Ethanol and field crops: Is there a price connection? Andrea Bastianin a , Marzio Galeotti b,⇑ , Matteo Manera c a University of Milan and Fondazione Eni Enrico Mattei, Italy b University of Milan and IEFE-Bocconi, Italy c University of Milan-Bicocca and Fondazione Eni Enrico Mattei, Italy article info Article history: Received 26 January 2016 Received in revised form 20 May 2016 Accepted 30 June 2016 Available online 15 July 2016 Keywords: Ethanol Field crops Granger causality Forecasting Structural breaks abstract We analyze the relationship between the prices of ethanol, corn, soybeans, wheat and cattle in Nebraska, U.S. We focus on long-run price relations, short-run Granger causality, in-sample and out-of-sample pre- dictability linkages between returns on ethanol, field crops and cattle. Since the ethanol market has been subject to many policy interventions, our analysis takes structural breaks and parameter instabilities into account using modern statistical techniques. We find no evidence that ethanol returns Granger cause food price variations. Conversely, both in-sample and out-of-sample results suggest that ethanol is Granger caused and can be predicted by returns on corn. No linkages between ethanol and cattle are found. Ó 2016 Elsevier Ltd. All rights reserved. 1. Introduction In recent years agricultural commodities have been a source of concern because of the tendency of prices to increase and become more volatile. The popular press and reports from international and non-government organizations have been voicing the respon- sibility of the significant expansion of biofuel production in causing increases of food prices, thus putting at serious risk the plight of millions of poor. 1 This has sparked the ‘‘Food versus Fuel” debate. According to the underlying view, the introduction of biofuels has strengthened the linkages between fuel and agricultural markets. In particular, because of the very rapid expansion of U.S.-produced ethanol whose main input is corn, the increased conversion of maize into ethanol reduced the supplies of food and increased food prices. The boom of U.S. ethanol production has been largely policy- driven. The gasoline used in American cars nowadays contains up to 10% ethanol (E10). At the root of this is the Energy Policy Act (EPA) of 2005 which established a mandate known as the Renew- able Fuel Standard (RFS). The RFS program originally required 7.4 billion gallons of renewable fuel to be blended annually into gasoline by 2012, to help to reduce greenhouse-gas emissions and cutting oil imports. In 2007 the U.S. Congress passed the Energy Independence and Security Act (EISA) scaling up the RFS mandate to 13.2 billion gallons of corn-based ethanol annually by 2012 and to an unprecedented 36 billion gallons by 2022. 2 In this paper we study the relationship between the prices of ethanol, corn, soybeans, wheat and cattle in Nebraska from January 1987 through March 2012. Due to the very high correlation with national prices, this state is often used as a representative case study for the U.S. We begin by analysing the stochastic properties of the price series considered. The results of unit root tests indicate that field crops and cattle prices are integrated of order one. As to ethanol, its price can be best described as being stationary around a broken trend. The break date, June 2005, can be associated with major policy changes in the U.S. ethanol market since, as noted above, the EPA was first voted in April 2005 and finally signed into law in August of the same year. Next, we study the long-run price relationship between ethanol and the other commodities building on the bound testing approach recently proposed by Pesaran et al. (2001). This procedure allows the investigation of level relations even when cointegration cannot be established because prices have different orders of integration. The results reveal that in the post-break period there is evidence of a level relationship running from the price of corn to the price ethanol, but not vice versa. Finally, we determine whether ethanol has predictive power for the other price series, or vice versa. To this end we evaluate short-run relationships between returns on ethanol, field crops and cattle both in-sample and out-of-sample via Granger causality testing. As for the out-of-sample analysis, we study the predictive content of different models and compare them against some benchmark specifications. We find no evidence of Granger causal- ity and predictability running from ethanol to the other commodi- ties. On the contrary, returns on ethanol are predictable by using http://dx.doi.org/10.1016/j.foodpol.2016.06.010 0306-9192/Ó 2016 Elsevier Ltd. All rights reserved. ⇑ Corresponding author. 1 See e.g. ‘‘As high as an elephant’s eye”, The Economist October 16th, 2010. 2 See Janda et al. (2012) for a more detailed discussion of biofuel policies. Food Policy 63 (2016) 53–61 Contents lists available at ScienceDirect Food Policy journal homepage: www.elsevier.com/locate/foodpol