A Best-Worst Scaling Approach To Understand The Risk Management Preferences Of Saskatchewan Grain And Oilseed Farmers

Cosmos Atta and Eric Micheels

No 345977, Agricultural Economics Society (AES) 98th Annual Conference, The University of Edinburgh, Edinburgh, UK, March 18-20, 2024 from Agricultural Economics Society (AES)

Abstract: Farm managers must continuously manage risk in their farm business if they are to remain competitive and successful in their farm business operations. Although various risk management strategies can be adopted to reduce the uncertainties farmers face, the choice of a risk management strategy is influenced by the unique characteristics of the farm or the farm manager. Therefore, assuming a relationship between a particular risk and the strategy to be adopted may not necessarily be valid across heterogeneous decision makers. Using data from a 2017 survey, the risk management practices of grain and oilseed farmers in Saskatchewan is examined using a count-based approach of best-worst scaling and latent class cluster analysis. The results indicate there is considerable diversity among strategies producers perceive important.

Keywords: Risk and Uncertainty; Farm Management (search for similar items in EconPapers)
Pages: 17
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://ageconsearch.umn.edu/record/345977/files/a ... _oilseed_farmers.pdf (application/pdf)

Related works:
Working Paper: A Best-Worst Scaling Approach To Understand The Risk Management Preferences Of Saskatchewan Grain And Oilseed Farmers (2022)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ags:aes324:345977

DOI: 10.22004/ag.econ.345977

Access Statistics for this paper

More papers in Agricultural Economics Society (AES) 98th Annual Conference, The University of Edinburgh, Edinburgh, UK, March 18-20, 2024 from Agricultural Economics Society (AES)
Bibliographic data for series maintained by AgEcon Search ().