Essays on Seasonal Variation in Fed Cattle Profitability and the Value of Beef Bull Attributes.pdf (1.19 MB)
ESSAYS ON SEASONAL VARIATION IN FED CATTLE PROFITABILITY AND THE VALUE OF BEEF BULL ATTRIBUTES
thesisposted on 2020-12-09, 17:08 authored by Minfeng TangMinfeng Tang
The first essay investigates if bull buyers’ marginal valuations of Angus bull attributes have changed over time using 17 years of bull auction data from Indiana. Results indicate statistically significant time effects on some traits (e.g., ribeye area, percent intermuscular fat, ribeye area expected progeny difference [EPD], and maternal milk EPD). Not all of these effects align with prior expectations. Nonetheless, results have important implications for the beef industry in terms of signaling quality ques and incorporating proven information in the form of EPDs.
The second essay identifies heterogeneity in bull buyer valuations of bull attributes across latent class using a FMM. Results indicate evidence that bull buyers have heterogeneous preferences for bull attributes. A three-class FMM is identified as providing the best view of bull buyer heterogeneity. Although results do not perfectly align with the bull buyer segments hypothesized, the end-use of claves produced does influence the latent class identified. These results have implications for beef industry as a whole for the improvement of beef products.
The third essay examines seasonal variation of fed cattle profitability by considering seasonality of choice-select price spread and seasonal weather impact on cattle feedlot performance and carcass characteristics. Seasonality of choice-select price spread is empirically identified and is incorporated into the estimation and simulation of cattle feeding profitability. Results indicate that cattle profitability and variability are subject to the influence of both seasonal weather conditions and seasonality in choice-select price spread. Results could help producers make efficient management decisions through enhanced predictive capacity by using expected seasonal weather information and predicted seasonal price trend.
- Doctor of Philosophy
- Agricultural Economics
- West Lafayette