Master of Agribusiness / Department of Agricultural Economics / Brian Briggeman / “Skyscrapers of the plains” is a term which refers to the country elevators spread throughout Kansas and the Midwest, along with the elevators are farmer cooperatives. Farmer cooperatives have been around for more than a century to serve the area farmers as a place to store and market their grain and to purchase their farm inputs. The objective of this research is to identify key profitability drivers of farmer cooperatives of different sizes throughout time. This will be done by using a unique data set gathered from the CoBank’s RiskAnalysis database and examining it with the DuPont model. The project breaks down the data by size, large vs. small, and location. If a cooperative has done more than 100 million dollars in sales in 2010, it was classified as large for the entire time period, all other cooperatives were small. Location was either Kansas or Midwest. In this model, operating profit margin or earns, asset turnover ratio or turns, debt-to-equity ratio or leverage, and spread are examined. Also examined are Return on Assets, the operating performance, and Return on Equity, the financial performance, of the cooperative. Board of Directors and cooperative managers will be able to take this information and hopefully make decisions which make their respective cooperatives more profitable. With the information provided, cooperative managers and Board of Directors will be able to financially compare themselves versus other cooperatives of similar size whether they are in Kansas or in other Midwestern states.

Master of Agribusiness / Department of Agricultural Economics / Vincent Amanor-Boadu / Farming is an important industry in the United States. The custom harvesting industry plays a major role in feeding the world. Schemper Harvesting is a family-owned and operated custom harvesting service that employs 20-25 seasonal workers and understanding how to manage a custom harvesting business professionally and efficiently is the key for its success. Today, there is data available through JDLink on John Deere combine performance beginning in year 2012. The purpose of this study is to examine the usefulness of this JDLink data to assess the efficiency of each of Schemper Harvesting’s seven combines, including machine efficiency and different combine operators. The goal is to determine how the data can improve Schemper Harvesting’s overall performance. Statistical methods were used to analyze Schemper Harvesting’s performance. The analysis indicated that fuel is a major expense and there are ways Schemper Harvesting can conserve fuel. This information may prove valuable in being able to operate a combine more efficiently and save money on expenses. Overall, the objective is to improve Schemper Harvesting’s performance, which results in higher profit without sacrificing quality. Precision technology is an added expense to the business. Being able to justify this expense with profit is the answer. Fuel, labor and machinery are the biggest inputs in the custom harvesting business. These costs related to production agriculture have increased the demand for precision agriculture to increase efficiency and profitability. In order to compensate for the investment in technology, it has been demonstrated that it pays for itself. Making correct use of precision technology adds to productivity. With experience, operators improve increasing their overall efficiency. Incentive plans can be utilized through this data. With the availability of data, the costs and benefits of precision technology can be further evaluated. Five of the seven combines are operated by family members and the other two by non-family employees. This study shows that the performance of the non-family employees was below that of family members. The initial assessment for this difference may be attributed to experience because all the family members have been operating combines for most of their lives. This implies that employing people with excellent performance experience records and/or a need to train non-family employees to help them understand the performance expectations at Schemper Harvesting. The results indicate that tracking operational output performance indicators, such as acreage and volume harvest should be completed so that they may be assessed in concert with the technical indicators such as time and fuel use. The study provides the potential benefits of using John Deere’s JDLink data service providing telematics information for its customers with the latest precision agriculture technologies.

Master of Agribusiness / Department of Agricultural Economics / Hikaru Hanawa Peterson / This thesis focuses on the question of the effect of commodity pricing and Federal programs on the cost of food in the United States. For many decades the debate around subsidy payments has been argued in the halls of Congress and in farm fields across the country. Corn, wheat, and soybeans are the three largest crops subsidized in the United States today; arguably, the prices of these crops are influenced by subsidy payments. The goal of this thesis is to determine the effects of the prices of the top three subsidized crops on the thrifty market basket for families for four published by the USDA, factoring in transportation costs, market spread, agricultural technology advancements, and market value share. Previous studies have focused on direct subsidy payments as a whole and their aggregate influence on the price of food. This paper builds on the past studies by evaluating the effects of crop-specific programs on the cost of food. Econometric regression analysis was used to analyze the data gathered to support or refute the hypothesis that commodity prices and Federal payments do influence the cost of food. Initially data were gathered from January 1960 to December 2012. The data were adjusted for inflation using the Producer Price Index and Consumer Price Index where appropriate. After multiple attempts of modeling it was discovered that data from 1960 to 1970 needed to be discarded due to the difference in the market basket price calculations from the rest of the series. Furthermore, the model was adjusted based on the presence of multicollinearity, and the Hildreth-Lu Method was utilized to correct for the autocorrelation in error. The regression results illustrated that the only commodity of the three considered in the study that had a positive and statistically significant impact on the cost of food over the sample period was corn (p-value = 0.005). The coefficients on wheat and soybean prices were statistically insignificant. The historical fuel price had the expected positive sign and was statistically significant. The agricultural technology factor was not significant. The results also suggested that the cereal grains supply chain has significantly increased the cost of food. Both the cereal grain farm value share and the retail-to-farm spread for cereal grains were statistically significant (p-value < 0.000) with positive coefficients. The price spread of fruit was statistically significant, (p-value = 0.000), but the farm value was not. The regression results were initially surprising for the crop price variables. The overall analysis supports previous studies that crop subsidies alone may not have impacted food prices per se, but biofuel policies may have had unintended consequences. Crop-specific results provide more information to consider when discussing The Farm Bill and the implications of such a complicated and omnibus piece of legislation.

Master of Science / Department of Agricultural Economics / Mykel R. Taylor / Land value research has been conducted over many decades with efforts being focused on a broad spectrum of topics encompassing many different issues. The research in this thesis will focus on understanding the relationship between net farm income, cash rent, and land value. This research could provide insight and direction in determining future land value behavior. Understanding land prices is important to many different segments of the agricultural industry. Those involved in the industry want to know where land values are going and what the future looks like. Although certain segments may not be directly affected by land value movements, if value decreases the environment of the agriculture industry is changed. Farmers and ranchers are interested in future land values as they make purchase and sale decisions or as they consider future growth of their operation. Agribusinesses understand the affect a decrease in land value would do to farmer’s decisions regarding capital purchases. Additionally, agriculture finance institutions are interested in the future movement of land value as they are concerned about the affects adverse movements in land value would have on their customer’s balance sheet and ultimately their collateral position. In this paper the relationship between land value and cash rent; where land value is a function of historical cash rent and cash rent is a function of net returns to the land will be tested for its’ existence in Kansas. Data were collected for the nine crop reporting districts in Kansas from 1973 through 2012.

Doctor of Philosophy / Agricultural Economics / Allen M. Featherstone / Christine Wilson / Farmland values have reached all-time highs and have significantly risen over the last few years. This has caused much debate about whether farmland prices are currently on a bubble and ready to burst, much like the earlier 1980s. Much research has been done on farmland values; however, work done outside of agricultural economics, looking at general asset values, can be incorporated into models of farmland value. Information cascades, or herding, are phenomenon where information in the market is sent between investors and this information is bid into the asset price, thus resulting in boom and bust periods. By using a Vector Autoregression (VAR) model, farmland price dynamics are modeled and analyzed for spatial dependencies from one region to the next. VAR allows for no a priori specification of network typology. This allows for the examination of the existence of information cascades and what form the network takes among spatially located farmland markets. This method is then compared to two other spatial estimation techniques. The first is a Spatial Autoregressive (SAR) model where network typology is imposed prior to estimation. The second is a VAR model where no network is modeled, and only the region’s own asset prices can influence future periods. It is found that information cascades exist and network typology is somewhat random. These results caution the current direction of the literature of imposing network or spatial structure. However, due to data requirements, SAR models are easier to estimate since they require less data and if network structure, which the SAR model inherently imposes by the weight matrix, could be determined by an autoregressive process instead of an adjacency rule it could prove to be the most accurate forecasting method.

Master of Agribusiness / Department of Agricultural Economics / Vincent Amanor-Boadu / Transforming Belmont Estate from a traditional agricultural production business into a profitable agri-tourism enterprise is the issue addressed in this thesis. The importance of this problem rests on the fact that the author is the general manager of this family business and needs to organize it in ways that facilitates its ability to keep growing in a rapidly changing market environment. Given the increasing positioning of Grenada as a preferred tourist destination and the increasing number of people who are responding to this positioning, the management of Belmont Estate believes that transforming this traditional agricultural production business into an agritourism business will create significant value for shareholders and stakeholders. The process of transforming the organization needs to start with a new way of envisioning it. Therefore, a strategic direction and a compelling value proposition were developed. An assessment of the business environment was conducted to develop a framework where specific strategies could be developed to support the new strategic direction that has been established. Additionally, a financial analysis that focused on the contribution of the different enterprises to the new strategic direction was conducted to assess the potential financial outcome of this effort. The results show that Belmont Estate is well-positioned to benefit from increasing tourism business in Grenada. If the management of Belmont Estate can implement the strategic plan, it can successfully transform Belmont Estate from an agricultural production business into an efficient agritourism business that not only creates value for its shareholders and stakeholders but offers a welcome diversity to Grenada’s growing tourism industry.

Master of Science / Department of Grain Science and Industry / Leland McKinney / The current forage handling equipment in the cellulosic ethanol industry is severely limited by the low bulk densities of baled and ground biomass. Low bulk densities contribute to flowability problems and lack of maximizing trailer capacities. By pelleting we can increase the bulk density and flowability characteristics of forages. The objectives of this research were to evaluate (1) the energy requirements of grinding sorghum stalks, corn stover, wheat straw and big bluestem through two different screen sizes, (2) the energy requirements of pelleting forages from the two grind sizes, and (3) the physical properties of our various end products. The two screen types were found to have significantly different energy consumptions from each other (P<.0001). The majority of the four forage types were also found to have significantly different energy consumptions for grinding from each other (P<.0001). The exception was big bluestem vs. corn (P=.2329). All of the 1/8” vs. 1/8” and 1/8” vs. 3/8” grinds were significantly different from each other (Most P<.0001 and all at least P<.05). 3/8” sorghum was significant against all other 3/8” forage types. No other comparisons were significant for 3/8” vs. 3/8” (All 3/8” sorghum P<.0001). Production rate through the 3/8” screen was almost 3 times that of the 1/8” screen (Average of 400 lb/hr vs. 150 lb/hr). The two screen types were found to have significantly different energy consumptions for pelleting from each other (P<.0001). The four forage types were also found to have significantly different energy consumptions from each other (P<.0001) while the big blue vs. wheat did not. (P=.1192). Particle length for the 1/8” grind ranged from .06 inches to .07 inches, while the 3/8” grind ranged from .08 inches to .12 inches. Pelleting increased bulk density from 6.24 lb/ft3 to 9.99 lb/ft3 for biomass grinds to 31.17 lb/ft3 to 43.77 lb/ft3 for pelleted biomass. Pellet quality ranged from 93% to 98%. A cost analysis indicated that it would take roughly $20 extra per ton for the transportation, pre-processing and storage of pelleted cellulosic biomass than whole corn. This cost is still almost half that of the cost for baled biomass.

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 Agribusiness / Department of Agricultural Economics / Kevin Dhuyvetter / This thesis was commissioned by Cooperative Producers, Inc. (CPI) of Hastings, Nebraska in order to better understand the preferences and uses of precision agriculture by customers within the company’s trade territory. With the rapid increase of precision agriculture (hardware, software, services, etc.) it is necessary to get a better understanding of what drives growers to adopt and implement precision agriculture practices. A paper survey was sent out in CPI’s monthly statements to patrons that also included instructions to be able to fill out an online survey if that was preferred. From that offering there were a total of 114 responses providing data from which several technology adoption models were estimated. Based on prior experience with precision agriculture and the development of services offered to growers, it is hypothesized that there are three primary variables influencing a grower’s decision to adopt precision agriculture. If the operation is managed by a younger grower (<40 years old), farms with a larger number of acres, and if a high percent of the operation’s acres are irrigated they will be more likely to adopt precision agriculture practices. The survey results generally revealed that younger farmers, larger farm size, and a higher percentage of irrigated acres did not increase the likelihood of utilizing precision agriculture. The questions asked in the survey were designed to provide information for the development of a tool that salespeople offering precision agriculture services could use to determine if a potential customer with be inclined to adopt and utilize precision agriculture. While some of the results were contrary to expectations they do offer insight into what type of customer adopts precision agriculture and a direction for CPI to move in order to maximize market penetration.

Master of Agribusiness / Department of Agricultural Economics / Michael Boland / Greenhouse gas (GHG) emissions and their negative effect on the environment is a growing concern in the world. It is estimated that agriculture is responsible for 7% of the total GHG emissions in the United States. Currently, environmental policies to regulate GHG are in place in different countries and are expected to increase in the future. Increased awareness about climate change by customers also represents an incentive for companies in measuring their emissions. The objective of this study is to estimate carbon dioxide-equivalent emissions from eight agribusiness retailers in Kansas. Data consisted of two years of energy inputs from the operation of the agribusiness retailers. Carbon emission coefficients were employed to determine carbon dioxide-equivalent emissions associated with the use of each energy input during their operations. Results suggest that electricity is the largest source of total carbon dioxide emissions from the retail operations followed by diesel fuel. Diesel fuel represents the main source of direct emissions and gasoline represents the second largest source of direct emissions. Emissions from the agricultural sector will not be regulated under the current American Clean Energy and Security Act of 2009 but information on their potential carbon footprint may be used in identifying specific processes where emissions could be reduced and to analyze possible climate legislation implications for their operations. If agribusinesses were to be regulated, none of the eight retailers have locations with emission levels that would be subject to the current cap and trade bill passed by the U.S. House of Representatives. But, if they were regulated and had to comply by purchasing carbon credits equal to 5 to 20% of their direct emissions, the cost would be low given estimation of future carbon prices in the literature. Even if agricultural retailers are not directly restricted, they will likely be affected by increases in energy input prices if such legislation is enacted.