IDEAS home Printed from https://ideas.repec.org/p/ags/aaea16/235798.html
   My bibliography  Save this paper

Estimating Site-Specific Crop Yield Response using Varying Coefficient Models

Author

Listed:
  • Li, Xiaofei
  • Coble, Keith H.
  • Tack, Jesse B.
  • Barnett, Barry J.

Abstract

This study estimates the site-specific crop yield response function using varying coefficient models. It is widely recognized that the parameters of yield response function vary dramatically across space and over time. Previous studies usually capture this variability of response by using locational and time dummy variables. While that approach reveals the existence of the response variability, the exact pattern of the variability is unknown, and the capacity of ex ante prediction of such models are limited. This study takes a step forward to explicitly explain how the response varies with the actual site characteristic variables, such as soil, water, topography, weather, and other factors that are commonly available to producers. By using the varying coefficient model, the parameters of the response function are specified to change continuously with those site variables. Based on a simulation data set, the varying coefficient model is demonstrate to outperform the site-dummy model by creating better variable rate application (VRA) fertilizer prescriptions. We further propose to apply the model to large sample of high resolution production data, and create ex ante spatially explicit optimal VRA fertilizer recommendations. The ultimate goal is to develop a precision decision system which can statistically turn the soil testing and weather forecasting information into input application prescriptions for producers.

Suggested Citation

  • Li, Xiaofei & Coble, Keith H. & Tack, Jesse B. & Barnett, Barry J., 2016. "Estimating Site-Specific Crop Yield Response using Varying Coefficient Models," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 235798, Agricultural and Applied Economics Association.
    • Handle: RePEc:ags:aaea16:235798
    DOI: 10.22004/ag.econ.235798
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/235798/files/Site-Specific%20Yield%20Response_2016_05_25_AAEA_Draft%20A.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.235798?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Hurley, Terrance M. & Malzer, Gary L. & Kilian, Bernard, 2003. "Estimating Site-Specific Nitrogen Crop Response Functions: A Conceptual Framework And Geostatistical Model," 2003 Annual meeting, July 27-30, Montreal, Canada 21950, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    2. 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.
    3. 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.
    4. 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.
    5. Bouman, B. A. M. & van Keulen, H. & van Laar, H. H. & Rabbinge, R., 1996. "The `School of de Wit' crop growth simulation models: A pedigree and historical overview," Agricultural Systems, Elsevier, vol. 52(2-3), pages 171-198.
    6. 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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    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. 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.
    4. 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.
    5. Velandia Margarita & Roderick M. Rejesus & Eduardo Segarra & Kevin Bronson, 2004. "Un análisis económico de la aproximación estadística para el establecimiento de zonas de manejo en agricultura de precisión: caso de algodón en Texas," Revista Desarrollo y Sociedad, Universidad de los Andes,Facultad de Economía, CEDE, September.
    6. Lambert, Dayton M. & Lowenberg-DeBoer, James & Malzer, Gary L., 2005. "Managing Phosphorous Soil Dynamics Over Space And Time," 2005 Annual meeting, July 24-27, Providence, RI 19452, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    7. Garth Holloway & Donald Lacombe & James P. LeSage, 2007. "Spatial Econometric Issues for Bio‐Economic and Land‐Use Modelling," Journal of Agricultural Economics, Wiley Blackwell, vol. 58(3), pages 549-588, September.
    8. Oishi, Kikuo & Hurley, Terrance M. & Malzer, Gary L., 2006. "Evidence of Temporal Variation in Site-Specific Crop Response to Fertilizer Inputs," 2006 Annual meeting, July 23-26, Long Beach, CA 21140, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    9. Velandia, Margarita M. & Rejesus, Roderick M. & Segarra, Eduardo & Bronson, Kevin, 2006. "Economics of Management Zone Delineation in Cotton Precision Agriculture," 2006 Annual Meeting, August 12-18, 2006, Queensland, Australia 25783, International Association of Agricultural Economists.
    10. Lambert, Dayton M. & Lowenberg-DeBoer, James & Malzer, Gary L., 2004. "A Systems Approach For Evaluating On-Farm Site-Specific Management Trials: A Case Study With Variable Rate Manure And Crop Quality Response To Inputs," 2004 Annual meeting, August 1-4, Denver, CO 20091, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    11. Lambert, Dayton M. & Malzer, Gary L. & Lowenberg-DeBoer, James, 2003. "A Systems Approach Incorporating Soil Test Information Into Site-Specific Manure Management Recommendations," Staff Papers 28623, Purdue University, Department of Agricultural Economics.
    12. Sharp, Benjamin E. & Miller, Shelie A., 2014. "Estimating maximum land use change potential from a regional biofuel industry," Energy Policy, Elsevier, vol. 65(C), pages 261-269.
    13. Chai, Yuan & Pannell, David J. & Pardey, Philip G., 2022. "Reducing Water Pollution from Nitrogen Fertilizer: Revisiting Insights from Production Economics," Staff Papers 320519, University of Minnesota, Department of Applied Economics.
    14. Saikai, Yuji & Patel, Vivak & Mitchell, Paul, 2020. "Machine learning for optimizing complex site-specific management," 2020 Conference (64th), February 12-14, 2020, Perth, Western Australia 305238, Australian Agricultural and Resource Economics Society.
    15. Lambert, Dayton M. & Malzer, Gary L. & Lowenberg-DeBoer, James, 2004. "General Moment And Quasi-Maximum Likelihood Estimation Of A Spatially Autocorrelated System Of Equations: An Empirical Example Using On-Farm Precision Agriculture Data," Staff Papers 28667, Purdue University, Department of Agricultural Economics.
    16. Harou, Aurélie & Liu, Yanyan & Barrett, Christopher B. & You, Liangzhi, 2014. "Variable returns to fertilizer use and its relationship to poverty: Experimental and simulation evidence from Malawi:," IFPRI discussion papers 1373, International Food Policy Research Institute (IFPRI).
    17. 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.
    18. Uri Shani & Yacov Tsur & Amos Zemel & David Zilberman, 2009. "Irrigation production functions with water‐capital substitution," Agricultural Economics, International Association of Agricultural Economists, vol. 40(1), pages 55-66, January.
    19. CARPENTIER, Alain & GOHIN, Alexandre & SCKOKAI, Paolo & THOMAS, Alban, 2015. "Economic modelling of agricultural production: past advances and new challenges," Review of Agricultural and Environmental Studies - Revue d'Etudes en Agriculture et Environnement (RAEStud), Institut National de la Recherche Agronomique (INRA), vol. 96(1), March.
    20. 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.

    More about this item

    Keywords

    Crop Production/Industries; Farm Management; Production Economics; Productivity Analysis;
    All these keywords.

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ags:aaea16:235798. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/aaeaaea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.