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A Structural Approach to Disentangling Speculative and Fundamental Influences on the Price of Corn

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  • Etienne, Xiaoli L.
  • Irwin, Scott H.

Abstract

Corn prices experienced enormous volatility over the last decade. In this paper, we apply a structural vector autoregression model to quantify the relative importance of various contributing factors in driving corn price movements. The identification of structural parameters is achieved through a data-determined approach—the PC algorithm of Directed Acyclic Graphs. We find that, in general, unexpected shocks in aggregate global demand and speculative trading activities do not have a statistically significant effect on corn price movements. By contrast, shocks in the crude oil market have large immediate effects that persist in the long-run. The forecast error variance decomposition suggest that at the two-year horizon, variations in crude oil prices account for over 50% of the total corn forecast error variances. We also find that, consistent with theory, unexpected shocks in market-specific fundamentals also have large negative effects on price movements. In addition, unexpected residual shocks play an important role in corn price movement, especially in the short-run.

Suggested Citation

  • Etienne, Xiaoli L. & Irwin, Scott H., 2014. "A Structural Approach to Disentangling Speculative and Fundamental Influences on the Price of Corn," 2014 Conference, April 21-22, 2014, St. Louis, Missouri 285810, NCR-134/ NCCC-134 Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
    • Handle: RePEc:ags:n13414:285810
    DOI: 10.22004/ag.econ.285810
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