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 lags related to each covariate in the model. To test the effectiveness of this analytical tool at dealing with the issues related to agri-food economy, we applied a VAR analysis on prices of major food and energy commodities (oil and biodiesel) referring to the period January 2000–December 2012. Our results identified statistically significant intertemporal relationships between the price of corn, soybean oil, rapeseed and oil, and suggested the direction of these relationships; we could conclude that the price of corn and soybeans are influenced mainly in the energy market. Moreover, we focused on the United States market and we set as variables the share of commodities used for the production of biofuels: 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 model, therefore, deals adequately with data and issues of the agri-food system and provides an analytical basis to develop economic policies that can take into account the complexity of the global food system.
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Notes
- 1.
The reference period applies to the prices of all commodities analyzed, with the only exception being the biodiesel prices, which are only available from July 2006, so VAR built with these data as variables were constructed considering only the period from 2006 to 2012.
- 2.
The time series used for the analysis of corn and ethanol ranged from January 2000 to December 2012, while the period considered for the analysis of soy was from July 2006 to December 2012. This choice is based on the availability of data.
- 3.
The statistical software used is R 2.14.2; analysis was implemented using the R packages Tseries and VAR.
- 4.
Time series is from July 2006 to December 2012, due to the availability of data.
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Acknowledgments
All authors would like to acknowledge Professor Roberto Fanfani of the Department of Statistical Sciences “P. Fortunati” (UNIBO) for his precious advice and help, and mostly for being a mentor for all of us.
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Leucci, A.C., Ghinoi, S., Sgargi, D., Wesz Junior, V.J. (2014). VAR Models for Dynamic Analysis of Prices in the Agri-food System. In: Zopounidis, C., Kalogeras, N., Mattas, K., van Dijk, G., Baourakis, G. (eds) Agricultural Cooperative Management and Policy. Cooperative Management. Springer, Cham. https://doi.org/10.1007/978-3-319-06635-6_1
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