The interconnections of agriculture and energy markets have increased through the rise in the new biofuel agribusinesses and the oil-ethanol-corn linkages. The question is whether these linkages have a causal structure by which oil prices affect commodity prices and through these links, instability is transferred from energy markets to already volatile agricultural markets. In this article, we present empirical results using contemporary time-series analysis and Granger causality supplemented by a directed graph theory modeling approach to identify the links and plausible contemporaneous causal structures among energy and commodity variables. The results show that although there is a strong correlation among oil and commodity prices, the evidence for a causal link from oil to commodity prices is mixed.

The behavior of agricultural commodity markets can arguably result in markedly asymmetric price cycles, that is, downward cycles of substantially different length and breadth than upward cycles. This study assesses whether asymmetric-cycle models can enhance the understanding of the dynamics and provide for a better forecasting of U.S. soybeans and Brazilian coffee prices. The forecasts from asymmetric cycle models are found to be substantially mode precise than those obtained from standard autoregressive models. The asymmetric cycle models also provide useful insights on the markedly different dynamics of the upward vs. the downward cycles exhibited by the prices of these two commodities.