Agricultural Grain Markets in the COVID-19 Crisis, Insights from a GVAR Model

The objective of this paper is to combine cross-commodity and spatial price transmission analysis study the dynamics global cereal feed market during COVID-19 pandemic. After reviewing nascent literature on impact agricultural markets, we discuss different channels prices. Then, provide stylized reactions three relevant wheat, barley, maize, a set simulated possible future shocks oil prices, stock-to-use ratios, export restrictions. These are useful assess what could be consequences policy responses (export restrictions) or disruptions due virus (stock-to-use reductions), in context lower To generate these reactions, use Global Vector Auto Regression (GVAR) model where each modelled independently, connected through trade-based composite variables. We expand work wheat by introducing maize barley. results empirical indicate that fall may have contributed stability world grain early 2020, despite fears supply chain disruption. also note restrictions significantly increase such affect more than targeted commodity, significant linkages.