1. VAR Models for Dynamic Analysis of Prices in the Agri-food System
- Author
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Stefano Ghinoi, V. J. Wesz Junior, D. Sgargi, Anna Caterina Leucci, Anna Caterina, Leucci, Stefano, Ghinoi, Daria, Sgargi, and Valdemar Joao, Wesz Junior
- Subjects
Competition (economics) ,Variable (computer science) ,Biodiesel ,Granger causality ,Biofuel ,Economics ,Econometrics ,Food systems ,Production (economics) ,VAR models, alternative energy source, biofuels ,Energy market - 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.
- Published
- 2014
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