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Variation and links among food and energy international prices. An analysis through VAR models from 2000 to 2012

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  • Leucci, A. C.
  • Ghinoi, S.
  • Sgargi, D.
  • Wesz, V. J., Jr.
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    Abstract

    An adequate understanding of the dynamics that characterize the agri-food market is fundamental for the development of really efficient economic policies, especially after the two recent hikes in the prices of food commodities. The econometric literature provides today advanced analysis tools such as VAR models: these models are based on a system of equations in which each variable is regressed on a set of deterministic variables, on a number of l delays related to each covariate in the model. To test the effectiveness of this analytical tool at dealing with the issues related to agrifood economy we applied a VAR analysis on prices of major food and energy commodities (oil and biodiesel) referred to the period January 2005-December 2012. Our results identified statistically significant intertemporal relationships between the price of corn, soybeans, rapeseed and oil, and suggested the direction of these relationships; we could conclude that the price of corn and soybeans are generated in the energy market only. Moreover, we used as variables the share of commodities used for the production of biofuels, and we could observe that important alterations on the food market are due to the convenience in producing ethanol and biodiesel, since the portion of the crops used for energy is in direct competition with that devoted to the feeding. This kind of models, therefore, deal adequately with datas and issues of the agri-food system and provide an analytical basis to develop economic policies that take into account the complexity of the global food system.

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    Bibliographic Info

    Paper provided by Italian Association of Agricultural and Applied Economics (AIEAA) in its series 2013 Second Congress, June 6-7, 2013, Parma, Italy with number 149923.

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    Date of creation: Jun 2013
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    Handle: RePEc:ags:aiea13:149923

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    Related research

    Keywords: alternative energy source; biofuels; var; Demand and Price Analysis; International Development; C32; Q16; Q42;

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    1. Manuel Frondel & Jörg Peters, 2005. "Biodiesel: A New Oildorado?," RWI Discussion Papers 0036, Rheinisch-Westfälisches Institut für Wirtschaftsforschung.
    2. Thomas W. Hertel & Jayson Beckman, 2011. "Commodity Price Volatility in the Biofuel Era: An Examination of the Linkage between Energy and Agricultural Markets," NBER Chapters, in: The Intended and Unintended Effects of U.S. Agricultural and Biotechnology Policies, pages 189-221 National Bureau of Economic Research, Inc.
    3. Zibin Zhang & Luanne Lohr & Cesar Escalante & Michael Wetzstein, 2009. "Ethanol, Corn, and Soybean Price Relations in a Volatile Vehicle-Fuels Market," Energies, MDPI, Open Access Journal, vol. 2(2), pages 320-339, June.
    4. Teresa Serra & David Zilberman & José M. Gil & Barry K. Goodwin, 2011. "Nonlinearities in the U.S. corn‐ethanol‐oil‐gasoline price system," Agricultural Economics, International Association of Agricultural Economists, vol. 42(1), pages 35-45, 01.
    5. Hochman, Gal & Rajagopal, Deepak & Timilsina, Govinda & Zilberman, David, 2011. "The role of inventory adjustments in quantifying factors causing food price inflation," Policy Research Working Paper Series 5744, The World Bank.
    6. Trostle, Ronald, 2008. "Factors Contributing to Recent Increases in Food Commodity Prices (PowerPoint)," Seminars 43902, USDA Economists Group.
    7. Gal Hochman & Scott Kaplan & Deepak Rajagopal & David Zilberman, 2012. "Biofuel and Food-Commodity Prices," Agriculture, MDPI, Open Access Journal, vol. 2(3), pages 272-281, September.
    8. David Zilberman & Gal Hochman & Deepak Rajagopal & Steve Sexton & Govinda Timilsina, 2013. "The Impact of Biofuels on Commodity Food Prices: Assessment of Findings," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 95(2), pages 275-281.
    9. Granger, C W J, 1969. "Investigating Causal Relations by Econometric Models and Cross-Spectral Methods," Econometrica, Econometric Society, vol. 37(3), pages 424-38, July.
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