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Optimal Information Acquisition under a Geostatistical Model

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

Abstract

Develops a framework for incorporating estimation risk into a decision model to determine the optimal amount of soil test information when applying nitrogen fertilizer using a variable rate technology (VRT). Producers should acknowledge that the soil nitrate mapping is a collection of estimates and does not provide information at non-sampled sites. Switching from single rate technology to VTR is more plausible for fields with greatest soil nitrate variability.

Suggested Citation

  • Gregory R. Pautsch & Bruce A. Babcock & F. Jay Breidt, 1999. "Optimal Information Acquisition under a Geostatistical Model," Center for Agricultural and Rural Development (CARD) Publications 99-wp217, Center for Agricultural and Rural Development (CARD) at Iowa State University.
    • Handle: RePEc:ias:cpaper:99-wp217
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    1. Lence, Sergio H. & Hayes, Dermot J., 1995. "Land Allocation In The Presence Of Estimation Risk," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 20(1), pages 1-15, July.
    2. Hennessy, David A. & Babcock, Bruce A., 1998. "Information, flexibility, and value added1," Information Economics and Policy, Elsevier, vol. 10(4), pages 431-449, December.
    3. Babcock, Bruce A. & Blackmer, Alfred M., 1992. "The Value Of Reducing Temporal Input Nonuniformities," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 17(2), pages 1-13, December.
    4. Hennessy, David A. & Babcock, Bruce A., 1998. "Information, Flexibility, and Value Added," Staff General Research Papers Archive 1362, Iowa State University, Department of Economics.
    5. James A. Chalfant & Robert N. Collender & Shankar Subramanian, 1990. "The Mean and Variance of the Mean-Variance Decision Rule," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 72(4), pages 966-974.
    6. Babcock, Bruce A. & Pautsch, Gregory R., 1998. "Moving From Uniform To Variable Fertilizer Rates On Iowa Corn: Effects On Rates And Returns," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 23(2), pages 1-16, December.
    7. Sergio H. Lence & Dermot J. Hayes, 1994. "The Empirical Minimum-Variance Hedge," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 76(1), pages 94-104.
    8. Swinton, Scott M. & Jones, Kezelee Q., 1998. "From Data To Information: The Value Of Sampling Vs. Sensing Soil Data," Staff Paper Series 11674, Michigan State University, Department of Agricultural, Food, and Resource Economics.
    9. Bruce A. Babcock, 1992. "The Effects of Uncertainty on Optimal Nitrogen Applications," Review of Agricultural Economics, Agricultural and Applied Economics Association, vol. 14(2), pages 271-280.
    10. Bruce A. Babcock & Alicia L. Carriquiry & Hal S. Stern, 1996. "Evaluation of Soil Test Information in Agricultural Decision‐Making," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 45(4), pages 447-461, December.
    11. Wesley N. Musser & James S. Shortle & Kathleen Kreahling & Brian Roach & Wen-Chi Huang & Douglas B. Beegle & Richard H. Fox, 1995. "An Economic Analysis of the Pre-sidedress Nitrogen Test for Pennsylvania Corn Production," Review of Agricultural Economics, Agricultural and Applied Economics Association, vol. 17(1), pages 25-35.
    12. Christopher Ackello-Ogutu & Quirino Paris & William A. Williams, 1985. "Testing a von Liebig Crop Response Function against Polynomial Specifications," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 67(4), pages 873-880.
    13. Klein, Roger W, et al, 1978. "Decisions with Estimation Uncertainty," Econometrica, Econometric Society, vol. 46(6), pages 1363-1387, November.
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    Cited by:

    1. 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).
    2. 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.
    3. 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.
    4. 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.
    5. 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).
    6. 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.
    7. 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).
    8. 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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