Master of Agribusiness / Department of Agricultural Economics / Allen M. Featherstone / Institutions of the Farm Credit System (FCS) focus on risk-based lending in accordance with regulatory direction. The rating of risk also assists retail staff in loan approval, risk-based pricing, and allowance decisions. FCS institutions have developed models to analyze financial and related customer information in determining qualitative and quantitative risk measures. The objective of this thesis is to examine empirical account data from 2006-2012 to review the probability of default (PD) rating methodology within the overall risk rating system implemented by a Farm Credit System association. This analysis provides insight into the effectiveness of this methodology in predicting the migration of accounts across the association’s currently-established PD ratings where negative migration may be an apparent precursor to actual loan default. The analysis indicates that average PD ratings hold relatively consistent over the years, though the distribution of the majority of PD ratings shifted to higher quality by two rating categories over the time period. Various regressions run in the analysis indicate that the debt to asset ratio is most consistently statistically significant in estimating future PD ratings. The current ratio appears to be superior to working capital to gross profit as a liquidity measure in predicting PD rating migration. Funded debt to EBITDA is more effective in predicting PD rating movement as a measure of earnings to debt than gross profit to total liabilities, although the change of these ratios over time appear to be weaker indicators of the change in PD rating potentially due to the variable nature of annual earnings of production agriculture operations due to commodity price volatility. The debt coverage ratio is important as it relates to future PD migration, though the same variability in commodity price volatility suggests the need implement multi-year averaging for calculation of earnings-based ratios. These ratios were important in predicting the PD rating of observations one year into the future for production agriculture operations. To further test the predictive ability of the PD ratings, similar regression analyses were completed comparing current year rating and ratios to future PD ratings beyond one year, specifically for three and five years. Results from these regression models indicate that current year PD rating and ratios are less effective in predicting future PD ratings beyond one year. Furthermore, because of the variation in regression results between the analyses completed for one, three and five years into the future, it is important to regularly capture ratio and rating information, at least annually.

Master of Agribusiness / Department of Agricultural Economics / Bryan Schurle / Quantifying the impact of various economic events is essential for risk management in community banks. Interest rate shocks of either rapidly increasing or decreasing rates, in magnitudes of at least 200 basis points, is one of the more common risks modeled. Liquidity crises that impact deposits or loan demand can arise from either local or national economic events is another risk factor that regulators are requiring banks to quantify and plan for. Excel spreadsheets can be used to develop models to measure and quantify these risks. Simulation tools and what-if analysis using data table and scenario manager identify possible outcomes for differing interest rate scenarios, interest rate shocks and liquidity stresses. Data table was used for simulation of a stochastic model to produce a cumulative distribution function of two hundred results each on three different interest rate environments. Scenario manager was used to narrow the simulation to a certain set of expectations affecting the balance sheet of the bank and another set of expectations from an interest rate shock. Changes in the bank’s balance sheet resulting from three different commodity price expectations were modeled. An interest rate shock of four hundred basis points over a two year period was also modeled. These models are simple and cost effective. Once data are captured, the time required to develop and generate scenarios is manageable. The model can be used for a wide range of what-if alternatives as an individual bank may see fit. These models are adequate to meet present regulatory requirements for a community bank of smaller size that is not complex and does not possess a high risk profile.

Master of Agribusiness / Department of Agricultural Economics / Vincent Amanor-Boadu / As the dairy industry faces the future, consumers’ demand for better milk quality and safety is increasing. Milk quality is of major interest to both consumers and dairy farmers alike. However, scientific data on milk quality in terms of somatic cell count (SCC) in Uganda and most developing countries has been lacking. This study used SCC to compare Southwestern Uganda’s milk quality against international standards. The study also sought to assess dairy farmers’ perceptions about milk quality. Milk samples were obtained from 100 farms in Mbarara and Kiruhura districts, the major cattle corridor in Uganda. The milk’s SCC was analyzed using a DeLaval DCC. A structured questionnaire surveyed farmers on milking procedures and milk-quality perception. Descriptive statistics and qualitative analysis was used to characterize and compare milk quality against the international benchmark. The study found that the 100 farms had an average SCC of 507,000 cells/ml. About 34% of farms in the study had SCC under 200,000 cells/ml, an indication of high-quality milk. Excluding 7% of the farms with SCC over 1,000,000 cells/ml, the remaining 93% had an average SCC of 276,000 cells/ml, a level comparable to international standards, well below the EU threshold of 400,000. The study also revealed that 98% of farmers considered milk quality as important or very important both to them and to the milk buyers. However, all farmers reported that they currently do not receive a milk-quality premium and are not penalized for poor quality. Seventy-nine percent of farmers reported the cooperative they belong to as their main source of information on management practices. An improved perception of milk quality both domestically and internationally will benefit Uganda’s dairy farmers and its dairy industry at large. Consumers must be assured that Uganda’s dairy industry, its government, industry stakeholders such as the Dairy Development Authority, the Uganda National Bureau of Standards, and the private sector place the utmost importance on the quality and safety of milk and other dairy products. New technologies to measure for SCC and strict food safety regulations will help improve the country’s milk-quality image, allowing Uganda’s dairy industry to tap into major milk export markets. Most developed countries have seen increased raw-milk quality or reduced SCC as a result of strong regulatory pressure.

Master of Agribusiness / Department of Agricultural Economics / Gregory Ibendahl / One of the latest buzzes amongst agriculture is the storage and analysis of “Big Data.” There are a number of questions surrounding the quality, quantity, and capacity of big data to form real-world decisions based upon past information. Much like the teachings of history, the storybook that big data can reveal about a grower’s operation may hold the answers to the question of: “what is necessary to increase food production which will be required to feed an ever-growing world?” With the increase in interest in precision agriculture, sustainability practices, and the processing of the immense spatial dataset generated on the farm, the next challenge at hand will be in determining how to make technology not only streamlined, but also profitable. Over the past few years, precision agriculture technology has become widely adopted as an agronomic decision making tool. Much like a scientific experiment, the greater the number of similar observations, the greater the degree of confidence can be placed upon a decision. As a means of increasing the number of observations that a farmer can use to base a decision upon, there is becoming increasing demand in being able to combine the data of similar farming operations in order to increase the size and scope of the dataset to generate better decisions benefitting many farms instead of just one. The growing interest in forming community data pools for farm data demonstrates the need for a study for determining how farming practices can be properly benchmarked. The goal was be to evaluate how to use farm data to make economic decisions in a similar manner as one would make agronomic decisions using similar observations. The objective was to design the proper protocol for benchmarking the farm’s potential, and evaluating potential increases in technical efficiency by adopting precision agriculture technology. To accomplish this, a data envelopment analysis was conducted using scale efficiency as a means of determining the frontier of efficient farms. The resounding goal for this study in the future will be to use the model as a means of implementing the secondary process of pooling precision agriculture data to analyze efficiencies gained by the adoption of technology. By demonstrating the value of generating peer groups to increase observations and refine farming practices, farmers can find increased profitability and efficiency by using resources that may already be held within the operation.

Master of Agribusiness / Agricultural Economics / Vincent R. Amanor-Boadu / The United States was the world’s third largest producer of raspberries (by pounds) in 2013, behind Russia and Poland. Raspberries are the third most popular berry in the United States behind strawberries and blueberries. Most U.S. production of red raspberries occurs in the states of Washington and Oregon during July and August depending on variety. Harvest and production for industrial pack typically runs for five weeks. Sieved red raspberries or single strength red raspberry puree is one of many industrial packs produced in the Pacific Northwest of the United States. Sieved red raspberries are produced by forcing fresh, cleaned and sorted red raspberries and red raspberry crumbles and pieces through a mesh screen, collected in drums or pails and stored for use in further processed products such as pies, confectioneries and other consumer food products. For this thesis, sieved berries are packed in 55-gallon steel drums lined with food grade plastic bags. They are shipped from the processing plant to a third party warehouse to be frozen and stored. The final processing plant draws on these stored frozen products for use in the production of the Company’s consumer food products. The purpose of this thesis is to review the Company’s current procurement practices of sieved red raspberries and determine how these practices may be improved to reduce its total delivered cost. We use an optimization modelling approach to assess the procurement process used by the Company. The results indicate that it is possible to reduce procurement costs and improve efficiencies by making changes to the current procurement strategy. By implementing the procurement strategy developed in this study, we show that the Company can save as much as $1.69 million per year, which is equivalent to about 20.3% of the current spend. This would suggest that adopting the optimization strategy could allow the Company to increase its total sieved raspberry utilization by as much as 0.9 million pounds per annum, all other things remaining unchanged.

Master of Agribusiness / Department of Agricultural Economics / Rodney D. Jones / After remaining stable for several decades, corn price has recently had unprecedented price increases and volatility. United States Department of Agriculture (USDA) predicts an average corn price of $5.80 per bushel for 2008, which is 232% of its 28-year (1980-2007) average price of $2.50. The record increase in corn price was the result of increased starch-based ethanol production associated with increased energy costs, and other factors such as a declining value in the United States dollar, and increased global commodity demand. High corn prices have impacted the profitability of the livestock feeding industry. It was less clear how the record high corn prices would affect the cow-calf industry since corn is not a significant input for cow-calf enterprises. This study quantified the relationship between cow-calf profitability and corn price. Because feed costs for a cow-calf producer are among the highest variable costs for the operation, both grazing and non-grazing feed costs were estimated as a function of corn price. Models were estimated to determine if a relationship between corn price and Returns Over Variable Costs (ROVC) at the cow-calf level could be identified. Corn price from 1978-2007 explained none of the variability in grass grazing rental rate, however when the projected 2008 corn price was included in the analysis, corn price explained 10% of the variation in grass grazing rates. Year (linear time trend) and corn price from 1978-2008 explained 88% of historical grass grazing rental rate variability, 71% of alfalfa price variability, and 63% of other hay price variability in Kansas. These results suggest that the new corn market paradigm likely will increase the relationship between corn price and feed costs at the cow-calf level. Several models were evaluated using bulk diesel fuel price, feeder calf price, corn price, alfalfa price, other hay price, and grass grazing rental rate to estimate Kansas cow-calf producer ROVC. Models that included diesel fuel price, feeder calf price, grazing rent, and one of the harvested feeds (corn, alfalfa, or other hay) price explained 90-91% of the variability in ROVC. Models that included diesel fuel price, feeder calf price, and either grazing rent or corn price explained less of the variability in ROVC; using grazing rent explained 89% and using corn price explained 79%. Including grass grazing rental rate along with corn price, feeder calf price, and bulk diesel fuel price improved the model's ability to predict ROVC, explaining 91% of the variability. While cow-calf producers might use very little corn directly in their operations, this research shows that corn price is an important determinant of cow-calf production returns, and corn price can be used by producers to plan for future rising costs in order to maximize returns.

Master of Agribusiness / Department of Agricultural Economics / Allen M. Featherstone / Providing a recommendation on whether to make a capacity expanding capital investment in an existing butter plant is the subject of this thesis. This is important as the success of this project will have a significant impact on the future profitability of Land O'Lakes and provide a significant home for its member's milk production. The dairy industry has undergone change over the past decades. Milk production has moved from the traditional production area of the Upper Midwest to drier, more arid areas such as California. This has led to milk price premiums in the Upper Midwest and since milk is the major input to butter manufacturing, it has become more attractive to produce butter in other areas such as California. Much of the data collected in review of the industry were obtained from the USDA. This data were used to describe the industry and focus on the number of butter plants over time, the milk productivity per cow, and the total milk production by state. It provides a clear picture of fewer bigger plants, more productive cows, and a dramatic shift in milk production to the West, primarily California. A Net Present Value (NPV) model is developed to analyze the trade off between the initial capital investment and less costly milk procurement over time. The model also considers maintenance costs, salvage values, plant startup delays, and a one time salvage value gain by shutting down an Upper Midwest plant. After the initial model is developed, sensitivity analysis is conducted, focusing on key variables such as demand growth, and the spread between California and Upper Midwest milk prices. The conclusion is that additional investment in California butter production would be profitable, earning a positive NPV and an Internal Rate of Return (IRR) greater than the Land O'Lakes cost of capital. The solution is robust as they remain the same even after modeling lower demand and smaller milk price differentials. Therefore, I recommend that Land O'Lakes move ahead with this capital investment.

Master of Agribusiness / Department of Agricultural Economics / Michael W. Woolverton / The sheep dairy industry in the United States is small. Producers are concentrated in a few areas geographically with the greatest demand for sheep milk products located on the east and west coasts. The purpose of this analysis is to determine if a family-run sheep dairy located in Central Iowa could produce an annual profit of $40,000 without utilizing labor hired outside the family. Budgets were created and used to determine the revenues and costs of operating a sheep dairy, and producing and selling three different end products for sale: fluid milk, cheese and bars of soap. Microsoft Solver was used to determine the product mix that would maximize the total profit of the enterprise. The profit of the enterprise depends on a number of factors including the cost of feed, the number of ewes milked and the amount of milk each ewe produces. A maximum profit of $66,993 could be generated by selling 74% of the milk as fluid milk, 25% of the milk processed into cheese and 1% of the milk processed into soap. The diversification of products would help buffer the enterprise from volatility in the product markets. While the budgets show that this enterprise is profitable, local markets for these products must be identified and/or developed for the profits to be realized.

Masters of Science / Department of Agricultural Economics / Jeffrey M. Peterson / The expansion of the biofuels industry, world demand, and various other factors are having a historic impact on the price of grains. These high prices have been creating a large increase in production of many water intensive crops such as corn. As corn is among the most input-intensive crops, this extra production has raised concerns about environmental impacts and pressures on water resources in particular. While water quality has been a longstanding concern in the cornbelt, much of the new production is in nontraditional corn regions including the southeast, the High Plains, and the western states. In these areas, there is mounting concern over depletion of already stressed water supplies. In the High Plains, the chief water source is the Ogallala aquifer, one of the largest water resources in the world that underlies eight states from South Dakota to Texas. The Ogallala has enabled many agricultural industries, such as irrigated crops, cattle feeding, and meat processing, to establish themselves in areas that would not be possible otherwise. A consequence is that the economy of this region has become dependent on groundwater availability. Continued overdrafts of the aquifer have caused a long-term drop in water levels and some areas have now reached effective depletion. This thesis seeks to estimate the impact of the rising commodity prices on groundwater consumption and cropping patterns in the Kansas portion of the Ogallala. The economy of this region is particularly dependent on water and irrigated crops, with more than 3 million head of feeder cattle and irrigated crop revenues exceeding $600 million annually. Sheridan (northwestern Kansas), Seward (southwestern Kansas), and Scott (west central Kansas) counties have been selected as representative case study regions. These counties have a wide range of aquifer levels with Seward having an abundant supply, Sheridan an intermediate supply, and Scott nearing effective depletion. Cropping patterns in these counties are typical of the western Kansas region, with most irrigated acreage being planted to corn and with dominant nonirrigated rotations of wheat-fallow and wheat-sorghum-fallow. A Positive Mathematical Programming (PMP) model was developed and calibrated to land- and water-use data in the case counties for a base period of 1999-2003. The PMP approach produces a constrained nonlinear optimization model that mimics the land- and water- allocation decision facing producers each year. The choice variables in the model are the acreages planted to each of the major crops and the water use by crop. The model was run for each of the case counties. The PMP calibration procedure ensures that the model solutions fall within a small tolerance of the base period observations. Once calibrated, the models were executed to simulate the impacts of the emerging energy demand for crops over a 60-year period. After the baseline projections were found, the model was then run under increased crop prices that reflect the higher prices observed in 2006 and after. The thesis found that under the high price scenario, both irrigated crop production and water application per acre increased significantly during the early years of the simulated period in all modeled counties. The size of the increases depended on the amount of original water available in each county. The increases generally diminished in magnitude toward the end of the simulation period, but led to smaller ending levels of saturated thickness as compared to the base price in all counties. Finally, in two of the three counties, it was observed that initial increases in irrigated crop acres and water application forces a decline in the aquifer such that less water can be applied per acre in the final years of the simulation. This suggests that high commodity prices forces a higher emphasis on early production levels than later production levels. Additionally, the higher prices have a significant effect on the rate of decline of the Ogallala aquifer.

Master of Agribusiness / Department of Agricultural Economics / David G. Barton / The goal of this thesis is to evaluate future financial strategies for the Garden City Co-op (GCC). The evaluation will include a standard financial analysis of historical financial information and pro forma financial projections of selected strategies. The strategies will be evaluated using management assumptions in which liquidity and solvency are proactively managed. The ultimate goal of the GCC is to return as much profit to its patron-owners as possible but at the same time provided them with the product and services they need for their own business at a competitive level. The GCC has recently experiencing unusually high profits and believes this will be the trend over the next six to eight years due to the business ventures and relationships that currently are in place to grow sales outside the Co-op's traditional trade territories. The increased revenues and profits have come primarily from profitable joint ventures, especially from a very high volume of petroleum sales to non-member patrons. The most critical relationship is member patron-owner relationship with CHS Inc., a large regional cooperative that owns two oil refineries and is the primary supplier of petroleum products to GCC. The profits being made by CHS Inc.'s fuel refineries are distributed to GCC as patronage refunds based on the volume of refined fuels purchased from them. This much larger stream of patronage refunds from CHS and other regional co-op's being distributed to GCC is causing GCC to pause and evaluate how best to move forward. The GCC has the challenge of what to do with increased earnings. Does the GCC return earnings back to its member-owners retain earnings for future investment opportunities, or do they commit them to help finance current investment opportunities? Does GCC grow its most profitable business lines, such as nonmember-nonpatron petroleum sales? Given the close relationship with CHS in terms of income distributions and equity management, including cash patronage refunds and cash equity redemptions of retained patronage refunds, and the close relationship with its own member patron-owners, is its current income distribution and equity management program sustainable under various strategies?