Linear and nonlinear Granger causality between three grains: corn, soybean, wheat and two livestock commodities: live cattle and lean hogs, was verified. Weak evidence of linear causal relationships was found, supporting the results published in other studies. However, strong nonlinear causal relationships between grain and livestock returns were found, which had not yet been documented in the literature on this subject. The revealed relationships have different patterns and features, and in some cases, they arise from second moment dependencies, but nonlinearities of a different type were also found. Most of the discovered nonlinear relationships are bidirectional.
Al-Ayoubi Mireille, Chikhi Mohamed, Terraza Michel (2014): The Dynamic Relationship between Oil and Wheat Markets. Applied Economics and Finance, 1, - https://doi.org/10.11114/aef.v1i1.404
Alzahrani Mohammed, Masih Mansur, Al-Titi Omar (2014): Linear and non-linear Granger causality between oil spot and futures prices: A wavelet based test. Journal of International Money and Finance, 48, 175-201 https://doi.org/10.1016/j.jimonfin.2014.07.001
Baek E.G., Brock W.A. (1992): A General Test for Nonlinear Granger Causality: Bivariate Model. Technical report, Iowa State University and University of Wisconsin.
Bampinas G., Panagiotidis T. (2015): On the relationship between oil and gold before and after financial crisis: linear, nonlinear and time-varying causality testing. Studies in Nonlinear Dynamics & Econometrics, 19: 657–668.
Bekiros S.D. (2014): Exchange rates and fundamentals: co-movement, long-run relationships and short-run dynamics. Journal of Banking & Finance, 39: 117–134.
Bekiros Stelios D., Diks Cees G.H. (2008): The relationship between crude oil spot and futures prices: Cointegration, linear and nonlinear causality. Energy Economics, 30, 2673-2685 https://doi.org/10.1016/j.eneco.2008.03.006
Census of Agriculture 2007 (2009): USDA, Summary and State Data, Volume 1, Geographic Area Series, Part 51.
Chatrath A., Adrangi B., Dhanda K.K. (2002): Are commodity prices chaotic? Agricultural Economics, 27: 123–137.
Diks Cees, Panchenko Valentyn (2006): A new statistic and practical guidelines for nonparametric Granger causality testing. Journal of Economic Dynamics and Control, 30, 1647-1669 https://doi.org/10.1016/j.jedc.2005.08.008
Diks Cees, Wolski Marcin (2016): Nonlinear Granger Causality: Guidelines for Multivariate Analysis. Journal of Applied Econometrics, 31, 1333-1351 https://doi.org/10.1002/jae.2495
Gallant A. Ronald, Rossi Peter E., Tauchen George (1992): Stock Prices and Volume. Review of Financial Studies, 5, 199-242 https://doi.org/10.1093/rfs/5.2.199
Granger C.W.J. (1980): Testing for causality. Journal of Economic Dynamics and Control, 2, 329-352 https://doi.org/10.1016/0165-1889(80)90069-X
Hiemstra C., Jones J.D. (1994): Testing for linear and nonlinear Granger causality in the stock price volume relation. Journal of Finance, 49: 1639–1664.
Holt M. T., Craig L. A. (2006): Nonlinear Dynamics and Structural Change in the U.S. Hog--Corn Cycle: A Time-Varying STAR Approach. American Journal of Agricultural Economics, 88, 215-233 https://doi.org/10.1111/j.1467-8276.2006.00849.x
Kohzadi Nowrouz, Boyd Milton S. (1995): Testing for Chaos and Nonlinear Dynamics in Cattle Prices. Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, 43, 475-484 https://doi.org/10.1111/j.1744-7976.1995.tb00136.x
Kovács S., Huzsvai L., Balogh P. (2013): Investigating the long memory property of the Hungarian market pig prices by using detrended fluctuation analysis. Journal of Agricultural Informatics, 4: 1–9.
Malcolm S., Aillery M., Weinberg M. (2009): Ethanol and a changing agricultural landscape. Economic Research Report No. 86, Economic Research Service, USDA.
Nazlioglu Saban (2011): World oil and agricultural commodity prices: Evidence from nonlinear causality. Energy Policy, 39, 2935-2943 https://doi.org/10.1016/j.enpol.2011.03.001
Pozo V.F., Schroeder T.C. (2012): Price and volatility spillover between livestock and related commodity markets. In: Proceedings of Agricultural & Applied Economics Association’s Annual Meeting, Seattle, Washington, Aug 12–14, 2012.
Rosa F., Vasciaveo M. (2012): Agri-commodity price dynamics: the relationship between oil and agricultural market. In: Proceedings of International Association of Agricultural Economists Triennial Conference, Foz do Iguaçu, Brazil, Aug 18–24, 2012.
Tegle A. (2013): An explorative study of grain and meat price relationships. [Master thesis.] Norwegian University of Life Sciences, UMB School of Economics and Business, Ås.
Tejeda H.A., Goodwin B.K. (2011): Dynamic price relationships in the grain and cattle markets, pre and post-ethanol mandate. In: Proceedings of Agricultural & Applied Economics Association AAEA & NAREA Joint Annual Meeting, Pittsburgh, Pennsylvania, July 24–26, 2011.
Westcott P.C., Hoffman L.A. (1999): Price Determination for Corn and Wheat: The Role of Market Factors and Government Programs. Technical Bulletin No. 1878, Market and Trade Economics Division, Economic Research Service, USDA.
XU Shi-wei, LI Zhe-min, CUI Li-guo, DONG Xiao-xia, KONG Fan-tao, LI Gan-qiong (2012): Price Transmission in China's Swine Industry with an Application of MCM. Journal of Integrative Agriculture, 11, 2097-2106 https://doi.org/10.1016/S2095-3119(12)60468-7