Producer perception of fed cattle price risk

Abstract

Risk is an inevitable part of agricultural production and all producers face various forms of risk. Output price has been shown to be the major contributor to the risk in cattle feeding, yet few choose to manage this risk. This study used subjective price expectations and price distributions of survey participants to determine how producer's expectations compare with that of the market. In addition, demographic information gathered from survey participants allowed for further examination as to how these factors effect price outlook and variability. Data used for this study were gathered through survey responses from Kansas State University Extension meeting and workshop participants and other meetings targeted to livestock producers. First, data were aggregated and analyzed at a group level. Only two of the twelve price forecast were significantly lower than the futures settlement price. On the other hand, all but one of the aggregated group volatility expectations was different. Typically nearby contract price risk expectation was underestimated and distant contract price risk expectation was overestimated. Individual respondent's discreet stated price and price distribution information was fitted to a continuous distribution and an implied mean and standard deviation were determined. These were compared to market price and price risk data. Respondent's expectation of price was significantly lower than the market for distant months for five of the six groups. Individual volatilities resulting from each fitted distribution were significantly lower from the volatility measure resulting from Black's model. Demographic data were estimated to show the impact of this information on overall error of price forecast and price risk expectations. Those living outside the Northeast and Northern Plains tended to have larger error in their expectation of price volatility. Larger backgrounding operations reported lower price variance error and selling more fed cattle each year increased price risk expectation error. Lastly, prior use of risk management tools for the most part did not have an impact on error in either price expectation or price volatility expectation.