Resituating relaunched migration systems as emergent entities manifested in geographic structures

California Exodus? A Network Model of Population Redistribution in the United States

Motivated by debates about California's net migration loss, we employ valued exponential-family random graph models to analyze the inter-county migration flow networks in the United States. We introduce a protocol that visualizes the complex effects of potential underlying mechanisms, and perform in silico knockout experiments to quantify their contribution to the California Exodus. We find that racial dynamics contribute to the California Exodus, urbanization ameliorates it, and political climate and housing costs have little impact. Moreover, the severity of the California Exodus depends on how one measures it, and California is not the state with the most substantial population loss. The paper demonstrates how generative statistical models can provide mechanistic insights beyond simple hypothesis-testing.

Time to Mainstream the Environment into Migration Theory?

As with all social processes, human migration is a dynamic process that requires regular theoretical reflection; this article offers such reflection as related to the role of the natural environment in contemporary migration research and theory. A growing body of evidence suggests that environmental contexts are increasingly shifting social and ecological realities in ways that are consequential to migration theory. We review some of this evidence, providing examples applicable to core migration theories, including neoclassical economic and migration systems perspectives, the "push-pull" framework, and the new economics of labor migration. We suggest that neglecting consideration of the natural environment may yield misspecified migration models that attribute migration too heavily to social and economic factors particularly in the context of contemporary climate change,. On the other hand, failure to consider migration theory in climate scenarios may lead to simplistic projections and understandings, as in the case of "climate refugees". We conclude that migration researchers have an obligation to accurately reflect the complexity of migration's drivers, including the environment, within migration scholarship especially in the context of global climate change.

The form and evolution of international migration networks, 1990-2015

Presently, there is no agreed upon data-driven approach for identifying the geographic boundaries of migration networks that international migration systems are ultimately manifested in. Drawing from research on community detection methods, we introduce and apply the Information Theoretic Community Detection Algorithm for identifying and studying the geographic boundaries of migration networks. Using a new set of estimates of country-to-country migration flows every 5 years from 1990 to 1995 to 2010-2015, we trace the form and evolution of international migration networks over the past 25 years. Consistent with the concept of dynamic stability, we show that the number, size and internal country compositions of international migration networks have been remarkably stable over time; however, we also document many short-term fluctuations. We conclude by reflecting on the spirit of our work in this paper, which is to promote consensus around tools and best practices for identifying and studying international migration networks.

The multidimensional clustering of health and its ecological risk factors

A diverse set of research has examined the ways in which population-level health and its ecological risk factors are embedded within self-reinforcing structures. Syndemic theory, for example, focuses on the co-occurrence of multiple diseases, whereas the spatial diffusion literature highlights the concentration of poor health among communities sharing geographic boundaries. This study combines these related but disciplinarily-isolated perspectives to examine the clustering of population-level health and its determinants across four dimensions: co-occurrence, spatial, temporal, and social network. Using data on U.S. county-level health outcomes and health factors from the Robert Wood Johnson Foundation's County Health Rankings, this study estimates associations between health outcomes within communities and the co-occurrence of community-level factors theorized to influence ecological health. Not only do health outcomes and their ecological risk factors cluster within counties, but also between geographically adjacent counties and counties connected via migration network pathways. Moreover, the self-reinforcing structures uncovered across the co-occurrence, spatial and network dimensions persist over time, and this clustering has consequences on county health and well-being. Rather than adopting the perspective that either health and its community-level factors should be broadly targeted and detached from local context or communities are different, have unique needs and thus should be treated in isolation, the approach advanced in this study identifies shared vulnerabilities in a way that allows for the development of knowledge networks between communities dealing with similar issues.

DIFFERENTIAL RECOVERY MIGRATION ACROSS THE RURAL-URBAN GRADIENT: MINIMAL AND SHORT-TERM POPULATION GAINS FOR RURAL DISASTER-AFFECTED GULF COAST COUNTIES

Places affected or threatened by extreme environmental disturbances confront a number of significant issues, including whether their populations will stay the same or change through migration. Research on Hurricanes Katrina and Rita shows some displaced residents returned to their disaster‐affected communities once the built environment was restored, new migrants settled in affected places as part of the rebuilding effort, and the regional migration system grew more urbanized and spatially concentrated during post‐disaster years. Research also shows that not all disaster‐affected places recovered their populations. Our study examines whether differential recovery is systematically patterned along the rural–urban gradient. Using U.S. Census Bureau estimates and IRS county‐to‐county migration data, we investigate whether the 2005 hurricane season differentially exacerbated or altered previous migration trends across a rural–urban gradient that incorporates proximity to metropolitan areas and disaster‐related housing loss. We find a rural–urban differential in Gulf Coast recovery migration: The disaster boosted migration among non‐metropolitan counties, yet these increases were smaller and short‐lived compared to the patterns found for metropolitan counties, most especially high loss metropolitan counties. Our findings encourage theories of environmental migration to incorporate spatial differentiation and scenarios of environmental changes to account for differential impacts on settlement patterns across the rural–urban continuum.

Changing Spatial Interconnectivity during the "Great American Migration Slowdown": A Decomposition of Intercounty Migration Rates, 1990-2010

Prior research on the "Great American Migration Slowdown," or the declining rate of U.S. internal migration in recent decades, is dominated by two research foci. The first is concerned with the determinants of the migration slowdown. The second is concerned with spatial heterogeneity in the migration slowdown in and across places. With respect to the aim of this paper, many studies of spatial heterogeneity in the migration slowdown have implicitly raised questions about whether and to what extent places are connected to one another by migration flows, or the spatial interconnectivity of migration. The spatial interconnectivity of migration is a concrete manifestation of underlying spatial interdependence among places, and, as such, deserves to be explicitly unpacked to further our understanding of the migration slowdown. Using county-to-county migration flow data from the Internal Revenue Service and a novel application of Das Gupta's demographic standardization and decomposition procedures, we document changes in the spatial interconnectivity of migration during the migration slowdown between 1990 and 2010. We show that counties became more connected to one another by migration over time, and that the increasing spatial interconnectivity of migration helped to keep the migration slowdown from slowing further. We also document changes in the spatial interconnectivity of migration for four types of migration flows: metro-to-metro, nonmetro-to-metro, metro-to-nonmetro, and nonmetro-to-nonmetro. Our work further elucidates the characteristics of the migration slowdown by describing changes in the spatial interconnectivity of migration. It also raises new questions for future research about the determinants and consequences of these changes.