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Contemporary Issues in Estimating Yield Distributions

Author

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  • Pujula, Aude Liliana
  • Maradiaga, David Isaias
  • Dicks, Michael R.

Abstract

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.

Suggested Citation

  • Pujula, Aude Liliana & Maradiaga, David Isaias & Dicks, Michael R., 2010. "Contemporary Issues in Estimating Yield Distributions," 2010 Annual Meeting, February 6-9, 2010, Orlando, Florida 56527, Southern Agricultural Economics Association.
    • Handle: RePEc:ags:saea10:56527
    DOI: 10.22004/ag.econ.56527
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    Cited by:

    1. Joseph Cooper & A. Nam Tran & Steven Wallander, 2017. "Testing for Specification Bias with a Flexible Fourier Transform Model for Crop Yields," American Journal of Agricultural Economics, John Wiley & Sons, vol. 99(3), pages 800-817, April.

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