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Causality and predictability in distribution: The ethanol–food price relation revisited

Andrea Bastianin (), Marzio Galeotti () and Matteo Manera ()

Energy Economics, 2014, vol. 42, issue C, 152-160

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.

Keywords: Biofuels; Ethanol; Field crops; Density forecasting; Granger causality; Quantiles (search for similar items in EconPapers)
JEL-codes: C22 C53 Q13 Q42 Q47 (search for similar items in EconPapers)
Date: 2014
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Related works:
Working Paper: Food versus Fuel: Causality and Predictability in Distribution (2013) Downloads
Working Paper: Food versus Fuel: Causality and Predictability in Distribution (2013) Downloads
Working Paper: Food versus Fuel: Causality and Predictability in Distribution (2013) Downloads
Working Paper: Food versus Fuel: Causality and Predictability in Distribution (2013) Downloads
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