Temporal Dynamics of Supply-Demand Equilibrium in Railway Transportation: An Integrated Analysis Using Granger Causality and Random Forest Methodologies

This study examines the hypothesis of a mutually causal relationship between railroad supply and demand in South Korea, delving into its causal structure. Understanding the causal dynamics between supply and demand is crucial for making informed decisions about railroad infrastructure investment, particularly given the rapid market changes brought about by high-speed train introductions and continuous line expansions. Through a comprehensive Granger causality analysis across time lags, periods, and market segments, we investigated the mutual influences, and developed a random forest model to assess the significance of supply indicators in explaining demand. Our findings reveal that the Korean railload market is predominantly supply-driven, emphasizing the importance of considering both supply factors and exogenous variables comprehensively. Advanced methodologies like random forest models should be employed to better understand railroad supply and demand interactions.