Flight Issues and Regional Partisan Dynamics: A Longitudinal Analysis

Music City Center 

Our study presents a longitudinal analysis that analyzes relationships between airline flight data
from the Bureau of Transportation Statistics and regional partisan shifts from the Biographical Directory of the U.S. Congress. Our motivation is to understand and explain relationships between
flight issues and the local political climates of regions containing airports, including constructing
causal models for these relationships. We focus our attention on 1990 and 2024, which crosses several changes in the national political environment and major historical events that influenced flight
patterns, including 9/11, the 2008 recession, and the COVID-19 pandemic. Using a spatiotemporal
autoregressive model, we identify significant connections between geographic and other factors. Our
findings prompted further modeling to explore causal effects and the partisan consequences of air
travel. Results suggest that while political climates shape flight issues, air travel disruptions can also
influence regional partisan dynamics, forming a feedback loop between transportation infrastructure
and political behavior.

Longitudinal Analysis

Causal Effects

Spatiotemporal Autoregressive Model

Partisan Shifts

Flight Issues

Transportation-Politics 

Section on Statistical Computing