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Disentangling Corn Price Volatility: The Role of Global Demand, Speculation, and Energy

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  • McPhail, Lihong Lu
  • Du, Xiaodong
  • Muhammad, Andrew

Abstract

Despite extensive literature on contributing factors to the high commodity prices and volatility in the recent years, few have examined these causal factors together in one analysis. We quantify empirically the relative importance of three factors: global demand, speculation, and energy prices/policy in explaining corn price volatility. A structural vector auto-regression model is developed and variance decomposition is applied to measure the contribution of each factor in explaining corn price variation. We find that speculation is important, but only in the short run. However, in the long run, energy is the most important followed by global demand.

Suggested Citation

  • McPhail, Lihong Lu & Du, Xiaodong & Muhammad, Andrew, 2012. "Disentangling Corn Price Volatility: The Role of Global Demand, Speculation, and Energy," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 44(3), pages 401-410, August.
  • Handle: RePEc:cup:jagaec:v:44:y:2012:i:03:p:401-410_00
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    References listed on IDEAS

    as
    1. Xiaodong Du and Lihong Lu McPhail, 2012. "Inside the Black Box: the Price Linkage and Transmission between Energy and Agricultural Markets," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2).
    2. Teguh Dartanto & Usman, 2011. "Volatility of World Soybean Prices, Import Tariffs and Poverty in Indonesia," Margin: The Journal of Applied Economic Research, National Council of Applied Economic Research, vol. 5(2), pages 139-181, May.
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    More about this item

    JEL classification:

    • Q11 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Aggregate Supply and Demand Analysis; Prices
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • G2 - Financial Economics - - Financial Institutions and Services
    • Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy

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