This dissertation combines large scale datasets to evaluate crop prediction, land values, and consumption of a crop being considered to advance a sustainable bioeconomy. In chapter 2, we propose a novel application of the multinomial logit (MNL) model to estimate the conditional transition probabilities of crop choice for the state of Kentucky. Utilizing the recovered transition probabilities the forecast distributions of total acreages for alfalfa, corn, soybeans, tobacco, and wheat produced in the state from 2010 to 2015 can be recovered. The Cropland Data Layer is merged with the Common Land Unit dataset to allow for the identification of crop choice at the field level. Our findings show there are higher probabilities of planting soybeans or wheat after corn relative to corn after corn, tobacco, or alfalfa. In addition, the transition probability of the crop rotation demonstrates that corn will be planted after soybean, and vice versa and that alfalfa has a lower probability of being rotated with other crops from year to year. These findings are expected with traditional crop rotation in the U.S., and a characteristic of a perennial crop, especially for alfalfa. Finally, forecasting results indicate that there are significantly wider distributions in corn and soybean, whereas there is a little variation in the tobacco, wheat and alfalfa acres in the simulation. In chapter 3, we identify critical consumer-demographic characteristics that are associated with the consumption of products containing hemp and investigate their effect on total expenditure in the U.S. To estimate the likelihood of market participation and consumption level, the Heckman selection model, is employed using the maximum likelihood estimation procedure utilizing Nielsen consumer panel data from 2008 to 2015. Results indicate marketing strategies targeting consumers with higher education and income levels can attract new customers and increase sales from current consumers for this burgeoning market. Head-of-household age in different regions shows mixed effects on decisions to purchase hemp products and consumption levels. Findings will provide a basic understanding of a consumer profile and overall hemp market that has had double-digit growth over the last six years. As the industry continues to move forward, policymakers are going to need a deeper understanding of the factors driving the industry if they are going to create regulations that support the development of the industry. In chapter 4, we investigate the factors that affect agricultural land values by proposing a new rich dataset, Zillow Transaction and Assessment Data (ZTRAX) provided by Zillow from 2009 to 2014. we also examine whether National Commodity Crop Productivity Index (NCCPI) could be a good indicator of land values or not by comparing two different regression models between county-level cash rent and parcel-level NCCPI. Finally, this study incorporates flexible functional forms of the parcel size to test the parcel size and land values relations. Findings show that factors influencing agricultural land values in states with heterogeneous agricultural lands such as Kentucky are not different from other states with relatively homogeneous agricultural lands. This study also provides suggestive evidence that there is a non-linear relationship between parcel size and land values. Furthermore, we find that a disaggregated NCCPI at parcel-level could be considered an acceptable indicator to estimate agricultural values compared to an aggregated cash rent at county-level.

<p dir="ltr">The Temperate Plains ecoregion of Indiana has experienced significant agricultural development since the 19th century, which has left streams vulnerable to impacts such as sedimentation and nutrient accumulation. This thesis describes first the accuracy of the USDA Cropland Data Layer (CDL) in land cover change, and second, the relationships between agricultural and forested land covers and stream biological integrity. I first employed the CDL to review land cover change, particularly relating to agriculture and forest, for the area of interest between 2010 and 2020. I determined that the CDL improved in accuracy for the area of interest in the chosen timeframe for non-agricultural and non-forest land cover. I concluded that the CDL was best used as a supplement to primary-source land cover measures. Next, I calculated the fish Index of Biotic Integrity (IBI) scores for 20 sampled agricultural and forested streams in North-Central Indiana. I also assessed the stream habitats at all sites using the Qualitative Habitat Evaluation Index (QHEI) and percent cultivated crops in drainage basin areas for all streams. Forested streams had significantly higher QHEI scores than agricultural streams (median = 62 and 40.4, respectively). No other relationships were statistically different, including IBI and land cover category, which may have been due to the small sample size (n = 20). I concluded that future studies may build on these findings by controlling for agricultural drainage types or using precise measures of forested land cover.</p>