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The Economics of Testing for Biotech Grain: Application to StarLink Corn

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  • Johnson, D. Demcey
  • Lin, William W.

Abstract

StarLink corn, a variety not approved for human use, disrupted the marketing system in 2000 because of inadvertent commingling. This paper provides an overview of the economics of testing grain for biotech content. What are the risks facing buyers and sellers, and how are these influenced by testing protocols? How do market premiums and discounts, testing costs, and prior beliefs affect the incentives to test? A conceptual model is developed in which sellers choose whether to pre-test grain prior to shipment. Through simulation analysis, we illustrate the impact of market premiums and other variables on testing incentives and buyer risk.

Suggested Citation

  • Johnson, D. Demcey & Lin, William W., 2005. "The Economics of Testing for Biotech Grain: Application to StarLink Corn," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 30(2), pages 1-17, August.
    • Handle: RePEc:ags:jlaare:31220
    DOI: 10.22004/ag.econ.31220
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    References listed on IDEAS

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    1. William W. Wilson & Todd Preszler, 1992. "End-Use Performance Uncertainty and Competition in International Wheat Markets," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 74(3), pages 556-563.
    2. Wilson, William W., 1986. "Competition in the International Wheat Market," Agricultural Economics Reports 23326, North Dakota State University, Department of Agribusiness and Applied Economics.
    3. Wilson, William W. & Dahl, Bruce L., 2002. "Costs And Risks Of Testing And Segregating Gm Wheat," Agribusiness & Applied Economics Report 23480, North Dakota State University, Department of Agribusiness and Applied Economics.
    4. William W. Wilson & Todd Preszler, 1992. "End-Use Performance Uncertainty and Competition in International Wheat Markets," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 74(3), pages 556-563.
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    Cited by:

    1. Ge, Houtian & Nolan, James & Gray, Richard & Goetz, Stephan & Han, Yicheol, 2016. "Supply chain complexity and risk mitigation – A hybrid optimization–simulation model," International Journal of Production Economics, Elsevier, vol. 179(C), pages 228-238.

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