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Food versus Fuel: Causality and Predictability in Distribution

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  • Andrea Bastianin
  • Marzio Galeotti
  • Matteo Manera

Abstract

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.

Suggested Citation

  • Andrea Bastianin & Marzio Galeotti & Matteo Manera, 2013. "Food versus Fuel: Causality and Predictability in Distribution," Working Papers 241, University of Milano-Bicocca, Department of Economics, revised Mar 2013.
  • Handle: RePEc:mib:wpaper:241
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    2. da Silveira, Rodrigo Lanna F. & Mattos, Fabio L., 2015. "Price And Volatility Transmission In Livestock And Grain Markets: Examining The Effect Of Increasing Ethanol Production Across Countries," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205684, Agricultural and Applied Economics Association.
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    6. Zhu, Bo & Lin, Renda & Deng, Yuanyue & Chen, Pingshe & Chevallier, Julien, 2021. "Intersectoral systemic risk spillovers between energy and agriculture under the financial and COVID-19 crises," Economic Modelling, Elsevier, vol. 105(C).
    7. 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.
    8. Bastianin, Andrea & Galeotti, Marzio & Manera, Matteo, 2016. "Ethanol and field crops: Is there a price connection?," Food Policy, Elsevier, vol. 63(C), pages 53-61.
    9. Amar, Amine Ben & Goutte, Stéphane & Isleimeyyeh, Mohammad & Benkraiem, Ramzi, 2022. "Commodity markets dynamics: What do cross-commodities over different nearest-to-maturities tell us?," International Review of Financial Analysis, Elsevier, vol. 82(C).
    10. Ahmadi, Maryam & Bashiri Behmiri, Niaz & Manera, Matteo, 2016. "How is volatility in commodity markets linked to oil price shocks?," Energy Economics, Elsevier, vol. 59(C), pages 11-23.
    11. 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.
    12. Ben Amar, Amine & Goutte, Stéphane & Isleimeyyeh, Mohammad, 2022. "Asymmetric cyclical connectedness on the commodity markets: Further insights from bull and bear markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 85(C), pages 386-400.
    13. 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.
    14. 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.
    15. Troster, Victor & Shahbaz, Muhammad & Uddin, Gazi Salah, 2018. "Renewable energy, oil prices, and economic activity: A Granger-causality in quantiles analysis," Energy Economics, Elsevier, vol. 70(C), pages 440-452.
    16. 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.
    17. 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.
    18. Ladislav Kristoufek & Karel Janda & David Zilberman, 2015. "Co-movements of Ethanol Related Prices: Evidence from Brazil and the USA," CAMA Working Papers 2015-11, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    19. Kang, Sang Hoon & Tiwari, Aviral Kumar & Albulescu, Claudiu Tiberiu & Yoon, Seong-Min, 2019. "Exploring the time-frequency connectedness and network among crude oil and agriculture commodities V1," Energy Economics, Elsevier, vol. 84(C).
    20. Bilgili, Faik & Koçak, Emrah & Kuşkaya, Sevda & Bulut, Ümit, 2020. "Estimation of the co-movements between biofuel production and food prices: A wavelet-based analysis," Energy, Elsevier, vol. 213(C).
    21. Sarwar, Muhammad Nadeem & Hussain, Hamid & Maqbool, Muhammad Bilal, 2020. "Pass through effects of oil price on food and non-food prices in Pakistan: A nonlinear ARDL approach," Resources Policy, Elsevier, vol. 69(C).
    22. Yahya, Muhammad & Dutta, Anupam & Bouri, Elie & Wadström, Christoffer & Uddin, Gazi Salah, 2022. "Dependence structure between the international crude oil market and the European markets of biodiesel and rapeseed oil," Renewable Energy, Elsevier, vol. 197(C), pages 594-605.
    23. Zingbagba, Mark & Nunes, Rubens & Fadairo, Muriel, 2020. "The impact of diesel price on upstream and downstream food prices: Evidence from São Paulo," Energy Economics, Elsevier, vol. 85(C).
    24. 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

    Biofuels; Ethanol; Field Crops; Density Forecasting; Granger Causality; Quantiles;
    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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