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Time-varying Yield Distributions and the U.S. Crop Insurance Program

Author

Listed:
  • Zhu, Ying
  • Goodwin, Barry K.
  • Ghosh, Sujit K.
Abstract
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 alternative parametric model that allows the moments of the yield distributions to change with time. Several model selection techniques suggest that the proposed time-varying model outperforms more conventional models in terms of in-sample goodness-of-fit, out-of- sample predictive power and the prediction accuracy of insurance premium rates.

Suggested Citation

  • Zhu, Ying & Goodwin, Barry K. & Ghosh, Sujit K., 2011. "Time-varying Yield Distributions and the U.S. Crop Insurance Program," 2011 Annual Meeting, July 24-26, 2011, Pittsburgh, Pennsylvania 104420, Agricultural and Applied Economics Association.
    • Handle: RePEc:ags:aaea11:104420
    DOI: 10.22004/ag.econ.104420
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    Cited by:

    1. Clarke,Daniel Jonathan & Mahul,Olivier & Verma,Niraj, 2012. "Index based crop insurance product design and ratemaking : the case of modified NAIS in India," Policy Research Working Paper Series 5986, The World Bank.

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    Keywords

    Risk and Uncertainty;

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