| Registro completo |
| Provedor de dados: |
AgEcon
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| País: |
United States
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| Título: |
Contemporary Issues in Estimating Yield Distributions
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| Autores: |
Pujula, Aude Liliana
Maradiaga, David Isaias
Dicks, Michael R.
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| Data: |
2010-01-16
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| Ano: |
2010
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| Palavras-chave: |
Probability Density Estimation
Nonparametric
Kernel
Nonstationary
Unit Roots
Data Transformations
Corn Yields
Weather
Production Economics
Research Methods/ Statistical Methods
Risk and Uncertainty
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| Resumo: |
In the research area of crop yield density estimation and in particular in risk analysis, little emphasis has been given to the appropriateness of transformation methods (e.g., removing a linear trend) and how such transformations impact the reliability of the empirical distribution functions and the resulting probability estimates. Similarly, there is little consensus on the impact of environmental variables (e.g., rainfall and temperature) on empirical distributions of yields. Using historical county corn yield data for Arkansas and Louisiana and nonparametric methods, this empirical analysis shed light on the importance of data transformation in crop risk analysis. Results demonstrate that inappropriate data treatment can lead to misestimation of probability density estimates.
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| Tipo: |
Conference Paper or Presentation
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| Idioma: |
Inglês
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| Identificador: |
http://purl.umn.edu/56527
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| Relação: |
Southern Agricultural Economics Association>2010 Annual Meeting, February 6-9, 2010, Orlando, Florida
Selected Paper
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| Formato: |
29
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