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Modeling Yield Risk Under Technological Change: Dynamic Yield Distribution and the U.S Crop Insurance Program AgEcon
Zhu, Ying; Goodwin, Barry K.; Ghosh, Sujit K..
The objective of this study is to evaluate and model the yield risk associated with major agricultural commodities in the U.S. We are particularly concerned with the nonstationary nature of the yield distribution, which primarily arises because of technological progress and changing environmental conditions. Precise risk assessment depends on the accuracy of modeling this distribution. This problem becomes more challenging as the yield distribution changes over time, a condition that holds for nearly all major crops. A common approach to this problem is based on a two-stage method in which the yield is first detrended and then the estimated residuals are treated as observed data and modeled using various parametric or nonparametric methods. We propose an...
Tipo: Working or Discussion Paper Palavras-chave: Crop Insurance; Model Comparison; Time-Varying Distribution; Financial Economics.
Ano: 2011 URL: http://purl.umn.edu/102048
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Measurement of Yield distribution: A Time-Varying Distribution Model AgEcon
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
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