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Optimal Information Acquisition Under A Geostatistical Model

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  • Pautsch, Gregory R.
  • Babcock, Bruce A.
  • Breidt, F. Jay

Abstract

Studies examining the value of switching to a variable rate technology (VRT) fertilizer program assume producers possess perfect soil nitrate information. In reality, producers estimate soil nitrate levels with soil sampling. The value of switching to a VRT program depends on the quality of the estimates and on how the estimates are used. Larger samples sizes, increased spatial correlation, and decreased variability improve the estimates and increase returns. Fertilizing strictly to the estimated field map fails to account for estimation risk. Returns increase if the soil sample information is used in a Bayesian fashion to update the soil nitrate beliefs in nonsampled sites.

Suggested Citation

  • Pautsch, Gregory R. & Babcock, Bruce A. & Breidt, F. Jay, 1999. "Optimal Information Acquisition Under A Geostatistical Model," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 24(2), pages 1-25, December.
    • Handle: RePEc:ags:jlaare:30797
    DOI: 10.22004/ag.econ.30797
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    Cited by:

    1. Lindset, Snorre & Lund, Arne-Christian & Matsen, Egil, 2009. "Optimal information acquisition for a linear quadratic control problem," European Journal of Operational Research, Elsevier, vol. 199(2), pages 435-441, December.
    2. Rejesus, Roderick M. & Nelson, Carl H., 2000. "Determinants Of The Value Of Site-Specific Information (Ssi) In Agriculture: A Unifying Theory To Analyze Its Relative Impacts," 2000 Annual meeting, July 30-August 2, Tampa, FL 21779, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    3. Hurley, Terrance M. & Kilian, Bernard & Malzer, Gary L. & Dikici, Huseyin, 2001. "The Value Of Information For Variable Rate Nitrogen Applications: A Comparison Of Soil Test, Topographical, And Remote Sensing Information," 2001 Annual meeting, August 5-8, Chicago, IL 20726, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    4. Biermacher, Jon T. & Epplin, Francis M. & Brorsen, B. Wade & Solie, John B. & Raun, Bill, 2006. "Precision Nitrogen Fertilization Technology with Micro Grids," 2006 Annual meeting, July 23-26, Long Beach, CA 21046, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    5. Lichtenberg, Erik & Majsztrik, John & Saavoss, Monica, 2014. "Willingness to Pay for Sensor-Controlled Irrigation," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 168211, Agricultural and Applied Economics Association.
    6. Tembo, Gelson & Brorsen, B. Wade & Epplin, Francis M., 2003. "Linear Response Stochastic Plateau Functions," 2003 Annual Meeting, February 1-5, 2003, Mobile, Alabama 35217, Southern Agricultural Economics Association.
    7. 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.
    8. Isik, Murat & Khanna, Madhu, 2002. "Variable-Rate Nitrogen Application Under Uncertainty: Implications For Profitability And Nitrogen Use," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 27(1), pages 1-16, July.
    9. McFadden, Brandon R. & Lusk, Jayson L., 2015. "Cognitive biases in the assimilation of scientific information on global warming and genetically modified food," Food Policy, Elsevier, vol. 54(C), pages 35-43.

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