This paper examines the relationship between biofuels, field crops and cattle prices in the U.S. from a new perspective. We focus on predictability in distribution by asking whether ethanol returns can be used to forecast different parts of field crops and cattle returns distribution, or vice versa. Density forecasts are constructed using Conditional Autoregressive Expectile models estimated with Asymmetric Least Squares. Forecast evaluation relies on quantile-weighed scoring rules, which identify regions of the distribution of 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 or cattle returns distributions. © 2013 Elsevier B.V.
Bastianin, A., Galeotti, M., Manera, M. (2014). Causality and predictability in distribution: the ethanol-food price relation revisited. ENERGY ECONOMICS, 42, 152-160 [10.1016/j.eneco.2013.12.014].
Causality and predictability in distribution: the ethanol-food price relation revisited
BASTIANIN, ANDREA;MANERA, MATTEO
2014
Abstract
This paper examines the relationship between biofuels, field crops and cattle prices in the U.S. from a new perspective. We focus on predictability in distribution by asking whether ethanol returns can be used to forecast different parts of field crops and cattle returns distribution, or vice versa. Density forecasts are constructed using Conditional Autoregressive Expectile models estimated with Asymmetric Least Squares. Forecast evaluation relies on quantile-weighed scoring rules, which identify regions of the distribution of 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 or cattle returns distributions. © 2013 Elsevier B.V.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.