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Optimal Sequential Plantings of Corn and Soybeans Under Price Uncertainty

Author

Listed:
  • Michael Livingston

    (US Department of Agriculture, Economic Research Service)

  • Michael J. Roberts

    (Department of Economics, University of Hawaii at Manoa)

  • Yue Zhang

    (Department of Agricultural and Resource Economics)

Abstract

Optimal crop choice and fertilizer applications depend on the stochastic dynamics of commodity prices, fertilizer prices, and the agronomic effects of rotation versus monoculture. The efficient decision rule accounts for real option values associated with maintaining land disposition in an environment with highly uncertain future prices and irreversible past planting decisions. We parameterize a baseline model for a representative acre in Iowa and compare the model's predictions and profits to relatively naive, shorter-horizon decision rules, and a field managed with optimal fertilizer applications conditional on corn and soybeans always being rotated. We also examine the effects of a permanently larger premium on corn prices relative to soybean prices, which has been observed in locations near recently established ethanol plants. We then compare the various decision rules to actual crop choices in a panel of over 6500 Iowa plots during 1979-2007. As compared to less forward-looking objectives, we find the agronomic benefits of rotations coupled with real option values can lead to a more inelastic response of planting decisions to both transitory and permanent price changes. Always rotating, regardless of prices, is close to optimal, but so are shorter-horizon objectives. One implication is that reduced corn monoculture and fertilizer application rates might be implemented with modest incentive payments of $4 per acre or less.

Suggested Citation

  • Michael Livingston & Michael J. Roberts & Yue Zhang, 2014. "Optimal Sequential Plantings of Corn and Soybeans Under Price Uncertainty," Working Papers 201412, University of Hawaii at Manoa, Department of Economics.
  • Handle: RePEc:hai:wpaper:201412
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    References listed on IDEAS

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    16. Deininger,Klaus W. & Ali,Daniel Ayalew & Kussul,Nataliia & Lavreniuk,Mykola & Nivievskyi,Oleg, 2020. "Using Machine Learning to Assess Yield Impacts of Crop Rotation : Combining Satellite and Statistical Data for Ukraine," Policy Research Working Paper Series 9306, The World Bank.
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    More about this item

    Keywords

    crop rotations; uncertainty; option value; supply response; dynamic programming.;
    All these keywords.

    JEL classification:

    • Q11 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Aggregate Supply and Demand Analysis; Prices
    • Q12 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets

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