Abstract
Environmental and climatic changes have shaped human mobility for thousands of years and research on the migration-environment connection has proliferated in the past several years. Even so, little work has focused on Latin America or on international movement. Given rural Mexico’s dependency on primary sector activities involving various natural resources, and the existence of well-established transnational migrant networks, we investigate the association between rainfall patterns and U.S.-bound migration from rural locales, a topic of increasing policy relevance. The new economics of labor migration theory provides background, positing that migration represents a household-level risk management strategy. We use data from the year 2000 Mexican census for rural localities and socioeconomic and state-level precipitation data provided by the Mexican National Institute for Statistics and Geography. Multilevel models assess the impact of rainfall change on household-level international out-migration while controlling for relevant sociodemographic and economic factors. A decrease in precipitation is significantly associated with U.S.-bound migration, but only for dry Mexican states. This finding suggests that programs and policies aimed at reducing Mexico-U.S. migration should seek to diminish the climate/weather vulnerability of rural Mexican households, for example by supporting sustainable irrigation systems and subsidizing drought-resistant crops.
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Notes
In a report published by the International Organization of Migration (IOM), Kniveton et al. (2008) analyze the association between migration and rainfall using MMP data for the Mexican states of Zacatecas and Durango. A decrease in rainfall is significantly associated with a decrease in international out-migration to the U.S. for Durango, but for Zacatecas this correlation is not significant. However, these results lack reliability, because the study used bivariate associations and a small migrant sample size, and they are therefore not considered in our discussion.
There is also some evidence that in Mexico migration may be associated with sudden-onset events. Using the 2000 Mexican Census, Saldaña-Zorilla and Sandberg (2009) found that local susceptibility to natural disasters is associated with the municipal out-migration rate (which includes both internal and international movement). Here, susceptibility (and the “push” to migrate) included absence of credit and associated declines in income.
The MMP is a collaborative research project based at Princeton University and the University of Guadalajara (PUGU 2010) and provides high-quality data for public use.
We obtained this figure by doing a query at http://www.inegi.org.mx/sistemas/olap/proyectos/bd/consulta.asp?p=14048&c=10252&s=est#, last consulted July 13, 2012.
Our migration measure does not include members of entire households that emigrated abroad during this time (and did not return by the interview date). While this omission could bias our estimates, the amount of error is likely to be small in rural areas, where migrants are more likely to return (Cornelius 1992; Riosmena 2004). In addition, our theoretical framework assumes that the majority of international moves are the result of ex-post/ex-ante household-level responses towards environmental stressors. We are unable to separate such moves from moves that are solely based on economic considerations or motivated by normative expectations of male young adults who might view migration to the U.S. as a rite of passage (e.g., Kandel and Massey 2002). Using a measure of migration that combines all of these various migration motivations can be considered as conservative. We might expect a much stronger relationship for moves solely motivated by risk/insurance considerations and environmental factors.
First, items were included that reflect the physical quality of housing units, in terms of materials used for building the wall, the roof, and the floor; the nature of toilet facilities; the number of rooms in the house; type of sewage disposal; type of water supply (piped vs. nonpiped); cooking fuel (electricity, charcoal, wood, etc.); and whether a hot water heater was available. Second, households were asked to report about the ownership of various means of personal transportation and other household durables—a car, a bicycle, television, radio, videocassette recorder, telephone, refrigerator, and washing machine. These variables were coded on a continuous scale or as dummies, with higher values indicating higher levels of physical capital. All items were used to form a standardized scale with a Cronbach’s α reliability of 0.859.
The index reflects the proportions of a municipality’s households (1) with dirt floors, (2) without indoor plumbing or a toilet, (3) without electricity, (4) without access to piped water, and (5) with more than two people per room, as well as the proportion of adults in the municipality (6) who are illiterate, (7) who have not completed primary education, and (8) who earn less than twice the minimum wage. This measure has been used in other studies of Mexican migration (e.g., Riosmena et al. 2012; Saldaña-Zorilla and Sandberg 2009).
The MOR was calculated as follows: MOR = exp(sqrt(2*σ2)*φ−1(0.75)), where φ(·) is the cumulative distribution function of the normal distribution with mean 0 and variance 1, φ−1(0.75) is the 75th percentile (0.674), exp(·) is the exponential function, and sqrt is the square-root (Larsen and Merlo 2005). The MOR is always greater than or equal to 1. If the MOR is 1, there is no variation between clusters. Large MOR values reflect substantial between-cluster variation. In contrast to the raw variance components, the MOR has the benefit of being directly comparable with the fixed-effects odds ratios. In addition the MOR has a substantively more meaningful interpretation. The MOR quantifies the variation between clusters by comparing two cases from two randomly chosen, different clusters.
The full model was checked for multicollinearity using the variance inflation factor (VIF) test. The VIF values for all variables remained smaller than two (except for the interaction and its involved variables). Heuristics suggest that values below 10 indicate that multicollinearity is of no concern.
To investigate whether the non-significant relationship for wet states can be attributed to the impact of Puebla we removed this state from the model. The rainfall decrease coefficient became positive (b = 1.092, z = 0.45) but did not reach significance. Due to convergence issues this model was fitted using the PQL1 instead of PQL2 estimation procedure.
Five robustness tests were performed. First, we used a repeated split sample procedure that randomly divided the sample of dry states (Model A, Table 3) into two groups of equal numbers of households and then ran the multilevel regression for each group separately. This procedure was repeated 150 times, resulting in 300 independent model estimations. We then calculated the mean and standard deviation of the coefficients and z-scores of the dryness increase measure across all iterations. This provides an indication regarding the stability of the parameter estimation when the model is fitted on a random subsample. The mean value of all iterations (b = 1.311) came close to the observed coefficient (b = 1.305), with a relatively small standard deviation (0.029). Also, the mean z-score (2.75) was only slightly smaller than the estimated value (2.84) for Model A, with a standard deviation of 0.25. Even if the standard deviation is subtracted from the mean, the z-score does not drop below the 5 % level, and thus both the rainfall decrease coefficient and its significance can be considered robust.
Second, we ran a jackknife type procedure to test for influential states by removing one state at a time from the sample of dry states in Model A of Table 3 (cf., Ruiter and De Graaf 2006). Regardless of which state was removed from the sample, the rainfall decrease measure remained significant.
Third, we reran Model A after removing the six states that border the U.S.: Baja California del Norte, Chihuahua, Coahuila, Nuevo Leon, Sonora, and Tamaulipas. It can be expected that emigration behavior in these states is quite different from that in the rest of Mexico owing to the economic and cultural influence of high concentrations of foreign-owned factories (“maquiladoras”) and the lower costs of border crossing (Feng et al. 2010). When these states were removed from the analysis the association remained similar in strength (b = 1.311) and increased in significance (z = 3.51, p < 0.001).
Fourth, it might be argued that our wet/dry classification masks differences in land use or number of people employed in the agricultural sector. To explore this potential problem we performed a group mean comparison (t test) between wet and dry states on major land use categories (forest, crops, pasture in square kilometers, obtained from the MMP supplemental file ENVIRONS) and the percentage of household heads employed as skilled agricultural and fishery workers. Wet and dry states did not differ on land use characteristics. However, a significant difference was detected for occupational categories with a higher percentage of household heads in wet states (48 %) working in the agricultural and fisher sector than in dry states (34 %). We then included the occupation and land-use variables one at a time in the interaction model (Model 4, Table 2) to control for these potentially confounding characteristics. Regardless which variable was included the interaction term between wet/dry areas and rainfall decline stayed significant.
Finally, we investigated the impact of outliers or influential cases on our main finding. Figure 4a reveals that the state of Pueblo constitutes an unusual case, with relatively high migration probability under conditions of substantial rainfall increase. If we remove this state from Models 3 and 4 in Table 2, both the nonlinear term and the interaction term become insignificant, and a significantly positive linear relationship (b = 1.268, p < 0.05) emerges across the remaining 31 Mexican states, in which a decline in rainfall predicts international out-migration. To explain this unique association between substantial out-migration under high levels of precipitation in Pueblo we can speculate that similarly to drought conditions excessive rainfall and associated flooding has detrimental impacts on crop yields. These results, thus, seem to suggest that extreme weather events at both ends of the continuum (wet to dry) and their impact on the agriculture sector may increase international outmigration.
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Acknowledgments
This project received funding and administrative support from the University of Colorado Population Center (NICHD R21 HD051146). Special thanks to three anonymous reviewers for insightful comments and suggestions on earlier drafts of this manuscript. We express our thanks to Nancy D. Mann for her careful editing and helpful suggestions.
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Nawrotzki, R.J., Riosmena, F. & Hunter, L.M. Do Rainfall Deficits Predict U.S.-Bound Migration from Rural Mexico? Evidence from the Mexican Census. Popul Res Policy Rev 32, 129–158 (2013). https://doi.org/10.1007/s11113-012-9251-8
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DOI: https://doi.org/10.1007/s11113-012-9251-8