Food Versus Fuel: Causality and Predictability in Distribution

Abstract

This paper examines the relationship between biofue ls and commodity food prices in the U.S. from a new perspective. While a large body of liter ature has tried to explain the linkages between sample means and volatilities associated with ethan ol and agricultural price returns, little is known about their whole distributions. We focus on predic tability in distribution by asking whether ethanol returns can be used to forecast different p arts of field crops returns distribution, or vice versa. Density forecasts are constructed using Cond itional Autoregressive Expectile models estimated with Asymmetric Least Squares. Forecast evaluation relies on quantile-weighed scoring rules, which identify regions of the distribution o f interest to the analyst. Results show that both the centre and the left tail of the ethanol returns distribution can be predicted by using field crops returns. On the contrary, there is no evidence that ethanol can be used to forecast any region of the field crops distribution.