Time-Series modeling of supply chain disruption drivers in ASEAN agri-food logistics networks

Information from the abstract

Disruptions in agri-food supply chains pose logistical and operational challenges for ASEAN member economies, whose agricultural sectors are simultaneously exposed to fluctuations in freight costs and climate-related production shocks. Prior time-series applications in shipping markets, agricultural commodity co-movement, and supply chain performance have generally examined these channels separately, and the joint transmission of these channels into ASEAN agri-food commodity logistics outcomes remains largely unexamined. This study applies a Vector Autoregression (VAR) time-series modeling framework to identify and quantify the principal drivers of disruption in ASEAN agri-food logistics networks, using 4,108 daily observations spanning January 2015 to March 2026. Seven variables are jointly modeled: Baltic Dry Index daily change (D_BDI), Brent crude oil log-return (R_Brent), Geopolitical Risk Index daily change (D_GPR), Oceanic Niño Index anomaly change (D_ONI), ASEAN aggregate agricultural production return (R_ASEAN_Production), and daily price changes of Robusta and Arabica coffee. Stationarity is verified by the Augmented Dickey-Fuller (ADF) tests. The lag order p = 2 is selected based on BIC and HQIC. GPR shocks exert statistically significant lagged effects on Arabica price (p = 0.007) and Robusta price (p = 0.021); ONI anomaly changes significantly propagate into Robusta prices (p = 0.021). A cross-domain pathway from ONI to GPR (p = 0.010) is consistent with climate disruption signals coinciding with subsequent geopolitical risk movements. BDI first-order persistence coefficient is 0.596 (p < 0.001). Forecast Error Variance Decomposition (FEVD) shows Robusta-to-Arabica cross-variance at 44.03% at horizon 10. Durbin-Watson statistics (1.958–2.061) confirm residual white noise across all equations. These results provide quantitative inputs for engineering early-warning systems for disruption and logistics resilience planning in ASEAN agri-food supply networks.

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Related topics: Market Dynamics and Volatility · Economics of Agriculture and Food Markets · Supply Chain Resilience and Risk Management