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Modelling yield risk measures of major crop plants AgEcon
Kobus, Pawel.
The paper deals with the problem of modelling yield risk measures for major crop plants in Poland. Hence, in some cases the gamma distribution offers a better fit to the data than normal distribution, and in addition to linear models, generalized linear models were also used. The research was based on data from Polish FADN, with sample sizes ranging from 416 up to 2300, depending on the crop plant. It was found that models based on the farm level data, can explain on average 20% of variation coefficient unevenness. The most important variables were average yield, type of farming, arable area and land quality. The elimination of the average yield from the models reduced the average determination coefficient to about 9%.
Tipo: Presentation Palavras-chave: Production risk; Risk measures; Yield distribution; Risk and Uncertainty; Q10; C46.
Ano: 2012 URL: http://purl.umn.edu/122535
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A Flexible Parametric Family for the Modeling and Simulation of Yield Distributions AgEcon
Ramirez, Octavio A.; McDonald, Tanya U.; Carpio, Carlos E..
The distributions currently used to model and simulate crop yields are unable to accommodate a substantial subset of the theoretically feasible mean-variance-skewness-kurtosis (MVSK) hyperspace. Because these first four central moments are key determinants of shape, the available distributions might not be capable of adequately modeling all yield distributions that could be encountered in practice. This study introduces a system of distributions that can span the entire MVSK space and assesses its potential to serve as a more comprehensive parametric crop yield model, improving the breadth of distributional choices available to researchers and the likelihood of formulating proper parametric models.
Tipo: Journal Article Palavras-chave: Risk analysis; Parametric methods; Yield distributions; Yield modeling and simulation; Yield nonnormality; Agribusiness; Agricultural Finance; Crop Production/Industries; Land Economics/Use; Production Economics; Productivity Analysis; Research Methods/ Statistical Methods; C15; C16; C46; C63.
Ano: 2010 URL: http://purl.umn.edu/90675
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