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Estimating the Potential Value of Variable Rate Nitrogen Applications: A Comparison of Spatial Econometric and Geostatistical Models

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  • Hurley, Terrance M.
  • Oishi, Kikuo
  • Malzer, Gary L.

Abstract

Site-specific crop response functions (SSCRFs) are useful for estimating the value of variable rate nitrogen applications (VRA), but appropriate statistical models are necessary. Problems estimating SSCRFs using experimental field data include region, spatial, treatment, and strip dependent heteroskedasticity and correlation. We develop a spatial autoregressive error (SARE) model for dealing with these problems and compare results with previous analysis based on a geostatistical (GEO) model. VRA value estimates for the two models differ notably for 1995 data from Southern Minnesota. Furthermore, findings show that the results of a comparison of model performance are location specific.

Suggested Citation

  • Hurley, Terrance M. & Oishi, Kikuo & Malzer, Gary L., 2005. "Estimating the Potential Value of Variable Rate Nitrogen Applications: A Comparison of Spatial Econometric and Geostatistical Models," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 30(2), pages 1-19, August.
    • Handle: RePEc:ags:jlaare:31210
    DOI: 10.22004/ag.econ.31210
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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. Perrin, Richard K. & Queiroz, Pedro & Silva, Felipe & Fulginiti, Lilyan E., 2018. "Ex-ante expected payoff from variable rate N application: an expected value of sample information (EVSI) approach," 2018 Annual Meeting, August 5-7, Washington, D.C. 274351, Agricultural and Applied Economics Association.
    3. Oishi, Kikuo & Hurley, Terrance M. & Malzer, Gary L., 2006. "Evidence of Temporal Variation in Site-Specific Crop Response to Fertilizer Inputs," 2006 Annual meeting, July 23-26, Long Beach, CA 21140, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    4. David S. Bullock & James Lowenberg‐DeBoer, 2007. "Using Spatial Analysis to Study the Values of Variable Rate Technology and Information," Journal of Agricultural Economics, Wiley Blackwell, vol. 58(3), pages 517-535, September.
    5. Queiroz, Pedro W. V. & Perrin, Richard K. & Fulginiti, Lilyan E. & Bullock, David S., 2023. "An Expected Value of Sample Information (EVSI) Approach for Estimating the Payoff from a Variable Rate Technology," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 48(1), January.
    6. Harper, David C. & Lambert, Dayton M. & Larson, James A. & Gwathmey, C. Owen, 2012. "Potassium carryover dynamics and optimal application policies in cotton production," Agricultural Systems, Elsevier, vol. 106(1), pages 84-93.
    7. Li, Xiaofei & Coble, Keith H. & Tack, Jesse B. & Barnett, Barry J., 2016. "Estimating Site-Specific Crop Yield Response using Varying Coefficient Models," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 235798, Agricultural and Applied Economics Association.

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    Keywords

    Crop Production/Industries;

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