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U.S. Soybean Yields: Estimation and Forecasting with Nonsymmetric Disturbances

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  • Paul Gallagher

Abstract

National average soybean yields are skewed with a relatively high chance of low yields. Maximum likelihood estimates support this hypothesis. Revised forecasts which account for skewed yields are positioned higher than forecasts based on the illusion of a symmetric distribution. Also, yield instability has been increasing steadily; the standard deviation of the soybean yield distribution is twenty-five percent higher in the late 1980s than it was in the early 1970s.

Suggested Citation

  • Paul Gallagher, 1987. "U.S. Soybean Yields: Estimation and Forecasting with Nonsymmetric Disturbances," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 69(4), pages 796-803.
    • Handle: RePEc:oup:ajagec:v:69:y:1987:i:4:p:796-803.
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    File URL: http://hdl.handle.net/10.2307/1242190
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    Cited by:

    1. Lima Miquelluti, Daniel & Ozaki, Vitor & Miquelluti, David J., 2020. "An application of geographically weighted quantile LASSO to weather index insurance design," 2020 Annual Meeting, July 26-28, Kansas City, Missouri 304288, Agricultural and Applied Economics Association.
    2. Daniel Schunk & Bruce Hannon, 2004. "Impacts of a carbon tax policy on Illinois grain farms: a dynamic simulation study," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 6(3), pages 221-247, September.
    3. Jesse B. Tack & David Ubilava, 2015. "Climate and agricultural risk: measuring the effect of ENSO on U.S. crop insurance," Agricultural Economics, International Association of Agricultural Economists, vol. 46(2), pages 245-257, March.
    4. Li, Lisha, 2015. "Three essays on crop yield, crop insurance and climate change," ISU General Staff Papers 201501010800005371, Iowa State University, Department of Economics.
    5. Qiujie Zheng & H. Holly Wang & Qing Hua Shi, 2014. "Estimating bivariate yield distributions and crop insurance premiums using nonparametric methods," Applied Economics, Taylor & Francis Journals, vol. 46(18), pages 2108-2118, June.
    6. Liman Harou, Issoufou & Whitney, Cory & Kung'u, James & Luedeling, Eike, 2021. "Crop modelling in data-poor environments – A knowledge-informed probabilistic approach to appreciate risks and uncertainties in flood-based farming systems," Agricultural Systems, Elsevier, vol. 187(C).
    7. Yu, Tian, 2011. "Three essays on weather and crop yield," ISU General Staff Papers 201101010800002976, Iowa State University, Department of Economics.
    8. 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.
    9. Yong Liu & Alan P. Ker, 2021. "Simultaneous borrowing of information across space and time for pricing insurance contracts: An application to rating crop insurance policies," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 88(1), pages 231-257, March.
    10. Jesse Tack & David Ubilava, 2013. "The effect of El Niño Southern Oscillation on U.S. corn production and downside risk," Climatic Change, Springer, vol. 121(4), pages 689-700, December.
    11. Arora, Gaurav & Agarwal, Sandip K., 2020. "Agricultural input use and index insurance adoption: Concept and evidence," 2020 Annual Meeting, July 26-28, Kansas City, Missouri 304508, Agricultural and Applied Economics Association.
    12. Antti Saastamoinen, 2015. "Heteroscedasticity Or Production Risk? A Synthetic View," Journal of Economic Surveys, Wiley Blackwell, vol. 29(3), pages 459-478, July.
    13. Chuck Mason & Dermot J. Hayes & Sergio H. Lence, 2002. "Systemic risk in U.S. crop reinsurance programs," Agricultural Finance Review, Emerald Group Publishing Limited, vol. 63(1), pages 23-39, December.
    14. Leif Erec Heimfarth & Oliver Musshoff, 2011. "Weather index‐based insurances for farmers in the North China Plain," Agricultural Finance Review, Emerald Group Publishing Limited, vol. 71(2), pages 218-239, August.
    15. Yaling Li & Fujin Yi & Yanjun Wang & Richard Gudaj, 2019. "The Value of El Niño-Southern Oscillation Forecasts to China’s Agriculture," Sustainability, MDPI, vol. 11(15), pages 1-23, August.
    16. Jing Wang & Feng Fang & Qiang Zhang & Jinsong Wang & Yubi Yao & Wei Wang, 2016. "Risk evaluation of agricultural disaster impacts on food production in southern China by probability density method," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 83(3), pages 1605-1634, September.
    17. Ozaki, Vitor & Campos, Rogério, 2017. "Reduzindo a Incerteza no Mercado de Seguros: Uma Abordagem via Informações de Sensoriamento Remoto e Atuária," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 71(4), December.
    18. Ramirez, Octavio & Shonkwiler, J. Scott, 2016. "Some Comparative Statics for Evaluating the Performance of the US Crop Insurance Program," SCC-76 Meeting, 2016, March 17-19, Pensacola, Florida 233761, SCC-76: Economics and Management of Risk in Agriculture and Natural Resources.
    19. Ramsey, A., 2018. "Conditional Distributions of Crop Yields: A Bayesian Approach for Characterizing Technological Change," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277253, International Association of Agricultural Economists.
    20. A Ford Ramsey, 2020. "Probability Distributions of Crop Yields: A Bayesian Spatial Quantile Regression Approach," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(1), pages 220-239, January.
    21. Xuche Gong & David A. Hennessy & Hongli Feng, 2023. "Systemic risk, relative subsidy rates, and area yield insurance choice," American Journal of Agricultural Economics, John Wiley & Sons, vol. 105(3), pages 888-913, May.
    22. Fujin Yi & Mengfei Zhou & Yu Yvette Zhang, 2020. "Value of Incorporating ENSO Forecast in Crop Insurance Programs," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(2), pages 439-457, March.
    23. Ramirez, Octavio A. & Shonkwiler, J. Scott, 2017. "A Probabilistic Model of Crop Insurance Purchase Decision," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 42(1), pages 1-17, January.
    24. Ying-Erh Chen & Barry K Goodwin, 2015. "Policy Design of Multi-Year Crop Insurance Contracts with Partial Payments," PLOS ONE, Public Library of Science, vol. 10(12), pages 1-15, December.
    25. Christopher N. Boyer & B. Wade Brorsen & Emmanuel Tumusiime, 2015. "Modeling skewness with the linear stochastic plateau model to determine optimal nitrogen rates," Agricultural Economics, International Association of Agricultural Economists, vol. 46(1), pages 1-10, January.

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