Theses and Dissertations

Permanent URI for this collectionhttps://hdl.handle.net/10217/100317

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Open Access
Three essays on the economic and environmental implications of agricultural conservation incentives at the field, regional, and global scales
(Colorado State University. Libraries, 2025) Wang, Ming, author; Manning, Dale T., advisor; Countryman, Amanda M., committee member; Suter, Jordan F., committee member; Ogle, Stephen M., committee member
Agricultural conservation policies are central to efforts to address the dual challenges of climate change mitigation and rural economic sustainability. Agriculture contributes significantly to greenhouse gas (GHG) emissions, particularly through soil-based processes, leading to the expansion of agri-environmental incentive programs aimed at encouraging the adoption of climate-smart practices. Evaluating the effectiveness of these policies requires careful consideration of economic feasibility, producer behavior, market interactions, and broader socio-economic impacts. This dissertation consists of three essays that use quantitative methods, integrating econometric models, biophysical simulations, and general equilibrium analysis, to examine these dimensions. Together, the essays underscore the importance of incorporating market feedbacks, accounting for international emissions leakage, and evaluating local labor market outcomes to design agri-environmental policies that are both environmentally effective and economically inclusive. In the first essay (chapter 2) of this dissertation, we examine how endogenous crop prices affect estimates of greenhouse gas abatement supply on corn and soybean acres at the farm level under alternative climate change scenarios in the U.S. Corn Belt. We combine a discrete choice model of farmer behavior with a spatially explicit biogeochemical model of GHG emissions and link this model to crop demand curves to allow for price feedbacks. Producers are offered payments from the GHG reductions achieved by adopting climate-smart practices, no-till, cover crops, and reduced nitrogen application, and their adoption behavior is simulated across varying carbon price and climate scenarios. Results indicate that accounting for endogenous prices increases estimated abatement, particularly from nitrous oxide reductions, by up to 18 percent at a carbon price of $190t CO2e under the extreme climate scenario and by 25 percent under the sustainability scenario, relative to estimates based on exogenous prices. Results underscore the importance of considering market interactions when constructing abatement cost functions. In the second essay (chapter 3), we investigate emissions leakage from domestic conservation policy at the global scale by modeling the worldwide GHG emissions implications of expanding the U.S. Conservation Reserve Program (CRP). While CRP has been considered as a policy that can reduce domestic GHG emissions, our results show that it also generates significant spillover effects via global market adjustments. For an additional 4 million acres (1.6 million hectares) enrolled in CRP, approximately 236 thousand hectares of forest are converted to agriculture within the U.S., while cropland expands by 205 thousand hectares outside the U.S. due to market-driven land use changes. These spillover effects fully offset the mitigation achieved on the enrolled cropland, resulting in over 200% global emissions leakage. These findings underscore the importance of incorporating international leakage and market-mediated effects into the evaluation of land-based climate policies. The study contributes a novel framework for assessing conservation policies in a globally integrated economy and highlights the need for internationally coordinated approaches to ensure environmental effectiveness. In the third essay (chapter 4), we assess the regional-level economic effects of agri-environmental programs by examining the employment trade-offs between land retirement and working lands programs. We use panel data and a fixed effect model to address the endogeneity of EQIP and CRP enrollment. We deploy alternative identification strategies and controls to test the robustness of our results. Findings indicate that both cropland retirement and working lands programs are associated with higher local employment levels, and that reallocating conservation dollars from temporary retirement to working lands at the state level increases overall employment in each rural county by 0.4% per million dollars, with agricultural jobs increasing faster than non-agricultural jobs. These results offer valuable insights for policymakers seeking to generate environmental benefits while supporting rural employment.
Open Access
Particulate matter and human vulnerability: impacts on cognition, respiratory health, and public safety
(Colorado State University. Libraries, 2025) Chen, Wenjie, author; Burkhardt, Jesse, advisor; Goemans, Christopher, committee member; Kroll, Stephan, committee member; Iverson, Terrence, committee member
This dissertation explores the broad impacts of air pollution on human vulnerability by examining how environmental stressors affect cognitive performance, respiratory health, and public safety. Focusing primarily on fine particulate matter (PM2.5), the study conducts three empirical analyses using behavioral, health, and transportation data. Chapter 1 uses chess performance as a proxy for cognitive function and estimates the effect of PM2.5 exposure on decision-making using fixed-effects logistic regression and a beta regression model. The results show that higher PM2.5 concentrations significantly reduce winning probability, with stronger effects observed among older, higher-income, and male players. Precipitation, relative humidity, rating difference, and age all have positive effects on winning percentage, while the opposite was true for the income variable. Chapter 2 investigates the link between air pollution and asthma prevalence using multinomial logistic regression and U.S. health survey data. Lagged exposure to PM2.5 and SO2 increases the likelihood of currently having asthma, while higher temperature and humidity reduce asthma risks. Women with higher BMI, higher frequency of smoking, poorer general health condition, and younger age have higher asthma recurrence rates. Interaction effects suggest that SO2 has a weaker impact among older individuals. Chapter 3 analyzes crash-level data from Colorado between 2007 and 2020 to examine the relationship between air pollution, weather, and traffic accidents. Negative binomial regression results indicate that PM2.5 and low visibility are associated with more frequent accidents. Accident counts are higher in locations and times with more DUI involvement, female drivers, PM2.5 amplifies the effect of over speeding and DUI. The number of crashes is higher on Wednesdays and relatively low at night. Together, these chapters provide novel evidence that air pollution has diverse and significant consequences for cognitive capacity, chronic disease, and public safety, underscoring the urgent need for coordinated environmental and public health policies.
Open Access
Three essays on nutritional disparities and policies in U.S. food purchases
(Colorado State University. Libraries, 2025) Wang, Duoyu, author; Cleary, Rebecca, advisor; Bonanno, Alessandro, committee member; Berning, Joshua, committee member; Mueller, Megan, committee member
This dissertation contains three essays examining the nutritional disparities and policy interventions aimed at improving dietary quality in the U.S. The second chapter investigates the nutritional quality gap between food-secure and food-insecure households in the United States using the public access USDA's National Household Food Acquisition and Purchase Survey (FoodAPS). Employing an unconditional quantile decomposition approach, the study reveals that disparities in nutritional quality persist across the distribution of the Healthy Eating Index (HEI)-2010 scores. Differences in household characteristics account for the majority of the diet quality gap among households with lower nutritional quality, whereas for households with higher nutritional quality, the diet quality gap is influenced more by differences in how these characteristics translate into dietary outcomes. The third chapter examines the impact of the Supplemental Nutrition Assistance Program (SNAP) on the dietary quality of Black households using an instrumental variable unconditional quantile regression (IVUQR) approach, again utilizing the public access FoodAPS dataset. The analysis finds that SNAP participation is associated with lower dietary quality for Black households, particularly at lower-to-middle quantiles of the HEI-2010 distribution, primarily due to an increased acquisition of foods high in empty calories. Compared to White SNAP households, as represented by their primary food purchaser, Black SNAP households show more stable nutritional outcomes across food sources, meaning their diet quality remains relatively consistent between food-at-home and food-away-from-home purchases. The fourth chapter evaluates the potential impact of an industry-wide sugar content ceiling on the U.S. sugar-sweetened beverage (SSB) market. Utilizing demand estimates from a random coefficients logit model and Circana point-of-sale (Pos) scanner data, the study simulates an how industry-wide product reformulation would affect equilibrium shares and per capita sugar amounts from purchasing SSBs.
Open Access
Three essays on pandemic-driven shifts in food purchasing and policy: insights for strengthening food system resilience
(Colorado State University. Libraries, 2025) Gill, Mackenzie, author; Thilmany, Dawn, advisor; Jablonski, Becca B. R., advisor; Bonanno, Alessandro, committee member; Chenarides, Lauren, committee member; Mueller, Megan, committee member
These three essays explore how pandemic-era shifts in (1) consumers' purchasing behaviors and (2) federal food policy may inform strategies to improve current and future food system outcomes. The COVID-19 pandemic caused significant shifts in food consumption patterns, some of which have persisted into the current food environment. Given the supply chain disruptions that occurred during this time, the pandemic also provides a case study for examining the tradeoffs of policy that supports flexible supply chains. Through three essays, this work examines purchasing behaviors and policy responses to uncover insights that can bolster the resilience of food markets in the face of future disruptions. The first essay explores the relationship between consumers' selection of multiple food market types and their usage of online FAH shopping options. National consumer survey data and latent class regression is used to capture various food shopping behaviors in the post-pandemic food environment. Two classes of online shoppers are discussed: values-driven consumers who use online options to find niche products, and frugal consumers who rarely use online options, but sometimes do so to save time and find bargains. The second essay uses Circana Retail Scanner Data to analyze consumers' stockpiling behaviors in response to pandemic-induced fears changes in pandemic-related public policies. The stockpiling of specific food categories is explored, with delineations made between perishable and non-perishable food. The third essay uses recent Difference-in-Difference techniques to evaluate the Farmers to Families Food Box (FFFB) program's impact on contracted businesses' employed labor, survival, and market opportunities. This analysis informs ongoing federal and state-level efforts to enhance food assistance programs and ensure food system resilience in times of crisis.
Open Access
The economic consequences of flood alerts: evidence from employment outcomes
(Colorado State University. Libraries, 2025) Muriqi, Diellza, author; Goemans, Christopher, advisor; Suter, Jordan F., advisor; Davenport, Frances, committee member
Floods are some of the costliest and most common natural hazards in the United States. As the frequency and intensity of extreme weather events increase, flood alerts have become an important tool for reducing damages and saving lives. Previous studies show that early warning systems can reduce economic losses and protect lives, but their effectiveness depends on alert accuracy and public response. Most of the existing research has focused on how false alarms and missed alerts affect trust and compliance, especially in the context of tornadoes. Much less is known about their economic impacts, particularly for floods, despite the fact that issuing an alert involves tradeoffs. False alarms may generate unnecessary costs, while missed events can lead to unanticipated disruptions. Understanding the labor market impacts of these inaccuracies is important for agencies like the National Weather Service, which must balance risk communication under constrained resources. This thesis investigates how flood alerts, false flood alarms, and missed flood events disrupt county-level employment outcomes in the United States. To answer this, I construct a county-by-month panel dataset from 2007 to 2023, combining data from the NOAA Storm Events Database, the Iowa Environmental Mesonet, and the Bureau of Labor Statistics. Using a two-way fixed effects model, I estimate how different combinations of alerts and flood events influence employment levels in total, as well as construction, and leisure & hospitality sectors. The results show that flash flood days accompanied by both a warning and a notification are associated with small but statistically significant declines in employment. These effects are most pronounced in the leisure and hospitality sector, followed by construction. I find no evidence that false alarms or missed events have a significant impact on employment. Additional analyses reveal that effects vary by rural and urban classification, emerge over several months in some cases, and are robust to alternative alert groupings and proximity-based exposure definitions. These findings highlight the economic importance of alert accuracy and suggest that the type and layering of alerts, as well as local context, influence short-term labor market outcomes.
Open Access
Preferences for hazardous fuel treatments: evidence from a survey of Colorado and Utah residents
(Colorado State University. Libraries, 2025) Hoban, Danielle, author; Suter, Jordan, advisor; Lewis, Lynne, committee member; Wei, Yu, committee member
The United States has experienced measurable increases in the prevalence and severity of annual wildfire events for the last few decades. The management of hazardous fuels can mitigate the spread and severity of wildfire events by removing or reorganizing excess woody materials that could otherwise feed fires. However, recent wildfire severity has required a large portion of the United States Forest Service (USFS) budget to be allocated to suppression efforts each year at the expense of other budget categories, such as fuel treatments. This motivates the importance of using available resources in a way that maximizes social welfare, but it is unclear what allocation is considered optimal by relevant stakeholders. This research investigates the preferences of the public for hazardous fuel treatments. The primary objective of this work is to assess how the public would prefer a portion of the USFS wildfire management budget be allocated among fuel reduction activities. A secondary objective is to determine how allocation preferences are affected when budgetary changes are presented as a loss or a gain. To address these questions, surveys were administered to a sample of the public residing in Colorado and Utah. Respondents were asked to complete a budget allocation exercise as the primary mechanism for assessing their preferences. Results indicate that on average, individuals would prefer to allocate a greater percentage of the USFS hazardous fuels budget to prescribed fire treatments than has been spent in previous years. Individuals who own their home allocate more to prescribed fire, on average, but few other characteristics are good predictors of allocation preferences. There is no statistical evidence that the framing of the budget decision affects allocation preferences.
Open Access
A decision aid for estimating financial feasibility of non-lethal wolf-livestock conflict prevention practices
(Colorado State University. Libraries, 2025) Morones, Mia, author; Hoag, Dana, advisor; Mooney, Daniel, advisor; Salerno, Jonathan, committee member; Breck, Stewart, committee member
U.S. reintroduction efforts of the gray wolf (Canis lupus) have contributed to negative externalities that disproportionately fall onto producers in the form of direct and indirect costs due to wolf-livestock predations. Direct costs incurred by livestock owners include market value losses due to livestock death, veterinary costs for injured livestock, and transaction costs associated with carcass management. Indirect costs also occur, such as reduced livestock weight, reduced milk production, and decreased pregnancies from livestock stress responses due to wolf presence. These losses, while not widespread, can be costly to those that experience them. However, there are non-lethal predation prevention practices that can be effective in reducing wolf-livestock conflict. Some of these practices include turbo fladry, electrified night penning, range riding, carcass composting, livestock guardian dogs and more. While there is a great deal of literature about these practices, uncertainty remains regarding their financial feasibility for producers. To help livestock producers manage their risk, this study develops a framework for determining the feasibility of these practices by combining the producer's risk probability of wolf-livestock conflict with their respective costs to implement prevention and mitigation practices of interest. To implement the framework, I develop an online decision aid that provides comparative break-even analysis to offer producers a metric to understand how effective their mitigation practice(s) must be to offset the potential costs associated with livestock predation. The tool provides an estimate of the probability of conflicts for specific properties based on local conditions such as habitat and presence of wildlife and livestock and helps users identify the cost of various mitigation tools and the value that might be lost in a conflict. Additionally, this analysis implements sensitivity analysis and Monte Carlo Simulation (MSC) to better understand how impactful varying inputs such as material costs, predation risk and state funding for practice implementation are on the financial outcomes of the model.
Open Access
The contributions and future outlook for Colorado's potato economy: modeling value-added market scenarios
(Colorado State University. Libraries, 2025) Davidson, Coryn Marie, author; Thilmany, Dawn, advisor; Hill, Rebecca, committee member; Komarek, Tim, committee member
The potato industry plays an important role in Colorado's economy, with the San Luis Valley as the leading production region in the state. The first paper in this thesis will share a 2022 baseline economic contribution analysis of Colorado's potato industry at both the San Luis Valley (SLV) regional and state levels, highlighting employment, labor income, and overall economic activity. To explore how various strategic changes that might be considered within potato supply chains may affect economic activity, the second paper will examine potential value-added market scenarios. Catalyzed by changes in consumer demand emerging in market trends, the first market scenario will model how changes to decrease potato packaging size could change how the potato industry contributes to the SLV regional economy. The second market scenario takes a relatively small niche of the potato industry, organic supply chains, and increases its relative production in the SLV region. Although the organic potato sector makes up only 3% of the potato production in Colorado, the aim of this analysis is to understand what implications would result from increasing the share of organic potato production. By assessing both scenarios, the paper will provide insights into how value-added potato production could shape the future economic contribution of Colorado's potato industry. The results of the 2022 baseline economic contribution analysis show that potato farming in Colorado supported over 3,100 jobs and created $165 million in economic activity. The San Luis Valley region had a total economic output of $328 million and supports over 2,200 jobs through the potato farming industry. The value-added market scenarios also produced positive outcomes. The results showed that increasing the market share of small packages of potatoes increased the farm-gate value of production, employment, and the economic output of the potato industry. Finally, the analysis results from increasing organic potato production show a positive effect on the SLV economy, despite yield loss. Although these scenarios represent estimates of various strategies being considered by potato producers, they provide guidance to sector leadership on how such initiatives more broadly impact regional economic activity.
Open Access
Market access through innovation: the case for dried watermelon in Malawi
(Colorado State University. Libraries, 2025) Banning, Brooke E., author; Magnan, Nicholas, advisor; Constanigro, Marco, committee member; Davis, Jessica, committee member
Farmers in Malawi face the dual challenges of low income and substantial post-harvest losses. Drying fruit offers a viable solution by preserving produce that would otherwise be wasted and allowing farmers to access high-value markets. However, no existing literature examines the demand for dried fruits in Malawi or the profitability of selling them domestically. This study investigates the feasibility of drying watermelon as a value-added product and assesses consumer willingness to pay (WTP) in Lilongwe, Malawi. A multiple price listing mechanism was used to elicit WTP for both solar- and electric-dried watermelon, along with a cost-benefit analysis comparing the two drying methods. The findings indicate that, while dried watermelon is unfamiliar to Malawian consumers, there is considerable demand. According to findings only electric dried watermelon is profitable at mean WTP.
Open Access
Forecasting fed beef production: an evaluation of systems forecasting by parts for optimal survey history
(Colorado State University. Libraries, 2025) Dodd-Zakely, Brandon Thomas, author; Koontz, Stephen, advisor; Thilmany, Dawn, committee member; Martin, Jennifer, committee member
The following study examines forecasts of fed beef production through a by-parts estimation framework to provide a more practical alternative to more complex simultaneous systems of equations. A disconnect exists between the academic literature and the methods commonly used in private industry decision making. Practical techniques employed by industry professionals hold promise in strengthening conversations around forecasting research. Recent shifts in cattle production, including elevated contributions of heifers in the slaughter mix and larger than anticipated weights in fed cattle, provide an appropriate case study that underscores the need to revisit past events in the development of new forecasting strategies. By analyzing survey history in the data selection process, examining analog time periods, and considering concerns of autocorrelated errors within Deterministic Trend / Deterministic Seasonality models, this study highlights that practical enhancements to forecast accuracy can be sustained by simple remedial measures. The results of this study demonstrate that (1) historical data selection can significantly impact forecast quality; (2) methods that allow for autocorrelated error corrections can improve model performance; (3) the effectiveness of different forecast estimation methods varies by the selected horizon; and (4) the use of more simplistic assumptions underlying a forecast model can produce competitive and accurate results.
Open Access
Identifying values among stakeholders in Colorado school-based agricultural education
(Colorado State University. Libraries, 2025) Cable, Jonathan David, author; Enns, Kellie, advisor; Pritchett, James, committee member; Thilmany, Dawn, committee member; Baxter, Aryn, committee member; Knobloch, Katie, committee member
To better understand the relationships between shared community values and experiences in School-Based Agricultural Education (SBAE), a mixed-methods study was conducted on the core values of SBAE in Colorado identified by three stakeholder groups. To inform programmatic decisions from the state's Agriculture, Natural Resources and Energy Program and Colorado Team Ag Ed, this study highlights both the philosophical and practical applications of core values respective to SBAE stakeholder engagement in Colorado. Qualitative survey instruments were used across three sample groups to question community stakeholders, high school agriculture instructors, and state agricultural education leadership. Findings represent the values that stakeholders hold as most important in SBAE and the aligned activities that demonstrate these values. Arranged in three parts, this paper identifies values in relation to 1) stakeholder identification, 2) cooperative decision-making, and 3) educational motivation and autonomy. A pragmatic approach to implications throughout each part seeks to deliver an easily applicable strategy for stakeholder engagement—both for readers and the author. A discussion on the relationships between values, motivation, and other educational and organizational theories is included. While results and suggestions from this study are specific to Colorado's SBAE programs, they could serve as frameworks for informing further agricultural education research and SBAE methods in other states.
Open Access
Evaluating the efficiency, equity, and effectiveness of wildfire suppression strategy using the microeconomic toolkit
(Colorado State University. Libraries, 2024) Bryan, Calvin R., author; Bayham, Jude, advisor; Manning, Dale T., committee member; Goemans, Chris, committee member; Wei, Yu, committee member
Most economic research related to wildfires focuses on their impact on people and populations. In my dissertation, I use economic tools to evaluate the efficiency and equity of wildfire suppression strategy. In the first chapter, I investigate whether socioeconomic factors of a community (income, race, age, etc.) are correlated with allocations of suppression effort. I use spatial data on retardant drops from large airtankers (LATs) and demographic information from the Census Bureau to find that communities threatened by wildfire with fewer minority residents, but more low-income residents, are more likely to receive LAT drops. I then find that socioeconomic factors aren't correlated with the decision to use LATs in suppression after conditioning on biophysical factors like fuels and burn probability. In my second chapter, I study whether the media's attention to wildfire influences suppression strategy. I instrument for the effect of media attention using the incidence of catastrophic events that would distract the media to find that media scrutiny of a wildfire has no tangible effect on the decision to use aviation on a fire. Finally, most economic research on wildfire suppression strategy has focused on the costs; little exists on its benefits. I use causal inference methods leveraging satellite data on wildfire growth and intensity, along with the spatial data on aerial suppression effort mentioned previously, to find that large airtankers are effective at limiting the physical extent of wildfire's spread, reducing the intensity of flames as it grows, and slows its spread.
Open Access
Three essays on the economics of energy, water, and pollution
(Colorado State University. Libraries, 2024) Rasul, Zarif I., author; Burkhardt, Jesse, advisor; Suter, Jordan, committee member; Manning, Dale, committee member; Carter, Ellison, committee member
This dissertation covers three policy-oriented topics in environmental economics. The first chapter explores the short-term impacts of US liquefied natural gas (LNG) exports on the domestic natural gas and electricity markets. Using a structural vector autoregression framework, we find that unexpected LNG exports corresponded to a 34% price increase in domestic natural gas spot prices in 2022. We illustrate the impact of this price increase on the electricity market by constructing counterfactual dispatch curves for Texas. Had gas prices not increased by 34% in 2022, our results indicate that NOx, SO2, and CO2 emissions from electricity generation in Texas would have been lower by 11.2%, 47%, and 10.7% respectively. The second chapter explores whether utilities can use pro-social appeals to influence residential water consumption by evaluating a program implemented by Denver Water. The program aimed to influence both the timing and volume of residential consumption to eliminate peaking by asking different customer groups to water their lawns on alternate days. Using difference-in-difference models, we find that while the timing of outdoor watering remains unchanged, there is weak evidence that one group of households water on assigned days while another does not, but overall we find no evidence of a significant average treatment effect. These results support previous findings that non-price interventions that include conservation tips or pro-social appeals have little or no impact, as opposed to interventions that contain some element of social comparisons or other incentives. The third chapter investigates the impact of concentrated animal feeding operations (CAFOs) on ammonia and methane concentrations across the United States, leveraging ground-level monitoring data for ammonia and satellite-based observations for methane. For ammonia, we find that wind direction and proximity to CAFOs within 10 km significantly influence concentrations. Additionally, the impact varies by CAFO type. Methane concentrations are similarly elevated in grids containing CAFOs, with the presence of shale plays and seasonal variations also playing significant roles. Our findings underscore the local environmental impacts of CAFOs, while also highlighting the challenges of isolating these effects from other sources.
Open Access
When is agrivoltaics profitable compared to agriculture and photovoltaics? A joint-product economic feasibility analysis
(Colorado State University. Libraries, 2024) Buzzelli, Maria, author; Mooney, Daniel, advisor; Hoag, Dana, committee member; Uchanski, Mark, committee member
Solar is the fastest-growing renewable energy sector in the United States, however, land suitable for solar installations competes with productive agricultural land. Agrivoltaics (AV) offers a potentially promising solution by creating a dual use for land and improving crop yields. This paper examines the trade-offs between agricultural and solar production on a finite amount of land, using tomato cultivation as a case study. The study reveals a significant trade-off between energy production and crop yield. Scenarios maximizing energy production, particularly with bi-facial 5% transparent panels, generate the highest net revenues, highlighting the profitability of energy over agriculture. The rate of product transformation (RPT) indicates an inverse relationship between energy and crop production, averaging a 2% decrease in tons of crops per additional MWh of energy produced. Converting all available land to traditional photovoltaic (PV) solar panels is the most financially viable option for farmers, generating 12.4% more annual revenue as compared to only producing crops. The increase in crop yields from AV does not outweigh the additional costs associated with AV installation and maintenance. This paper identifies the subsidy levels required for AV to break even with crop production and with the traditional PV scenario. The results and discussion contribute to the economic literature on AV by highlighting key aspects of AV field configurations and related policy incentives to keep agricultural land productive while also growing the renewable energy sector.
Open Access
Optimizing brush pile disposal on western USFS land
(Colorado State University. Libraries, 2024) Axlund, Caleb E., author; Suter, Jordan, advisor; McCollum, Daniel W., committee member; Bayham, Jude, committee member; Wei, Yu, committee member
This research evaluates the social costs of burning piled biomass and the economic trade-offs of alternative removal strategies. Timber harvesting and forest thinning often leave behind branches and other tree parts, which are piled and burned, resulting in what are known as brush or slash piles. These piles pose significant costs to nearby communities and have global environmental impacts, including greenhouse gas (GHG) emissions and reduced local air quality (Wiedinmyer et al., 2006; Ganguly et al., 2018; Pierobon et al., 2022). The United States Forest Service (USFS) is testing a new device called the 'Charboss' that removes excess brush and repurposes it as biochar, a substance with potential environmental and agricultural benefits. Analyzing the external social costs of burning brush piles is crucial for assessing the economic viability of future brush removal strategies. By using social costs as a gauge, this study employs an optimization model to maximize benefits while minimizing the associated costs of this new forest management technology. Private investment and social planners' perspectives are considered when determining optimal deployment strategies. This study examines various scenarios for deploying the USFS device cost-effectively and concludes that, under certain assumptions, it can significantly benefit local communities and global environmental health.
Open Access
Three essays on the inequality of household food security
(Colorado State University. Libraries, 2024) Zhou, Siwen, author; Berning, Joshua, advisor; Bonanno, Alessandro, committee member; Bayham, Jude, committee member; Miller, Ray, committee member
This dissertation contains three essays on the inequality of household food security in the United States. In particular, the second chapter examines the effect of economic cycle, particularly unemployment, on the likelihood of food insecurity for different immigrant households in the United States relative to native US households. As unemployment is not randomly determined for households, we create a Bartik instrument by exploiting exogenous variation in industry shares across locations interacted with national industry growth rates to identify the disproportional effect of unemployment rate on food insecurity for immigrant households. The third chapter examines how immigrant households use time and money to manage their household food security relative to natives. To overcome the potential measurement errors and endogeneity of household level time-use and expenditures, aggregated cell-level means of food production time and expenditures are employed as instruments separately to identify the causal effects of time and money inputs on household food insecurity and how these effects vary across immigrant and native households. The fourth chapter seeks to elucidate the long-term structural nature of food security dynamics through household financial asset holdings in United States. By adopting an econometric strategy, this chapter uses a 19-years panel dataset from the Panel Study of Income Dynamics (2001-2019) to establish the new the Structural Probability of Food Security (SPFS) measure for long-run study of food security dynamics.
Open Access
Informed decision-making on photovoltaic adoption for western Colorado peach orchards
(Colorado State University. Libraries, 2024) Bryan, Samantha, author; Hoag, Dana, advisor; Mooney, Daniel, advisor; Tonnessen, Brad, committee member
The Solar Orchard Analysis and Recommendation Tool (SOAR) is an interactive decision-support tool curated for Western Colorado's peach growers to characterize photovoltaic adoption on their farms. Peach orchards use a substantial amount of energy that has the potential to be offset by photovoltaic arrays, allowing the farmer to reduce their operational costs as well as contribute to renewable energy initiatives. In addition, the benefits of solar energy can be enhanced as producers electrify their equipment where appropriate. Each farmer has their own unique energy supply and demand needs that can change over time as tools and vehicles become electrified and as photovoltaic technology evolves. In response, SOAR was created with engineers and local orchard growers to help farmers manage their energy needs. Furthermore, this tool allows farmers to evaluate the effects of different financing options on payback period, return on investment and initial investment cost of a PV array. The use of this decision support tool is exemplified with the use of a case study farm to demonstrate various supply and demand scenarios.
Open Access
Exploring labor dynamics: Indigenous identity, wage differentials, and poverty risk among Mexican-born farmworkers in the U.S. agricultural sector
(Colorado State University. Libraries, 2024) Coronel-Bautista, Jorge, author; Thilmany, Dawn, advisor; Hill, Alexandra E., advisor; Pena, Anita A., committee member
This thesis examines the challenges faced by Mexican Indigenous farmworkers within the U.S. agricultural landscape, with a specific focus on an observed wage differential when compared to their Mexican Non-Indigenous counterparts. While existing research has extensively investigated various facets of the U.S. farm labor force, there remains a gap in understanding the specific economic and earnings hurdles encountered by Mexican Indigenous farmworkers. Most of the existing literature has concentrated on overarching demographic trends, farm labor productivity, and the ramifications of immigration policies, leaving the experiences and labor market outcomes of Mexican Indigenous farmworkers insufficiently examined. This research explores the relationship between Indigenous identity, wages, and poverty within the U.S. agricultural sector, using data from the National Agricultural Workers Survey (NAWS) spanning 2003 to 2020. This study focuses on Mexican-born workers, distinguishing between Indigenous and non-Indigenous individuals. Over 17 years, we found a significant average wage gap of -5.25% between the two groups, with Indigenous farmworkers earning less. We investigate the factors contributing to the observed wage gap and examine the relationship of Indigenous identity and farmworkers' earnings. Specifically, we analyze whether Indigenous identity is independently associated with lower earnings among farmworkers, while controlling for various factors that may explain differences in earnings compared to Non-Indigenous counterparts. Additionally, we explore if Indigenous identity increases one's risk of poverty, while also controlling for factors influencing this risk. We conduct additional analyses by examining whether Indigenous identity affects earnings within specific farmworker cohorts. The second data approach examines the distribution of farmwork weeks worked in the past year by Indigenous farmworkers surveyed by the NAWS. It explores the average characteristics of Indigenous farmworkers who have worked very few weeks compared to those who have worked more extensively. The third is a marginal effects analysis which quantifies the economic significance of employee and employment characteristics on earnings across Indigenous and Non-Indigenous farmworkers. This approach enables us to assess the specific cumulative influence of Indigenous identity on earnings, while also considering the average effects associated with Indigenous status. Findings from this research will identify the determinants of the wage gap between Mexican-Indigenous and Mexican-Non-Indigenous farmworkers, potentially attributable to observable characteristics (such as education and years of experience), Indigenous identity (indicative of wage discrimination), or a combination of both. Depending on the results, we can recommend policy initiatives aimed at improving educational attainment and other skills for Mexican-Indigenous farmworkers, enabling them to earn wages comparable to their Non-Indigenous counterparts. Additionally, we can inform new legislation seeking to improve the types of work arrangements between Indigenous farmworkers and agricultural employers, in efforts to take a step towards preventing wage discrimination based on Indigenous identity as part of those work arrangements.
Open Access
Exploring the use of credit/debit card transaction data in estimating national park visitor spending: a Mount Rushmore case study
(Colorado State University. Libraries, 2024) Stockmoe, Evan, author; Burkhardt, Jesse, advisor; Bayham, Jude, committee member; Komarek, Tim, committee member
Visitor spending refers to trip-related expenditures made by tourists. Estimates of visitor spending are needed for national park economic contribution studies, and are an essential component in evaluating tourism-related economic activity [Thomas et al., 2019, Wilton and Nickerson, 2006]. Traditional methods for estimating visitor spending rely on visitor surveys, which are costly and subject to multiple forms of survey bias [Stynes and White, 2006, Sinclair et al., 2023, Wilton and Nickerson, 2006]. Using Mount Rushmore National Memorial as a case study, I explore the use of granular credit and debit card transaction data to estimate visitor spending without the need for survey data. I use Safegraph Spend as the source of credit and debit card transaction data. I gather transaction data at stores within 100 miles of Mount Rushmore for the period 2019-2023. Combining this data and Mount Rushmore visitation data from the National Park Service, I develop and compare multiple models that use fixed effect regressions to estimate average spending per visit in the Accommodation, Food Service, Retail, and Arts/Entertainment/Recreation sectors. Using results from the best performing model, for 2022, I estimate Mount Rushmore visitor spending to be $41.0 million in the Accommodation sector, $38.4 million in the Food Service sector, $154.8 million in the Retail sector, and $6.4 million in the Arts/Entertainment/Recreation sector. I compare these estimates with NPS survey-based Mount Rushmore visitor spending estimates. I find that model estimates for the Food Service and Retail sectors are statistically indifferent to NPS estimates, however, model estimates for the Accommodation and Arts/Entertainment/Recreation sectors are below NPS estimates. I find several strengths and weaknesses in the credit/debit card transaction models. One strength is the use of observed spending data rather than stated spending data. Another strength is the representation of yearly visitor spending habits. A third strength is the ability to provide measures of estimate precision, like standard errors. One weakness is the inability to identify park-specific visitor spending when other nearby tourist attractions have similar visitation. Another weakness is the failure to account for visitor trip purpose. Additionally, I find that Safegraph Spend underrepresents spending in the Accommodation sector since vacation rental websites (like Airbnb) are not reflected in the data. Looking forward, further research should focus on methodological refinement and the integration of other data sources to improve visitor spending estimation using credit/debit card transaction data.
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Three essays on the economics of land use and conservation
(Colorado State University. Libraries, 2024) Shartaj, Mostafa, author; Suter, Jordan F., advisor; Manning, Dale T., committee member; Bayham, Jude, committee member; Jones, Kelly, committee member
This dissertation consists of three chapters focused on the economics of land use and conservation. The first chapter investigates the differences in groundwater use among wells irrigating State Land Board (SLB) parcels and nearby private parcels. SLB parcels represent leased parcels with limited tenure length and uncertainty of renewal. In the chapter, we demonstrate that wells irrigating SLB lands pump substantially more groundwater compared to non-SLB wells. The second chapter makes use of a novel dataset of discount rates elicited from agricultural producers across the United States to explore how estimates of discount rates for can be utilized to improve the performance of agri-environmental programs. The final paper examines camping in US Forest Service (USFS) campgrounds during the COVID-19 pandemic. Using data on campground reservations made through recreation.gov, we illustrate how camping on USFS lands was impacted by infection rates, public health restrictions and proximity to metropolitan areas and National Parks (NPs). Imperfect property rights can lead to over-extraction of resources and provide disincentives to invest in conservation of the resource stock. In the first chapter, making use of a natural experiment, we explore the case of groundwater usage on State Land Board (SLB) parcels, relative to nearby private parcels. The SLB of Colorado leases out land to agricultural producers, with groundwater rights tied to the land leases. Leases by the SLB have tenure lengths of 10 years, where the leaseholder is allowed to renew their lease if they can match the highest bid for the next lease term. This generates uncertainty regarding access to future groundwater stocks. We contribute to the literature by demonstrating the causal impact of SLB designation on groundwater use. We show that wells irrigating SLB lands, on average, use 15 to 24 percent more groundwater compared to nearby private lands. Adoption of conservation practices in agriculture often requires upfront costs, while the private benefits are produced in the future. As such, farmers' time preferences can play an important role in adoption decisions. In the second chapter, using elicited discount rates of farmers from 26 US states, we explore the role of farmers' discount rates in cover crop adoption, program participation, and continuation of cover cropping after the contract period. The data reveal that mean observed discount rates are lower both for farmers that adopt cover cropping and for farmers that participate in conservation programs, compared to those who do not. This suggests that time preferences play a key role in conservation adoption decisions. The empirical results are followed by a simulation analysis, which utilizes the discount rate data to explore benefits of tailoring conservation contracts based on discount rates. The simulations point out that a small increase in upfront payments can substantially increase cover cropping during the contract period, but they do little to increase continuation of cover cropping after the contract period. The simulations also reveal that tailoring the contract length and annual payment, according to the discount rate information, can allow policy makers to target higher levels of continuation, which are unattainable under the 5-year status quo contract. In the extreme case where the program administrator can observe individual discount rates, it is possible to dramatically reduce the costs of increasing continual adoption by individually tailoring the contracts. During the COVID-19 pandemic, US public land managers faced the challenge of catering to large increases in camping demand, while maintaining social distancing guidelines. In the final chapter, we use multivariate linear regression to analyze weekly changes in reservations to US Forest Service (USFS) campgrounds between 2019 and 2020. Our sample includes 1,688 individual USFS campgrounds from across the contiguous US. The results illustrate the dramatic increases in camping on USFS land that occurred in the summer of 2020 and demonstrate that increases in local infection rates led to significant increases in camping nights reserved in the summer. The results also illustrate that the increase in camping nights reserved at USFS campgrounds was particularly dramatic for campgrounds located near large metropolitan areas and near National Parks that saw increases in overall recreational visits. These results point to the important role that public lands played during the pandemic and can help guide public land resource allocations for campground maintenance and operation.

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