IDEAS home Printed from https://ideas.repec.org/p/ags/uerssr/278796.html
   My bibliography  Save this paper

Weather and Yield, 1950-94: Relationships, Distributions, and Data

Author

Listed:
  • Teigen, Lloyd D.
  • Thomas, Milton, Jr.

Abstract

Nonlinear functions of weather explain almost all significant variations in crop yield. Corn, soybean, and spring wheat responses were estimated. Yields respond to monthly temperature and precipitation during May - September. Farm size is also important. Farms that harvest more acreage get higher yields. The yield distribution depends on the probability distribution of weather and the nonlinear response function. Temperature data follow a normal (symmetric) probability distribution, while precipitation data are better described by a (nonsymmetric) gamma distribution. The probability distribution for crop yields contains components that are normal, log-normal, chi-squared, and other random variables. Monthly temperature and precipitation data for 1950-94 are aggregated to State and regional estimates, using either harvested cropland or geographic area in 344 sub-State climatic divisions.

Suggested Citation

  • Teigen, Lloyd D. & Thomas, Milton, Jr., 1995. "Weather and Yield, 1950-94: Relationships, Distributions, and Data," Staff Reports 278796, United States Department of Agriculture, Economic Research Service.
    • Handle: RePEc:ags:uerssr:278796
    DOI: 10.22004/ag.econ.278796
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/278796/files/ers-report-657.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.278796?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
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Tannura, Michael A. & Irwin, Scott H. & Good, Darrel L., 2008. "Weather, Technology, and Corn and Soybean Yields in the U.S. Corn Belt," Marketing and Outlook Research Reports 37501, University of Illinois at Urbana-Champaign, Department of Agricultural and Consumer Economics.
    2. Clop-Gallart, M. Merce & Juarez-Rubio, Francisco, 2005. "Elicitation of Subjective Crop Yield PDF for DSS Implementation," 2005 International Congress, August 23-27, 2005, Copenhagen, Denmark 24561, European Association of Agricultural Economists.
    3. Kiker, Greg & Ranjan, Ram, 2006. "Decision Support System for Soybean Rust (Phakopsora pachyrhizi) Management using QnD," 2006 Annual meeting, July 23-26, Long Beach, CA 21248, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).

    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:uerssr:278796. 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.

    We have no bibliographic references for this item. You can help adding them by using 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/ersgvus.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.