|
|
|
|
|
| Ozaki, Vitor Augusto; Ghosh, Sujit K.; Goodwin, Barry K.; Shirota, Ricardo. |
| This article focuses on the modeling of agricultural yield data using hierarchical Bayesian models. In recovering the generating process of these data, we consider the temporal, spatial and spatio-temporal relationships pertinent to the prediction and pricing of insurance contracts based on regional crop yields. A county-average yield data set was analyzed for the State of Paraná, Brazil for the period of 1990 through 2002. The choice of the best model from among the several non-nested models considered was based on the posterior predictive criterion. The methodology used in this article proposes improvements in the statistical and actuarial methods often applied to the calculation of insurance premium rates. These improvements are especially relevant to... |
| Tipo: Conference Paper or Presentation |
Palavras-chave: Research Methods/ Statistical Methods. |
| Ano: 2005 |
URL: http://purl.umn.edu/19142 |
| |
|
|
| Ozaki, Vitor Augusto. |
| The implementation of a crop insurance program is an old requirement of the agricultural sector. After the failure of the National Crop Insurance Company (CNSA), in the period of 1954 through 1966, the federal government started to stimulate the agricultural insurance market. Aiming increase the crop insurance operations the Government approved Law n. 10.823 which subsidize part of the premium paid by farmers. The nature of this work is essentially analytical, such that any quantitative model has been established. Over the years, government risk management tools, such as, Proagro and some private insurance companies have had unsatisfactory financial results suggesting that the current crop insurance model presents signals of decline. This article shows the... |
| Tipo: Journal Article |
Palavras-chave: Crop insurance; Paradigm; Subsidy; Agribusiness; Q19. |
| Ano: 2008 |
URL: http://purl.umn.edu/61274 |
| |
|
|
| Ozaki, Vitor Augusto. |
| This paper analyses the spatial pattern of the agricultural yield data. Using the spatial statistics, it is possible to estimate some parameters of the semivariogram to study the problem of the systemic risk, which has great implications for the crop insurance program in Brazil. In particular, the “range” parameter was estimated. This parameter measures the distance, in which the spatial correlation tends to zero. For the empirical analysis, county yield data was used provided by IBGE, for soybean and corn, in the state of Paraná, through 1990 and 2002. The results showed that there is spatial dependence in every year analysed, going to zero in relatively long distances (in km). |
| Tipo: Journal Article |
Palavras-chave: Crop insurance; Systemic risk; Spatial correlation; Semivarioram.; Agribusiness; Q19. |
| Ano: 2008 |
URL: http://purl.umn.edu/61239 |
| |
|
|
|
