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Economic Impacts of Soybean Rust on the US Soybean Sector

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  • Gomez, Miguel I.
  • Nunez, Hector M.
  • Onal, Hayri

Abstract

The spread of Asian Soybean Rust (ASR) represents a real threat to the U.S. soybean sector. We assess the potential impacts of ASR on domestic soybean production and commodity markets as well as the competitive position of the US in the soybean export market. We develop a mathematical stochastic dynamic sector model with endogenous prices to assess the economic impacts of ASR on US agriculture. The model takes into account the disease spread during the cropping season, the inherent uncertainty regarding the risk of infection, and the dichotomous decisions that farmers make (no treatment, preventive treatment, and curative treatment) facing the risk of infection. Our results suggest substantial impacts from potential ASR spread on agricultural output, prices and exports. Our simulation results suggest that substantial losses to the US soybean producers may be avoided by establishing effective soybean rust controls. ASR control policies can be particularly efficient if applied in the gateway regions on the path of the ASR spread. On the other hand, our results indicate a possible gradual shift in soybean production from lower-latitude states toward higher-latitude states

Suggested Citation

  • Gomez, Miguel I. & Nunez, Hector M. & Onal, Hayri, 2009. "Economic Impacts of Soybean Rust on the US Soybean Sector," 2009 Annual Meeting, July 26-28, 2009, Milwaukee, Wisconsin 49595, Agricultural and Applied Economics Association.
    • Handle: RePEc:ags:aaea09:49595
    DOI: 10.22004/ag.econ.49595
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    References listed on IDEAS

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    1. Johansson, Robert C. & Livingston, Michael J. & Westra, John & Guidry, Kurt, 2006. "Simulating the U.S. Impacts of Alternative Asian Soybean Rust Treatment Regimes," Agricultural and Resource Economics Review, Cambridge University Press, vol. 35(1), pages 116-127, April.
    2. Bekkerman, Anton & Goodwin, Barry K. & Piggott, Nicholas E., 2008. "Spatio-temporal Risk and Severity Analysis of Soybean Rust in the United States," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 33(3), pages 1-21.
    3. Bruce A. McCarl & Thomas H. Spreen, 1980. "Price Endogenous Mathematical Programming As a Tool for Sector Analysis," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 62(1), pages 87-102.
    4. Roberts, Michael J. & Schimmelpfennig, David E., 2006. "Public Information Creates Value," Amber Waves:The Economics of Food, Farming, Natural Resources, and Rural America, United States Department of Agriculture, Economic Research Service, pages 1-6, April.
    5. Roberts, Michael J. & Schimmelpfennig, David E. & Ashley, Elizabeth & Livingston, Michael J. & Ash, Mark S. & Vasavada, Utpal, 2006. "The Value of Plant Disease Early-Warning Systems: A Case Study of USDA's Soybean Rust Coordinated Framework," Economic Research Report 7208, United States Department of Agriculture, Economic Research Service.
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    Cited by:

    1. Carroll, Christine & Carter, Colin A. & Goodhue, Rachael E. & Lin, C.-Y. Cynthia & Subbarao, Krishna, 2013. "Bioeconomic Modeling of an Imported Disease in California Lettuce," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 150495, Agricultural and Applied Economics Association.
    2. Christine L. Carroll & Colin A. Carter & Rachael E. Goodhue & C.-Y. Cynthia Lin Lawell, 2018. "Crop Disease and Agricultural Productivity: Evidence from a Dynamic Structural Model of Verticillium Wilt Management," NBER Chapters, in: Agricultural Productivity and Producer Behavior, pages 217-249, National Bureau of Economic Research, Inc.
    3. Christine L. Carroll & Colin A. Carter & Rachael E. Goodhue & C.-Y. Cynthia Lin Lawell, 2017. "Crop Disease and Agricultural Productivity," NBER Working Papers 23513, National Bureau of Economic Research, Inc.

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    More about this item

    Keywords

    Crop Production/Industries;

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • Q13 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Agricultural Markets and Marketing; Cooperatives; Agribusiness

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