978 resultados para Life insurance premiums.


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This paper applies Hierarchical Bayesian Models to price farm-level yield insurance contracts. This methodology considers the temporal effect, the spatial dependence and spatio-temporal models. One of the major advantages of this framework is that an estimate of the premium rate is obtained directly from the posterior distribution. These methods were applied to a farm-level data set of soybean in the State of the Parana (Brazil), for the period between 1994 and 2003. The model selection was based on a posterior predictive criterion. This study improves considerably the estimation of the fair premium rates considering the small number of observations.

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Over the years, crop insurance programs became the focus of agricultural policy in the USA, Spain, Mexico, and more recently in Brazil. Given the increasing interest in insurance, accurate calculation of the premium rate is of great importance. We address the crop-yield distribution issue and its implications in pricing an insurance contract considering the dynamic structure of the data and incorporating the spatial correlation in the Hierarchical Bayesian framework. Results show that empirical (insurers) rates are higher in low risk areas and lower in high risk areas. Such methodological improvement is primarily important in situations of limited data.

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This article presents a statistical model of agricultural yield data based on a set of hierarchical Bayesian models that allows joint modeling of temporal and spatial autocorrelation. This method captures a comprehensive range of the various uncertainties involved in predicting crop insurance premium rates as opposed to the more traditional ad hoc, two-stage methods that are typically based on independent estimation and prediction. A panel data set of county-average yield data was analyzed for 290 counties in the State of Parana (Brazil) for the period of 1990 through 2002. Posterior predictive criteria are used to evaluate different model specifications. This article provides substantial improvements in the statistical and actuarial methods often applied to the calculation of insurance premium rates. These improvements are especially relevant to situations where data are limited.

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This article considers alternative methods to calculate the fair premium rate of crop insurance contracts based on county yields. The premium rate was calculated using parametric and nonparametric approaches to estimate the conditional agricultural yield density. These methods were applied to a data set of county yield provided by the Statistical and Geography Brazilian Institute (IBGE), for the period of 1990 through 2002, for soybean, corn and wheat, in the State of Paran. In this article, we propose methodological alternatives to pricing crop insurance contracts resulting in more accurate premium rates in a situation of limited data.

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The investigation of the factors that interfere in the well-being of the elderly and their QoL can provide theoretical and methodological subsidies in structuring actions and policies in the health area, in order to fulfill the needs of that population. In this descriptive transversal study, body composition and QoL of elderly women at the UTA program in Piracicaba (Sao Paulo, Brazil) were verified. The participants were 81 women from UTA, and the general levels of physical activity were evaluated, as well as body weight (BW), height, and bodymass index (BMI). The waist circumference (WC) was measured at the level of the umbilical scar and the body composition by impedance (BIA 310e). QoL was verified by means of WHOQOL-Bref and statistical analysis developed with the SAS program. The decrease of weight, height, BMI, and fat-free mass (FFM) was observed among the several age groups, although with no significant difference. The average levels of the general QoL scores and physical, psychological and environmental domains decreased in higher age groups, but social domains showed the opposite result. This fact can be a particular characteristic of the UTA group, and factors the influence such behavior are yet to be studied. (C) 2010 Elsevier Ireland Ltd. All rights reserved.

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Sensory analysis is one of the most suitable processes for measuring oxidative damage and determining the shelf-life of nuts, but it is an expensive and time-consuming methodology. Thus, our objective was to correlate sensory data and chemical markers obtained during the accelerated oxidation of Brazil nuts and to determine the chemical parameters values associated with the sensory shelf-life of the nuts as established by the consumers. Brazil nuts were kept at 80 A degrees C for 21 days. At intervals of 2 days, the oxidized odor of the samples was analyzed by nine trained panelists using a discriminative scale, and the oil was extracted to quantify the chemical parameters. A high (r > 0.95) and significant correlation (p < 0.05) was observed between the sensory data and the hydroperoxide concentration (PV), para-anisidine value (pAV), hexanal content, and alpha- and gamma-tocopherol concentrations. When compared with fresh samples, sensory identification of oxidized odor occurred on the 4th day, noticeably earlier than changes in chemical markers (12th day). Consumers rejected the nuts after 12 days of storage, which corresponded to PV = 18.8 meq kg(-1) oil, pAV = 7.68, hexanal = 48.95 mu mol 100 g(-1) oil, alpha-tocopherol = 15.01 mg kg(-1) oil, and gamma + beta-tocopherol = 73.88 mg kg(-1) oil. Our study suggests that simple spectrometric methods, such as PV and pAV, can be used to estimate the oxidative shelf-life of nuts based on sensory analysis.

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