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Estimating Crop Rotations as Dynamic Cycles using Field Data

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  • MacEwan, Duncan
  • Howitt, Richard E.

Abstract

Crop rotation systems are an important part of agricultural production for managing pests, diseases, and soil fertility. Recent interest in sustainable agriculture focuses on low input-use practices which require knowledge of the underlying dynamics of production and rotation systems. Polices to limit chemical application depending on proximity to waterways and flood management require field-level data and analysis. Additionally, supply elasticity estimates based on crop production as independent activities omit the dynamic effects of a cyclical rotation. We estimate a dynamic programming model of crop rotation which incorporates yield and cost inter-temporal effects in addition to field-specific factors including salinity and soil quality. Using an Optimal Matching algorithm from the Bioinformatics literature we determine empirically observed rotations using a geo-referenced panel dataset of 14,000 fields over 13 years. We estimate the production parameters which satisfy the Euler Equations of the field-level rotation problem and solve an empirically observed four-crop rotation.

Suggested Citation

  • MacEwan, Duncan & Howitt, Richard E., 2011. "Estimating Crop Rotations as Dynamic Cycles using Field Data," 2011 Annual Meeting, July 24-26, 2011, Pittsburgh, Pennsylvania 103635, Agricultural and Applied Economics Association.
    • Handle: RePEc:ags:aaea11:103635
    DOI: 10.22004/ag.econ.103635
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    References listed on IDEAS

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    1. Talaat El-Nazer & Bruce A. McCarl, 1986. "The Choice of Crop Rotation: A Modeling Approach and Case Study," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 68(1), pages 127-136.
    2. 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.
    3. Doole, Graeme J., 2009. "A Practical Algorithm for Multiple-Phase Control Systems in Agricultural and Natural Resource Economics," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 34(1), pages 1-21, April.
    4. Christian Brzinsky-Fay & Ulrich Kohler & Magdalena Luniak, 2006. "Sequence analysis with Stata," Stata Journal, StataCorp LP, vol. 6(4), pages 435-460, December.
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    Cited by:

    1. Brewin, D. & Sakulanda, H., 2018. "Optimal Rotations with Considerations for Corn in Southern Manitoba," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277282, International Association of Agricultural Economists.
    2. Zhang, Wendong & Irwin, Elena G., 2013. "From Farmers' Management Decisions to Watershed Water Quality: A Spatial Economic Model of Land Management Choices," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 150729, Agricultural and Applied Economics Association.

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    Keywords

    Crop Production/Industries; Production Economics; Research Methods/ Statistical Methods;
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