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An Economic Assessment Of The Whole-Farm Impact Of Precision Agriculture

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  • Olson, Kent D.
  • Elisabeth, Pascal
Abstract
The full impact of an investment in a management information system (MIS), such as precision agriculture (PA), comes from improved managerial decision making throughout the whole farm and not just from improvements in a specific part of the farm. This study was conducted to determine whether the adoption of PA had a positive impact on whole-farm profitability. To overcome problems of simultaneity and self-selection in the adoption decision of PA, this study used a two stage econometric model using data from farms in Southwest Minnesota. The PA adoption decision was evaluated in the first stage, and the impact of adopting PA was evaluated in the second stage. The whole farm rate of return to assets (ROA) was used to measure the impact of PA. For all 212 farms in the dataset, the adoption of precision agriculture was explained significantly (p<0.1) by two variables: positively by the farmer's self-described soil variability and negatively by the level of non-farm income. For the 63 crop farms in the dataset, adoption of PA was explained significantly (p<0.1) only by the farmer's self-described soil variability. The adoption of PA was estimated to have a significant (p<0.1) negative impact on ROA for the entire group of farms but was not significant when the farms were separated into crop farms only and into size clusters. PA's lack of significance in explaining ROA in the subgroups may be due to small sample size, the variability of ROA itself, the lack of fully implementing PA as an MIS, differences in management ability, and the availability of other farming methods that are just as profitable as PA.

Suggested Citation

  • Olson, Kent D. & Elisabeth, Pascal, 2003. "An Economic Assessment Of The Whole-Farm Impact Of Precision Agriculture," 2003 Annual meeting, July 27-30, Montreal, Canada 22119, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    • Handle: RePEc:ags:aaea03:22119
    DOI: 10.22004/ag.econ.22119
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    References listed on IDEAS

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    7. Tomaszewski, M. A. & van Asseldonk, M. A. P. M. & Dijkhuizen, A. A. & Huirne, R. B. M., 2000. "Determining farm effects attributable to the introduction and use of a dairy management information system in The Netherlands," Agricultural Economics, Blackwell, vol. 23(1), pages 79-86, June.
    8. Tvedt, Douglas D. & Olson, Kent D. & Hawkins, Douglas M., 1989. "Short-Run Indicators Of Financial Success For Southwest Minnesota Farmers," Staff Papers 13933, University of Minnesota, Department of Applied Economics.
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    Cited by:

    1. Miller, Noah J. & Bergtold, Jason S. & Griffin, Terry W. & Shanoyan, Aleksan, 2017. "A Spatio-Temporal Analysis of the Adoption Process of Complementary Precision Agricultural Practices in Kansas," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 258199, Agricultural and Applied Economics Association.
    2. Griffin, Terry W. & Yeager, Elizabeth A. & Ibendahl, Gregg, 2019. "Pr - Adoption Of Precision Agriculture Technology," 22nd Congress, Tasmania, Australia, March 3-8, 2019 345898, International Farm Management Association.
    3. Miller, Noah J. & Griffin, Terry & Bergtold, Jason & Sharda, Ajay & Ciampitti, Ignacio, 2017. "Adoption of Precision Agriculture Technology Bundles on Kansas Farms," 2017 Annual Meeting, February 4-7, 2017, Mobile, Alabama 252832, Southern Agricultural Economics Association.

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