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Price Dynamics in Food-Energy Market in China


  • Yang, Juan
  • Leatham, David J.


In this paper we examine price transmission for major agriculture (food) and energy products in China for the years 2004 to 2010. The Error correction model (ECM) and the directed acyclic graphs (DAG) are applied to identify price dynamics among these six variables: rice, wheat, corn, coal, crude oil and ethanol. Our major contribution to the existing literature lies in two perspectives: 1) We firstly employ the error correction model with directed acyclic graphs to study the price dynamics in the food-energy sector in China. The advantage of this approach is that it can offer data-determined (as opposed to a subjectively-determined) pattern for the contemporaneous causal flows which are then used to conduct a more reliable innovation accounting analysis of the ECM shocks. 2) We uncover a recent price transmission among major food-energy markets in China and provide a broad understanding of price adjustments across markets. The result indicates that in the short run, crop price is driving the energy price, while in the long run, crude oil is the leading factor that drives food and other energy prices. We also find that ethanol price is neither in the long-run equilibrium nor responding to deviation from long-run equilibrium. It supports that under the current policy, Chinese government has done well to prevent the ethanol price driving up the food price. The biofuel production is not the cause of rising food price in China.

Suggested Citation

  • Yang, Juan & Leatham, David J., 2012. "Price Dynamics in Food-Energy Market in China," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 124631, Agricultural and Applied Economics Association.
  • Handle: RePEc:ags:aaea12:124631

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    1. JunJie Wu & Richard M. Adams & Catherine L. Kling & Katsuya Tanaka, 2004. "From Microlevel Decisions to Landscape Changes: An Assessment of Agricultural Conservation Policies," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 86(1), pages 26-41.
    2. Christian Langpap & Ivan Hascic & JunJie Wu, 2008. "Protecting Watershed Ecosystems through Targeted Local Land Use Policies," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 90(3), pages 684-700.
    3. William Breffle & Edward Morey & Jennifer Thacher, 2011. "A Joint Latent-Class Model: Combining Likert-Scale Preference Statements With Choice Data to Harvest Preference Heterogeneity," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 50(1), pages 83-110, September.
    4. Ivan Hascic & JunJie Wu, 2006. "Land Use and Watershed Health in the United States," Land Economics, University of Wisconsin Press, vol. 82(2), pages 214-239.
    5. Christian Langpap & JunJie Wu, 2008. "Predicting the Effect of Land-Use Policies on Wildlife Habitat Abundance," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 56(2), pages 195-217, June.
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    energy; food; biofuel; ethanol; error correction model; direct acyclic graph; Agricultural and Food Policy; Demand and Price Analysis; Environmental Economics and Policy; Food Security and Poverty;

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