| Registro completo |
| Provedor de dados: |
AgEcon
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| País: |
United States
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| Título: |
Measurement of Yield distribution: A Time-Varying Distribution Model
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| Autores: |
Yang, Tsung Yu
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| Data: |
2011-05-02
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| Ano: |
2011
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| Palavras-chave: |
Time-Varying Distribution
Mixture Distribution
Crop Insurance
Agricultural Finance
Crop Production/Industries
Research Methods/ Statistical Methods
Risk and Uncertainty
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| Resumo: |
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 the yield risk may be underestimated under the common selection -- Beta distribution. A mixed normal distribution under a time-varying structure, under which the parameters are allowed to vary over time, tends to collapse to a single normal distribution. The time-varying mixed normal model fits the realized yield data in one step that avoids the possible bias caused by sampling variability. Also, the time-varying parameters imply that the premium rates can be adjusted to represent the most recent information and that lifts the efficiency of the insurance market.
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| Tipo: |
Conference Paper or Presentation
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| Idioma: |
Inglês
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| Identificador: |
http://purl.umn.edu/103422
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| Relação: |
Agricultural and Applied Economics Association>2011 Annual Meeting, July 24-26, 2011, Pittsburgh, Pennsylvania
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| Formato: |
20
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