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Modeling Yield Distribution In High Risk Counties: Application To Texas Upland Cotton

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  • Chen, Shu-Ling
  • Miranda, Mario J.

Abstract

Very little attention has been given to the modeling of yield distribution for crops and regions in which yields exhibit irregular behavior. We undertake a statistical case study of Texas upland cotton and propose an alternative mixture distribution based on regime-switching model in which the conditional distribution of yield depends upon an observable drought index. The results show that the mixture distribution model provides a better fit to the data than conventional parametric distributions and produces higher implied premium rates than the current published Group Risk Plan insurance rates in more than two-thirds of Texas counties examined.

Suggested Citation

  • Chen, Shu-Ling & Miranda, Mario J., 2006. "Modeling Yield Distribution In High Risk Counties: Application To Texas Upland Cotton," 2006 Annual meeting, July 23-26, Long Beach, CA 21392, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    • Handle: RePEc:ags:aaea06:21392
    DOI: 10.22004/ag.econ.21392
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    References listed on IDEAS

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    Cited by:

    1. Conradt, Sarah & Bokusheva, Raushan & Finger, Robert & Kussaiynov, Talgat, 2014. "Yield Trend Estimation in the Presence of Farm Heterogeneity and Non-linear Technological Change," Quarterly Journal of International Agriculture, Humboldt-Universitaat zu Berlin, vol. 53(2), pages 1-20, May.
    2. Conradt, Sarah & Bokusheva, Raushan & Finger, Robert & Kussaiynov, Talgat, 2012. "Yield trend estimation in the presence of non-constant technological change and weather effects," 123rd Seminar, February 23-24, 2012, Dublin, Ireland 122541, European Association of Agricultural Economists.

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