Recognizing Production Risk a Use of Best-worst Scaling in Agriculture

Risk, Risk management, Best-worst scaling, Latent class cluster.

Abstract

A Reducing agricultural revenue variability is mostly dependent on risk assessment and management. The perceived significance of the risk and the perceived degree of control that producers have over risk management are two variables that may influence the selection of risk management instruments and techniques. This study examines how Saskatchewan grain and oilseed farmers perceive the most significant sources of risk and the factors that affect these perceptions using data from a 2017 survey. It does this by using a count-based method of best-worst scaling and latent class cluster analysis. The findings imply that the most significant risks for farmers are those related to production and marketing, including fluctuations in input pricing, rainfall variability, and output price variation. Nevertheless, the findings also show variation in how these hazards were responded to, indicating that farmers must handle risk in a variety of ways.