Agricultural Commodity Price Volatility and Its Macroeconomic Determinants: A GARCH-MIDAS Approach

Abstract

This paper investigates the main drivers of the agricultural commodity price volatility using the GARCH-MIDAS model of Engel et al. (2013), a new class of component models that allows for isolating the low-frequency component of volatility and taking into consideration macroeconomic factors via mixed data sampling. We show that modelling the agricultural price volatility as the product of high and low frequency components is more efficient than filtering it through a standard GARCH(1,1) model. After combing wheat, corn and soybean daily prices with monthly market specific and common macroeconomic drivers over the period 1986-2012, it appears that supply-demand indicators and conventional speculation proxies are crucial in explaining the low-frequency component of volatility while monetary factors and energy markets play significant but less important role. Nevertheless, when we consider only the period following the recent price spikes (2006-2012), the monetary factors – especially interest rate – become essential to describe agricultural price fluctuations, suggesting also that the heterogeneity in the effects of the drivers on different crops is decreasing.