This dissertation explores the adoption of Best Management Practices (BMPs) in the Kentucky River watershed. Through a survey of farmers in the Kentucky River watershed, chapter two investigates farmers’ current BMP adoption and their willingness to engage in additional adoption incentivized through a proposed Water Quality Trading (WQT) program. This chapter includes two parts: the first part is to investigate the factors influencing farmers’ current usage of BMPs; the second part is to estimate farmers’ willingness to implement BMPs given different levels of compensation specified in the survey. Farmers’ experiences about BMPs are more likely to persuade them to adopt additional BMPs. The activities of using riparian buffers, fencing off animals and building up waste storage facilities are found to be responsive to the levels of compensation offered. The third chapter discusses farmers’ expected economic benefits from BMP adoption, and addresses the missing data issue. In the survey, of those respondents who indicated that they accept the offered level of compensation, about 20% of them did not answer the follow-up question of how much they would adopt the practice, creating missing data. We compare three methods to handle the issue of missing data: deletion method, mean imputation, and multiple imputation method. Following these methods, we estimate factors affecting how much farmers may engage in BMPs using a Tobit or Poisson model. The results show that increasing the compensation for using BMPs is more likely to encourage farmers to adopt riparian buffers. Results obtained using the method of multivariate imputation by chained equation are more promising than using the deletion or mean imputation method. The fourth chapter examines whether wealth change and local community interaction may affect BMP adoption. Survey data on BMP adoption are combined with the local community data from publically available sources. Results show that the decrease in land values between 2007 and 2012 discouraged the adoption of riparian buffers; the equine inventory in local communities has positive impact on the adoption of animal fences and nutrient management; the more rural the local communities are, the less likely farmers would fence off livestock from water resources.

The purpose of this research is to identify factors that contribute to wood fuel consumption as a space heating source and estimate a county-wide proportion for wood fuel consuming households. In addition, environmental problems associated with deforestation such as erosion and loss of wildlife habitat are delineated; moreover, air pollution resulting from wood fuel emissions are discussed. An exhaustive literature review provided the basis for the study. Data on Warren County wood fuel consumption patterns were derived from a mail survey. Proportion estimates were tested by using a classical two-tail test of hypothesis. Subsequently, factors were identified and used in a multiple regression analysis. The study found that low income households equipped with electric space heating systems located in rural areas are the most wood intensive. Unlike homes equipped with other alternate heating systems, electric space heat equipped households tend to consume wood fuel proportionally to income. The study also found that 26.3 percent of single family residences in the county use wood for space heating.

There is broad consensus that a transition to renewable energy and a low-carbon economy is crucial for future development and prosperity, yet there are differing perspectives on how such a transition should be achieved. The overarching goal of this dissertation, which is comprised of three interrelated studies, is to analyze and compare energy futures scenarios to achieve a renewable energy transition and low-carbon economy in the State of Vermont. In the first study, an analysis is presented of the role of energy pricing regimes and economic policy in the context of pursuing a renewable energy transition in the State of Vermont. Through the development and application of a system dynamics model, results address the limits to technological substitution due to path dependence on nonrenewable energy. The role of complementary economic policy is also highlighted to shift from a goal of quantitative growth to qualitative development in order to decouple economic welfare from energy consumption. In the second study, an analysis is presented of the impact of modeled energy transition scenarios to address energy development and land use trade-offs. Simulations with a spatio-temporal land cover change model find that Vermont could achieve a complete transition to renewable electricity using in-state resources through developing between 11,000 and 100,000 hectares of land for solar and wind, or up to four percent of state land area, including some environmentally sensitive land. This approach highlights the need for integration of energy policy and land use planning in order to mitigate potential energy-land use conflict. In the final study, trade-offs between energy, economic, environmental, and social dimensions of Vermont's renewable energy transition are explored through the use of a multi-criteria decision analysis. Energy transition alternatives were designed to reveal trade-offs at the intersection of economic growth and carbon price policy. While there were no optimal pathways to achieving Vermont's energy transition, some energy transition alternatives achieve a more socially desirable balance of benefits and consequences. Navigating the trade-offs inherent in the ongoing energy transition will require an adaptive approach to policymaking that incorporates iterative planning, experimentation, and learning.

Large corporations largely control food production and distribution in the global food system and have generated a desire for locally produced food. Although small independent producers still contribute to regional food systems, there is little understanding about how they distribute and market their products. This thesis uses both semistructured interviews to investigate the distribution practices of urban, family, and regional producers in the New Orleans region and discourse analysis to disclose how localist discourse shapes producers marketing practices. The discourse analysis discovered that the web presence of local New Orleans restaurants, farmers, and Crescent City Farmers Market targeted concepts that reflect localist beliefs and values. It was also established that small producers respond to consumer demands, but still have the power to shape the regional food system through negotiating informal contracts and striving to enter into the niche market.

<div>The purpose of this dissertation is to study the effectiveness of public policies in generating fuel savings and emissions reductions. I focus on applying various empirical methods to analyze consumer responses to policy changes on both extensive and intensive margins. This dissertation consists of two chapters.</div><div><br></div><div>In the first chapter, I compare the effectiveness of fuel taxes and product taxes on reducing gasoline consumption of new car buyers. I employ a unified data source for vehicle choice and subsequent vehicle use to estimate a random effects logit demand model that explicitly accounts for vehicle use heterogeneity. My demand estimation suggests that new car buyers fully value the fuel-saving benefits from improved vehicle fuel efficiency when they initially purchase their cars. My policy simulations indicate that high-mileage drivers are more responsive to a change in fuel taxes than to a change in product taxes, even as low-mileage drivers are more responsive to product taxes. By capturing such heterogeneous consumer response to policies, I show that a counterfactual increase of the fuel tax is more effective than a revenue-equivalent product tax in reducing the total gasoline consumption of new car buyers. Further, when accounting for its effects on consumer response on both extensive and intensive margins, a change in fuel taxes has a clear advantage over a change in product taxes in reducing the consumption of gasoline even when the magnitude of tax increase is small. More importantly, a model not accounting for vehicle use heterogeneity understates the fuel saving effects of both policies and misleads us about the relative effectiveness when comparing different policies. </div><div><br></div><div>The second chapter explores how changes in the marginal cost of driving affect consumers decisions about passenger vehicle utilization, as measured by average daily miles traveled per vehicle. This intensive margin of consumer response has important implications for the effectiveness of usage-based policies, such as the fuel tax and the mileage tax, that designed to address externalities of driving. I estimate the elasticity of driving with respect to fuel cost per mile using a large panel data that covers 351 towns and cities in Massachusetts over 24 quarters. While most researchers in this literature apply fixed effects estimators to examine the elasticity of driving, I use a factor model econometric setup to account for unobserved common factors and regional heterogeneity. Residual diagnostics confirm that the factor model setup does a better job of removing the cross-section dependence than fixed effects estimators do. Given low consumer responsiveness to changes in the marginal cost of driving engendered by current usage-based policies, rights-based approaches like congestion charges might be better alternatives to influence vehicle utilization and vehicle ownership.</div>

The fresh-water mussel industry of the Tennessee River is nearing an end. Overharvesting, habitat alterations, and pollution are the major contributors to the depletion of the mussel resource, upon which the shell industry is based. A history of unconcern by shell harvesters and weak conservation enforcement by governmental agencies, has left the major waterways of the United States nearly void of commercial clams. The lower Tennessee River presently supplies the mussel industry with nearly all the important species of mollusks. If this industry is to be maintained in the United States, ways to preserve and propagate the mussel population must be sought. A number of recommendations have been submitted in this work that could aid in the protection of the mussel fauna. Limitations or harvesting methods, more stringent enforcement of existing laws, and extended research on propagation possibilities are suggested as aids in the preservation of this valuable natural resource.

“Local,” “organic,” “natural,” and “Fairtrade” are just several of the many claims adorning the food products that line grocery store shelves. These promises of environmental sustainability and social responsibility are pillars of the “good food revolution” sweeping the nation as consumers demand alternatives to the products of the industrial food system. Green consumerism, the premise that consumer demand for environmentally sustainable goods will bring about ecologically beneficial outcomes, is at the heart of the sustainable food movement. This thesis takes a critical look at the operation of green consumerism in the food system. It explores the ideology and shortcomings of neoliberal consumer-citizenship that informs the “vote with your fork” rhetoric promoted throughout alternative food markets. Examining the plant-based foods movement as a case study, it attempts to shed light on aspects of food production that are obscured by the promises of “conscious consumption,” such as environmental impacts, accessibility, and reinforcement of the dominant dietary and patriarchal paradigm. Ultimately, the emphasis on consumerism as a means to remedy the failures of the industrial food system instead perpetuates social inequalities and environmental exploitation while relieving powerful institutions and the public of the responsibility to enact significant change. This thesis concludes with recommendations for a multi-sectored approach to the good food revolution that incorporates government, corporate, and grassroots action to bring about a truly sustainable food system.

Over the last decades, economics as a field has experienced a profound transformation from theoretical work toward an emphasis on empirical research (Hamermesh, 2013). One common constraint of empirical studies is the access to data, the quality of the data and the time span it covers. In general, applied studies rely on surveys, administrative or private sector data. These data are limited and rarely have universal or near universal population coverage. The growth of the internet has made available a vast amount of digital information. These big digital data are generated through social networks, sensors, and online platforms. These data account for an increasing part of the economic activity yet for economists, the availability of these big data also raises many new challenges related to the techniques needed to collect, manage, and derive knowledge from them. The data are in general unstructured, complex, voluminous and the traditional software used for economic research are not always effective in dealing with these types of data. Machine learning is a branch of computer science that uses statistics to deal with big data. The objective of this dissertation is to reconcile machine learning and economics. It uses threes case studies to demonstrate how data freely available online can be harvested and used in economics. The dissertation uses web scraping to collect large volume of unstructured data online. It uses machine learning methods to derive information from the unstructured data and show how this information can be used to answer economic questions or address econometric issues. The first essay shows how machine learning can be used to derive sentiments from reviews and using the sentiments as a measure for quality it examines an old economic theory: Price competition in oligopolistic markets. The essay confirms the economic theory that agents compete for price. It also confirms that the quality measure derived from sentiment analysis of the reviews is a valid proxy for quality and influences price. The second essay uses a random forest algorithm to show that reviews can be harnessed to predict consumers’ preferences. The third essay shows how properties description can be used to address an old but still actual problem in hedonic pricing models: the Omitted Variable Bias. Using the Least Absolute Shrinkage and Selection Operator (LASSO) it shows that pricing errors in hedonic models can be reduced by including the description of the properties in the models.

The dissertation consists of three studies that seek to identify school caterer and women farmer constraints that have hindered the buy-local policy mandate of the Ghana School Lunch program, and to explore gendered agricultural technology adoption and contract participation strategies that could facilitate the policy mandate. The first study documents the constraints that have minimized caterer purchases of school food items from local farmers. The study presents an overview of the Ghana School Lunch Program and the buy-local policy mandate issued to school caterers. Survey data and descriptive analysis are employed to document and discuss the constraints that prevent school caters from purchasing from local farmers as well as the constraints faced by smallholder women farmers in supplying to school caters. The study subsequently discusses school caterers’ compensating variation of a hypothetical policy that requires them to firstly provide recommended portions of vegetables and protein, and secondly include fruits in the lunch of the schoolchildren. The second study analyses the factors underlying the probability that women smallholder farmers - compared to male farmers - adopt less a) improved seeds, b) fertilizer, c) herbicides and d) pesticides. The study further examines the sensitivity of gender differences in technology adoption to crop choice, particularly maize and legume, as well as the possible heterogeneity of technology adoption differences within rural and peri-urban communities. The adoption of these improved technologies is modeled using multivariate probit regressions. A gender gap is observed among legume farmers for improved seed and pesticide adoption. Moreover, the findings indicate that female maize farmers who have input into all cash crop production decisions are more likely to adopt improved seeds and pesticides. Among legume farmers, the results indicate that female farmers who are educated and have access to credit are more likely to adopt fertilizer, while female legume farmers who have a say in what the use of income generated from cash crop farming are more likely to adopt pesticides. These results imply that policy-makers and development practitioners in sub-Saharan Africa should consider strategies to target and increase educational, financial and productive assets of female farmers in order to close the gender technology gap and increase multiple technology adoption. The third study examines the use of farm-to-school contracts as a means to provide access to credit for women farmers in rural and peri-urban areas and facilitate the buy-local policy mandate. In particular, the study examines the factors influencing male and female smallholder farmers’ minimum willingness to accept (WTA) farm-to-school-lunch contracts for maize and cowpea beans. The minimum WTA simultaneously measures the decision to participate as well as the minimum price at which the smallholder farmer accepts the contract. Using sex-disaggregated data from a field experiment, a Tobit model is applied to explain the underlying factors influencing male and female smallholder farmer’s minimum WTA for a set of hypothetical maize and cowpea beans contracts. The results for the pooled sample indicate that the delivery at harvest option increases farmers’ minimum willingness to accept both the maize and beans contracts. The study further examines heterogeneity in the minimum WTA among smallholder farmers. The results in the female specification indicate that, the advance pay option lowers the minimum WTA for maize contracts. Additionally, women farmers who own non-farm business, compared to a male with a non-farm business, have a lower minimum WTA for the maize and beans contracts. The results suggest that if the government considers contractual arrangements between school caterers and local farmers to facilitate the buy-local policy mandate, an advance pay option to women farmers may yield lower premiums for contracted food items.

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.