PARAMETRIC AND NON-PARAMETRIC CROP YIELD DISTRIBUTIONS AND THEIR EFFECTS ON ALL-RISK CROP INSURANCE PREMIUMS

dc.creatorTurvey, Calum G.
dc.creatorZhao, Jinhua
dc.date2017-04-01T19:23:27Z
dc.date.accessioned2026-07-09T04:22:47Z
dc.descriptionNormal, gamma and beta distributions are applied to 609 crop yield histories of Ontario farmers to determine which, if any, best describe crop yields. In addition, a distribution free non-parametric kernel estimator was applied to the same data to determine its efficiency in premium estimation relative to the three parametric forms. Results showed that crop yields are most likely to be described by a beta distribution but only for 50% of those tested. In terms of efficiency in premium estimation, minimum error criteria supports use of a kernel estimator for premium setting. However, this gain in efficiency comes at the expense of added complexity.
dc.identifierdoi:10.22004/ag.econ.34129
dc.identifierhttps://ageconsearch.umn.edu/record/34129/files/wp9905.pdf
dc.identifierhttp://ageconsearch.umn.edu/record/34129
dc.identifier.urihttp://hdl.handle.net/123456789/549015
dc.languageeng
dc.publisher
dc.sourcehttp://ageconsearch.umn.edu/record/34129
dc.titlePARAMETRIC AND NON-PARAMETRIC CROP YIELD DISTRIBUTIONS AND THEIR EFFECTS ON ALL-RISK CROP INSURANCE PREMIUMS
dc.typeText

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