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Efficient Estimation of Copula Mixture Model: An Application to the Rating of Crop Revenue Insurance AgEcon
Ghosh, Somali; Woodard, Joshua D.; Vedenov, Dmitry V..
The association between prices and yields are of paramount importance to the crop insurance programs. Proper estimation of the association is highly desirable. Copulas are one such method to measure the dependence structure. Five single parametric copulas, a non- parametric copula and their fifteen different combinations taking a mixture of two different copulas at a time have been used in the crop insurance rating analysis. Using data of corn from 1973-2009 for 602 counties in the Mid-West area two different efficient methods have been proposed to generate the optimal mixtures using the cross validation approach. A resampling technique is used to check for the significance of the expected indemnities.
Tipo: Conference Paper or Presentation Palavras-chave: Copulas; Crop Insurance; Cross-Validation; Empirical distribution; GRIP; Indemnities; Out-Of-Sample Log-Likelihood; Agricultural Finance; Q14.
Ano: 2011 URL: http://purl.umn.edu/103738
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Whole Farm Income Insurance in a Canadian Context AgEcon
Turvey, Calum G..
This paper employs mean-variance and mean-skewness optimization to investigate farmers’ crop choices under Gross Revenue Insurance (GRIP), Whole Farm Income Insurance, the Canadian Agricultural Income Stabilization program, and its modified 2008 program AgrInvest. To our knowledge this paper is the first to fully consider the endogenous optimization of whole farm insurance in a farm optimization model. The results indicate that farmers will alter farm plans significantly in response to the type of insurance offered and the level of subsidy. Farmers will take on production risks that they would not otherwise take and this risk taking behavior is exacerbated by subsidy.
Tipo: Conference Paper or Presentation Palavras-chave: Agricultural Insurance; Skewness Maximization; Mean-Variance; Farm Income Insurance; GRIP; CAIS; AgrInvest; Agricultural Finance.
Ano: 2010 URL: http://purl.umn.edu/61732
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