Assessing the regional context of migration in the Brazilian Amazon through spatial regression modeling. (August 2019) - Sathler, Douglas
Abstract: The Brazilian Amazon contains the most active rainforest frontier in the world, and its socioeconomic, demographic and spatial dynamism has been a topic of interest for academics and policy makers for decades. In this paper, we use spatial statistical modeling to examine the context of migration in the Brazilian Amazon by investigating its socioeconomic, demographic, spatial and environmental heterogeneities at the municipal level between 2000 and 2010. First, we visualized the spatial distribution of net-migration, in-migration and out-migration rates among municipalities in the Brazilian Amazon. Then, we explored the presence of spatial autocorrelation using Global Moran ' s I Index, and use spatial modeling techniques to investigate the associations between response variables (in-migration and out-migration) and selected explanatory variables. We identified several in-migration frontiers in the region, especially in Center Mato Grosso and Southeast Pará, while out-migration seems more diffuse in the Amazonia territory. Global Moran ' s I scores indicate that most of the selected variables exhibit spatial dependence, and the spatial regression models present better estimates of the coefficients by incorporating the spatially lagged autoregressive parameter. Our results also confirm the spatial heterogeneity and multidimensional character of in-migration and out-migration in the Brazilian Amazon. Economic growth, regional inequality and the environmental dynamism of the rainforest frontier appear to be closely associated with the intensity of migration flows in the region. We also find that less-populated municipalities have a central role in regional migration dynamics, forming relevant in-migration frontiers and ensuring territorial robustness for migration in the region. Highlights: There are several in-migration frontiers in the Brazilian Amazon. Out-migration seems more diffuse in the Amazonia territory. There is significant spatial patterning in in-migration and out-migration rates. Socioeconomic and environmental variables are closely associated with migration.