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For my MFA thesis exhibition in 2021, I created seven narrative driven prints that were displayed on a hand painted wall mural which acts as the framework or backdrop for a small field of corn stalks. These works and this paper examine the relationship between crops and humans through both visual and oral storytelling as well as the hopeful nature of my work as I continue to reflect upon what it means to engage in a practice of regenerative making and active listening. I explore the use of myself and my twin brother as a character who are each able to view the world through the others lens, color as a form of strengthening connection between the human and non-human figures, and the agency of materials who have equal value in our shared landscape. My inquiry into this relationship is bolstered through the arguments made by political and agricultural ecologists like Jane Bennett, Michael Pollan, Bill Mollison, and Robin Wall Kimmerer whose work speaks to the tethers that bind materials, persons, and all organic matter under one roof.

This dissertation examines production and or technical efficiencies in agricultural and energy systems. The first essay examines production capabilities of smallholder corn farmers following Zimbabwe’s fast track land reform program of 2000. This paper accounts for semi-parametric production frontier to provide more reliable efficiency estimates than can be obtained using traditional parametric methods. The second essay examines efficiency and state level fuel substitution in the US electricity generation sector. I apply the recent fixed effects stochastic frontier estimation to understand the implications of changes in inter-fuel substitution for technical efficiency. The third essay examines the role of drilled but uncompleted wells (DUCs) in the US natural gas production. This study considers variations in producing, newly completed and drilled but uncompleted wells to understand the current production of natural gas.

Of the current techniques used to forecast agricultural commodity prices, none carries as high of a cost as a supply and demand analysis. Because of this expense, firms that have the ability to produce forecasts that rely on supply and demand analysis, do not update their models very frequently. In this paper we will examine if statistical methodologies can provide price forecasts at least as accurate at supply and demand analysis techniques. Both statistical as well as supply and demand models will be evaluated at one, three, six, nine, and twelve month horizons. These horizons are typical for price forecasts that can be used for buying and selling activities, contract negotiations, and production decisions. Of the models we investigated an autoregressive model was found to provide the best price forecasts over a shorter horizon. Whereas a vector autoregressive model was shown to provide the best price forecasts beyond a six-month horizon. This study reveals that a few statistical techniques have the ability to outperformed models that incorporate supply and demand analysis in forecasting the price of U.S. corn.

Corn-based ethanol is the leader of sustainable sources of energy in the United States due to the abundance of corn and the popularity of ethanol-gasoline mixes. Over the past decade, ethanol production has risen from 1.5 million gallons in 1999 to 13 million gallons in 2011. This increase in production requires expansion of ethanol plants. Since Nebraska is the second highest producer of ethanol, we focus our research on the expansion of ethanol plants in Nebraska. The aim of this study is to develop an optimization model for capital investments in ethanol in Nebraska and a medium sized ethanol plant with 100 million gallons capacity in 2011. The model is developed for a firm in Nebraska and uses a planning horizon of five years. The problem is formulated as a dynamic programming model and solved using spread sheets. The data used are gathered from published papers, USDA reports, official Nebraska government website and Renewable Fuel Association reports (RFA). We find that the best strategy for a medium sized plant with capacity of 100 million gallons is to expand the capacity by 50 million gallons in the first year and reject the decision to expand in the following years up to 2016. The best expansion for ethanol in Nebraska is 200, 100 and 100 million gallon for 2012, 2013 and 2014 respectively and no expansion in 2015 and 2016. A scenario analysis is used to illuminate the decision space for different scenarios of profit margin and ethanol demand fluctuations. Adviser: Fred Choobineh