IDEAS home Printed from https://ideas.repec.org/p/ags/aaea12/124759.html

When do the USDA forecasters make mistakes?

Author

Listed:
  • Isengildina-Massa, Olga
  • Karali, Berna
  • Irwin, Scott H.

Abstract

This study analysed forecasts for all US corn, soya bean and wheat categories published within the World Agricultural Supply and Demand Estimates (WASDE ) reports over the 1987/88 through 2009/10 marketing years in an attempt to identify patterns and better understand when the USDA forecasters make mistakes. Two general sources of errors were investigated: behavioural and macroeconomic factors. The first objective was to examine how these factors affect the size of the forecast error and the second concentrated on the direction of the error due to these effects. Our findings suggest that the largest increase in the size of USDA forecast errors was associated with structural changes in commodity markets that took place in the mid-2000s. Corn, soya bean and wheat forecast errors also grew during the periods of economic growth and with changes in exchange rates, while inflation and changes in oil price had a much smaller impact. With respect to behavioural sources, we identified patterns consistent with leniency and pessimism across different categories. Predictability of forecast errors based on the information available at the time the forecasts are made provides evidence of inefficiency and suggests that these forecasts may be improved using the findings of this study.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Isengildina-Massa, Olga & Karali, Berna & Irwin, Scott H., "undated". "When do the USDA forecasters make mistakes?," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 124759, Agricultural and Applied Economics Association.
    • Handle: RePEc:ags:aaea12:124759
    DOI: 10.22004/ag.econ.124759
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/124759/files/When%20forecasters%20make%20mistakes_AAEA_2012.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.124759?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
    ---><---

    Other versions of this item:

    Citations

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


    Cited by:

    1. is not listed on IDEAS
    2. MacDonald, Stephen & Ash, Mark & Cooke, Bryce, 2017. "The Evolution of Inefficiency in USDA’s Forecasts of U.S. and World Soybean Markets," MPRA Paper 87545, University Library of Munich, Germany.
    3. Bahram Sanginabadi, 2018. "USDA Forecasts: A meta-analysis study," Papers 1801.06575, arXiv.org.
    4. Li, Ziran & Li, Ding & Zhang, Tengfei & Zhang, Tianyang, 2022. "Climate impact on the USDA ending stocks forecast errors," Finance Research Letters, Elsevier, vol. 48(C).
    5. Zhang, Tianyang & Li, Ziran, "undated". "How Well Do Rational Expectations Storage Model Forecast Crop Ending Stocks?," 2018 Annual Meeting, August 5-7, Washington, D.C. 273803, Agricultural and Applied Economics Association.
    6. Massa, Olga Isengildina & Karali, Berna & Kuethe, Todd & Katchova, Ani, 2019. "Sources of Errors In USDA’s Net Cash Income Forecasts," 2019 Conference, April 15-16, 2019, Minneapolis, Minnesota 309630, NCR-134/ NCCC-134 Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
    7. Tianyang Zhang & Ziran Li, 2022. "Can a rational expectation storage model explain the USDA ending grain stocks forecast errors?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(3), pages 313-337, March.

    More about this item

    Keywords

    ;
    ;

    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:aaea12:124759. 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/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.