Master of Science / Department of Agricultural Economics / Glynn T. Tonsor / The past several years has marked one of the most heightened periods of fed cattle basis volatility since the installment of live cattle futures contracts. Understanding basis, the difference between local cash price and the futures contract price, is imperative when making marketing and procurement decisions. In the face of increased volatility, the ability to produce accurate basis expectations is no simple task. The purpose of these analyses was to develop econometric models to determine the greatest influencers of fed cattle basis, to test the presence of structural changes in the determinants of fed cattle basis, and to compare out-of-sample forecasting performance. This study analyzed in-sample econometric models using monthly data from January 2003 through September 2016, then compared the results of the competing models. Using the same time period, we then identified the presence of structural breaks in the data. Furthermore, this study analyzed the out-of-sample forecasting performance for January 2012 through September 2016. The out-of-sample results were then compared to in-sample estimations and historical average basis models. The in-sample estimations indicated the important factors that influence fed cattle basis. The results indicate that there are multiple structural breaks present in the determinants of fed cattle basis examined during this study. We can robustly conclude that there was a market structural break present in the fourth quarter of 2013 and within the 2005-2006 time period. The results indicate that the out-of-sample regression estimations were outperformed by historical average models and did not improve our ability to accurately forecast basis. Overall, a 3 or 4 year historical average model should be preferred over econometric estimations when forecasting fed cattle basis.

Master of Science / Department of Agricultural Economics / Glynn T. Tonsor / The objective of this analysis is to develop econometric models for forecasting fed cattle basis as well as compare these models with historic averaging methods of forecasting basis popular in existing literature. The econometric analysis also aims to identify important determinants of fed cattle basis. Both monthly and weekly models were assessed with data provided by the Livestock Marketing Information Center. All models analyzed the three regions of Nebraska, Kansas, and Texas. Monthly historic average approaches utilized historic fed cattle futures and fed cattle cash price series from January of 1995 through December of 2010. Weekly historic average approaches utilized historic fed cattle futures and fed cattle cash prices series from June of 2001 through December 2010. Data collected post mandatory price reporting implementation in 2001 was used in all econometric models. Overall lags of fed cattle basis, the spread between the nearby live cattle futures contract and the next deferred futures contract, and seasonality regularly proved to explain much of the variation in fed cattle basis in the econometric modeling. Multiple historic average based models were examined on both monthly and weekly frequencies. Once all competing models were estimated in-sample, out-of sample testing was conducted. The forecasting errors of all weekly models were compared to determine which methods prove to be dominant forecasters of fed cattle basis. This testing suggests historic averaging methods outperform the alternate econometric models in out-of-sample work. The econometric models helped to reveal some of the important factors determining fed cattle basis, however lags in collecting data on these factors may inhibit the forecaster’s ability to use these techniques in real time. One interesting revelation in regards to historic averages is the potential of Olympic averages as forecasters. These methods have not been explored in previous academic literature but tend to perform quite well in comparison with other methods explored.

Master of Science / Department of Agricultural Economics / Ted C. Schroeder / With the decline in negotiated trade in the live cattle cash market, feedyards and packers are looking for new ways to increase cash trade. An online, fed cattle auction was created to increase transparency as well as increase the cash trade. Hedonic models have been used heavily to study feeder cattle and the value placed on their characteristics. There is little hedonic modeling done on live cattle and the value of their characteristics. The Fed Cattle Exchange is a new online platform, therefore, no research has been done on it. The objective of this research is to use hedonic modeling to determine the value packers place on characteristics of each lot of fed cattle sold. These characteristics include, weight, number of head, sex, days on feed, location, yield grade, quality grade, delivery time period, and use of a beta-agonist. This research found that use of a beta agonist, location, days on feed, number of head, weight, delivery time frame as well as inclusion of a Select percentage were all statistically important to the price paid. Results will benefit feedyards by informing the sellers on what buyers find the most desirable. This will help with both feedyard procurement practices as well as feedyard management practices.

Grass-fed cattle ranching is growing in popularity, but the characteristics and motivations of the ranchers, however, remain undefined. Based in Texas and using a mail survey and interviews with three grass-fed, three organic, and three conventional ranchers to identify some of their distinctive characteristics, this study achieved similar results to those comparing organic and conventional farmers. Grass-fed cattle ranchers tend to have high levels of education, approach ranching as a second career, and possess outside income sources. Motivated as much by ethics as economics, they embrace grass-fed methods primarily because they believe them to be healthiest for animals, humans, and the land. They eschew organic certification primarily because they perceive government regulations to be influenced by large conventional competitors, and they market their beef directly, often locally. Although many hope to expand their herd, most grass-fed cattle ranchers believe they are resisting “conventionalization” and say that they feel more self-sufficient and satisfied thanks to their choices. / text

Master of Science / Department of Agricultural Economics / Ted C. Schroeder / Newer marketing techniques and production technologies have made large amounts of data available in fed cattle production that previously were not available to the cow-calf producer. The application of this data in breeding and management practices has only begun to be evaluated. This research used individual records, taken from birth to slaughter, on 6,360 calves from a single cow-calf producer who retained ownership of the calves through a custom feed yard and marketed them in a grid system. Using this information, four major topics were analyzed; identifying profitability drivers among animal characteristics, assessing weaning weight as a predictor of finished performance, utilizing lifetime performance of calves to evaluate cow productivity, and quantifying the effects of illness on cattle efficiency and carcass quality. The main profitability driver was hot carcass weight, while avoiding quality and yield grade discounts was also imperative to returns. Weaning weight did not prove to be a highly accurate tool to predict the finished quality and profitability of an animal. Evaluations of cow performance based on calf productivity were accomplished, accounting for all variation possible, however since sires were not known these performance evaluations may not be capturing an accurate picture of maternal influence on calf genetics. Performance evaluations can still be useful, but it is suggested that they not be the basis for all culling and replacement decisions. Evaluating calves based on the age of their dam highlights a peak in performance in most all measures when a cow is 7 years old. Illness in the feedlot linearly affected Net Return in a negative fashion and also negatively influenced Return to Ranch. This was mostly related to losses in efficiency, but also losses in hot carcass weight and dressing percentage in highly treated animals.