IDEAS home Printed from https://ideas.repec.org/a/ags/ifaamr/303727.html
   My bibliography  Save this article

Identifying risk in production agriculture: an application of best-worst scaling

Author

Listed:
  • Atta, Cosmos
  • Micheels, Eric T.

Abstract

The identification and management of risk plays a significant role in reducing variability in farm income. The choice of risk management tools and strategies may depend on several factors, including the perceived importance of the risk and the perceived level of control that producers have in managing the risk. This study uses data from a 2017 survey of grain and oilseed farmers in Saskatchewan and employs a countbased approach of best-worst scaling and latent class cluster analysis to examine their perception of the most important sources of risk and the factors that influence these perceptions. The results suggest production and marketing risks, such as variation in output prices, rainfall variability, and changes in input prices, are the most important risks to farmers. However, results also reveal heterogeneity in responses to these identified risks, suggesting that a multifaceted approach is needed by farmers to address risk.

Suggested Citation

  • Atta, Cosmos & Micheels, Eric T., 2020. "Identifying risk in production agriculture: an application of best-worst scaling," International Food and Agribusiness Management Review, International Food and Agribusiness Management Association, vol. 23(2), May.
    • Handle: RePEc:ags:ifaamr:303727
    DOI: 10.22004/ag.econ.303727
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/303727/files/ifamr2019.0133.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.303727?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
    ---><---

    More about this item

    Keywords

    Farm Management; Risk and Uncertainty;

    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:ifaamr:303727. 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/ifamaea.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.