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Using Spatial Analysis to Study the Values of Variable Rate Technology and Information

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  • David S. Bullock
  • James Lowenberg‐DeBoer

Abstract

For adoption of variable rate technology to increase, more knowledge of how crop yields respond to inputs is needed. As the necessary agronomic research involves approximating site‐specific yield response functions, data used inherently lend themselves to spatial analysis. We discuss the different types of spatial analyses that may be appropriate. Then we present a taxonomy for the discussion of the economics of technology and information, and use it to review studies that have contributed significantly to the literature over the past few years. We contend that longer‐term, multilocation agronomic experiments are needed for the estimation of site‐specific ex ante optimal variable input rates, and of expected profitability of variable rate technology and information.

Suggested Citation

  • 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.
    • Handle: RePEc:bla:jageco:v:58:y:2007:i:3:p:517-535
    DOI: 10.1111/j.1477-9552.2007.00116.x
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    References listed on IDEAS

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    1. Luc Anselin & Rodolfo Bongiovanni & Jess Lowenberg-DeBoer, 2004. "A Spatial Econometric Approach to the Economics of Site-Specific Nitrogen Management in Corn Production," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 86(3), pages 675-687.
    2. Neil R. Miller, 2006. "Is Site-Specific Yield Response Consistent over Time? Does It Pay?," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 88(2), pages 471-483.
    3. 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.
    4. Bullock, David S. & Lowenberg-DeBoer, Jess & Swinton, Scott M., 2002. "Adding value to spatially managed inputs by understanding site-specific yield response," Agricultural Economics, Blackwell, vol. 27(3), pages 233-245, November.
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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. 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. 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.
    5. 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.
    6. Hough, Ella Christina & Nell, Wilhelm T. & Maine, Ntsikane & Groenewald, Jan A. & van der Rijst, M., 2010. "Best fit model selection for spatial differences (regression) in the profitability analysis of precision phosphate (P) application to winter cereals in Precision Agriculture (PA)," 2010 AAAE Third Conference/AEASA 48th Conference, September 19-23, 2010, Cape Town, South Africa 96642, African Association of Agricultural Economists (AAAE).
    7. 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.
    8. Bourgain, Odile & Llorens, Jean-Marc, 2013. "Simulation des seuils de rentabilité économique de techniques d’application localisée des pesticides," Économie rurale, French Society of Rural Economics (SFER Société Française d'Economie Rurale), vol. 333(January-F).

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    More about this item

    JEL classification:

    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • Q16 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - R&D; Agricultural Technology; Biofuels; Agricultural Extension Services

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