Dynamic Differentiated Correlation between Coal and Non-coal Transportation: A VAR Model Analysis of Railway Energy Transportation and Macroeconomy

As a strategic artery for the development of the national economy, the dynamic correlation between energy transportation and the macroeconomy is particularly important against the backdrop of the restructuring of the global energy supply chain. We take the transportation data of a self-operated railway of an energy enterprise from 2020 to 2025 as a sample, select Gross Domestic Product (GDP), Producer Price Index (PPI), Coal Transportation Plan (CTP), Coal Transportation Volume (CT), Non-coal Transportation Plan (NCTP) and Non-coal Transportation Volume (NCTP) as research objects, construct a Vector Autoregression (VAR) model, and explore the dynamic correlation mechanism between coal and non-coal transportation indicators and the macroeconomy through Granger causality test, impulse response function and variance decomposition. The results show that the coal transportation volume is mainly driven by the planned volume and GDP, with their contribution rates being 35.59% and 20.88% respectively, which reflects the strong planned attribute under the integration mode of production, transportation and marketing; the non-coal transportation volume is significantly affected by GDP and PPI, with the influence degrees being 25.71% and 23.02% respectively, which reflects the market sensitivity under the agency mode. Based on the above-mentioned differentiated correlation characteristics, this study can provide theoretical support and decision-making reference for energy enterprises to formulate differentiated transportation scheduling strategies and improve the response efficiency of the supply chain.