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Biofuels and Food Prices: Searching for the Causal Link

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  • Andrea Bastianin
  • Marzio Galeotti
  • Matteo Manera

Abstract

We analyze the relationship between the prices of ethanol, agricultural commodities and livestock in Nebraska, the U.S. second largest ethanol producer. The paper focuses on long-run relations and Granger causality linkages between ethanol and the other commodities. The analysis takes possible structural breaks into account and uses a set of techniques that allow to draw inferences about the existence of long-run relations and of short-run in-sample Granger causality and out-ofsample predictive ability. Even after taking breaks into account, evidence that the price of ethanol drives the price dynamics of the other commodities is extremely weak. It is concluded that, on the basis of a formal, comprehensive and rigorous causality analysis we do not find evidence in favour of the Food versus Fuel debate.

Suggested Citation

  • Andrea Bastianin & Marzio Galeotti & Matteo Manera, 2013. "Biofuels and Food Prices: Searching for the Causal Link," IEFE Working Papers 55, IEFE, Center for Research on Energy and Environmental Economics and Policy, Universita' Bocconi, Milano, Italy.
    • Handle: RePEc:bcu:iefewp:iefewp55
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    Cited by:

    1. Silva, E. & Lima, R., 2018. "Examining the relationship between biofuel and food crops markets in Brazil," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 275883, International Association of Agricultural Economists.
    2. Doshi, Amar & Pascoe, Sean & Coglan, Louisa & Rainey, Thomas J., 2016. "Economic and policy issues in the production of algae-based biofuels: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 64(C), pages 329-337.
    3. Carpio, Lucio Guido Tapia, 2019. "The effects of oil price volatility on ethanol, gasoline, and sugar price forecasts," Energy, Elsevier, vol. 181(C), pages 1012-1022.
    4. Gustavo Carvalho Santos & Flavio Barboza & Antônio Cláudio Paschoarelli Veiga & Mateus Ferreira Silva, 2021. "Forecasting Brazilian Ethanol Spot Prices Using LSTM," Energies, MDPI, vol. 14(23), pages 1-15, November.
    5. Pavla BLAHOVA & Karel JANDA & Ladislav KRISTOUFEK, 2014. "The perspectives for genetically modified cellulosic biofuels in the Central European conditions," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 60(6), pages 247-259.
    6. Eckert, C.T. & Frigo, E.P. & Albrecht, L.P. & Albrecht, A.J.P. & Christ, D. & Santos, W.G. & Berkembrock, E. & Egewarth, V.A., 2018. "Maize ethanol production in Brazil: Characteristics and perspectives," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 3907-3912.
    7. Štěpán Chrz & Karel Janda & Ladislav Krištoufek, 2014. "Modelování provázanosti trhů potravin, biopaliv a fosilních paliv [Modeling Interconnections within Food, Biofuel, and Fossil Fuel Markets]," Politická ekonomie, Prague University of Economics and Business, vol. 2014(1), pages 117-140.
    8. Bastianin, Andrea & Galeotti, Marzio & Manera, Matteo, 2014. "Causality and predictability in distribution: The ethanol–food price relation revisited," Energy Economics, Elsevier, vol. 42(C), pages 152-160.
    9. Filip, Ondrej & Janda, Karel & Kristoufek, Ladislav & Zilberman, David, 2019. "Food versus fuel: An updated and expanded evidence," Energy Economics, Elsevier, vol. 82(C), pages 152-166.
    10. Zhuo Chen & Bo Yan & Hanwen Kang, 2022. "Dynamic correlation between crude oil and agricultural futures markets," Review of Development Economics, Wiley Blackwell, vol. 26(3), pages 1798-1849, August.
    11. Karel Janda & Štěpán Krška & Jan Průša, 2014. "Česká fotovoltaická energie: modelový odhad nákladů na její podporu [Czech Photovoltaic Energy: Model Estimation of The Costs of its Support]," Politická ekonomie, Prague University of Economics and Business, vol. 2014(3), pages 323-346.
    12. Mohcine Bakhat & Klaas WŸrzburg, 2013. "Price Relationships of Crude Oil and Food Commodities," Working Papers fa06-2013, Economics for Energy.
    13. Karel Janda & Ladislav Kristoufek, 2019. "The relationship between fuel and food prices: Methods, outcomes, and lessons for commodity price risk management," CAMA Working Papers 2019-20, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    14. Sergio Adriani David & Claudio M. C. Inácio & José A. Tenreiro Machado, 2019. "Ethanol Prices and Agricultural Commodities: An Investigation of Their Relationship," Mathematics, MDPI, vol. 7(9), pages 1-25, August.
    15. Paulo Henrique Hoeckel & Augusto Mussi Alvim & José Pedro Pontes & João Dias, 2023. "The Ethanol Market and Its Relation to the Price of Agricultural Commodities," Energies, MDPI, vol. 16(6), pages 1-18, March.
    16. Karel Janda & Ladislav Krištoufek & Barbora Schererová & David Zilberman, 2021. "Price transmission in biofuel-related global agricultural networks," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 67(10), pages 399-408.
    17. Krzysztof Drachal, 2019. "Analysis of Agricultural Commodities Prices with New Bayesian Model Combination Schemes," Sustainability, MDPI, vol. 11(19), pages 1-23, September.
    18. Dar, William D., 2014. "Food versus energy: Crops for energy," 2014: Ethics, Efficiency and Food Security: Feeding the 9 Billion, Well, 26-28 August 2014 225568, Crawford Fund.
    19. Janda, Karel & Krska, Stepan & Prusa, Jan, 2014. "Odhad nákladů na podporu české fotovoltaické energie [The Estimation of the Cost of Promotion of the Czech Photovoltaic Energy]," MPRA Paper 54108, University Library of Munich, Germany.

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    More about this item

    Keywords

    Ethanol; Field Crops; Granger Causality; Forecasting; Structural Breaks;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • Q13 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Agricultural Markets and Marketing; Cooperatives; Agribusiness
    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources
    • Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting

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