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

Calum Turvey () and Jinhua Zhao ()

No 34129, Working Papers from University of Guelph, Department of Food, Agricultural and Resource Economics

Abstract: Normal, 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.

Keywords: Crop Production/Industries; Risk and Uncertainty (search for similar items in EconPapers)
Date: 1999
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Working Paper: Parametric And Non- Parametric Crop Yield Distributions and Their Effects on All-Risk Crop Insurance Premiums (1999) Downloads
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Persistent link: https://EconPapers.repec.org/RePEc:ags:uguewp:34129

DOI: 10.22004/ag.econ.34129

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