The goal of this study is to evaluate the introduction of cellulosic ethanol conversion plants using switchgrass as the feedstock and how it impacts the economies of two Tennessee regions. Switchgrass feedstock production, storage, and transportation costs are estimated for one plant in West Tennessee and one plant in East Tennessee. In each region, the location for a cellulosic ethanol conversion plant and the acreage required to meet a 61.8 million-gallon/year capacity are specified. The costs associated with switchgrass production and cellulosic ethanol conversion are then entered into IMPLAN to estimate the economic impacts of one cellulosic ethanol plant in each region. The key findings of the study for West Tennessee are as follows. The investment impacts of switchgrass farming are $100.4 million more in total industry output, an increase of 914 jobs, and $46.9 million more in total valued added. Investment impacts of a cellulosic ethanol conversion plant include $121.3 million increase in total industry output, an additional 653 jobs, and a $47.7 million increase in total valued added. Year-to-year operations of switchgrass farming and cellulosic ethanol conversion increase the region’s total industry output by $57.1 million, increase jobs by 296, and increase total value added by $26 million.In East Tennessee the investment impacts of switchgrass farming are $118.3 million increase in total industry output, 949 jobs created, and a $66.4 million increase in total valued added. Investment impacts of a cellulosic ethanol conversion plant include a $116.9 million increase in total industry output, an additional 765 jobs, and a $48.3 million increase in total valued added. Year-to-year operations of switchgrass farming and cellulosic ethanol conversion increase the region’s total industry output by $80.4 million, jobs by 396, and the total value added by $39.2 million.

Concerns regarding energy security, resource sustainability, and environmental protection have heightened interests in renewable fuels and sparked the research and development of ethanol as a transportation fuel. This study examines consumers’ willingness to pay for ethanol from various potential feedstocks; corn, switchgrass and wood wastes. Data was collected via a survey of fuel consumers across the United States in 2009. Results show that consumers have a preference for E85 (a fuel blend with 85 percent ethanol and 15 percent gasoline) from corn, switchgrass and wood wastes compared to E0 (gasoline) and a preference for E85 from switchgrass and wood wastes, but not corn when compared to E10 (10 percent ethanol and 90 percent gasoline). Also, consumers have a preference for E85 compared to E10 but not compared to E0. Mean WTP for E85 was insignificant across all models, but significant for all other product attributes; percentage of fuel imported, percentage of greenhouse gas emissions reduced, and the proximity of fuel in driving distance. This suggests a WTP for a combination of fuel attributes associated with ethanol rather than just for E85. Results suggest that price and proximity of the fuel have a greater impact on fuel selection than percentage of the fuel imported and reductions in greenhouse gas emissions. Republicans had a positive WTP for E85 compared to E10 and a negative WTP for E85 compared to E0 regardless of feedstock, which may suggest that Republicans actually have no preference for E85; however, these findings may also suggest that Republicans view E85 as a voluntary “policy” whereas E10 is an example of government intrusion in the free market. Thus, they may ultimately have preferences over the manner in which the blend is being introduced to the market. Across all models, those undecided in political affiliation, those previously familiar with ethanol, and those who prefer to devote U.S. farmland to food instead of fuel generally exhibited a lower WTP for E85 while Westerners, those worried about the environment, and those believe that reducing dependence on foreign oil is more important than environmental protection generally had a greater WTP for E85.

Efforts to reduce the United States’ dependence on foreign petroleum encourage the production of fuels from bioenergy crops. Recent energy mandates have therefore “opened doors” for alternative feedstock sources for ethanol production. Switchgrass is a candidate feedstock. Under the University of Tennessee’s Biofuels Initiative, the University of Tennessee, partnering with DuPont-Danisco Cellulosic Ethanol LLC, contracted for the production of switchgrass with local farmers to guarantee biomass feedstock supply for an ethanol conversion research facility. This study used methods borrowed from the social psychology literature in combination with economic theory to analyze factors influencing switchgrass farmers’ intentions to continue growing switchgrass after contracts with the granting agent expired. Understanding what motivates producers to make long term commitments to switchgrass production as an energy crop may be important information for private investors who will rely on a fixed supply of switchgrass.A probit model was used to determine the factors affecting producers’ intentions to continue producing switchgrass after their contract expires. Results suggest that community perceptions about the production of switchgrass as a dedicated energy crop may have an important impact on farmers’ intentions to make a long-term commitment to produce switchgrass. Therefore, educating and involving community and extension personnel may have a positive impact on farmers’ decisions to make long-term commitments to grow switchgrass as a dedicated energy crop.

In recent decades, climate change has become one of the most crucial challenges for humanity. Climate change has a direct correlation with global warming, caused mainly by the green house gas emissions (GHG). The Environmental Protection Agency in the U.S. (EPA) attributes carbon dioxide to account for approximately 82\% of the GHG emissions. Unfortunately, the energy sector is the main producer of carbon dioxide, with China and the U.S. as the highest emitters. Therefore, there is a strong (positive) correlation between energy production, global warming, and climate change. Stringent carbon emissions reduction targets have been established in order to reduce the impacts of GHG. Achieving these emissions reduction goals will require implementation of policies like as cap-and-trade and carbon taxes, together with transformation of the electricity grid into a smarter system with high green energy penetration. However, the consideration of policies solely in view of carbon emissions reduction may adversely impact other market outcomes such as electricity prices and consumption. In this dissertation, a two-layer mathematical-statistical framework is presented, that serves to develop carbon policies to reduce emissions level while minimizing the negative impacts on other market outcomes. The bottom layer of the two layer model comprises a bi-level optimization problem. The top layer comprises a statistical model and a Pareto analysis. Two related but different problems are studied under this methodology. The first problem looks into the design of cap-and-trade policies for deregulated electricity markets that satisfy the interest of different market constituents. Via the second problem, it is demonstrated how the framework can be used to obtain levels of carbon emissions reduction while minimizing the negative impact on electricity demand and maximizing green penetration from microgrids. In the aforementioned studies, forecasts for electricity prices and production cost are considered. This, this dissertation also presents anew forecast model that can be easily integrated in the two-layer framework. It is demonstrated in this dissertation that the proposed framework can be utilized by policy-makers, power companies, consumers, and market regulators in developing emissions policy decisions, bidding strategies, market regulations, and electricity dispatch strategies.

The purpose of this research is to quantify how macro-scale factors such as weather, crop prices, and land conversion affect agricultural water use at the irrigation district level in central Arizona and to understand what constraints and considerations district managers face when making water-sourcing decisions. A conceptual model is developed and econometrically estimated finding that much of the annual variation in total water use for agriculture can be explained by differences in precipitation, cotton prices, and alfalfa prices. Further, results from empirical analysis support the notion that total water use for agriculture has been greatly affected by land conversion from agriculture to other uses. Irrigation district manager interviews indicate that the water sourcing process is very similar across districts in central Arizona and has varied little since 1995, due to common constraints. This research lays an important foundation for future models designed to forecast agricultural water use in central Arizona.

This dissertation investigated farm management concerns faced by grain producers due to the acquisition of various precision agriculture technologies. The technologies evaluated in the three manuscripts included 1) auto-steer navigation, 2) automatic section control, and 3) autonomous machinery. Each manuscript utilized a multifaceted economic model in a whole-farm decision-making framework to determine the impact of precision agriculture technology on machinery management, production management, and risk management. This approach allowed for a thorough investigation into various precision agriculture technologies which helped address the relative dearth of economic studies of precision agriculture and farm management. Moreover, the research conducted on the above technologies provided a wide array of economic insight and information for researchers and developers to aid in the advancement of precision agriculture technologies. Such information included the risk management potential of auto-steer navigation and automatic section control, and the impact the technologies had on optimal production strategies. This dissertation was also able to provided information to guide engineers in the development of autonomous machinery by identifying critical characteristics and isolating the most influential operating machine. The inferences from this dissertation intend to be employed in an extension setting with the purpose of educating grain producers on the impacts of implementing such technologies.

The purpose of this study is to review existing literature of factors that influence farmers’ decision to participate in conservation programs. This study is also intended to collect county data and information on conservation programs and participation in the Kentucky River watershed region, which can be analyzed and used to draw differences in characteristics of the region that would suggest willingness to participate in a trading scheme for improvements in water quality. The results suggest that more participation in a trading scheme from some counties than others should be expected. Counties with more farms and larger farms will probably have higher rates of participation in conservation programs. The cost-share amounts being paid by current government programs must be considered as the minimum staring point to negotiate in a trading scheme. To target the impact of watersheds, such as the Kentucky River in the Mississippi system, that discharges significant amounts of pollutants into the Gulf of Mexico, policy makers and program administrators should be advising and stimulating the adoption of practices with the best abatement performance for such pollutants considering technical complementarity between practices.

This project investigates the impacts of nutrition merchandising on consumers’ willingness to pay for local tomatoes and strawberries. The data come from survey of Kentucky and Ohio residents in June 2011. Two thousand one hundred twelve individuals from Kentucky and Ohio were surveyed, to find out the impact of selfawareness of health benefits and health benefits information on their willingness to pay. The consumers were offered one of the three survey versions. The versions varied by how much nutrition information was provided to the consumer related to both strawberries and tomatoes – otherwise identical. A had the most, B had text only, and C omitted any nutritional benefits. This nutrition preamble was offered just before doing a payment card willingness-to-pay experiment. Standard demographic data were also included. The goal of the study was to see if and in what way the provision (or nonprovision) of this information, as well as consumers’ own knowledge of nutritional benefits of local foods, their beliefs and lifestyle influenced their willingness to pay for these local products.

This thesis examines the economic and environmental impacts that precision agriculture technologies (PATs) can have on the carbon footprint of a grain farm. An analysis is offered using two manuscripts. The first examines the impacts of three PATs and compares the findings to a conventional farming method. It was found that all three PATs investigated showed a potential Pareto improvement over conventional farming. The second manuscript expanded the model used previously to in order to develop a process to construct a carbon efficient frontier (CEF). The model employed examined uniform and variable rate technologies. In addition to the CEF, a marginal abatement cost curve was constructed. Using these curves in a complementary fashion, more accurate information on the adaptive behavior of farmer technology adoption can be gleaned. the information gleaned for the two manuscripts can give both producers and policy makers the analytical tools needed to make more information decisions with regard to economic and environmental feasibility of PATs.

A large body of research, typically nationally focused, has examined the relationship between family structure, educational attainment, and healthcare access. Within this field of study, there is limited availability of regionally based studies, specifically the Lower Mississippi Delta (LMD) region. This exploratory study examines the effects of family structure on high school graduation rates and health insurance coverage within the LMD region. The objective is to determine if family structure has a direct impact on the educational attainment and health outcomes of a child within the region using concepts from nationally focused literature. Through the use of an OLS regression, we find that family structure does not have a strong impact on the educational attainment of children within the region. However, we did find that family structure had a strong impact on the health insurance coverage of youth within the region. Additionally, we examine the impact that spatial location and race has on these variables. These results can encourage the development of potential intervention programs, outreach initiatives, and other programs geared toward helping youth within the region. The study's conclusions provide insight on the impact of family structure on health and education thus encouraging further research within the LDM region.