Data-driven anatomy of hierarchical migration patterns in the United States

Population migration has become a dominant force in shaping local demographic changes in the United States, surpassing natural growth rates. However, whether the migration pattern and the influential factor have distinctive disparities between hierarchical county pairs is still elusive. This study delves into the spatial diversity and driving forces behind migration patterns at the county level, with a particular focus on the disparities through an examination of migration levels and scales. We utilize county-pair-level migration data from the U.S. Census Bureau's American Community Survey to unveil the intricate network structure of population movement. Our findings reveal a pronounced spatial diversity in migration patterns, while cities witness a net influx of population, and in contrast to rural areas, majority of population inflow of cities primarily stems from metro areas. We employ Hierarchical Linear Models to analyze the impact of social connectedness, local wealthiness, and racial diversity on migration flows. The results highlight that cities with robust social networks, higher economic status, and balanced racial diversity are more attractive to migrants. Notably, the influence of racial diversity differences between origin and destination counties is found to be more significant in attracting migration compared to per capita income disparities. The findings offer valuable insights for policymakers and urban planners in managing demographic changes and addressing the challenges associated with migration-driven population redistribution. The study underscores the importance of considering social, economic, and racial factors in understanding and shaping migration patterns, with implications for regional development and social cohesion.