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	Provedor de dados 31 (2) Autor Lanoue, Christopher (1) Paulson, Nicholas D. (1) Sherrick, Bruce J. (1) Woodard, Joshua D. (1) Yang, Tsung Yu (1) Palavra-chave Crop Insurance (2) Mixture Distribution (2) Agricultural Finance (1) Beta Distribution (1) Crop Production/Industries (1) Farm Management (1) Financial Economics (1) Goodness-of-Fit (1) Insurance Rating Efficiency (1) Land Economics/Use (1) Out-of-Sample Efficiency (1) Research Methods/ Statistical Methods (1) Risk and Uncertainty (1) Time-Varying Distribution (1) Weibull Distribution (1) Yield distributions (1) Mais... Tipo do documento Conference Paper or Presentation (2) Ano 2011 (1) 2010 (1) País United States (2) Idioma Inglês (2)		Ordenar por:  Relevância Autor Título Ano Registros recuperados: 2 Primeira ... 1 ... Última Measurement of Yield distribution: A Time-Varying Distribution Model 31 Yang, Tsung Yu. Regarding the nature of yield data, there are two basic characteristics that need to be accommodated while we are about to model a yield distribution. The first one is the nonstationary nature of the yield distribution, which causes the heteroscedasticity related problems. The second one is the left skewness of the yield distribution. A common approach to this problem is based on a two-stage method in which the yields are detrended first and the detrended yields are taken as observed data modeled by various parametric and nonparametric methods. Based on a two-stage estimation structure, a mixed normal distribution seems to better capture the secondary distribution from catastrophic years than a Beta distribution. The implication to the risk management is... Tipo: Conference Paper or Presentation Palavras-chave: Time-Varying Distribution; Mixture Distribution; Crop Insurance; Agricultural Finance; Crop Production/Industries; Research Methods/ Statistical Methods; Risk and Uncertainty. Ano: 2011 URL: http://purl.umn.edu/103422 Evaluating Yield Models for Crop Insurance Rating 31 Lanoue, Christopher; Sherrick, Bruce J.; Woodard, Joshua D.; Paulson, Nicholas D.. Generated crop insurance rates depend critically on the distributional assumptions of the underlying crop yield loss model. Using farm level corn yield data from 1972-2008, we revisit the problem of examining in-sample goodness-of-fit measures across a set of flexible parametric, semi-parametric, and non-parametric distributions. Simulations are also conducted to investigate the out-of-sample efficiency properties of several competing distributions. The results indicate that more parameterized distributional forms fit the data better in-sample due to the fact that they have more parameters, but are generally less efficient out-of-sample–and in some cases more biased–than more parsimonious forms which also fit the data adequately, such as the Weibull. The... Tipo: Conference Paper or Presentation Palavras-chave: Yield distributions; Crop Insurance; Weibull Distribution; Beta Distribution; Mixture Distribution; Out-of-Sample Efficiency; Goodness-of-Fit; Insurance Rating Efficiency; Farm Management; Financial Economics; Land Economics/Use. Ano: 2010 URL: http://purl.umn.edu/61761 Registros recuperados: 2 Primeira ... 1 ... Última

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