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An Empirically-Grounded Comparison of the Johnson System versus the Beta as Crop Yield Distribution Models AgEcon
Ramirez, Octavio A.; McDonald, Tanya U..
Previous research established that the expanded Johnson system can accommodate any theoretically possible mean-variance-skewness-kurtosis combination. Therefore, it has been hypothesized that this system can provide for a reasonably accurate modeling approximation of any probability distribution that might be encountered in practice. In order to test that hypothesis, this manuscript develops a more flexible expanded form of the Beta distribution which, in its original form, has been widely used to model and simulate crop yields for risk analysis. Empirically grounded evaluations suggest that the Johnson system can model a variety of typical yield data-generating processes that are based on the Beta distribution much more precisely than the Beta can model...
Tipo: Conference Paper or Presentation Palavras-chave: Crop Production/Industries.
Ano: 2007 URL: http://purl.umn.edu/9814
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The Expanded Johnson System: A Highly Flexible Crop Yield Distribution Model AgEcon
Ramirez, Octavio A.; McDonald, Tanya U..
Replaced with revised version of paper 11/28/06. Former title: The Expanded and Re-Parameterized Johnson System: A Most Crop-Yield Distribution Model
Tipo: Conference Paper or Presentation Palavras-chave: Crop Production/Industries.
Ano: 2006 URL: http://purl.umn.edu/21455
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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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