[Paper Review] Rooted America: Immobility and Segregation of the Intercounty Migration Network

Peng Huang, Carter T. Butts|arXiv (Cornell University)|May 4, 2022

Urban, Neighborhood, and Segregation Studies186 references4 citations

TL;DR

This paper proposes a systemic, network-based model of U.S. intercounty migration using valued temporal exponential-family random graph models (tergm) to analyze migration flows from 2011–2015. It reveals that political, urbanization, and racial dissimilarities between counties create segmented immobility, suppressing an estimated 4.6 million annual intercounty moves—equivalent to 27% of observed migration—under a counterfactual where such barriers were absent.

ABSTRACT

Despite the popular narrative that the United States is a "land of mobility," the country may have become a "rooted America" after a decades-long decline in migration rates. This article interrogates the lingering question about the social forces that limit migration, with an empirical focus on internal migration in the United States. We propose a systemic, network model of migration flows, combining demographic, economic, political, and geographic factors and network dependence structures that reflect the internal dynamics of migration systems. Using valued temporal exponential-family random graph models, we model the network of intercounty migration flows from 2011 to 2015. Our analysis reveals a pattern of segmented immobility, where fewer people migrate between counties with dissimilar political contexts, levels of urbanization, and racial compositions. Probing our model using "knockout experiments" suggests one would have observed approximately 4.6 million (27 percent) more intercounty migrants each year were the segmented immobility mechanisms inoperative. This article offers a systemic view of internal migration and reveals the social and political cleavages that underlie geographic immobility in the United States.

Motivation & Objective

• To address the underexplored phenomenon of geographical immobility in the U.S., particularly the social and political forces that limit migration despite economic incentives.
• To move beyond traditional areal-unit models that aggregate migration flows, by modeling migration as a relational, networked system between counties.
• To integrate demographic, economic, political, and geographic factors into a unified network model to capture feedback mechanisms and structural dependencies in migration.
• To quantify the extent to which dissimilarities in political context, urbanization, and racial composition suppress intercounty migration.
• To simulate the impact of removing these segmentation mechanisms via 'knockout experiments' to estimate the scale of suppressed mobility.

Proposed method

• Uses valued temporal exponential-family random graph models (tergm) to model intercounty migration flows as a weighted, dynamic network from 2011 to 2015.
• Incorporates network statistics such as reciprocity, degree distribution, and triadic configurations (e.g., waypoint flow and transitivity) to capture relational dependencies.
• Integrates county-level covariates including political ideology, urbanization level, racial composition, and economic indicators (e.g., unemployment, income) as predictors.
• Employs a network-based approach to model migration as a system of flows between origin and destination counties, preserving relational structure and feedback effects.
• Applies 'knockout experiments' by removing key network statistics (e.g., dissimilarity in political context) to simulate counterfactual migration patterns.
• Uses sampling-based inference with conservative standard errors due to computational constraints, ensuring robustness of statistical conclusions.

Experimental results

Research questions

• RQ1 To what extent do political, racial, and urbanization dissimilarities between counties suppress intercounty migration in the U.S.?
• RQ2 How do network dependence structures—such as reciprocity and triadic configurations—shape the dynamics of internal migration?
• RQ3 What would be the magnitude of intercounty migration if structural barriers to mobility were removed?
• RQ4 How do demographic and economic factors interact with social and political dissimilarities in shaping migration patterns?
• RQ5 To what extent do feedback mechanisms within the migration network sustain or suppress mobility over time?

Key findings

• Political, racial, and urbanization dissimilarities between counties significantly suppress intercounty migration, creating a pattern of segmented immobility.
• Knockout experiments estimate that approximately 4.6 million (27%) more intercounty migrants would have moved annually if dissimilarity-based barriers were absent.
• The model shows that dissimilarity in political context has a stronger suppressive effect on migration than differences in racial composition or urbanization levels.
• Network dependence structures such as waypoint flow and reciprocity are statistically significant, indicating that migration flows are not random but shaped by relational dynamics.
• The suppression of migration due to social and political dissimilarities is substantial and systemic, not merely a byproduct of economic or demographic factors.
• The findings suggest that the U.S. has transitioned from a 'land of mobility' to a 'rooted America,' where social cleavages now constrain geographic mobility at scale.