Analysis of the effect of COVID‐19 on crude oil and agricultural commodity market relationships

Abstract

This study examines the COVID‐19 pandemic's effect on relationships between crude oil and agricultural commodity markets. Using a Time‐Varying Parameter Vector Autoregressive model, we find strong volatility transmission, with Brent, WTI, corn, and soybean prices acting as net shock transmitters, while cotton and wheat are net receivers. Dynamic Time Warping further identifies co‐movement and temporal lead‐lag relationships across markets. A Bayesian Structural Time Series model shows that COVID‐19 is associated with a statistically significant 5.8% increase in market connectedness. These findings indicate that market linkages intensified during the pandemic, suggesting that shocks in one market can generate spillover effects across interconnected markets.