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The Value of Variable Rate Technology: An Information-Theoretic Approach

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  • Matías L. Ruffo
  • Donald G. Bullock
  • Germán A. Bollero

Abstract

We present a theoretical treatment of the economics of variable rate technology and its interplay with information. The framework facilitates description of on-farm empirical profitability studies of variable rate nitrogen application on Illinois cornfields. We estimate site-specific ex ante economically optimal nitrogen application rates, and the value of site-specific information in the management of variable rate technology. We find that with site-specific information provided free, variable rate nitrogen application would have been profitable in six of eight fields. Because private markets are unlikely to provide such information sufficiently, more public funding of long-term, multiregion, multiyear experimentation is appropriate. Copyright 2009, Oxford University Press.

Suggested Citation

  • Matías L. Ruffo & Donald G. Bullock & Germán A. Bollero, 2009. "The Value of Variable Rate Technology: An Information-Theoretic Approach," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 91(1), pages 209-223.
    • Handle: RePEc:oup:ajagec:v:91:y:2009:i:1:p:209-223
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    File URL: http://hdl.handle.net/10.1111/j.1467-8276.2008.01157.x
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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. 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.
    3. Nathan D. DeLay & Nathanael M. Thompson & James R. Mintert, 2022. "Precision agriculture technology adoption and technical efficiency," Journal of Agricultural Economics, Wiley Blackwell, vol. 73(1), pages 195-219, February.
    4. Jon T. Biermacher & B. Wade Brorsen & Francis M. Epplin & John B. Solie & William R. Raun, 2009. "The economic potential of precision nitrogen application with wheat based on plant sensing," Agricultural Economics, International Association of Agricultural Economists, vol. 40(4), pages 397-407, July.
    5. Ebel, Robert M. & Schimmelpfennig, David E., 2012. "Production Cost and the Sequential Adoption of Precision Technology," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 124393, Agricultural and Applied Economics Association.
    6. Osei, Edward & Li, Huijun, 2016. "Value of information: costs and returns of precision corn production in Livingston County, Illinois," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 236184, Agricultural and Applied Economics Association.
    7. Rejesus, Roderick M. & Marra, Michele C. & Roberts, Roland K. & English, Burton C. & Larson, James A. & Paxton, Kenneth W., 2013. "Changes in Producers' Perceptions of Within-Field Yield Variability after Adoption of Cotton Yield Monitors," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 45(2), pages 295-312, May.
    8. McFadden, Jonathan R., 2017. "Yield Maps, Soil Maps, and Technical Efficiency: Evidence from U.S. Corn Fields," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 258120, Agricultural and Applied Economics Association.
    9. DeLay, Nathan & Comstock, Haden, 2021. "Recent Trends in PA Technology Adoption and Bundling in CornProduction: Implications for Farm Consolidation," Western Economics Forum, Western Agricultural Economics Association, vol. 19(2), December.
    10. Späti, Karin & Huber, Robert & Finger, Robert, 2021. "Benefits of Increasing Information Accuracy in Variable Rate Technologies," Ecological Economics, Elsevier, vol. 185(C).
    11. Mojtaba Zeraatpisheh & Esmaeil Bakhshandeh & Mostafa Emadi & Tengfei Li & Ming Xu, 2020. "Integration of PCA and Fuzzy Clustering for Delineation of Soil Management Zones and Cost-Efficiency Analysis in a Citrus Plantation," Sustainability, MDPI, vol. 12(14), pages 1-17, July.
    12. Schimmelpfennig, David, 2016. "Farm Profits and Adoption of Precision Agriculture," Economic Research Report 249773, United States Department of Agriculture, Economic Research Service.
    13. Mills, Brian E. & Brorsen, B. Wade & Arnall, D. Brian, 2020. "Using Grid Soil Sampling to Determine Profit Maximizing Phosphorus Application Rates in Wheat," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 46(2), August.
    14. Jonathan R. McFadden & Alicia Rosburg & Eric Njuki, 2022. "Information inputs and technical efficiency in midwest corn production: evidence from farmers' use of yield and soil maps," American Journal of Agricultural Economics, John Wiley & Sons, vol. 104(2), pages 589-612, March.
    15. 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.
    16. Osei, Edward & Jafri, Syed H., 2015. "In-field Spatial Variability and Profitability of Precision Nitrogen Application On Corn in Buchanan County, Iowa," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205845, Agricultural and Applied Economics Association.
    17. Bullock, David S., 2013. "Simulating the Value of Information Generated by On-farm Agronomic Experimentation Using Precision Agriculture Technology," 2013: Productivity and Its Impacts on Global Trade, June 2-4, 2013. Seville, Spain 152370, International Agricultural Trade Research Consortium.
    18. McFadden, Jonathan & Njuki, Eric & Griffin, Terry, 2023. "Precision Agriculture in the Digital Era: Recent Adoption on U.S. Farms," USDA Miscellaneous 333550, United States Department of Agriculture.

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