Date of Award:
12-2026
Document Type:
Thesis
Degree Name:
Master of Science (MS)
Department:
Applied Economics
Committee Chair(s)
Ryan Feuz
Committee
Ryan Feuz
Committee
Andrew Anderson
Committee
Brandon Willis
Abstract
The US Department of Agriculture’s Risk Management Agency (RMA) offers livestock producers an insurance program called Livestock Gross Margin (LGM) insurance to protect against changes in commodity prices that negatively impact livestock producer profitability. LGM has been available to beef cattle producers since 2006, but the program has had little producer participation or academic interest, although the former may be changing thanks to the introduction of subsidies ranging from 18 to 50 percent in 2020. Loss ratios, defined as the indemnities producers receive divided by the premiums producers pay, from LGM-Cattle Summary of Business data suggest that the insurance program does not help producers protect profits on average. This research vastly expands the volume of relevant data by assessing how LGM would have performed for cattle producers from July 2009 to June 2025 under the program’s current rules including subsidies. Contract outcomes at every potential sales date and all deductible levels ($0 to $150 per head) as well as a representative set of twenty different marketing strategies are considered. The analysis suggests that, largely, producers are better off not purchasing the margin insurance program, and this, in turn, implies that LGM-Cattle is not priced effectively to meet RMA standards. Further research is recommended to determine a better-rated pricing model. Producers of both commodity types should insure cattle to be marketed in at least two months and avoid marketing beyond five months into the future. A higher feeder-to-corn price ratio is associated with better outcomes for calf finishing operations when using LGM-Cattle.
Recommended Citation
Berlin, Benjamin F., "Evaluating Livestock Gross Margin-Cattle Insurance Loss Ratios, Producer Outcomes, and the Case for Rating Model Reform From Hypothetical Contract Data" (2026). All Graduate Theses and Dissertations, Fall 2023 to Present. 961.
https://digitalcommons.usu.edu/etd2023/961
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