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An Empirical Model of Crop Rotations

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  • MacEwan, Duncan
  • Howitt, Richard E.

Abstract

Crop rotation systems have played a key role in agricultural production for thousands of years, dating back to the biennial grain-fallow rotations employed by the Ancient Greeks. Fundamentally, rotations are rooted in intertemporal spillover effects between crops, the economic consequences of which depend on relative input and output prices. We contribute to the literature by developing a dynamic, field-level model of crop rotations using a geo-referenced panel dataset that covers 12 years and over 14,000 individual fields. We identify empirical rotations using a Sequence Analysis procedure from the bio-informatics literature, and calibrate a dynamic field-level profit function that satisfies the underlying Euler dynamic first-order conditions using Generalized Maximum Entropy. The resulting model is based entirely on empirical data, and exhibits a stable rotational cycle which responds to changes in expected prices and costs. We illustrate the mechanics of the model with a four-crop rotation of alfalfa, cotton, grain, and fallow, and simulate field-level changes resulting from changes in relative prices.

Suggested Citation

  • MacEwan, Duncan & Howitt, Richard E., 2011. "An Empirical Model of Crop Rotations," 2011 Conference (55th), February 8-11, 2011, Melbourne, Australia 100581, Australian Agricultural and Resource Economics Society.
    • Handle: RePEc:ags:aare11:100581
    DOI: 10.22004/ag.econ.100581
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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. 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.
    3. 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. Stigler, Matthieu M., 2018. "Supply response at the field-level: disentangling area and yield effects," 2018 Annual Meeting, August 5-7, Washington, D.C. 274343, Agricultural and Applied Economics Association.
    2. Alain Carpentier & Alexandre Gohin, 2015. "On the economic theory of crop rotations: value of the crop rotation effects and implications on acreage choice modeling," Working Papers SMART 15-04, INRAE UMR SMART.

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    Keywords

    Crop Production/Industries;

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