Recent work with graphical methods for inductive causal inference with observational econometric data is reviewed and compared with earlier work. Two alternative algorithms are described. Caveats on applications are discussed.

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This study examines causal mechanisms linking exchange rates and prices of oil and ethanol to the 2006-08 price surge in corn, soybeans and wheat, as well as identifies the relative importance of the selected factors to the price spikes using the graphical causal method and forecast error variance decomposition (FEVD). Results suggest that the interactions among the crop prices are more important than other causal factors in explaining the price hikes. We also find that significant growth in the use of corn for biofuel production and hence increased corn prices play dominant roles in price setting among the major crops.

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