Food versus Fuel: Causality and Predictability in Distribution
This paper examines the relationship between biofuels and commodity food prices in the U.S. from a new perspective. While a large body of literature has tried to explain the linkages between sample means and volatilities associated with ethanol and agricultural price returns, little is known about their whole distributions. We focus on predictability in distribution by asking whether ethanol returns can be used to forecast different parts of field crops 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 distribution.
|Date of creation:||Mar 2013|
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- Giuseppe Piroli & Pavel Ciaian & d'Artis Kancs, 2011.
"Land Use Change Impacts of Biofuels: Near-VAR Evidence from the US,"
EERI Research Paper Series
EERI_RP_2011_11, Economics and Econometrics Research Institute (EERI), Brussels.
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- Peter C. B. Phillips & Jun Yu, 2011.
"Dating the timeline of financial bubbles during the subprime crisis,"
Econometric Society, vol. 2(3), pages 455-491, November.
- Peter C. B. Phillips & Jun Yu, 2009. "Dating the Timeline of Financial Bubbles During the Subprime Crisis," Finance Working Papers 23051, East Asian Bureau of Economic Research.
- Peter C. B. Phillips & Jun Yu, 2010. "Dating the Timeline of Financial Bubbles during the Subprime Crisis," Cowles Foundation Discussion Papers 1770, Cowles Foundation for Research in Economics, Yale University.
- Peter C. B. Phillips & Jun Yu, 2009. "Dating the Timeline of Financial Bubbles During the Subprime Crisis," Working Papers 18-2009, Singapore Management University, School of Economics.
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