Despite extensive literature on contributing factors to the high commodity prices and volatility
in the recent years, few have examined these causal factors together in one analysis.We
quantify empirically the relative importance of three factors: global demand, speculation, and
energy prices/policy in explaining corn price volatility. A structural vector auto-regression
model is developed and variance decomposition is applied to measure the contribution of
each factor in explaining corn price variation. We find that speculation is important, but only
in the short run. However, in the long run, energy is the most important followed by global
demand.
