Energy-agriculture market linkages: Asymmetric effects in the context of the Russia-Ukraine conflict

Research background: The study examines the impact of geopolitical tensions, in particular the Russia-Ukraine conflict, on agricultural commodity markets at a global level. The research focuses on the period from February 2021 to February 2024, a period characterized by significant economic instability due to the ongoing conflict. The research covers global agricultural commodity markets, focusing on three main categories: soft commodities, grains and livestock. Purpose of the article: The purpose of this paper is to examine the asymmetric interactions between crude oil and gas prices and agricultural commodity yields from February 2021 to February 2024. The study aims to analyze these interactions on a global scale, encompassing the world markets for soft commodities, grains and livestock. The research aims to provide insights into how geopolitical tensions, in particular the Russia-Ukraine conflict, are affecting these global agricultural markets and their linkages to energy prices. Methods: This study uses the Nonlinear Autoregressive Distributed Lag (NARDL) model to analyze the asymmetric interactions between crude oil and gas prices and agricultural commodity yields, capturing both short-run and long-run asymmetries. The study divides the sample period into three distinct sub-periods of the Russia-Ukraine conflict, allowing for a detailed examination of how energy price fluctuations affect agricultural commodities under different economic conditions. Findings & value added: Our main findings are the following: (1) positive correlations with oil and gas prices for soft commodities and grains; (2) weaker but significant relationship for livestock; (3) short-term asymmetries are particularly pronounced during periods of high economic turbulence (e.g. Russia-Ukraine conflict); (4) grain and livestock yields show stronger responses to negative oil price shocks; (5) no long-run equilibrium relationship found by cointegration tests. The present paper is unique in combining the Nonlinear Autoregressive Distributed Lag (NARDL) model with a detailed analysis of the Russia-Ukraine conflict, providing unprecedented insights into the asymmetric impact of geopolitical tensions on agricultural commodity markets, which is essential for understanding market dynamics during crises.