility (local mobility, internal migration, and international migration), controlling for a large number of covariates. This approach is generalizable to other study areas and responds to calls for the development of more rigorous methods in this field. The results indicate that adverse environmental conditions do not consistently increase rural out-migration and, in some cases, reduce migration. Instead, households respond to environmental factors in diverse ways, resulting in complex migratory responses. Overall, the results support an alternative narrative of environmentally induced migration that recognizes the adaptability of rural households in responding to environmental change.
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Cantons are administrative units that are roughly equivalent to counties in the United States.
This three-stage sampling procedure provides less-precise estimates than a simple random sample of households but offers considerable cost and logistical advantages, particularly for sampling rare migrant types.
For example, in communities with 10–19 at-risk households, up to 4 households were selected from each stratum, with a minimum total of 7 households and a maximum of 10. In a community with 10 nonmigrant households, 5 households sending a migrant to an urban destination, and 2 sending a migrant to an international destination, the sample selected would comprise the 2 sending to an international destination, 4 to an urban destination, and 4 nonmigrant households, yielding a total of 10. If instead there were 16 nonmigrant households, 1 urban-sending household, and 1 international-sending household, 4 nonmigrant households would be selected at random to go with the single urban-sending and international-sending households, and 1 additional household would be selected at random—in this case from the nonmigrant stratum—to attain a minimum of 7 households.
The most relevant previous study evaluating recall in migration surveys is Smith and Thomas (2003), who found in Malaysia that retrospective recall of the same move after a 12-year lag introduced a median date error of less than 1 year and underreported number of interdistrict moves by only 5 %.
Using these data, we estimate that 75 % of local movers, 70 % of internal migrants, and 85 % of international migrants departed as individuals rather than as part of whole households.
As an alternative specification of the environmental context, indices combining various measures of topography (e.g., slope, elevation, and aspect) and climate (e.g., rainfall, temperature, and seasonality) were examined, but the measures described earlier provided as good a fit and a more parsimonious explanation.
Additional temporal lags (e.g., two years) were explored but were consistently found to be nonsignificant.
Men and women contribute 4,024 and 3,265 person-years, respectively, to the data set. Similarly, land-poor and nonpoor households contribute 2,992 and 4,297 person-years, respectively.
For example, 63 % of adult men in the study areas worked in own-farm agriculture and 43 % worked in off-farm agriculture in 2008 versus 47 % and 9 % of women, respectively.
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Funding for this research was provided by the National Institutes of Health (HD052092, HD061752, AG000155). We are indebted to our Ecuadorian partners at the Centro de Estudios de Poblacion y Desarrollo Social, as well as to the team of field researchers and the participating communities. We thank Luis Vallejo and Brian Frizzelle for their respective efforts on data cleaning and spatial analysis. Helpful comments on a previous draft were provided by Jason Bremner.
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Gray, C., Bilsborrow, R. Environmental Influences on Human Migration in Rural Ecuador. Demography 50, 1217–1241 (2013). https://doi.org/10.1007/s13524-012-0192-y
- International migration
- Internal migration
- Event history