Theses and Dissertations

Advisor

Coatney, Kalyn

Committee Member

Lacy, Curtis

Committee Member

Li, Xaiofei

Committee Member

Zhou, Qian

Committee Member

Rivera, Daniel

Date of Degree

8-12-2026

Original embargo terms

Immediate Worldwide Access

Document Type

Graduate Thesis - Open Access

Major

Agriculture (Agricultural Economics)

Degree Name

Master of Science (M.S.)

College

College of Agriculture and Life Sciences

Department

Department of Agricultural Economics

Abstract

Cattle producers retain ownership through the feeding phase in the hopes of increasing profits. Because not all cattle generate positive profits, retention decisions on an individual basis substantially affect overall profitability. This study develops, simulates, and evaluates among others a new prediction methodology intended to help improve profitability. The method is an integrated framework combining a novel multilevel (hierarchical) growth model, futures basis-adjusted price forecasting, and production cost estimation to predict which animals are expected to be profitable. Individual performance data were collected for 12,066 in-sample (2003 to 2011) to predict growth and profits for 12,496 out-of-sample cattle (2011 to 2023). The study found that total profits increased for all projection methodologies as apposed to retaining all cattle. The new methodology slightly outperformed an industry-based group average projection methodology. However, both methods were surpassed by combining a refinement of the industry-based growth projections with the individuality of the new methodology.

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