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Analyzing Federal Farm Program and Crop Insurance Options to Assess Policy Design and Risk Management Implications for Crop Producers

Author

Listed:
  • Lubben, Bradley
  • Stockton, Matthew
  • Protopop, Iuliia
  • Jansen, Jim

Abstract

Recent changes in federal farm programs and contemporary farm program proposals highlight an evolving shift in farm policy from income support to risk management. A mix of price- and revenue-based commodity programs as well as yield- and revenue-based insurance products provide crop producers a complex portfolio of risk management tools and choices. To make effective risk management decisions, crop producers must integrate farm programs and crop insurance alternatives in a comprehensive risk management decision-making framework. This work assesses the risk management performance and complementarity or substitutability of farm program and crop insurance options. A novel representative farm model for Nebraska is used that incorporates national, state, district, county, and farm-level yield variables along with national and state-level price variables to accurately assess multiple farm program and crop insurance alternatives. The four-stage simulation model simultaneously estimates all necessary yield and price variables in a statistically-distributed and correlated framework. This allows for a consistent and complete analysis of alternative farm program and crop insurance choices and designs. The simulation produces crop revenue, farm program, and crop insurance results for eight representative farms indicative of the crop mix and productivity levels in each of the eight agricultural statistics districts in Nebraska. The results demonstrate the risk management performance of alternative farm program and crop insurance choices for the eight representative farms in Nebraska. The analysis demonstrates the complementarity of farm programs with some crop insurance products and protection levels while showing potential substitutability or overlap with other products and protection levels. The results provide insight for more effective policy design, farm program participation, and farm-level risk management decision-making.

Suggested Citation

  • Lubben, Bradley & Stockton, Matthew & Protopop, Iuliia & Jansen, Jim, 2013. "Analyzing Federal Farm Program and Crop Insurance Options to Assess Policy Design and Risk Management Implications for Crop Producers," 2013 AAEA: Crop Insurance and the Farm Bill Symposium 157827, Agricultural and Applied Economics Association.
  • Handle: RePEc:ags:aaeaci:157827
    DOI: 10.22004/ag.econ.157827
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    File URL: https://ageconsearch.umn.edu/record/157827/files/Lubben_etal_Farm_Programs_Crop%20Insurance_Policy_Design_Risk_Management_AAEA_Oct_2013.pdf
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    References listed on IDEAS

    as
    1. Lubben, Bradley D. & Novak, James L., 2010. "Discussion: What Have We Learned from the New Suite of Risk Management Programs of the Food, Conservation, and Energy Act of 2008?," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 42(3), pages 537-541, August.
    2. Jansen, Jim A. & Stockton, Matthew C. & Lubben, Bradley D., 2012. "Modeling Correlated and Disaggregated Crop Revenue Distributions: Implications under Mixed Policy and Program Initiatives," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 124688, Agricultural and Applied Economics Association.
    3. Jansen, Jim A. & Lubben, Bradley D. & Stockton, Matthew C., 2012. "Analyzing Crop Revenue Safety Net Program Alternatives and Implications on Marketing Decisions," Journal of Agribusiness, Agricultural Economics Association of Georgia, vol. 30(2).
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    Cited by:

    1. Feng, Siyi & Patton, Myles & Binfield, Julian C.R. & Davis, John, 2014. "Assessing the costs of risk management tools: A crop insurance scenario based on a stochastic partial equilibrium model approach," 88th Annual Conference, April 9-11, 2014, AgroParisTech, Paris, France 170538, Agricultural Economics Society.

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    More about this item

    Keywords

    Agricultural and Food Policy; Farm Management; Risk and Uncertainty;
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