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DSSP: A Model of Production and Marketing Decisions on a Midwestern Crop Farm

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  • Harry M. Kaiser
  • Jeffrey Apland

Abstract

Discrete stochastic sequential programming (DSSP) is a mathematical programming technique that allows for random coefficients in the objective function and constraint set, and a multi-stage decision process. Despite its intuitive appeal, DSSP is often overlooked in empirical research because 1) the size of the programming matrix becomes large as the number of states of nature and stages increases, and 2) the data requirements associated with these models are formidable. The purpose of this article is to document the construction and use of a DSSP model of a Midwestern corn-soybean farm. The model is general in the decision variables and the sources of risk it includes. The costs of using DSSP are decreasing, and such models should be considered seriously for a wide variety of empirical problems.

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  • Harry M. Kaiser & Jeffrey Apland, 1989. "DSSP: A Model of Production and Marketing Decisions on a Midwestern Crop Farm," Review of Agricultural Economics, Agricultural and Applied Economics Association, vol. 11(2), pages 157-169.
    • Handle: RePEc:oup:revage:v:11:y:1989:i:2:p:157-169.
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    File URL: http://hdl.handle.net/10.1093/aepp/11.2.157
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    Cited by:

    1. Houk, Eric E. & Taylor, Garth & Frasier, W. Marshall, 2000. "Valuing The Characteristics Of Irrigation Water In The Platte River Basin," 2000 Annual Meeting, June 29-July 1, 2000, Vancouver, British Columbia 36454, Western Agricultural Economics Association.
    2. Ekman, Sone, 2002. "Cost-Effective Farm-Level Nitrogen Abatement in the Presence of Environmental and Economic Risk," 2002 International Congress, August 28-31, 2002, Zaragoza, Spain 24860, European Association of Agricultural Economists.
    3. Apland, Jeffrey & Hauer, Grant, 1993. "Discrete Stochastic Programming: Concepts, Examples And A Review Of Empirical Applications," Staff Papers 13793, University of Minnesota, Department of Applied Economics.
    4. Franco Rosa & Mario Taverna & Federico Nassivera & Luca Iseppi, 2019. "Farm/crop portfolio simulations under variable risk: a case study from Italy," Agricultural and Food Economics, Springer;Italian Society of Agricultural Economics (SIDEA), vol. 7(1), pages 1-15, December.
    5. Dorward, Andrew, 1999. "Modelling embedded risk in peasant agriculture: methodological insights from northern Malawi," Agricultural Economics, Blackwell, vol. 21(2), pages 191-203, October.
    6. Flaten, O. & Lien, G., 2007. "Stochastic utility-efficient programming of organic dairy farms," European Journal of Operational Research, Elsevier, vol. 181(3), pages 1574-1583, September.
    7. Flaten, Ola & Lien, Gudbrand D., 2005. "Stochastic Utility-Efficient Programming of Organic Dairy Farms," 2005 International Congress, August 23-27, 2005, Copenhagen, Denmark 24743, European Association of Agricultural Economists.
    8. Ahumada, Omar & Villalobos, J. Rene, 2009. "Application of planning models in the agri-food supply chain: A review," European Journal of Operational Research, Elsevier, vol. 196(1), pages 1-20, July.
    9. Dillon, Carl R. & Shearer, Scott A. & Mueller, Thomas, 2001. "A Mixed Integer, Nonlinear Programming Model Of Innovative Variable Rate Planting Date With Polymer Seed Coatings," 2001 Annual meeting, August 5-8, Chicago, IL 20572, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).

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