A dynamic analysis of causality between prices of corn, crude oil and ethanol

Papież, Monika (2014): A dynamic analysis of causality between prices of corn, crude oil and ethanol.

Abstract

The objective of the paper is to analyse causality between prices of corn, crude oil and ethanol. The analysis conducted in this paper is a dynamic one, and the data used consist of weekly futures prices of crude oil, corn, and ethanol from January 5, 2007 till April 11, 2014. The assessment of causal links between prices of corn, crude oil and ethanol is carried out with the use of rolling regression applied to augmented-VAR framework proposed by Toda and Yamamoto (1995). The application of the rolling regression procedures into the modified Wald (MWALD) causality test allows for the investigation of the persistence of stability in causal relations between analysed prices. The results obtained indicate that the linkages between energy prices and agricultural commodity prices change in the period analysed. The results of Granger causality tests reveal that in the analysed period the price of corn influences the price of energy (crude oil and ethanol). Also crude oil prices influence corn prices and ethanol prices. However, the influence of ethanol prices on crude oil prices and corn prices has not been observed.

• Item Type: MPRA Paper
• Language: English
• Keywords: Granger causality, rolling regression, Toda -Yamamoto tests, commodity prices.
• Subjects: C - Mathematical and Quantitative Methods > C3 - Multiple or Simultaneous Equation Models ; Multiple Variables > C32 - Time-Series Models ; Dynamic Quantile Regressions ; Dynamic Treatment Effect Models ; Diffusion Processes ; State Space Models; Q - Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q1 - Agriculture > Q13 - Agricultural Markets and Marketing ; Cooperatives ; Agribusiness; Q - Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q4 - Energy > Q41 - Demand and Supply ; Prices

References

Chen, S., Kuo, H., and Chen, C. (2010). Modeling the relationship between the oil price and global food prices. Applied Energy 87, 2517–2525.

Ciaian, P., and Kancs, A. (2011a). Food, energy and environment: is bioenergy the missing link? Food Policy 36, 571–580.

Ciaian, P., Kancs, A. (2011b). Interdependencies in the energy–bioenergy–food price systems: a cointegration analysis. Resource and Energy Economics 33, 326–348.

Dickey, D., and Fuller, W. (1979). Distribution of the estimators for autoregressive time series with a unit root. Journal of the American Statistical Association 74, 427–431.

Elliott, G., Rothenber, T.J., Stock, J.H., (1996). Efficient tests for an autoregressive unit root. Econometrica 64, 813–836.

Gardebroek, C., and Hernandez, M. A. (2013). Do energy prices stimulate food price volatility? Examining volatility transmission between US oil, ethanol and corn markets. Energy Economics 40, 119-129.

Haixia, W., and Shiping, L. (2013). Volatility spillovers in China’s crude oil, corn and fuel ethanol markets. Energy Policy 62, 878-886.

Harri, A., Nalley, L., and Hudson, D. (2009). The relationship between oil, exchange rates, and commodity prices. Journal of Agricultural and Applied Economics 41, 501–510.

Kilian, L., and Park, C. (2009). The impact of oil price shocks on the U.S. stock market. International Economic Review 50 1267-1287.

Kristoufek, L., Janda, K., and Zilberman, D. (2012). Mutual Responsiveness of Biofuels, Fuels and Food Prices. Working paper, Centre for Applied Macroeconomic Analysis. Australian National University, Canberra.

Kwiatkowski, D., Phillips, P.C.B., Schmidt, P., Shin, Y., (1992). Testing the null hypothesis of stationary against the alternative of a unit root. J. Econ. 54, 159–178.

McPhail, L. L. (2011). Assessing the impact of US ethanol on fossil fuel markets: A structural VAR approach. Energy Economics 33(6), 1177-1185.

Natalenov, V., Alam, M.J., McKenzie, A.M., and Van Huylenbroeck, G. (2011), Is there co-movement of agricultural commodities futures prices and crude oil? Energy Policy 39, 4971–4984.

Natanelov, V., McKenzie, A. M., and Van Huylenbroeck, G. (2013). Crude oil–corn–ethanol–nexus: A contextual approach. Energy Policy 63, 504-513.

Nazlioglu, S. (2011), World oil and agricultural commodity prices: evidence from nonlinear causality. Energy Policy 39, 2935–2943.

Nazlioglu, S., and Soytas, U. (2011). World oil prices and agricultural commodity prices: evidence from an emerging market. Energy Economics 33, 488–496.

Nazlioglu, S., and Soytas, U. (2012). Oil price, agricultural commodity prices, and the dollar: A panel cointegration and causality analysis. Energy Economics 34, 1098–1104.

Papież, M., and Śmiech, S. (2012), Causality in mean and variance between returns of crude oil and metal prices, agricultural prices and financial market prices. In: Proceedings of 30th International Conference Mathematical Methods in Economics (Ramík, J. and Stavárek, D. (eds.)), Karviná: Silesian University, School of Business Administration, 675-680.

Qiu, C., Colson, G., Escalante, C., and Wetzstein, M. (2012). Considering macroeconomic indicators in the food before fuel nexus. Energy Economics 34, 2021–2028.

Rambaldi, A.N., and Doran H.E. (1996). Testing for Granger non-causality in cointegrated system made easy. Working papers in Econometrics and Applied Statistics, 88, Department of Econometrics, University of New England.

Saghaian, S.H. (2010). The impact of the oil sector on commodity prices: correlation or causation? Journal of Agricultural and Applied Economics 42, 477–485.

Serra, T., Zilberman, D., Gil, J. M., and Goodwin, B. K. (2011). Nonlinearities in the US corn- ethanol- oil-gasoline price system. Agricultural Economics 42(1), 35-45.

Śmiech, S., and Papież, M. (2013). Fossil fuel prices, exchange rate, stock market: a dynamic causality analysis on the European market. Economics Letters 118, 199-202.

Toda, H. Y., and Yamamoto, T. (1995). Statistical inference in vector autoregressions with possibly integrated processes. Journal of Econometrics 66, 225-250.

Trujillo-Barrera, A., Mallory, M., and Garcia, P. (2012). Volatility Spillovers in US Crude Oil, Ethanol, and Corn Futures Markets. Journal of Agricultural and Resource Economics 37(2), 247–262.

Wixson, S.E., and Katchova, A.E. (2012). Price asymmetric relationships in commodity and energy markets. In: Paper presented at the 123rd European Association of Agricultural Economists' Seminar, Price Volatility and Farm Income Stabilisation, Dublin, February 23–24.

Zapata, H.O., and Rambaldi, A.N. (1997). Monte Carlo evidence on cointegration and causation. Oxford Bulletin of Economics and Statistics 59(2), 285-298.

Zhang, Z., Lohr, L., Escalante, C., and Wetzstein, M., (2009). Ethanol, corn, and soybean price relations in a volatile vehicle-fuels market. Energies 2(2), 320-339.

Zhang, Z., Lohr, L., Escalante, C., and Wetzstein, M., (2010). Food versus fuel: what do prices tell us? Energy Policy 38, 445–451.

Zivot, E., and Andrews, D., (1992). Further evidence of the Great Crash, the oil-price shock and the unit-root hypothesis. Journal of Business and Economic Statistics 10, 251-270.