Revisiting the Oil and Food Prices Dynamics: A Time Varying Approach

Abstract

Given the cyclicality of energy and food commodity prices influenced by global macroeconomic uncertainties, there is a need to provide appropriate measures for understanding the predictive relationship between energy and food commodities. This study revisits the dynamics of oil and food prices using Shi et al. (J Financ Econom 18:158–180, 2020) bootstrapped time-varying Granger causality method to identify and date-stamp causal changes in the predictive effects between oil and food markets, while considering homoscedasticity and heteroscedasticity assumptions. Our results reveal bidirectional and feedback influences between Brent oil and six food commodity prices: corn, rice, sugar, coffee, meat, and palm oil. These influences align with critical global events such as the mid-1990s Asian financial crisis, the early 2000s recession, the 2000s energy crisis, the 2014 oil price crisis, the GFC and food crisis of 2008, the 2020 oil-price war, and the COVID-19 pandemic. Additionally, we observed a causal effect running from wheat and soybean prices to Brent oil prices, highlighting the importance of the predictive power of food prices in the trajectory of oil prices during periods of global events. Longer episodes of Granger causality from food price to oil price were date-stamped across the algorithms. The study suggests that global economic events and crises can affect the relationship between prices in different markets, indicating that the ability to predict prices based on information from another market may change during times of economic and financial instability. The research has a number of practical implications.