Fine-grained analysis of transport-demographic relationships: County-level responses to multimodal connectivity across metropolitan and peripheral China

Junxi Qu, Xiaoyi Ma, Yang Zhou, Xianlong Chen and Tianren Yang

Transportation Research Part A: Policy and Practice, 2025, vol. 199, issue C

Abstract: Despite extensive research on transport-induced demographic change, few studies have systematically investigated how different transport modes shape population distribution across diverse geographical contexts at fine spatial scales. This study explores the relationship between multimodal transport networks and population density using 20 years of county-level panel data, focusing on differential impacts in metropolitan and peripheral counties across China. Employing high-dimensional fixed effects models and centrality measures derived from aviation, high-speed rail and conventional rail networks, our results show that higher degree centrality (i.e., more direct connections) is positively associated with population concentration (+0.018%), while higher inverse closeness centrality (i.e., greater average shortest distance to all other nodes) is negatively associated (−0.005%). These effects are not instantaneous but emerge with significant five-year lags. Metropolitan counties experience approximately 4% greater population gains from improved connectivity than peripheral regions. While connectivity effects are observed across all transport modes, high-speed rail exhibits relatively consistent and positive associations with population growth over longer time lags, although its effects in metropolitan areas are generally weaker than those of aviation and conventional rail. Complementing the regression results, LightGBM-based SHAP analysis reveals substantial spatial heterogeneity: even within the same classification (metropolitan or peripheral), counties with advantageous network positions—such as regional hubs—exhibit markedly stronger demographic responses. The findings offer valuable guidance for urban planning and transport policy, emphasising the need for targeted, mode-sensitive investment strategies that account for regional disparities in transport access and development potential.

Keywords: Multimodal transport network; Population dynamics; Network centrality; Urban modelling; Urban systems; Computational urban science (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1016/j.tra.2025.104572

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