Author
Feuz, Ryan
We identify optimal producer-selected coverage options across all marketing months and insurable commodities within Livestock Risk Protection Insurance. Optimal contracts are defined as those having combinations of coverage length and level that have historically provided the highest probability of a positive net return and the highest average net return. Using probabilistic modeling, we evaluate the effect of producer size on the likelihood of purchasing optimal contracts. Results indicate that (i) optimal contracts generally have relatively higher coverage levels, (ii) producers often purchase contracts not identified as optimal, and (iii) producers are categorized within two distinct groups when considering optimal contract selection.
We identify optimal producer-selected coverage options across all marketing months and insurable commodities within Livestock Risk Protection Insurance. Optimal contracts are defined as those having combinations of coverage length and level that have historically provided the highest probability of a positive net return and the highest average net return. Using probabilistic modeling, we evaluate the effect of producer size on the likelihood of purchasing optimal contracts. Results indicate that (i) optimal contracts generally have relatively higher coverage levels, (ii) producers often purchase contracts not identified as optimal, and (iii) producers are categorized within two distinct groups when considering optimal contract selection.
Feedlot managers make difficult culling decisions using their best subjective judgment together with advice from animal health professionals. Using routinely collected operational feedlot data and five well-known classification methods, we construct mortality predictive models to aid managers in making objective culling decisions. Simulation results suggest that net return per head for calves having been treated at least once for any health incident would increase on average by $14.01 if the best-performing model were used as a culling decision aid. The probability of a positive return is 60.9%. Using cost-sensitive learning, the average value may increase to $45.27/head.