Despite extensive literature on contributing factors to the high commodityprices and volatility in the recent years, few have examined these causalfactors together in one analysis. We quantify empirically the relativeimportance of three factors: global demand, speculation, and energyprices/policy in explaining corn price volatility. A structural vectorauto-regression model is developed and variance decomposition is applied tomeasure 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.

A time-varying-parameter VAR for real output growth and inflation is estimated with annual U.S. series dating back to 1870. Volatility for both variables rises quickly with World War I and its aftermath, stays high until the end of World War II, and drops rapidly until the 1960s. This Postwar Moderation yields the largest decline in volatilities, surpassing the Great Moderation. Conditional on temporary shocks, inflation and output growth are positively correlated. Our model implies that aggregate demand played a key role in inflation volatility fluctuations. Conversely, the two variables are negatively correlated conditional on permanent shocks. Our model suggests that aggregate supply played an important role in output volatility fluctuations. Most impulse responses support an aggregate supply interpretation for permanent shocks. However, before World War I, a permanent increase in output raised the price level at longer horizons, and these responses are frequently statistically significant. This evidence supports the hypothesis that aggregate demand had a long-run positive effect on output during the pre–World War I period.