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Rating Crop Insurance Contracts with Nonparametric Bayesian Model Averaging

Author

Listed:
  • Liu, Yong
  • Ker, Alan P.

Abstract

Crop insurance is plagued by relatively little historical information but significant spatial information. We investigate the efficacy of using nonparametric Bayesian model averaging (BMA) to incorporate extraneous information into the estimated premium rates. Nonparametric BMA is particularly suited to this application because it does not make any assumptions about parametric form or the extent to which yields are similar. We evaluate the proposed estimator under small-to-medium sample sizes and various geographical restrictions on the distance of spatial smoothing for policy relevance. The nonparametric BMA consistently decreases error and enables statistically significant and economically important rents to be captured.

Suggested Citation

  • Liu, Yong & Ker, Alan P., 2020. "Rating Crop Insurance Contracts with Nonparametric Bayesian Model Averaging," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 45(2), March.
    • Handle: RePEc:ags:jlaare:302453
    DOI: 10.22004/ag.econ.302453
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    Cited by:

    1. Koliadenko, Svitlana & Andreichenko, Andrii & Galperina, Liubov & Minenko, Sofiia & Kovylina, Maria, 2020. "Analysis and forecasting of Ukrainian agrarian exports to the EU countries," Agricultural and Resource Economics: International Scientific E-Journal, Agricultural and Resource Economics: International Scientific E-Journal, vol. 6(3), September.
    2. Yikuan Chen & B. Wade Brorsen & Jon T. Biermacher & Mykel Taylor, 2022. "Spatially varying wheat protein premiums," Letters in Spatial and Resource Sciences, Springer, vol. 15(3), pages 587-598, December.
    3. Liang, Weifang & Liu, Yong, 2023. "Rating Crop Insurance Contracts with Model Stacking of Gaussian Processes," 2023 Annual Meeting, July 23-25, Washington D.C. 335759, Agricultural and Applied Economics Association.
    4. Park, Eunchun & Harri, Ardian & Coble, Keith H., 2022. "Estimating Crop Yield Densities for Counties with Missing Data," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 47(3), September.
    5. Addey, Kwame Asiam & Shaik, Saleem & Nganje, William, 2022. "DEVELOPMENT OF FARM MODEL FOR ND and NGP Prediction of Corn and Soybean Yields in the Presence of Random Shocks," Agribusiness & Applied Economics Report 320066, North Dakota State University, Department of Agribusiness and Applied Economics.

    More about this item

    Keywords

    Crop Production/Industries;

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