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Determining Optimal Levels of Nitrogen Fertilizer Using Random Parameter Models

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  • Tumusiime, Emmanuel
  • B. Wade, Brorsen
  • Mosali, Jagadeesh
  • Johnson, Jim
  • Locke, James
  • Biermacher, Jon T.

Abstract

The parameters of yield response functions can vary by year. Past studies usually assume yield functions are nonstochastic or “limited” stochastic. In this study, we estimate rye–ryegrass yield functions in which all parameters are random. The three functional forms considered are the linear response plateau, the quadratic, and the Spillman-Mitscherlich. Nonstochastic yield models are rejected in favor of stochastic parameter models. Quadratic functional forms fit the data poorly. Optimal nitrogen application recommendations are calculated for the linear response plateau and Spillman-Mitscherlich. The stochastic models lead to smaller recommended levels of nitrogen, but the economic benefits of using fully stochastic crop yield functions are small because expected profit functions are relatively flat for the stochastic yield functions. Stochastic crop yield functions provide a way of incorporating production, uncertainty into input decisions.

Suggested Citation

  • Tumusiime, Emmanuel & B. Wade, Brorsen & Mosali, Jagadeesh & Johnson, Jim & Locke, James & Biermacher, Jon T., 2011. "Determining Optimal Levels of Nitrogen Fertilizer Using Random Parameter Models," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 43(4), pages 541-552, November.
    • Handle: RePEc:cup:jagaec:v:43:y:2011:i:04:p:541-552_00
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    Cited by:

    1. Mkondiwa, Maxwell Gibson, 2015. "Whither Broad or Spatially Specific Fertilizer Recommendations?," Master's Theses and Plan B Papers 237344, University of Minnesota, Department of Applied Economics.
    2. Klaus Moeltner & A. Ford Ramsey & Clinton L. Neill, 2021. "Bayesian Kinked Regression with Unobserved Thresholds: An Application to the von Liebig Hypothesis," American Journal of Agricultural Economics, John Wiley & Sons, vol. 103(5), pages 1832-1856, October.
    3. Park, Seong Cheol & Vitale, Jeffrey D. & Turner, Jason Clemn & Stoecker, Arthur L. & Hattey, Jeffory A., 2011. "Economic Potential of Swine Effluent in Intensified Forage Systems in the Southern Plains," Journal of the ASFMRA, American Society of Farm Managers and Rural Appraisers, vol. 2011, pages 1-22, June.
    4. Boyer, Christopher N. & Larson, James A. & Roberts, Roland K. & McClure, Angela T. & Tyler, Donald D. & Zhou, Vivian, 2013. "Stochastic Corn Yield Response Functions to Nitrogen for Corn after Corn, Corn after Cotton, and Corn after Soybeans," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 45(4), pages 669-681, November.
    5. McFadden, Brandon R. & Brorsen, B. Wade, 2015. "Pr - Nitrogen Fertilizer Recommendations Based On Precision Sensing And Bayesian Updating," 20th Congress, Quebec, Canada, 2015 345756, International Farm Management Association.
    6. Brorsen, B. & Ouedraogo, Frederic, 2015. "Using Bayesian Estimation Methods to Determine Optimal Levels of Nitrogen Fertilization," 2015 Conference, August 9-14, 2015, Milan, Italy 211373, International Association of Agricultural Economists.
    7. Park, Seong C. & Brorsen, B. Wade & Stoecker, Arthur L. & Hattey, Jeffory A., 2012. "Forage Response to Swine Effluent: A Cox Nonnested Test of Alternative Functional Forms Using a Fast Double Bootstrap," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 44(4), pages 593-606, November.
    8. Du, Qianqian & Mieno, Taro & Bullock, David S., 2023. "Measuring the Estimation Bias of Yield Response to N Using Combined On-Farm Experiment Data," Land, Farm & Agribusiness Management Department 344222, Harper Adams University, Land, Farm & Agribusiness Management Department.
    9. Boyer, Christopher N. & Larson, James A. & Roberts, Roland K. & McClure, Angela T. & Tyler, Donald D. & Smith, S. Aaron, 2014. "Probability of Irrigated Corn Being Profitable in a Humid Region," 2014 Annual Meeting, February 1-4, 2014, Dallas, Texas 162470, Southern Agricultural Economics Association.
    10. Agarwal, Sandip Kumar, 2017. "Subjective beliefs and decision making under uncertainty in the field," ISU General Staff Papers 201701010800006248, Iowa State University, Department of Economics.
    11. Du, Qianqian & Mieno, Taro & Bullock, David S., 2023. "Measuring the Estimation Bias of Yield Response to N Using Combined On-Farm Experiment Data," Agri-Tech Economics Papers 344222, Harper Adams University, Land, Farm & Agribusiness Management Department.
    12. Du, Qianqian & Mieno, Taro & Bullock, David S., 2024. "Measuring the Estimation Bias of Yield Response to N Using Combined On-Farm Experiment Data," 2024 Annual Meeting, July 28-30, New Orleans, LA 344051, Agricultural and Applied Economics Association.
    13. Rashki, Paria & piri, halimeh & Khamari, Eisa, 2022. "Determining the production function and optimal irrigation depth of Roselle in deficit irrigation conditions and using potassium fertilizer," Agricultural Water Management, Elsevier, vol. 271(C).
    14. Harmon, Xavier & Boyer, Christopher N. & Lambert, Dayton M. & Larson, James A., 2017. "Temporal Frequency Of Soil Test Information Effects On Returns To Potassium Fertilization In Cotton Production," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 49(2), pages 251-272, May.
    15. Frederic Ouedraogo & B. Wade Brorsen, 2018. "Hierarchical Bayesian Estimation of a Stochastic Plateau Response Function: Determining Optimal Levels of Nitrogen Fertilization," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 66(1), pages 87-102, March.
    16. Harmon, Xavier & Boyer, Christopher N. & Lambert, Dayton M. & Larson, James A. & Gwathmey, C. Owen, 2016. "Comparing the Value of Soil Test Information Using Deterministic and Stochastic Yield Response Plateau Functions," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 41(2), May.

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    More about this item

    JEL classification:

    • Q10 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - General
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity

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