Mobility, Neighborhood Context, and Voting: A Network Approach to Political Polarization

Abstract

This paper examines whether commuting-based exposure to neighborhood disadvantage predicts partisan realignment across American census tracts. Using LODES/LEHD origin-destination employment data, we construct a tract-level measure of Outdegree Network Disadvantage (OND), the flow-weighted mean socioeconomic disadvantage of commuting destinations, and link it to precinct-level presidential election returns from 2016, 2020, and 2024. We find that OND predicts Republican vote share in predominantly white tracts, and that this relationship deepened continuously across all three election cycles. Additionally, income moderates the OND effect in ways that shifted structurally between periods, concentrating among economically vulnerable white communities by 2020–2024. Lastly, the politically relevant exposure is outward and increasingly comparative: it is tied to where residents commute rather than who commutes into their tract. These findings further suggest that daily mobility patterns are a consequential yet undertheorized dimension of political geography.