Thompson, Nathanael M.

May, 2023

Implicit Market Segmentation and Valuation of Angus Bull Attributes

By: Tang, Minfeng; Thompson, Nathanael M.; Boyer, Christopher N.; Olynk Widmar, Nicole J.; Lusk, Jayson L.; Stewart, Terry S.; Lofgren, Donna L.; Minton, Nick
Previous hedonic assessments have largely relied on the assumption that bull buyers have homogeneous demands for bull attributes. However, quality differentiations and heterogeneous demands support the existence of submarkets. This analysis investigates market segments using a finite mixture model and 13 years of bull auction data. Results indicate that valuations of bull attributes vary across implicit buyer segments. Differences in demand may be influenced by a variety of factors, includingÑbut not limited toÑfarm goals, labor availability, and end-use marketing arrangements for calves. Results have important implications for signaling quality cues throughout the industryÕs breeding sectors.
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September, 2019

The Cost and Market Impacts of Slow-Growth Broilers

By: Lusk, Jayson L.; Thompson, Nathanael M.; Weimer, Shawna L.
There has been substantial productivity growth in the broiler industry; however, high growth rates might adversely affect animal welfare, resulting in calls for slow-growth breeds. This research shows production costs are 11%'25% per pound higher for slower-growing breeds than for modern breeds, depending on the target endpoint. Breakeven wholesale price premiums needed equate net returns of slow- to fast-growth broilers range from $0.10/lb to $0.36/lb. Annual costs of an industry-wide conversion to slow growth are $450 million for consumers and $3.1 billion for producers. Consumer willingness-to-pay would need to increase 10.8% to offset the producer losses.
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September, 2019

Practical Alternatives for Forecasting Corn and Soybean Basis in the Eastern Corn Belt throughout the Crop-Marketing Year

By: Thompson, Nathanael M.; Edwards, Aaron J.; Mintert, James R.; Hurt, Christopher A.
This paper re-evaluates practical methods of forecasting corn and soybean basis in the eastern Corn Belt. The accuracy of forecast methods differs over the course of the crop-marketing year. At harvest, historical moving average forecasts perform best. Post-harvest forecasts may be improved at short forecast horizons (<8'12 weeks ahead) by combining historical moving averages and recent basis levels. Results suggest that using 3-to-5-year moving average forecasts for corn basis and a 2- or 5-year moving average for soybean basis from harvest through April. The accuracy of these corn and soybean basis forecasts decreases markedly during the summer months.
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May, 2016

Using Genetic Testing to Improve Fed Cattle Marketing Decisions

By: Thompson, Nathanael M.; DeVuyst, Eric A.; Brorsen, B. Wade; Lusk, Jayson L.
We estimate the value of using genetic information to make fed cattle marketing decisions. Efficiency gains result from sorting cattle into marketing groups, including more accurate optimal days-on-feed and reduced variability of returns to cattle feeding. The value of using genetic information to selectively market cattle ranged from $1–$13/head depending on how a producer currently markets cattle and the grid structure. Although these values of genetic information were generally higher than those reported in previous research, they were still not enough to offset the current cost of genetic testing (about $40/head).
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April, 2014

Value of Genetic Information for Management and Selection of Feedlot Cattle

By: Thompson, Nathanael M.; DeVuyst, Eric A.; Brorsen, B. Wade; Lusk, Jayson L.
We estimate the value of using information from genetic marker panels for seven economically relevant feedlot cattle traits. The values of using genetic information to sort cattle by optimal days-on-feed are less than $1/head for each of the traits evaluated. However, the values associated with using genetic information to select cattle for placement are as much as $38/head. The most economically relevant genetic traits are average daily gain and marbling. It would not be profitable at the current testing cost of $38/head to sort cattle by optimal days-on-feed, but it could be profitable to use the genetic tests for breeding cattle selection.
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