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Do energy prices stimulate food price volatility? Examining volatility transmission between US oil, ethanol and corn markets

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  • Hernandez, Manuel A.
  • Gardebroek, Cornelis

Abstract

This paper examines volatility transmission in oil, ethanol and corn prices in the United States between 1997 and 2011. We follow a multivariate GARCH approach to evaluate the level of interdependence and the dynamics of volatility across these markets. The estimation results indicate a higher interaction between ethanol and corn markets in recent years, particularly after 2006 when ethanol became the sole alternative oxygenate for gasoline. We only observe, however, significant volatility spillovers from corn to ethanol prices but not the converse. We also do not find major cross-volatility effects from oil to corn markets. The results do not provide evidence of volatility in energy markets stimulating price volatility in grain markets.

Suggested Citation

  • Hernandez, Manuel A. & Gardebroek, Cornelis, 2012. "Do energy prices stimulate food price volatility? Examining volatility transmission between US oil, ethanol and corn markets," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 124583, Agricultural and Applied Economics Association.
    • Handle: RePEc:ags:aaea12:124583
    DOI: 10.22004/ag.econ.124583
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    1. Sorda, Giovanni & Banse, Martin & Kemfert, Claudia, 2010. "An overview of biofuel policies across the world," Energy Policy, Elsevier, vol. 38(11), pages 6977-6988, November.
    2. Bruce A. Babcock, 2008. "Distributional Implications of U.S. Ethanol Policy ," Review of Agricultural Economics, Agricultural and Applied Economics Association, vol. 30(3), pages 533-542.
    3. van Dijk, Dick & Osborn, Denise R. & Sensier, Marianne, 2005. "Testing for causality in variance in the presence of breaks," Economics Letters, Elsevier, vol. 89(2), pages 193-199, November.
    4. Harry de Gorter & David R. Just, 2008. "Water in the U.S. Ethanol Tax Credit and Mandate: Implications for Rectangular Deadweight Costs and the Corn-Oil Price Relationship," Review of Agricultural Economics, Agricultural and Applied Economics Association, vol. 30(3), pages 397-410.
    5. Teresa Serra & David Zilberman & José Gil, 2011. "Price volatility in ethanol markets," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 38(2), pages 259-280, June.
    6. Engle, Robert F. & Kroner, Kenneth F., 1995. "Multivariate Simultaneous Generalized ARCH," Econometric Theory, Cambridge University Press, vol. 11(1), pages 122-150, February.
    7. Serra, Teresa, 2011. "Volatility spillovers between food and energy markets: A semiparametric approach," Energy Economics, Elsevier, vol. 33(6), pages 1155-1164.
    8. Christopher Gilbert & Wyn Morgan, 2010. "Has food price volatility risen?," Department of Economics Working Papers 1002, Department of Economics, University of Trento, Italia.
    9. Manuel A. Hernandez & Raul Ibarra & Danilo R. Trupkin, 2014. "How far do shocks move across borders? Examining volatility transmission in major agricultural futures markets," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 41(2), pages 301-325.
    10. Byrne, Joseph P. & Fazio, Giorgio & Fiess, Norbert, 2013. "Primary commodity prices: Co-movements, common factors and fundamentals," Journal of Development Economics, Elsevier, vol. 101(C), pages 16-26.
    11. Marc Lavielle & Eric Moulines, 2000. "Least‐squares Estimation of an Unknown Number of Shifts in a Time Series," Journal of Time Series Analysis, Wiley Blackwell, vol. 21(1), pages 33-59, January.
    12. Fiorentini, Gabriele & Sentana, Enrique & Calzolari, Giorgio, 2003. "Maximum Likelihood Estimation and Inference in Multivariate Conditionally Heteroscedastic Dynamic Regression Models with Student t Innovations," Journal of Business & Economic Statistics, American Statistical Association, vol. 21(4), pages 532-546, October.
    13. Luc Bauwens & Sébastien Laurent & Jeroen V. K. Rombouts, 2006. "Multivariate GARCH models: a survey," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(1), pages 79-109, January.
    14. Du, Xiaodong & Yu, Cindy L. & Hayes, Dermot J., 2011. "Speculation and volatility spillover in the crude oil and agricultural commodity markets: A Bayesian analysis," Energy Economics, Elsevier, vol. 33(3), pages 497-503, May.
    15. Nazlioglu, Saban & Erdem, Cumhur & Soytas, Ugur, 2013. "Volatility spillover between oil and agricultural commodity markets," Energy Economics, Elsevier, vol. 36(C), pages 658-665.
    16. Long, Xiangdong & Su, Liangjun & Ullah, Aman, 2011. "Estimation and Forecasting of Dynamic Conditional Covariance: A Semiparametric Multivariate Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(1), pages 109-125.
    17. Luchansky, Matthew S. & Monks, James, 2009. "Supply and demand elasticities in the U.S. ethanol fuel market," Energy Economics, Elsevier, vol. 31(3), pages 403-410, May.
    18. Kausik Chaudhuri, 2001. "Long-run prices of primary commodities and oil prices," Applied Economics, Taylor & Francis Journals, vol. 33(4), pages 531-538.
    19. Benavides Guillermo & Capistrán Carlos, 2009. "A Note on the Volatilities of the Interest Rate and the Exchange Rate Under Different Monetary Policy Instruments: Mexico 1998-2008," Working Papers 2009-10, Banco de México.
    20. Bollerslev, Tim, 1990. "Modelling the Coherence in Short-run Nominal Exchange Rates: A Multivariate Generalized ARCH Model," The Review of Economics and Statistics, MIT Press, vol. 72(3), pages 498-505, August.
    21. Alghalith, Moawia, 2010. "The interaction between food prices and oil prices," Energy Economics, Elsevier, vol. 32(6), pages 1520-1522, November.
    22. Seth Meyer & Wyatt Thompson, 2010. "Demand Behavior and Commodity Price Volatility Under Evolving Biofuel Markets and Policies," Natural Resource Management and Policy, in: Madhu Khanna & Jürgen Scheffran & David Zilberman (ed.), Handbook of Bioenergy Economics and Policy, chapter 0, pages 133-148, Springer.
    23. Helen Higgs & Andrew Worthington, 2004. "Transmission of returns and volatility in art markets: a multivariate GARCH analysis," Applied Economics Letters, Taylor & Francis Journals, vol. 11(4), pages 217-222.
    24. Andrew Worthington & Helen Higgs, 2004. "Transmission of equity returns and volatility in Asian developed and emerging markets: a multivariate GARCH analysis," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 9(1), pages 71-80.
    25. Karolyi, G Andrew, 1995. "A Multivariate GARCH Model of International Transmissions of Stock Returns and Volatility: The Case of the United States and Canada," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(1), pages 11-25, January.
    26. 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, January.
    27. Rajagopal, Deepak & Zilberman, David, 2007. "Review of environmental, economic and policy aspects of biofuels," Policy Research Working Paper Series 4341, The World Bank.
    28. Tse, Y K & Tsui, Albert K C, 2002. "A Multivariate Generalized Autoregressive Conditional Heteroscedasticity Model with Time-Varying Correlations," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(3), pages 351-362, July.
    29. Carrasco, Marine & Chen, Xiaohong, 2002. "Mixing And Moment Properties Of Various Garch And Stochastic Volatility Models," Econometric Theory, Cambridge University Press, vol. 18(1), pages 17-39, February.
    30. Kelvin Balcombe & George Rapsomanikis, 2008. "Bayesian Estimation and Selection of Nonlinear Vector Error Correction Models: The Case of the Sugar-Ethanol-Oil Nexus in Brazil," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 90(3), pages 658-668.
    31. Ronald A. Babula & Agapi Somwaru, 1992. "Dynamic impacts of a shock in crude oil price on agricultural chemical and fertilizer prices," Agribusiness, John Wiley & Sons, Ltd., vol. 8(3), pages 243-252.
    32. Zibin Zhang & Luanne Lohr & Cesar Escalante & Michael Wetzstein, 2009. "Ethanol, Corn, and Soybean Price Relations in a Volatile Vehicle-Fuels Market," Energies, MDPI, vol. 2(2), pages 1-20, June.
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    Keywords

    Demand and Price Analysis; Financial Economics;

    JEL classification:

    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources
    • Q11 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Aggregate Supply and Demand Analysis; Prices
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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